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Australian Centre on Quality of Life Bulletin Archive

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ACQol Bulletin Vol 4/27: 020720 to Vol 4/39: 240920

ACQol Bulletin Vol 4/39: 240920Bulletin of the Australian Centre on Quality of Lifehttp://www.acqol.com.au/Editor: Robert A. Cummins [[email protected]]Back-issues of the Bulletin are available at http://www.acqol.com.au/publications#bulletins

Note 1: The ACQol site is under development and some content is missing.Note 2: Please address any intended group correspondence to the editor only.

Subjective wellbeing and the basic structure of affect Cummins, R. A.

Background: Kimina Lyall [email protected] is leading a draft publication on the relationship between

mindfulness and Homeostatically Protected Mood (HPMood) (Cummins 2017a). We have received some excellent, detailed, and critical reviews from a leading journal. So we are now in the phase of crafting a reply to their comments, and producing an edited version of the manuscript which is acceptable to both the reviewers and the insightful editor.

Responding to critical reviews is always a challenging task, in this case exacerbated because the topic crosses between psychological science (HPMood) and religion (Buddhism). There are tender toes on both sides of this fence! While I am confident that we will find middle ground, I have become aware that reviewers who are expert in the mindfulness/Buddhist literature are having difficulty with some of the commonly accepted material from within psychological science. So this caused me to reflect on what research into subjective wellbeing is really building on. What are the basic foundations of Subjective Wellbeing (SWB) upon which our common thinking is based?

In order to operationalize this thought, I have started to explore three ‘foundational’ ideas, on the topic of affect, as described below. Perhaps such descriptions can be developed into a useful statement of common-ground between researchers? First, however, it is essential to establish the extent to which such views are accepted within our research community, and whether they represent a valid interpretation of available empirical evidence. With such an objective in mind, comments and critiques will be welcomed.

1. AFFECTThe term affect refers to feelings in general (Russell and Feldman Barrett 1999, Buchanan

2007). Affects may be further categorized into two independent dichotomies, and one tetrachotomy. The dichotomies are Mood and Emotion, and Positive and Negative affect. The tetrachotomy is the Affective Circumplex.

1.1 Moods and emotions are distinguished by the following features:


1.1.1 Moods are primitive, genetic in origin, object-free, and chronic (Oatley and Johnson-Laird 1987, Bower and Forgas 2000).

1.1.2 Emotions are complex, acute, affective-cognitive-somatic responses to percepts or ideas (Scherer 2000, Russell 2003).

1.1.3 Moods are low intensity, background affects (Buchanan 2007, Ekkekakis 2013). Emotions may be high or low intensity (Forgas 1995).

1.1.4 The only known example of a mood, which has been empirically demonstrated to meet all the above criteria, is Homeostatically Protected Mood (HPMood). Using the English language, HPMood comprises the affects of content, happy and alert (Cummins 2017a). Each affect refers to an affective trait, located on the affective circumplex (Russell, 2003) (see section 1.3).

1.1.5 In phylogenetic terms, it seems likely that the evolution of emotion preceded that of mood. Even single-cell amoeba display emotion in the form of an approach-avoidance response. Thus in these terms, emotion is more basic than mood. However, HPMood is, quite possibly, the most basic mood. It is genetically prescribed at a level peculiar to each individual, it does not change, it does not carry specific information, and it forms a part of all self-evaluations (Cummins, Capic et al. 2018a).

1.1.6 HPMood exists as a weak, background affect within consciousness. This allows emotion to be normally stronger, and therefore dominant in consciousness. Emotions inform the brain of changes in percepts, arising from the activation of sensory receptors, and also of thoughts through the generation of cognitive/affective complexes. The presence of emotions in consciousness generally masks awareness of HPMood. However, the presence of HPMood can be demonstrated in one of two ways. One is through the practice of meditation, directed at the elimination of emotion through various techniques. The other is statistical, by removing the variations in affect, which are caused by emotion, for each individual over time. The affective residue, following such ‘emotion stripping’, mainly comprises HPMood (Cummins, Li et al. 2014a, Capic, Li et al. 2018).

1.1.7 Conjecture. HPMood may be a by-product of the ‘spontaneous’ neural activity described as occurring through the whole brain at rest, within linked neural structures called Resting State Networks (Vahdat, Khatibi et al. 2020). The purpose of these RSNs is to keep the brain ‘functionally active’ during periods of quiescence, rather than to convey specific information. It has been proposed (Cummins 2020) that there could be an evolutionary linkage between the generation of ‘spontaneous intrinsic activity’ in these RSNs throughout the Central Nervous System at rest, and the demonstration of Homeostatically Protected Mood (HPMood) in consciousness at rest. It is possible that HPMood is a specific manifestation in consciousness, of the more general brain phenomenon displayed by RSNs, representing non-specific neural activation at rest.

1.2 The difference between Positive Affect (PA) and Homeostatically Protected Mood (HPMood)

The term Positive Affect (PA) refers to a class of affects based solely on their valence (positive). In other respects, members of this class may be very different from one another. They may be either Emotions or Moods (see 1.1), and they may be either ‘activated’ or ‘deactivated’ as classified by Russell’s (1980) Circumplex Model (see 1.3).

Homeostatically Protected Mood (HPMood) comprises an amalgam of three affects as ‘Content’, ‘Happy’, and ‘Alert’. Together, these represent the mildly positively-activated portion of the circumplex. HPMood is described as follows:

1.2.1 HPMood comprises trait affect, generated as the phenotype of each person’s genetic ‘setpoint’. HPMood is a neuro-physiologically generated mood that comprises the simplest, constant,

non-reflective feeling (following Russell’s 1980 notion of ‘Core Affect’). It is hardwired for each individual, representing the tonic state of affect that provides the activation energy, or motivation, for behaviour (Cummins 2017a) .

1.2.2 HPMood is not modifiable by conscious experience, yet is a ubiquitous component of conscious experience (Cummins, Capic et al. 2018a).

1.2.3 HPMood is the dominant constituent of SWB, as first determined by Davern, Cummins et al. (2007).

1.2.4 Under normal resting conditions, the average level of HPMood represents a ‘set-point’ for each person, and their ‘set-point-range’ describes the limits within which homeostatic processes strive to maintain a steady level of SWB. This range is conceptually similar to the theoretical ‘attractor region’ of ecological systems (Holling 1973), and the propositions of Dynamic Systems Theory (e.g., Vallacher and Nowak 1997, Carver 1998). Thus, HPMood is the basic mood set-point that homeostasis seeks to defend.

1.2.5 The set-point for HPMood is a genetically-determined, individual difference. Within the general Australian population, these set-points have been shown to be normally distributed between 70 and 90 percentage points (pp), referenced to a 0-100pp scale, with an average of 80pp (Cummins, Li et al. 2014a, Capic, Li et al. 2018).

1.2.6 HPMood perfuses all self-report variables (Cummins, Capic et al. 2018a) but most strongly the rather abstract notions of self (e.g., I am a good person). These self-perceptions are held at an average strength of positivity that approximates the HPMood set-point. This common content of HPMood causes all self-report variables to correlate (Cummins, Capic et al. 2018a).

1.2.7 The level of HPMood for each person accounts for over 60 percent of the variance in SWB. Hence, the conventional scales to measure SWB (Satisfaction with Life Scale: Diener, Emmons et al. (1985); Personal Wellbeing Index: (International Wellbeing Group 2013) are heavily influenced by their HPMood content. This domination of SWB by HPMood challenges the conventional view that SWB is dominated by either personality or cognition, as has been generally reported in the literature (Emmons and Diener 1985).

1.2.8 While the affect generated as HPMood is at a constant level, our conscious awareness of affect in consciousness is highly varied. This reflects the character of SWB homeostasis as an open system, such that emotions are being constantly processed. These emotions are normally stronger source of affect than HPMood, thereby causing average experienced affect to be different from set-point. These excursions of affective experience beyond the setpoint, stimulate homeostatic forces with the role of returning experienced affect to its set-point. These forces are the "attractors" that attempt to retain SWB within its set-point-range (1.2.4). Thus, actual affective experience normally oscillates around its set-point and, as long as homeostasis is in control, chronic affective experience remains within its set-point-range for each person.

1.3 The Affective CircumplexThe dichotomy of negative and positive affect (‘Hedonic valence’), has been combined with the dichotomy of activated and deactivated, to produce the tetrachotomy of the Affective Circumplex (Russell 1980). In this conception, the ‘negative-positive’ dimension is characterised through adjectives classified on the unpleasant-pleasant continuum, while adjectives on the ‘activated-deactivated’ dimension represent the ‘high arousal-low arousal’ continuum.

1.3.1 The Affective Circumplex model is depicted by a circle, with the affective adjectives (affects) arranged around the periphery by the CIRCUM program. The circle is divided by the two orthogonal and bi-polar dimensions. On the horizontal axis the unpleasant affects are located around

the left hemicircle, and the pleasant affects around the right. On the vertical axis, high-arousal affects are located around the upper hemicircle, and low arousal affects around the lower.

1.3.2 When establishing the model, the CIRCUM program fixes one variable (usually pleasant) at 0 degrees. All other adjectives are then allocated polar angles with respect to this reference variable. One outcome is that the position of each adjective, on the circumference of the circle, depends on the degree of relatedness to the reference variable ‘pleasant’. So, ‘happy’ lies close to ‘pleasant’ and they are highly positively correlated. ‘Elated, on the other hand, is located closer to activation, and so demonstrate a low positive correlation. Sad is located at 180 degrees from happy, and so they are highly negatively correlated.

1.3.3 The circumplex model is a theoretical bipolar model of the underlying structure of affective experiences. This creates the assumption that the two independent and bipolar dimensions of Hedonic Valence and Arousal are constructed from 4 unipolar scales (pleasant vs. unpleasant and activated vs. deactivated), with each adjective being measured on a scale from 0-10. Hence, the centre of the circumplex represents no felt experience.

1.3.4 The positioning of adjectives on the circumplex is highly meaningful. Most obviously, consistent with its bi-polar structure, opposite-meaning feelings lie opposite one another across the circle. So, ‘unhappy’ is opposite ‘happy’, and ‘active’ is opposite ‘calm’. Less obviously, around the circumplex perimeter, similar (i.e. highly positively correlated) affects lie close to each other. This also applies to functional groupings. Thus, the three affects that form HPMood (content, happy, alert) lie within 250 of one another (from 3530 to 180), within the ‘Mildly Pleasant and Activated’ sector (Hartley-Clark 2014; Fig 20, p.183).

Comments on any of the above ideas are welcome

References: see end of Bulletin

Further discussion of material, for circulation to members, is invited. Send to: [email protected]

Substantive comments received by midnight Oz time, on Sunday 27th September, will be published in the following Bulletin. Such comments may offer a novel extension to the view

that has been put, an alternative and informed view, or offer a critique.

ACQol members are invited to send papers, queries or comments, on the topic of life quality, for distribution and discussion by members under these same conditions.

Brief reportSourced from the Analysis & Policy Observatory

Cortis, N., & Blaxland, M. (2020). Australia’s community sector and COVID-19: Supporting communities through the crisis. Sydney: Social Policy Research Centre , UNSW https://www.acoss.org.au/wp-content/uploads/2020/09/Australias-community-sector-and-Covid-19_FINAL.pdf.

This report provides information about the state of Australia’s community service sector during the COVID-19 pandemic. It is based on survey data collected in July 2020 from 744 community sector workers around Australia. Respondents included 201 frontline practitioners, 264 leaders of organisations (CEOs and senior managers) and 279 staff in other roles. The survey explored the ways community sector workers are experiencing the crisis; the changing circumstances and patterns of demand that services are confronting; and the ways the sector is responding to the high levels of poverty, social disadvantage and inequality in the community in the context of the pandemic.

Media news

https://www.acoss.org.au/wp-content/uploads/2020/09/Australias-community-sector-and-Covid-19_FINAL.pdf

Tanika Roberts [[email protected]]Executive Volunteer, Bulletin Co-Editor– Media

How to engage with life when you feel downhttps://psyche.co/guides/how-to-engage-with-life-when-you-feel-downLucy Foulkes

When you feel low or fed up, it’s tempting to shut down and do very little. You might cancel activities and social events, and choose passive options instead, such as staying in bed or watching TV. Of course, during the COVID-19 pandemic, many people have had their activities and social events cancelled for them. For anyone experiencing depression or low mood, these restrictions will have compounded their desire to withdraw, and the prospect of coming out of lockdown might feel daunting. Behavioural activation therapy works by breaking the cycle between inactivity and low mood.

ConferenceNotification supplied by Peter Achterberg [email protected]

OECD Webinar series: Measuring people's perceptions, evaluations and experienceshttp://www.oecd.org/statistics/lac-well-being-metrics.htm?

utm_source=Adestra&utm_medium=email&utm_content=Learn%20more&utm_campaign=Latest%20on%20well-being%2C%20September%202020&utm_term=sdd

Additional recommend reading‘Today’s Research’, edited by Dr Bob Murray, provides a weekly digest of research, mainly in biology and the social sciences. https://fortinberrymurray.us13.listmanage.com/subscribe?u=6a411e8ce902df7c73232a8f2&id=4ee17adb2b&mc_cid=e1cac10cf4&mc_eid=e9a2e6453f

Membership changesSangeetha Thomas <[email protected]>[email protected]

Membership RegistrarWelcome to new membershttp://www.acqol.com.au/members

Mrs. Anne Marie HodgesDoctoral student, American College of EducationKeywords: Personal wellbeing, Self-care models, Job satisfaction, Leadership, Professional development, Mentoring/coaching, Education

Mr Ian GoodRetiredKeywords: Interested bystander

Dr. Micah AltmanResearch Scientist, Center for Research on Equitable and Open Scholarship

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Keywords: Open science, Methodology, Information science, Information and communication technology and politics

-----------------------ReferencesBower, G. H., & Forgas, J. P. (2000). Affect, memory, and social cognition. In E. Eich, J. F. Kihlstrom, G. H.

Bower, J. P. Forgas, & P. M. Niedenthal (Eds.), Cognition and Emotion (pp. 87-168). New York: Oxford University Press.

Buchanan, T. W. (2007). Retrieval of emotional memories. Psychological Bulletin, 133(5), 761-779.

Capic, T., Li, N., & Cummins, R. A. (2018). Confirmation of Subjective Wellbeing Set-points: Foundational for Subjective Social Indicators. Social Indicators Research, 137(1), 1-28. Retrieved from 10.1007/s11205-017-1585-5.

Carver, C. S. (1998). Resilience and thriving: Issues, models, and linkages. Journal of Social Issues, 54, 245-266.

Cummins, R. A. (2017a). Subjective Wellbeing Homeostasis - Second edition. In D. S. Dunn (Ed.), Oxford Bibliographies Online. Retrieved from http://www.oxfordbibliographies.com/view/document/obo-9780199828340/obo-9780199828340-0167.xml

Cummins, R. A. (2020). A neurophysiological link to a basic aspect of psychology: Maybe. Australian Centre on Quality of Life Bulletin, 4 (36) Retrieved from http://www.acqol.com.au/publications#bulletins.

Cummins, R. A., Capic, T., Hutchinson, D., Fuller-Tyszkiewicz, M., Olsson, C. A., & Richardson, B. (2018a). Why self-report variables inter-correlate: The role of Homeostatically Protected Mood. Journal of Wellbeing Assessment, 2, 93-114. doi:10.1007/s41543-018-0014-0

Cummins, R. A., Li, L., Wooden, M., & Stokes, M. (2014a). A demonstration of set-points for subjective wellbeing. Journal of Happiness Studies, 15, 183-206. doi:10.1007/s10902-013-9444-9

Davern, M., Cummins, R. A., & Stokes, M. (2007). Subjective wellbeing as an affective/cognitive construct. Journal of Happiness Studies, 8(4), 429-449. doi:10.1007/s10902-007-9066-1

Diener, E., Emmons, R. A., Larsen, R. J., & Griffin, S. (1985). The satisfaction with life scale. Journal of Personality Assessment, 49, 71-75.

Ekkekakis, P. (2013). The measurement of affect, mood, and emotion: A guide for health-behavioral research. Cambridge: Cambridge University Press.

Emmons, R. A., & Diener, E. (1985). Personality correlates of subjective well-being. Personality and Social Psychology Bulletin, 11, 89-97.

Forgas, J. P. (1995). Mood and judgment: the affect infusion model (AIM). Psychological Bulletin, 117(1), 39-66.

Hartley-Clark, L. (2014). Investigating the Affective Core of Subjective Wellbeing: the Circular Way. (PhD ), Deakin University Melbourne Campus http://dro.deakin.edu.au/view/DU:30074804.

Holling, C. S. (1973). Resilience and stability of ecological systems. Annual Review of Ecological Systems, 4, 1-23.

International Wellbeing Group. (2013). Personal Wellbeing Index Manual: 5th Edition. Retrieved from http://www.acqol.com.au/instruments#measures

Oatley, K., & Johnson-Laird, P. N. (1987). Towards a cognitive theory of emotions. Cognition and Emotion, 1, 29-50.

Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39, 1161-1178.

Russell, J. A. (2003). Core affect and the psychological construction of emotion. Psychological Review, 110(1), 145-172.

Russell, J. A., & Feldman Barrett, L. F. (1999). Core affect, prototypical emotional episodes, and other things called emotion: Dissecting the elephant. Journal of Personality and Social Psychology, 76(5), 805-819.

Scherer, K. R. (2000). Psychological models of emotion. In J. C. Borod (Ed.), The neuropsychology of emotion (pp. 137-162). New York: Oxford University Press.

Vahdat, S., Khatibi, A., Lungu, O., Finsterbusch, J., Büchel, C., Cohen-Adad, J., . . . Doyon, J. (2020). Resting-state brain and spinal cord networks in humans are functionally integrated. PLoS Biology, 18(7), e3000789.

Vallacher, R. R., & Nowak, A. (1997). The emergence of dynamical social psychology. Psychological Inquiry, 8, 73-99.

ACQol Bulletin Vol 4/38: 170920 Bulletin of the Australian Centre on Quality of Lifehttp://www.acqol.com.au/Editor: Robert A. Cummins [[email protected]]Back-issues of the Bulletin are available at http://www.acqol.com.au/publications#bulletins


Paper for private studyThe attached paper, on the topic of life quality, is sent to you for your personal private study and discussion within ACQol. You are prohibited from further distributing this paper to any

other person.The Affect System

Background: Researchers engaged in Subjective Wellbeing (SWB) research are fond of asking questions about the felt-strength of affect (feelings). For example, ‘How happy do you feel?’ with estimates recorded on a linear scale. The technology is simple, but understanding the responses that people make, beyond the simple number on a scale, is not. So, the intellectual challenge, of comprehending the structure and function of this form of subjective experience in theoretical and empirical terms, has drawn the attention of many accomplished researchers.

What is the affect system? Cacioppo and Berntson (1999) correctly describe its operation as being inextricably linked with the cognitive (information processing) system. The affect system signals the significance of stimuli, while the two systems combine to direct attention and learning, guide automatic decision making, to trigger thoughts and choreograph conscious behavior.

How is the affect system structured? One of the earliest attempts to provide structure was the ‘Circumplex model of affect’ (Russell 1980). Here, two orthogonal axes are projected onto a circle. The horizontal axis depicts valence (unpleasant to pleasant) while the vertical axis


depicts activation (activated to deactivated). Then, through the application of a statistical procedure (see Russell), which allocates each affect an angle based on its content of the two dimensions, the affect’s position is determined on the circle perimeter.

This systematic positioning of the affects around the circumplex has functional implications. Those affects lying close to one another (e.g. ‘happy’ and ‘content’) demonstrate a similarity of the affective experience and are positively correlated, while those which are opposite in meaning (e.g. satisfied and dissatisfied), lie opposite one another and are negatively correlated. This has fuelled one of the enduring controversies in affect theory. Is happiness strength best represented empirically and conceptually as unipolar (e.g. from 0 to 10), or as bipolar with sadness (from 10 happy, to 0, to 10 sad)?

One approach taken by investigators, is to explore the question of whether people can feel happy and sad at the same time. The Circumplex view (e.g. Russell and Carroll 1999) says no. It proposes that happiness and sadness are bipolar opposites, so the experience of happy and sad are mutually exclusive (they exist on the same scale of measurement). Thus, no such ‘mixed’ experience should exist. However, several lines of enquiry run counter to this view. First, even assuming affect is experienced as unipolar, rapid oscillation between happy and sad could give a ‘mixed’ experience. Second, as Larsen, McGraw et al. (2001) point out, experimental conclusions in favour of bipolar or unipolar experience are based on complex statistical procedures, applied to data collected under controlled conditions, where the authors have a single, limited aim to establish uni- or bi-polarity. It is therefore possible that happy/sad in open experience follows more complex rules than investigators have allowed in their methodology. Thus, they conclude, the determination of either unipolar or bipolar can be an artefact of methodological limitations. In conclusion, the circumplex is a limited tool to investigate the conceptual structure of affect.

A second limitation is that the circumplex does not speak directly to the relationship between affect and cognition. Russell (1980), however, acknowledges that this link must be considered in any broader view of affective experience. He proposes the thesis “that affective experience itself is the end product of a cognitive process that has already utilized that same cognitive structure for affect (p.1176). This claim, that cognition shares the same circumplex structure as affect, seems strained. However, it would be less strained if it is the cognition, rather than the affect, that is driving the positioning of affects on the circumplex.

What seems evident at this juncture is that the circumplex has played a strong role in providing a taxonomy of affect, as well as generating research into the character of affect at the level of measurement scales. It is also evident that a different model is required to provide a broader understanding of the affect experience.

Reference: Cacioppo, J. T., & Berntson, G. G. (1999). The affect system: architecture and operating characteristics. Current Directions in Psychological Science, 8, 133-137.

Author summary: “Affect has traditionally been treated as the conscious subjective aspect of an emotion. As such, it represents the output of a set of information processing operations. There is a voluminous literature on the effects of affective states and their causes and concomitants, but recent developments have drawn attention to the affect system as an object of study in its own right” (p.136).

Comment on Cacioppo & Berntson (1999) The Evaluative Space Model (ESM: Cacioppo and Berntson 1999) represents a quite different view from that provided by the circumplex. Within ESM, the affect system is considered as a whole, superordinate system, which subsumes the measurement issues of uni- and bi-polar variables. The ESM still involves a dichotomy, but here it concerns the functional components involved in positive (approach) and negative (avoidant) information processing.

The idea of such a basic dichotomy is consistent with deep evolutionary origins. Positive affect (PA: approach) and negative affect (NA: avoid) represent the two most basic, and phylogenetically ancient, affects. They are evident even in amoeba, which does not have a single neuron, let alone a nervous system. So, PA and NA do not necessarily involve cognition – in the amoeba anyway.

Rising up the phylogenetic tree, it is evident that the process of evolution is highly parsimonious. Good genetic programs that enhance fitness are retained, then modified as needed by a newly evolved species. So, both PA and NA have survived into humans, carrying this same crucial, basic information.

Moreover, because PA and NA carry such essential information, they normally exist concurrently in consciousness. This concurrence is normally not noticeable because one affect is so much stronger than the other. But in some circumstances (such as a funeral), PA and NA are both strong, and so will noticeably compete for attention within consciousness. This produces awareness of mixed emotions.

Variations on PA and NA have also evolved, as represented by the other affects. But they differ from PA and NA in having an evolved attachment to cognition, designed to refine the experience of ‘avoid’ and ‘approach’ into a certain class of stimuli relevant to each emotion. This refined PA/NA meaning is evident in the the extent to which any two cognitive/emotional complexes can be concurrent in consciousness, as predicted by Russel’s affective circumplex. Affects close to one another on the circumplex, such as ‘agitated’ and ‘anger’ are more likely to be concurrently experienced. However, the emotions of ‘agitated’ and ‘content’, which are positioned on opposite sides of the circumplex, have quite different cognitive attachments. Their affective/cognitive structures are so different from one another, that they are cannot exist concurrently in consciousness.

These considerations are accommodated within the Evaluative Space Model (ESM). The model is built around two ‘evaluative processors’ each of which has its own output (‘activation function’). This output has the characteristic of being negatively accelerated. That is, it creates high activation when first stimulated, which then decrements over time. This is consistent with habituation and adaptation.

This model also adopts a bipolar approach to the activation function, such that positive and negative activation are reciprocal (p.135). As a given stimulus increases positivity activation, it also decreases negativity activation. However, this bipolar proposal sits uncomfortably with the authors’ acknowledgement of mixed emotions in ‘intense situations’. They refer to these as “conflicting feelings … being the predictable consequence of co-activated positivity and negativity …” (p.135). The inconsistency of such dual activation producing mixed emotions, with their claimed bipolar activation function, is not explained.

Their model also proposes that the positivity activity function is set at a higher level than the negative function. Such that at low levels of stimulus input there is a ‘positivity offset’, such that the resting level of positivity is higher. This is consistent with the ubiquitous presence of Homeostatically Protected Mood causing positivity in self-reports (Cummins 2017a).

In relation to the other ‘evaluative processor’, their model proposes that, when stimulated, the negativity activity function rises more quickly than the positivity function (i.e., there is a ‘negativity bias’)…” (p.135). The authors suggest that both of these two ‘biases’ have evolutionary significance. The positivity offset provides approach motivation in a neutral environment, while the negativity bias allows a heightened sensitivity to negative information, thereby allowing a strong and rapid response to perceived threat. This is certainly a useful perspective for understanding.

In summary, the Evaluative Space Model is consistent with the theory of subjective wellbeing homeostasis (Cummins 2017a). The Homeostasis Theory is more explicit in describing the ‘positivity bias’ as comprising Homeostatically Protected Mood, and in describing the role of that mood within positive thoughts concerning the self. The Model is more explicit in describing the separation of PA and NA, and the differential activity function characteristics of each, along with their evolutionary significance. Notably, neither model advances the unipolar-bipolar controversy, which issue appears to be a distractor. Perhaps it is time to simply agree that measures of affect should use unipolar scales because bipolar scales impose an uncertain structure on the measured variables. With this issue shelved, research efforts can be better directed at furthering understanding the affect system as a whole.


Further discussion of this paper, for circulation to members, is invited. Send to: [email protected]




Brief reportsSourced from the Analysis & Policy Observatory

Dudgeon, P., Bray, A., Darlaston-Jones, D., & Walker, R. (2020). Aboriginal Participatory Action Research: An Indigenous Research Methodology Strengthening Decolonisation and Social and Emotional Wellbeing, Discussion Paper. Melbourne: The Lowitja Institute https://www.lowitja.org.au/content/Document/Lowitja-Publishing/LI_Discussion_Paper_P-Dudgeon_FINAL3.pdf.

This discussion paper explicates the concepts and application of a critically reflexive and transformative Indigenous Research Methodology (IRM) — Aboriginal Participatory Action Research (APAR) — designed to centre and increase Indigenous voice and ‘epistemic self-determination’ in Indigenous research and psychology. The intent is to justify and legitimate Indigenous knowledges and methodologies as authentic, rightful, valued, and critical

components of transformative research in Indigenous contexts to build self-determination in communities, strengthen Indigenous social and emotional wellbeing (SEWB) and Australian Indigenous psychology.

This report was recommended to us by Antonina Mikocka-Walus <[email protected]>

Purser, R. (2019, June 14). The Mindfulness Conspiracy. In: The Guardian, https://www.theguardian.com/lifeandstyle/2019/jun/14/the-mindfulness-conspiracy-capitalist-spirituality.

It is sold as a force that can help us cope with the ravages of capitalism, but with its inward focus, mindful meditation may be the enemy of activism.

Media newsTanika Roberts [[email protected]]

Executive Volunteer, Bulletin Co-Editor– Media

How to be Indistractable – Manage your inner triggers to enjoy greater focus and a fuller lifehttps://psyche.co/guides/to-become-indistractable-recognise-that-it-starts-within-you Nir Eyal

Smartphones didn’t invent distraction – they’re just the latest culprit. Before that, we blamed television. And before that, it was the telephone, or comic books, or the radio. Still, our present feels different, with the sources of distraction seeming greater in number and more universal. Distraction often begins from within, not without. Most of the time distraction is your brain avoiding challenging feelings such as boredom, loneliness, insecurity, fatigue and uncertainty (aka internal triggers or root causes). Therefore the fix comes from identifying and managing the psychological discomfort that leads us off track and responding in a more advantageous manner.


Turner, B. (2020). The world's greatest psychological experiment: When the loneliness epidemic met the coronavirus pandemic. Good Weekend: Sydney: Sydney Morning Herald. https://www.smh.com.au/national/the-world-s-greatest-psychological-experiment-when-the-loneliness-epidemic-met-the-coronavirus-pandemic-20200806p55j8g.html?utm_content=FEATURES&mc_cid=20a5be527e&mc_eid=e9a2e6453f.

Bob Murray quotes from the article: “loneliness is the near-inevitable consequence of long-term, systemic insistence on economies over societies; freedoms – individual and market – over community.”


https://www.smh.com.au/national/the-world-s-greatest-psychological-experiment-when-the-loneliness-epidemic-met-the-coronavirus-pandemic-20200806p55j8g.html?utm_content=FEATURES&mc_cid=20a5be527e&mc_eid=e9a2e6453f







https://www.theguardian.com/lifeandstyle/2019/jun/14/the-mindfulness-conspiracy-capitalist-spirituality

https://www.theguardian.com/lifeandstyle/2019/jun/14/the-mindfulness-conspiracy-capitalist-spirituality

Membership RegistrarWelcome to new membershttp://www.acqol.com.au/members

Mr Izzie ConsultingCEO, Izzie Shmukler Consulting (ISConsulting)Keywords: Well-Being, Employee safety, Coaching, Wellness

Mr Rodney MullerStrath Steam, Strath SteamKeywords: Just interested in stats

Mrs Heather SmythKeywords: Freedom from religion, Climate change action.

Ms Margaret BowdenKeywords: Quality of life, Ageing

Mr Kenneth NewmanRetired, N/aKeywords: Survey participant

Ms Lynda GraceKeywords: Health, Wellbeing, Nutrition

Mr Sakari KainulainenSpecialist, Diaconia University of Applied SciencesKeywords: life satisfaction; happiness; SWB; marginalized subpopulations

Mr Dante SteffanAircraftman, DefenceKeywords: N/A

Dr. John BarileAssociate Professor, University of Hawaii at ManoaKeywords: Health-related quality of life; community psychology; program evaluation; social determinants

Dr Clara V BardoletKeywords: Subjective wellbeing; Work-life balance; Quality of work; Domains-of-life satisfaction

Mr Douglas MaroldKeywords: NA

Mrs Alyssa Cairns


Keywords: Wellbeing

Mr Geoffrey KirtonKeywords: General

Mr Naveed Ali QureshiStudent, Comsats university IslamabadKeywords: Wellbeing quality of life

Mr Bruce WoottenRetiredKeywords: Disability services

Professor Emeritus Alex C. MichalosDirector, Institute for Social Research and Evaluation, University of Northern British ColumbiaKeywords: Quality of Life; Political Science; Philosophy

-----------------------ReferencesCacioppo, J. T. and G. G. Berntson (1999). "The affect system: architecture and operating characteristics." Current Directions in Psychological Science 8: 133-137.

Cummins, R. A. (2017a). Subjective Wellbeing Homeostasis - Second edition. Oxford Bibliographies Online. D. S. Dunn. New York Oxford University Press.

Larsen, J. T., A. P. McGraw and J. T. Cacioppo (2001). "Can people feel happy and sad at the same time?" Journal of personality and social psychology 81(4): 684-696.

Russell, J. A. (1980). "A circumplex model of affect." Journal of Personality and Social Psychology 39: 1161-1178.




other person.

fMRI: What can it really tell us?


I am grateful to Peter Achterberg <[email protected]> for drawing this paper to our attention

Background: This topic is a follow-up to last week’s discussion of functional magnetic resonance imaging (fMRI). Let me find context by going back to the time before fMRI.

On 4 August 1875, Richard Caton reported to the British Medical Association in Edinburgh (Caton 1875), that he had used a galvanometer to observe electrical impulses from the surfaces of living brains in the rabbit and monkey. Note that this event preceded both the development of inhalation anaesthesia in the 1940s (https://en.wikipedia.org/wiki/Anesthesia#History) and the first set of guidelines for ethics committees, which came from the 1964 ‘Declaration of Helsinki’, for the World Medical Association. However, despite the extraordinary potential of his discovery, that seems obvious in hindsight, Caton’s observations resulted in little medical interest during his lifetime. It took another 50 years before the potential of Caton’s discovery was recognized by Hans Berger (1929), who reported the recording of systematic electrical signals from the surface of the scalp, in the form of Alpha waves. Berger’s discovery led to the development of the electroencephalogram (EEG), as the first non-invasive, physiological method for investigation brain functioning (discounting phrenology!) by measuring the brain’s electrical activity.

But new discoveries are more easily dismissed than accepted. As reported by Millet (2002) “When Berger described his technique for recording the electrical activity of the human brain from the surface of the head in 1929, the medical and scientific establishments met him with incredulity and overwhelming scepticism, when they did not ignore him altogether, only accepting the human EEG after Berger's discovery was replicated by the Cambridge physiologist Lord Adrian in 1934” (p.1).

The EEG measures voltage fluctuations resulting from ionic current within the neurons of the brain. In medicine, it is normally used to measure the brain's spontaneous electrical activity over a period of time, as recorded from multiple electrodes placed on the scalp. In its hay-day it was regarded as a wondrous ‘window into the brain’, which would reveal great details and insights into human thought processing. However, the reality has been rather more subdued, as might be expected from such a gross instrument, measuring the average electrical activity of millions of neurons. Today its use is generally at a gross-level of functioning, such as to diagnose epilepsy, sleep disorders, depth of anesthesia, and brain death.

Then along came Functional Magnetic Resonance Imaging (fMRI). First demonstrated by Ogawa, Lee et al. (1990), it represents a more sophisticated approach to studying brain operating characteristics. fMRI allows measurement of the functional activation of the brain, as detected by measuring the extent of tissue perfusion with blood, blood-volume changes, or changes in the concentration of oxygen. The latter, blood oxygenation level–dependent (BOLD) contrast mechanism, is currently the mainstay of human neuroimaging, as a non-invasive technique for measuring brain functions,

As with the early use of EEG some 50 years earlier, much early excitement was, and still is, generated by the potential of this new ‘window into the brain’. A 2010 review (VanDenHeuvel and Pol) of resting-state fMRI functional connectivity, extols the virtues of this technique claiming new insights and concluding “resting-state fMRI studies examining

functional connectivity between brain regions have revealed new fundamental insights in the organization of the human brain and provide a new and promising platform to examine hypothesized disconnectivity effects in neurologic and psychiatric brain diseases”(p.530) such as “Alzheimer's disease, dementia, schizophrenia and multiple sclerosis” (p.519). Not a harsh word of critique is spoken.

Can any technique really be so flawless? A reality check is needed.

Reference: Logothetis, N. K. (2012). What We Can and What We Can’t Do with fMRI. Paper presented at the Society for Neuroscience: 2012 Short Course II MRI and Advanced Imaging in Animals and Humans (pp.7-14).

Author summary: The interpretation of fMRI signals in brain research, and by extension, the utility of fMRI, critically depends on factors such as signal specificity and spatial and temporal resolution. However, the limitations of fMRI derive from the circuitry and functional organization of the brain as well as inappropriate experimental protocols that ignore this organization.

Comment on Logothetis (2012)There is a tendency in psychology, at least, to be overawed by ‘hard science’, and this paper is a wake-up call. The reality, is that the interpretation of fMRI data is just as liable to over-interpretation as the data from any other branch of science. The author of this critique is a senior neuroscientist at Stanford University. Logothetis has an h-index of 112 and his work, largely in the field of fMRI, has received over 58,000 citations.

His review is a methodical critique. The main points he makes are:

1. With 1010 neurons and 1013 connections in the cortex alone, attempting to study dynamic interactions between subsystems, at the level of single neurons, makes little sense, even if it was technically feasible. Instead, it is more relevant to understand the differential activity of functional subunits. This, however, requires that the fMRI can accurately map such subunits, and record their activity validly. There are many sources of error in such endeavours that involve, for example, problems with signal specificity, which concerns whether the generated maps reflect actual neural changes, and spatial and temporal resolution.

2. Does the activation of an area mean it is truly involved in the task at hand? This question implies that we understand what sort of neural activity, in a given area, would unequivocally show its participation in a studied behavior. But such simple interpretations are usually unwarranted. The outputs from neural processors represents, inter alia, the balance between excitatory and inhibitory processes. Yet the fMRI is unable to make such a distinction. It also cannot easily differentiate between function-specific processing and neuromodulation, or between bottom-up and top-down signals.

3. Brain connectivity is bidirectional and involving both local and distant connections. The relative influence exerted by these connections varies over time and between tasks. Such complexity cannot be resolved by fMRI.

Certainly this paper is 8y old, and much technical improvement can occur over such a period, but the author also make it clear that the problems of interpretation are not technical

limitations. Rather, such interpretive difficulties may be intractable, as a function of the vast complexity of the information processor under investigation. Logothetis ends his paper with the following conclusions:

- The limitations of fMRI are not related to physics or poor engineering and are unlikely to be resolved by increasing the sophistication and power of the scanners. The limitations have neural origins.

- The fMRI signal cannot easily differentiate between function-specific processing and neuromodulation, or between bottom-up and top-down signals, and it may potentially confuse excitation and inhibition.

- The magnitude of the fMRI signal cannot be quantified to accurately reflect differences among brain regions, or among tasks within the same region. The cause of this problem is not our current inability to accurately estimate the fMRI signal, but the fact that such signals are sensitive to the size of the activated population of neurons. This population size may change as the sparsity of neural representations varies spatially and temporally. In cortical regions, especially, these issues make it impossible to deduce the exact role of the area in the task at hand. Moreover, neuromodulation is also likely to affect the ultimate spatiotemporal resolution of the fMRI signal.

In summary, “the limitations of fMRI derive from the circuitry and functional organization of the brain as well as inappropriate experimental protocols that ignore this organization” (p.13).






News of Mother[One data file, 26 longitudinal and 35 cross-sectional surveys, 5,500 variables and over 8 million responses]

Executive Volunteer – Data ManagementSarah Khor [[email protected]]

Executive Data Analyst

On 10th September we sent out the third-wave of our longitudinal study (LONG-3) to around 1,000 continuing respondents, and to another 1,000 respondents recruited from our most recent cross-sectional study, who we are hoping will agree to join LONG-3. The resulting data should be especially interesting. Melbourne city (around 5 million people) has been in stage-4 lockdown (stay at home!) for the past 6 weeks, and we have just heard that this level of lockdown will likely continue for another 2 to 4 weeks. But even more interesting from a research perspective, the rest of Australia (around 20 million) has a lower level (more relaxed) of lockdown, or almost none at all, depending on the state/territory. So, we will have

differential within-survey comparisons, and three previous years of comparisons for around 500 people who are already in LONG-3. Watch this space.


Nickson, S., Thomas, A., & Mullens-Burgess, E. (2020). Decision making in a crisis: First responses to the coronavirus pandemic. London: Institute for Government.https://apo.org.au/sites/default/files/resource-files/2020-09/apo-nid308011.pdf

The coronavirus pandemic required the UK government to take high-stakes decisions under conditions that make good policy making hard. This report examines decisions made by the government about three key aspects

of its early response to the pandemic: the economic support package, Covid-19 testing and the commitment to run 100,000 tests per day by 30 April, and the lockdown and school closures. We examine how these decisions

were taken and how that affected the outcomes.



In Defense of the Psychologically Rich Lifehttps://www.scientificamerican.com/article/in-defense-of-the-psychologically-rich-life/ Scott Barry Kaufman

“I do not accept any absolute formulas for living. No preconceived code can see ahead to everything that can happen in a man’s life. As we live, we grow, and our beliefs change. They must change. So I think we should live with this constant discovery. We should be open to this adventure in heightened awareness of living. We should stake our whole existence on our willingness to explore and experience.”—Martin Buber. At the end of the day, there is no one singularly acceptable path to the good life. You have to find a path that works best for you.



Membership RegistrarWelcome to new membershttp://www.acqol.com.au/membersDr Angelina Wilson FadijiResearch Specialist, Human Sciences Research CouncilKeywords: Positive Psychology, Meaning in life, Relational well-being

Dr Ricardo Pagan






https://apo.org.au/sites/default/files/resource-files/2020-09/apo-nid308011.pdf

University of MalagaKeywords: Wellbeing, Disability, Time use, Leisure, Labour

Professor Justin HollanderProfessor, Tufts UniversityKeywords: Urban planning, Happiness, Biometrics, Social listening

-----------------------ReferencesCaton, R. (1875). "The electrical currents of the brain." British Medical Journal: Forty-Third Annual Meeting of the British Medical Association 2: 278.

Millet, D. (2002). The Origins of EEG. International Society for the History of the Neurosciences. http://www.bri.ucla.edu/nha/ishn/ab24-2002.htm.

Ogawa, S., T.-M. Lee, A. R. Kay and D. W. Tank (1990). "Brain magnetic resonance imaging with contrast dependent on blood oxygenation." proceedings of the National Academy of Sciences 87(24): 9868-9872.

VanDenHeuvel, M. P. and H. E. H. Pol (2010). "Exploring the brain network: a review on resting-state fMRI functional connectivity." European neuropsychopharmacology 20(8): 519-534.




other person.

A neurophysiological link to a basic aspect of psychology: Maybe

Background: Our research focus, in recent decades, has been fundamentally driven by a reductionist approach, aimed at understanding the operational character and composition of Subjective Wellbeing (SWB). This journey began with the realization that reported results from measures of SWB, derived from diverse response scales (e.g. 1-5, 0-7, 1-11, etc), could be standardized by the application of a simple formula (International Wellbeing Group 2013; Section 5.2). This converts the scale mean score into a ‘percentage of the scale maximum’, and the resulting variable is referred to as ‘percentage points’ (pp). In 1995, Cummins demonstrated that when Western population estimates of SWB were compared, they fell within a 10pp range with a mean of 75pp.The author speculated that this result could signal the existence of a psychological, homeostatic mechanism” (p. 193).


The next step in understanding came from demonstrating that the major correlate of SWB was not personality, as had been long prescribed (Diener, Sandvik et al. 1992), but rather was affect in the form of a mood (Davern, Cummins et al. 2007). Following Russell (1980), this mood was initially referred to as ‘Core Affect’. However, when Russell started to use Core Affect to refer to both mood and emotion (Russell 2009), that term was no longer appropriate. Moreover, the ‘homeostatic model of SWB’ was starting to take shape (Cummins 2003). So ‘core affect’ was replaced by ‘Homeostatically Protected Mood (HPMood)’ (Cummins 2010a). This new term not only referred exclusively to mood, thereby excluding emotion, but also linked HPMood to homeostatic management.

At that time there was still uncertainty as to the precise composition of HPMood, and several years of experimentation followed. Only very recently have we settled on the group of three affects as Content, Happy, and Alert, as best representing the HPMood construct (Cummins 2018b).

The next step in understanding involved the different contributions of mood and emotion in SWB. At a conceptual level it made logical sense that HPMood represents the stable, genetically determined, individual difference which is unchanging. It is the phenotype of each person’s genotype, as their setpoint. The role of HPMood is to provide a low-level, background positive affect. This proposal accounts for both the chronic stability of SWB and its normal positivity.

Emotion, on the other hand, is the variable component of SWB. It is the product of both information processing by sensory receptors (percepts), informing about the environment, combined with information processing concerning thoughts about the self. This stream of cognitive/affective information includes a level of affect that is normally stronger than HPMood. The role of this emotion is to direct attention to new information, by influencing the overall level and valence of affect in consciousness.

While this scenario has a logical appeal, the crucial evidence for setpoints is missing. The issue of ‘setpoints for SWB’ had been the topic of speculation and inference for many years prior, however no empirical evidence for their existence had been produced. This changed with the publication of two papers which first demonstrated the existence of setpoints for HPMood (Cummins, Li et al. 2014a), and then provided confirmation (Capic, Li et al. 2018). Note that this is not setpoints for SWB, but for the component of SWB that is HPMood.

One final aspect of this new understanding completes the story to date. This is the pervasive presence of HPMood in thoughts about the self. Because HPMood is an individual difference, it is held at the same level within all self-report variables (eg optimism, self-esteem, etc) for each person. Then, because this level of HPMood is different for each individual, when data are grouped as a population sample, the HPMood content causes the variable to correlate with one another (the 'crud factor': Cummins, Capic et al. 2018a). This can be demonstrated by statistically removing the HPMood content (see ACQol Bulletin Vol 4/31: 300720 :http://www.acqol.com.au/publications#bulletins). This issue of the Bulletin shows the results from four separate studies confirming that at least half of the variance connecting 10 different self-evaluative variables is HPMood. Moreover, in about half of these, the reduction is so severe as to render the initially significant correlation, non-significant.

In summary of this journey, the reductionist approach has moved the understanding of SWB from a vague cognitive/affective variable, to one with a clear division into mood and emotion components, with the stable HPMood (molecule) comprising the three affective (atoms) of content, happy, and alert. Moreover, the background influence of HPMood is present in all abstract evaluative thoughts about the self, causing all self-report variables to significantly inter-correlate.

So, two considerations flow from this story based on the principle of evolutionary parsimony (see phylogenetics: Wikipedia), wherein well-functioning systems tend to be retained during evolution and adapted for new purposes. So;(a) Why has HPMood evolved? To form the basis of motivation and to allow effective cohesive processing of positive thoughts.(b) Might HPMood be the psychological manifestation of a more general biological property of neural tissue; which is the need to maintain a minimal level of neural activity even when not engaged in functional outcomes?(c) Might, then, HPMood be a psychological manifestation of ‘resting-state functional neural networks’?

Reference: Vahdat, S., Khatibi, A., Lungu, O., Finsterbusch, J., Büchel, C., Cohen-Adad, J., . . . Doyon, J. (2020). Resting-statebrain and spinal cord networks in humans are functionally integrated. PLoS Biology, 18(7), e3000789.

Author summary: In the absence of any task, both the brain and spinal cord exhibit spontaneous intrinsic activity organised in a set of functionally relevant neural networks. Here, we show that the brain and spinal cord activities are strongly correlated during rest periods, and specific spinal cord regions are functionally linked to consistentlyreported brain sensorimotor Resting State Networks. The functional organisation of these networks follows well-established anatomical principles, including the contralateral correspondence between the spinal hemicords and brain hemispheres as well as sensory versus motor segregation of neural pathways along the brain–spinal cord axis. Thus, our findings reveal a unified functional organisation of sensorimotor networks in the entire central nervous system (CNS) at rest.

Comment on Vahdat et al (2020)Using functional Magnetic Resonance Imaging, the authors claim to have produced “the first neuroimaging evidence for the existence of resting-state, functional networks spanning both the brain and spinal cord structures… In summary, our findings reveal a close relationship between spontaneous activities of different brain areas with musculoskeletal afferent and efferent intrinsic activities, which may reflect a functional property of the entire central nervous system (CNS) at rest” (p.9).

Comment: The authors have documented a whole-CNS (brain and spinal cord), background-level of ‘spontaneous’ neural activity, within brain regions that receive information from (afferent) muscles and associated structures, as well as within brain regions sending (efferent) information to these same regions. The associated neural structures are called Resting State Networks (RSNs). RSNs are identified within spatially and anatomically distinct regions with related functioning.

“Spontaneous modulations of … signals … in the absence of any overt task or stimulation have been well characterised in the human brain [1,2]. These slow fluctuations partition the resting brain into temporally synchronised networks of spatially distinct areas… (RSNs), which mimics the clusters of brain regions that are co-activated during the performance of different sensorimotor and cognitive tasks [2]…(p.1-2).

Comment: The RSNs have two characteristics. First, each RSN corresponds with a set of neurologically-connected brain regions (spatially distinct areas) that cooperate in performing sensorimotor and related cognitive tasks. Second, when resting, each RSN is characterised by patterns of slow fluctuations of neural activity that are characteristic of each particular network.

“Although still speculative, this suggests that the spontaneous activities of the afferent and efferent signals during resting-state periods might keep the brain and spinal cord connections functionally active and follow the same organisation as that in the active task performance” (p.11).

Comment: The purpose of these RSNs is to keep the areas concerned ‘functionally active’ during periods of quiescence, rather than to convey specific information. The general organization of each RSN corresponds with the same neural network that is otherwise engaged is receiving or sending information.

“However the intrinsic functional connectivity of the cerebrospinal networks in the absence of any task or external stimulation has never been investigated” (p.1-2).

Comment: While such ‘spontaneous neural activity’ in RSNs has been previously described, this study is the first to observe such activity in the entire CNS (brain plus spinal cord) ‘in the absence of any task or external stimulation’.

Conclusion: It would appear possible that there could be an evolutionary linkage between the generation of ‘spontaneous intrinsic activity’ in ‘resting-state functional networks’ throughout the CNS at rest, and our demonstration of the general activation of Homeostatically Protected Mood in consciousness at rest. Perhaps HPMood is a specific manifestation in consciousness, of the more general brain phenomenon of non-specific neural activation at rest?

I wrote to the Vahdat team, explaining setpoints and HPMood, expressing interest in the possibility of a linkage with their findings. Their entire reply was “I don't think there is any relationship between our finding and yours.”







Cassells R., Dockery M., Duncan A., Kiely D., Kirkness, M., Twomey C., . . . Seymour, R. (2020). The Early Years: Investing in Our Future: Focus on Western Australia Report Series, No. 13. Perth: Business School, Curtin University https://bcec.edu.au/assets/2020/08/BCEC-The-Early-Years-Investing-in-Our-Future-Report-2020-270820.pdf.

This report highlights the critical importance of investment in the early years, illustrating that disadvantage starts during pregnancy and extends through toddlerhood and in the preschool years, with significant differences in child outcomes evident across various domains including mental health, language development and early learning, well before formal school commences.

A new early learning disadvantage index highlights the extent of inequality of early learning opportunities across Western Australia and Australia. The divide between the most advantaged and disadvantaged areas is staggering. Children living in the most disadvantaged communities are far less likely to be attending preschool, more likely to be developmentally vulnerable, less likely to have access to the internet at home and if they are attending preschool, are generally facing higher preschool student-to-teacher ratios.



How the brain builds a sense of self from the people around ushttps://theconversation.com/how-the-brain-builds-a-sense-of-self-from-the-people-around-us-new-research-141844 Sam Ereira

As we grow older, we learn what other people think, feel and want – and adapt to it. Our brains are really good at this – we copy computations inside the brains of others. But how does the brain distinguish between thoughts about your own mind and thoughts about the minds of others? Our ability to copy the minds of others is hugely important. When this process goes wrong, it can contribute to various mental health problems. You might become unable to empathise with someone, or, at the other extreme, you might be so susceptible to other people’s thoughts that your own sense of “self” is volatile and fragile.


Report from the ACQol siteGoogle Analytics inclusive period: August 2020





https://bcec.edu.au/assets/2020/08/BCEC-The-Early-Years-Investing-in-Our-Future-Report-2020-270820.pdf

Number of users who initiated at least one session during the date range: 1,413Number of sessions: 1,799


Membership RegistrarWelcome to new memberhttp://www.acqol.com.au/members

Matt BevanOutcomes Measurement Lead, Uniting NSW.ACTKeywords: Wellbeing and social progress

-----------------------ReferencesCapic, T., Li, N., & Cummins, R. A. (2018). Confirmation of Subjective Wellbeing Set-points:

Foundational for Subjective Social Indicators. Social Indicators Research, 137(1), 1-28. Retrieved from 10.1007/s11205-017-1585-5.

Cummins, R. A. (1995). On the trail of the gold standard for life satisfaction. Social Indicators Research, 35(2), 179-200. doi:10.1007/BF01079026

Cummins, R. A. (2003). Normative life satisfaction: Measurement issues and a homeostatic model. Social Indicators Research, 64(2), 225-256.

Cummins, R. A. (2010a). Subjective wellbeing, homeostatically protected mood and depression: A synthesis. Journal of Happiness Studies, 11, 1-17. doi:10.1007/s10902-009-9167-0

Cummins, R. A. (2018b). Measuring and interpreting subjective wellbeing in different cultural contexts: A review and way forward. New York: Cambridge University Press.




Diener, E., Sandvik, E., Pavot, W., & Fujita, F. (1992). Extraversion and subjective well-being in a US national probability sample. Journal of Research in Personality, 26(3), 205-215.



Russell, J. A. (2009). Emotion, core affect, and psychological construction. Cognition & Emotion, 23, 1259-1283.




http://www.acqol.com.au/instruments#measures



other person.

Alone in Finland

Background: Humans are naturally social animals. In evolutionary time, they needed to form collectives to survive (see, e. g. Davey, Chen et al. 2009, Tsai and Dzorgbo 2012). Indeed, before the 1950s, no society had large numbers of people living alone (Klinenberg 2013). There is nothing surprising about this – many species have evolved the same survival strategy of a social-bonding imperative. More surprising that since the1950’s, a sizable proportion of the human race has done something no other social species has done – people started living alone through choice. By 1981, 23% of all American households comprised just one person (U.S. Bureau of the Census 1981).

At face value, this is an unexpected trend. It would be strange indeed to discover that basic neural programming is being trumped by cultural change. Yet at a societal level, the related trend of decreasing social capital has been well documented within economically developed countries (Putnam 2000), whose iconic book ‘Bowling Alone’ has received over 65,000 citations. But decreased bridging social capital is not restricted to single living: Contemporary nuclear families can also be disengaged from their host society.

One explanation of this trend to single living, is that the phrase ‘living alone through choice’ is ambiguous. If this referred to a true ‘choice from other attractive options’, then it might be expected that the people who ‘choose’ to live alone would have a higher, or at least equivalent level of subjective wellbeing (SWB), compared to people living with others. But the reverse is true. Despite some of the great minds in history having chosen the reclusive lifestyle (https://en.wikipedia.org/wiki/Recluse), presumably from a position of real choice, for the most part people living alone have a significantly low-level of SWB compared to people living with their partner.

It is therefore disconcerting that, currently in Australia, about a quarter of households comprise single people, and 12% of Australian adults live alone (deVaus and Qu 2015a). The people who stand-out within this group are middle-aged men who live alone. They are more likely to have lower levels of education, less likely to be in the labour force, to have lower income and to have less prestigious (and lower paying) jobs. de Vaus & Qu interpret this in terms of such men being less reliable breadwinners and thus less attractive as partners. Maybe so, but there is a bigger picture to consider as to the reason for this ‘living alone’ trend.

Since the 1950’s, when the move to single living was gaining momentum, it is evident that, for the first time, people with few resources had a realistic choice of living alone. Society was increasingly tolerant of such an arrangement and people could afford to do it, at least within those countries providing appropriate social support. Not that such people live well (Davidson, Saunders et al. 2018). The poverty line in Australia is 50% of median household disposable income, yielding a very frugal $433 a week for a single adult living alone. The single person pension (plus government supplements) approximates this income (Davidson,

https://en.wikipedia.org/wiki/Recluse

Saunders et al. 2018). Clearly these people would choose a different lifestyle if they could, yet they have ‘chosen’ to live alone.

The upshot is that, on average, people living alone have one of the lowest levels of SWB found within Australian demographic groups (Cummins, Walter et al. 2007a). They largely comprise disadvantaged, vulnerable people. This has been demonstrated by numerous studies which include finding a high prevalence of common mental disorders (Jacob, Haro et al. 2019) and a poor capacity to recover from natural disasters which adversely affect their resources (Ardalan, Mazaheri et al. 2010, Calvo, Arcaya et al. 2015). Clearly, therefore, the general level of wellbeing, of people living alone, and who therefore spend much of their time alone, is a useful barometer of Government success in providing for its most vulnerable citizens. It therefore follows that surveys which concern these people, with a view to understanding the nature and extent of the difficulties they face, need to be methodologically impeccable.

Reference: Anttila, T., Selander, K., & Oinas, T. (2020). Disconnected Lives: Trends in Time Spent Alone in Finland. Social Indicators Research, 150, 711–730.

Author summary: Discussions about social isolation have been extensive over the past few decades. A less sociable nature of social ties has been identified in Western societies. The phenomenon has been associated with demographic changes such as aging and living alone as well as changes in the use of new technologies. In this study we employ representative Finnish Time Use Surveys from three decades, 1987–1988 (n = 1887), 1999–2000 (n = 2673) and 2009–2010 (n = 1887) to examine the trends in social isolation, measured as time spent alone. Our results showed that between 1987 and 2010 the time spent alone increased by124 min per day. The increase was linear and occurred in nearly all population groups.Structural factors, such as aging and an increase in the number of single households, are strongly associated with increased time spent alone. Time spent alone has increased, especially during leisure activities. Specifically, time spent watching television and using computers is associated with the decreasing tendency for face-to-face interaction.

Comment on Anttila et al (2020)The focus of this paper is on the proportion of time people spend ‘alone’ and, so, has special relevance for people who live alone. However the authors struggle to explain why, exactly, ‘time spent alone’ is a useful measure of human behaviour. They state:

[time spent alone] “is an objective measure that … serves as an indicator of social isolation” (p.715).

“The trends and consequences of social isolation [are considered] along with the parallel concept of loneliness” (p.711).

“Several studies have established that there is only a low correlation (r = 0.10–0.25) between loneliness and social isolation (references)” (p.713).

In other words, the variable being measured (time spent alone) is not a reliable proxy for loneliness. Yet the link concerning the negative associations of loneliness are mentioned on eight separate occasions in the introduction, involving nine references, certainly leading the reader to consider the relevance of loneliness to the research being described. Further confusion is provided by the statement “… we emphasize that time spent alone cannot be

judged as a purely good or bad phenomenon” (p.725). While this is necessarily true, it does not assist understanding.

A further concern with the above extracts, is the assumption that ‘time spent alone’ is not sociable. This is unwarranted. Interacting with others using social media is highly sociable. The sociability of time alone cannot be determined in the absence of relevant other data.

Moving now to their methodology, by far the most arresting feature of this paper, is the process of data collection. While the authors provide scant detail, a more informative description is provided by Statistic Finland. They explain that the Finnish Time Use Survey, which supplied the data used by Anttila et al, form part of the ‘Harmonised European Time Use Surveys’ and their 2019 Guidelines are available from:https://ec.europa.eu/eurostat/documents/3859598/9710775/KS-GQ-19-003-EN-N.pdf/ee48c0bd-7287-411a-86b6-fb0f6d5068ccThis address leads to a 233 page Eurostat document which provides a detailed description of the entire Time Use Surveys methodology, which has been used repeatedly by collaborating European countries over several decades.

The methodological description below is drawn from the simpler description provided by Time Use Survey 2009 https://www.stat.fi/til/akay/akay_2014-12-01_men_001_en.html

The overview is as follows: “The time use survey is an interview survey in which the respondents keep an accurate diary of their time use over a two-day period…the survey also studies the daily and weekly rhythms of time use, and the time spent together with other people” (https://www.stat.fi/til/akay/meta_en.html).The second attachment to this email, ‘Diary instructions adults 2020 Finland’, provides the diary guidelines provided to respondents.

Other details of the survey methodology include:

(a) “Participants kept accurate records of their time use for two 24-hour periods. For example, the survey looks at working time, time spent on domestic work, sleeping and having meals, free time activities as well as how people spend time together and where the activities take place. It also examines how the time of the day, day of the week and seasons affect the rhythms of time use”.

(b) “The 2009 survey was conducted over 12-month period (between April and May) and targeted those aged 10y or over.”

(c) “In addition to the interviews, data were collected by means of time use diaries distributed to the respondents. The members of a household kept a record of their time use on one weekday and one Saturday or Sunday.”

(d) The diary was acceptably returned by 41 per cent of respondents. The respondents wrote in their diaries a freely worded description of what they were doing with an accuracy of 10 minutes. It was possible to record two simultaneous activities in the diary. Time spent together with other members of the household and acquaintances was also recorded. The location where the activity took place was determined in connection with data classification”.

https://www.stat.fi/til/akay/meta_en.html

https://www.stat.fi/til/akay/akay_2014-12-01_men_001_en.html

https://ec.europa.eu/eurostat/documents/3859598/9710775/KS-GQ-19-003-EN-N.pdf/ee48c0bd-7287-411a-86b6-fb0f6d5068cc

https://ec.europa.eu/eurostat/documents/3859598/9710775/KS-GQ-19-003-EN-N.pdf/ee48c0bd-7287-411a-86b6-fb0f6d5068cc

Comments in relation to this description are as follows:1. The demand on respondent time is several magnitudes higher than might be considered reasonable. Respondents are expected to document multiple behaviors, for every 10 minute period, over two 24 hour periods.

1.1 The respondents were not expected to actually provide their data at 10 minute intervals. Their instructions are to “Keep the diary with you and fill it in several times during the day.” The reliability of such data is likely to be a major concern. Such recall will be biased not only by memory capacity but also by emotions. For a review of state-dependent memory see (Bower 1981).

1.2 The respondent demands are so excessive that their responses will necessarily be estimates. To assume (see d above) that this methodology yields data with an “an accuracy of 10 minutes” is pure fantasy. Data reliability is not discussed within the provided material.

1.3 Requiring 10y children to complete this task will yield invalid data. The authors do not state approval from their university ethics committee.

1.4 The frequency and duration of activities outside the home will be influenced by the climate. Helsinki lies in the south of the country, with day length varying from 6h in winter to 19h in summer. At Finland's northernmost point, the sun does not set for 73 consecutive days during summer, and does not rise at all for 51 days during winter (Wikipedia). Thus, over the course of a year, substantial seasonal differences in such activities will be expected. Yet the data for this population study were averaged over the one year period of data collection.

1.5 If respondents actually responded each 10 minutes, all responses would concern describing their experience of completing the form. For other respondents, concern with the demands of form completion and how it represents their life, would undoubtedly cause an abnormal pattern of time expenditure. Thus, the collected data are not only unreliable but also invalid as a measure of normal time use.

In summary, both the reliability and validity of the results from this report are highly questionable. The interpretation of ‘time spent alone’ is uncertain, but is not a proxy for either loneliness or social isolation. It seems timely for Eurostat to reconsider its support for Time Use Surveys in their current form.



Substantive comments received by midnight Oz time, on Sunday 30th August, will be published in the following Bulletin. Such comments may offer a novel extension to the view



Website additions and changes

Tanja Capic <[email protected]>WebMaster

RE: http://www.acqol.com.au/publications#Open-access

Over the past few weeks we have been refining the information and presentation at our new Open-Access site. We think it is now about as good as we can devise, so we will value further ideas from you. Please take a look at the site. If you have any views about how the content or

presentation could be improved, we will greatly appreciate you letting us know.


Farmer, J., & etal. (2020). Mapping the impact of social enterprise on disadvantaged individuals and communities in Australia’s regional cities. Melbourne: Swinburne University https://apo.org.au/sites/default/ files/resource-files/2020-08/aponid303490.pdf

There is ongoing discussion about the impact of social enterprises on the health and wellbeing of individuals and communities (Roy et al. 2014; Farmer et al. 2012). Here, we explore where wellbeing is realised in social enterprises, which helps to explain how and why social enterprises help to realise benefits.

In this project, we examine social enterprises through the frame of wellbeing. The concept is applied to explore positive experiences of life that are about more than simply freedom from physical illness (see Munoz et al. 2015). Wellbeing is about having the ‘resources’ to enable flourishing lives (Atkinson & Scott 2015). The concept aligns with a social model of health, which places health in its social context (Blaxter 1990; Bowling 1991; Gattrell et al. 2000; Cattell et al. 2008)



How culture can help you through dark timeshttps://www.artshub.com.au/news-article/features/covid-19/megan-sheehy/how-culture-can-help-you-through-dark-times-260226Megan Sheehy

While it is important to try to remain optimistic about the future of humanity, we also need space and time to process the more difficult emotions we are experiencing. The arts are one of the best realms we have for exploring the dark and complex parts of the human condition. Whether we are consuming it or creating it, or a mixture of both, this surge towards creativity, culture and the arts serves as an important reminder of its transformative power in our lives.

Additional recommend reading‘Today’s Research’, edited by Dr Bob Murray, provides a weekly digest of research, mainly in biology and the social sciences. https://fortinberrymurray.us13.listmanage.com/subscribe?


https://www.artshub.com.au/news-article/features/covid-19/megan-sheehy/how-culture-can-help-you-through-dark-times-260226

https://www.artshub.com.au/news-article/features/covid-19/megan-sheehy/how-culture-can-help-you-through-dark-times-260226


http://www.acqol.com.au/publications#Open-access

u=6a411e8ce902df7c73232a8f2&id=4ee17adb2b&mc_cid=e1cac10cf4&mc_eid=e9a2e6453f


Membership RegistrarWelcome to new membersProfessor Mark WoodenProfessorial Fellow, and Director, HILDA Survey project, University of MelbourneKeywords: Life satisfaction, Mental health, Work, Longitudinal data, Survey methods

Mr Marco DugatoSenior Researcher, Università Cattolica del Sacro Cuore di Milano- TranscrimeKeywords: Security; Crime; Fear of crime; Victimisation; Urban life

Dr. Ida KubiszewskiAssociate Professor, Australian National UniversityKeywords: Resilience, Environmental influences

Prof Paul DugdaleAssoc Prof Public Health, ANUKeywords: Wellbeing

Dr Elizabeth RiegerAssociate Professor, Research School of Psychology, Australian National UniversityKeywords: Clinical psychology, Wellbeing, Obesity, Eating disorders

-----------------------ReferencesArdalan, A., Mazaheri, M., Vanrooyen, M., Mowafi, H., Nedjat, S., Naieni, K. H., & Russel, M.

(2010). Post-disaster quality of life among older survivors five years after the Bam earthquake: implications for recovery policy. Ageing and Society, 31(02), 179-196.

Bower, G. H. (1981). Mood and memory. American Psychologist, 36, 129-148.

Calvo, R., Arcaya, M., Baum, C. F., Lowe, S. R., & Waters, M. C. (2015). Happily ever after? Pre-and-post disaster determinants of happiness among survivors of Hurricane Katrina. Journal of Happiness Studies, 16(2), 427-442.

Cummins, R. A., Walter, J., & Woerner, J. (2007a). Australian Unity Wellbeing Index: Report 16.1 - “The Wellbeing of Australians - Groups with the highest and lowest wellbeing in Australia”. Melbourne: Australian Centre on Quality of Life, School of Psychology, Deakin University. http://www.acqol.com.au/publications.

Davey, G., Chen, Z., & Lau, A. L. D. (2009). ‘Peace in a Thatched Hut—that is Happiness’: Subjective Wellbeing Among Peasants in Rural China. Journal of Happiness Studies, 10, 239-252. doi:10.1007/s10902-007-9078-x

http://www.acqol.com.au/publications



Davidson, P., Saunders, P., Bradbury, B., & Wong, M. (2018). Poverty in Australia, 2018. ACOSS/UNSW Poverty and Inequality Partnership Report No. 2. Sydney: ACOSS.

deVaus, D., & Qu, L. (2015a). Demographics of living alone. Melbourne: Australian Institute of Family Studies: http://apo.org.au/node/53372.

Jacob, L., Haro, J. M., & Koyanagi, A. (2019). Relationship between living alone and common mental disorders in the 1993, 2000 and 2007 National Psychiatric Morbidity Surveys. PloS one, 14(5), e0215182.

Klinenberg, E. (2013). Going solo: The extraordinary rise and surprising appeal of living alone. New York: Penguin.

Putnam, R. D. (2000). Bowling alone: The collapse and revival of American community. New York: Simon and Schuster.

Tsai, M. C., & Dzorgbo, D. B. S. (2012). Familial Reciprocity and Subjective Well‐being in Ghana. Journal of Marriage and Family, 74(1), 215-228.

U.S. Bureau of the Census. (1981). Marital status and living arrangements: March I980 (Current Population Report, Series P-20, No. 365). Washington, DC: Government Printing Office.




other person.

The (in)validity of resilience measures

Background:There is a virtual zoo of positive constructs in psychology. Some have been around for many decades, forming indeed the bedrock of psychological research involving self-report data. These are, for example, self-esteem, optimism, positive affect, extraversion, etc. Joining these terms in recent years, often under the umbrella of positive psychology, are a plethora of new terms. These are inevitably claimed as valid unique constructs, such as Self-Determination (Deci, Ryan et al. 2015) – for a critique see Cummins (2016g), Grit (Duckworth, Peterson et al. 2007)- for a critique see Maul (2017), etc.

The psychometric weakness, evidenced by all of such measures, is uncertain discriminant validity. That is, while these positive constructs clearly have shared variance, which causes them to typically inter-correlate at around .4 to .6, their content of unique construct variance is less certain, and yet is used as the defining quality of each measure considered as an


http://apo.org.au/node/53372

independent construct. Also uncertain, or at least not usually unspecified, is the source of this shared variance. However, evidence is accumulating that much of this shared variance may be the ubiquitous presence of Homeostatically Protected Mood (HPMood).

As far as is known, all positive self-report variables contain HPMood (Cummins, Capic et al. 2018a) in addition to the unique variance derived from the cognitive/affective construct being measured. HPMood is a composite-affective variable, comprising the three affects: content, happy and alert (Davern, Cummins et al. 2007). The level of this HPMood is stable within-person, as the phenotype of each person’s setpoint. This mood then combines in consciousness with whatever cognitive/affective emotion is being experienced as an acute response to a self-report question. The net result is that when people are asked to rate themselves on the item ‘I take a positive attitude toward myself’, their response comprises the combination of a personally-stable mood and a variable emotion. Crucially, then, in order to understand what is driving the correlation between ‘self-esteem’ and ‘life satisfaction’, the shared mood and unique emotion variance must be separately estimated. This methodology has been described (Cummins, Li et al. 2014a, Capic, Li et al. 2018).

An understanding derived from this technology, is that the correlation between two variables cannot be used as evidence that the unique content of the two constructs is significantly related. If their shared HPMood variance is strong, and their shared unique cognitive/emotion variance is weak, the correlation will be strong (Cummins, Capic et al. 2018a).

A further complication is introduced by the positive self-report measure of ‘resilience’. Here, careful definition of the term is crucial. A recent review (Cummins and Wooden 2014) has adopted the parsimonious, generic definition of ‘resilience’ (Merriam-Webster 2020) as: ‘an ability to recover from or adjust easily to misfortune or change’. From this definition, in empirical terms, measuring the strength of ‘resilience’ must involve a longitudinal study design. This may be either prospective, such that variables are studied for their ability to protect against the pathological effects of future stressful events, or retrospective, wherein variables are studied in relation to past events. If the prospective design is used, then no conclusions regarding resilience can be drawn until the participants have actually experienced a stressful event. In any event, any measure of resilience for research purposes must involve a longitudinal study design.

Reference: Kunicki, Z. J., & Harlow, L. L. (2020). Towards a Higher-Order Model of Resilience. Social Indicators Research, 151, 329–344.Author summary: Resilience theory often conceptualizes resilience as a higher-order construct that draws upon other constructs which individuals use to adapt when facing adverse circumstances... the current study developed and tested a higher-order model of resilience with underlying components from a trait resilience perspective. Two samples were gathered from Mechanical Turk (n = 500) and undergraduate college students (n = 720) who completed measures of 8 constructs theorized to underlie resilience, and a previously validated measure of resilience. Using exploratory and confirmatory factor analysis, results suggested six constructs (purpose in life, self-esteem, life satisfaction, cognitive flexibility, proactive coping, and social support) comprise a higher-order model of resilience… We found evidence for validity by correlating the higher-order factor in our sample with the already validated resilience measure. These findings provide support for a higher-order model of resilience with at least six underlying components…

Comment on Kunicki (2020)

The authors define resilience as a personality dimension “resilience was viewed from a trait perspective” (p.331). While this definition provides self-approval for the authors to measure resilience from cross-sectional data, as argued above, such measures are inadequate as a valid measure of the resilience construct. The ‘ability to recover from or adjust easily to misfortune or change’ (Merriam-Webster 2020) requires the involvement of an event and an assessment of success in managing the self. When the definition is reduced to that part of the construct which refers to personality, this causes the measure of resilience to behave as a general positive construct. Predictably, then, their measure of ‘resilience’ correlates with other positive constructs (see Background), as the authors’ results demonstrate. However, this approach is uninformative about the true nature of resilience and also confuses causation with outcome.

This problem has been well articulated by Fayers and colleagues (Fayers, Hand et al. 1997, Fayers, Groenvold et al. 1998, Fayers and Machin 2007) who distinguish between indicator and causal variables. Indicator variables (e.g. Life Satisfaction) constitute the measured end-state. Causal variables are the conditions (e.g. resilient personality, money availability, social support, extraversion, etc) that cause the end-state to change (e.g. Life satisfaction). Logically, then, it makes no sense to combine indicator and causal variables, yet this is precisely what Kunicki & Harlow have done.

The authors selected 8 of 20 positive constructs on the grounds that they “were identified as the most common constructs theorized to underlie resilience” (p.331). Their review methodology is not described, but their selected constructs are: purpose in life, self-esteem, life satisfaction, cognitive flexibility, proactive coping, social support, locus of control, and stress management. This list mixes together causal (e.g cognitive flexibility) and indicator (life satisfaction) variables; an invalid procedure. But this is not the only methodological problem.

One of their aims is “to investigate evidence for validity between the higher-order resilience factor and the already-established resilience scale (Wagnild and Young 1993)” (p.336). As argued in ‘Background’, the finding of a super-ordinate factor resulting from the combination of the eight measures is practically assured due to the common presence of Homeostatically Protected Mood (HPMood). However, whether a link between this super-ordinate factor andthe ‘Resilience Scale’ (Wagnild and Young 1993) has meaning beyond a link between positive constructs, depends on the assumption that the scale is a valid measure of resilience.Certainly a highly favorable review of this scale, by the scale author (Wagnild 2009), which has been cited over 700 times, tends to the affirmative. So, the question of validity is worth further examination.

The introduction to Wagnild and Young (1993) defines 'Resilience' as connoting “emotional stamina, courage and adaptability in the wake of life's misfortunes” (p.166). The 25 item scale was developed de novo from a qualitative analysis of interviews with “women who had adapted successfully following a major life event’ (p.167), with keywords from the interviews matched against 5 pre-conceived ‘definitions and perspectives’ from the extant resilience literature. Items were then refined using criteria of ‘Internal consistency, test-retest reliability, construct and concurrent validity’. Their reported analysis, based on data from an elderly sample in the USA, is an exploratory factor analysis applied to cross-sectional data. They extract two factors named Personal Competence and Acceptance of Self and Life. The following can be noted:

1. The validity of a ‘resilience’ scale cannot be verified through cross-sectional data. The studies included in the 2009 review are also cross-sectional.

2. The two discovered factors match neither their definition of resilience nor their ‘perspectives’ drawn from their literature review.

3. The items which comprise their two scales are the typical positive-abstract-personally referential items found in many other scales comprising positive psychological constructs. For example “I keep interested in things’ and ‘My life has meaning’. In summary, there is no compelling evidence that their ‘Resilience Scale’ measures resilience as a distinct, from a generalized sense, of positivity about the self.

A further apparent problem lies with their data. They measured ‘Life Satisfaction’ using the Satisfaction With Life Scale (Diener, Emmons et al. 1985), presumably using the original response scale of 1-7. If so, then both of their samples are pathological. Using the formula in the manual of the Personal Wellbeing Index (International Wellbeing Group 2013: Section 5.2), which converts scale responses to a 0-100 percentage point standard measure, their MTurk sample scored 37.33pp and the USA Student sample 40.5pp. Comparing this against PWI norms based on Australian data (Khor, Fuller-Tysziewicz et al. 2020), values <50pp are abnormally low and exhibiting psychometric invalidity (Richardson, Fuller-Tyszkiewicz et al. 2014). They are also abnormally low in terms of USA undergraduate data, which values are generally around 65-70pp (e.g. Christopher and Gilbert 2010: 62.7pp, Fowers, Mollica et al. 2010: 69.3pp, Allan and Duffy 2014: 71.1pp).

Their sample variance estimates are also highly abnormal. The sample standard deviations for the three USA studies are: 16.09; 16.07; and 17.47pp, respectively. The Kunicki estimates are: MTurk: 13.88; Students: 9.05pp. The student variance, at least, is seriously abnormal. In summary, the Life Satisfaction estimates reported by Kunicki (2020) are either in error or pathological. If these concerns extend to the other variables, the reliability of the entire study is thrown into doubt.

Their final analysis used a ‘correlated CFA model to investigate evidence for validitybetween their higher-order resilience factor and the “already-established resiliencescale (Wagnild and Young 1993)” (p.336). They report “This model showed acceptable fit with most indices, χ2 (13) = 519.57, p < 0.001, CFI = 0.90, RMSEA = 0.18: 90% CI [0.17, 0.19], SRMR = 0.07” (p.336). Their claim of ‘acceptability’ misrepresents these statistics. According to Hu and Bentler (1999), who the current authors cite, CFI should be >.95 and RMSEA should be <.06.

In summary, Kunicki & Harlow have inappropriately used cross-sectional data to generate a new ‘Resilence scale’, have mistakenly claimed an extant scale (Wagnild and Young 1993) as valid to measure resilience, have used data with questionable reliability, have mixed together causal and indicator variables, and have misrepresented evidence that their ‘higher-order model of resilience’ is a valid representation of the construct. This paper does not contribute to an understanding of resilience.



Substantive comments received by midnight Oz time, on Sunday 23rd August, will be published in the following Bulletin. Such comments may offer a novel extension to the view



New publications by membersCummins, R. A. (2020) Quality of life of adults with an intellectual disability. Current Developmental Disorders Reports, 7(3), 182-187. https://doi.org/10.1007/s40474-020-00205-x

Quality of life can be measured both objectively, by frequencies and quantities, and subjectively through feelings. The subjective dimension is the most difficult to measure and the topic of this review. Subjective wellbeing is commonly measured by asking how “happy” or “satisfied” people feel on a standardized set of questions. One crucial requirement is that these questions are the same for everyone, whether they have a disability or not. This ensures equivalent standards for judging high and low life quality. The Personal Wellbeing Index meets these requirements. It contains seven items, three of which form the “Golden Domain Triangle” as satisfaction with money, relationships, and achieving in life. These three “Golden Domains” represent the key resources supporting life quality for both disabled and non-disabled people. For service provision to be maximally effective in facilitating life quality, it should target sufficiency in these areas.

Member’s website newsRuut Veenhoven

World Database of Happiness

The website of the World Database of Happiness has been renewed. The address is still https://worlddatabaseofhappiness.eur.nl.

The old site will be maintained for the time being and remains available at https://worlddatabaseofhappiness- archive .eur.nl

The improved search functions on the new site will help you find your way in the growing body of knowledge on happiness in the sense of satisfaction with one’s life as a whole. Try and enjoy!

Please check whether all your publications on this subject are in the Bibliography. Send us a copy in pdf of missing papers.

Consider joining the project as an associated researcher or have us enter your findings

If you want to know more about the technique of this finding archive and its application in research synthesis, attend the e-seminar at the virtual 2020 conference of the International Society for Quality of Life Studies (ISQOLS) on Friday August 28, 15h30-18h00 Central European Time. The program is on attach.

https://doi.org/10.1007/s40474-020-00205-x

Ruut VeenhovenEmeritus professor of Social Conditions for Human HappinessErasmus University Rotterdam, Netherlands. Erasmus Happiness Economics Research Organization EHEROHomepage: https://personal.eur.nl/veenhoven


Stanford, J. (2020). The Robots are NOT Coming (And why that’s a bad thing…). Canberra: Centre for Future Work at the Australia Institute. https://apo.org.au/sites/default/files/resource-files/2020-08/ apo-nid307476.pdf

Public discussion about the ‘future of work’ has been strongly influenced by a widespread fear that accelerating technological change is likely to result in the displacement of large numbers of workers by robots and other machines. The application of many new technologies – like machine-learning, new optical and mobility technologies, and nanotechnology – allows machines to undertake a much wider range of productive tasks. It also allows them to be assigned duties which require flexibility and judgment, not just specific programmable instructions.

Once these machines are deployed in the real-world economy, surely the implications for employment must be dire. Robots are capable of performing a greater variety of tasks, faster and better than humans, in many cases for lower cost. And they never go on strike. Some studies have estimated that as many as half of all jobs in modern industrial economies are subject to a high probability of automation within the next decade.This paper argues that, while the adoption of new production technologies can certainly disrupt and in some cases reduce employment, there are many reasons why feared mass technological unemployment is unlikely to prevail in practice:



Finding Opportunities for Insight and Growth During Isolationhttps://www.mindful.org/finding-opportunities-for-insight-and-growth-during-isolation/Kelly Barron

Seclusion makes room for renewal and insight. For centuries, human beings have used seclusion as a means of understanding fundamental truths about the world and ourselves. Meditation teacher Shinzen Young suggested to reframe the pandemic predicament of social isolation as a time of seclusion during which their mindfulness practices could deepen. Provided our basic needs get met, such a subtle shift in perspective has the power to lighten our load psychologically.







Membership Registrar

Welcome to new membersDr. Leire Iriarte Director, El Buen VivirKeywords: Subjective Wellbeing, Sustainability, Transformations,

Professor Peigang WangPopulation and Health Research Center, Director, Wuhan UniversityKeywords: Wellbeing

-----------------------ReferencesAllan, B. A. and R. D. Duffy (2014). "Examining moderators of signature strengths use and well-being: Calling and signature strengths level." Journal of Happiness Studies 15(2): 323-337.

Capic, T., N. Li and R. A. Cummins (2018). "Confirmation of Subjective Wellbeing Set-points: Foundational for Subjective Social Indicators." Social Indicators Research 137(1): 1-28.

Christopher, M. S. and B. D. Gilbert (2010). "Incremental validity of components of mindfulness in the prediction of satisfaction with life and depression." Current Psychology 29(1): 10-23.

Cummins, R. A. (2016g). Self-Determination Theory and the Theory of Subjective Wellbeing Homeostasis: An examination of congruence. ACQol Open-Access Publications by Members. Melbourne, Australian Centre on Quality of Life, Deakin University. http://www.acqol.com.au/publications#Open-access.

Cummins, R. A., T. Capic, D. Hutchinson, M. Fuller-Tyszkiewicz, C. A. Olsson and B. Richardson (2018a). "Why self-report variables inter-correlate: The role of Homeostatically Protected Mood." Journal of Wellbeing Assessment 2: 93-114.

Cummins, R. A., L. Li, M. Wooden and M. Stokes (2014a). "A demonstration of set-points for subjective wellbeing." Journal of Happiness Studies 15: 183-206.

Cummins, R. A. and M. Wooden (2014). "Personal resilience in times of crisis: The implications of SWB homeostasis and set-points." Journal of Happiness Studies 15: 223-235.

Davern, M., R. A. Cummins and M. Stokes (2007). "Subjective wellbeing as an affective/cognitive construct." Journal of Happiness Studies 8(4): 429-449.

Deci, E. L., R. M. Ryan, P. P. Schultz and C. P. Niemiec (2015). being aware and functioning fully. Handbook of Mindfulness: Theory, Research, and Practice. K. W. Brown, J. D. Creswell and R. M. Ryan. New York, Guilford Press: 112-129.

Diener, E., R. A. Emmons, R. J. Larsen and S. Griffin (1985). "The satisfaction with life scale." Journal of Personality Assessment 49: 71-75.

Duckworth, A. L., C. Peterson, M. D. Matthews and D. R. Kelly (2007). "Grit: perseverance and passion for long-term goals." Journal of personality and social psychology 92(6): 1087-?

Fayers, P. M., M. Groenvold, D. J. Hand and K. Bjordal (1998). "Clinical impact versus factor aanlysis for quality of life questionnaire construction." Journal of Clinical Epidemiology 51(3): 285-286.


Fayers, P. M., D. J. Hand, K. Bjordal and M. Groenvold (1997). "Causal indicators in quality of life research." Quality of Life Research 6: 393-406.

Fayers, P. M. and D. Machin (2007). Quality of life: The assessment, analysis and interpretation of patient-reported outcomes (2nd ed.). . West Sussex, England, John Wiley and Sons Ltd.

Fowers, B. J., C. O. Mollica and E. N. Procacci (2010). "Constitutive and instrumental goal orientations and their relations with eudaimonic and hedonic well-being." The Journal of Positive Psychology 5(2): 139-153.

Hu, L. and P. M. Bentler (1999). "Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives." Structural equation modeling: a multidisciplinary journal 6(1): 1-55.

International Wellbeing Group (2013). Personal Wellbeing Index Manual: 5th Edition. Melbourne, Australian Centre on Quality of Life, School of Psychology, Deakin University http://www.acqol.com.au/instruments#measures.

Khor, S., M. Fuller-Tysziewicz and D. Hutchinson (2020). Australian normative data for Subjective Wellbeing. Personal Wellbeing Index Manual: 6th Edition. International Wellbeing Group. R. A. Cummins. Melbourne, Australian Centre on Quality of Life, Deakin University http://www.acqol.com.au/publications#Open-access

Maul, A. (2017). "Rethinking traditional methods of survey validation." Measurement: Interdisciplinary Research and Perspectives 15(2): 51-69.

Merriam-Webster. (2020). "Online dictionary." Retrieved 16 November 2019, from http://www.merriam-webster.com.

Richardson, B., M. D. Fuller-Tyszkiewicz, A. J. Tomyn and R. A. Cummins (2014). "The Psychometric equivalence of the Personal Wellbeing Index for normally functioning and homeostatically defeated Australian adults." Journal of Happiness Studies 15 (1): 43-56.

Wagnild, G. (2009). "A review of the Resilience Scale." Journal of nursing measurement 17(2): 105-113.

Wagnild, G. M. and H. Young (1993). "Development and psychometric evaluationof the Resilience Scale." Journal of Nursing Measurement 1(2): 165-178.



Open-access publishing in ACQolhttp://www.acqol.com.au/publications#Open-access

At long last our website offers ACQol members open-access publication of their documents at no cost to either the author or user.

We have been gradually developing this site over the past 6-months. The key people responsible have been Tanja Capic <[email protected]> -WebMaster, Iestyn Polley <[email protected]> - Executive Web Developer , Josipa Crnic <[email protected]> - Scholarly Services Librarian, and myself.


http://www.merriam-webster.com/




The aim of this site is to allow access to otherwise relatively-inaccessible documents. The criteria for acceptance of documents for publication are as follows:

1. The author agrees that they relinquish all control over the document once it is published. This is made clear at the start of this webpagehttp://www.acqol.com.au/publicationsstating our Creative Commons licenceCreative Commons Attribution-NonCommercial 4.0 International LicenseThis statement essentially covers all of the material we publish on these pages, which includes our reports, their associated data, etc.

2. The published document must directly address the issue of life quality in some clear scientific way, as judged by the WebMaster and ACQol Director together.

3. The kinds of documents the site may contain are:3.1 Conference papers either unpublished or previously published in inaccessible conference proceedings.3.2 Unpublished manuscripts3.3 Previously published papers with no copyright.3.4 Previously published papers which are inaccessible through Google Scholar. 3.5 Previously published papers with approval from the publisher.3.6 Lectures or informal talks, either as text or power-point.

4. The documents will be republished in whatever form they are submitted as: word, pdf, or power-point. The documents will not be edited for spelling, grammar or format. However, documents will not be accepted if they lack coherence.

5. Each document will be preceded by the information required on the submission form.

6. Documents will not be accepted if they use offensive language, including blasphemy, offensive images, or personal vilification.

The ACQol Open-Access Publishing facility is now operational and documents are invited.

Authors are invited to submit via: http://www.acqol.com.au/publications#Open-access

A beginning


An initial collection of eight documents has been published and listed below. These have been selected opportunistically, to give some indication of the diversity of documents which are considered acceptable for publication. The ‘comments’ are for orienting purposes and restricted to this Bulletin issue. They will not normally be employed with the published documents.

Comment A: The 6th edition of the Manual for the Personal Wellbeing Index is currently under development. It will make no change to the PWI itself, but the manual will contain a number of chapters designed to elaborate various aspects of the Index, data treatment, analysis, and interpretation. The Manual is scheduled to be completed before the end of 2020, however four chapter are already completed and are published prior to collation in the manual as:

Capic, T. (2020). Analytic manual for the publication: Cummins et al (2018)“Why Self-Report Variables Inter-Correlate: the Role of Homeostatically Protected Mood”.

Abstract: The intention of this manual is to describe the syntax underlying the statistical analysis within the manuscript “Why self-report variables inter-correlate: The role of Homeostatically Protected Mood.” published by Cummins, Capic, Hutchinson, Fuller-Tyszkiewicz, Olsson, & Richardson. (2018). This manuscript provides empirical evidence for the influence of the Homeostatically Protected Mood on self-reported Subjective Wellbeing variables. The extent of this influence was estimated by comparing the change in the standardised correlation coefficients before and after the removal of HPMood variance. The analytical process in this manual is described in detail, from preparation of data to analyses of change between non-adjusted and adjusted correlation coefficients.

Hartanty, N. (2020). Psychometric overview of the Personal Wellbeing Index-Adult.

Abstract: The aim of this review is to assist researchers to understand the psychometric properties of the Personal Wellbeing Index. This review is not evaluative. Rather, it comprises a list of available psychometric results. Evaluating these results is a task for each researcher who is considering whether to use the instrument.

Khor, S., Fuller-Tysziewicz, M., & Hutchinson, D. (2020). Australian normative data.

Abstract: This document provides normative statistics for two measures of subjective wellbeing in Australia. One measure is the single item ‘Global Life Satisfaction’, and the second is the Personal Wellbeing Index.

Stokes, M. A. (2020). Mediation and Moderation.

Abstract: Moderation and mediation are two methods to evaluate the relationship between variables that go beyond the traditional notion of an independent variable (IV) relating to a dependent variable (DV). These methods allow assessment of other variables while evaluating the traditional IVDV relationship, and facilitate examination of multiple forms of relationships between variables. The present chapter outlines the basic of these techniques in a simple manner.

Comment B: Rejected manuscripts are welcome provided that the author(s) consider the content makes a contribution to understanding.

Cummins, R. A. (2016). Self-Determination Theory and the Theory of Subjective Wellbeing Homeostasis: An examination of congruence.

Abstract: The original intention of this chapter was to study the relationship between Positive Psychology, represented by Self-Determination Theory, and Subjective Wellbeing, represented by the Theory of Subjective Wellbeing Homeostasis. The construction of the chapter begins with a general introduction to the statements and claims of each theory. This is followed by an examination of their overlap, most especially with a view to seeking theoretical common ground. Empirical evidence from each area is then examined and the chapter ends with a statement of conclusions. These conclusions are unfavourable. The editors who had invited the chapter considered these conclusions, and their supporting text, to be unsuitable for inclusion in their positive psychology handbook. Rather than make the text-reductions required by the editors for publication, the manuscript was withdrawn. This is the original unexpurgated version of that manuscript.

Comment C: I cannot recall my precise motivation for compiling this critique in 2007, but I am unlikely to go back to complete it for refereed publication. It does contain valid points of critique and many references.

Cummins, R. A. (2020). SF-36/SF-12 and Other HRQOL Scales: Description and Critique.

Abstract: The current version of the SF-36 was published by John Ware in 1993, and the brief version in 1995. The scale has become the most widely used instrument to measure Health Related Quality of life, with a massive citation record. Despite this, several authors have made severe criticisms of the scale. This document is one such critique.

Comment D: We produced this report for the ACQol membership and citculated it at that time.

Cummins, R. A., & Choong, S. A. (2012). A listing and content of population surveys to measure aspects of wellbeing: Australian and International.

Abstract: This report contains a description of 123 most easily accessible population surveys concerning the measurement of wellbeing. Each of the surveys is described in some detail regarding its location, sample character, and quality of life domains measured.

Comment D: Academics are sometimes advised not to bother publishing in conference proceedings because they have such a low citation rate. But there are always exceptions. Perhaps because of the informative title, which means people do not have to actually read the paper in order to cite it, this conference proceedings paper has received 483 citations.

Cummins, R. A., & Gullone, E. (2000). Why we should not use 5-point Likert scales: The case for subjective quality of life measurement. Paper presented at the Second International Conference on Quality of Life in Cities (pp.74-93), Singapore: National University of Singapore.

Abstract: An argument is presented that the Likert scales commonly employed to measure subjective quality of life (SQOL) are not sufficiently sensitive for the purpose of using SQOL as a measure of outcome. A review of the literature indicates that expanding the number of choice-points beyond 5- or 7-points does not systematically damage scale reliability, yet such an increase does increase scale sensitivity. It is also argued that naming the Likert scale categories detracts from the interval nature of the derived data. As a consequence it is recommended that SQOL be measured using 10-point, end-defined scales.

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Further discussion of this initiative, for circulation to members, is invited. Send to: [email protected]

Substantive comments received by midnight Oz time, on Sunday 16th August, will be published in the following Bulletin. Such comments may offer a novel extension to the view



Website additions and changesTanja Capic <[email protected]>

WebMaster

Resource added to the Health Related Resources page : Title: 60 Digital Resources for Addressing Substance Use Disorders, Addiction and RecoveryLink: https://www.onlinemswprograms.com/resources/social-issues/resources-addiction-and-recovery/Summary: This guide has compiled a list of organizations and digital resources that support individuals working toward recovery and that offer advice to their families, friends, and communities on how to aid in the process. Detailed in this piece are 4 sections on the signs and symptoms of substance abuse and addiction, treatment and recovery options, how to help a loved one, resources for various types of addictions, and many more relevant resources.

Publications by members

Sirgy, M. J. (2020). Positive Balance: A Theory of Well-Being and Positive Mental Health. Cham, Switzerland: Springer.

The foundation for the theory of positive balance is a hierarchical model of the balanced life (and positive mental health). I argued that individuals with positive balance are characterized to experience:• A preponderance of neurochemicals related to positive emotions (dopamine, serotonin, etc.) relative to neurochemicals related to negative emotions (cortisol), at a physiological level• A preponderance of positive affect (happiness, joy, etc.) relative to negative affect (anger, sadness, etc.), at an emotional level• A preponderance of domain satisfaction (satisfaction in salient and multiple life domains such as family life and work life) relative to dissatisfaction in other life domains, at a cognitive level• A preponderance of positive evaluations about one’s life using certain standards of comparison (satisfaction with one’s life compared to one’s past life, the life of family members, etc.) relative to negative evaluations about one’s life using similar or other standards of comparison, at a meta-cognitive level• A preponderance of positive psychological traits (self-acceptance, personal growth, etc.) relative to negative psychological traits (pessimism, hopelessness, etc.), at a development level• A preponderance of perceived social resources (social acceptance, social actualization, etc.) relative to perceived social constraints (social exclusion, ostracism, etc.), at a social-ecological level.


[copied into Pandect – NO]

Mental Health Commission of NSW. (2020). Journey of wellbeing. Sydney: Author https://apo.org.au/sites/default/files/resource-files/2020-08/apo-nid307439.pdf

The Journey of Wellbeing is a social and emotional wellbeing model of care that emphasises the individual at the core of a healing plan. This model consolidates the exemplary elements of practice in the social and emotional wellbeing (SEWB) space that are being used by some Aboriginal Service Providers (ASPs) across NSW. The Journey model is based upon the advice and direction of Aboriginal communities, community leaders, service providers and the Aboriginal Health and Medical Research Council (AH&MRC). This project was co-ordinated by the NSW Mental Health Commission to build an evidence base for non-clinical models of care in social and emotional wellbeing.



The language of fear? Australian media and the pandemichttps://psychology.org.au/for-members/publications/inpsych/2020/June-July-Issue-3/The-language-of-fear-Australian-media-and-the-pandCindy Gallois

Panic increases panic. We communicate panic interpersonally, through language and nonverbal channels. When looking at the impact of behavioural contagion via the media – how might the use of intense and negative emotional language in the media influence the fear we feel? We should read all news media critically. What does the story say? What emotional impression does it give? Is this accurate, and is it appropriate?



Membership RegistrarWelcome to new membersDr Cathy BaldwinAffiliate Research Fellow, University of GlasgowKeywords: Psychosocial; urban; community; social cohesion; resilience

Dr. Lindsay McCunnProfessor, Vancouver Island UniversityKeywords: Environmental psychology

Dr Carolyn WinslowResearcher Keywords: Positive organizational psychology, work-life balance, affect/emotions at work, job stress management





Mrs. Tonje ElgsasPsychologist, Akershus UniversitetssykehusKeywords: Intellectual disability, quality of life, personal wellbeing index

-----------------------ReferencesXxxxxx




other person.

Importance x SatisfactionBackground: It is almost perfectly intuitive. If someone is highly satisfied with their partner’s cooking, then they will regard it as very important in their life. If someone has mistakenly chosen a bad cook as their partner, then harmony requires that they rate their partner’s ‘cooking skills’ as having low importance. Therefore, the intuition goes, when measuring subjective life quality, by levels of satisfaction, the strength and validity of satisfaction measures will be enhanced by forming a multiplicative composite: satisfaction x importance. Interestingly, however, this intuition is wrong. A substantial, and almost unanimous literature over the past 50 years, has concluded that forming such a multiplicative composite does not statistically advantage the variable of ‘satisfaction’ used alone (e.g. Trauer and Mackinnon 2001, Wu and Yao 2006, Wu 2008).

One demonstration of this phenomenon involved an early scale to measure Subjective Wellbeing (SWB). This was the first edition of the Comprehensive Quality of Life Scale (ComQol: Cummins 1991) and it applied ‘importance x satisfaction’ to each of 7 life domains. Then Trauer and Mackinnon (2001) ‘named and shamed’ the 5th edition of ComQol (Cummins 1997) with their provocatively titled paper ‘Why are we weighting?’ Their main point of critique was that the use of ‘importance x satisfaction’ was invalid.

In that same year, Hagerty, Cummins et al. (2001) critiqued ComQol on the same grounds, citing (Andrews and Withey 1976) “Although a number of questions remain with respect to the nature and meaning of the importance measures, we have an unambiguous answer to our original question: Data about the importance people assign to concerns did not increase the accuracy with which feelings about life-as-a-whole could be predicted...our results point to a


simple linear additive, one in which an optimal set of weights is only modestly better than no weights (i.e., equal weights). We confess to both surprise and pleasure at these conclusions. (pp. 119-120)”

So compelling was this evidence against the usefulness of IxS, that the ComQol scale was withdrawn. However, this allowed it to metamorphose into the Personal Wellbeing Index (International Wellbeing Group 2004) by retaining only the seven domain satisfactions. The PWI has proved more robust and the manual is about to enter its 6th edition (International Wellbeing Group 2020).

While the weight of this early IxS literature created a level of certainty sufficient to deter most researchers from continuing to ‘demonstrate the demonstrated’, a related issue still has research currency. This is the question of why it is, that the intuitive feeling that IxS must be useful, is wrong. Cummins and Weinberg (2015) consider this question in their review of multi-item scales, and cite Locke (1969, 1976) as providing the answer.

It was Locke who first noted that ratings made with respect to specific topics, such as job satisfaction, comprise both a judgment of importance to the individual as well as a satisfaction evaluation based on the discrepancy between what the individual wants and what they perceive them self as getting. Most crucially, as determined by Locke, these two processes are not independent. That is, the level of satisfaction is influenced by the interaction of the have-want discrepancy with importance.

He states this principle as the ‘range-of-affect hypothesis’, in which the level of importance determines the range of satisfaction. That is, an item with high personal importance will produce a wide range of affective reactions, from great satisfaction to great dissatisfaction. An item with low personal importance, on the other hand, will produce a far narrower range of satisfaction. In summary, the range of the satisfaction ratings on an item, is determined by the item’s importance. Therefore, according to Locke, item satisfaction has already incorporated the information of item importance, which renders weighting item satisfaction with item importance redundant.

Voluminous psychometric data confirm this prediction and numerous authors have argued more generally, that the differential weighting of items in scales is psychometrically unsound (e.g. Evans 1991; Hagerty et al. 2001; Wooden 2002), or at the least unhelpful (Adams 1969; Mikes and Hulin 1968).

There is also a logical objection to using importance as a weighting variable, linked to the ambiguity of its meaning. People can regard areas of their life as important for a wide variety of very different reasons. For example, they may see something as important because they do not have it and want it (e.g., an expensive car), or because they have it and do not want it (e.g., chronic pain), or because they have it and wish to retain it (e.g., political power). The logical link to another dependent variable, such as satisfaction, is clearly not going to be simple.

Due the presence of this cohesive and compelling literature, it is surprising to see contemporary research directed to investigating the IxS formulation.

Reference: Sirgy, M. J., Kim, M. Y., Joshanloo, M., Lee, D.-J., & Bosnjak, M. (2020). The Relationship Between Domain Satisfaction and Domain Importance: The Moderating Role of Depression. Journal of Happiness Studies, 1-24.

Author summary: A study involving a large-scale social survey was administered to a representative German sample provided evidence demonstrating three information processing principles associated with life satisfaction judgments: (1) judgments of domain satisfaction tend to influence judgments of domain importance; (2) the effect of domain satisfaction on domain importance tends to be moderated by depressive realism; and (3) depression tends to influence domain satisfaction judgments. Specifically, depression mitigates the influence of domain satisfaction on domain importance. Non-depressed individuals tend to use compensation (an ego-enhancing strategy) to inflate the importance of domains they experience high satisfaction as well as deflate the importance of those domains they experience low satisfaction. As such, the effect of domain satisfaction on domain importance is accentuated for the non-depressed compared to the depressed.

Comment on Sirgy et al (2020)The authors use data from a German, general population survey of adults. Through four survey waves, Subjective Wellbeing (SWB) was measured through the combined scores from 7 domains of satisfaction (family, work, leisure time, friends, neighbors, financial situation, and health) using a 7 response-choice, bipolar scale. Importance was measured using the same scale format. The authors do not comment on how they handled the data from respondents with no ‘family’ or ‘work’, and no psychometric justification for the scale, in terms of its factorial structure or validity, is provided.

Depression was measured by 8 items. No information is provided on the provenance of these items. The items were combined to yield a single measure and an exploratory factor analysis demonstrated a single factor for each wave. No validity, normative data, or previous results from the scale are presented. Their results show:

1. Domain importance and satisfaction are positively related. These results have been reported by most researchers in this area.

2. Domain satisfaction and depression are inversely related.This finding is virtually incontestable. Positively and negatively valenced variables will be inversely correlated with one another.

3. Weighting domain satisfaction by importance did not increase the explanatory power of the domain satisfaction index on life satisfaction.This phenomenon has been covered in the ‘background’. However, instead of calling on Locke for the explanation, the authors propose a ‘Compensation Principle’, such that respondents are attempting to “enhance their life satisfaction by amplifying the importance or significance of those domains in which they experience high satisfaction; conversely, they reduce the importance of those domains in which they experience dissatisfaction.” (p.2022). Rather than offering an explanation, this proposal begs the questions of ‘why?’ and ‘how?’ It is not clear what purpose might be served by such an ‘amplification’ mechanism. It is surely redundant for a dual system to operate for the same purpose; this is to make high satisfaction dependent on high importance, when both variables always move together. Moreover, since it is established that the psychometric quality of IxS is virtually indistinguishable from S alone,

this surely suggests that the I component has no modulating influence on S. In summary, the ‘Compensation Principle’ requires additional explanation.

4. That the positive relationship between domain satisfaction and domain importance is weaker for the respondents who were depressed. The authors’ justify this hypothesis as “Depression is associated with a loss of the normal ‘illusory positivity’, with resultant ‘depressive realism” (p.2010). However, why this relates to a weaker satisfaction x importance correlation is not explained. Rather, the authors then segue into a different tack, presenting a hypothetical scenario (p 2011) in which people protect against loss of SWB by increasing the importance of successful life domains and diminishing the importance of unsuccessful domains.

Both of these idea are inconsistent with the understanding that levels of I and S for each person change together. If they move together, they cannot change their correlation with one another. [As an aside, such ‘domain compensation’ under challenging conditions has been empirically demonstrated using variations in satisfaction alone (Best, Cummins et al. 2000). Moreover, this demonstration found domain importance to play no significant role in the compensation process].

Despite the authors’ failure to present a convincing rationale, they did find that the correlation between I and S was weaker in depression. An explanation for this, not considered by the authors, involves the processes of SWB homeostasis (Cummins 2017a). Satisfaction responses comprise two main components, as mood (Homeostatically Protected Mood: HPMood) and emotion (Capic, Li et al. 2018). The mood is stable, as an individual difference, and is a component of most responses to personal evaluations (Cummins, Capic et al. 2018a). This common and stable component for each person is variable between people. Thus, using group data, HPMood is largely responsible for the correlations between satisfaction responses, including those with importance. However, while the stable, positive level of HPMood is defended by homeostasis, strong and persistent negative challenges defeat homeostatic control, as evidenced by depression. Then, as HPMood loses its stability, it loses its character as an individual difference, and loses its ability to provide a common, stable element within both satisfaction and importance responses. As a consequence, the correlations involving satisfaction diminish (Richardson, Fuller-Tyszkiewicz et al. 2014), presumably including the correlations between satisfaction and importance.



Substantive comments received by midnight Oz time, on Sunday 9th August, will be published in the following Bulletin. Such comments may offer a novel extension to the view that has

been put, an alternative and informed view, or offer a critique.



WebMaster

Addition to ‘useful sites’http://www.acqol.com.au/instruments#usesful-sites

Title: Dental health and care for seniorsLink: https://www.authoritydental.org/senior-dental-careSummary: Many people lose their dental insurance upon retirement. At the same time, some medical conditions may negatively affect oral health. This guide may help seniors take better care of their teeth.


Carroll, M., Hand, K., Budinski, M., & Baxter, J. (2020). Families in Australia survey: Life during COVID-19. Report 2. Staying connected when we're apart. Melbourne: Australian Institute of Family Studies https://apo.org.au/sites/default/files/resource-files/2020-07/apo-nid307223.pdf.

May 2020: the first wave of the coronavirus pandemic was upon us, and we surveyed 7,306 people about how they had been affected. Every state and territory was in some form of lockdown. The restrictions differed, but what everyone had in common was a degree of forced isolation. We have a special interest in families and what helps them thrive, so a number our questions focussed on how people stayed connected, particularly when physically separated.

KEY FINDINGS Many people (37%) found it difficult to connect with family members living elsewhere, though almost everyone (93%) made the effort.

The families who kept up the best connection often lived close by or made creative use of technology.

Many older people struggled with video calls and the like, and many still depended on face-to-face visits for contact and support.



We Could All Use Some Psychological First AidMary McNaughton-Cassillhttps://www.psychologytoday.com/us/blog/mental-health-matters/202007/we-could-all-use-some-psychological-first-aid

Psychological First Aid won’t cure the pandemic, but it can help us generate and maintain the hope that, like oxygen, is essential for our well-being. Definitions of Psychological First Aid vary, but at least five components seem to be key. These include helping people feel safe, create a sense of calm, regain a sense of control, social connection and hope.

Additional recommend reading‘Today’s Research’, edited by Dr Bob Murray, provides a weekly digest of research, mainly in biology and the social sciences. https://fortinberrymurray.us13.listmanage.com/subscribe?


https://www.psychologytoday.com/us/blog/mental-health-matters/202007/we-could-all-use-some-psychological-first-aid

https://www.psychologytoday.com/us/blog/mental-health-matters/202007/we-could-all-use-some-psychological-first-aid



https://www.authoritydental.org/senior-dental-care

http://www.acqol.com.au/instruments#usesful-sites

u=6a411e8ce902df7c73232a8f2&id=4ee17adb2b&mc_cid=e1cac10cf4&mc_eid=e9a2e6453f

Report from the ACQol siteGoogle Analytics inclusive period: July 2020


---------------Number of ACQol members: 450

-----------------------ReferencesAndrews, F. M., & Withey, S. B. (1976). Social indicators of well-being: American's perceptions of

life quality. New York: Plenum Press.Best, C. J., Cummins, R. A., & Lo, S. K. (2000). The quality of rural and metropolitan life. Australian

Journal of Psychology, 52, 69-74. Capic, T., Li, N., & Cummins, R. A. (2018). Confirmation of Subjective Wellbeing Set-points:


Cummins, R. A. (1991). Comprehensive Quality of Life Scale: Manual (1st ed.). Melbourne: : Victoria University, Psychology Research Centre.

Cummins, R. A. (1997). Comprehensive Quality of Life Scale - Adult (5th ed.). Melbourne: School of Psychology, Deakin University



Cummins, R. A., & Weinberg, M. K. (2015). Multi-item Measurement of Subjective Wellbeing: Subjective Approaches. In W. Glatzer, L. Camfield, V. Møller, & M. Rojas (Eds.), Global Handbook of Quality of Life: Exploration of Well-Being of Nations and Continents (pp. 239-268). Dordrecht: Springer.

Hagerty, M. R., Cummins, R. A., Ferris, A. L., Land, K., Michalos, A. C., Peterson, M., . . . Vogel, J. (2001). Quality of life indexes for national policy: Review and agenda for research. Social Indicators Research, 55, 1-91.

International Wellbeing Group. (2004). Personal Wellbeing Index Manual: 1st Edition. Melbourne: Australian Centre on Quality of Life, School of Psychology, Deakin University.


Richardson, B., Fuller-Tyszkiewicz, M. D., Tomyn, A. J., & Cummins, R. A. (2014). The Psychometric equivalence of the Personal Wellbeing Index for normally functioning and homeostatically defeated Australian adults. Journal of Happiness Studies, 15 (1), 43-56. doi:http://link.springer.com/article/10.1007/s10902-015-9613-0

Trauer, T., & Mackinnon, A. (2001). Why are we weighting? The role of importance ratings in quality of life measurement. Quality of Life Research, 10, 579-585.

Wu, C. H. (2008). Examining the appropriateness of importance weighting on satisfaction score from range-of-affect hypothesis: Hierarchical linear modeling for within-subject data. Social Indicators Research, 86(1), 101-111.

Wu, C. H., & Yao, G. (2006). Do we need to weight satisfaction scores with importance ratings in measuring quality of life? Social Indicators Research, 78(2), 305-326.

http://link.springer.com/article/10.1007/s10902-015-9613-0


http://www.oxfordbibliographies.com/view/document/obo-9780199828340/obo-9780199828340-0167.xml







other person.

Unrealistic optimism

Background: It all started when Weinstein (1980) proposed a human tendency “to be unrealistically optimistic about future life events” (abstract), triggering a torrent of research (6,300 citations). The terminology he chose to describe this phenomenon clearly implies pathology, so a systematic approach to evaluating the validity of this claim requires a definition of ordinary ‘optimism’. Weinstein is silent on this matter. But Merriam-Webster (2020) is more forthcoming, defining optimism as “an inclination to put the most favorable construction upon actions and events or to anticipate the best possible outcome.”

This is an extreme view. The Oxford Online Dictionary (2020) has a more modest view as “Hopefulness and confidence about the future or the success of something.” This seems more in line with contemporary thinking of optimism as a trait of general positivity, consistent with the authoritative review of optimism provided by Carver and Scheier (2002), who suggest a ‘generalized sense of confidence’. So, consider optimism as a general positivity trait, based in personality. How, then, can optimism be ‘unrealistic’?

The obvious answer, is that the ‘unrealism’ refers to excessive positivity (as with the authors below). Thus, unrealistic optimism is an overly confident view of a positive future outcome. It seems intuitive that this could be demonstrated by the fact of a less positive future than had been predicted. If, at the age of 25y, a person predicted that their income would double in 10y time, and at the end of the 10y it had only increased by 50%, then it could be said that their optimism at age 25y had been ‘unrealistic’. But there are several problems with this reasoning.

The first problem is that the measurements involved in this demonstration involve two quite different types of variables. These are subjective variables, which can only be validated by the respondent, and objective variables, which can be validated by an observer. Combining such variables is a conceptually dangerous practice, because each variable type exists in a different universe of reality (Cummins 2000a). In this instance, such combination results in an invalid conclusion because ‘unrealistic optimism’ exists entirely without reference to objective reality. It represents a semi-abstract, subjective view of the self, consistent with such a commonly-held feeling as ‘I am luckier than most people’ (Cummins and Nistico 2002). Such views reflect the general sense of the self as positive and are strongly resistant to


objective realities, such as persistent financial loss at the local casino. If the predictive measurement involves an objective variable (such as financial loss or gain), then the conclusion to be drawn from a prediction over time does not concern unrealistic optimism, but ‘predictive accuracy’.

Predictive accuracy is a function of two factors. One is the strength of the optimism. The other is knowledge that has informed the prediction. Consider, for example, a response to the question “Looking ahead, will you be married tomorrow? [very unlikely, don’t know, very likely]. So, the respondent is asked to make a prediction (subjective variable) about an event (objective variable). The question appears silly because, of course, the respondent knows the answer with certainty due to cognitive evaluation. So, now consider this variation.

“Looking ahead, how do you see your financial situation a year from now? [better, same, worse than now]. Notably, if ‘a year from now’ is changed to ‘tomorrow’, the question has the same structure as ‘married tomorrow’. That is, it involves the subjective prediction of an objective variable (financial status). The longer time-span in the second allows more uncertainty, is all.

Making the dependent variable objective (financial situation) can, under quite ordinary circumstances, allow a high level of predictive accuracy. Increased certainty may be due to an automatic annual salary increment, a partner returning to work after an absence, or a steady growth in business. Any of these could provide the basis for a response that is both highly optimistic and rational. It has nothing to do with unrealistic optimism.

In conclusion, estimating unrealistic optimism involving tangible outcomes is an invalid procedure. Weinstein (1980) was aware of this and devised a clever alternative methodology confined to subjective variables.

He provided students with a list of positive hypothetical events (e.g. Your work is recognized with an award”. They were asked "Compared to other [name of university] students, of the same sex as you - what do you think are the chances [%] that the [event] will happen to you?” Subsequently, these same students were asked to “estimate the % of students at the university to whom the event would occur.” Overall, the students rated themselves more likely than the average student to experience a positive event. In other words, they demonstrated ‘unrealistic optimism’.

Reference: DeMeza, D., & Dawson, C. (2020). Neither an optimist nor a pessimist be: mistaken expectations lower well-being. Personality and Social Psychology Bulletin.

Author summary: This article speaks to the classic view that mental health requires accurate self-perception. Using a representative British sample (N = 1,601) it finds that, as measured by two established well-being indicators, those with mistaken expectations, whether optimistic or pessimistic, do worse than realists. We index unrealistic optimism as the difference between financial expectations and financial realizations measured annually over 18 years. The effects are not small, with those holding the most pessimistic (optimistic) expectations experiencing a 21.8% (13.5%) reduction in long-run well-being. These findings may result from the decision errors and counteracting emotions associated with holding biased beliefs. For optimists, disappointment may eventually dominate the anticipatory feelings of expecting the best while for pessimists the depressing effect of expecting doom may eventually dominate the elation when the worst is avoided. Also, plans based on inaccurate beliefs are bound to deliver worse outcomes than would rational expectations.

Comment on DeMeza & Dawson (2020)These authors measure ‘unrealistic optimism’ using an objective variable. At successive intervals they asked:“Looking ahead, how do you think you yourself will be financially a year from now; better than you are now, worse than you are now, or about the same?and later:“Would you say that you yourself are better off, worse off or about the same financially than you were a year ago?

As previously argued, this procedure measures predictive accuracy, not unrealistic optimism. The DeMeza and Dawson paper will not be further considered. Instead, the opportunity is taken to consider how optimism relates to other subjective variables. It will be argued that Subjective Wellbeing (SWB) and other commonly associated variables, such as self-esteem and perceived control, share much of their basic character with optimism.

The construct of optimism is most commonly measured by the revised Life Orientation Test [LOT-R]; Scheier, Carver, & Bridges, 1994). This scale comprises four positively-worded items such as ‘In uncertain times, I usually expect the best.’ As such it is similar in structure to the simplest measure of SWB which is Global Life Satisfaction (GLS); a single item as ‘In general, how satisfied are you with your life as a whole? Both of these two items are highly personal (they refer directly to the respondent), concern positive feelings, and have a semi-abstract target (‘usually expect the best’ and ‘life as a whole’). These are the perfect conditions for Homeostatically Protected Mood (HPMood) to form a strong part of the response that people make to these questions (Cummins 2018a).

The HPMood is a stable, positive, and unchanging background affect, which is constantly present in the experienced feelings of each individual person. HPMood is a composite affect (content, happy, alert) representing the phenotype of each person’s HPMood set-point (Capic, Li et al. 2018). HPMood is, thus, an individual difference for each person and, as such, is the dominating influence on the experienced level of both optimism and GLS. So, each person reports their experience of both optimism and GLS at about the level of their setpoint for HPMood.

While the level of HPMood is stable for each individual, this setpoint level is different between people. Thus, while each person reports both optimism and GLS at much the same idiosyncratic (setpoint) level, other people will report their optimism and GLS at a different level. Thus, within grouped data, the reported level of optimism and GLS are much the same for each group member, which causes optimism and GLS to be significantly correlated (Lai and Cummins 2013: r=.42).

There are several consequences of this understanding, for example:1. Numerous authors have noted that there is a strong tendency for optimism to be normally reported as quite strongly positive and stable. The reason for this is its HPMood content (happy, content, alert). Levels of HPMood exhibit a normal distribution within the population, lying between 70 to 90 percentage points (pp) on a strength scale from 0 to 100pp (Capic, Li et al. 2018).

2. Numerous authors have noted that optimism correlates with other subjective measures of positive experience, and that these other measures also correlate with one another. The reason for these correlations is the same as for that between optimism and GLS: it is their shared

content of HPMood. This can be demonstrated by statistically removing the HPMood content. When HPMood is removed, the correlations are greatly reduced. Examples of correlations before (r) and after partialling-out HPMood (pr) are as follows: Engel (2009), study 2, Optimism vs. Self-efficacy, r = .39, pr = .09; Depression vs. Self-esteem, r = −.66, pr = −.31. Lai (2010), Religious self-esteem vs. Personal Wellbeing Index, r = .14, pr = .08; Primary Control vs. Christianity Secondary Control r = .11, pr = .05. Lai and Cummins (2013), Global Life Satisfaction (GLS) vs. self-esteem, r = .57, pr = .22; Global Life Satisfaction vs. optimism, r = .42, pr = .03. In summary, these results from four separate studies confirm that at least half of the variance connecting these 10 different self-evaluative variables is HPMood. Moreover, in about half of these, the reduction is so severe as to render the initially significant correlation, non-significant.

In summary, ‘unrealistic optimism’ is an unfortunate term in that it implies pathology. To the contrary, a determinedly positive life outlook is normal, such that people generally consider themselves to have a higher level of subjective wellbeing than they imagine is average for the population. Importantly, this positivity is not ‘zero sum’; everyone can have it. While this general optimism serves to provide motivation for living, as with all aspects of life, more is not necessarily better. Very high levels of optimism, likely beyond the HPMood setpoint range, are maladaptive (Haaga and Stewart 1992, Ruthig, Perry et al. 2004) in generating impaired judgements.

Importantly, and unknown to (Weinstein 1980), this natural positivity is not restricted to optimism. All of the positively-valanced variables associated with subjective wellbeing (e.g. self-esteem) are also naturally infused with HPMood and thereby held at a level which approximates each person’s setpoint. The overall consequence is twofold. First, that the general overview each person has of themselves is positive. Second, that the separate subjective variables that comprise this overview positively correlate with one another.



Substantive comments received by midnight Oz time, on Sunday 2nd August, will be published in the following Bulletin. Such comments may offer a novel extension to the view that has

been put, an alternative and informed view, or offer a critique.



Australian Institute of Health and Welfare. (2020). Australia’s health 2020 data insights. Australia’s health series no. 17. Cat. no. AUS 231. Canberra: : AIHW https://apo.org.au/sites/default/files/resource-files/2020-07/apo-nid307044_0.pdf.

Australia’s health 2020 is the 17th biennial flagship report on health released by the

https://apo.org.au/sites/default/files/resource-files/2020-07/apo-nid307044_0.pdf

Australian Institute of Health and Welfare since it was established in 1987. Australia has dealt with the potential threat of COVID-19 comparatively well and as a result, discussions are now focusing more on other critical aspects of overall health, including mental health. Isolation from family, friends and other support networks can negatively affect mental health and may also lead to a reduction in physical activity or to increased use of alcohol and other drugs. Large-scale loss of employment, broad economic downturn and general uncertainty add to these stressors. The social and economic impacts of COVID-19 may have a range of flow-on effects—for example, an increased incidence of family, domestic and sexual violence and a greater burden of mental health issues.



Is Boredom All Bad?Ed Halliwellhttps://www.mindful.org/is-boredom-all-bad/

While many of us practice for inner peace, what we find when we stop and sit is rather disconcerting: Our minds flit on a seemingly endless loop of tedious thoughts, and our bodies itch and ache. We realize we’d rather be anywhere than stuck with our antsy selves. Why is it so hard just to be ourselves, alone, without embellishment? And what is this strange experience we call boredom, which seems to fuel our relentless drive always to be getting somewhere, doing something? Mindfulness invites us to see boredom not as something to reject, but rather to know, understand, and even embrace.



Membership RegistrarWelcome to new memberDr MARIA ARMAOU

Keywords: Psychological well-being, Resilience, Health promotion, Digital interventions

-----------------------ReferencesCapic, T., Li, N., & Cummins, R. A. (2018). Confirmation of Subjective Wellbeing Set-points:


Carver, C. S., & Scheier, M. (2002). Optimism. In S. J. Lopez & C. R. Snyder (Eds.), Positive psychological assessment: Handbook of models and measures (pp. 75-89). Washington, DC: American Psychological Association.

Cummins, R. A. (2000a). Objective and subjective quality of life: An interactive model. Social Indicators Research, 52, 55-72.





Cummins, R. A. (2018a). Subjective wellbeing as a social indicator. Social Indicators Research, 135, 879-891. doi:10.1007/s11205-016-1496-x

Cummins, R. A., & Nistico, H. (2002). Maintaining life satisfaction: The role of positive cognitive bias. Journal of Happiness Studies, 3(1), 37-69.

Engel, L. (2009). Psychological Impact of DAFNE training in adults with type 1 diabetes. Unpublished doctoral thesis. Melbourne: Deakin University http://www.acqol.com.au/projects#reports.

Haaga, D. A., & Stewart, B. L. (1992). Self-efficacy for recovery from a lapse after smoking cessation. Journal of Consulting and Clinical Psychology, 60(1), 24-28.

Lai, L. C. H. (2010). Religiosity and Subjective Wellbeing in Christianity, Buddhism and Taoism: unpublished doctoral thesis. Melbourne: Deakin University http://www.acqol.com.au/projects#reports.

Lai, L. C. H., & Cummins, R. A. (2013). The contribution of job and partner satisfaction to the homeostatic defense of subjective wellbeing. Social Indicators Research, 111(1), 203-217. doi:10.1007/s11205-011-9991-6

Merriam-Webster. (2020). Online dictionary. Retrieved from http://www.merriam-webster.comOxford Online Dictionary. (2020). http://www.oxforddictionaries.com. Oxford: Oxford University

press.Ruthig, J. C., Perry, R. P., Hall, N. C., & Hladkyj, S. (2004). Optimism and Attributional Retraining:

Longitudinal Effects on Academic Achievement, Test Anxiety, and Voluntary Course Withdrawal in College Students. Journal of Applied Social Psychology, 34(4), 709-730.

Weinstein, N. D. (1980). Unrealistic optimism about future life events. Journal of Personality and Social Psychology, 39(5), 806-820.




other person.

Title NIH Toolbox Emotion measureshttp://www.nihtoolbox.org

In the course of studying the publication by (Mwilambwe-Tshilobo, Ge et al. 2019), discussed in ACQol Bulletin Vol 4/29, it was noted that the scales used by the authors to measure loneliness and meaning in life, were both drawn from the NIH Toolbox Emotion measures (http://www.nihtoolbox.org). This resource is not commonly used within the social sciences, so is worthy of examination.

Such a resource is automatically welcomed by the many authors who struggle to determine what scales they should use to measure subjective wellbeing constructs. There are just too many scales to enable time-poor researchers to make a well informed choice. The Australian Centre on Quality of Life offers a brief description of some 1,200 instruments measuring

http://www.nihtoolbox.org/



http://www.oxforddictionaries.com/


http://www.acqol.com.au/projects#reports


some aspect of subjective life quality (http://www.acqol.com.au/instruments), but this is just a fraction of the number that has been published. So surely it would be a good idea to seek advice from an assortment of experts in such measurement, obtain results from likely candidate scales, and then create a list of constructs matched to their best performing scale? Maybe, maybe not.

This idea was operationalized in 2004 by the American National Institutes of Health. Their goal was to locate, or develop, a collection of standard instruments to measure cognitive and emotional health, which could then serve as an international resource (Gershon, Cella et al. 2010). A team of experts was duly assembled and The Toolbox was made available in September 2012 (Talan 2012). It was designed in four independent modules — cognition, emotion, motor, and sensation — with the whole collation intended to be administered within two hours.

While the NIH Toolbox measures were originally freely available from Assessment Center, this facility is no longer available. The toolbox has transitioned into an iPad app, available via the App Store, and requires a year’s subscription.

So, was generating the Toolbox ever a good idea? Of course there is the overarching convenience for researchers, and a ready justification (NIH recommended) for using one of the recommended scales. But there are also considerable dangers to such an endeavour from a scientific perspective. Some of these are as follows:

1. The NIH ‘Toolbox team’ clearly has a medical disciplinary bias in its choice of instruments. This is to be expected. However, since the instruments collect data through self-report assessment, the psychological literature is going to be crucial to the psychometric rationale for selecting one scale over another. Yet there is no evidence, for example, that the selection of scales to represent the ‘emotion’ module was made with a view to represent affects in a manner representative of the Circumplex Model of Affect (Russell 1980). Yet this model has become the theoretical, standard description, of the underlying structure of affective experience.

2. The relative worthiness of scales changes as new information becomes available. Thus, any such list requires regular revision in order to stay current. This has not happened. As enthusiasm and resources to maintain this resource has diminished, the list of recommended instruments has increasingly passed its use-by date and become a scientific hazard.

3. Such a list of instruments, endorsed by the august NIH, may well act, inadvertently, to inhibit psychometric progress. This may be due to both the development, by non-NHS researchers, of superior scales to those listed, as well as researcher unwillingness to report results demonstrating the inadequacy of listed scales.

4. The claim of the Toolbox authors that their scales represent an ‘international resource’ is unjustified. Not only was all psychometric testing performed on American population samples, but contemporary opinion holds that the cross-cultural use of scales developed from Anglophone cultures is a fraught process (Cummins 2018b).

The following publication describes the development and testing protocols used to compile the ‘emotion module’ NIH Toolbox scales.

https://en.wikipedia.org/wiki/Emotional_health

https://en.wikipedia.org/wiki/National_Institutes_of_Health

http://www.acqol.com.au/instruments

Reference: Salsman, J. M., Butt, Z., Pilkonis, P. A., Cyranowski, J. M., Zill, N., Hendrie, H. C., … Choi, S. W. (2013). Emotion assessment using the NIH Toolbox. Neurology, 80(11 Supplement 3), S76-S86.

Author summary: Based on an extensive literature review and expert input, the Emotion team identified 4 central subdomains: Negative Affect, Psychological Well-Being, Stress and Self-Efficacy, and Social Relationships. A subsequent psychometric review identified several existing self-report and proxy measures of these subdomains with measurement characteristics that met the NIH Toolbox criteria. In cases where adequate measures did not exist, robust item banks were developed to assess concepts of interest. A population-weighted sample was recruited by an online survey panel to provide initial item calibration and measure validation data. Participants aged 8 to 85 years completed self-report measures whereas parents/guardians responded for children aged 3 to 12 years. Data were analysed using a combination of classic test theory and item response theory methods.

Comment on Salsman (2013)Several previous authors have commented unfavourably on the instruments comprising the NIH Toolbox, especially those involving the Emotion module (e.g. Kupst, Butt et al. 2015). Other observations on these instruments can be made as follows:

1. The major form of analysis, used to measure psychometric adequacy, is confirmatory factor analysis. The results are displayed in Tables 2 to 5 as the Comparative Fit Index (CFI) and Root Mean Square Error of Approximation (RMSEA). Each of these statistics estimates the discrepancy (model fit) between the proposed scale structure (e.g. a single factor) and the actual data. Each statistic has a set value for acceptability, which has changed over the years as new information became available. The original criteria were CFI >.90 and RMSEA of <.10 (Bentler 1992). The conventional view then changed, to regard these as too lenient. They were therefore revised to be CFA >.95 and RMSEA <.06 (Hu and Bentler 1999). These have remained the acceptable criteria since that time and had been in place for over a decade at the time of the Salsman publication. Nevertheless, these authors employed the original, weaker, criteria when describing their results. When the results are evaluated using contemporary criteria, of the 73 scales listed in these two tables, only 10 (14%) meet both criteria for model fit.

2. The authors promote proxy reporting for the emotional wellbeing of children (p.S77). They seem unaware that, for over 40 years, the invalidity of both teacher and parental proxy responding for children’s subjective feelings have been confirmed by a highly consistent literature (Reynolds 1979, Garbarski 2014). If a measure is invalid, then it does not matter whether it is reliable or whether there is no valid alternative, the measure should not be used.

3. Their analytic tables report convergent validity of scales as though this necessarily a positive feature. In fact, it is an automatic feature when the scale responses contain Homeostatically Protected Mood, as most of the ‘emotion’ scales will (Cummins, Capic et al. 2018a). The more crucial statistic for construct integrity is discriminant validity, upon which the authors are silent.

4. The expectation that the 180 items of the Emotion Module will be completed by adults in 30 minutes is unrealistic. The required rate of 6 questions per minute for adults may be achievable by the experienced respondents who were engaged for this exercise (Internet panel samples) but not by inexperienced people. If respondents need to spend much more than 30

minutes on a questionnaire, they are increasingly likely to experience respondent fatigue and engage in careless responding.

5. “The mechanisms underlying these associations [between emotions and disease] are not well understood, but they can be organized into 2 general families: direct effects via physiologic pathways and indirect effects via the impact of NA on health-related behaviors” (p.S78). It is true that the correlations between emotions and disease are poorly understood. It is not true that causal statements can be made regarding the unidirectional ‘impact’ of physiological pathways on emotion, which then affect ‘health related behaviors’. It is just as likely that purposive changes in health related behaviors (e.g. exercise) have a direct effect on emotion (positive affect) which decreases the physiological stress pathway (e.g. cortisol), for example. Practically all research papers concerning such relationships generate only correlational data.

In summary, the authors of the NIH Toolbox have produced a product which has many undesirable aspects. Of greatest note, most scales in the Emotion Module cannot be regarded as valid.



Substantive comments received by midnight Oz time, on Sunday 26th July, will be published in the following Bulletin. Such comments may offer a novel extension to the view that has been

put, an alternative and informed view, or offer a critique.



WebMaster

http://www.acqol.com.au/instruments#usesful-sitesNAME: The Recovery Village RidgefieldURL: https://www.ridgefieldrecovery.com/SUMMARY: Our goal is to provide individuals and loved ones with the information, support and resources they need to find hope and healing in recovery.

Publications by membersNaidoo Y, 2019, 'A Multi-dimensional Individual Well-Being Framework: With an

Application to Older Australians', Social Indicators Research, 146, 581–608. http://dx.doi.org/10.1007/s11205-019-02132-w

This paper constructs a multi-dimensional individual well-being (MIW) indicator framework to explicitly recognise the inter-relationship between economic and non-economic dimensions in encapsulating the totality of an individual’s life. The MIW framework treats individual well-being as a multi-dimensional concept disaggregable into uniquely defined but latent well-being dimensions

with observable indicators attached to each. A composite well-being index applicable to individual level analysis is developed through a series of intra-personal aggregative procedures. The results are based on person-level data from the household, income and labour dynamics in Australia survey and applied to an assessment of the individual well-being of older Australians, aged 65 years and over. The findings indicate that, although older Australians have slightly lower overall well-being compared to non-older adults, driven primarily by declining physical health and to a lesser extent mental health, they maintain strong personal relationships, and engage actively in their communities. More generally, the approach outlines how to quantify objective multi-dimensional assessments of individual well-being.


Australian Institute of Family Studies. (2020). Families in Australia Survey: Life During COVID-19. Report no. 1: Early findings. Melbourne: Author. https://apo.org.au/sites/default/files/resource-files/2020-07/apo-nid306590.pdf

OverviewThe Life during COVID-19 survey ran from May 1 to June 9 2020 and had 7,306 participants from around Australia. It was the first survey in the Families in Australia Survey series.

KEY FINDINGSThe proportion of people always working from home rose from 7% before COVID-19 to 60% during it.Before COVID-19, 30% of families used parent-only care. That rose to 64% of families during COVID-19.While parents worked from home, 40% always or often ‘actively’ cared for children during work. “Felt like we got abandoned by work to sort out our own arrangements with little to no understanding of maintaining our productivity whilst having young children with us 24/7”.Male, 45, lives in a major city, household with childrenAlmost half (43%) of respondents reported they or their partner had lost employment, reduced hours or wages. However 65% reported no real change to their personal income.Young adults were disproportionately impacted by the economic downturn, being almost four times (15% vs 4%) more likely to ask for help from government or NGO.-----------------------------------------

Committee for Economic Development of Australia. (2019). Disrupting disadvantage setting the scene. Melbourne: Author https://apo2.o0rg1.au9/sites/default/files/resource-files/2019/11/apo-nid267176-1397621.pdf.

Entrenched disadvantage is unfortunately a well-known feature of the Australian socio-economic landscape. CEDA’s primary focus in this paper is on people who become stuck or are at risk of becoming stuck in disadvantage. Families, social groups, individuals, and people in particular locations can all find themselves unable to break out of adverse economic and social circumstances. There are a range of estimates for the number of people currently in entrenched disadvantage. For example, 700,000 people have faced continuous income poverty for at least the last four years. In addition, over one million people are estimated to be experiencing deep social isolation or exclusion.



How Does Yoga Improve Body Image?


https://apo2.o0rg1.au9/sites/default/files/resource-files/2019/11/apo-nid267176-1397621.pdf

Jessica M Allevahttps://www.psychologytoday.com/au/blog/mind-your-body/202007/how-does-yoga-improve-body-image

Numerous studies have shown that practicing yoga not only helps people to achieve greater peace of mind and physical well-being, but it can also help them to feel more positively about their bodies. In our newest study, my colleagues and I asked the question: How exactly does yoga lead to a more positive body image?



Membership RegistrarWelcome to new membersDr. L Rey-AresKeywords: Household finances, financial literacy

Dr Yuvisthi NaidooResearch Fellow, Social Policy Research Center, Faculty of Arts and Social Sciences, UNSWKeywords: well-being, social indicators, life course, subjective well-being, poverty, deprivation, income

Ms. Laura MusikanskiExecutive Director, Happiness AllianceKeywords: happiness, well-being, sustainability, subjective well-being, community organizing

Professor Hisham AbusaadaHousing and Building National Research Center (HBRC), Housing and Building National Research Center (HBRC)Keywords: Urban design, Urban nightlife, Convivial evening, and Conviviality of nightlife atmospheres

-----------------------ReferencesBentler, P. M. (1992). On the fit of models to covariances and methodology to the Bulletin.

Psychological Bulletin, 112(3), 400. Cummins, R. A. (2018b). Measuring and interpreting subjective wellbeing in different cultural

contexts: A review and way forward. New York: Cambridge University Press.Cummins, R. A., Capic, T., Hutchinson, D., Fuller-Tyszkiewicz, M., Olsson, C. A., & Richardson, B.

(2018a). Why self-report variables inter-correlate: The role of Homeostatically Protected Mood. Journal of Wellbeing Assessment, 2, 93-114. doi:10.1007/s41543-018-0014-0




Garbarski, D. (2014). Comparing self and maternal reports of adolescents’ general health status: Do self and proxy reports differ in their relationships with covariates? Quality of Life Research, 23, 1953-1965.

Gershon, R. C., Cella, D., Fox, N. A., Havlik, R. J., Hendrie, H. C., & Wagster, M. V. (2010). Assessment of neurological and behavioural function: the NIH Toolbox. The Lancet Neurology, 9(2), 138–139.

Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55.

Kupst, M. J., Butt, Z., Stoney, C. M., Griffith, J. W., Salsman, J. M., Folkman, S., & Cella, D. (2015). Assessment of stress and self-efficacy for the NIH Toolbox for Neurological and Behavioral Function. Anxiety, Stress, & Coping, 28(5), 531-544.

Mwilambwe-Tshilobo, L., Ge, T., Chong, M., Ferguson, M. A., Misic, B., Burrow, A. L., . . . Spreng, R. N. (2019). Loneliness and meaning in life are reflected in the intrinsic network architecture of the brain. Social cognitive and affective neuroscience, 14(4), 423-433.

Reynolds, W. M. (1979). The utility of multiple-choice test formats with mildly retarded adolescents. Educational and Psychological Measurement, 39, 325 - 331.


Talan, J. (2012). NEWS FROM THE NINDS: New NIH Toolbox Rolled Out for Standardized Behavioral and Clinical Assessment Measures. Neurology Today, 12(21), 7.




other person.

The wisdom of measuring loneliness physiology

Background: There is an almost automatic reaction for scientists to view the ‘scientific-ness’ of biological research as superior to that of scientific psychology. It is a natural and primitive belief. Whereas one is based on objective data, which can be viewed by any second party, the latter is based on measured ‘thoughts or feelings’ which can only be verified by the person supplying the data. Moreover, since it is certain that all thoughts and feelings are generated through the operation of biological processes, surely a scientific understanding of psychology can best be validated by understanding of the biological processes producing the data? No. There are good scientific reasons for doubting that such reductionism is necessarily applicable, especially in relation to complex constructs such as loneliness. Some ideas to support this view are as follows:


1. Perhaps a good starting point is to tackle the scientific credentials of research based on self-report data. First in the negative. Anyone reading contemporary studies into psychological constructs will be impressed by the statistical sophistication that some researches apply to their data. When this is accompanied by adequate methodological care, the resulting package reporting the outcome can be very compelling. BUT. So many of such studies lose contact with the sine qua non of scientific research, which is that the result can be repeated by other researchers. Many uses of multivariate statistics produce results of such methodological specificity that the probability of replication is very low. If, in addition, the study is not specific to testing a clearly specified theory, then the probability that the result will assist understanding approaches zero. Statistical and methodological sophistication does not a science make. This truth has been demonstrated over the past 50 years of research into parapsychology (https://en.wikipedia.org/wiki/James_Randi#Skeptic).

2. However, many data generated through self-report are reliably replicable. And all examples of such data share a single characteristic. They represent simple variables and simple ideas that, when stated, seem almost intuitive. It is fitting that the earliest example is provided by Gustav Theodor Fechner (1801-1887), German philosopher, physicist and experimental psychologist, who is now known as the founder of psychophysics. In 1873 he wrote: “In so far as conscious impulses always bear a relation to pleasure or pain, pleasure or pain may be thought of in psycho-physical relationship to conditions of stability and instability … that every psycho-physical movement rising above the threshold of consciousness is charged with pleasure in proportion as it approximates—beyond a certain limit—to complete equilibrium … [similarly with pain and that] between the two limits, which may be described as the qualitative thresholds of pain or pleasure, there is a certain area of aesthetic indifference” (Fechner 1873, p.94).

He went on to demonstrate the logarithmic relationship between psychological sensation and the physical intensity of a stimulus, which became known as the Weber–Fechner law. His idea of a psychophysical region of ‘aesthetic indifference’ inspired (Helson 1947, Helson 1964) to develop his ‘Adaptation Level Theory’, which proposes an active system of psychological adaptation around a neutral ‘adaptation-level’. His 1964 book has been cited over 1,500 times.

The reliability of self-report data took a quantum jump when (Miller 1956) demonstrated it applied to cognition. His article has been cited over 33,000 times. ‘Miller’s Law’ proposes that the number of objects an average person can hold in working memory is about seven, plus or minus two. This, then, is the span of reliable categorical judgements that people can make on a continuum (eg. from ‘no satisfaction’ to ‘complete satisfaction’) thereby putting the 5-choice Likert scale into retirement, as an obsolete, very blunt instrument (Cummins and Gullone 2000b).

An extension of these demonstrations of reliable self-report data, this time concerning affect, was first proposed by (Russell 2003: cited >5,200 times). He proposed the affective circumplex as a classification system. He also coined the term core affect, to describe a neurophysiological state experienced as a basic feeling. Russell describes core affect as analogous to felt body temperature in that it is always there, it can be accessed when attention is drawn to it, extremes are most obvious, and it exists without words to describe it. This idea was subsequently simplified (Davern, Cummins et al. 2007) and theoretically contextualized (Cummins 2017a) into a simple mood under homeostatic control. This Homeostatically Protected Mood (HPMood) comprises just three affects (content, happy, alert) and has been

https://en.wikipedia.org/wiki/Weber%E2%80%93Fechner_law

https://en.wikipedia.org/wiki/James_Randi#Skeptic

demonstrated to be remarkable stable, chronically normally varying by only a few percentage points for each person (Anglim, Weinberg et al. 2015). It is proposed such stability is consistent with HPMood being the phenotype of an individual difference, representing a set-point for each person (Cummins, Li et al. 2014a, Capic, Li et al. 2018).

In summary, each of these simple demonstrations of reliable and valid basic measurement within psychological science have built on one another. The demonstration of HPMood set-points has incorporated Fechner’s ‘area of aesthetic indifference’ as the resting level of HPMood, the 0-10 choice response scale created data with the sensitivity to demonstrate set-points, Adaptation Level Theory provided the fundamental basis for homeostatic theory defending set-points, and Russell’s simplified ‘core affect’ has provided the affects comprising HPMood. The outcome is a coherent theoretical model, which is eminently suited to being falsified – the essence of scientific worthiness.

So, from this point in the developing story, the potential contribution of biology seems clear. Homeostasis theory proposes a genetic basis for HPMood setpoints. If these could be demonstrated then a new bridge forms between genetics and psychology. This evident possibility, leads to considerations of similar bridging possibilities for higher-level psychological constructs than the level of three simple affects. For example, might the application of sophisticated neurological measuring devices be able to demonstrate a biological basis for loneliness? Maybe not, and the paper under review this week is informative.

Reference: Mwilambwe-Tshilobo, L., Ge, T., Chong, M., Ferguson, M. A., Misic, B., Burrow, A. L., . . . Spreng, R. N. (2019). Loneliness and meaning in life are reflected in the intrinsic network architecture of the brain. Social cognitive and affective neuroscience, 14(4), 423-433.

Author summary: We took a multivariate network approach to examine resting-state fMRI functional connectivity’s association with loneliness and meaning in a large cohort of adults (N=942). Loneliness and meaning in life were negatively correlated with one another. In their relationship with individually parcelled whole-brain measures of functional connectivity, a significant and reliable pattern was observed. Greater loneliness was associated with dense, and less modular, connections between default, frontoparietal, attention and perceptual networks. A greater sense of life meaning was associated with increased, and more modular, connectivity between default and limbic networks. Low loneliness was associated with more modular brain connectivity, and lower life meaning was associated with higher between-network connectivity.

Comment on Mwilambwe-Tshilobo et al (2019)The previous Bulletin commented on Bzdok and Dunbar (2020) in terms of their confusion between ‘being alone’ and ‘loneliness’. But the main issue addressed in their article was the biology of loneliness. In relation to this topic I wrote “The melding of phenomenological science (self-report data) with biological measurement is fraught with difficulty. Each area has its own exquisite methodological and conceptual issues affecting validity, and few researchers are sufficiently informed about both area to devise scientifically clean studies. Worse, the measured interaction between psychological experience and biological functioning is almost always highly approximate and suppositious because the mechanism of the interaction is not understood. The result is a multitude of studies which are little more than fishing expeditions in the hope of serendipity”.

The current paper uses Functional Magnetic Resonance Imaging (fMRI) to test the hypothesis that “loneliness would be associated with greater connectivity between regions that support attention, including the FPN, dorsal attention (DAN), and the ventral attention networks. In contrast, ‘Meaning in Life’ would be associated with greater connectivity within the ‘Default Network”. Comments in relation to this are:

1. The authors’ introduction does not simply link past research to this hypothesis. For example, the FPN (frontoparietal network) is not even mentioned, the Default Network is activated by many known psychological states in addition to ‘attention’ (see Wikipedia), and no explicit prior connection is mentioned between Meaning in Life and Default Network activation.

2. The dependent variable of Resting State Functional Connectivity (RSFC), measured by fMRI, is a very crude index of neural activation. It represents changes in blood flow. The assumption is, the more a neurological region is active, the more oxygen it requires, so the more blood is supplied. So it cannot inform about the functional connection between simultaneously activated regions. Is their activation indicative of functional excitation, inhibition, or some other purpose entirely? The technique is silent.

3. The study is based on data collected as part of the Human Connectome Project (HCP) 1200 subject release dataset (http://www.humanconnectome.org). The authors provide N (942), gender, age (23-37y) and an exclusion criterion of <27 on the Mini Mental State. Neither they nor the website appear to provide further methodological information. Thus, the conditions under which data were gathered are not readily available. The two psychological variables are measured using scales from the NIH Toolbox Emotion measures (http://www.nihtoolbox.org). No psychometric data are provided. The data are supplied to the researchers as T-scores, which are standardized to have a mean of 50 and a standard deviation of 10. In other words, the researchers are accepting the validity, reliability, and population normality of the data they use, on faith.

4. Perhaps the most critical missing information is the temporal interval between data collected on perceived loneliness and the corresponding fMRI measurement. It is generally agreed that loneliness is not a stable aspect of personality, and that loneliness can happen to anyone given the necessary inducing conditions (Cacioppo and Cacioppo 2018). Thus, valid fMRI linkage with loneliness requires contemporaneous assessment. The authors show no awareness of this requirement.

5. Within their analyses, the authors used multiple t-tests with significance set at p<.05. The absence of a Bonferroni correction opens their results to Type 1 errors.

6. Their first hypothesis is that “loneliness would be associated with greater connectivity between regions that support attention, including the FPN, dorsal attention (DAN), and the ventral attention networks (VAN). In contrast, ‘Meaning in Life’ would be associated with greater connectivity within the ‘Default Network”. Their results do not simply support this hypothesis. They found that for BOTH loneliness and meaning in life “the most robust associations were observed … between the Default network and FPN as well as networks implicated in more externally directed cognition including attentional (e.g. VAN)…(p.429). This discrepancy is not mentioned in their abstract.


In conclusion, this publication fails to provide results which add to the understanding of loneliness.







WebMaster

Australian Centre on Quality of Life Bulletin Archive http://www.acqol.com.au/publications#bulletinsNew quarterly additionACQol Bulletin Vol 4/14: 020420 to Vol 4/26: 250620

Publications by membersLaura Musikanski <[email protected]>

“Please share the opportunity to acquire a free inspection copy of a coursebook, Happiness, Well-being and Sustainability: A Course in Systems Change that I co-authored” The inspection copy request form: https://www.routledge.com/textbooks/evaluation/9780367488703

Happiness, Well-being and Sustainability: A Course in Systems Change is the first textbook bridging the gap between personal happiness and sustainable social change. The book provides a guide for students to increase their skills, literacy and knowledge about connections between a sense of well-being and systems change. Further, it can help students live a life that brings them happiness and contributes to the well-being of others and the sustainability of our planet. The book is presented in seven chapters covering the subjects of systems thinking, personal and societal values, measuring happiness, human needs, ecological sustainability and public policy. In addition, each section includes engaging exercises to empower students to develop their own ideas, prompts for group discussion, suggestions for additional research and an extensive list of resources and references. The book is written in the context of systems thinking with a style that is approachable and accessible.


Bray, J. R. (2020). Measuring the social impact of income management in the Northern Territory: An updated analysis, Working Paper no. 136/2020. Canberra: Centre for Aboriginal Economic Policy Research, Australian

National University. https://caepr.cass.anu.edu.au/sites/default/files/docs/2020/7/CAEPR_WP_no_136_2020_Bray_0.pdf

Income management policies have been in place in the Northern Territory since 2007. These policies limit how recipients of government income support payments can spend a proportion of these funds. The policies were initially directed at Indigenous Australians who remain the major group on the program. The objective of the policy was to improve individual and community outcomes. Around one-third of the Northern Territory Indigenous population aged 15 years and over have been subject to the policy. Initial evaluation findings could not identify any such gains at the community level. This paper extends the analysis undertaken in the 2014 evaluation using contemporary data covering child health and wellbeing, education, crime and alcohol consumption. It confirms the previous finding of an absence of evidence of discernible, positive benefits across these measures which could be attributed to the policies.



How will dating change after coronavirus? Psychology offers some cluesMartin Graff https://theconversation.com/how-will-dating-change-after-coronavirus-psychology-offers-some-clues-138893

The dating scene could be a confusing place in world where at least some social distancing seems likely for the foreseeable future. And while many people will have maintained or begun contact with romantic partners online during lockdown, video chats and text messages are clearly not a long-term substitute for intimate (or even non-intimate) physical contact.



Membership RegistrarWelcome to new memberDr Niels LindUniversity of WaterlooKeywords: Life Quality Index; Social Index calibration, Inequality

-----------------------ReferencesAnglim, J., Weinberg, M. K., & Cummins, R. A. (2015). Bayesian hierarchical modeling of

the temporal dynamics of subjective well-being: A 10 year longitudinal analysis. Journal of Research in Personality, 59(3), 1-14. doi:10.1016/j.jrp.2015.08.003

Bzdok, D., & Dunbar, R. I. M. (2020). The Neurobiology of Social Distance. Trends in cognitive sciences.

Cacioppo, J. T., & Cacioppo, S. (2018). The growing problem of loneliness. The Lancet, 391(10119), 426.





https://caepr.cass.anu.edu.au/sites/default/files/docs/2020/7/CAEPR_WP_no_136_2020_Bray_0.pdf

Capic, T., Li, N., & Cummins, R. A. (2018). Confirmation of Subjective Wellbeing Set-points: Foundational for Subjective Social Indicators. Social Indicators Research, 137(1), 1-28. Retrieved from 10.1007/s11205-017-1585-5.


Cummins, R. A., & Gullone, E. (2000b). Why we should not use 5-point Likert scales: The case for subjective quality of life measurement. In ACQol Open-Access Publications by Members. Melbourne: Australian Centre on Quality of Life, Deakin University. http://www.acqol.com.au/publications#publications.



Fechner, G. T. (1873). Einige Ideen zur Schöpfungs- und Entwicklungsgeschichte der Organismen. Section XI, Note p. 94. Leipzig: Breitkopf und Härtel.

Helson, H. (1947). Adaptation-level as frame of reference for prediction of psychophysical data. The American Journal of Psychology, 60(1), 1-29.

Helson, H. (1964). Adaptation-level theory: An experimental and systematic approach to behavior. New York: Harper and Row.

Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63(2), 81-97.

Russell, J. A. (2003). Core affect and the psychological construction of emotion. Psychological Review, 110(1), 145-172.




other person.

Loneliness

Background: The issue of loneliness is making big news. And so it should. The over-riding concern by public-health authorities in the face of the Covid-19 threat, is to contain the spread of the virus. And from this perspective alone, the solution is simple. Stop people occupying the same social environment. But this solution ignores the psychological consequences of involuntary social isolation, which reviewers Haslam, Haslam et al. (2019)


http://www.acqol.com.au/publications#publications



describe as ‘a killer’. So, in order to avoid a coincident epidemic of induced psychopathology, a more complex solution is required, advised by a scientific understanding of loneliness.

The starting-point for understanding lies in defining the construct and agreeing on a valid and reliable form of measurement. An excellent and informed definition of loneliness has been provided by the Commissioner for Senior Victorians (2016) as “Loneliness is a subjective, unwelcome feeling of lack or loss of companionship or emotional attachment with other people” (p.46). Crucially, they note the difference between loneliness and Social Isolation, which is “an objective state of having minimal contact and interaction with others and a generally low level of involvement in community life” (Grenade and Boldy 2008). They also note that the direct link between being alone and being lonely should not be assumed. Some people are happy to be alone, while others can feel lonely despite the presence of other people.

So how can loneliness be measured? There are many scales that purport to measure the construct. Nine are described in the ACQol Directory of Instruments http://www.acqol.com.au/instruments#measures. Of these, probably the most popular is the UCLA Loneliness Scale (Russel, Peplau et al. 1980) which has been cited over 4,000 times. However, at 20 items it is far too long to measure a single-construct, and it does not factor reliably. A derivative and well-cited 3-item, short form (Hughes, Waite et al. 2004) asks:How often do you feel that you lack companionship:How often do you feel left out:How often do you feel isolated from others?

The extraction of these items from the original scale reveals the psychometric danger of assuming that all scales labelled by their originators as a ‘Loneliness scale’ measure the same construct. They clearly do not. For example, an item in the original 20 item version of the Russel, Peplau et al. (1980) scale asks how much the respondent agrees “I am an outgoing person”, which is a classical measure of extraversion. Another item requests agreement with “I do not feel alone”. People are supposed to disagree with this if they feel lonely. But such disagreement confuses the objective reality (someone actually is alone) with the subjective feeling of loneliness (they are alone, but not lonely). [This also reveals the perils of asking negative questions]. Finally, and oddly, neither version of the scale asks “How often do you feel lonely?” which, conceivably, is a more valid measure of loneliness than the scales.

So, who gets to feel lonely? Much research has been devoted to the search for particular person characteristics which predispose people to loneliness, but to little avail. Instead, the contemporary conclusion is that loneliness can happen to anyone given the necessary inducing conditions (Cacioppo and Cacioppo 2018). This understanding is highly relevant to considerations of treatment. Instead of treating the condition per se, treatment should target the provision of resources which are causing the condition to become manifest.

Finally, the treatment of loneliness by common sense methods (eg, social skills training, and provisions for social support and social contact) is ineffective (Masi, Chen et al. 2011). Quite possibly, the reason that loneliness is so hard to treat is that it requires the same set of resources (money, relationships, and purposeful activity) as does the homeostatic defence of SWB. These are also the most challenging for governments to provide.

So, assuming the above matters have been dealt with, what do the data tell us about the condition of loneliness? First, as per the definition, it is an ‘unwanted feeling’ and so is


potentially pathological. To what extent such feelings are strong enough to be manifest as overt psychopathology will depend on other factors, many of which are intuitive. First, of course, is the strength of the felt loneliness. Second, is the almost certain co-occurrence of other negative feelings, such as may come from stress, anxiety or depression. Third, is the co-availability of defensive resources, succinctly described as the Golden Domain Triangle (Cummins 2018e), comprising a sufficiency of money, a purposeful activity, and an emotionally intimate relationship. These three domains are pre-eminent in the homeostatic maintenance of SWB (Cummins 2017a). In summary, the risk of loneliness is a balance of forces, all of which will inter-correlate, and an etiology that looks a lot like SWB homeostatic failure. From this description, several statements about loneliness are obvious and do not require elaborate research confirmation. These include:

1. Being alone is not equivalent to being lonely.

2. Susceptibility to loneliness varies greatly between individuals. However, loneliness is more common among people with low resources. This especially applies to relationship resources (Haslam, Haslam et al. 2019), but also to money and having a purposeful activity.

3. Different measures of loneliness have different levels of validity in measuring the construct. Thus, data from different scales are not necessarily equivalent.

4. People who are lonely will also, on average, experience higher levels of negative states, such as depression, anxiety, and stress. They will also experience lower levels of SWB and positive emotions. All of these variables will inter-correlate.

5. Simply inviting a 'lonely' individual to join a group or interact with others provides either minimal or transient relief from loneliness, particularly once this has become a chronic experience or cycle (Masi, Chen et al. 2011, Lim 2018).

All of the above are not only intuitive, but also have been empirically demonstrated in numerous studies. They do not need to be demonstrated again. Reviews that simply detail the relevant studies have no more than archival value unless their synthesis of material results in a new insight.

Reference: Bzdok, D., & Dunbar, R. I. M. (2020). The Neurobiology of Social Distance. Trends in cognitive sciences.

Author summary: Never before have we experienced social isolation on such a massive scale as we have in response to coronavirus disease 2019 (COVID-19). However, we know that the social environment has a dramatic impact on our sense of life satisfaction and well-being. In times of distress, crisis, or disaster, human resilience depends on the richness and strength of social connections, as well as on active engagement in groups and communities. Over recent years, evidence emerging from various disciplines has made it abundantly clear: perceived social isolation (i.e., loneliness) may be the most potent threat to survival and longevity. We highlight the benefits of social bonds, the choreographies of bond creation and maintenance, as well as the neurocognitive basis of social isolation and its deep consequences for mental and physical health.

Comment on Bzdok & Dunbar (2020)In their abstract above, the authors start on the wrong foot. They use the phrase “perceived social isolation (i.e., loneliness)”. This conveys the misperception that objective social isolation (in ‘perceived social isolation' one correctly perceives one is socially isolated) is equivalent to loneliness. The failure to understand this crucial distinction contaminates much of their subsequent literature description, where results from isolation and loneliness are presented as equivalent.

In terms of their review, other wrong feet are their failure to either define ‘loneliness’ or consider the validity of the loneliness data they cite. While their first section covers the familiar territory described as ‘background’, their main review target is the neurobiology of loneliness. Here they weave an elaborate story that is woven from highly technical cloth.

The melding of phenomenological science (self-report data) with biological measurement is fraught with difficulty. Each area has its own exquisite methodological and conceptual issues affecting validity, and few researchers are sufficiently informed about both area to devise scientifically clean studies. Worse, the measured interaction between psychological experience and biological functioning is almost always highly approximate and suppositious because the mechanism of the interaction is not understood. The result is a multitude of studies which are little more than fishing expeditions in the hope of serendipity.

This topic will be continued into the next Bulletin. Here, however, a couple of general observations can be made. The first of these is the use of sub-human animal models to explore topics like loneliness. As a reminder, the definition of Loneliness is “a subjective, unwelcome feeling of lack or loss of companionship or emotional attachment with other people”. This clearly indicates a strong cognitive element, in which the ‘feeling’ of loneliness is influenced not simply by being alone (that is the objective state) but by the implications of losing ‘companionship’ and ‘emotional attachment’. Such implications will be vastly different depending on the level of cognitive processing the animal possesses. While a rat can surely appreciate ‘aloneness’, it is much less likely they can appreciate the difference between that state and ‘loneliness’. So researchers using such animal models need to show clearly that they understand this limitation.

A second observation is that the study of loneliness may open a bridge between the named sciences and philosophy. The following observations pertain: (a) lonely people remain lonely in the presence of other people; (b) loneliness is not a particular person characteristic, but a state which can be induced in anyone; (c) loneliness is associated with impaired emotion regulation (Lim, Eres et al. 2019); (d) loneliness is associated with low levels of the same key psychological resources as may also defeat SWB homeostasis (relationship intimacy, money sufficiency, and purposeful engagement); (e) loneliness and self-esteem are strongly negatively correlated (Ouellet and Joshi 1986), while loneliness and meaning in life have been biologically linked through resting-state fMRI functional connectivity (Mwilambwe-Tshilobo, Ge et al. 2019). The philosophers have a name for the conceptual space of this discussion, as existentialism.

A central plank in existentialist thought is authenticity (Flynn 2006). The proposition that each individual—not society or religion—is solely responsible for giving meaning to life and living it passionately and sincerely, or ‘authentically’. The failure of authenticity is termed ‘Despair’, generally defined as a loss of hope. More specifically, despair is a loss of hope resulting from a breakdown in the defining qualities of one's self or identity. If a person has

https://en.wikipedia.org/wiki/Meaning_(existential)

https://en.wikipedia.org/wiki/Authenticity_(philosophy)

nothing to rely on for their identity, they are unable to be what defined their being. They are lonely.







WebMaster

Australian Centre on Quality of Life Bulletin Archive http://www.acqol.com.au/publications#bulletinsNew quarterly additionACQol Bulletin Vol 4/14: 020420 to Vol 4/26: 250620

Publications by membersSeif, M., Asadollahi, A., Yarelahi, M., & Rezaian, E. (2020). Item response analysis to explore psychometric properties of the Persian version of Troutman successful aging inventory: Rasch partial credit model. Journal of Health Psychology, https://doi.org/10.1177/1359105320931174

The study aimed to evaluate Persian version of the TSAI-2011 to determine successful aging issues in older adults. In a psychometric study, the instrument was completed by 400 men and women aged 60 and above and the Rasch partial credit model was used. The PCM indicated that items 1 and 20 were misfitting. Also, it successive response categories for all items were located in the expected order and version of TSAI with 22-items had more internal consistency. Although Rasch analysis indicated to relevant of TSAI 22-Items, it should be evaluated in further studies and divergent cultures.


Streitfeld, D. (2020). The Long, Unhappy History of Working From Home. New York Times, June 30, 2020, Section B, Page 1 https://www.nytimes.com/2020/06/29/technology/working-from-home-failure.html?action=click&module=Editors%20Picks&pgtype=Homepage&mc_cid=5c228ed6fa&mc_eid=e9a2e6453f

https://www.nytimes.com/2020/06/29/technology/working-from-home-failure.html?action=click&module=Editors%20Picks&pgtype=Homepage&mc_cid=5c228ed6fa&mc_eid=e9a2e6453f



https://doi.org/10.1177%2F1359105320931174

Three months after the coronavirus pandemic shut down offices, corporate America has concluded that working from home is working out. Many employees will be tethered to Zoom and Slack for the rest of their careers, their commute accomplished in seconds. Richard Laermer has some advice for all the companies rushing pell-mell into this remote future: Don’t be an idiot.

A few years ago, Mr. Laermer let the employees of RLM Public Relations work from home on Fridays. This small step toward telecommuting proved a disaster, he said. He often couldn’t find people when he needed them. Projects languished.“Every weekend became a three-day holiday,” he said. “I found that people work so much better when they’re all in the same physical space.”



Does Diversity Undermine Community Trust?https://www.psychologicalscience.org/news/were-only-human/does-diversity-undermine-community-trust.html Wray HerbertOur culture and our economy are based on immigration and diversity, yet newcomers have always been threatening for some. Indeed, underlying all the complex legal and economic issues are some fundamental psychological questions: Will these people who don’t look and talk like me—will they hurt me in some way? Can I trust them to share my streets and shops and schools and workplaces? Schmid and her colleagues wanted to examine the effects of diversity on three kinds of trust—in-group trust, out-group trust, and overall neighborhood trust. The findings show that diversity can enable people—both established majority and newcomers—to open up to others. But it’s not enough just to live side-by-side in the same community. Only meaningful face-to-face interactions can trump the potentially destructive effects of diversity on trust and solidarity.



Membership RegistrarWelcome to new membersDr Andrew SeatonSpiritual awakening author, teacher and mentor, Keywords: Spiritual awakening, Enlightenment, Peace, Consciousness, Education, Mindfulness, Presence





Mr Albert HizgilovPhD candidate, Bar-ilan universityKeywords: Financial literacy, Financial inclusion, Financial development

-----------------------ReferencesCacioppo, J. T., & Cacioppo, S. (2018). The growing problem of loneliness. The Lancet, 391(10119), 426.

Commissioner for Senior Victorians. (2016). Ageing is everyone’s business: a report on isolation and loneliness among senior Victorians. Melbourne: Commissioner for Senior Victorians. http://apo.org.au/files/Resource/ageing_is_everyones_business_web_report_2016.pdf.


Cummins, R. A. (2018e). The Golden Triangle of Happiness: Essential resources for a happy family. International Journal of Child, Youth & Family Studies, 9(4), 12–39.

Flynn, T. (2006). Existentialism - A Very Short Introduction. New York: Oxford University Press.

Grenade, L., & Boldy, D. (2008). Social isolation and loneliness among older people: issues and future challenges in community and residential settings. Australian Health Review, 32(3), 468-478.

Haslam, A., Haslam, C., & Cruwys, T. (2019). Loneliness is a Social Cancer, Every Bit as Alarming as Cancer Itself. The Conversation, retrieved 25 May 2020 from: http://theconversation.com/loneliness-is-a-social-cancer-every-bit-as-alarming-as-cancer-itself-126741.

Hughes, M. E., Waite, L. J., Hawkley, L. C., & Cacioppo, J. T. (2004). A short scale for measuring loneliness in large surveys: Results from two population-based studies. Research on aging, 26(6), 655-672.

Lim, M. H. (2018). Is loneliness Australia's next public health epidemic? InPsych, 40(4), 7-11.

Lim, M. H., Eres, R., & Peck, C. (2019). The young Australian loneliness survey. Understanding loneliness in adolescence and young adulthood. Melbourne: Centre for Mental Health, Swinburne University of Technology.

Masi, C. M., Chen, H.-Y., Hawkley, L. C., & Cacioppo, J. T. (2011). A meta-analysis of interventions to reduce loneliness. Personality and Social Psychology Review, 15(3), 219-266.

Mwilambwe-Tshilobo, L., Ge, T., Chong, M., Ferguson, M. A., Misic, B., Burrow, A. L., . . . Spreng, R. N. (2019). Loneliness and meaning in life are reflected in the intrinsic network architecture of the brain. Social cognitive and affective neuroscience, 14(4), 423-433.

Ouellet, R., & Joshi, P. (1986). Loneliness in relation to depression and self-esteem. Psychological Reports, 58(3), 821-822.

Russel, D., Peplau, L. A., & Cutrona, C. E. (1980). The revised UCLA Loneliness Scale: Concurrent and discriminant validity evidence. Journal of Personality and Social Psychology, 39(3), 472-480.


Note 1: The ACQol site is under development and some content is missing.


http://theconversation.com/loneliness-is-a-social-cancer-every-bit-as-alarming-as-cancer-itself-126741




http://apo.org.au/files/Resource/ageing_is_everyones_business_web_report_2016.pdf

Note 2: Please address any intended group correspondence to the editor only.


other person.

SWB in New Zealand and Australia

Background: The previous issue of the Bulletin commented on Sibley, Greaves et al. (2020) and found it wanting in various respects. In an elaboration of two issues raised, Robert Brooks <[email protected]> comments:

“Your summary is disturbing. The cherry-picking of items from questionnaires is distinctly problematic. A question is not fully self-contained as this practice assumes. I spoke with John Ware about this issue in relation to the SF-36 (Ware, Snow et al. 2000), and he indicated that the context of questions is an important component of the result obtained. Even the order in which questions are asked changes the results if it is changed.In relation to items from the Satisfaction With Life Scale (SWLS: Diener, Emmons et al. 1985), in my PhD studies I examined the SWLS in two samples, general practice and intensive care patients. I undertook the general practice study because intensive care patients kept asking me how they could answer q5 of the SWLS. The general practice patients asked the same question. The structure of the SWLS does not hold in Australia, and the 5th question is the problem. This talks to the cross-cultural validity of surveys, even from the US to Australia”.

Cummins comments: Since you mention the SF-36, it is an opportunity for me to add that I have a low opinion of both the construct of Health Related Quality of life in general (Cummins 2010b), and the SF-36 scale in particular (Cummins 2007a). They provide poor service in representing the experience of life quality. In terms of the SWLS, question #5 is “If I could live my life over, I would change almost nothing.” This statement uses counterfactual reasoning, which may well be confusing for many people, especially for those who have not been trained within a Western culture (Bloom 1981). It does, indeed, detract from the factorial coherence of the scale.

Robert continues: “In regard to the differences between NZ and Australia on the governance issue, one obvious difference is the proportion of indigenous people in the population. A second is that although Jacinta has positive international regard, there have been ongoing problems in relation to the coalition partners and this may be contributing to the lower ratings”.

Cummins comments: The lower scores, on both the National and Personal Wellbeing Index scores (PWI: International Wellbeing Group 2013) of New Zealander (NZ), compared with Australian (AU) respondents, have been previously reported. This surprising result caught the attention of myself and Alexandra Ganglmair-Wooliscroft [email protected] over a decade ago. Alexandra had just published a psychometrically-detailed paper on the PWI in NZ (Ganglmair‐Wooliscroft and Lawson 2008) and reported this result (see attached). She suggested it may involve:


(a) The generally laid-back culture which encourages a tendency to understatement. [but when asked to rate agreement, that NZ is a good country to live in, they rate 87.5 percentage points: pp].(b) The composite culture – European, dominantly British, and Polynesian.(c) The high proportion of Maori [16%] in the general population samples [as also suggested by Robert. On the PWI: European-NZ = 68pp, Maori =65pp. Results on the NWI are similar]. This result is the most interesting, and runs counter to the explanation, as a simple demographic, of more Maori in the sample. It indicates that the ‘non-Maori’ population score is some 7pp below the AU norm of 75.43pp (SD 0.65pp). This is a massive difference when viewed in terms of AU normative ranges (Khor, Fuller-Tysziewicz et al. 2020), with the value of 68pp falling 10.7 standard deviations below the AU mean.

A decade ago we had no further comparative data, and so I let the issue lapse. Now, however, Sibley, Greaves et al. (2020) have produced pre-Covid measures from a 2019, not of the PWI but of various domains drawn from the PWI and NWI (National Wellbeing Index). In summary, these results compared with the AU norms also show a NZ deficit as: PWI: Standard -1.41pp; Health -7.93; Future -9.57; Relationships -4.49. NWI: Economy -10.06; Social -17.02; Business -4.88; Government +0.81pp. In this paper, the authors report only their composite sample results, with no separate estimates for Maori respondents. However, an earlier paper from these authors does make the distinction.

Sibley, Harré et al. (2011) report results from 2005 and 2009. Their results for 2005 are based on the same data as Ganglmair‐Wooliscroft and Lawson (2008) [attached]. However, their 2009 results use data collected following the Global Financial Crisis. These latter results show that, overall, the NZ PWI results are lower following the GFC, and also that the fall is smaller for European NZ than for Maori. This difference was judged to be consistent with the greater level of disadvantage caused by the GFC for the Maori people. Most notably, however, the European NZ mean of the 4-item ‘PWI’, in 2009, is 67.7pp, which is very similar to the 2005 figure of 68pp, and is about 7pp below the AU normative range for the full PWI.

Two conclusions can be reasonably drawn from all this. First, that the indigenous Maori have a level of SWB that lies some 3-4pp below the European-NZ population. This is consistent with results from other lands showing a chronic disadvantage in wellbeing by the indigenous people, almost irrespective of how wellbeing is measured. But the unique result from these studies is the lower level of SWB by the European-NZ population. Why might this be so?

A similar level of PWI difference has been convincingly demonstrated between Australian norms and peoples from Confucian-influenced cultures, such as China, Japan, Hong Kong, Macau, and Taiwan (e.g. Chen and Davey 2008b). Within this frame of comparison, it is proposed that people raised in Confucian influenced societies tend to hold back from registering extreme scores. In contrast, people raised in North American or Australian societies are more likely to simply report how they feel, using the whole extent of the response scale options.

But such an explanation cannot apply to European-NZ vs. Australian comparisons. Both of these population groups share the English language and a dominating common heritage of British culture (both are a Constitutional Monarchy under Elizabeth II), laws, service structure, and humor. They are both in the top-cluster of countries as judged by objective indices: GDP NZ=$40K, AU= $54K; Gini NZ 33.9, AU 34.0 ; Human Development Index

NZ 14th , AU 6th , etc. Of the 180 countries ranked by Transparency International, New Zealand ranks 1st and Australia 13th (Smith 2018). So the difference in level of SWB surely cannot be attributed to objective circumstances of living, or to religion (both are ‘weakly’ Christian).

This looks like an interesting anomaly requiring more information for understanding. Until that moment of enlightenment arrives, I am running with Ganglmair‐Wooliscroft and Lawson (2008), and their idea that the difference can be attributed to the generally laid-back NZ culture which encourages a tendency to understatement. If this could be verified, it would be the first demonstration of a non-religious cultural influence on reported levels of subjective wellbeing.







WebMaster

ACQOL Bulletin Vol 4/14-26 02/04/20 - 25/06/20These quarterly issues have been archived at http://www.acqol.com.au/publications#publications


Coalition of Peaks. (2020). A Report on Engagements with Aboriginal and Torres Strait Islander People to Inform a New National Agreement on Closing the Gap. Canberra: Author https://apo.org.au/sites/default/files/resource-files/2020-06/apo-nid306455.pdf.

This report came about because of the conviction of the Coalition of Peaks that, if Australia is to truly close the gap in life outcomes between Aboriginal and Torres Strait Islander people and other Australians, there needs to be a new way of working established between us and governments. Australian Governments confirmed its support for this when it agreed to a formal partnership with representatives of Aboriginal and Torres Strait Islander people to underpin the next phase of its Closing the Gap strategy. Subsequently, Australian governments, including the Australian Local Government Association, signed off with the Coalition of Peaks a formal Partnership Agreement on Closing the Gap, which is a historic demonstration of this new way of working.






The Psychological Importance of Extraordinary Experienceshttps://www.discovermagazine.com/mind/the-psychological-importance-of-extraordinary-experiencesGaladriel Watson

Psychologists say feelings of awe go beyond good memories. According to psychologists, two things have to happen to trigger an awe reaction. First, you have to perceive something is vast — either in its physical size (perceptual awe) or in its scope (conceptual awe). Then, the vast thing has to challenge your current understanding of the world. That is, it must require some mental processing. How can we have more awe in our day to day life? Take the scenic route, slow down and notice those things that amaze us, pay attention to your surroundings. “I think often people might be in a hurry and neglect to pay attention to the world around them, when there are so many opportunities to feel awe” Nelson-Coffey.


Report from the ACQol siteGoogle Analytics inclusive period: June 2020



Membership RegistrarWelcome to new membersMr Ross CarlyopnPresident, Strength Potential IncorporatedKeywords: youth mentoring strengths schooling

Ms. Adriana Marcelino da MartinsSpeech-language pathologist, Keywords: palliative care, intellectual disability

Professor Isabella SulisAssociate Professor of Social Statistics, University of CagliariKeywords: measurement models, social indicators, assessment in education, missing data, multi-level analysis.

-----------------------ReferencesBloom, A. (1981). The linguistic shaping of thought. Hillsdale, NJ, Earlbaum.

Chen, Z. and G. Davey (2008b). "Normative life satisfaction in Chinese societies." Social Indicators Research 89(3): 557-564.




Cummins, R. A. (2007a). SF-36/SF-12 and Other HRQOL Scales: Description and Critique. Melbourne, Deakin University, Australian Centre on Quality of Life http://www.acqol.com.au/publications#publications.

Cummins, R. A. (2010b). "Fluency disorders and life quality: Subjective wellbeing vs. health related quality of life. Invited paper." Journal of Fluency Disorders 35: 161-172.

Diener, E., R. A. Emmons, R. J. Larsen and S. Griffin (1985). "The satisfaction with life scale." Journal of Personality Assessment 49: 71-75.

Ganglmair‐Wooliscroft, A. and R. Lawson (2008). "Applying the international wellbeing index to investigate subjective wellbeing of New Zealanders with European and with Maori heritage." Kotuitui: New Zealand Journal of Social Sciences Online 3(1): 57-72.

International Wellbeing Group (2013). Personal Wellbeing Index Manual: 5th Edition. Melbourne, Australian Centre on Quality of Life, School of Psychology, Deakin University.

Khor, S., M. Fuller-Tysziewicz and D. Hutchinson (2020). Australian normative data for Subjective Wellbeing. Personal Wellbeing Index Manual: 6th Edition. International Wellbeing Group. R. A. Cummins. Melbourne, Australian Centre on Quality of Life, Deakin University http://www.acqol.com.au/publications#publications.

Sibley, C. G., L. M. Greaves, N. Satherley, M. S. Wilson, N. C. Overall, C. H. Lee, P. Milojev, J. Bulbulia, D. Osborne and T. L. Milfont (2020). "Effects of the COVID-19 pandemic and nationwide lockdown on trust, attitudes toward government, and well-being." American Psychologist.

Sibley, C. G., N. Harré, W. J. Hoverd and C. A. Houkamau (2011). "The gap in the subjective wellbeing of Māori and New Zealand Europeans widened between 2005 and 2009." Social indicators research 104(1): 103-115.

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Ware, J., K. Snow, M. Kosinski and B. Gandek (2000). SF-36 Health Survey : Manual and Interpretation Guide. Lincoln, Nebraska, Quality Metric Inc.

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