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LIFE SPAN AND DISABILITY

LIFE

SPA

N AN

D DI

SABI

LITY

Journal promoted by theDepartment of PsychologyInstitute for Research on Mental Retardationand Brain Ageing “Oasi Maria SS.” - Troina

Psychology Social issuesEducationRehabilitationHabilitation

• Life events exposure in people with intellectualdisabilities

• Marital satisfaction and attribution style inparents of children with Autism Spectrum Disor-der, Down Syndrome and non-disabled children

• The Scale of Personal Conceptions of Intelli-gence: A comparison of the Italian, Portugue-se, and Romanian versions

• Communicative and cognitive functioning inAngelman syndrome with UBE3A mutation: a casereport

• Italian standardization of the dynamic version ofthe Logical Operations and Conservation test(LOC-DV)

• Demographic and personnel service delivery data:implications for including students with disabili-ties in Italian schools

LIFE SPAN AND DISABILITYVol. XV / n. 1 /

January - June 2012

Vol. XV / n.1 / January - June 2012 ISSN 2035-5963

Psychology Social issuesEducationRehabilitationHabilitation

LIFE SPAN AND DISABILITYPsychology, Social issues, Education, Rehabilitation, Habilitation

Promotes interdisciplinary research about psychological, social, educational, rehabilitative and neuro psy-chological aspects of the human life span. The aim is to give diffusion to the scientific studies of personswho have to cope with cognitive and emotional and interpersonal problems – for transient or persistentreasons – in the different periods of the life, when specific existential events (e.g., adolescence, lost ofwork, retirement, end of fertility, normal and pathological aging) could cause disease or actual disability.The neuropsychological and social aspects of Intellectual Disability, and the strategies to enhance the co-gnitive rehabilitation and the quality of life of these persons, were a main target in the published studies.The attention is focused, for the different phases of life and for the specific conditions of disease, on theskills suitable to promote the person’s development, fully using all the existing or residual potentialities.The view to consider these aspects may be in turn educational, social, environmental, but taking into ac-count the connections with the bio-psychological bases and/or with the data derived from empirical rese-arch. Both quantitative and qualitative methodological approaches are welcomed.

The contributions received are submitted to two members of the scientific committee or external ex-perts, for a blind peer-review process.

Two issues per year will be edited, in English language, and published online on the website www.lifespan.it.Each issues will include research contributes, reporting original theoretical, methodological or empirical stu-dies; diagnostic or intervention instruments (validation of techniques as tests or grids in the field of interestof the Journal); case-reports of clinical or rehabilitative relevance; reviews on specific themes.

Editors in chief:Santo Di Nuovo (Catania) / Renzo Vianello (Padova) / Serafino Buono (Troina)

International scientific committee:• Valeria Abusamra (Buenos Aires) • Fredi Buchel (Geneva) • Gerhard Buettner (Frankfurt) • RaquelCasado Muñoz (Burgos) • Annick Comblain (Liège) • Vitor Da Fonseca (Lisbon) • Larry Dana (NewYork) • Douglas K. Detterman (Cleveland) • Monique Ernst (Bethesda) • Reuven Feuerstein (Jerusa-lem) • Sebastian Gaigg (London) • Carl Haywood (Nashville and New York) • Edward Janicki (Chi-cago) • Olga Jerman (Pasadena) • Mike Kerr (Wales) • Fernando Lezcano Barbero (Burgos) • JeanLouis Paour (Provence) • Ruth Luckasson (Albuquerque) • Michèle Mazzocco (Baltimore) • SusanPolirstok (New York) • Paul Probst (Hamburg) • Johannes Rojahn (Fairfax) • Jean Rondal (Liège)• Luis Salvador (Cadiz) • Elena Tanti Burlo (Malta) • John A. Tsiouris (New York) • David Tzuriel(Ramat-Gan, Israel) • Henny M J van Schrojenstein • Lantman-de Valk (Maastricht) • BenedettoVitiello (Bethesda) • Patricia Walsh (Dublin) • Germain Weber (Wien) • Karl Wiedl (Osnabruck)

EDITORIAL BOARD:Tommasa Zagaria (coordinator)

Maria Teresa Amata / Cinzia Bonforte / Santina Città / Francesco Di Blasi / Bernadette Palmigiano /Simonetta Panerai / Fabio Scannella / Marinella Zingale / Rosa Zuccarello

The English texts have been revised by Philip Doughty

© Associazione Oasi Maria SS. - IRCCS / Città Aperta EdizioniAll rights reserved

LIFE SPAN AND DISABILITY

Journal promoted by theDepartment of Psychology

Institute for Research on Mental Retardation and Brain Ageing “Oasi Maria SS.” - Troina

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Published online: June 2012

Summary

Life events exposure in people with intellectual disabilities

Paul J. Patti 7

Marital satisfaction and attribution style in parents of children with

Autism Spectrum Disorder, Down Syndrome and non-disabled children

Federica Santamaria, Francesca Cuzzocrea, Maria Cristina

Gugliandolo & Rosalba Larcan 19

The Scale of Personal Conceptions of Intelligence: A comparison

of the Italian, Portuguese, and Romanian versions

Annamaria Pepi, Luísa Faria, Marianna Alesi,

& Laura Ciochină 39

Communicative and cognitive functioning in Angelman syndrome

with UBE3A mutation: a case report

Marinella Zingale, Rosa Zuccarello, Serafino Buono, Maurizio

Elia, Antonino Alberti, Pinella Failla & Corrado Romano 55

Italian standardization of the dynamic version of the Logical Operations and Conservation test (LOC-DV)Renzo Vianello, Silvia Lanfranchi, Francesca Pulina,& Sara Bidinost 69

Demographic and personnel service delivery data: implications for

including students with disabilities in Italian schoolsMichael F. Giangreco, Mary Beth Doyle & Jesse C. Suter 97

Abstract

People with Intellectual Disabilities (ID), especially those living in resi-

dential settings, will likely experience one or more life events as they age

through the lifespan. Relocation, personal illness, and losses were the most

common life events in the ID population and have been implicated as risk

factors for physical and mental health problems. A number of studies have

reported a significant relationship between life events exposure and psy-

chiatric problems in people with ID. When and where a life event occurs,

and the ability to cope with an event(s) can have consequences on physical

and emotional well-being. The impact of a life event as being positive or

negative is also dependent upon how it is viewed by the person who expe-

riences it. Multiple life events exposure was found to have a cumulative

effect over time and increases the likelihood of emotional and behavioral

problems. Within the ID population, moving (relocation) was a more fre-

quent life event for adults with Down syndrome due to the higher incidence

of functional decline and dementia. Further studies are needed that look at

different age groups, living settings and sample grouping to better under-

stand the effects of life events exposure in people with ID.

Keywords: Life events exposure, Intellectual disabilities, Relocation

Received: September 30, 2011, Accepted: February 10, 2012.

© 2012 Associazione Oasi Maria SS. - IRCCS / Città Aperta Edizioni

1 George A. Jervis Clinic, New York State Institute for Basic Research in Developmental Disabilities

Staten Island, NY 10314 USA. E-mail: [email protected]

Send Correspondence to:

Paul J. Patti, George A. Jervis Clinic New York State Institute for Basic Research in Developmental Di-

sabilities, 1050 Forest Hill Road, Staten Island, New York 10314 USA

Fax: 011 (718) 494-2258

7

Life Span and Disability XV, 1 (2012), 7-18

Life events exposure in people

with intellectual disabilities

Paul J. Patti1

1. Introduction

Significant life events can have a direct as well as an indirect effect on phy-

sical and mental health. Negative life events have been associated with the

onset of depression in both children and adults in the general population (Bril-

man & Ormel, 2001; Tiet, Bird, Hoven, Moore, Wu, Wicks et al., 2001; Kraaji,

Arensman, & Spinhoven, 2002; Muscatell, Slavich, Monroe, & Gotlib, 2009).

Changes in routine or living situations were found to have a negative effect

on physical health and mortality for people with dementia (Mirotznik & Kamp,

2000; Butler, Orrell, Ukoumunne, & Bebbington, 2004; Waite, Bebbington,

Skelton-Robinson, & Orrell, 2004).

People with ID respond to traumatic and significant life events in similar

ways as in the general population. In an early study, Ghaziuddin (1988) repor-

ted that life events exposure was more associated with behavior problems in

individuals with mild ID than for those with severe ID and behavior problems

without a history of recent life events. Studies have consistently demonstrated

a significant relationship between life events exposure and psychiatric pro-

blems in adults with ID (Hastings, Hatton, Taylor, & Maddison, 2004; Hamil-

ton, Sutherland, & Iacono, 2005; Esbensen & Benson, 2006; Cooper, Smiley,

Morrison, Williamson, & Allan, 2007). Robust associations were also found

between specific adverse life events and psychiatric disorders among children

with ID (Hatton & Emerson, 2004). A study of referrals to a mental health ser-

vice revealed that depression, personality disorder, and adjustment reaction

were reliably linked with multiple exposure to life events (Tsakanikos, Bouras,

Costello, & Holt, 2007). Associations were also found between exposure to

negative life events and an increased frequency of aggressive/destructive be-

havior and the presence of affective disorder (Owen, Hastings, Noone, Chinn,

Harman, Roberts et al., 2004).

People living in a residential setting were found to experience more life events

than people living with natural or foster families (Hastings et al., 2004; Ha-

milton et al., 2005). When and where a life event occurs and the ability to cope

with an event(s) can have consequences on a person’s physical and/or emo-

tional well-being and even influence their continued placement in a particular

setting. The need to differentiate between traumatic experiences and life events

as predictors of psychopathology was raised by Martorell and Tsankanikos

(2008). They questioned whether such events served as risk factors or as trig-

gering factors when mental health problems occur; however this has yet to be

explored.

Specific life events such as moving to a new residence, experiencing a personal

loss, and changing jobs have been implicated as risk factors for physical and

8

Life Span and Disability Patti P. J.

mental health problems. Moving to a group home or changing jobs may be a

negative event for some individuals, whereas for others it can be a welcomed

positive event. The impact of a life event is dependent upon how it is viewed

by the person who experiences it. In a recent study, positive life events were

not found to be associated with concurrent behavior problems, however, the

frequency counts of life events and life events perceived as negative were re-

ported to play a role in the development of behavior problems and depressive

symptoms among adults with ID (Esbensen & Benson, 2006). In a critical re-

view of the studies conducted with people with ID thus far, Hulbert-Williams

and Hastings (2008) reported, “it appears likely that life events are causally

related to subsequent psychological problems but further research is needed

to establish the temporal precedence of life events and to build models of me-

chanisms by which this effect takes place”.

2. Issues in recording life events exposure

Currently, there is no gold standard in how investigators collect and record

life events data in people with ID. From a review of the literature, different

criteria have been used when analyzing and interpreting the data. In the seven

studies reviewed in this report, the number and category of life events studied

differed between the instruments used to measure them (see Table 1). The Psy-

chiatric Assessment for Adults with Developmental Disabilities (PAS-ADD)

(Moss, Prosser, Costello, Simpson, Patel, Rowe et al., 1998) was used in three

studies (Hastings et al., 2004; Tsakanikos et al., 2007; Martorell, Tsakanikos,

Pereda, Gutiérrez-Recacha, Bouras & Ayuso-Mateos, 2009). The PAS-ADD

is a semi-structured informant-based interview measure designed to identify

psychiatric problems in people with ID; it includes a checklist of 17 negative

life events which are not specific to people with ID. Two studies constructed

their own life events checklists for research purposes which were tailored for

people with ID (Owen et al., 2004; Patti, Amble, & Flory, 2005). The remai-

ning two studies used previously published questionnaires that included a va-

riety of life events (Hamilton et al., 2005; Esbensen & Benson, 2006).

According to Owen et al. (2004), adults with ID residing in an institutional

setting are exposed to a range of potentially negative life events over the course

of a typical year.

However, the impact of a life event as being positive or negative can be diffe-

rent based upon how it is perceived by the person who experiences it (Esbensen

& Benson, 2006).

9

Life events exposure in people with ID

The nature of an event as having a positive, neutral or negative impact on the

individual may be more important than the frequency of events (Stack, Haldi-

pur, & Thompson, 1987).

Variables such as the age of the person and the location where a life event

occurs can have a bearing on its impact especially for adults with Down syn-

drome (see Patti et al., 2005). Other factors to take into account are the sample

size and grouping, and the age-range of a study cohort which can have a bea-

ring on a study’s findings and conclusions. Only one study conducted thus far

was population-based in its scope (Hastings et al., 2004). The age-range and

mean age also varied across the seven studies; only one (Patti et al., 2005) fo-

cused on life events exposure in an “over age 50” adult cohort (see Table 1).

Therefore, studies on life events exposure need to include a number of factors

when exploring the effect(s) of one or more life events on the individuals who

experience them.


Table 1- Studies and instruments used to record life events exposure in peo-

ple with ID

Authors, year Instrument Used # Life events Type of events Cohort sizea Study duration

Owen et al.,

(2004)

Life Events List (LEL)

(developed by au-

thors)

20 only negative

events listed

93

M = 55.2 yrs

R = 24–93 yrs

previous

12 mos.

Hastings et al.,

(2004)

PAS-ADD

(Moss et al., 1998)

17 only negative

events listed

1155

M = 43.9 yrs.

R = 17-92 yrs.

previous

12 mos.

Hamilton et al.,

(2005)

Life Quality and He-

alth for Adults with

DD (1999)

37 events not rated 624

M = 34.2 yrs.

R = 18-76 yrs.

previous

24 mos.

Patti et al.,

(2005)

Life Events and Chan-

ges Checklist (develo-

ped by authors)

33 events not rated 211

M = 69.3 yrs.

R = 50-86 yrs.

previous

60 mos.

Tsakanikos et al.,

(2007)

PAS-ADD

(Moss et al., 1998)

17 only negative

events listed

281

M = 34.5 yrs.

R = 16-86 yrs.

previous

12 mos.

Esbensen &

Benson (2006)

Life Experiences Sur-

vey (Sarason et al.,

1978)

45 events rated as

positive, negative

or no impact

104

M = 42.0 yrs.

R = 21-79 yrs.

two 4 mo.

intervals.

Martorell et al.,

(2009)

PAS-ADD

(Moss et al., 1998)

17 only negative

events listed

177

M = 29.6 yrs.

R = not listed

previous

12 mos.

aM = mean age of study cohort; R = age range in study cohort

10

3. Multiple exposure to life events over time

Half the studies listed in Table 1 investigated life events exposure over a

12-month period which may limit assumptions when attempting to explain

their long-term effects. Owen et al. (2004) reported long-term hospital resi-

dents to have encountered an average of 3.50 negative events (range 0-8) in

the previous 12 months. The most frequently reported were staffing and resi-

dence changes, conflicts with staff/other residents, death of a close friend/re-

lative, and personal injury/illness. Analyses revealed that individuals exposed

to more recent (negative) life events were also rated as displaying more aggres-

sive/destructive behavior and were at increased risk for affective/neurotic disorder.

In a population-based sample of adults with ID who were receiving commu-

nity and residential services (N = 1155), 46% encountered at least one signifi-

cant life event and over 17% had two or more life events in the previous 12

months (Hastings et al., 2004). Significant relationships were found between

life events exposure and psychiatric problems. Similar to the findings of Owen

et al. (2004), the most frequent events were moving residence, illness of close

relative/friend, conflicts with others, illness/injury to self, and death of close

friend/relative. It was found that those living in an institution were more likely to

have experienced at least one recent event in the previous 12 months than those

residing in a community setting indicating location to be an important variable.

For 281 adults with ID seen in a mental health clinic, an average of 1.17

life events (range 0-7) was reported during the last 12 months (Tsakanikos et

al., 2007). Events such as moving out of house or residence and bereavement

were associated with some form of psychopathology. The study findings indi-

cated that depression, personality disorder and adjustment reaction were re-

liably associated with the multiple exposure to life events. In a study of 177

adults with ID living in the community, 75% had experienced at least one trau-

matic event during their lifespan, and 50% had experienced at least one nega-

tive life event in the previous 12 months (Martorell et al., 2009).

Others have investigated life events exposure over different time periods. Es-

bensen and Benson (2006) studied the life events (both positive and negative)

in 104 adults with ID over two 4 month periods. An average of 2.6 life events

(range 0-13) were reported with 0.8 rated as negative and 1.3 rated as positive.

Individuals with major depression were found to experience a significantly

greater number of all life events and more events perceived as negative in the

prior four months. It was proposed that experiencing life events in general and

negative life events can predict the development of behavior problems and de-

pressive symptoms among individuals with higher-functioning levels of ID.

11


Over a 2 year period, an average frequency of 4.68 life events (range 0-

16) was reported in 624 adults with ID living in family/foster care or a resi-

dential setting (Hamilton et al., 2005). Associations were found between emo-

tional and behavioral problems and life events exposure; the frequency of life

events varied according to the type of residence where the individual resided.

Regarding location, people living in a residential setting were found to en-

counter more life events than those living with family or a foster family which

supports the findings of Owen et al. (2004).

The number and types of life events over a 5 year period in an older cohort

of 211 adults with and without Down syndrome (DS) living in community

group homes were reported by Patti et al. (2005). Life events were divided

into four distinct categories: 1) relocations (i.e., moving to a new residence or

living setting), 2) environmental/social changes (i.e., change in day program,

bedroom, social relationships), 3) losses/separations (i.e., death of a parent/fa-

mily member/peer, change or loss of a roommate), and 4) medical events (i.e.,

hospitalization(s), surgery, onset of seizures, sustaining a fracture, pneumonia,

other medical changes). The DS adults were found to experience more life

events in all four categories than those without DS. The differences in life

events exposure for those with and without DS are highlighted in Table 2.


Life events category DS Group (n = 108)

(50-59 years)

NDS Group (n = 103)

(50-86 years)

Environmental/Social Changes .45 (.63)* .14 (.35)*

Loss/separation .45 (.72)* .12 (.39)*

Medical events/changes 1.35 (1.21)* .56 (.85)*

Table 2 - Mean number of life events by category in a cohort of older per-

sons with and without Down syndrome* (N = 211)

Due to the nature of an intellectual disability and the need for some form of

support, it is very likely that people with ID, especially those living in resi-

dential settings, will experience one or more life events and changes (positive

12

*taken from Patti et al. 2005

* The number in parenthesis is the standard deviation for each calculated mean. For all four categories, si-

gnificant differences between the DS and NDS groups were found (p < .001).

and negative) as they age through the lifespan. Most research has focused on

negative or adverse events, however specific events such as relocation (e.g.,

moving to a group home, transferring from one group home to another group

home) and changing jobs (e.g., a new job placement) may not be a true nega-

tive event as such a change may actually be anticipated or desired by the person

and result in a more positive outcome for them. What seems to be more im-

portant is the occurrence of multiple life events (both positive and negative)

and the inability to cope with their cumulative effect that can cause some form

of psychopathology.

From the cited studies, both the occurrence and frequency of life events were

associated with physical and mental health changes, but the degree of their im-

pact can vary based the person’s level of functioning, and on where they reside.

Additionally, the effect of one or more specific life events (e.g., relocation,

death of a relative/friend, physical illness) may not be fully manifested within

a certain time period (e.g., 12-months) as the consequences of multiple events

have been found to be cumulative but may take a longer time period before an

effect occurs.

Studying life events exposure over longer time periods (>12 months) may

provide more information to better predict the onset of depressive symptoms

and behavior problems in people with ID. Following this approach in future

studies, preventative efforts could then be developed to intervene with people

who have experienced one or more life events in order to reduce or prevent

behavior problems, symptoms of depression or other psychiatric conditions.

4. Life events exposure in subgroups of the ID population

A review of the literature revealed few studies that looked at life events in

children with ID. In an early study, Ghaziuddin, Alessi and Greden (1995)

found children with pervasive developmental disorder (PDD) and depression

to experience significantly more life events in the 12-months preceding eva-

luation than children with PDD alone. Coe, Matson, Russell, Silfer, Capone,

Baglio et al. (1999) found that children with Down syndrome (ages 6–15) ex-

perienced fewer life events in the preceding 12 months, but had more behavior

problems than typically developing (TD) children of the same age. This diffe-

red somewhat from Hatton and Emerson, (2004) who reported that children

with ID were more likely to experience a greater number and a wider range of

negative life events (e.g., losses, separations) than TD children.

It was also found that there was an association between some life events and

emotional disorders, and that the effect of the events appears to be cumulative.

13


Life events research has mainly focused on the general adult ID population;

most studies did not single out any special subgroups (e.g., people with Pra-

der-Willi and Fragile X syndromes, autism). Some studies, however, did in-

vestigate life events exposure in people with Down syndrome. Hamilton et al.

(2005) included 129 DS adults in their sample of 624 adults with ID (mean

age 34.2 years) but presented only frequency data on life event exposure. A

strong relationship between the frequency of life events and emotional/behavio-

ral problems was found for DS adults who were functioning in the mild range

but not for those in the moderate to severe range of ID. Owen et al. (2004) had

only 6 DS adults in their residential sample of 93 adults; as a result no distinctions

could be made with such a small number.

In the study by Patti et al. (2005) comparisons were made between the num-

ber and types of life events experienced by older adults with and without DS.

The findings revealed that DS adults in the sixth decade of life experienced a

significantly greater number of relocations and medical events than their non-

DS counterparts of similar or older ages. A follow-up study focused on the

number of relocations that occurred in an older cohort of 140 adults with and

without DS over a 5 and 10 year period (see Patti, Amble, & Flory, 2010). Data

on 61 DS adults (mean age 61.8 years) was compared with 79 non-DS adults

(mean age 70.7 years). The DS group encountered significantly more reloca-

tions (i.e., changing group homes, nursing home placements) than the non-DS

group over both time periods which were attributed to age-related functional

decline and presence of dementia that was more prevalent in the DS group. A

mean of 1.07 and 1.26 relocations respectively occurred during the 5 and 10

year periods in the DS group compared to a mean of 0.59 and 1.00 respectively

in the non-DS group. Nursing home placement for end-of-life care was signi-

ficantly higher in the DS group (39% versus 9%) whereas the majority (91%)

in the non-DS group remained in a group home setting. Mortality differences

were also significant between the two groups. Of the 44 DS adults who died,

the locations were nursing home 46%; hospital 39% and group home 16%; for

the 25 who died in the non-DS group it was group home 52%, hospital 28%

and nursing home 20% (Patti et al., 2010).

5. Conclusions

Life events exposure can have a direct as well as an indirect influence on phy-

sical and mental health of people with ID. Caregivers and health care profes-

sionals need to monitor both young and older people with ID who have

experienced one or more life events (both positive and negative) because they

are at risk for a consequential change in their behavior or functioning.

14


Studies have demonstrated that multiple life events can have a cumulative effect;

can have an impact on behavior, health and stability; and result in some form of

psychopathology. In addition, a medical event (e.g., a new illness or medical

condition), can further contribute to a change in a person’s emotional well-being

and affect quality of life.

Relocation (e.g., moving/changing residences), personal illness and personal

losses were reported to be the most common life events experienced in the

adult ID population. Often an older person with ID who is displaying age-re-

lated functional decline needs to be moved to another setting for increased care

and/or for safety management issues. Within the ID population, moving (relo-

cation) was reported to be a more frequent occurrence for older adults with

DS due to the higher incidence of functional decline and dementia which ne-

cessitates placing them in an alternative residence or health-related facility for

an increased level of care and supervision. It was suggested by Patti et al.

(2005) that the cumulative exposure of one or more life events with the addi-

tional onset of medical frailties associated with aging and dementia can com-

bine to create a stressful period for older adults with Down syndrome.

Further studies are necessary to better identify and evaluate the effects of

life events exposure in people with ID. Few studies to date have focused on

life events exposure in children, teenagers and the elderly as well as studying

life events in different subgroups of the ID population. These remain important

areas for future research. In addition, studying different living settings where

people with ID reside and including more population-based samples should

also be done. By tracking the occurrence of significant life events and developing

proactive coping strategies, we may be able to minimize or prevent the display of

behavioral problems and any associated psychiatric disorders. Also significant to

take into account is the impact of medical events on the physical and mental health

of older adults with ID, especially for those with DS, as they can present challen-

ges for caregivers on future placement and the delivery of care and services.

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18

Life Span and Disability / Ciclo Evolutivo e Disabilità Patti P. J.

Abstract

The aim of this research is to explore whether there are any differences in

couple satisfaction and couple attributions between families with disabled

and non-disabled children and to understand if a relationship exists among

the above-mentioned variables in parents of children with and without di-

sability. Parents of children with Autism Spectrum Disorder (low functio-

ning n = 16; high functioning n = 20); with Down Syndrome (n = 24) and

parents of non-disabled children (n = 40) were selected. Couple relationship

was investigated using the Italian version of the Dyadic Adjustment Scale

(DAS) and the Relationship Attribution Measure (RAM). Compared with

other groups, parents of children with ASD reported lower marital satisfaction

and a pattern of attribution that is negatively related to marital satisfaction.

Couple satisfaction and couple attribution are strongly related both in families

of children with ASD and in families of children with Down Syndrome. Results

showed differences between families of children with or without a disability,

and between parents of children with Autism and with Down syndrome. These

results can act as both a stimulus towards further research in families with

disabled children and as a starting point for clinical interventions.

Keywords: Family, Couple functioning, Dyadic Adjustment Scale, Di-

sability.

Received: September 08, 2011, Revised: December 07, 2011, Accepted: January 17, 2012.


1 University of Messina, Via Concezione 6/8, 98100 Messina (Italy). E-mail: [email protected] University of Messina, e-mail: [email protected] University of Messina, e-mail: [email protected] University of Messina, e-mail: [email protected]

19


Marital satisfaction and attribution style in parents

of children with Autism Spectrum Disorder, Down

Syndrome and non-disabled children

Federica Santamaria1, Francesca Cuzzocrea2, Maria Cristina Gugliandolo3 & Rosalba Larcan4

1. Introduction

Research on family and disability focuses on individual, familiar and social

aspects, such as the severity of disability, maternal well-being and family re-

sources (Weiss, 2002; Olsson & Hwang, 2008). These factors have been ge-

nerally analysed comparing families with a disabled child to families of

children with typical development.

Several studies have reported that parents of children with disabilities ex-

perience higher levels of stress than parents of typically developing children

(Boyd, 2002). When a child is born with a disability, the family must modify

previous routines to guarantee the child’s care. The difficulties encountered

from the reorganization of familiar relationships could be related to anxiety,

overprotection, rigidity (Lardieri, Blacher, & Swanson, 2000), and might ex-

plain lower levels of coherence, less emphasis on the personal growth of other

family members (Larcan, Cuzzocrea, & Oliva, 2008; Larcan & Cuzzocrea,

2011), and higher levels of parental depression compared with parents of non-

disabled children. The unexpected and permanent nature of the problem could

influence family functioning and future outcomes (Llewellyn, McConnell,

Thompson, & Whybrow, 2005). This is more evident in parents of children

with Autism Spectrum Disorder (Osborne, McHugh, Saunders, & Reed, 2008).

Belchic (1996) reported significantly lower parenting efficacy in parents of

a child with autism compared to parents of a child without disability. Mothers

of children with mental retardation reported a higher social burden than those

of children with a physical disability (Tangri & Verma, 1992), especially when

the children with disabilities grow up (Rimmerman & Duvdevani, 1996; Cuz-

zocrea & Larcan, 2005).

Children with autism can experience various problems, such as insomnia (Joh-

nson & Malow 2008), and sensory impairment like taste, smell, visual and au-

ditory processing problems (Rogers, Hepburn, Stackhouse, & Wehner, 2003;

Ghanizadeh, Alishahi, & Ashkani, 2009). These problems are likely to affect

the behaviour of their parents who are usually tired and depressed, showing ne-

gative reactions in both their professional and family life.

Mothers especially report lower parenting competence (Raj Kumari & Har-

preet, 2010), greater stress (Weiss, 2002) and a lower level of marital intimacy,

compared with mothers of children with normal development and with mothers

of children with Down Syndrome (Dabrowska & Pisula, 2010).

Family functioning and, moreover, how each part of the family perceives

the situation, is fundamental for the comprehension of interactions between

children with disability and their parents. The cognitive model of Lazarus and

Folkman (1984) regarding the relation between stress and coping has been consi-

20

Life Span and Disability Santamaria F. et al.

dered one of the theoretical foundations on the development of specific models

on family functioning (McCubbin & Patterson, 1983; Patterson, 1988). Paren-

tal cognitions have been analyzed from several studies that indicated that pa-

rents can develop characteristics of self-blame in response to their child’s

disability (Grant & Whittell, 2000). Garwick, Kohrman, Titus, Wolman and

Blum (1999) pointed out that parents with children with autism tend to blame

themselves for child’s disability. This dysfunctional pattern seems to be related

with parental resilience; in fact parents who tended to blame themselves for

the child’s disability were less resilient than those families who adopted other

causal explanations (Sanders, Mazzucchelli, & Studman, 2004).

On the other hand, Ireland, Sanders and Markie-Dadds (2003) have analysed

other variables that influence the family system: in particular, marital relation-

ship seems to be strongly related with children’s emotional and behavioural

problems. The poor dyadic adjustment in parents of children with disabilities

has been highlighted by many authors (Walker, Manion, Cloutier, & Johnson,

1992; Najman, Behrens, Andersen, Bor, O’Callaghan, & Williams, 1997). Pa-

rents are more likely to report difficult child behaviour when there are low le-

vels of partner support and high levels of disagreement between partners

(Cuzzocrea & Larcan, 2005). Parents of children with disruptive behaviour di-

sorders show low cohesion and expression of affection, less parental support

and poorer marital adjustment than parents of non-disabled children (Hibbs,

Hamburger, Kruesi, & Lenane, 1993).

Marital satisfaction is one of the protective factors for a positive adaptation

to stressful situations, such as the management of a disabled child. Higher le-

vels in marital satisfaction are related to lower levels of depression, lower pa-

renting stress, and improved efficiency in the parents' role (Kersh, Hedvat,

Hauser-Cram, & Warfield, 2006).

Much of the research demonstrates that parents of disabled children and, specifi-

cally, those with children with ASD, report lower levels of marital satisfaction

when compared with couples of non-disabled children and with those of children

with Down syndrome (Higgins, Bailey, & Pearce, 2005; Kersh et al., 2006).

Sanjuán and Magallares (2009) underlined how attribution styles could be

considered an important aspect for marital satisfaction in couples with children

with normal development; in fact the attribution style is a cognitive variable

which reflects how people typically explain the causes of negative events in

which they are involved (Sanjuán & Magallares, 2009), even more in stressful

situations (Fincham & Bradbury, 1992).

According to the Abramson, Seligman, and Teasdale model (1978), there are

three dimensions from which attributions regarding the causes of situations

21

Marital satisfaction and attribution style in parents of disabled and non-disabled children

are made, locus (degree to which a situation is attributed to something about

oneself), stability (degree to which a situation is a result of long-lasting causes),

and globality (degree of pervasiveness of the cause of a situation).

Fincham and Bradbury (1992) identify three other responsibility attribution

styles: the intent of the act, the motivation, and blame. The sharing of meanings

attributed to an event plays a key role in the organization and maintenance of

family processes; it helps to reduce the ambiguities and misunderstandings re-

lating to a difficult situation and creates a coordinated response that is critical

to maintaining stability within the couple. Many researchers (Bradbury & Fin-

cham, 1990; Fincham & Bradbury, 1992; McNulty & Karney, 2001) highli-

ghted how couples in stressful situations showed a depressotypic attribution

style. These couples tend to consider negative events as being internally cau-

sed, stable and global (Horneffer & Fincham, 1995) and, in some cases, the

spouses blame each other for the situation (Fincham & Bradbury, 1993).

In dissatisfied couples, negative attributions are related to the depreciation of

the positive partner's behaviour and the accentuation of its negative expression,

while the opposite pattern is true for satisfied couples. The partner’s negative

behaviours are judged as intentional, part of the person’s character and unlikely

to change over time (Fincham & Bradbury, 1992). A similar pattern of attri-

bution can cause feelings of hostility and dysfunctional interactions with the

partner. Opposite attribution styles were found in satisfied couples (Jacobson,

McDonald, Follette, & Berley, 1985; Baucom, 1986). Even though there is

strong evidence (Kersh, et al., 2006; Sanjuán & Magallares, 2009) about the

role of couple attribution in marital satisfaction, in literature there is a lack of

analysis of these variables in families of children with disability (Boyd, 2002).

2. Aims and hypothesis

For these reasons, the main aim of this study was to investigate the rela-

tionship between attribution style and couple adjustment in families with di-

sabled children. In particular, it was analysed whether there were significant

differences in couple adjustment and in style of attribution among four familiar

contexts: (1) Parents of children with low functioning Autism Spectrum Disorder;

(2) Parents of children with high functioning Autism Spectrum Disorder; (3) Pa-

rents of children with Down Syndrome; (4) Parents of non-disabled children.

The second object was to investigate whether there were significant corre-

lations among the above-mentioned variables, in each of the four groups of

parents.

22



3. Methods

3.1 Participants

Fifty married couples with two children agreed to take part in the study:

30 of them had a child with disability and 20 had both non-disabled children

(fathers’ average age = 43.8±5.5; mothers’ average age = 40.1±4.8). The par-

ticipants were selected from the same information obtained through a socio-

demographic questionnaire. All families belonged to a middle socio-cultural

level (20% of parents had a secondary school level, 45% of parents had a high

secondary school level and 35% had a university degree. Most of the mothers

were housewives (58%), while the 42% worked in public offices. Most of the fa-

thers worked in public administration (64%), while 36% had an independent job.

These families were divided into four groups in relation to the presence or

absence of a child with disability and in relation to the type of disability. 36

parents of children with Autism Spectrum Disorder, of which 20 parents (ave-

rage age = 40.5±4.8) of high functioning children, and 16 parents of low fun-

ctioning children (average age = 41.13±5.1) were selected. 24 parents (age =

43.7±6.2) had a child with Down Syndrome and 40 parents (age = 41.9±5.4) had

non-disabled children.

3.2 Instruments and Procedure

Individual questionnaires were separately presented to each parent. The Latin

Square design was used to control the order in which the questionnaires were

presented.

In order to investigate the partners’ perceptions of couple adjustment, both

partners were asked to fill in separately the Italian format of Dyadic Adjustment

Scale (DAS) (Gentili, Contreras, Cassaniti, & D’Arista, 2002). The DAS (Spa-

nier, 1976) is a 32-item self-report measure of relationship adjustment by de-

termining the degree of satisfaction couples are experiencing. Respondents are

asked to rate each of the items on a Likert-type scale choosing the most suitable

response options.

The DAS reliability in this study was α = .93 (fathers: α = .95; mothers: α =

.89). DAS includes the following four sub-scales: (1) Dyadic Cohesion, 5

items, assess the common interests and activities shared by the couple (fathers:

α = .72; mothers: α = .67); (2) Dyadic Consensus, 13 items, focus on matters

important to the relationship: religion, recreation, friends, household tasks, and

time spent together (fathers: α = .94; mothers: α = .86); (3) Dyadic Satisfac-

tion, 10 items, measure commitment and satisfaction perceived by partners

with the present state of the relationship (fathers: α = .82; mothers: α = .70);

23


(4) Affectional expression, 4 items, measure individual’s satisfaction in the ex-

pression of affection and sex in the relationship (fathers: α = .69; mothers: α =

.48). High scores in this questionnaire indicate a functional couple adjustment.

The attribution style was evaluated by the Relationship Attribution Measure

(RAM) (Fincham & Bradbury, 1992). Stimulus events on the Relationship At-

tribution Measure (RAM) consisted of 10 hypothetical negative partner’s be-

haviours (e.g. “your spouse criticizes something you say”). Specifically parents

are asked to rate on a 6-point scale the extent to which they agreed or disagreed

with attribution statements made about each of the negative partner’s beha-

viours. The statements were used to assess the different types of attributions.

The reliability of all RAM subscales is good with α = .98 (fathers: α = .98;

mothers: α = .97). For causal attributions, respondents were asked about the

extent to which the cause lies in the partner (locus - fathers: α = .87; mothers:

α = .80), was likely to change (stability - fathers: α = .92; mothers: α = .88)

and affected other areas of the marriage (globality - fathers: α = .93; mothers:

α = .91). For responsibility attribution, items assessed criteria believed to be

fundamental for the ascription of responsibility and intentionality of the act

(intent - fathers: α = .94; mothers: α = .94), its motivation (fathers: α =.95;

mothers: α =.95) and whether it was justified by mitigating circumstances

(blame - fathers: α = .96; mothers: α = .94). In this questionnaire high scores

underline a dysfunctional style of attributions for couple relationship.

3.3 Data analysis

The Statistical Package for Social Science (SPSS) was used to verify the

hypothesis. Non-parametric statistics were used to analyse data. To analyse

possible differences among groups the Kruskal-Wallis (1952), based on χ2 sta-

tistic, and the Jonckheere-Terpstra test (J-T) (1954) were calculated. In addi-

tion, to verify statistical differences between simple comparisons the

Mann-Whitney (U) test (1947) was applied. In order to verify statistical diffe-

rences within sub-scales, Wilcoxon Signed Ranks Tests (1945) were calculated

separately on dependent variables (DAS and RAM scores).

To verify whether there were significant correlations between dyadic adju-

stment (DAS) and styles of attribution (RAM) in each of the four groups of pa-

rents, Spearman tests (1904) were calculated. To better compare the results, all

data were transformed into sin-1 (Freeman & Tukey, 1950).

4. Results

4.1 Differences between groups

Table 1 synthesizes the means and standard deviations of DAS scores ob-

24


tained from the four groups of parents. The statistical analysis showed signi-

ficant differences among groups for dyadic satisfaction [χ2 (3) = 16.69; p <

.001] and in the total DAS scores [χ2 (3) = 8.01; p < .05]. These differences

were confirmed by the Jonckheere-Terpstra test [DAStot: J-T = 2.36; p < .02;

Dyadic Satisfaction: J-T = 3.34; p < .001].

Table 1 - Means and Standard Deviations of Dyadic Adjustment Scale (DAS)

scores by parents of disabled (low and high functioning Autism and

Down Syndrome) and nondisabled children

Parents of children with

Dyadic

cohesion

Dyadic

consensus

Dyadic

satisfaction

Affectional

expressionDAS Total

M SD M SD M SD M SD M SD

Autism Spectrum

Disorder – Low Funct..93 .24 1.01 .29 .95 .17 1.03 .31 .98 .21

Autism Spectrum

Disorder – High Funct..91 .23 1.08 .23 1.04 .17 1.13 .27 1.04 .19

Down Syndrome .99 .17 1.13 .13 1.08 .11 1.15 .21 1.09 .11

No disability .99 .17 1.15 .11 1.11 .08 1.14 .17 1.11 .09

Regarding the total DAS scores, parents of children with low functioning au-

tism reported poorer couple adjustment than parents of children with Down

Syndrome [U = 119.5; Z = -2.01; p < .04] and parents of non-disabled children

[U = 176; Z = -2.61; p < .009], but they didn’t differ with parents of children

with high functioning autism [U = 127; Z = -1.05; p = .3]. No statistical diffe-

rences were found when comparing parents of children with high functioning

autism with parents of children with Down Syndrome [U = 215; Z = -.57; p =

.56] and parents of non-disabled children [U = 305; Z = -1.49; p = .13].

All families with autistic children presented lower scores in all DAS subscales.

The statistical analysis confirmed that parents of children with high functioning

autism reported lower couple satisfaction then parents of non-disabled children

[U = 28; Z = -1.91; p < .05]. Instead these parents did not differ in affectional

expression [U = 378; Z = -.34; p = .173], consensus [U = 336; Z = -.99; p =

.31] and cohesion [U = 310; Z = -1.41; p = .15] in comparison with parents

with non-disabled children. No statistical differences between parents of chil-

dren with high functioning autism and of children with low functioning autism

were found [Dyadic Cohesion: U = 157; Z = -.08; p = .93; Dyadic Consensus:

25

U = 132; Z = -.89; p = .38; Dyadic Satisfaction: U = 110; Z = -1.58; p = .11;

Affectional expression: U = 135; Z = -.79; p = .44]. No statistical differences

between parents of children with high functioning autism and parents of chil-

dren with Down Syndrome were found [Dyadic Cohesion: U = 203; Z = -.87;

p = .38; Dyadic Consensus: U = 227; Z = -.30; p = .76; Dyadic Satisfaction:

U = 208; Z = -.74; p = .45; Affectional expression: U = 237; Z = -.07; p = .94].

Parents of children with low functioning autism had lower scores in the

dyadic consensus [U = 202; Z = -2.14; p < .03] and couple satisfaction [U =

102; Z = -3.97; p < .0001] when compared with families with a non-disabled

child. These groups were not differing in affectional expression [U = 283; Z =

-.66; p = .49] and cohesion [U = 266; Z = -.97; p = .33].

Parents of children with low functioning autism had lower scores in couple

satisfaction than parents of children with Down Syndrome [U = 97; Z = -2.63;

p < .008]. These groups did not differ in affectional expression [U = 165; Z =

-.74; p = .47], consensus [U = 136; Z = -1.53; p = .12] and cohesion [U = 165;

Z = -.75; p = .47].

There were no significant differences between parents of children with Down

Syndrome and non-disabled children in affectional expression [U = 1472; Z = -

.11; p = .90], consensus [U = 405; Z = -1.04; p = .29], couple satisfaction [U =

363; Z = -1.63; p = .11] and cohesion [U = 460; Z = -.27; p = .78].

The Wilcoxon Signed Ranks Test confirmed that parents of children with high

functioning autism have higher levels of affectional expression than of con-

sensus [Z = 1.91; p < .05], couple satisfaction [Z = 1.98; p < .05], and cohesion

[Z = 3.55; p < .0001]. In addition, they presented a lower evaluation in cohesion

than in consensus [Z = 3.66; p < .0001] and couple satisfaction [Z = 2.76; p <

.006]. These parents had the lowest scores in consensus and couple satisfaction

and no statistical differences were found between these aspects [Z = .78; p = .43].

Parents of children with low functioning autism showed low dyadic ad-

justment in all sub-scales analysed. No statistical differences were found com-

paring affectional expression scores with consensus [Z = -.465; p = .64], couple

satisfaction [Z = -1.345; p = .18] and cohesion [Z = -1.55; p = .12]. In the same

way, no statistical differences were found comparing cohesion with consensus [Z

= -1.34; p = .18] and with couple satisfaction [Z = -.31; p = .76], such as couple

satisfaction and consensus [Z = -1.810; p = .07]. Parents of children with Down

syndrome have higher levels of affectional expression than couple satisfaction

[Z = 2.1; p < .04], and cohesion [Z = 3.34; p < .001], but no statistical diffe-

rences were found comparing with consensus [Z = -.91; p = .36]. On the other

hand, levels of cohesion were lower if compared with consensus [Z = 3.14; p <

.002] and couple satisfaction [Z = 2.54; p < .01]. Also in this situation, differences

between couple satisfaction and consensus were not found [Z = 1.29; p = .2].

26



Parents of non-disabled children evaluated the affectional expression better

than cohesion [Z = 3.69; p < .0001]. No statistical differences were found com-

paring affectional expression with couple satisfaction [Z = .51; p = .61] and

with consensus [Z = -.25; p = .79]. These parents gave a lower evaluation in

cohesion than in consensus [Z = 4.53; p < .0001] and in couple satisfaction [Z

= 3.6; p < .0001]. In addition, these parents presented a higher consensus than

couple satisfaction [Z = 1.99; p < .05].

Table 2 shows means and standard deviations of RAM sub-scales obtained

from parents of children with high and low functioning autism, with Down

Syndrome and from family of non-disabled children. The analysis highlighted

some significant differences among groups in

the globality sub-scale [χ2 (3) = 8.71; p < .03], confirmed by the Jonckheere-

Terpstra test [J-T = -2.19; p < .03].

The groups differed in the motivation sub-scale [χ2 (3) = 7.81; p < .05],

even though the tendency test did not confirm these results [J-T = -1-67; p <

.09]. On the other hand, even if no statistical differences comparing blame sco-

res between parents were found [χ2 (3) = 6.9; p = .07], the Jonckheere-Terpstra

test underlined a significant tendency [J-T = -2.25; p < .02].

The analysis of scores of couple attributions expressed by parents and

the data analysis underlined how parents of children with high functioning au-

tism obtained the same statistical scores comparing with parents of children

with low functioning autism [Locus: U = 127; Z = -1.03; p = .3; Globality: U

= 128; Z = -1.01; p = .3; Stability: U = 127; Z = -1.05; p = .3; Motivation: U =

101; Z = -1.8; p =.06; Intent: U = 109; Z = -1.62; p = .1; Blame: U = 141; Z =

-.57; p = .58] and comparing with parents of children with Down Syndrome

Parents of children with Locus Stability Globality Intent Motivation Blame

M SD M SD M SD M SD M SD M SD

Autism Spectrum

Disorder – Low Funct..80 .29 .64 .29 .70 .28 .69 .32 .71 .31 .66 .34

Autism Spectrum

Disorder – High Funct..69 .23 .56 .27 .61 .27 .53 .30 .56 .37 .57 .31

Down Syndrome .66 .21 .56 .27 .64 .28 .54 .35 .55 .30 .52 .36

No disability .73 .17 .53 .18 .48 .21 .46 .24 .45 .22 .44 .23

Causal attribution Responsibility attributions

Table 2 - Means and Standard Deviations of Relationship Attribution Measure

(RAM) scores by parents of disabled (low and high functioning Autism

and Down Syndrome) and nondisabled children.

27

[Locus: U = 237; Z = -.07; p = .94; Globality: U = 223; Z = -.40; p = .9; Stability:

U = 234; Z = -.14; p = .88; Motivation: U = 238; Z = -.03; p = .97; Intent: U = 234;

Z = -.13; p = .9; Blame U = 209; Z = -.72; p = .47] and comparing with parents of

non-disabled children [Locus: U = 361; Z = -.61; p = .4; Globality: U = 317; Z = -

1.3; p = .2; Stability: U = 397; Z = -.04; p = .9; Motivation: U = 359; Z = -.64; p =

.51; Intent: U = 353; Z = -.73; p = .5; Blame: U = 288; Z = -1.7; p = .08].

Simple comparisons show, instead, that parents of children with low functio-

ning autism have higher scores in the globality [U = 170.5; Z = -2.71; p < .007],

intent [U = 162.5; Z = -2.86; p < .004], motivation [U = 154; Z = -3.02; p < .003]

and blame sub-scales [U = 172.5; Z = -2.68; p < .007] than parents of non-disa-

bled children; no statistical differences were found between these two groups in

locus [U = 286; Z = -.61; p = .4] and stability [U = 237; Z = -1.5; p = .13] scores.

Parents of children with Down Syndrome had a higher score in globality sub-

scale than parents of non-disabled children [U = 319.5; Z = -2.23; p < .03]. No

statistical differences were found in other sub-scales [Locus: U = 407; Z = -1.01;

p = .3; p = .3; Stability: U = 450; Z = -.41; p = .7; Motivation: U = 401; Z = -1.09;

p = .27; Intent: U = 435; Z = -.62; p = .5; Blame: U = 433; Z = -.65; p = .5].

The Wilcoxon Signed Ranks Test showed the same results in families with

children with high and low functioning autism. Parents of children with high fun-

ctioning autism tend to attribute negative events to the partner more than stability

[Z = 3.54; p < .0001], globality [Z = 1.89; p < .05], intent [Z = 3.22; p < .001],

motivation [Z = 2.45; p < .01] and blame [Z = 2.69; p < .007].

The same results were found in parents of children with low functioning

autism. They showed the same dysfunctional pattern of attributions in which

one partner’s behaviour is perceived as the cause of the problem more than

stability [Z = 2.58; p < .01], globality [Z = 2.27; p < .02], intent [Z = 1.96; p <

.05] or blame [Z = 2.86; p < .004]. No statistical differences between locus

and motivation were found [Z = 1.65; p < .09].

A different result was found in parents of children with Down Syndrome: in

this case there were higher scores in locus only in comparison with motivation

[Z = 2.16; p < .03] and globality [Z = 2.03; p < .04]. Unlike other groups, these

parents show higher scores in globality compared with motivation [Z = 2.55;

p < .01] and blame [Z = 2.11; p < .03] scales.

The style of attribution of parents with non-disabled children seems more si-

milar to that of parents of autistic children. In fact, even in this family context,

parents tend to attribute negative events more to the partner than to stability

[Z = 4.88; p < .0001], globality [Z = 4.87; p < .0001], intent [Z = 4.76; p <

.0001], motivation [Z = 5.08; p < .0001] or blame [Z = 5.13; p < .0001]. Ho-

wever, unlike others, in these groups parents had a significantly higher score

28



in stability than intent [Z = 2.68; p < .007], motivation [Z = 2.17; p < .03] and

blame [Z = 2.34; p < .02] scales.

4.2 Correlations between DAS and RAM

The second object was to investigate whether there were statistical cor-

relations between couple adjustment and style of attribution in each of the four

groups of parents. As shown in table 3, higher scores in RAM sub-scales that

represent a dysfunctional style of attributions are negatively related with total

DAS, especially in the two groups of parents with autistic children. The relation

between attributions style and couple functioning are similar in parents of Down

Syndrome children and in parents with non-disabled children. In families with

high functioning children, all DAS sub-scales were negatively correlated with

the different aspects of couple attribution.

These results were also confirmed when analysing parents of low functioning

children, but, in this case, couple satisfaction seems not to be related with locus

[ρ = -.16; p = .55], stability [ρ = -.35; p = .18], globality [ρ = -.39; p = .14]

and blame [ρ = -.45; p = .08]. Parents of low functioning children show that a

high level of dyadic satisfaction was associated with a lower tendency to at-

tribute intentionality [ρ = -.53; p < .03] and to blame the partner [ρ = -.49; p

< .05] in negative situations. In parents of children with Down syndrome, only

the locus sub-scale was strongly related to all the DAS sub-scales [Locus vs. Con-

sensus: ρ = -.42; p < .037; Locus vs Satisfaction: ρ = -.53; p < .007; Locus vs. Co-

hesion: ρ = -.55; p < .005; Locus vs. Affectional Expression: ρ = -.48; p < .016].

Different correlations in parents with non-disabled children were found. In

this context, it was possible to observe a lower tendency to attribute responsi-

bility to the other partner together with high dyadic consensus [ρ = -.38; p <

.02]. Consequently, the lower tendency to attribute responsibility to the other

was associated with less difficulty in expressing affection [ρ = -.32; p < .04].

In families with non-disabled children, couple satisfaction seems to be a relevant

aspect in moderating the partners’ relationship. High scores in satisfaction were

significantly correlated with the tendency to attribute motivation [ρ = -.57; p <

.0001], blame [ρ = -.51; p < .001] and intent [ρ = -.43; p < .005]. In addition,

couple satisfaction in parents of non-disabled children significantly reduced the

generalization of negative partner behaviour [Globality: ρ = -.42; p < .006].

29


Table 3 - Spearman's rho correlations between total DAS and Couple At-

tributions (RAM) scores expressed by parents of disabled (low

and high functioning Autism and Down Syndrome) and nondisa-

bled children.

Groups Locus Stability Globality Intention Motivation Blame

Autism Spectrum

Disorder - LF

(N=16)

ρ -.51 -.57 -.58 -.81 -.75 -.79

p .045 .02 .02 .001 .001 .001

Autism Spectrum

Disorder - HF

(N=20)

ρ -.71 -.83 -.79 -.82 -.75 -.71

p .001 .001 .001 .001 .001 .001

Down Syndrome

(N=24)

ρ -.57 -.24 -.21 -.15 -.27 -.26

p .003 .26 .33 .49 .21 .22

No disability

(N=40)

ρ -.11 .02 -.28 -.29 -.44 -.37

p .53 .91 .08 .07 .004 .02

5. Discussion and Conclusion

The first object of this research project was to analyse the differences in

dyadic adjustment and couple attributions in parents of children with high

and low functioning Autism Spectrum Disorder and in parents of children with

Down Syndrome, compared to parents of non-disabled children.

This paper has brought to light some interesting results, underlining differences

between families of children with disability and families with non-disabled

children and between parents of children with different types of disabilities.

The presence of a disabled child is associated with a lower level of dyadic ad-

justment and, as expected, it seems that parents with autistic children expe-

rience more difficulties. In particular, it is clear that parents of children with

low functioning autism perceive lower levels of couple adjustment when com-

pared with parents of children with Down Syndrome and with parents of non-

disabled children. The presence of a child with high functioning autism seems

to be associated with less dyadic adjustment only if compared with parents of

non-disabled child.

30

Interesting results regard the style of attribution: parents of children with low

functioning autism use different parental styles of attribution comparing with

parents of non-disabled children. In particular, parents of children with low

functioning autism show a tendency to generalize partner’s negative behaviour

and to use internal locus of control for negative events. In this group, the couple

blames partner’s behaviour that are perceived as intentional and stable over

time. On the other hand, parents of children with Down Syndrome tend to gene-

ralize partner’s negative behaviour more than parents of non-disabled children.

The second object was to examine the correlations between partners’ percep-

tions of couple adjustment and style of attribution in each of the four groups

of parents. In accordance with literature (Fincham & Bradbury 1992), results

confirmed that couple attributions are strongly related with dyadic adjustment

in all families. However, a stronger relationship emerged in parents of children

with low functioning autism that reported a dysfunctional pattern of couple at-

tribution and an internal locus of control for negative events. In addition, the

results show that parents of children with Down Syndrome probably had an

internal locus of control for negative events which is extremely dysfunctional

for couple relationship. Overall, this paper underlines a strong negative relation

between a dysfunctional attributional style and dyadic adjustment, mostly in

families of children with low functioning autism. Even though it is not possible

to verify the direction of the relation between couple adjustment and couple at-

tributions, the strong relation between these variables has been demonstrated.

In conclusion, it is possible that the stressful situation experienced by parents

of children with Autism Spectrum Disorder, mostly those of children with low

functioning autism, have contributed to maintaining a dysfunctional pattern

of attributions over time and, consequently, to decreasing couple satisfaction.

Unfortunately, the limited number of parents does not allow generalizations

regarding these results. The results obtained can act as both a stimulus towards

further research on families of children with autism and other disabilities, and

also as a starting point for further clinical interventions. In fact, these results

highlight a dysfunctional pattern of attribution in the two groups of parents

with autistic children and a strong relation between this pattern and dyadic ad-

justment. For this reason, it could be useful in the assessment of families of

children with disabilities to consider the importance of cognitive factors (Ven-

katesh, 2008), because dysfunctional beliefs can quickly become stable and

be the cause of dysfunctional behaviours against the partner (Fincham & Brad-

bury, 1992; Boyd, 2002; Sanjuán & Magallares, 2009). Partners, using dysfun-

ctional patterns of attribution, would be more prone to develop depression

when faced with stressful situations than those who habitually offer external,

unstable, and specific causes to explain these negative events: this pattern could

31


be extremely dysfunctional for family functioning and for parenting.

A specific training for parents of children with disabilities, focused on couple

relationship and, in particular, on dyadic attribution, could be important to pre-

vent any possible problem that could interfere on a healthy psychological de-

velopment of the child.

Furthermore, it could be interesting to study these variables, not only in

relation with couple satisfaction and couple adjustment, but also in relation

with other variables that can influence family functioning, such as the parents’

perception of stress or coping strategies used to deal with the child’s disability.

In fact, the differences among groups reported in this study showed that the

type of disability is a very important variable that can influence couple rela-

tionship in different ways. This study focused on families of children with au-

tism spectrum disorder and with Down Syndrome, but it could also be useful

to evaluate couple functioning and attribution styles in families of children

with other types of disability, such as learning disorders or ADHD.

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Abstract

Background: The aim of this research project was to conduct studies of

confirmatory factor analyses of ECPI (Scale of Personal Conceptions of

Intelligence) in three different cultural contexts – Italy, Portugal and Ro-

mania. We hypothesized a bi-factor structure of the instrument constructed

in Portugal by Faria (1990; 2006). Method: 617 subjects, 222 Italian, 200

Portuguese, and 195 Romanian students participated in the study, atten-

ding high school, equally distributed according to their gender and so-

cioeconomic status. We administered the ECPI composed of 26 items, of

which 15 static and 11 dynamic. Results: In the three cultural contexts the

results revealed the existence of 7 items, one measuring the incremental

and 6 the static theory, with low factor loadings – inferior to .30. These

results convinced us to test a new model eliminating these 7 items. There-

fore, even if the fit of the model improved, this could not be considered a sa-

tisfactory result. Conclusions: Future research could include more in depth

analyses of linguistic properties of items which compose the static sub-scale,

in order to find better operationalizations of the static personal conceptions

of intelligence.

Keywords: Motivation, Self-Concept, Psychological Assessment.

Received: February 10, 2011, Revised: October 26, 2011, Accepted: February 10, 2012.


1 This study was carried out with funds of the University of Palermo/Italy (Bando CoRI, 2005) and the Faculty

of Psychology and Education – University of Porto/Portugal.2 Department of Psychology, University of Palermo, v.le delle Scienze, Edificio 15, 90128 Palermo; fax 091-

7028430, e-mail: [email protected] 3 Faculdade de Psicologia e de Ciências da Educação, Universidade do Porto, Portugal. E-mail: lfaria@fpce.

up.pt4 Department of Psychology, University of Palermo. E-mail: [email protected]

Faculdade de Psicologia e de Ciências da Educação, Universidade do Porto, Portugal. E-mail: lciochina@

fpce.up.pt39


The Scale of Personal Conceptions of Intelligence:

A comparison of the Italian, Portuguese,

and Romanian versions1

Annamaria Pepi2, Luísa Faria3, Marianna Alesi4,& Laura Ciochină5

1. Introduction

The present study on personal conceptions on the intelligence of Italian, Por-

tuguese, and Romanian students extends previous research which was aimed

at comparing the psychometric properties of the Portuguese and Italian versions

of the Scale of Personal Conceptions of Intelligence (Pepi, Faria, & Alesi, 2007).

Faria (1990, 1998, 2003, 2006) developed and validated a questionnaire called

the Scale of Personal Conceptions of Intelligence, originally abbreviated ECPI

(Scale of Personal Conceptions of Intelligence), to measure Portuguese ado-

lescents’ beliefs about the nature of their own abilities. The instrument stems

from Carol Dweck’s theoretical model (1999) which postulates two different

views of ability or intelligence, incremental and entity views. Individuals be-

lieving in the incremental conception conceive intelligence as a controllable

quality, malleable and susceptible to being increased through effort, which

leads prevalently to the adoption of learning goals designed to increase one’s

ability and competency. On the other hand, individuals affirming the entity

conception, conceive intelligence as a fixed and uncontrollable quality, inhe-

rent in the individual, which leads prevalently to performance goals for the

immediate demonstration of the adequacy of one’s abilities (Dweck & Leggett,

1988; Elliott & Dweck, 1998; Dweck, 1999; Grant & Dweck, 2003).

More specifically, the ECPI consists of 26 items, 11 for the incremental and

15 for the entity conception.

The ECPI is a multidimensional instrument since it also includes items mea-

suring the relevance of effort versus ability and the choice of learning goals re-

lated to mastering new abilities versus performance goals related to demonstra-

ting one’s own intelligence through the achievement of positive outcomes.

On the whole our earlier study evidenced to a satisfactory degree psychometric

properties, both in the Italian and in the Portuguese contexts (Pepi et al., 2007).

In particular, the results of factor analyses revealed the existence of two distinct

factors, static and dynamic, that explain together 40% of the total variance.

Factor 1 was loaded prevalently by the dynamic items, which aim to measure

intelligence as a potential that can be improved and increased through effort,

while factor 2 was loaded by the static items, which measure intelligence as a

fixed and immutable gift. The internal consistency of the scales evidenced alpha

coefficients between .72 and .80. Nevertheless, we had pointed out some shor-

tcomings of the mentioned study.

First, we used two rather similar cultural contexts (Italy and Portugal); second,

the sample needed to be futher expanded. These limits gave rise to the need of fur-

ther research that would provide us with a more comprehensive assessment of the

psychometric properties of the ECPI in other cultural contexts.

40

Life Span and Disability Pepi A. et al.

As such, we conducted further research employing a third terriorial context,

Romania. Within the context of this research, this country results qualitatively

different, due to its socio-economic conditions and also with regard to the cul-

tural dimension of individualism-collectivism (IND/COL). The majority of

cross-cultural studies of ability-related beliefs has long been focused on the

analysis of the individualism-collectivism dichotomy (Hofstede, 1980; Kagit-

çibaci, 1994; Heine, Kitayama, & Lehman, 2001; Harrington & Liu, 2002).

Individualism considers the individual as the unit of analysis in a society, sup-

ports the perception of the uniqueness of personal qualities, and proposes the

construction of the self independently from the group, with particular emphasis

on idiocentrism, self-efficiency, autonomy, and competition, to help achieve

personal goals while pursuing self-realization and success (Triandis, McCu-

sker, & Hui, 1990; Carver, Lawrence, & Scheier, 1996). Collectivism, on the

contrary, considers the group as the unit of analysis in a society and asserts

that personal involvement and commitment are dimensions defined by one’s

own group of reference thus leading to an interdependent construction of the

“Self” (Sampson, 1988). Emphasis is placed on aspects such as allocentrism,

obedience, and conformity, with special attention given to the family as the

most important in-group (Georgiou, 1995).

Specifically, Italy and Portugal appear to be more easily classified as indivi-

dualistic cultures characterized by elements such as dominance of individual

interests, freedom of the press, political power exercised by the electorate, the

prevalence of the value of freedom over that of equality, and the search for

personal self-realisation as the main objective of the individual (Faria, Pepi,

& Alesi, 2004; Pepi, Faria, & Alesi, 2004).

The differences between Portugal and Romania identified by Ciochină and

Faria (2006a; 2006b) appear to be greater. Although both countries have un-

dergone dictatorial regimes (fascism in Portugal and communism in Romania),

“...which conditioned the structuring of a collectivist mentality through ideo-

logical, political, cultural, and social mechanisms” (Ciochină & Faria, 2006b),

they differ in that the Portuguese society is characterized by assimilation to a

greater extent of individualistic values and norms, as a result of a higher Gross

National Product and of an economy strongly based on individual interests.

These differences in IND/COL foster distinct belief systems about the meaning

of the terms “ability” and “effort” and influence personal conceptions of in-

telligence. Portuguese tend to orient the conception of “intelligence” towards re-

garding one’s personal attributes and motivational elements such as concentration,

effort, interest, curiosity, while the Romanians orient it towards more pragmatic

factors, with social weight such as “... getting by in society, not committing big

mistakes, appearing intelligent in life” (Ciochină & Faria, 2006a, p. 1024).

41

The Scale of Personal Conceptions of Intelligence

Given these theoretical premises, this study aims to compare the psy-

chometric properties of the Scale of Personal Conceptions of Intelligence in

three cultural contexts. In particular, our goal is to verify its factor structure

through confirmatory factor analyses in three samples of Italian, Portuguese,

and Romanian adolescents.

2. Method

2.1 Instruments and procedure

Subjects were given the Scale of Personal Conceptions of Intelligence con-

sisting of 26 items, 15 for the entity conception and 11 for the incremental one.

The entity or static items describe intelligence as a fixed trait which is not

under the individual’s own control, as a gift the individual is endowed with

and cannot change (I have a certain amount of intelligence and I can’t do much

to change it or The difficulties and the challenges I encounter prevent me from

developing my intelligence). In contrast, the incremental or dynamic items de-

scribed intelligence as a quality that is controllable, malleable and susceptible

to being improved as a function of commitment and effort (Effort enables me to

become more intelligent or What I learn with the tasks I make is more important

than the results obtained).

The administration was collective and the task lasted no more than 20 minutes.

The Portuguese version of the scale was translated into Italian by the collabo-

rative efforts of the Portuguese and Italian authors. The same administration

procedure was used in both countries. In particular, subjects were asked to read

each sentence carefully and express their degree of agreement with it, using

an answer scale ranging from Totally agree to Totally disagree. The scoring

were from 1 to 6 points for each dynamic item and from 6 to 1 point for each

static item: the maximum score (6) corresponded to total agreement with the

items from the dynamic scale or total disagreement with the items from the

static scale. On the contrary, the minimum score (1) corresponded to total di-

sagreement with the items from the dynamic scale and total agreement with

the items from the static scale.

Thus, higher scores indicated more dynamic and less static conceptions of in-

telligence and thus produced a dynamic evaluation of the scale.

In Italy we employed the Italian version of ECPI obtained by previous tran-

slation from Portuguese to Italian and then by back translation from Italian into

Portuguese to ensure maximum linguistic and cultural coherence among the

versions (Van de Vijver & Hambleton, 1996). As mentioned in the Introduction

section the Italian ECPI showed a bifactor structure and the internal consi-

stency of the scales yielded alpha coefficients between .72 and .80.

42



In the Portuguese sample, Cronbach’ alpha coefficient is .78 for the static subscale

and .78 for the dynamic one (Faria & Fontaine, 1997). In the Romanian sample,

previous studies (Ciochină & Faria, 2006b) yielded an alpha coefficient of .72

for the static subscale and of .77 for the dynamic one.

2.2 Sample

The subjects in this study were 617 Italian, Portuguese and Romanian students

attending the tenth or the twelve grade of secondary school (humanistic, scien-

tific and technical schools). Specifically, the Italian group consisted of 222

students, with an average chronological age of 17.1 yrs. old (SD = 1.07). The

Portuguese group consisted of 200 students, with an average chronological

age of 17.6 yrs. old (SD = .86). The Romanian group consisted of 195 students,

with an average chronological age of 17.1 yrs. old (SD = 1.02). Look at table

1 for other demographics.

Table 1 – Sample distribution by cultural context, school grade, gender,

scholastic emphasis and socioeconomic status.

School Grade Gender Scholastic emphasis Socioeconomic status

Cultural

Context10

th12

thTotal F M Total S H T Total High Middle Low Total

Italian

N 111 111 222 110 112 222 73 74 75 222 87 93 42 222

% 50.0 50.0 100 50.5 49.5 100 32.9 33.3 33.8 100 39.2 41.9 18.9 100

Portuguese

N 100 100 200 131 69 200 70 77 53 200 49 77 73 199

% 50.0 50.0 100 34.5 65.5 100 35.0 38.5 26.5 100 24.6 38.7 36.7 99.0*

Romanian

N 97 98 195 134 61 195 57 74 64 195 59 122 2 183

% 49.7 50.3 100 31.3 68.7 100 29.2 37.9 32.8 100 30.3 62.6 1.0 93.9**

Legend: S = scientific-oriented program; H = humanistic; T = technical; SES = Socioeconomic status.

Note: *There was a missing value (1%) in the answers to the SES variable.**There were 12 missing values (6.1%) in the answers to the SES variable.

43


3. Results

A confirmatory factor analysis was conducted using the EQS program, version

6.1. In evaluating the fit of the models that we tested, we took into account the

following fit indices: χ2, CFI (comparative fit index), RMR (root mean-square

residual) and RMSEA (root mean-square error of approximation).

The χ2 analyses the discrepancy between the observed model and the theore-

tical one. If a certain model has a statistically significant χ2, this means that

the observed model differs from the theoretical one. Since the value of χ2 is

sensible to the dimension of the sample (Schumacker & Lomax, 1996, in San-

tos & Maia, 2003), we also took into consideration other three indices for a

more exhaustive analysis of the fit.

Thus, we considered the CFI which compares the observed model with a

null model, that is, a model in which no estimates are made. The values of the

CFI range between 0 and 1. Values above .90 and .95 are considered to indicate

an acceptable and good fit respectively (Byrne, 1994).

Another index we looked at was the RMR which provides a summary of the

magnitude of the residuals. The value of the RMR should be inferior to .05

(Byrne, 1994). Finally, the last index we employed was the RMSEA which

analyses the approximation of the observed model to the population model.

Consequently, this index should have a p value inferior to .05. Models with

values of the RMSEA superior to .01 should be rejected and those with values

of the RMSEA between .08 and .05 or inferior to .05 should be maintained in

the analyses (Byrne, 1994).

The first model – the theoretical model – is presented in Figure 1 with two

factors, 15 items which load on the static-entity factor, and 11 which load on

the dynamic-incremental factor, analyzed separately for the Portuguese, Ro-

manian, and Italian groups. The hypothesis is that in each sample group, the

items of the two sub-scales (static and dynamic) load only on their latent va-

riable, either the static or the dynamic one.

In none of the three samples, Italian, Portuguese, and Romanian, did the re-

sults indicate a satisfactory fit to the theoretical model. In fact, in each group

the same 7 items presented low loadings, inferior to .30. Specifically, of these

items, 6 measure the static conception (items n. 1, n. 10, n. 14, n. 16, n. 19,

and n. 20) and 1 measures the dynamic conception (item n. 4). The values of

the fit indices considered in the CFA are presented in Table 2.

44


Figure 1 – Theoretical model of ECPI

Table 2 – Values of fit indices to the theoretical model in Italian, Portuguese

and Romanian samples.

Theoretical model

χ2 gl CFI RMR RMSEA

Italian sample

(N = 222) 763.78 298 .63 .18 .09

Portuguese sample

(N = 200) 764.81 298 .62 .19 .09

Romanian sample

(N = 195) 762.90 298 .62 .19 .09

45

Given the unsatisfactory fit to the theoretical model, we decided to test a

reconfigured model of the ECPI, whose structure did not include items with

loadings lower than .30, mentioned above. Consequently, the static sub-scale

was reduced to 9 items (n. 2, n. 5, n. 7, n. 8, n. 12, n. 15, n. 18, n. 22, and n.

25) and the dynamic sub-scale to 10 items (n. 3, n. 6, n. 9, n. 11, n. 13, n. 17,

n. 21, n. 23, n. 24, and n. 26). The configuration of the new model is presented

in Figure 2.


Figure 2 – Reconfigured model of ECPI

The new model was tested in the Portuguese, Romanian, and Italian groups

and yielded better values of the fit indices, although they were not completely

satisfactory, as it can be seen in Table 3.

Table 3 – Values of fit indices to the reconfigured model in Italian, Portuguese

and Romanian samples

Theoretical model


Italian sample

(N = 222) 321.03 150 .81 .12 .07

Portuguese sample

(N = 200) 342.65 150 .81 .13 .08

Romanian sample

(N = 195) 370.92 150 .79 .12 .07

46


The improved results in all three groups (Italian, Portuguese, and Romanian)

obtained with the reconfigured model led us to conduct an analysis of confi-

gural invariance, that is, we verified if the two new factors are common to the

Portuguese, Italian, and Romanian samples and if they are loaded by the same

items. In this kind of analysis the samples were considered together (multiple

population analysis).

We then conducted a final analysis of metric invariance, to test the invariance

of the magnitude of the parameters of our model (the loadings of the items,

the variance errors, and the correlation between factors) within the three

groups. We began to test the model starting from the supposition that the ma-

gnitude of the loadings of the items on the two factors is equal in the three

groups. Subsequently, we tested the model by assigning an equal correlation

between the two factors in the Italian, Portuguese, and Romanian groups. La-

stly, we tested the model using the supposition that the variance errors of the

items are also equal in the three groups. The results of these analyses are pre-

sented in Table 4.

Table 4 – Values of fit indices to the reconfigured model after the analyses

of configural and metric invariance

Total sample (N = 617)


Analysis of configural

invariance 999.01 452 .80 .13 .04

Loadings of factors999.41 485 .81 .13 .04

Correlation between

factors 999.56 487 .81 .13 .04

Variance errors 1001.24 525 .82 .13 .04

The results obtained after the analyses of metric invariance did not point to

a good fit of the data to the introduced constraints (factor loadings, variance

errors, and correlation between factors). In particular, although items n. 5 and

n. 25, while testing the theoretical model, revealed loadings superior to .30 in

all the three groups, they contributed greatly to the size of the residual values

among the tested models.

4. Discussion and conclusions

The goal of this project was to conduct a comparative study of confirmatory

factor analyses of the Scale of Personal Conceptions of Intelligence (ECPI) –

47

constructed and validated for the Portuguese population by Faria (1990, 1996,

2003, 2006), for the Italian population by Pepi, Faria, and Alesi (2007), and

for the Romanian population by Ciochină and Faria (2006b) – in three cultural

contexts, Italian, Portuguese, and Romanian.

Differing from the scale of Dweck (Dweck, 1993, in Faria 1998), which had

only three items measuring the static conception, the final version of the scale

of Faria was composed of 26 items; this scale includes new aspects related to

the two personal conceptions of intelligence, such as the role of effort, different

ways of demonstrating one’s ability, and the avoidance of failure. Previous

studies conducted with exploratory factor analyses were able to identify a bi-

factor structure of he ECPI, comprising both an entity or static factor, and an

incremental or dynamic one, representing the two types of personal concep-

tions of intelligence theorized by Dweck (1999).

The results obtained in this study revealed a poor fit of the theoretical model

of the ECPI, moreover, in all three cultural groups there were 7 items, of which

6 illustrative of the static conception and 1 illustrative of the dynamic concep-

tion, which presented very low loadings on their original factors. The low loa-

dings, below .30, of the same 7 items in the three groups suggested to us that

it was necessary to test, in each group, a reconfigured model which eliminated

these items, and subsequently, to analyze – using the entire sample –, the con-

figural and metric invariance. In light of these analyses, although the data yiel-

ded indices of improved fit, they still were not yet entirely satisfactory. These

results thus suggested that the 7 eliminated items may be actually correlated

with other items requiring further investigation in the future.

Specifically, we eliminated from the static sub-scale in all three groups – Ita-

lian, Portuguese, and Romanian – items n. 1 (I have a certain amount of intel-

ligence and I cannot do much to change it), n. 10 (Good performance in a task

is a good way of showing others that I’m intelligent), n. 14 (Good preparation

for assignment I must do can be a good way to show others that I’m intelli-

gent), n. 19 (Getting high marks on an assignment demonstrates my intelli-

gence), and n. 20 (The mistakes I make should be forgotten because they

demonstrate that I’m not very intelligent). Except for item n. 1, the other 5

items measure personal conceptions of intelligence in their relation to success

and achievement of positive results (item n. 10 and n. 19), effort (item n. 14 and

item n. 16), and the value of one’s mistakes (item n. 20).

Of these items, only item n. 1 explicitly describes intelligence as a “quantity”

in a de-contextualized manner, without any reference to individual factors, for

example personal effort, or factors linked to the school context, for example

the difficulty of assignments.

Nevertheless, although this item clearly aims to capture the static nature of

48



intelligence, its formulation, unusual in spoken Italian, Portuguese and Roma-

nian – amount of intelligence –, may have led students to express lower agree-

ment with the item, unlike the other items also designed to measure intelligence

in a de-contextualized manner, but which were maintained in the scale (item

n. 15, I cannot increase my innate intelligence, item n. 18, If I’m not as intel-

ligent as I would like, I cannot do much to change this, item n. 22, I cannot

change my intelligence much).

The low loadings of the remaining items of the static factor may indicate pro-

blematic aspects related to the operationalization of the static personal concep-

tion of intelligence. For example, as far as items n. 10 and n. 19 are concerned,

it may be that succeeding or receiving high marks on an easy assignment is

not equivalent to succeeding when the assignment is difficult. Thus it is im-

probable that there will be univocal agreement with the idea that success and

high marks are indicators of intelligence. At the same time, succeeding or re-

ceiving high marks on a difficult task may be indeed a way to show others pro-

ofs of intelligence, without inferring that one has a static conception of

intelligence. As far as item n. 14 is concerned, the introductory wording “Good

preparation for an assignment ...” might induce the student to respond more

in terms of evaluating the effort applied to the preparation of an assignment,

rather than in terms of demonstrating intelligent behaviors to others. An alter-

native wording which more clearly indicates a performance objective related

to the static-entity pole could be “Good preparation of an assignment ...”, al-

though, once again, this would not necessarily mean that one has a static con-

ception of intelligence.

Moreover, the students in all three cultural contexts do not seem to perceive

effort, referred to in item n. 16, and errors, referred to in item n. 20, as indica-

tors of lesser competence. In the first case, it is possible that the value of effort

is linked to a possible social representation of effort in the school context as

an indicator of persistence and perseverance. Similarly, in the second case re-

garding errors, we can cite very common aphorisms in the three cultures such

as “to err is human” or “we learn from our mistakes” which may influence the

meaning students attach to the process of making mistakes.

Thus, for the future, it is necessary to reconsider the items which compose

the static sub-scale, in order to find better operationalizations of the static per-

sonal conceptions of intelligence.

We also eliminated item n. 4 from the dynamic sub-scale, What I learn by

doing my assignments is more important than the marks I receive; from a theore-

tical standpoint, the belief expressed in this item brings up a very complex issue

in the sphere of academic motivational psychology dealing with overcoming

dichotomous constructs.

49

If it is true that learning objectives implicate the desire to acquire new abilities

and master new tasks to increase one’s abilities in a long-term time frame, and

on the contrary, that performance objectives imply short-term comparative

evaluations and the achievement of positive assessments, it cannot be denied

that both categories are “normal and almost completely universal and both

contribute to success” (Dweck, 1999). In fact, in an ideal situation of school

performance, students would direct themselves towards learning and perfor-

mance goals simultaneously, tackling tasks with the goal of acquiring new abi-

lities and, at the same time, of achieving positive results and meaningful social

approval (Alesi & Pepi, 2008). In addition this theoretical aspect brings up

another crucial question concerning the difficulty of measurement of these va-

riables involving opposing orientations, such as incremental or entity concep-

tion, intrinsic or extrinsic motivation, learning or performance goal (Fulmer

& Frijters, 2009).

The existence of the above mentioned items may suggest the possibility that

they load on some third factor. However, they share essential characteristics

with other items that revealed satisfactory factor loadings and were retained

in the questionnaire, that is they were all conceived in order to measure con-

textual aspects attached to the perception of the static or dynamic nature of in-

telligence: success, failure and effort. Therefore it would be neither informative

nor justified to test a third factor of the ECPI since this third factor does not

comprise items different from those kept in the questionnaire.

Consequently, as we indicated above when analyzing the items which were

eliminated, the problem might reside either in their formulation (items n. 1 and

n. 14) or in their interpretable nature (items n. 4, n. 10, n. 16, n. 19 and n. 20).

As such, before proceeding to further factor analyses, our aim is to reconsider

the formulation of the items that proved to be problematical, and to achieve in

the clearest possible way an introduction to their aspects which refer to the re-

lations between success, failure, effort and intelligence.

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53


Abstract

Angelman syndrome (AS) is a neurodevelopmental disorder characterized

by a severe intellectual disability, severe expressive language deficits, ata-

xia and a specific behavior with easy excitability excitable personality and

an inappropriately happy predisposition. Phenotypical variations have

been described on the basis of the underlying genetic mechanism. Several

reports have suggested that individuals with AS resulting from UPD,

UBE3A mutations and imprinting mutations show a milder or atypical

phenotype than that observed in patients with a deletion of 15q11-q13 re-

gion. The purpose of this study is to describe cognitive and adaptive fun-

ctioning in a child with AS resulting from UBE3A gene mutation, and

especially the linguistic development, verbal and mimic-gestual, whose in-

ventory and use are greater than those reported in literature.

Keywords: Angelman syndrome, Language, Phenotype, Autism Spectrum

Disorders

Received: December 27, 2011, Revised February 10, 2012, Accepted: April 26, 2012.


1 Unit of Psychology, IRCCS Oasi Maria SS. Troina, Italy – E-mail: [email protected] Pedagogy Service IRCCS Oasi Maria SS Troina Italy – E-mail: [email protected] Unit of Psychology, IRCCS Oasi Maria SS. Troina, Italy – E-mail: [email protected] Unit of Neurology and Clinical Neurophysiopatology, IRCCS Oasi Maria SS Troina, Italy – E-mail:

[email protected] Unit of Pediatric and Medical Genetics, IRCCS Oasi Maria SS Troina Italy - E-mail: [email protected] Unit of Pediatric and Medical Genetics, IRCCS Oasi Maria SS Troina Italy - E-mail: [email protected] Unit of Pediatric and Medical Genetics, IRCCS Oasi Maria SS Troina Italy - E-mail: [email protected]

55


Communicative and cognitive functioning

in Angelman syndrome with

UBE3A mutation: a case report

Marinella Zingale1, Rosa Zuccarello2, Serafino Buono3,

Maurizio Elia4, Antonino Alberti5, Pinella Failla6

& Corrado Romano7

1. Introduction

Angelman syndrome (AS) is a neurodevelopmental disorder, occurring with

an estimated prevalence between 1:10,000 and 1:40,000 (Petersen, Brondum-

Nielsen, Hansen, & Wulff, 1995; Thomson, Glasson, & Bittles, 2006; Dan,

2009). It is characterized by severe Intellectual Disability (ID), profound spe-

ech impairment with absent or minimal use of speech, ataxia, epilepsy and a

characteristic behavioral profile including frequent and inappropriate laughter,

a happy predisposition, an easily excitable personality, hypermotoric behavior,

short attention span. Other common features include seizures, microcephaly,

peculiar EEG pattern, sleep disturbances, hypopigmentation, and strabismus

(Williams, Driscoll, & Dagli, 2010).

Four major molecular mechanisms are known to cause AS: maternally de-

rived interstitial deletion of 15q11-q13 chromosome region in 65-75% of

cases (Kaplan, Wharton, Elias, Mandell, Donlon, & Latt, 1987; Magenis,

Brown, Lacy, Budden, & Lafranchi, 1987; Cooke, Tolmie, Glencross,

Boyd, Clarke, Day et al., 1989; Pembrey, Fennel, Vad De Berghe, Fitchett,

Summers, Butler et al., 1989; Williams, Gray, Hendrickson, Stone, &

Cantu’, 1989; Fryns, Kleczkowska, De Cock, & Vendenberghe, 1990); mu-

tation in the UBE3A gene (10% of cases) (Kishino, Lalande, & Wagstaff,

1997; Matsuura, Sutcliffe, Fang, Galjard, Jiang, Benton et al., 1997); im-

printing center defects (3-5 % of cases) (Nicholls, Saitoh, & Horsthemke,

1997; Young-Hui, Ting-Fen, Bressler, & Beaudet, 1998); paternal unipa-

rental disomy (UPD) observed in 3-5 % of cases. In about 10% of patients

with a clinical diagnosis, no genetic defect is found.

In particular, the cognitive and neuro-behavioral phenotype is characte-

rized by:

• Severe psychomotor delay with onset around 6-12 months. Not repor-

ted, however, loss of acquired skills. Sitting autonomously is reached

between six months and three years (on the average this milestone is

achieved around 18 months), crawling becomes possible around 22

months, and standing without support around 7 years (Zori, Hendrick-

son, Woolven, Whidden, Gray, & Williams, 1992; Buntix, Hennekam,

Brouwer, Stroink, & Beuten, 1995). Lossie, Whitney, Amidon, Dong,

Chen, Theriaque et al. (2001) reported that 50% of AS patients with

deletion were non-ambulatory by 5 years of age, while 95% of those

with other molecular mechanisms were able to walk unassisted until 5

years of age. The study reported that children with UBE3A gene mutation

walked much earlier with mean ages in the 2.4 - 2.8 years range.

56

Life Span and Disability Zingale et al.

• Severely compromised verbal communication with minimal or ab-

sent use of words. Expressive language is limited to 6-8 words in

almost all individuals (Williams, Angelman, Clayton-Smith, Dri-

scoll, Hendrickson, Knoll et al., 1995). Lossie et al. (2001) did not

find significant differences regarding verbal language and its evo-

lution between patients with UBE3A mutation and those with AS

by other genetic mechanisms. The patients with UBE3A gene mu-

tations are statistically similar to the deletion patients in terms of

absence of speech (Paprocka, Jamroz, Szweed-Bialozyt, Jezela-

Stanek, Kopyta, & Marszal, 2007; Sartori, Anesi, Polli, Toldo, Ca-

sarin, Drigo et al., 2008).

A not homogeneous developmental profile with greater abilities in

the receptive component is reported (Clayton-Smith, 1993; Wil-

liams, Zori, Hendrickson, Stalker, Marum, Whidden et al., 1995;

Trillingsgaard & Ostergaad, 2004; Dan, 2009). Some children with

AS communicate using gestures and by pointing (Clayton-Smith,

1993; Alvares & Downing, 1998).

• Typical behavior, with frequent and excessive smile/laughter, inap-

propriately “happy” behavior, excitability often associated to “hand

flapping”, psychomotor instability and attention deficit (Pelc, Che-

ron, & Dan, 2008a). Children affected by AS seem very interested

in exploring the surroundings, and manifest curiosity and specific

interest for water. Hyperactivity is present in both sexes (Buntinx et

al., 1995; Williams et al., 2010). The attention span may be so short

as to interfere with social interactions.

• Intellectual Disability, often severe. Thompson and Bolton (2003)

sustain that in the majority of the patients with AS the cognitive im-

pairment is in the severe-profound range. Children with a milder

form of attention deficit may have a moderate ID (Williams et al.,

1995); a small percentage may obtain better results in some areas,

particularly in social abilities.

Several reports have suggested that individuals with AS resulting from

UPD, imprinting mutations and UBE3A gene mutations show a milder or

atypical phenotype than that observed in those with deletion, with a lower

incidence and later onset of seizures, less severe ataxia, earlier age of walking,

a greater ability to use some symbolic communication, or a lower frequency

of anomalies in the facial morphology (Bottani, Robinson, DeLozier-Blanchet,

Engel, Morris, Schmitt et al., 1994; Smith, Marks, Haan, Dixon, & Trent, 1997;

57


Smith, Robson, & Buchholz, 1998; Moncla, Malzac, Livet, Voelckel, Mancini,

Delaroziere et al., 1999; Fridman, Varela, Kok, Diament, & Koiffman, 2000).

Others, however, have argued that the supposed milder phenotype described

in cases without deletion is within the range observed in all molecular classes

of AS (Smith, Wiles, Haan, McGill, Wallace, Dixon et al., 1996; Prasad &

Wagstaff, 1997; Thompson & Bolton, 2003; Pelc et al., 2008).

2. Clinical case

2.1 Personal History

The child is a male, first born of two. He was born full term by cesarean

section following an uneventful pregnancy. His birth weight was 3530 gr. At

birth all vital signs were normal. He had physiological jaundice, and was breast

fed until four months of age. Poor growth rate and altered sleep-wake rhythm

were noticed around three months.

Development was globally delayed: he controlled his head at 6 months,

sat independently at 8 months and walked at 20 months. Vocalization and bab-

bles development were normal.

Bisyllable words were present at three years of age with further gradual

acquisition, up to 50 words functionally used, by age five.

Play activity was poorly organized, and inclined towards oral exploration.

Significant psychomotor instability was also present, in particular during the

first years of life, with gradual reduction especially in a structured learning

environment, following specific rehabilitation treatment.

Diagnostic investigations were started early (the first evaluation was done at

the age of seven months for a gastroesofageal reflux). Diagnosis of AS, ho-

wever, was formulated at the age of four years. The patient started rehabilita-

tion at the age of 13 months. An intensive habilitation treatment (speech

therapy and physiotherapy, psychomotor and psychoeducational treatment)

was carried out at the age of 36 months for a period of two months.

At the age of four, he underwent a short alternative communication treatment,

interrupted voluntarily by the parents. He started kindergarten regularly.

The patient has a "de novo" duplication in exon 15 of UBE3A gene which

produces a protein truncation at RNA analysis.

2.2 Psychometric evaluation and discussion

The child was assessed at the age of 70 months.

Neuropsychological functioning was assessed in a semi-structured environ-

ment with parents present. They were interviewed about their child’s develop-

58


mental milestones and behavioral features. The child was assessed with (I)

Leiter International Perfomance Scale (LIPS: Leiter, 1979), (II) Psychoeducatio-

nal Profile Revised (PEP-R: Schopler, Reichler, Bashford, Lansing, & Marcus,

1990), (III) Griffiths Mental Development Scales (GMDS: Griffiths, 1986), (IV)

Learning Accomplishment Profile (LAP: Sanford & Zelman, 1987) and (V) Vi-

neland Adaptive Behaviour Scale (VABS: Sparrow, Balla, & Cicchetti, 1984).

The “Test di valutazione del linguaggio” (TVL, Cianchetti & Sannio Fancello,

1997), was also used to assess language evaluation.

Considering that some studies have reported a consistently high rate of autistic

behavior in AS (Peters, Beaudet, Madduri, & Bacino, 2004) using Autism Dia-

gnostic Observation Schedule (ADOS: Lord, Rutter, DiLavore, & Risi, 1999),

the patient was also assessed with ADOS, module 1.

The LIPS evaluation showed a moderate ID (IQ = 43), according to ICD-10

criteria. It is to be underlined that the LIPS provides a culture-free, non verbal

mean of assessing general intelligence, not influenced by the patient’s expres-

sive speech impairment.

The developmental profile, based on the results of the Griffiths scale, cor-

responded to a mental age of 26.3 months.


Table 1 - Patient’s scores in GMDS

Scale A B C D E F Total

M. A. 21 30 23.5 27 30 26 26.3

S. Q. 30 42.85 33.57 38.57 42.85 37.14 37.49

Legend: A: locomotor scale; B: personal – social scale; C: hearing & speech scale; D: eye & hand co-

ordination scale; E: performance scale; F: practical reasoning scale; MA: mental age; SQ: sub-

quotient.

The patient’s score in GMDS showed a general developmental delay, as well

as an uneven profile of abilities across different domains. A detailed analysis

of the results showed a weakness in locomotor scale (MA = 21; SQ = 30), in

hearing and speech scale (M.A. = 23.5; S.Q. = 33.57) and in practical reasoning

scale (MA = 26; SQ = 37.14). The best results were obtained in the personal/social

scale (MA = 30; SQ = 42.85) and performance scale (MA = 30; SQ = 42.85).

The test results seem to reflect the typical clinical profile of children with AS

(Zori et al., 1992; Williams et al., 1995; Andersen, Rasmussen, & Stromme, 2001).

Although the scale does not evaluate specifically the communication skills,

59

it allows us to obtain some information. The related items in the two to three

years age group, requires that the child recognizes and denominates some ima-

ges of objects. Our patient was able to discriminate all images (33 out of 40),

but nominated correctly 12 only (shoe, cup, dog, ball, train, hat, fork, flower,

cat, star, child, fish), and reproduced the corresponding onomatopoeic sound

to the car (“bruum”). This data seem to differ from that reported in literature

as far as the number of words that a person with AS may acquire (Williams et

al., 1995; Lossie et al., 2001).

The PEP-R profile evaluation showed greater abilities in the perceptive and

fine-motor skills, whereas in other areas the performances appeared to be rather

homogeneous: Development Age (DA) = about 24 months, with the exception

of the cognitive verbal area where greater performance deficits are recorded

(DA = 18 months). These results, reported in Table 2, seem to confirm, once

again, the typical cognitive profile in children with AS.

PEP-R has been conceived by Schopler for the evaluation of children with

Autistic Spectrum Disordes (ASD). It is an inventory of behaviors and abilities

leading to the identification of discrepancies and idiosynchrasies throughout

the items of learning. The child’s profile does not fit the usual one of children

with ASD (bell-shaped curve with better performances in the fine-motor and

gross-motor skills, and eye-hand integration than the imitative, cognitive and

verbal abilities). Notwithstanding previous reports prompting an overlap bet-

ween AS and ASD, we have found differences, mainly regarding the cognitive

skills.


Table 2 – Patient’s score in PEP-R

Scale I P FM GM HE PC CV Total

Total 7 12 12 14 4 11 2 62

D. A. 22 48 38 30 24 24 18 24

Legend: I = Imitation; P = Perception; FM = Fine-motor Skill; GM = Gross-motor Skills; OM = Hand-

eye coordination; PC = Cognitive performance; CV = Cognitive-verbal performance; DA =

Developmental age.

The LAP has been designed for the assessment of psychomotor development

in young children. Table 3 lists the resuls of LAP test in our boy. Our child showed

30-month skills in the pre-wri-ting and autonomy, lower scores in the gross-motor

and fine-motor skills, and strengthenesses in the communication and social

abilities.

60


Furthermore, some items, out of the fine-motor and autonomy’s areas, were

compatible with to a 36-month psychomotor development.

Such scores are coherent with the other administered tests, highlighting the

weaknesses and strengths of people with AS, with the exception of the Lan-

guage area (MA = 36 months).

The results obtained from the VABS, reported in Table 4, indicated an overall

level of adaptive functioning equivalent to 19 months.

Table 3 – LAP test results

Areas Gross Motor Fine Motor Pre-writing Cognitive Language Self-Help Personal-Social

M. A. 21 27 30 30 36 30 36

Legend: MA: = mental age.

Table 4 – Patient’s scores in VABS

Subscale Equivalent Age

Communication

Receptive

Espressive

Written

Total

17

18

18

17

Daily Living Skills

Personal

Domestic

Community

Total

27

21

21

24

Socializzation

Interpersonal

Play and leisure time

Coping Skill

Total

21

19

20

19

Motor Skills

Gross

Fine

Total

18

24

20

No further evaluation of the communication’s skills was been possible, due

to the child’s severe impairments in this area, and the lack of adequate tools in

children with low functioning, attention deficits and hyperactivity. The admi-

nistration of the above-mentioned developmental scales, the TVL score, and

61

video-recorded observations in free situations, where the child has spoken

words spontaneously or after stimulus, lead to the total count of 54 spoken

words. All the words reported from the mother during the personal history, but

not heard by us, were omitted, for the lack of objective confirmation.

The patient’s ADOS scores, reported in Table 5, excluded the diagnosis of

Autism and ASD.

Although verbal communication was severely impaired, the patient was

observed to use a number of other means to communicate, including pointing,

gesturing, and directing facial expressions. Verbalizzation was also observed

to be well coordinated with eye contact.

The patient showed some appropriate pleasure in interaction with the exami-

ner, answered to joint attention, with delayed spontaneous onset.

He was observed to engage in some functional play with objects, but imagi-

native play was more limited.

Repetitive or stereotyped behaviors did not occur during the ADOS evaluation.


Table 5 – Patient’s score in ADOS

ADOS Autism spectrum cut-off Autism cut-off Patient’s scores

Communication (CO) 2 4 2

Reciprocal Social

Interaction (RSI) 4 7 3

RSI + CO 7 12 5

3. Conclusions

Data collected by us seem to confirm a less severe phenotype in patients

with UBE3A mutations (Bottani et al., 1994; Smith et al., 1997, 1998; Moncla

et al., 1999b; Fridman et al., 2000).

The age of acquisition of autonomous walking in our patient (20 months)

seems to confirm the report from Lossie et al., (2001) averaging at 2.8 years

the age of spontaneous walking in children with UBE3A mutations, earlier

than the children with AS due to deletions. Our results show a nonhomogene-

ous profile, peaking his weaknesses in the gross-motor, understanding, speech,

62

and practical reasoning areas, and his strengths in the personal/social, eye-

hand coordination, and performance areas.

Such results seem to overlap with those authors (Williams et al., 1995; An-

dersen et al., 2001) reporting on a peculiar profile in AS. Our child scores 25.8

months at the Mental Age (MA) evaluation following the GMDS developmen-

tal scale administration. This disagrees with that reported from Andersen et

al., (2001), who administered the same test to 20 children (age range 2-14

years, mean age 7 years) with AS, averaging their MA at 10 months, with only

two 7-year-old children peaking at 23 months. On the contrary, our results

overlap with those of Williams et al. (2010).

In our case, the global functioning is compatible with a moderate degree

of ID, while previous reports (Thompson & Bolton, 2003) usually have found

severe or profound degree of ID. However, other studies (Williams et al., 1995)

have pointed out that the less impaired the attention, the more probable is the

reaching of a moderate ID.

No differences regarding the development of communication among genetic

subgroups are evident in people with AS, according to Lossie et al., (2001).

Several reports (Clayton-Smith, 1993; Williams et al., 1995; Andersen et

al., 2001) maintain in the 6-8 words range the language portfolio of people

with AS. However, our patient speaks out 54 different words in a communica-

tive functional way. Currently, it is unclear why this boy has reached such per-

formance, and if the early stimulation has played a role in this achievement,

but this is conceivable. Only a longitudinal follow-up will tell about the global

functioning reached by this boy.

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Abstract

In the present paper we propose a standardization of the dynamic version

of the LOC test (Logical Operations and Conservation) elaborated by Via-

nello and Marin (1997). The dynamic assessment, compared with the tra-

ditional assessment, provides us with more information about the

development of logical thinking, because it also measures potential abili-

ties that can be perfected and will consolidate if the person is placed in

optimal learning conditions. The LOC-DV test, standardized on a sample

of 550 Italian children with typical development ages between 4 and 8

years (110 per age; 280 males and 270 females), results a highly reliable

instrument (r = .91; split-half). The high regression coefficient (.85) bet-

ween participants' scores and age guarantees a satisfactory progression

of the developmental score parallel to the growth of age. The comparison

between males and females performance reveals the absence of any signifi-

cant differences. We present also the conversion tables of scores in mental

age, deviation IQ and ratio IQ, giving reasons for the opportunity to prefer,

in the age of development, at least at a clinical level, the utilization of the

mental age and of IQ ratio rather than the deviation IQ.

Received: March 26, 2012, Revised: April 15, 2012, Accepted: May 12, 2012.


1 Department of Development and Socialization Psychology, University of Padua. E-mail: renzo.vianello

@unipd.it2 Department of Development and Socialization Psychology, University of Padua. E-mail: silvia.lanfranchi

@unipd.it3 Department of Development and Socialization Psychology, University of Padua. E-mail: : francescapulina@li-

bero.it4 Department of Development and Socialization Psychology, University of Padua. E-mail: sara.bidinost87

@gmail.com

69


Italian standardization of the dynamic

version of the Logical Operations and

Conservation test (LOC-DV)

Renzo Vianello1, Silvia Lanfranchi2, Francesca Pulina3,& Sara Bidinost4

We advise the use of the LOC-DV test above all when the performances at

the traditional tests result inferior than the potentiality, particularly in cases

of socio-cultural disadvantages, intellective disabilities, and borderline co-

gnitive functioning with negative interferences at environmental and moti-

vational levels.

Keywords: Dynamic testing, Cognitive development, Logical thinking,

Piagetian Tests

1. Introduction

The aim of the present paper is to propose a first attempt at formulating a

standardization of the dynamic version of the Logical Operations and Conser-

vation test (LOC-DV), an instrument created by Vianello and Marin (1997)

for the evaluation of intelligence, and in particular for the level of development

of logical thinking, which is considered a crucial step, even if not an exclusive

one, in intelligence development5.

The basic tasks of the test are the same used by Piaget, together with Szemin-

ska and Inhelder (Piaget & Szeminska, 1941; Piaget & Inhelder, 1959, 1962).

In some cases they have been simplified: a development test requires diffi-

culty-graduated tasks. For example, the classic task of seriation must be exe-

cuted with 10 houses in series and the insertion of another 9 houses. The LOC

test presents also seriation with 5+4 small houses (in two dimensions, paper

made) and 5+4 rods. However, some concepts grounding the building of the

test only partially agree with the piagetian theory, and others result even in contrast

with it. We would like to highlight the crucial ones.

- The passage from intuitive thinking to concrete operational thinking (to

use the Piagetian terminology) is slower and patchier than that hypothe-

sized by Piaget.

- A fundamental role was played by:

- familiarity with the material;

- verbal and visuospatial short term memory capacity;

- complexity of the mental actions required at working memory level

(central executive).

5 Several collaborators contributed to the data collections. Special thanks to Maddalena Baroni, Annalisa

Catzeddu, Ilaria Ferrarese, Gloria Gelain, Fernanda Pappalardo, Sara Roman and Elena Savoia.

70

Life Span and Disability Vianello R. et al.

- The development of logical thinking is more crucial in the adolescent pe-

riod of growth between 4 and 8 years old, rather than be fore or after.

The theoretical background encompasses not only references to Piagetian

theory but also to the post-Piagetian (for example Case, 1985) and cognitivist

references (for example Baddeley, 1986 and Sternberg, 1988).

The dynamic version of the test intends to assess more than the base test

(which is conceived to avoid rigidity, in the spirit of the Piagetian approach,

and is conceived to enhance the participant’s complete comprehension, spirit

of initiative and activity of the participant; see also Inhelder, Sinclair, & Bovet,

1974) not only in the achieved abilities, but also in the abilities in construction,

which are the ones that can be perfected at the moment in which the tasks are

faced, thanks to the mediation of the proposer. The main theoretical references

are Vygotskij (see his definition of Zone of Potential Development, also said

Zone of Proximal Development; Vygotskij, 1935), and the synthesis about the

dynamic evaluation elaborated by Sternberg and Grigorenko (2002).

Over many years of research, the LOC test has demonstrated to be a valid

and reliable instrument (Vianello & Marin, 1997). The new version's aim is to

provide more information than the previous version, not only about the level of

development reached by the child, but also about his potential for development.

The importance of a “dynamic” assessment of intelligence, able to catch

the hidden abilities of individuals, is supported by many authors in literature. First

of all, by Vygotskij, who underlines the importance of cooperation and interaction

with more expert individuals in order to promote learning and development.

Many authors, particularly in the last decades, starting from Vygotskij’s

conceptualizations, expressed the necessity to bring some changes into the

field of assessment and gave their contribution to the development of dynamic

testing (Sternberg & Grigorenko, 2002). This is in large part due to the changes

in the concept and definition of intelligence and its meaning that is now con-

ceived also as the capacity to utilize information and apply it to different con-

texts (Resnik, 1976; Campione, Brown, & Bryant, 1985). So intelligence is

not a stable attribute, but an ability in constant development, influenced by the

life contexts of the individual.

Sternberg and Grigorenko (2002) claim the importance of juxtaposing the

dynamic tests to static testing, because the dynamic tests aim to assess also

the learning potentials, which represent the hidden abilities. The authors be-

lieve that individuals' abilities are the result of a continuous process of acqui-

sition and consolidation of abilities required for a certain area of demonstrated

performance (developing expertise).

Also Feuerstein (see Feuerstein, Rand, & Hoffman, 1979; Feuerstein, Rand,

Hoffman, & Miller, 1980; Feuerstein, Rand, Jensen, Kaniel, & Tzuriel, 1987)

71

Italian standardization of the dynamic version of the LOC-DV

expressed the necessity of a dynamic evaluation, claiming that the abilities

reached by the individual at a certain moment in his process of development

are not fixed and unchangeable, but that intelligence is rather an auto-regula-

tion dynamic process, exposed to the influence of the external environment.

The contributions to dynamic testing are more in number than the ones that

we have quoted. Many other authors have proposed new and different approa-

ches to dynamic assessment (Carlson & Wiedl, 1978, 1979, 1980; Budoff,

1987a, 1987b; Campione & Brown, 1987; Swanson, 1995a, 1995b; Guthke,

1992; Guthke & Wiedl, 1996; Guthke & Beckman, 2000; ecc.).

The dynamic version of the LOC test originates in this context. This version,

acting in particular on the Zone of Proximal Development (Vygotskij, 1935),

is aimed at investigating the development and learning potentialities in the

child. Differently from the static version of the test, the dynamic alternative

provides the presentation of aids and more instructions to the participant, fol-

lowing a modality called cake format (Sternberg & Grigorenko, 2002): for

each item there are some possible suggestions for the child in case that he/she

shows perplexity and difficulty in the resolution of the task. The aim of the

“aids” is to stimulate the reasoning of the child in order to facilitate the com-

prehension of the task, however without giving him/her the solution. In this

way the interaction between the experimenter and the child becomes interac-

tive and bidirectional.

Therefore, the score obtained becomes indicative also of the potential abilities

of the child, of what he/she will acquire and consolidate, if well supported and

stimulated. We think that information about the potential of development is

always fundamental, but in particular for those children who are at risk to be

at being undervalued because of disabilities (sensory, physical, intellectual or

other), borderline cognitive functioning, learning disabilities, socio-cultural

disadvantages, communicative or social difficulties; for instance, the subject’s

belonging to another mother tongue or culture.

At an introductory level we also claim the importance of another important

element. We think that every test can be more or less static or dynamic. We

prefer considering in terms of a continuum in which the most static test (charac-

terized by maximum equality in the presentation of the instructions, as happens

through the computer, and by any adaptation in the participant's reactions) is

located at one extreme, while the most dynamic test (characterized by maxi-

mum adaptation to the participant's actions, and maximum help) is located in

the other extreme. Proposing a test personally is a social relationship, and for

that reason it has always something of a dynamic characteristic. The critical

point concerns the choice of how much flexibility can be permitted.

72



Our dynamic version of the LOC test is sensitive to preserving a prudent

flexibility while totally ensuring an interrelated comparison between the indi-

vidual's performances and the ones of the normative group. Our “aids” have

been standardized and presented attempting to avoid any “suggested” answer.

Vice versa we have looked for “provoked” answers, as they are called by Piaget

(1926), that represent the child's original own behaviour, even if triggered by

our proposed “situation”; as Vygotskij would say, the typical behaviour in the

child’s zone of proximal development.

We acted prudently in order to ensure the normative comparison. However,

we don't exclude, in the future, another version of the LOC test in an advanced

dynamic version (of course with its new standardization), more proximal to

the dynamic extreme of the continuum that we referred to before. In any case,

we won't ever give in to the temptation of supplying aids that would only be

passively absorbed by the child, because this could result in only a temporary

and superficial effect on the child's learning process.

2. Characteristics of the LOC-DV test

As LOC, LOC-DV consists of 24 items, regarding the areas of Logical Ope-

rations and Conservation.

From a structural point of view, what mainly distinguishes the test from the

previous version are the tasks relating to the area of conservation. In some

cases, in the past, it seemed that the instructions were not interpreted correctly

by the children.

For each task 1 point is assigned in case of success and 0 points in case of

failure, so the minimum score was 0 and the maximum was 24.

For each area quite difficult tasks are provided together with easier ones; tasks

are inspired by traditional Piagetian tasks, but by changing the contents in order

to highlight different levels in the acquisition of logical thinking.

The new version of LOC is characterized by presence of “aids” for each

task, which have the purpose of guiding the child’s reasoning toward the reso-

lution of the tasks, in order to assess not only the actual level of development,

but also the potential development of the child.

However, it seems important to emphasize that also in the traditional LOC

some cues were provided, but only for specific tasks. For this reason, the pre-

vious test was collocated at a not extreme level in the static-dynamic conti-

nuum that we mentioned in the introduction.

Table 1, 2, 3, 4 (see Appendix) show each tasks for both “static” and “dy-

namic” tests, in order to facilitate demonstration of the comparisons.

73


3. Means of the scores at each age, table of conversion of

score in mental age, reliability, deviation and ratio IQ,

differences between males and females.

We currently have data from several research projects carried out in recent

years in different regions of Italy that concerns the administration of LOC-DV

to 550 Italian children aged from 4;0 to 8;11, evenly divided in five age groups

(4, 5, 6, 7 and 8 years old).

The table 5 (Appendix) shows results distinguished according to the age. At

age 4 children already gain a high score. This result was expected as some

tasks are very easy even for younger children and have above all an introductive

function, in order to favor the understanding of the following tasks.

Between age 4 and 7 years there is a strong increase in performances, while

between 7 and 8 years differences are much smaller.

In all age groups the mean scores are higher than those obtained through

the administration of the test in the static version (see Vianello & Marin, 1997,

p. 41). The biggest difference is present at 6 years of age (means 19.05 vs

15.35). This finding could suggest a greater efficacy of the dynamic test in the

middle age group, or when the child's abilities are developing, but not yet fully

developed and acquired (see Inhelder, Sinclair & Bovet, 1974; Doise &

Mugny, 1981).

In order to verify the relationship between age and scores in LOC-DV, we

carried out on our data a regression analysis. Through linear regression we ob-

tained the following equation:

Mental age = 32.47 + 2.69 x LOC-DV score

This equation allows us to express the LOC-DV score in terms of mental age.

Specifically, starting from a mental age of about 32 months, each success at

LOC-DV tasks increases mental age of 2.69 months.

The linear regression analysis showed a high coefficient (r = .85; p < .001).

It indicates that there is a good relationship between increasing age and LOC-

DV score.

Using scores obtained by regression equation and considering the means of

the scores, it was possible to build a table of conversion of scores in mental

age (Appendix, table 6), which is crucial for understanding and interpreting

the performance. Since some tasks are very easy, we take the score into account

only if it is equal to or greater than 7.

The table shows that LOC-DV is too difficult for those who totalize from 1 to

74


6 points and it’s too easy for whoever reaches 22 points or more.

LOC-DV is particularly adequate for children with mental age from 4 to 7

years and 6 months.

Comparing the present table with the table shown in the LOC manual (Vianello

& Marin, 1997, p. 43), we can see that the dynamic version anticipates the age

of resolution of tasks (on mean about 6 months). In other words, LOC-DV al-

lows the child to achieve levels of performance of children of about 6 months

older assessed with the original test.

As LOC test, LOC-DV has demonstrated good psychometric properties.

As regards reliability, by using the split-half procedure, we obtained a coeffi-

cient of .91, p < .001 (24 tasks). It is higher than that of the static version, that

is .87, p < .001. Regarding test validity, it is possible to state that it does not

deviate from the validity of the original version of the test (Vianello & Marin,

1997, pp. 48-53); indeed the correlation between the two versions (LOC and

LOC-DV) is very high (.91, p < .001).

The analysis of variance showed no difference between male (280) and female

(270) performance (F(1,548)

= 1.64, p = .202). This result confirms results ob-

tained about static version of LOC.

The tables 7 and 8 (Appendix) present both ratio IQs and deviation IQs,

derived from age scores analysis.

As will be easy to see, ratio and deviation IQs are not equivalent and provide

different information.

Deviation IQ is a measure of how far one may deviate from the mean IQ; in

other word, it compares people of the same age.

Ratio IQ shows the relationship between a child or boy’s real performances (Men-

tal Age) and what is typical of his chronological age. Depending on the aims,

either one can give a better result.

The deviation IQ is certainly more useful for people older than 18 and for

comparisons within typical development. This isn’t our case.

We think that ratio IQ may be more meaningful with lower than 18 years old

people, and, above all, with individuals with atypical development (in parti-

cular, with intellective disabilities and borderline cognitive functioning). Con-

cerning this we must point out the tendency, very widespread and often

erroneous in believing that - also in cases of people with atypical development

- the deviation IQ can be used as if it were an IQ ratio. For example, if we

have a eighteen - years - old boy with Down Syndrome, who has a deviation

IQ of 50, this information doesn’t permit us to say that “it is as if he was 4

years old of mental age”. On the basis of our tables, we can say that this affir-

mation is not true.

In the table of the deviation IQs for a 8-years-old child, a deviation IQ of <55

75

corresponds to exceeded 16 tasks. In the table of the ratio IQs for an 8 - years

- old child, if the tasks solved are 16, we have a ratio IQ of 75. The difference

is huge. This means that a deviation IQ of 50 doesn’t correspond to a mental

age of 48 months (4 years), but of 72 months (6 years).

Unfortunately a deviation IQ of <55 provides poor information about our 8

years old child with Down Syndrome, or rather that, compared to 100 peers,

it shows the worst performance (among the 2 or 3 worst out of 1000 peers). In

fact <55 means a position in more than three standard deviations from the

mean, and under three standard deviations from the mean there is less of one

individual out of 100.

We believe that the use of the IQ ratio may be, in clinical developmental

psychology, more informative and less misleading than the deviation IQ.

We invite the reader to make a comparison between the two tables of IQ.

He/she can find considerable differences so as to strengthen the belief that de-

viation and ratio IQs aren’t equivalent, and that the practice should be aban-

doned that uses the deviation IQs as if they were ratio IQs.

The ratio IQ has been calculated for a population sample of children with

chronological ages from 4 to 13 years. Such a choice is related to the possible

use of the test for young people with atypical development. With increasing

age a precise attribution of IQ appears poorly informative. For this reason in

the table below the 55 points of IQ, the precise values were not included. For

ages above 14 years, also with the solution of 21 tasks, the ratio IQ is less than

55. In these cases, the mental age gives much more useful information.

Similarly, we considered appropriate not to specify the scores above 145. As

stated above, it is also valid with regard to the deviation IQs.

4. Discussion

Each test measures “its” intelligence. For that reason David Wechsler offered

evidence to the fact that his tests measured not only intelligence, but also other

cognitive non-intellectual aspects. At the same time, however, Wechsler ascer-

tained the presence of good communicative, verbal, and social adaptation abi-

lity.

The LOC test, both in his original and dynamic versions, evaluates a particular

aspect of intelligence: the development of logical thinking. This is an important

aspect in the ages between 4 and 8 years, but probably less important in the

first four years (in which sensory-motor intelligence and symbolic thinking seem

to be crucial), and then in the adult age (in which there seem to be many compe-

tences and abilities that contribute to the definition of intelligence; and the relative

importance of logical thinking decreases).

76



With the passing of time, as claims Sternberg (1981, 1984), the “contents” (or

better the factors) of intelligence change.

As anticipated, the perceptive and motor factors are crucial in the first years

of life. From 2 to 4 years of age, the symbolic factors acquire much importance.

From 4 years of age, the reasoning ability, without logical mistakes, tends to reveal

its importance. The LOC test presumes to evaluate this aspect.

So we think that one of the merits of the LOC test is due to the evaluation of

a crucial factor of intelligence in the period between 4 and 8 years of life.

Other merits are of a psychometric order: solid theoretical foundations, good

reliability, high regression coefficient between test scores and chronological age

(which allows the table of conversion of scores in mental age).

In our opinion, the absence of differences between males and females is

also a positive result. It seems to us that this could be interpreted in the sense

that social stereotypes have not yet acted significantly at this level, and that

the test itself is able to evaluate basic abilities.

The LOC test doesn’t want to substitute other tests, some offering more

informative data and whose utilization is already professionally consolidated.

In normal practice, the LOC test should be used with appropriately comple-

mentary aims. However, we think that the fact that the correlation coefficient

between LOC and Wechsler Scales results over .60 (Vianello & Marin, 1997)

is a positive aspect, most of all if we consider that the administration of the

LOC test requires on average less than 30 minutes, and that the verbal com-

ponent is much reduced.

The dynamic version of the LOC test seems promising. We hope that future

research will highlight its utility in situations where there is risk that static tests

can lead some persons to lower performances than their actual potential showed.

We are talking about children with socio-cultural disadvantages, intellective

inhibition, relational difficulties. We are also talking about children and adole-

scents with intellective disabilities or borderline cognitive functioning.

In our opinion, there are clear limits to the LOC test.

First of all, the fact that in persons with typical intellective development

the test cannot be applied at a longitudinal level (apart from the period, in each

case very important, from the subject’s attendance in the last 2 years of infancy

school to the first two years of attendance in primary school), that means also

before and after 4-8 years of age. The most evident way to highlight this limit is

comparing the LOC test with the Wechsler Scales, which “accompany” the sub-

jects from infancy school age through a complete lifetime to old age and senility.

Another limit is the relative scarcity of research data: there are just about a

few tens (of these just a few are diffused at an international level, and just in-

directly, when the use of the test is quoted) and of course not about a hundred,

as the most famous intelligence tests.77

The version in Italian language was till now the only one currently available.

Consequently, there was only limited distribution.

We know that the LOC test is widely used in Norway, but in this case there is

not yet a standardization as in Italy. We hope that the distribution of the test in

the English language through the Journal that hosts this article will favour stan-

dardization in other languages.

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80


APPENDIX

81



SERIATION

LOC LOC-DV

Material Instructions and procedure Material Instructions and procedure

1 5 houses with bases of

cm 4, 6, 8, 10 and 12.

The psychologist places the 5 houses on

the table at random and says: “Place

these houses in order from the largest to

the smallest” making at the same time a

gesture with the hand tracing an oblique

segment in the air from up to down. It is

very important to be sure that the child

has understood the instructions. If the

psychologist thinks it necessary, he/she

can ask the subject to point at the largest

house, and then the largest one of the re-

mainder, suggesting him to place the se-

cond next to the first; then he/she can ask

him to go on saying: “Place the other

houses too from the largest to the smal-

lest”. The psychologist can help only in

this task (considered as passed, like the

next ones, even if the child places the

houses in order from the smallest to the

largest). What is important is that he/she

arranges the houses in a series.

The same as in the

static version.

The aids are already present

in the static instructions.

2 The 5 houses of the

first task, plus another

4 houses with bases of

cm 5, 7, 9 and 11.

If the child does not pass task n.1, the

psychologist helps him until he succeeds

(however the task can’t be considered as

passed).

Then the psychologist goes on placing

the other four houses in their right places

(pointing at the spaces between the hou-

ses) in order to form again a scale from

the largest to the smallest.

If the subject has made the previous se-

riation placing the 5 houses close to one

another, before formulating the instruc-

tions of this task it is necessary to sepa-

rate them in order to have enough room

to insert the others: on this occasion the

psychologist can say: “Let’s make some

room, as we have to place other houses”.

If the child starts reorganizing the series

already made, the psychologist stops

him/her and says: “Don’t do it all over

again, place the new houses without mo-

ving the others”. After this further in-

struction the task is passed only if the

child inserts the houses correctly without

reorganizing the previous series. In other

words he/she must not make a new seria-

tion of 9 elements, but he/she has to in-

sert the other 4 elements in a series of 5.

This is also valid for tasks 4 and 6.

The same as in the

static version.

If the child is wrong by in-

serting the first or the se-

cond house, the pychologist

helps him placing the house

in its right place and saying

him: “This is the right place,

because so this house (poin-

ting at the house inserted) is

smallest then this (pointing

at the previous house), but it

is largest then this (pointing

at the following house).

Now houses are in order

from the largest to the smal-

lest (making at the same

time a gesture with the hand

tracing an oblique segment

in the air from up to down)”.

If the child inserts correctly

the two or three houses that

remain, the task can be con-

sidered as passed. If the

child inserts correctly the

first two houses, but he/she

is wrong the third (and the,

consequently, the fourth),

the psychologist doesn’t

must help the child. At that

point, also say “Think it

over” would be not easing,

but suggestive, because

there are only two possibili-

ties and the child may be

change just for suggestion,

without be aware of why it’s

opportune to change house.

82

Table 1 – Description of the tasks regarding the seriation area. Presentation of material and instructions

regarding each task of both static and dynamic versions.


SERIATION

LOC LOC-DV


3 5 1 × 1 cm square

sectioned green rods

of cm 10, 12, 14, 16,

18.

The procedure is the same as in the

task 1. The psychologist says: “Pla-

ces these rods in order from the lon-

gest to the shortest”, making at the

same time a gesture with the hand

tracing an oblique segment in the hair

from up to down. If the child tries to

place them upright, the psychologist

adds: “Lay them down on the table,

in order from the longest to the shor-

test”.

The same as in the

static version.

If the child is wrong the task, the

psychologist, as in previous task,

telling him/her how to do, but

considering the task as not passed.

4 The 5 rods of the pre-

vious task, plus other

4 1 × 1 cm square

sectioned green rods

of cm 11, 13, 15, 17.

This task is proposed only if the pre-

vious task has been passed. The pro-

cedure is the same as in task 2. The

psychologist says: “Put these rods in

their right places (pointing at the spa-

ces between the rods) in order to

form a scale from the longest to the

shortest”.

The same as in the

static version.

The same instructions as in task 2.

5 10 1×1 cm square

sectioned blue rods of

cm 10, 11, 12, 13, 14,

15, 16, 17, 18, 19

The procedure is the same as in task

3.

The same as in the

static version.

If the child didn’t pass either the

task 2 or the task 4, it’s advisable

to pass on the task 7. If the psy-

chologist proposes this task,

he/she can help the child saying

him that he/she must be patient

and that he/she must go on step by

step, comparing well the rods.

Further, if the child compares the

first rods, without “leaning them on

a field basic line”, the psychologist

can help him/her putting the first

two or three rods on this field line.

If the child succeeded the task 2,

but not the task 4, It’s advisable

don’t insist. Indeed if he/she is

clearly hard put, it’s better attend,

saying: “This task is for kids older

than you” or “This task is very dif-

ficult; it’s better to do another one”

and go on directly at the task 7.

6 10 1×1 cm square


cm 10, 11, 12, 13, 14,

15, 16, 17, 18, 19

plus 9 1x1 square


cm 10,5, 11,5, 12,5,

13,5, 14,5, 15,5, 16,5,

17,5, 18,5.

The procedure is the same as in task

4.

The same as in the

static version.

This task is proposed only if the

tasks 4 and 5 has been passed. The

procedure is the same as in the

tasks 2 and 4.

83

NUMERATIONLOC LOC-DV


Table 2 – Description of the tasks regarding the numeration area. Presentation of material and instruc-

tions regarding each task of both static and dynamic versions.

7 5 bottles and 7 glasses. The psychologist places a row of 5

bottles on the table and, apart, a

group of 7 glasses. The instruction

formula is: “Place a glass in front

of each bottle”.

The same as in the

static version.

No aids are provided.

8 5 bottles and 5 glasses. If the child doesn’t pass the pre-

vious task, the psychologist helps

him until he/she succeeds (however

the task can’t be considered as pas-

sed). Then the psychologist remo-

ves the two surplus glasses from the

table and says: “Count the glasses;

how many are there?”. The psycho-

logist goes on only if the child says

the right number, placing a cardbo-

ard sheet in front of the bottles, in

order to hide them completely, and

saying: “Can you tell me how many

bottles there are behind this

sheet?”.

The same as in the

static version.

If the child counts (up) to 5, but

after he/she cannot say how

many are the bottles, the psy-

chologist can pick up, for a mo-

ment, the cardboard sheet

saying: “You can see only a lit-

tle bit”, but for a minimum time

that cannot allow the child to

count the bottles, but only to

note that for each glass there is

a bottle.

9 5 bottles and 5 glasses. Even if the child hasn’t passed the

previous task, the psychologist goes

on taking the cardboard sheet away,

grouping the glasses and saying:

“Are there more bottles or more

glasses, or are there the same num-

ber?”.

The same as in the

static version.

If the child keeps silence, du-

bious, the psychologist can say:

“Look, we do it again” and the

psychologist puts the glasses in

front of the bottles and then

he/she groups the glasses again.

10 10 red counters and 12

blue counters.

The psychologist places the 10 red

counters in a row on the table and

groups the 12 blue counters toge-

ther. The procedure is the same as

in task 7: the psychologist asks the

child to place a blue counter in front

of each red counter. If the child doe-

sn’t succeed the task is not passed.

If, on the contrary, he succeeds, the

psychologist removes the two sur-

plus counters and says: “How many

blue counters are there?”. If the

child can’t count them, the task is

not passed. If, on the contrary,

he/she can count them, the proce-

dure is the same as in task 8: the

psychologist places a cardboard

sheet over the red counters, in order

to hide them completely and asks:

“Can you tell me how many red

counters there are?”

The same as in the

static verion.

The procedure is the same as in

task 8.

84



11 10 red counters and 10

blue counters.

The procedure is the same as in task 9.

The psychologist says: “Are there more

red counters or more blue counters, or

is the number the same?”.

The same as in the

static version.

The procedure is the same as in

task 9.

12 8 cardboard cutout boys

(9, 11, 13, 15, 17, 19, 21,

23 cm high) and 8 car-

dboard cutout walking

sticks (5,4; 6,6; 7,8; 9,0;

10,2; 11,4; 12,6; 13,8 cm

high).

The psychologist places the cutout

boys and sticks on the table and asks

the child to arrange the 8 cutout boys

in a series. If he/she succeeds the psy-

chologist says: “Place in front of each

boy his own stick, from the highest to

the shortest”. If the child carries it out

correctly the psychologist goes on

“closing” the series of sticks (that is

drawing them nearer to each other, wi-

thout undoing the series) and saying

(pointing at the third stick from the

left): “Which boy does this stick belong

to?”.

The same as in the

static version.

Since it is important that the

third stick be far from third cu-

tout boy (for example if all

sticks are grouped, moving

them far to the right compared

to the row of the boys); if the

child’s wrong or, at the request

for identify the owner of third

stick, he/she doesn’t point the

correct cardboard cutout boy,

the psychologist asks him/her:

“Which boy does this stick be-

long to (pointing at the first

stick)? And this (pointing at the

last stick)? And this (pointing at

the third stick)?”.

85

NUMERATIONLOC LOC-DV



Table 3 – Description of the tasks regarding the classification area. Presentation of material and

instructions regarding each task of both static and dynamic versions.

CLASSIFICATIONLOC LOC-DV


13 8 cardboard geometrical figures

which differ in shape, color and

dimension: an 8 cm diameter red

circle, a 4 cm diameter red circle,

an 8 cm diameter blue circle, a 4

cm diameter blue circle, an 8×8

cm red square, a 4×4 cm red

square, an 8×8 cm blue square, a

4×4 cm blue square.

The psychologist places the 8 figures on

the table at random saying: “Group the fi-

gures that are similar, and have some-

thing alike”. If the child makes a figural

collection or makes some distinctions

(for example grouping the red squares

and the blue squares), the task can be

considered as passed and the psycholo-

gist goes on with the next task.

The same as in

the static ver-

sion.

No aids are provided.

14 8 cardboard geometrical figures

which differ in shape, color and

dimension: an 8 cm diameter red

circle, a 4 cm diameter red circle,

an 8 cm diameter blue circle, a 4

cm diameter blue circle, an 8×8

cm red square, a 4×4 cm red

square, an 8×8 cm blue square, a

4×4 cm blue square.

If the child, following the previous in-

structions has already classified the ma-

terial into two groups according to color,

shape or dimension, this task can also be

considered as passed. If, on the contrary,

this fact hasn’t happened, the psycholo-

gist says (making an explicative gesture

with the hands in order to locate two dif-

ferent places, one on the left and the other

on the right, where the child has to place

the elements of the two groups): “Now

you have to make two groups with the fi-

gures that have something alike: place

one group here and the other one here

(making a gesture with the hands just as

before). In each group you must place the

figures that have something alike”.

If during the execution of this task or of

the previous one the child hasn’t made

two groups, but four (for example grou-

ping the two red circles, the two red squa-

res, the two blue circles, and the two blue

squares) task 13 can be considered as pas-

sed, but in task 14 it is necessary to spe-

cify: “Not four groups, but only two. You

have to make only two groups with the fi-

gures. In each group you must place the

figures that have something alike”.

The same as in

the static ve-

rion.

If the child cannot make two

groups, the psychologist

takes a cardboard figure and

asks him/her to describe it.

If the child says “red” (or

blue) or “circle” (or square),

the psychologist repeats

what said: “Well, this is red

(or what child said) and we

place it here. Now we place

also the other figures, a few

here and a few there”.

86

15 The same as in the tasks 13 and

14.

If the child passes the previous task, the

psychologist picks up the figures, mixes

them up and says: “Now you should make

two groups again, but in a different way

from before (brief pause); in each group

you put the figures that have something

alike, but it must not be the same thing as

before”.

The same as in

the static ve-

rion.

If the child seems confused,

or he/she can’t (do it), the

psychologist can add some-

thing at the standard in-

structions, as in the task 14,

namely he/she can ask to

describe an element (a car-

dboard geometrical figure),

saying something like:

“This is red, but it is also...”.

Then the psychologist con-

tinues what child told (for

example “circle”) saying:

“Well, this is a circle and we

place it here...now place

also the other figures...a few

here and a few there...”.


87

16 The same as in the tasks 13, 14

and 15.

If the child passes task 15, the psycholo-

gist picks up the figures, mixes them up

and says: “Now you should make two

groups again, but in yet another way

(brief pause); in a different way from the

two previous time”.

The same as in

the static version.

If the child didn’t pass the

task 14, the psychologist

doesn’t help him/her (when

the task is too difficult, hel-

ping the child could be

counterproductive at level

of the motivation for the

continuation of the test).

If the child passed task 15,

the procedure is the same as

in task 15, or rather the psy-

chologist invites him/her to

describe the figures, saying

something as: “This is red

and it is also a circle (or

what the child said), but is

it also...?”. If the child doe-

sn’t say “small” (or big) it’s

better not insist for not risk

the suggestion.

17 Three 4 cm diameter circles

(green, blue and yellow), a 4×6

cm red rectangle, a 4×4 cm red

square and 4×4 cm red isosceles

triangle.

The psychologist arranges the three cir-

cles in a vertical position, one under the

other, and the other three elements in a

horizontal position, one beside the other,

in order to form a right angle whose ver-

tex is missing. Then he/she asks: “Can

you tell me what figure, which is not pre-

sent, is missing here? (pointing at the

empty place at the intersection between

the column of the circles and the row of

the polygons). What figures can fit in

with this group (pointing at the column)

but also with this one (pointing at the

row)?”.

If the child answers correctly that what

is missing is the red circle, the following

task can be also considered as passed.

A cardboard sheet

containing 6 geo-

metrical figures:

three circles

(green, blue and

yellow) in a verti-

cal position, one

under the other,

and other three

red elements (a

triangle, a rectan-

gle and a square)

in a horizontal

position, one be-

side the other.

The elements are

placed in order to

form a right angle

whose vertex is

missing.

Since this is, normally, one

of the most difficult task of

the test, it can take in order

to provide an aid only if

he/she were succeeded

most of the previous tasks,

and in particular the task 15.

If the child answer wron-

gly, the psychologist can

help him/her by guiding

him/her in a description of

the elements, one by one,

starting from the red figu-

res, and then proceeding

with the circles, giving

time to the child in order to

describe up to say “red” (in

the first three elements) and

“circle” (for the other three).

It’s important not insist in

a way demotivating.

18 The same as in task 17 plus a car-

dboard sheet containing 6 geo-

metrical figures arranged in two

parallel columns. On the left co-

lumn, from top to bottom, there

are: a 4×2 cm red rhombus, a 4

cm diameter brown circle and a

6×4 cm blue rectangle. On the

right column there are from top

to bottom: a 4 cm diameter violet

circle, a 4 cm diameter red circle

and a 4 cm diameter orange cir-

cle.

If the child does not pass the previous

task, the psychologist shows him/her the

cardboard sheet with the 8 geometrical

figures and asks him: “Now, can you tell

me which of these figures (pointing at the

cardboard sheet) can fit in with this

group (pointing at the three circles arran-

ged on the table) and with this one too

(pointing at the three polygons arranged

on the table)?”.

The same as in

the previous task

plus a cardboard

sheet containing

a red rhombus

(at the bottom

left), a violet cir-

cle (at the top

left), a brown

circle (at the bot-

tom right) and a

red circle (at the

top right).

The psychologist can help

the child by guiding

him/her in a description of

the elements, one by one.

CLASSIFICATIONLOC LOC-DV



19 Two transparent glasses

of equal size and a third

transparent glass higher

and narrower than the

others. A bottle to pour

the water.

The psychologist places on the

table the two glasses of equal size

(A and B) containing the same

quantity of water and makes sure

that the two glasses contain the

same quantity of waters also from

the child's point of view, asking

him/her: "Here (pointing at A) and

here (pointing at B) is there the

same quantity of water, or is there

more here (pointing at A) or here

(pointing at B)?". If the child doe-

sn't recognize the equality, the psy-

chologist adds or takes away water

until he/she agrees that in the two

glasses there is the same quantity

of water. At this point the psycho-

logist proceeds with the real task.

He/she pours the contents of B into

the third glass (C) and asks: "Water

that there is here (pointing at C) is

it the same that there was here

(pointing at B), or is another?”.

Two black strings

of the same length.

The psychologist places the

two strings on the table and

talks with the child in order to

agree that they make believe

that the strings are sweets and

to be sure that the child agrees

that the length is the same

(placing the strings on the

table, as two segments of line).

After this the psychologist

modifies one of the string

rolling up it, while the other

stays as a segment if line.

The psychologist asks the

children to do the same on

more than one way (for

example as a spiral too nar-

row, or a little more large)

and, above all, seeing that the

string be place before as a

segment of line, and then as

a spiral. At this point, the

psychologist asks: “We can

suppose that you eat this

string (pointing at the string

rolled up) and I eat this

string (pointing at the string

as segment of line). One of us

eat more or we eat the same

quantity of sweet?”.

88

CONSERVATIONLOC LOC-DV


Table 4 – Description of the tasks regarding the conservation area. Presentation of material and

instructions regarding each task of both static and dynamic versions.

20 The same as in task 19. Even if the child hasn't passed the

previous task, the psychologist

goes on saying: "Now I want to

pour into this glass (pointing at B)

as much water as there was before,

like this one (pointing at A). To do

this is the water that is here (poin-

ting at C) all right or do I have to

take some away or do I have to put

some more in?".

The same as in

task 19.

The psychologist places the

two strings of the previous

task. While one remains rol-

led up the other is folded like

a V (very narrow). Then the

psychologist asks child to do

the same on more than one

way (for example as a “V”

too narrow, or a “V” too

large), and above all seeing

that the string be place before

as a segment of line, and then

as a “V”. Then the psycholo-

gist asks: “We can suppose

that you eat this string (poin-

ting at the string rolled up)

and I eat this string (pointing

at the string folded like a

“V”). One of us eat more or

we eat the same quantity of

sweet?”.


21 The same as in the tasks

19 and 20.

Even if the child hasn’t passed the


goes on asking: "Here and here

(pointing at A and C) is there the

same quantity of water or is there

more in this glass (pointing at A) or

in this one (pointing at C)?".

Two transparent

glasses of equal

size and a third

transparent glass

higher and narro-

wer than the

others. A bottle to

pour the water.

If the child gives the wrong

answer, the psychologist asks

him/her: “Can you point what

will be the level of the water

in this glass (B), if I pour it

from this (C)?”. If the child

points at the same level of A,

the psychologist says

him/her: “I’m not quite sure.

If I pour the water that is here

(pointing at C) into this glass

(pointing at B), is the quan-

tity of water as in this (poin-

ting at A), or not?”.

22 Plasticine or other mal-

leable material to form

two about 7-8 cm dia-

meter balls.

The psychologist places on the

table two equal balls (A and B) of

malleable material and says: "What

do you call this?". If the child can't

answer, the psychologist says:

"Let's call it paste (or another term

used locally). All right?". If, on the

contrary, the child uses another

term, the psychologist has to use it

instead of the term "paste" here

mentioned. Then the psychologist

asks: "Here and here (pointing at A

and B) are there two equal balls or

is there more paste here (pointing

at A) or here (pointing at b)?" If the

child doesn't recognize the equality,

the psychologist adds or takes away

paste until he/she agrees that the

balls have the same quantity of

paste. At this point the psychologist

proceeds with the real task. The

psychologist shapes one of the balls

into a "sausage" (C) and asks: "The

paste that there is here (pointing at

C) is it the same that there was in

the previous ball, or is it another?”.

The same as in

task 21.

Before to ask the child if into

the two glasses (A and C)

there is the same quantity of

water, the psychologist can

help him/her by asking to

point up to where the water

arrived, in the glass B, before

being poured. It’s important

not influence the child.

This aid can be useful be-

cause it’s a further invitation

to think about.

23 The same as in task 22. Even if the child hasn't passed the


goes on saying: "Now I want to

make a ball like the former one, the

same as this one (pointing at A). To

do this is the paste that is here

(pointing at C) all right or do I

have to take some away or do I

have to add some more?".

Plasticine or other

malleable material

to form two about

7-8 cm diameter

balls.

If the child gives the wrong

answer, the psychologist asks

him/her: “Can you point how

was this (pointing at the “sau-

sage”)?”. If the child says

that it was as “A”, the psy-

chologist asks: “I’m not quite

sure. If I shape this (pointing

at the “sausage”) like a ball,

does it become like this (poin-

ting at A) or different?”.

If the child answers “diffe-

rent”, the psychologist asks:

“Greater or smaller?”, in

order to be sure that he/she is

considering the quantity and

not the shape.

89



24 The same as in the tasks

22 and 23.

Even if the child hasn't passed the


goes on saying: “Here (pointing at

A) and here (pointing at C) is there

the same quantity of paste or is

there more here (pointing at A) or

here (pointing at C)?".

The same as in

task 23.

Before to ask if the “sausage”

(C) and the ball (A) contain

the same or a different quan-

tity of plasticine, the psycho-

logist can help the child

asking him/her how were the

two balls, before that one be

shaped. This aid can be useful

because it’s a further invita-

tion to think about.




Table 5 – Means and standard deviations at different ages of children 4 to

8 years old in the LOC-DV and in the LOC tests.

LOC-DV LOC

Age Mean St. Dev. Mean St. Dev.

4 years 9.30 2.83 8.18 2.28

5 years 13.40 3.58 11.44 3.15

6 years 19.05 2.43 15.35 3.35

7 years 20.85 1.99 19.59 2.45

8 years 21.63 1.74 20.41 2.96

Table 6 – Table of conversion of score in mental age.

Score Mental Age

7 4;00

8 4;03

9 4;06

10 4;09

11 5;00

12 5;03

13 5;06

14 5;08

15 5;10

16 6;0017 6;02

18 6;04

19 6;06

20 7;00

21 7;06

22-23-24 > 8;00

90


Tab

le 7

– L

OC

-DV

: ra

tio I

Q.

Sco

re

Age

78

910

1112

13

14

15

16

17

18

19

20

21

4;0

04;0

34;0

64;0

95;0

05;0

35;0

65;0

85;1

06;0

06;0

26;0

46;0

67;0

07;0

6

4;0

0100

106

113

119

125

131

138

142

>145

>145

>145

>145

>145

>145

>145

4;0

198

104

110

116

122

129

135

139

143

>145

>145

>145

>145

>145

>145

4;0

296

102

108

114

120

126

132

136

140

144

>145

>145

>145

>145

>145

4;0

394

100

106

112

118

124

129

133

137

141

145

>145

>145

>145

>145

4;0

492

98

104

110

115

121

127

131

135

138

142

>145

>145

>145

>145

4;0

591

96

102

108

113

119

125

128

132

136

140

143

>145

>145

>145

4;0

689

94

100

106

111

117

122

126

130

133

137

141

144

>145

>145

4;0

787

93

98

104

109

115

120

124

127

131

135

138

142

>145

>145

4;0

886

91

96

102

107

113

118

121

125

129

132

136

139

>145

>145

4;0

984

89

95

100

105

111

116

119

123

126

130

133

137

>145

>145

4;1

083

88

93

98

103

109

114

117

121

124

128

131

134

145

>145

4;1

181

86

92

97

102

107

112

115

119

122

125

129

132

142

>145

5;0

080

85

90

95

100

105

110

113

117

120

123

127

130

140

>145

5;0

179

84

89

93

98

103

108

111

115

118

121

125

128

138

>145

5;0

277

82

87

92

97

102

106

110

113

116

119

123

126

135

145

5;0

376

81

86

90

95

100

105

108

111

114

117

121

124

133

143

5;0

475

80

84

89

94

98

103

106

109

113

116

119

122

131

141

5;0

574

78

83

88

92

97

102

105

108

111

114

117

120

129

138

5;0

673

77

82

86

91

95

100

103

106

109

112

115

118

127

136

5;0

772

76

81

85

90

94

99

101

104

107

110

113

116

125

134

5;0

871

75

79

84

88

93

97

100

103

106

109

112

115

124

132

5;0

970

74

78

83

87

91

96

99

101

104

107

110

113

122

130

5;1

069

73

77

81

86

90

94

97

100

103

106

109

111

120

129

5;1

168

72

76

80

85

89

93

96

99

101

104

107

110

118

127

6;0

067

71

75

79

83

88

92

94

97

100

103

106

108

117

125

6;0

166

70

74

78

82

86

90

93

96

99

101

104

107

115

123

6;0

265

69

73

77

81

85

89

92

95

97

100

103

105

114

122

6;0

364

68

72

76

80

84

88

91

93

96

99

101

104

112

120

6;0

463

67

71

75

79

83

87

89

92

95

97

100

103

111

118

6;0

562

66

70

74

78

82

86

88

91

94

96

99

101

109

117

6;0

662

65

69

73

77

81

85

87

90

92

95

97

100

108

115

6;0

761

65

68

72

76

80

84

86

89

91

94

96

99

106

114

6;0

860

64

68

71

75

79

83

85

88

90

93

95

98

105

113

91

Sco

re

Age

78

910

1112

13

14

15

16

17

18

19

20

21

4;0

04;0

34;0

64;0

95;0

05;0

35;0

65;0

85;1

06;0

06;0

26;0

46;0

67;0

07;0

6

6;0

959

63

67

70

74

78

81

84

86

89

91

94

96

104

111

6;1

059

62

66

70

73

77

80

83

85

88

90

93

95

102

110

6;1

158

61

65

69

72

76

80

82

84

87

89

92

94

101

108

7;0

057

61

64

68

71

75

79

81

83

86

88

90

93

100

107

7;0

156

60

64

67

71

74

78

80

82

85

87

89

92

99

106

7;0

256

59

63

66

70

73

77

79

81

84

86

88

91

98

105

7;0

355

59

62

66

69

72

76

78

80

83

85

87

90

97

103

7;0

455

58

61

65

68

72

75

77

80

82

84

86

89

95

102

7;0

5<

55

57

61

64

67

71

74

76

79

81

83

85

88

94

101

7;0

6<

55

57

60

63

67

70

73

76

78

80

82

84

87

93

100

7;0

7<

55

56

59

63

66

69

73

75

77

79

81

84

86

92

99

7;0

8<

55

55

59

62

65

68

72

74

76

78

80

83

85

91

98

7;0

9<

55

55

58

61

65

68

71

73

75

77

80

82

84

90

97

7;1

0<

55

<55

57

61

64

67

70

72

74

77

79

81

83

89

96

7;1

1<

55

<55

57

60

63

66

69

72

74

76

78

80

82

88

95

8;0

0<

55

<55

56

59

63

66

69

71

73

75

77

79

81

88

94

8;0

1<

55

<55

56

59

62

65

68

70

72

74

76

78

80

87

93

8;0

2<

55

<55

55

58

61

64

67

69

71

73

76

78

80

86

92

8;0

3<

55

<55

55

58

61

64

67

69

71

73

75

77

79

85

91

8;0

4<

55

<55

<55

57

60

63

66

68

70

72

74

76

78

84

90

8;0

5<

55

<55

<55

56

59

62

65

67

69

71

73

75

77

83

89

8;0

6<

55

<55

<55

56

59

62

65

67

69

71

73

75

76

82

88

8;0

7<

55

<55

<55

55

58

61

64

66

68

70

72

74

76

82

87

8;0

8<

55

<55

<55

55

58

61

63

65

67

69

71

73

75

81

87

8;0

9<

55

<55

<55

<55

57

60

63

65

67

69

70

72

74

80

86

8;1

0<

55

<55

<55

<55

57

59

62

64

66

68

70

72

74

79

85

8;1

1<

55

<55

<55

<55

56

59

62

64

65

67

69

71

73

79

84

9;0

0<

55

<55

<55

<55

56

58

61

63

65

67

69

70

72

78

83

9;0

1<

55

<55

<55

<55

55

58

61

62

64

66

68

70

72

77

83

9;0

2<

55

<55

<55

<55

55

57

60

62

64

65

67

69

71

76

82

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re

Age

78

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13

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15

16

17

18

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20

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64;0

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94

Sco

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Age

78

910

111

213

14

15

16

17

18

19

20

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087

96

103

110

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75

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73

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72

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92

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100

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5


Tab

le 8

– L

OC

-DV

: dev

iati

on I

Qs

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re

Age

78

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1112

13

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15

16

17

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75

81

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79

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Abstract

Recent research in inclusion-oriented schools in the United States has

begun to document how a variety of demographic and service delivery va-

riables (e.g., percent of students identified as disabled, percent of time in

regular class, personnel utilization) can hinder or support innovations in

curriculum, instruction, and social/behavioral interventions. After provi-

ding some contextual information about Italian and American special edu-

cation and describing key findings from the US research exploring service

delivery variables in inclusion-oriented schools, the current study presents

school demographic and service delivery data collected in 16 schools in

five regions of Italy. The findings indicate substantial variation across scho-

ols on a variety of variables. We pose a series of questions prompted by the

data and invite Italian researchers and practitioners to offer their analysis,

interpretation, and insights about the meaning and potential implications

of these data for improving inclusive educational opportunities for students

with disabilities.

Keywords: Disabilities, Inclusion, Personnel service delivery, Italian

Schools

Received: March 04, 2012, Accepted: May 10, 2012.


1 University of Vermont. E-mail: Michael.Giangreco@uvm2 St. Michael's College. E-mail: [email protected] University of Vermont: E-mail: [email protected].

97


Demographic and personnel service delivery

data: implications for including students

with disabilities in Italian schools

Michael F. Giangreco1, Mary Beth Doyle2 & Jesse C. Suter3

1. Demographic and personnel service delivery data: implications

for including students with disabilities in Italian schools

International research on educating students with disabilities and other special

educational needs has been dominated by studies evaluating a wide variety of

curricular, instructional, and social/behavioral interventions to identify evi-

dence-based practices meant to facilitate positive academic, functional and so-

cial outcomes. There has been substantially less attention devoted to school

and classroom service delivery practices that allow such interventions to be

effectively implemented under typical conditions, rather than conditions that

rely on extra or atypical supports from researchers in school or nonschool set-

tings (e.g., clinics). While some literature (Gersten, Keating, Yovanoff, & Har-

niss, 2001; Russ, Chiang, Rylance, & Bongers, 2001) has addressed important

special education service delivery practices (e.g., special educator caseload is-

sues), much of the available research has not: (a) focused on the unique con-

texts presented by inclusion-oriented schools, (b) explored a wide array of

service delivery parameters, (c) examined the interrelationships among service

delivery variables within and across schools, or (d) identified the service de-

livery practices under which successful interventions have been utilized.

Inattention to service delivery issues has contributed to an ongoing research-

to-practice gap (McLeskey & Billingsly, 2008), which may explain why scho-

ols sometimes do not use interventions reported to be effective. Some recom-

mended interventions simply have not been sufficiently researched under real

world conditions nor have many investigations sought to determine what types

of service delivery configurations (e.g., staffing patterns, class size/configu-

rations) would allow them to be implemented in schools. Although intervention

research remains vital to continued development of the field, without corre-

spondingly effective service delivery configurations, even the most advanta-

geous innovations in curriculum, instruction, and social/behavioral

interventions will not fully realize their intended impact or sustain it over time.

The primary purposes of this paper are to: (a) provide a brief overview of

key similarities and differences between the Italian and American special education

context to assist the reader in understanding the service delivery data presented,

(b) describe key findings from a recent line of research exploring service delivery

parameters in inclusion-oriented schools in the United States; (c) present school

demographic data representing a subset of these parameters collected in 16 Italian

schools, and (d) pose a series of questions about what implications these data may

have for improving practices in public schools in Italy. In reference to this final

purpose, we invite Italian researchers and practitioners who are knowledgeable

about inclusion-oriented education for students with disabilities and other special

98

Life Span and Disability Giangreco M. F. / Doyle M. B. / Suter J. S.

educational needs to comment on the findings and offer their perspectives on

their potential meaning and implications. We hope this opens a dialogue to fa-

cilitate international collaboration and extend our understanding about the roles

service delivery data play in improving practices in inclusion-oriented schools

in Italy, the US, and potentially other countries.

2. Similarities and differences between Italian and American

Special Education

In the 1960s there was societal unrest in both Italy and the US; one manifesta-

tion was a groundswell of public concern and about segregated mental health

and disability-related services. Grassroots efforts by parents, self-advocates,

and their allies led to the deinstitutionalization movement as well as the pas-

sage of national education legislation in the 1970s designed to increase access

to public schooling and regular class placement for students with the full range

of disabilities. At that time, some school-aged children with more severe disa-

bilities did not attend school and for those who did, special schools and classes

dominated the educational landscape. In both countries only about 20% of stu-

dents with disabilities attended regular classes (Vianello, 1996; Cornoldi, Ter-

reni, Scruggs, & Mastropieri, 1998; US Department of Education, 2010b).

Although the initial legislation in both countries provided a legal basis favoring

regular class placement for students with disabilities, both also left open the

possibility to educate students with severe disabilities in more segregated en-

vironments (Taylor, 1988; D’Alessio, 2011).

Over the past 40 years the two countries have taken different paths toward

pursuing their common legislative intent, namely to provide appropriate edu-

cation and more inclusive opportunities for students with disabilities. The Ita-

lian approach began with rapid initial placement of students with disabilities

and other special educational needs in regular classes followed by incremental

legislative and implementation adjustments over a period of many years. Pas-

sage of Law 118 in 1971 led to widespread national closure of nearly all the

country's special education schools and special education classes in favor of

regular class placements for students with disabilities and other special edu-

cational needs (Sidoli, 2008; Canevaro & de Anna, 2010). In the early years

of this transition (1971-1977) concerns were voiced that the rapid insertion of

students with disabilities in regular education classes was implemented without

sufficient supports in place (Vitello, 1991; D'Alessio, 2011). Proponents of re-

gular class placement contended that this rapid transition was essential because

without the actual presence of students with disabilities there would be insufficient

99

Service delivery for inclusion in Italian schools

impetus for change; they argued if Italy waited for attitudes to be more positive

and all supports to be in place this substantial shift toward regular class place-

ment might not have occurred and therefore the educational and civil rights of

students with disabilities would have been unnecessarily compromised and

delayed (Berrigan, 1988; Canevaro & de Anna, 2010).

Incremental adjustments progressed with a series of legislative efforts (e.g.,

Law 517/1977; Law 104/1992; Law 185/2006) providing frameworks and me-

chanisms (e.g., assessment, availability of support teachers, caseload limits,

class size parameters, functional dynamic profile, individual education plan)

designed to support the national policy of school inclusion referred to as inte-

grazione scolastica. Once this shift to regular class placement was initiated, it

advanced from about 20% in the early 1970s to consistent reports of approxi-

mately 98% of its students with disabilities placed in general education classes

by the 1990s (Cornoldi et al., 1998; Palladino, Cornoldi, Vianello, Scruggs,

& Mastropieri, 1999).

In the US, education is primarily a state, rather than national, responsibility.

Prior to the passage of federal legislation in 1975, the Education for All Han-

dicapped Children Act (later reauthorized as IDEA, the Individuals with Di-

sabilities Education Act), many states already had compulsory public education

laws for all or most students with disabilities. So when the national law was

passed ensuring access to a free, appropriate, public education for all children

and youth with disabilities ages 3 through 21, most students with mild disabi-

lities were already receiving public education as were some students with more

severe disabilities in some states, albeit most commonly in publicly operated

special schools or special classes. The new federal law initially had the most

immediate impact on students with severe or low incidence disabilities who

were not previously afforded access to public schooling in some states.

These students had been either at home without access to public schooling or

were educated in schools associated with private non-profit or charitable or-

ganizations such as the ARC (formerly the Association for Retarded Citizens),

Easter Seals, United Cerebral Palsy Association, and others, many of which were

created or operated by parents who had children with disabilities.

In contrast to Italy, the US approach to including students with disabilities in

regular classes has been incremental. On average, the rate of primary regular

class placement (meaning 80% or more of their school day) of students with

disabilities, has progressed only about 1% per year and consistently has main-

tained this slow upward trend over four decades. For example, from 1990 to

2006, the rate of primary regular class placement rose from approximately

33% to 54% with substantial variation among states still existing in 2006 (e.g.,

Virginia 10%; North Dakota, 78%; Giangreco, Hurley, & Suter, 2009).

100



By 2010 approximately 61% of students with disabilities nationally were in-

cluded in regular classes as their primary educational placement (US Depar-

tment of Education, 2010a). There continues to be wide variation in placement

based on type of disability. For example, whereas 61% of students with specific

learning disabilities and 86% with speech language impairments are in regular

classes as their primary educational placement, the rates are only 16% and

13% respectively for students with intellectual disabilities and multiple disa-

bilities (National Center for Educational Statistics, 2011b).

It is important to recognize that the respective regular class placement rates

in Italy (98%) and the US (61%) are not exactly comparable, nor are they quite

as far apart as they may seem at first glance. The US percentage represents

only students with disabilities who are in regular class at least 80% of the time.

When US students who attend regular class 40% to 79% of the time are added,

the US total rises to 81%; when those in regular class less than 40% of the

time are added in, the US total for regular class placement reaches 95% (US

Department of Education, 2010a). What remains unreported in Italy is the ac-

tual percent of time students with disabilities spend in the regular classes where

they are assigned. Some Italian students with disabilities are pulled out of class

for individual or small group instruction, for behavioral reasons, or to receive

services (e.g., physical therapy) away from school during the school day. What

can be said with some confidence is that approximately 98% of students with

disabilities in Italy attend regular class for all, most, or some portion of the

school day, but the average percentage of time in versus time out of the regular

classroom is unknown. Unless or until countries adopt similar definitions and

reporting standards it will remain challenging to compare the nuances of re-

gular class placement statistics, leaving only the most segregated options (e.g.,

percent in special education schools) as potential points of accurate comparison.

Another difference confounding the comparison of regular class placement

rates is the respective ways the countries define disability and count students

as disabled.

Historically Italy certifies approximately 2% of its students as disabled

(Palladino et al., 1999; Meijer & DeJager, 2001), whereas the US identifies

over 13% of students enrolled in school as disabled and eligible to receive ser-

vices under the IDEA (National Center for Educational Statistics, 2011a). Ap-

proximately 60% of American students with disabilities are identified as either

learning disabled or speech language impaired, while in Italy most students

with specific learning disabilities are not considered “disabled” and are not

eligible for services under Italy's national disability-related education laws. In

Italy students with learning disabilities are a regular education responsibility

and their needs are addressed under other legislation.

101


For example, recently Law 170/2010 was designed to ensure that general edu-

cation teachers provide necessary accommodations for children such as those

with dyslexia, dysgraphia, and dyscalculia. As a result of these socially con-

structed differences in disability definitions and special educational needs la-

beling, there are students with specific learning disabilities in US, some of

whom spend the majority of their school day in special education classes, who

if they lived in Italy would not be certified as “disabled” under Italian educa-

tion law and would in regular class full-time. Similarly, the 98% of students

with disabilities that Italy reports including in regular class all, most, or some

of the time, are primarily students with more significant intellectual, physical, sen-

sory or multiple disabilities that are included at markedly lower rates in the US.

There are undoubtedly many other differences between how Italy and the US

provide educational supports for students with disabilities. Further, it is vital

to recognize that educational placement data, even when favorable, do not pro-

vide any information about the quality of educational services being offered

in either country and therefore should not be considered alone as a proxy for

appropriate or quality education.

3. Research exploring service delivery in US

inclusion-oriented schools

Over the past several years our team at the University of Vermont has initiated

a line of research exploring school service delivery variables and practices

with a particular focus on inclusion-oriented schools. Key findings about

school service delivery have been gleaned from national US data sources

(Giangreco, Hurley, & Suter, 2009), studies conducted in inclusion-oriented

schools in Vermont (Giangreco & Broer, 2005; Giangreco, Smith, & Pinckney,

2006; Suter & Giangreco, 2009; Giangreco, Suter, & Hurley, 2011), and in in-

clusion-oriented schools across six states (i.e., California, Connecticut, Kansas,

New Hampshire, Vermont, Wisconsin; Giangreco & Broer, 2007; Giangreco,

Broer, & Suter, 2011).

Viewed together, these studies depict a wide range of service delivery practices

from state to state and school to school. In the sample of inclusion-oriented

schools, with primary regular class placement rates around 94% and class sizes

generally in the low 20s (making them similar on these dimensions to many

schools in Italy), a subset of findings are especially relevant. A key difference

between Italy and the US is that, on average, these US inclusion-oriented scho-

ols identify approximately 14% of their students as disabled (i.e., eligible for

special education under the IDEA federal legislation) and another 16% as having

102


some other kind of special need making them at-risk for educational problems

or failure (e.g., substantial delays in literacy or numeracy); so the combined total

of students with disabilities and some other special need was approximately 30%

of a school's population.

These schools, on average, employed three to four times as many special edu-

cation paraprofessionals (hereafter referred to as assistants) as special education

teachers; in some cases many more. This is consistent with national trends in-

dicating that US states that have higher regular class placement rates tend to

employ proportionally more assistants. Regardless of how many assistants a

school had per the number of students with disabilities (e.g., 1:3, 1:6, 1:10),

school staff consistently reported feeling either just adequately staffed or un-

derstaffed; in part this suggests that there is no "right" ratio and that often what

"feels right" is based on what school personnel are accustomed to.

In many schools, assigning more assistants has become the primary mecha-

nism to support students with disabilities in regular classes with escalating re-

quests for more. Although there are many skilled assistants who make valuable

contributions, the research literature in the US and internationally has identi-

fied concerns that assistants have unclear and potentially inappropriate instruc-

tional roles, tend to be inadequately trained and supervised, and may actually

pose obstacles to providing quality inclusive education and appropriate instruc-

tional supports (Giangreco, Doyle, & Suter, in press). A substantial percentage

of assistants in these US schools, estimates ranging from 30% to over 50%, are

assigned in a one-to-one format, a problematic approach because it can contri-

bute to a wide variety of inadvertent detrimental effects (Giangreco, 2010).

The caseloads and practices of special education teachers in inclusion-oriented

schools raise serious concerns about their opportunities to utilize the skills they

have gained through their teacher preparation studies and ongoing professional

development. The average number of students with disabilities served per spe-

cial education teacher ranged from approximately 11 to nearly 17. Many spe-

cial educators also had additional support responsibilities for other students

with special needs (e.g., 3 to 6 students with delays in literacy and/or math)

who did not qualify as disabled under US law. These special educators often

have their time spread across several classrooms and grade levels, while on

average they attempt to supervise three to four assistants. They tend to spend

less time (under 40%) in instruction than both regular education teachers and

assistants, and also provide a substantial amount of their instructional time

(approximately 75%) with students with disabilities outside the regular cla-

ssroom. Under these conditions they are only able to offer about 2% of their time

per assistant to provide training and supervision (Suter & Giangreco, 2009; Gian-

greco, Suter, & Hurley, 2011).

103

In addition to caseload numbers, one variable has been shown to have a

significant relationship to the self-efficacy ratings of special education teachers

in inclusion-oriented schools, namely the ratio of special education teachers

in FTE (full-time equivalents) to total school enrollment; this is referred to as

special educator school density (Suter & Giangreco, 2009; Giangreco, Suter,

& Hurley, 2011). The range of special educator school density ranged widely,

from 1:38 to 1:224, averaging around the 1:94 in Vermont schools and 1:111

in the six states listed earlier (Giangreco, Broer, & Suter, 2011). Two important

findings have been discovered about special educator school density in the

sample of inclusion-oriented schools studied. First, special educator school

density shows an inverse correlational relationship with the percentage of stu-

dents identified as disabled; as the percentage of students labeled disabled in

a school rises, the special educator school density ratio decreases.

This explains why schools where special educators have approximately the

same average caseload size can have substantially different special educator

school density ratios. For example, the data set includes two schools that both

have an average special educator caseload size of 11.5, but School A has a spe-

cial educator school density ratio of 1:131 while School B's ratio is 1:69. This

occurs because School A identifies 8.8% of its students as disabled, while

School B identifies 18.5% as disabled. Interestingly, these two schools had a

very similar combined percentage of students with disabilities or other special

need, 26% and 28% respectively. Funding mechanisms that provide special

educator resources to schools based on the number of students identified as di-

sabled create an incentive to label students as disabled. Ironically, in these sy-

stems where resources are linked to disability labeling, schools that are able to

appropriately serve students with special needs by strengthening their school-

wide supports and avoiding disability labeling often lose resources. Undersco-

ring the importance of this loss of resources, higher special educator school

density has been correlated with lower self-efficacy ratings by special educa-

tors (Giangreco, Suter, & Hurley, 2011). A potential solution to this problem

is to provide resources to schools based on total school enrollment numbers

along with potential adjustments for likely contributors to student learning

challenges (e.g., economic disadvantage, non-dominant language use). In other

words, in schools that are inclusion-oriented, where it is known that all or ne-

arly all their students with disabilities or special needs are expected to be in

the regular classroom, we could consider basing availability of personnel re-

sources on total enrollment rather than percentage identified as disabled.

In the present study, we collected data in Italian schools on a subset of the

demographic variables from the US studies. The aforementioned US studies in-

cluded three types of quantitative, descriptive data from: (a) a school demographic

104



questionnaire, (b) a special educator questionnaire about their caseload and

work responsibilities, and (c) a special educator questionnaire about their stu-

dents who received ongoing one-to-one support from assistants (e.g., student

characteristics, service provision). This initial study of Italian schools was li-

mited exclusively to a subset of the school demographic variables that: (a) see-

mingly spanned cross-cultural boundaries, (b) were identified as important

variables in the US studies, and (c) could reasonably be collected during mee-

tings with school leaders.

4. Method

4.1 Design

This study employed a descriptive, quantitative design. Data were collected

between October and November 2011 from a convenient, purposeful, sample

of inclusion-oriented schools. This was one component of a larger set of sab-

batical activities conducted by the first and second authors during a three-month

stay in Italy to learn about “integrazione scolastica” (i.e. school inclusion).

4.2 Settings

The 16 public schools that participated in this study were located in five re-

gions of Italy (e.g., Lazio, Lombardia, Puglia, Veneto, Sicilia). The schools

were identified with the assistance of university colleagues and regional edu-

cation ministry administrators who served as liaisons between the researchers

and the schools. As shown in Table 1, the schools spanned all grade levels in-

cluding five elementary schools (“Infanzia” – “Primaria”), four

elementary/middle schools (“Infanzia” – “Primaria” – “Secondaria I”), and

seven high schools (“Secondaria II”).

Total student enrollment in these schools ranged from 231 to 1,560 (M = 752.8,

SD = 339.0). On average, approximately 14% of enrolled students were from

cultural/ethnic minorities (non-Italians) and approximately 12% were learning

Italian as a second language. Estimates regarding the percentage of students

in these schools who were considered economically disadvantaged ranged

from approximately 1% to over 20% (M = 9.4%, SD = 6.8). Average class size

ranged from 19 to 27 (M = 23.3, SD = 2.7).

4.3 Participants

One or more school leaders in each site, typically the principal and/or assistant

principal, supplied the school demographic data presented in this study, often

with the assistance of other school personnel (e.g., office staff, special educa-

tion teachers).

105


Although not reflected in the demographic data, other individuals we encoun-

tered during our travels further informed the questions we pose in the discus-

sion section of this paper. These individuals included: (a) 81 students with

certified disabilities we observed in the 16 schools and 2 agency sites we vi-

sited, (b) approximately 860 nondisabled students and 91 school personnel

(e.g., classroom teachers, special educators, assistants) in 37 regular classro-

oms where 52 of the 81 students with disabilities were observed, and (c) con-

versations with 89 individuals associated with the schools (e.g., teachers,

special educators, administrators, parents, agency personnel), a small subset of

whom also were also observed.

106

Table 1 - Overall School Demographic Data

Note. L = Liceo; T = Tecnico/Technical; P = Professionale/Professional. aEstimates provided by school administrators.

Mean TotalCultural/Ethnic

MinoritiesaEconomical

Disadvantageda

Italian as Second

Language

School by

Region

School Level Class School

Enrollmentn % n % n %

Lazio 1 Infanzia -

Primaria25 577 54 (9.4) 40 (6.9) 8 (1.4)

Lazio 2 Secondaria II

(T)25 1030 200 (19.4) 250 (24.3) 134 (13.0)

Lombardia 1 Secondaria II

(L)25 1560 70 (4.5) 20 (1.3) 70 (4.5)

Lombardia 2 Primaria 22 521 47 (9.0) 21 (4.0) 47 (9.0)

Lombardia 3 Primaria 23 231 22 (9.5) - - 22 (9.5)

Lombardia 4 Secondaria II

(P)25 669 120 (17.9) 84 (12.6) 120 (17.9)

Puglia 1 Primaria 20 427 43 (10.1) 60 (14.1) 20 (4.7)

Sicilia 1 Primaria -

Secondaria I25 1000 50 (5.0) 200 (20.0) 20 (2.0)

Sicilia 2 Secondaria II

(L)20 440 5 (1.1) 20 (4.5) 5 (1.1)

Veneto 1 Infanzia -

Secondaria I24 846 371 (43.9) 104 (12.3) 371 (43.9)

Veneto2 Secondaria II

(L, T, P)27 735 66 (9.0) 100 (13.6) 84 (11.4)

Veneto 3 Secondaria II

(L)27 1100 10 (0.9) 10 (0.9) 10 (0.9)

Veneto 4 Infanzia -

Secondaria I20 896 151 (16.9) 80 (8.9) 90 (10.0)

Veneto 5 Primaria -

Secondaria I20 854 85 (10.0) 43 (5.0) 85 (10.0)

Veneto 6 Primaria 19 309 109 (35.3) 30 (9.7) 109 (35.3)

Veneto 7 Secondaria II

(T, P)25 850 203 (23.9) 30 (3.5) 140 (16.5)

M 23.3 752.8 100.4 (14.1) 72.8 (9.4) 83.4 (11.9)

SD 2.7 339.0 94.3 (11.9) 69.4 (6.8) 89.8 (12.1)


4.4 Procedures and instrumentation

Prior to our arrival in Italy we prepared a brief letter introducing ourselves,

explaining our upcoming sabbatical visit. The letter expressed our interest in

observing in schools where students with intellectual and multiple disabilities

were being included in regular education classes and speaking with school per-

sonnel. Secondly, we developed a 13-item school demographic questionnaire

patterned after one component of our US studies, though smaller in scope co-

vering basic demographic and personnel utilization variables (e.g., student en-

rollment, average class size, number of students with disabilities, number of

“insegnante di sostegno”, number of assistants). Both the introductory letter

and questionnaire were translated from English to Italian. After arrival in Italy,

but before distribution to potential school sites, a bilingual Italian researcher re-

viewed both documents and minor edits were made to improve the translation.

Our university and education ministry liaisons shared the letter and que-

stionnaire (in both Italian and English) with their local school colleagues to

assist us in scheduling school visits. Typically, we spent a half-day or more at

each site, and in one case two days at the same site. One or more bilingual col-

leagues accompanied us to each site; additionally some of our school hosts

were bilingual or they identified a teacher who was bilingual, often the school's

English teacher. In an effort to minimize misunderstanding or misinterpretation

of questionnaire items, rather than asking the administrators to simply com-

plete questionnaire as a written document, we posed each question verbally,

through an interpreter when necessary. This allowed us to ask follow-up que-

stions to clarify the meaning of the question and to verify their responses. Even

though the questions seemed fairly simple, typically it took 1 to 2 hours to re-

spond to the 13 demographic questions. For example, it took time clarifying

the question and responses pertaining to the percentage of time students with

disabilities were actually present in typical classrooms or who should be coun-

ted as an assistant -- these types of counts often resulted in an extensive di-

scussion before the school leader provided a final response. Additionally, some

variables, such as the reported number of students: (a) economically disadvan-

taged, (b) from cultural/ethnic minorities, and (c) with special educational

needs who were not disabled, were offered as estimates because: (a) the scho-

ols did not all maintain data on these variables, and (b) the schools did not

share common definitions for these variables.

4.5 Data analyses

Questionnaire data were analyzed using basic descriptive statistics (e.g.,

percent, mean, standard deviation; see base variables in Tables 1 and 2) in

SPSS (Statistical Package for the Social Sciences).

107

By summing or deriving ratios from the base variables we created five calcu-

lated variables (see Table 3). A small number of Pearson correlations (two-tailed)

were run to explore relationships between variables that were statistically signifi-

cant in the US studies.

108


Students

with Certified

Disabilities

Students with CertifiedDisabilities in RegularClass (80% or More)

Students with BES

(Not Certified Disa-

bled)

“insegnante di

sostegno”/

Specialized Support

Teacher

FTE

Assistente/

Assistant

FTE

School by Region n % n % n %

Lazio 1 14 (2.4) 14 (100.0) 49 (8.5) 6.0 3.0

Lazio 2 74 (7.2) 54 (73.0) 155 (15.0) 23.0 6.0

Lombardia

1

13 (0.8) 13 (100.0) 20 (1.3) 5.0 4.0

Lombardia 2 30 (5.8) 28 (93.3) 5 (1.0) 8.5 13.0

Lombardia 3 6 (2.6) 6 (100.0) 20 (8.7) 2.0 4.0

Lombardia 4 40 (6.0) 39 (97.5) 67 (10.0) 13.0 4.0

Puglia 1 17 (4.0) 12 (70.6) 50 (11.7) 12.0 6.0

Sicilia 1 26 (2.6) 26 (100.0) 46 (4.6) 11.0 1.0

Sicilia 2 43 (9.8) 43 (100.0) 44 (10.0) 32.0 8.0

Veneto 1 38 (4.5) 37 (97.4) 17 (2.0) 17.9 4.0

Veneto2 26 (3.5) 24 (92.3) 19 (2.6) 14.0 3.0

Veneto 3 4 (0.4) 4 (100.0) 4 (0.4) 3.2 2.0

Veneto 4 24 (2.7) 24 (100.0) 13 (1.5) 13.0 8.0

Veneto 5 16 (1.9) 16 (100.0) 15 (1.8) 9.0 1.4

Veneto 6 12 (3.9) 10 (83.3) 20 (6.5) 4.5 0.4

Veneto 7 18 (2.1) 10 (55.6) 20 (2.4) 8.0 3.0

M 25.1 (3.8) 22.5 (91.4) 35.3 (5.5) 11.4 4.4

SD 17.5 (2.4) 14.6 (13.6) 36.8 (4.6) 7.8 3.2

Table 2 - Students with Disabilities, Other Special Educational Support

Needs, and Specialized Support Personnel

Note. BES = Bisogni Educativi Speciali/Special Educational Needs; FTE = Full-Time Equivalent.


109

Table 3 - Calculated Variables Regarding Students with SEND and Personnel

Utilization

SEND

Combined students

with disabilities and

BES

Ratio of IdS FTE toStudents with Disabilities

Ratio of IdS FTE

to SEND

IdS School

Density:

Ratio of IdS

FTE to

Total School

Enrollment

Special Services

Concentration:

Ratio of

Assistants FTE

to IdS FTE

School by Region n %

Lazio 1 63 (10.9) 2.3 (10.5) 96.2 0.5

Lazio 2 229 (22.2) 3.2 (10.0) 44.8 0.3

Lombardia

1

33 (2.1) 2.6 (6.6) 312.0 0.8

Lombardia 2 35 (6.7) 3.5 4.1 61.3 1.5

Lombardia 3 26 (11.3) 3.0 13.0 115.5 2.0

Lombardia 4 107 (16.0) 3.1 8.2 51.5 0.3

Puglia 1 67 (15.7) 1.4 5.6 35.6 0.5

Sicilia 1 72 (7.2) 2.4 6.5 90.9 0.1

Sicilia 2 87 (19.8) 1.3 2.7 13.8 0.3

Veneto 1 55 (6.5) 2.1 3.1 47.4 0.2

Veneto2 45 (6.1) 1.9 3.2 52.5 0.2

Veneto 3 8 (0.7) 1.2 2.5 341.6 0.6

Veneto 4 37 (4.1) 1.8 2.8 68.9 0.6

Veneto 5 31 (3.6) 1.8 3.4 94.9 0.2

Veneto 6 32 (10.4) 2.7 7.1 68.7 0.1

Veneto 7 38 (4.5) 2.3 4.8 106.3 0.4

M 60.3 (9.2) 2.3 5.9 100.1 0.5

SD 51.5 (6.4) 0.7 3.2 92.8 0.5

Note. SEND = Students with Educational Needs and Disabilities; BES = Bisogni Educativi Speciali/Speial Educationa

Needs;

IdS = “Insegnante di Sostegno”/Specialized Support Teacher; FTE = Full-Time Equivalent.

5. Findings

Although this sample of 16 schools is too small to draw many statistically

significant inferences or to make broad generalizations, visual analyses of the

data raise a series of potentially important issues and offer some interesting

patterns overall, especially when comparing the seven “Secondaria II” schools

with the nine lower graded schools (see Tables 2 and 3). For example, the per-

centage of students with certificates of disability in the full sample averaged

3.8% (SD = 2.4), ranging from 0.4% to 9.8%; making this sample's percentage

slightly higher than 2% to 2.5% rate typically reported nationally. A closer

examination of the schools shows that five of the seven “Secondaria II” schools

were those situated at the furthest ends of the distribution, with two schools

identifying less than 1% and three schools identifying over 6% as disabled;

the highest at 9.8%. Overall, the percentage of these students with disabilities

who were reported to spend 80% or more of their time in the regular classroom

was fairly high, with an average of 91.4% (SD = 13.6). While half of the schools

reported 100% of their students with disabilities were in regular class at least

80% of the time, the remaining half ranged from 55.6% to 97.5%, with four

schools reporting below 85%.

The percent of students identified by the schools as having "special edu-

cational needs" (i.e., “bisogni educativi speciali”) but not meeting the criteria

to receive disability-related services presents an interesting pattern. Given that

Italy has relatively stringent criteria to certify a student as disabled, resulting

in a relatively low identification rate compared to many other western coun-

tries, one might reasonably expect the percentage of students with the "special

educational needs" (not disabled) designation to exceed those labeled disabled.

In general this expectation is reflected in this sample; on average these schools

identified 5.5% (SD = 4.6) of their students as having special educational

needs, ranging from below 1% to 15%; on average this is approximately 2%

higher than the percentage with certified disabilities. There were some excep-

tions to this pattern; five of the schools identified the same or a higher percen-

tage of students as disabled than those identified as having special educational

needs. Overall, there was a strong and significant relationship between schools'

percentage of students certified as disabled and those with special educational

needs, r (16) = .59, p = .02. Schools with a low percentage of students with

disabilities tended to identify a relatively low percentage with special educa-

tional needs (e.g., Veneto 3,Veneto 5), and schools with relatively high per-

centage of students with disabilities tended to identify a relatively high

percentage with special educational needs (e.g., Lazio 2, Sicilia 2).

A closer look at the distribution suggests three subcategories of relationship

between the percentage of students identified as disabled and those with special

educational needs exist. First, of the 16 schools, just under half (n = 7) identi-

fied substantially more students as having special educational needs than cer-

tified as disabled, often two, three or four times as many (e.g., 2.4% disabled,

an additional 8.7% with special educational needs).

110



Second, in five schools, the percentage of students with disabilities and those

with special educational needs were virtually identical, within one-half of one

percent. And third, the remaining four schools identified a lower percentage of

their students as having special educational needs compared to those certified as

disabled, the reverse of what might be expected in the general population.

Interestingly, four of five of these cases that had nearly identical percentages

of students with disabilities and those with special educational needs were “Se-

condaria II” schools, and again they represented the outer ranges of the distri-

bution on both the high and low ends. For example, the high school that

identified 9.8% of students as disabled also identified an additional 10% of its

students as having special educational needs. Conversely, the high school that

identified 0.4% of its students as disabled only identified an additional 0.4%

of its students as having special educational needs.

When one examines the combined percentage of students with special educa-

tional needs and disabilities (SEND; see Table 3), the average of 9.2% (SD =

6.4) may obscure the more interesting finding represented by the wide range

from 0.7% to 22.2%; nine schools had a combined SEND percentage of ap-

proximately 7% or below while seven schools were over 10%. Again, Secon-

daria II schools populated both ends of the distribution.

On average, special education teachers (“insegnante di sostegno”) in FTE (full-

time equivalents) were available to support approximately two students with

certified disabilities (M = 2.3, SD = 0.7). This caseload size number of students

with disabilities represented the most tightly clustered data point with the least

variability among the schools, ranging from an average low of 1.3 to a high of

3.5. In addition, a strong and significant correlation was found between “inse-

gnante di sostegno” FTE and the percentage of students with disabilities, r

(16) = .83 p < .001. When the total SEND population (i.e., students with special

educational needs and disabilities) is considered, on average there is one “in-

segnante di sostegno” FTE for approximately every six students (M = 5.9, SD

= 3.2), with a wider distribution across schools, ranging from 2.5 to 13.

Beyond caseload numbers of students with certified disabilities or those

with other special educational needs, another way to conceptualize the availa-

bility of “insegnante di sostegno” to serve an individual school is using a metric

called special educator school density (i.e., the number of special

educators/“insegnante di sostegno” in FTE in a school compared to the total

student enrollment in the school). On average, this sample of schools had

one “insegnante di sostegno” for approximately every 100 students enrolled

in the schools (M = 100.1, SD = 92.8). This average is below the 1:138 ratio

that until recently had been codified in law after first being included in Law

449/1997, with a later provision (Ministerial Circular 27/2003) that the school

111

principal could appoint more support teachers to face school needs (D'Alessio,

2008, p. 59).

Special educator school density ratios in this sample ranged quite drama-

tically, from approximately 1:14 a low ratio (very dense), to a high ratio (very

lean) of approximately 1:342. Only two schools exceeded the 1:138 ratio, in-

terestingly both again were Secondaria II schools and both were Liceo. In se-

veral of the schools the special educator school density varied substantially

even though the average special educator caseloads, which varied by only one

of two students on average, were quite similar. For example, Lombardia 1 and

Veneto 6 reported nearly identical average special educator caseloads of stu-

dents with disabilities, 2.6 and 2.7 respectively. Yet their special educator

school density ratios differed vastly, 1:312 and 1:68.7 respectively. In part this

may be explained by the differences in the percentage of students with certified

disabilities in each school (i.e., Lombardia 1, 0.8%; Veneto 6, 3.9%). These

schools closely followed the same pattern identified in the inclusion-oriented

schools in the US, namely that there was a statistically significant inverse re-

lationship between the percentage of students a school certifies as disabled

and the special educator school density, r (16)= -.69, p = .003). In other words,

schools that identify a lower percent of students as disabled tend to have a hi-

gher special educator school density, fewer special educators per capita to serve

the total school enrollment. Alternately, schools that identify a higher percent

of students as disabled tend to have a lower special educator school density,

more special educators per capita to serve the total school enrollment. When

the two special educator school density statistical outliers (i.e., 1:312; 1:346)

were removed from the analysis, the inverse relationship was even stronger, r

(14) = -.82, p < .001).

The schools in this sample, on average, employed twice as many “inse-

gnante di sostegno” as assistants, referred to in Table 3 as the special services

concentration (i.e., ratio of assistants to “insegnante di sostegno” in FTE; M =

0.5, SD = 0.5). Notably, there were two schools that employed more assistants

than “insegnante di sostegno”. Among the remaining schools, their special ser-

vices concentration ranged from 0.8 to 0.1, with schools that had nearly the

same number of special educators and assistants (e.g., Lombardia 1) to schools

where they employed substantially more “insegnante di sostegno” than assi-

stants (e.g., Sicilia 1).

6. Discussion

In considering the findings, the reader is encouraged to remain cognizant of

the study's limitations. First, data were collected from a convenient sample of

112



schools (n = 16), each at a single point in time. Although this is a small number

of schools, our research experiences in Vermont have indicated that even a

sample of this modest size can be useful and potentially representative of a

broader set of schools. In our Vermont-based research, once we had collected

school demographic data from approximately our first 12 schools, the results

(e.g., means, standard deviations, ranges, ratios) remained virtually the same

after collecting data in over 60 schools. Whether a similar level of stability of

results would be replicated in Italian schools is unknown. Second, there is the

ever-present possibility of a translation error, miscommunication, or cultural

misunderstanding. Third, all data were based on report rather than direct ob-

servation or counts. Fourth, an inherent limitation of any questionnaire respon-

ses is the potential for idiosyncratic interpretation. We attempted to minimize

these limitations through our on-site data collection procedures presented in

the Method section. Despite these limitations, the findings offer a variety of

information regarding special education service delivery and hold potential

implications for these and other schools seeking to improve inclusive oppor-

tunities for their students with disabilities in general education classes.

As we first presented in our introduction to this article, our intention is not

to make judgments about these data as we might if we were studying a system

with which we were more familiar. Rather, our intention here is to point out

findings that raised questions for us and to pose those questions to Italian re-

searchers and practitioners so that they might offer their analyses and inter-

pretation of these findings. We have purposely included all of the raw data

provided by the schools in Tables 1 and 2 so that Italian researchers might ex-

plore or notice additional patterns or relationships that we did not report in the

findings. We offer the following comments and questions in a spirit of colla-

boration and gratitude to all of our Italian colleagues who took their valuable

time to help us understand inclusive educational efforts in Italy. We hope this

discussion contributes to our shared mission, namely to advance inclusive edu-

cational opportunities for students with disabilities by extending this interna-

tional dialogue about school service delivery.

6.1 Students with disabilities and other special educational needs

It seemed to us as visitors, that in Italy the social construction of what it

means to be "normal" is quite expansive -- this is something we left the country

appreciating and wanting to understand more thoroughly. This wide sense of

"normal" is partly evidenced by the fact that the national prevalence of the

school-aged population certified as disabled is only approximately 2.0% to 2.5%,

and students with other special educational needs referred to as DSA (Disturbo

Specifico dell'Apprendimento/Specific Disorders of Learning) (e.g., learning

113

disabilities, dyslexia, dysgraphia, reading or math delays, relatively minor

speech/language difficulties) are not considered disabled. So what does it mean

that the schools in this sample had an average of 3.8% of their students certified

as disabled? Is this merely an insignificant artifact of the small sample size, or

does it reflect a national trend toward higher rates of identification of students

as disabled? If it is the later, are there are actually now more students with di-

sabilities severe enough to be certified disabled, or are those previously iden-

tified as having special educational needs (e.g., DSA, learning disabled)

increasingly being certified as disabled in some schools?

Even more importantly, why did the high schools in this sample occupy the

furthest ends of the distribution both top and bottom, ranging from 0.4% to

9.8% of their students certified as disabled? Is there something about the tran-

sition process to “Secondaria II” schools that results in these wide differences?

Similarly, why do some of these high schools that have a high percentage of di-

sabled students also have a high percentage of students with special educational

needs and those with a lower percentage of disabled students tend to have rela-

tively few other students with special educational needs? There seems to be

wider variability between the high schools, but more consistency within them.

Regardless of why, what impact does a relatively high or low concentration of

students with disabilities and special educational needs have on school service

delivery, faculty and students? Some US proponents of inclusive education

have historically advocated for "natural proportions" in placement (Brown,

Ford, Nisbet, Sweet, Donnellan, & Gruenewald, 1983), meaning that the per-

centage of disabled students in any given school or classroom should closely

align with the percentage of students with disabilities in the local community;

thus seeking to avoid congregating students with disabilities. Are the higher

percentages of students with disabilities and other special educational needs

in some schools: (a) simply a naturally occurring phenomenon, (b) a conscious,

desired choice, or (c) a cause for concern and potential action? Are teenage

students with disabilities staying in school until age 19, like most of their peers

without disabilities? How many students with more severe disabilities are lea-

ving school shortly after they reach the compulsory schooling age of 16 and

transitioning to adult services options that are primarily disability-only settings?

One similarity between the US and Italy is that specialized supports often are

provided based on the number of students identified as disabled. A positive

feature of the role of the “insegnante di sostegno” (specialized support teacher)

is that they are present in classes where students with disabilities are placed to

support the entire classroom, not exclusively the students with disabilities.

What are the implications of this model for students who have special educational

needs but who are considered not disabled (e.g., DSA, learning disabled)?

114



Are the grouped in classes or schools with students who have disabilities in

an effort to offer them support? If they are not in a class where an “insegnante

di sostegno” is assigned, what supports are available to them? Are there diffe-

rent school or post-school (e.g., university, vocational) outcomes for students

with special educational needs who are in classes where “insegnante di soste-

gno” supports are available because of the presence of a student with a disa-

bility versus when these same students are in classes where “insegnante di

sostegno” services are not available to them? Ultimately, are more students

getting labeled disabled in a benevolent attempt to provide them with access

to otherwise unavailable supports?

6.2 Regular class placement

A couple of fundamental issues were raised by our simple data collection in

reference to percent of time students with disabilities spend in the regular cla-

ssroom. What constitutes 100% and what constitutes a regular class? It turns

out these seemingly obvious questions are not quite as straightforward as they

appear. Here are some ambiguous examples we encountered where respon-

dents interpreted the same phenomena differently. Consider the example of a

student with a severe disability who spends the first 25% of each typical school

day at a local therapy center receiving specialized services (e.g., physiothe-

rapy) before being transported to school. From the moment the student arrives

at school midmorning she is in regular class with her nondisabled peers the

entire time. What percent of time is she in regular class? Is it 75% because she

is in class 75% of the time available to her classmates, or 100% because during

the time she is at school she is in class the entire time?

None of the schools we visited had any designated special classes. Yet in

some cases small groups of students, all with certified disabilities, were taught

together for varying periods of time in separate rooms at school where no nondi-

sabled peers were present or away from school (e.g., community recreation cen-

ter). In other cases individual students were taught in a one-to-one format by

either an “insegnante di sostegno” or assistant for varying periods of time in a

separate room. Are these examples considered participation in regular class? If

there are no designated special classes, is everything else considered regular class?

While there is no doubt that for decades Italy has been an international leader

in providing access to regular class for students with disabilities as well stu-

dents who would be considered disabled in other countries, the regular class

inclusion statistics most commonly associated with Italy (e.g., 98% of students

with disabilities in regular class) may not clearly represent what is happening

in a way that can be consistently understood and readily compared across scho-

ols within Italy or internationally.

115

Is there any value to Italian students with disabilities, schools, or researchers

in developing a more consistently applied operational definition of what con-

stitutes regular class placement or inclusion rates? In our US-based research

we have identified some modest discrepancies between what administrators

and special education teachers reported about issues such as the extent to which

particular students were included in regular class or taught by various personnel

(e.g., teachers, special educators, assistants). This encourages us to collect data

from multiple sources allowing for data triangulation and to explore the use of

direct observational measures or other methods (e.g., student schedule review) to

gain a more accurate understanding of regular class placement.

It is important to recognize that none of the aforementioned points address

the qualitative issues of what happens in regular class or elsewhere. Some level

of individualized or small group instruction outside the regular classroom may

be appropriate for certain students, regardless of whether they have disabilities,

special educational needs, or neither designation. When considering potential

pull-out services or scrutinizing current ones, it is important to: (a) examine

why the student is being pulled-out and for how long, (b) whether the support

can be appropriately offered in the regular classroom, (c) whether the pull-out

suggests needed changes in the structure or operation of the regular classroom,

and (d) develop a plan to reintegrate students into the regular classroom as

much as possible. Invariably, these considerations lead to qualitative questions

about what is happening in the regular classroom. Are students with disabilities

seated with their classmates participating in shared activities or they seated

apart from their classmates with an “insegnante di sostegno” or assistant doing

the same or different work? Do students with disabilities have appropriately

adapted curriculum and instruction? Does the classroom teacher demonstrate

shared ownership for the instruction of the student with a disability in the cla-

ssroom? While these and other qualitative questions are beyond the scope of

this study, it is vital to remain cognizant of the fact that while placement in a

regular class is an important point of access, mere presence in the regular cla-

ssroom does not ensure quality of curriculum, instruction, or supports neces-

sary for a successful inclusive education (Giangreco, 2011).

6.3 Personnel utilization

A point of great interest to us during our time in Italian schools was the

generally consistent practice of employing proportionally more “insegnante

di sostegno” than assistants to support students with disabilities in general edu-

cation classes. This practice, one we consider desirable, is the reverse of what

is encountered in many inclusion-oriented schools in the US, where assistants

substantially outnumber special education teachers. Our research has identified

116



the disproportionate utilization of assistants rather than more highly trained

special educators as a major area of concern in inclusion-oriented US schools

and a serious threat to equitable educational opportunities for students with di-

sabilities (Giangreco, Broer, & Suter, 2011; Giangreco, Suter, & Hurley, 2011).

When American special educators, administrators, and parents hear that the

average caseload size for an “insegnante di sostegno” in this sample is slightly

over two students with disabilities, with minimal variability across schools, it

would not surprising if they immediately assumed that Italian schools have

many more personnel resources than American schools, where double-digit

caseloads are the norm in inclusion-oriented schools and the national caseload

size for special educators in recent years have averaged around 15 (Giangreco,

Hurley, & Suter, 2009). By using the calculated variable, special educator

school density (i.e., ratio of special education teacher FTE to total school en-

rollment), we can see that on average inclusion-oriented schools in Vermont

actually have slightly more special education teacher resources than the Italian

schools in this sample. With a ratio of about 1:94, the Vermont schools have a

slightly lower ratio than the average 1:100 ratio in this sample of Italian schools.

Although the descriptor, special educator school density, is not one used

in the Italian context, it seems that the concept is one that has been considered,

discussed, and applied in Italy at least since Law 449/1997 referred to a ratio

of “insegnante di sostegno” to student population of 1:138. This ratio was not

necessarily selected as desirable ratio based on research, but was rather was a

number based on a national average of what existed in schools at the time the

law was passed (Renzo Vianello, personal communication, October 2011). Our

recent research suggests that special educator school density is significantly

correlated with special educator self-efficacy ratings (Giangreco, Suter, & Hur-

ley, 2011) and we find potential value in assigning special education teacher

resources based on total school population, rather than exclusively based on

the number of students identified as disabled -- this assumes a naturally oc-

curring distribution of students with disabilities and other special educational

needs. Variations in special educator school density may help explain perceived

concerns expressed by Italian educators about the adequacy of resources to

support inclusive placements of students with disabilities (Cornoldi et al.,

1998), especially in schools where the ratio substantially exceeds 1:100. Al-

though cross-cultural comparisons are always fraught with complications (D'Ales-

sio & Watkins, 2009), this ratio may allow for more accurate comparison of

personnel utilization internationally, at least in countries that rely on some form

of special education teacher role.

What do Italian researchers and practitioners think are the implications of

the wide range special educator school density ratios identified across schools

117

in this sample? How might the special education school density ratio variable

be utilized by Italian schools ensure equitable access of “insegnante di soste-

gno” services for students with disabilities and those with other special edu-

cational needs? How do Italian researchers and practitioners interpret the

similarities between the findings in the US and Italy that: (a) percent of stu-

dents with disabilities and special educator school density are significantly ne-

gatively correlated, and (b) schools with very similar average caseload sizes

for their “insegnante di sostegno” can have substantially different special edu-

cator school density ratios?

7. Conclusion

While inclusion-oriented schools around the world continue to advance their

curricular and instructional practices, the service delivery parameters within which

inclusive education is delivered remain vital to ensuring appropriate and quality

schooling for students with and without disabilities. The variables presented in

this study provide a set of foundational variables with the potential to impact prac-

tice and offer a starting point for international exchange and cooperation. More

fully understanding the potential impact and importance of these service delivery

variables is especially important during this era of global economic challenges.

We hope to learn more about the meaning and potential implications of these data

by inviting Italian researchers and practitioners to offer their analysis, interpreta-

tion, and insights. We look forward to extending the dialogue on these issues and

continue to be grateful for what we have learned to date through the generosity

of our Italian colleagues.

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and Italy: A comparison. International Journal of Special Education, 6,

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123

Notes for Contributors

The Journal will publish original papers (not early published nor in press). Papers submitted for publication should besent in electronic format, using one of the versions of Microsoft Word, through the e-mail address indicated below.A supplementary version in pdf format (built by means of Acrobat Reader), added to the word file, may be usefulto allow a clear vision of the format foreseen for printing. The most recent edition of the Publication Manual of theAmerican Psychological Association (Washington, APA), should be used as the style guide for the preparation of themanuscripts.

The first page of the manuscript should give the title, authors' names and affiliations, and the complete mailing addressof one of the authors (included fax number and e-mail address). A running title and at least three keywords shouldbe indicated.

The abstract should not exceed 200 words. Theoretical aspects, goals and methods, results and a short discussionshould be clearly reported.

The text of the paper should clearly indicate the following sections (example for an empirical paper):1. Introduction2. Aims and hypothesis3. Methods: Sample, Instruments, Procedure4. Data analysis5. Discussion

Tables and Figures should be in a limited number. They should be typed in a separate page, and they shouldreport a descriptive title (e.g.: Table 3, Figure III) followed by the legend. Illustrations should be made accordingto the linked models, and kept modifiable for an editorial work. The approximate location of figures and tablesshould be clearly indicated in the text.Decimal point should be used both in the tables and the text. For descriptive statistics, correlations, inferential stati-stics, etc., two decimal digits have to be reported. Omit zero before decimal digits when the value cannot be greaterthan 1 (e.g., correlations and significance level).

Citations in the text should be indicated with the author's name, year of publication and page number, e.g.: Achin-stein (1968, p. 32). A letter should be added to the year of publication if there are two references of the same au-thor in the same year: Orne (1973a). According to A.P.A. norms, in the quotations with more than one author thesymbol & should be used if the quotation is enclosed in parenthesis (Estes & Skinner, 1940), otherwise “and” hasto be used: e.g. Estes and Skinner (1940).For three to six authors, all surnames should be cited the first time the reference occurs (es. Wasserstein, Zappulla,Rosen, Gerstman, & Rock, 1994). Subsequent citations should use et al.: Wasserstein et al., 1994. If the authorsare more than six, use et al. after the six name. For subsequent citations use et al. after the first author’s name.References list should be given at the end of the article in alphabetical order, conform to the A.P.A. reference list,as illustrated by the following examples:

Achinstein, P. (1968). Concepts of science. Baltimore: John Hopkins Press.Anisman, H., Remington, G., & Sklar, L. S. (1979). Effects of inescapable shock on subsequent escape performance: Catecholaminergic and cholinergic mediation of response initiation and maintenance. Psychopharmacology, 61 (1), 107-124.Grossman, H. J. (Ed.). (1973). A manual on terminology and classification in mental retardation (Rev. ed.). Washington, DC: American Association on Mental Deficiency.Harter, M. R., & Aine, C. J. (1984). Brain mechanisms of visual selective attention. In R. Parasumaran & D. R. Davies (Eds.), Varieties

of attention (pp. 293-319). New York: Academic Press.Lanktree, C., & Briere, J. (1991). Early data on the trauma Symptom Checklist for Children (TSC-C). Paper presented at the meeting of the American Professional Society on the Abuse of Children, San Diego, CA.Piaget, J.(1967). Biologie et connaissance, Paris: Éditions de la Pléïade. (Engl. transl., Biology and Knowledge. Chicago: University of Chicago Press, 1971).Shallice, T. (1972). Dual function of consciousness. Psychological Review, 79, 383-393.

Please be sure that all the citation in the text are reported in the bibliography, while references not quoted in the text shouldnot be included.Footnotes should be avoided as possible. When their use is absolutely necessary, footnotes should be numbered consecuti-vely using superscript numbers for citation in the text, and inserted in the text according to Microsoft Word criteria for notesat the foot of the page.The Authors have to sign the statements regarding Conflict of Interest, Informed Consent, and Human Rights. Please followthe instructions included in the linked file.

Correspondence should be addressed to the editorial secretary:Dr. Tommasa Zagaria, Associazione "Oasi" Maria SS. I.R.C.C.S., via Conte Ruggero 73, Troina, 94018 Italy.Phone: ++39-935-936263/ 936233/ 936111; Faxline: ++39-935-653327; E-mail: [email protected] articles submitted for publication will be sent anonymously to two members of the scientific committee orexternal experts. The evaluation will be sent to the corresponding author normally within three months after the recep-tion of the version prepared according to the notes for contributors.The copyright of the accepted articles is retained by the publisher.Authors will receive two free copies of the issue including the printed article. Reprints may be ordered on a form sentto the authors together with the communication that article is accepted for the publication.

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