psychom_familyandhealth

500 http://psy.psychiatryonline.org Psychosomatics 45:6, November-December 2004

Family, Health, and Adolescence

NICOLAS ZDANOWICZ, M.D., PH.D.PASCAL JANNE, PH.D.

CHRISTINE REYNAERT, M.D., PH.D.

The present research examined the correlations between types of family relationships and adoles-cents beliefs about their own health. Healthy adolescents (N765) completed both the Multi-dimensional Health Locus of Control questionnaire and Olsons scale assessing family cohesionand adaptability. They were compared to a group of 358 adolescents diagnosed with mental dis-orders. Cohesion in the family of origin was a significant factor in the adolescents feeling ofcontrol over their own health as well as in the level of power they attributed to other people.Among these adolescents, adaptability of the family of origin was positively correlated withstronger feelings of control over ones own health and with lower levels of belief in chance. Fam-ily relations were significant in the adolescents acquisition of feelings of control over their ownhealth. (Psychosomatics 2004; 45:500507)

Received June 5, 2003; revision received March 23, 2004; accepted April7, 2004. From the Universite Catholique de Louvain. Address reprintrequests to Dr. Zdanowicz, Service de psychosomatique, Clinique deMont-Godinne, Universite Catholique de Louvain, 5530 Yvoir, Belgium;[email protected] (e-mail).

Copyright 2004 The Academy of Psychosomatic Medicine.

About 10 years ago, the development of preventivemedicine became a major objective in many devel-oped countries. The populations that are targeted to benefitfrom these campaigns of prevention are teenagers, youngadults, and their parents. These populations are consideredmore likely to be influenced and to adopt behaviors in favorof their health. However, what do we really know aboutthe evolution of health at this age and about its correlateswith family dynamics? Until now, the largest number ofstudies on the evolution of health have been conductedwith the Multidimensional Health Locus of Control(MHLC),1 even though new instruments for addressingthese issue have since been developed.

In 1978, Wallston and colleagues developed theMHLC, which measures the respondents beliefs about hisor her responsibility in determining his or her own healthstatus. This scale is multidimensional as it enables the iden-

tification of three different types of belief: two are exter-nal in nature, and one is internal. Internally controlledindividuals tend to believe that the reinforcements they en-counter depend on the behaviors they perform. This di-mension is measured with the subscale for internalityhealth locus of control. Externally controlled individualstend to believe 1) that their health is either the result ofchance or fate (this belief is assessed by the subscale forchance health locus of control) or 2) that it results fromothers actions (this belief is assessed by the subscale forpowerful others health locus of control). Finally, the re-lation between internal and external tendencies can be cal-culated through the internality/externality ratio.2 The de-velopment of this scale has triggered considerable research,including a review by Pauwels et al.,3 which has indicatedthat, especially through primary and secondary individualpreventive attitudes, the MHLC is a good predictor of re-spondents medical as well as psychiatric health. It is nev-ertheless important to remember that, as with all scales, theMHLC suffers from several limitations and seems particu-larly less appropriate for assessing respondents will tocontrol and the value they assign to health.4

After reviewing the relevant literature on this topic,

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we found only two studies that have used the MHLC withadolescents. Besides confirming the usefulness and stabil-ity of the MHLC during adolescence, the study by Stantonet al.5 also pointed at gender differences in locus of control.More specifically, Stanton and associates found that thelevels of attribution of health locus of control to chanceand to powerful others vary between the ages of 13 and 15but only among female subjects. The second study, con-ducted by Nada-Raja and colleagues,6 included more than800 young people 15 years old. While this research did notstudy the influence of age on MHLC scores, it still foundgender differences in levels of internality regarding healthlocus of control (higher levels among male subjects) andin levels of attribution to powerful others (lower amongmale subjects). In addition, the preceding research showedthat negative life events and mothers beliefs about theirown locus of control had a significant influence on theirdaughters level of internality. A positive correlation of in-ternality with a high level of social support and/or self-perception of strength was also found among male sub-jects.

One particularity of the MHLC is that item 7, whichis used to assess belief in powerful others as a locus ofcontrol over health, measures respondents belief in theinfluence their families have over their own health. How-ever, we do not know of any study that has ever been pub-lished on this particular item. No study has demonstratedwhether, as we can reasonably assume, peoples attitudestoward their own health are influenced by their familyseducational as well as relational patterns. Thus, while aparticular family might promote in its members a sense ofcontrol over their individual health, another might promotea more fatalistic disposition. In addition to research mea-suring the relationship between MHLC scores and adoles-cence, other studies have used Olsons scale7 to investigatethe relationship between family functioning and illnessamong adolescents. More precisely, Olsons circumplexmodel aims at assessing two dimensions (axes) of a givenrelational system at work: cohesion and adaptability. Co-hesion is defined as the emotional ties each member ofa family develops towards the other members, and adapt-ability is defined as the conjugal or family systems abil-ity to change its power structure and relational rules androles in response to a stressful situation or development.A self-rating version of this scale is the FACES III (FamilyAdaptability and Cohesion Evaluation Scale),8 which en-ables a quick, quantitative evaluation of the two axes,thereby describing the interactive and structural stylewithin the system under study. The model is conceived in

such a way that family health is found in the medianvalues of the two axes. In other words, family cohesionis measured by a value found on the separated-linkedcontinuum, and system adaptability is measured by avalue found on the structured-flexible continuum.9 Stud-ies with adolescents have shown significant differences infamily functioning between families containing an adoles-cent member with psychiatric or medical pathology andfamilies without an ill adolescent (Table 1).

Thus, we have, on the one hand, some informationabout the evolution of feelings about ones control overones health during adolescence and, on the other hand,information about the role played by family dynamics insome disorders. However, research on the effect of familydynamics on feelings about control over health is lacking.Our objective was to try to build a bridge between familydynamics and adolescents attributions of responsibility fortheir own health. In order to test the hypothesis that thesevariables are associated, we studied the correlations be-tween the functioning of the family of origin and theMHLC scores of a group of healthy adolescents andcompared those to similar correlations for a group of ad-olescents with psychiatric disorders (henceforth referred toas unhealthy adolescents). For the latter group, weavoided selecting any particular pathology for two reasons.First, the research conducted with Olsons scale includeda great variety of disorders (Table 1), and second, the re-search results described by Prange et al.15 and by us17 sug-gest that family characteristics are associated with vulner-ability to disorders in general rather than to a particularone.

METHOD

The present research took place between December 1998and June 1999. The subjects completed the MHLC and theFACES III questionnaires. We used Fontaines French ver-sion of Olsons scale18 and Mortreus French version of theMHLC.19

Participants and Procedure

The healthy subjects were selected by using two dif-ferent strategiesa procedure that aimed at including ad-olescents from varied cohorts and backgrounds. The firstrecruitment took place in each of the 6 grades of threesecondary public schools (i.e., with ages normally rangingfrom 12 to 18 years) in the province of Namur (Belgium).Under a psychiatrists supervision, these adolescents were



TABLE 1. Previous Studies Using Olsons Scale7 to Assess the Cohesion and Adaptability of Families of Children or Adolescents WithPsychiatric or Other Medical Illnesses

AuthorsAdolescents Condition

or Treatment Goal Age and/or Sex Family Cohesion and/or AdaptabilityCoburn and Ganong10 Bulimia Female university students Bulimic adolescents families were weakly

cohesive; adaptability had no influenceKashani et al.11 Depression 13 years Depressive childrens families were

disengaged; adaptability had no influenceLawler et al.12 Diabetes control 1518 years Diabetes control correlated with family

cohesion; families of disengaged patientshad the worst results

Lundholm and Waters13 Eating disorders Female university students Female university students with eatingdisorders had extreme familiesa

Michaels and Lewandowski14 Learning and writing disabilities 612 years Children with learning disabilities hadextreme familiesa

Prange et al.15 Affective disorders 1218 years Adolescents with affective disorders haddisengaged families; weak familycohesion positively correlated with a highlevel of psychopathology

Tubiana et al.16 Diabetes control 713 years Cohesion and adaptability were proportionalto patients compliance with theirtreatment; rigid and disengaged familieslacked control over patients diabetes

Zdanowicz et al.17 Healthy versus unhealthy 1025 years Families of healthy subjects had high levelsof cohesion and adaptability

aIn the circumplex model of cohesion and adaptability, an extreme family is one scoring at either extreme of either the cohesion axis or theadaptability axis.

asked to answer a sociodemographic questionnaire (age,gender, high school level, nationality) and to complete theMHLC and Olsons scale assessing their family of origin.The second group of subjects was selected by 4th-year psy-chology students at the Catholic University of Louvain,who distributed to adolescents they were acquainted withan anonymous questionnaire whose items included socio-demographic variables (birth date and gender) as well asthe MHLC and Olsons scale. It should be noted that thehealthy subjects were considered normal by default.Thus, although they were not recruited in a hospital oranother health facility, we cannot exclude the possibilitythat some of them might actually have been hospitalizedfor one or another reason. To limit this possibility and be-cause of the frequency of depressive disorders at this age,the young people completed the Zung Self-Rating Depres-sion Scale.20

The unhealthy group was constituted from data thatwere systematically collected from 1989 to December 1998among hospitalized patients in the Psychosomatic Medi-cine and Psychopathology Units at the Mont-Godinne Uni-versity Clinics of the Catholic University of Louvain. Atthe very beginning of their hospitalization, the patients sys-tematically completed the MHLC and Olsons scale and

provided general sociodemographic data (birth date andgender) under the supervision of a psychologist. For eachpatient it was the first hospitalization, the admission wasvoluntary, and the patient was not coming from any resi-dential type of service. In an attempt to control the effectof the length of the enrollment period, every result wascontrolled by using the date of admission as a covariate.We disregarded these patients diagnoses in order to respectthe diagnostically nonspecific nature of our hypotheses.The patients diagnoses are shown in Table 2 for infor-mation purposes only. Patients who were initially enrolledon the basis of DSM-III-R diagnoses have been rediag-nosed with DSM-IV on the basis of their initial DSM-III-R diagnosis, symptoms at admission, and past psychiatrichistory. For the most frequent disorders, such as mood dis-orders, we have previously reported our results.21

Regardless of whether they belonged to the healthy orunhealthy group, the candidates had to be 1) between theages of 13 and 25 years, 2) single or living as an unmarriedcouple, 3) unemployed, receiving public assistance, or astudent. The World Health Organization22 proposed thesethree criteria as determining the condition of adoles-cence. In order to further homogenize our groups, the sub-jects had to be Caucasian, French-speaking, and students.

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TABLE 2. DSM-IV Axis I Diagnoses of 358 AdolescentsDuring Their First Psychiatric Hospitalization

Diagnostic Variablea N %Number of diagnoses

None 30 8.4One 207 57.8More than one 121 33.8

Specific diagnosisMajor depressive disorder 154 43.0Dysthymic disorder 6 1.7Anxiety disorders, combined 51 14.2Posttraumatic stress disorder 7 2.0Panic disorder 12 3.4Obsessive-compulsive disorder or phobia 6 1.7Anxiety-depressive state 25 7.0Alcohol dependence 31 8.7Alcohol abuse 12 3.4Other chronic substance abuse 63 17.6Factitious disorders 1 0.3Somatization disorder 24 6.7Conduct disorder, oppositional defiant

disorder, or disruptive behaviordisorder not otherwise specified 50 14.0

Schizophrenia or other psychotic disorder 17 4.7Eating disorders 27 7.5Adjustment disorders 11 3.1Mental retardation 2 0.6Learning disorders 8 2.2

aThere were a total of 464 diagnoses.

Analysis

SPSS for Windows 95/98/NT Advanced Model 9.0Swas used for our statistical analyses. Given the consider-able number of observations, the necessity to analyze theinfluence of several covariates, and the need not to changestatistical methods during the analysis, we used only para-metric tests. Pearsons chi-square test was used to compareproportions. Pearsons r coefficient was used to assess cor-relations between continuous variables, eventually con-trolled for partial correlation (with a covariate). Studentst test was used for comparisons of quantitative variables.The significance levels were tendency, significance (p0.05), and strong significance (p0.01). All the statisticswere two-tailed. Results are displayed in the following or-der: analysis of the demographic variables (age and gen-der), discussion of the impact of these variables, compar-isons of the scores for the two groups on Olsons scale andthe MHLC, and hypothesis testing (results of the correla-tions between the MHLC and Olsons scale). Other stan-dard demographic variables, such as ethnic origin, occu-pation, and educational level, were not considered relevantin the present study since the first two had already been

established as criteria for selection in the research designand the educational level is directly dependent on age.

RESULTS

Ten healthy subjects exceeded the threshold score of 0.699on the Zung scale (suspicion of depressive state), and 39were excluded from the protocol because of missing data.

Demographic Characteristics

The total study group comprised 1,123 subjects, ages13 to 25 years, with a mean age of 18.8 (SD3). Theunhealthy group included 358 subjects, ages 14 to 25, nor-mally distributed, with a mean age of 20.5 (SD3). Thehealthy group included 765 subjects, ages 13 to 25, nor-mally distributed, with a mean age of 18.3 (SD3). Thedifference in age between the healthy and unhealthy groupswas statistically significant (t13.18, df1121,p0.001).

In the healthy group, the sex ratio was 0.75 (329 menfor 436 women) as compared to a sex ratio of 0.56 (129men for 229 women) in the unhealthy group. This between-group difference was statistically significant (Pearsonsv269.11, df1, p0.001).

Not only were the differences between the two groupsin age and sex distribution meaningful, but previous re-search (see introduction) also suggests that both gender andage influence the results on the MHLC and Olsons scale.Consequently, it seems clear that these variables have tobe controlled.

Groups Differences on MHLC and FACES III

As Table 3 shows, Students t tests indicate significantdifferences both on the MHLC and Olsons scale betweenthe healthy and unhealthy groups. These results replicateboth the patterns typically found in the literature for theMHLC and Olsons scale (see introduction), i.e., more co-hesive and adaptive families among healthy subjects,greater internality in regard to health locus of control, andless attribution of control over health to higher powers.23Consequently, they can be considered as a control of thevalidity of this study.

Hypothesis Testing

Table 4 confirms our hypothesis about a link betweenbeliefs about control over health and family dynamics. Forthe entire study group, there were positive relationships



TABLE 4. Correlations, Controlled for Gender and Age, Between Scores on the Multidimensional Health Locus of Control Questionnaire(MHLC) and Olsons Scale of Family Cohesion and Adaptability for Healthy Adolescents and Adolescents Hospitalized forPsychiatric Disorders

Axis of Olsons Scale7

Family Cohesion Family AdaptabilityGroup and MHLC1 Measure r p r pTotal group (N1,123)

Belief in internality as locus of control over health 0.11 0.001 0.10 0.002Belief in external factors as locus of control over health

Powerful others 0.06 0.051 0.00 0.95Chance 0.03 0.34 0.08 0.02

Internality/externality ratio 0.05 0.14 0.08 0.02Healthy group (N765)



Internality/externality ratio 0.04 0.38 0.07 0.10Unhealthy group (N358)



Internality/externality ratio 0.04 0.50 0.03 0.58

TABLE 3. Scores on the Multidimensional Health Locus of Control Questionnaire (MHLC) and Olsons Scale of Family Cohesion andAdaptability for 765 Healthy Adolescents and 358 Adolescents Hospitalized for Psychiatric Disorders

Score AnalysisMeasure and Group Mean SD t df pOlsons scale7

Family cohesion 11.60 1121 0.001Healthy group 33.8 7.1Unhealthy group 28.0 8.7

Family adaptability 3.43 1121 0.001Healthy group 26.5 5.7Unhealthy group 25.2 6.3

MHLC1Belief in internality as locus of control over health 4.50 1121 0.001

Healthy group 24.1 4.7Unhealthy group 22.6 6.1

Belief in external factors as locus of control over healthPowerful others 7.96 1121 0.001

Healthy group 19.2 5.8Unhealthy group 22.3 6.3

Chance 5.76 1121 0.001Healthy group 17.9 5.5Unhealthy group 19.9 5.8

Internality/externality ratio 8.63 1121 0.001Healthy group 1.40 0.5Unhealthy group 1.12 0.4

between cohesion in the family of origin and the results forinternality and belief in powerful others control overhealth. A positive relationship was also found betweenfamily adaptability and the results for internality and theinternality/externality ratio. Finally, a negative relationship

was observed between family adaptability and belief thatchance controls health.

If we examine the influence of the dichotomous vari-able of belonging to either the healthy or unhealthy group,we can add three observations. First, this dichotomous vari-

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FIGURE 1. Relationship Between Age and Belief in PowerfulOthers Control Over Healtha for 762 HealthyAdolescentsb

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Age (years)

013 14 15 16 17 18 19 20 21 22 23 24

5

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aThis measure is a subscale of the Multidimensional Health Locus ofControl questionnaire.1

bPearsons partial correlation between healthy subjects age andbelief in powerful others as a locus of control over health, controlledfor gender: r0.17, p0.001. Data were derived from previousresearch.26

FIGURE 2. Relationship Between Age and Family Cohesiona for734 Healthy Adolescentsb

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mily

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Age (years)13 14 15 16 17 18 19 20 21 22 23 24

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aThis measure is one of the axes in Olsons scale for family cohesionand adaptability.7

bPearsons partial correlation between healthy subjects age andfamily cohesion, controlled for gender: r0.10, p0.008. Data werederived from previous research.26

able does not seem to influence the relationship betweenfamily cohesion and internality (v20.63, df1,p0.43), but in contrast, the relationship between cohe-sion and belief in powerful others as a health locus of con-trol appears stronger (r2) and more genuine (p) among thehealthy subjects (v23.66, df1, p0.05). This findingis troubling since we know that in the healthy group co-hesion is high and the belief in powerful others as a locusof control is less (see Table 3). However, we also knowthat among the healthy adolescents, age has a negative in-fluence on the belief in powerful others control (Figure 1)and that age is also correlated with decreasing family co-hesion (see Figure 2). Hence, the findings seem to suggestthat the combined effects of the interaction of age withbelief in powerful others and the interaction of age withfamily cohesion are stronger than the effect of the inter-action between family cohesion and belief in powerful oth-ers (in which the influences of age and gender do not ap-pear because they are statistically controlled). It thusappears that the first two combined effects tend to limit oreven weaken the latter.

Second, the dichotomous variable, healthy versus un-healthy, does not seem to influence the association eitherbetween family adaptability and the internality/externalityratio (v20.92, df1, p0.34) or between family adapt-ability and internality (v22.30, df1, p0.13).

Third, with regard to the link between family adapt-ability and belief in chance as a locus of control overhealth, it is interesting that whereas the adaptability of thehealthy adolescents families was correlated with less be-lief in chance, this influence was not present among theunhealthy adolescents (v23.78, df1, p0.05).

DISCUSSION

In the studies that have explored the relationships betweenfamily variables and pathology among adolescents (Table1), the most interesting finding we uncovered is theirmissing link aspect. Indeed, while reviewing this litera-ture, one can only wonder about the origin of the mecha-nisms that link family functioning to pathology. In the pres-ent research, it appears that the style of family dynamicsis significant in the formation of adolescents attributivejudgments as to who or what is responsible for their health.

It thus appears that a cohesive family supports its ad-olescent members beliefs in their own ability to influencetheir health, as does a minimal degree of trust in the other(which is necessary in a patient-doctor relationship). It alsoappears that flexible families ensure an internal/externalattributive judgmental process that fosters their adolescentmembers belief in their sense of worth and diminisheshealthy adolescents attribution of health control to chanceor fate.

It is true that one can also interpret the results pre-



sented here differently and approach the pathology-familylink in the reverse order: i.e., How does illness influenceour beliefs, and how do these beliefs shape our family sys-tem? If we cannot disregard the fact that our interactionspartially follow this logic as well, its probability is never-theless quite weak for at least two reasons. First, it makesmore intuitive sense to assume that the direction of theseinterrelations originates in the family, as it is itself for-mative of beliefs about locus of control, than to assume areverse order. Second, although we know of no prospectiveresearch on the MHLC (except the 5-year longitudinalwork by Thomas and Hooper,24 which studied the proba-bility of social integration among 65-year-olds as a func-tion of their MHLC scores rather than investigating pa-thology proper), there is indirect evidence that supports thispoint of view.3 Thus, as is the case in adult diabetes, forwhich internality can be correlated with patients bettercontrol over pathology,25 we can posit that beliefs aboutlocus of control influence health rather than the other wayaround.

Limitations

The main restriction on the present study is the weakproportion of explained variance, but we would have beenastonished (and a bit worried) if attitudes toward healthdepended solely on family variables. The second restrictionregarding the validity of our results is the duration of re-cruitment of the unhealthy subjects. Indeed, the fact of hav-ing controlled the results for the date of hospitalizationdoes not allow us to totally exclude sociocultural condi-

tions (e.g., divorce, illness of parents), pharmacologictreatment, or other factors (e.g., childhood medical condi-tions) that might have influenced our results.

Conclusions

From a practical point of view, we wonder whether theenhancement of health among young people would warrantthe deployment of preventive measures whereby parentswould be encouraged to adopt more flexible and cohesivehealth-related attitudes with their adolescent children ratherthan rigid and poorly structured ones. Such a messagecould be conveyed both during medical consultations andthrough media campaigns. From a therapeutic point ofview, the results of this study suggest that parents must besupported in the same sense during their adolescent chil-drens pathological afflictions. From a theoretical point ofview, it seems that we can speak of a developmental aspectof health in the same way that we speak of a developmentalaspect of pathology. Health, especially ones effort to con-trol ones health, is an ever-evolving attribute from child-hood to adulthood to which we must attend. Furthermore,such a developmental approach to heath is not reduced toa child or an adolescents individual condition but is de-veloping in the midst of a family system. This theoreticalaspect evokes the psychodynamic clinicians emphasis onadolescence as a salutary crisis that contributes to health.This theoretical developmental perspective nevertheless in-troduces a fundamental difference: it approaches pathologyas an insufficient development of health, rather than as amanifestation that contributes to more health. Of course,we need outcome studies to confirm all this.

References

1. Wallston KA, Wallston BS, De Vellis R: Development of the mul-tidimensional health locus of control (MHLC) scale. Health EducMono 1978; 6:160170

2. Reynaert C, Janne P, Delire V, Pirard M, Randour P, Collard E,Installe E, Coche E, Cassiers L: To control or to be controlled?from health locus of control to morphine during patient-controlledanalgesia. Psychother Psychosom 1995; 64:7481

3. Pauwels A, Janne P, Reynaert C: De differents mode`les de croy-ances envers la sante au vecu subjectif de controle vis-a`-vis de lasante: une tentative dapproche integrative. J Therapie Compor-tementale et Cognitive 1999; 9:99107

4. Conner M, Norman P: Predicting Health Behaviour. Buckingham,UK, Open University Press, 1999

5. Stanton WR, Nada-Raja S, Langley J: Stability in the structure ofhealth locus of control among adolescents. Br J Clin Psychol 1995;34:279287

6. Nada-Raja S, McGee R, Williams S: Health beliefs among NewZealand adolescents. J Paed Child Health 1994; 30:523529

7. Olson DH, Killorin E: Clinical Rating Scale for Circumplex Model

(revised version). St Paul, University of Minnesota, Family SocialScience, 1985

8. Olson DH: Circumplex Model VII: validation studies and FACESIII. Fam Process 1986; 25:337351

9. Reynaert C, Janne P, Zdanowicz N, Vause M, Vervier J-F: De-scription du syste`me familial par ses membres: le sentimentdautonomie. Cahiers des Sciences Familiales et Sexologiques1993; 17:95111

10. Coburn J, Ganong L: Bulimic and non-bulimic college femalesperceptions of family adaptability and family cohesion. J AdvNurs 1989; 14:2733

11. Kashani JH, Allan WD, Dahlmeier JM, Rezvani M, Reid JC: Anexamination of family functioning utilizing the circumplex modelin psychiatrically hospitalized children with depression. J AffectDisord 1995; 35:6573

12. Lawler MK, Volk R, Viviani N, Mengel MB: Individual and familyfactors impacting diabetic control in the adolescent: a preliminarystudy. Matern Child Nurs J 1990; 19:331345

13. Lundholm JK, Waters JE: Dysfunctional family systems: relation-

Zdanowicz et al.


ships to disordered eating behaviors among university women. JSubst Abuse 1991; 3:97106

14. Michaels CR, Lewandowski LJ: Psychological adjustment andfamily functioning of boys with learning disabilities. J Learn Dis-abil 1990; 23:446450

15. Prange ME, Greenbaum PE, Silver SE, Friedman RM, Kutash K,Duchnowski AJ: Family functioning and psychopathology amongadolescents with severe emotional disturbances. J Abnorm ChildPsychol 1992; 20:83102

16. Tubiana RN, Moret L, Czernichow P, Chwalow J: The associationof poor adherence and acute metabolic disorders with low levelsof cohesion and adaptability in families with diabetic children.Acta Paediatr 1998; 87:741746

17. Zdanowicz N, Janne P, Reynaert C: Role of the family duringadolescence (abstract). Eur Psychiatry 2002; 17(suppl 1):114115

18. Fontaine P: Famille saines: esquisse conceptuelle generale, in Dic-tionnaire Clinique des Therapies Familiales Systemiques. Editedby Benot JC, Malarewicz JA. Paris, Editions Sociales Francaises,1988, pp 267282

19. Janne P: De la douleur a` la plainte: pour une comprehension psy-

chosomatique de lischemie myocardique dite silencieuse (doc-toral thesis). Yvoir, Belgium, Universite Catholique de Louvain,Faculte de Psychologie et des Sciences de lEducation, 1989

20. Zung WWK: A self-rating depression scale. Arch Gen Psychiatry1965; 12:6370

21. Zdanowicz N, Coremans E, Verdicq S, Reynaert C: La depressiona` ladolescence: une maladie de linternalite? (abstract). Arch Pe-diatr 2002; 9(suppl 2):298

22. Organisation Mondiale de la Sante/World Health Organization: Lasante des jeunes: un defi, un espoir. Geneva, OMS/WHO, 1994

23. Zdanowicz N, Reynaert C, Janne P: Comparaison du MHLC entreune population dadolescents sains et en souffrance. Rev Psy-chiatr Psychol Med 2002; 54:2733

24. Thomas PD, Hooper EM: Healthy elderly: social bonds and locusof control. Res Nurs Health 1983; 6:1116

25. Reynaert C, Janne P, Donckier J, Buysschaert M, Zdanowicz N,Lejeune D, Cassiers L: Locus of control and metabolic control.Diabe`te Metab 1995; 21:180187

26. Zdanowicz N, Janne P, Reynaert Ch: Changes in health locus ofcontrol during adolescence of student. Eur J Psychiatry 2003; 2:107115

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