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Abstract

This paper presents the development and validation of a new well-being questionnaire: the Scales of General Well-Being (SGWB). A review of current measures identified fourteen common constructs as lower-order indicators of well-being: happiness, vitality, calmness, optimism, involvement, self-awareness, self-acceptance, self-worth, competence, development, purpose, significance, self-congruence and connection. Three studies were then conducted. In study 1, the item pool was developed and the adequacy of its content to assess each of the fourteen constructs was evaluated by consulting a panel of six subject expert academics. In study 2, the dimensionality was assessed in an adult North American sample (N = 560). The results supported the hierarchical factor structure. In study 3, further evidence confirmed the factor structure, and provided support for the measure's internal and test-retest reliability, measurement invariance across gender, age and a longitudinal period of 5 weeks, and criterion validity in an adult North American sample (N = 1101). The SGWB promises to be a useful research tool that provides both a global measure of well-being as well as a collection of fourteen individual health-related scales.

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... The Scale of General Well-being (Longo et al., 2017), a self-report scale measuring psychological growth and well-being through the facets of hedonic (subjective) and eudaimonic (psychological) wellbeing, is considered a measure of human flourishing and the organismic capacity for growth towards psychological change (ibid.). The short scale (Longo et al., 2018) was used in this study and consists of 14 items-reduced from the original 65-item version and validated in the clinic by Holland et al. (2021). ...
... For example, in the light of the positive associations between authenticity and well-being, it is possible there may be some overlap between the two concepts, explaining why the subjective experience of well-being and authenticity increases over time in therapy. This seems logical as well-being is said to reflect indicators such as self-awareness, congruence and self-acceptance (Longo et al., 2017), which are synonymous with Rogers' concept of congruence and the fully functioning person (Rogers, 1963). ...
... Interestingly, well-being was found to significantly correlate with, and predict, later levels of authenticity, which was not originally predicted. This would suggest, theoretically, that facets of wellbeing, such as happiness, vitality, calmness, optimism, involvement, self-awareness, self-acceptance, self-worth, competence, development, purpose, significance and connection (Longo et al., 2017) impact the degree to which one lives in accordance with their organismic experiencing. This suggests that therapy that works towards increasing well-being might lead to greater authenticity, rather than the other way around. ...
Article
There have been substantial research efforts demonstrating the effectiveness of person‐centred therapy. However, little research has investigated whether person‐centred therapy is effective in facilitating psychological growth amongst clients experiencing suicidal ideation and serious mental health difficulties. This study aimed to determine whether suicidal clients who received person‐centred therapy experienced increased levels of authenticity, well‐being and psychological distress. The predictive validity of authenticity and well‐being upon psychological distress was also tested. The study utilised quantitative, longitudinal methodology. Data were collected from a clinical sample of clients receiving person‐centred therapy at a counselling research clinic (N = 56) over the course of 20 sessions. There were statistically significant improvements in levels of authenticity, well‐being and psychological distress over 20 sessions of therapy; a minimum of 15 sessions were required for significant change to be observed. Authenticity and well‐being were negatively associated with psychological distress, whilst authenticity and well‐being were positively associated with each other. Early authenticity and well‐being predict levels of distress later in therapy. These results provide initial evidence to support Rogers' theory of therapy, which is suitable for clients experiencing both mild and severe distress; the findings refute the view that person‐centred therapy is only suitable for the “worried well.” There is now preliminary justification for person‐centred therapy being suitable for suicidal clients. Person‐centred therapists could consider offering suicidal clients at least 15 sessions to achieve meaningful change; ethical considerations pertaining to this are explored.
... There are many qualitative definitions of wellbeing, which define it in broad conceptual terms [1][2][3]. There are also many quantitative definitions of wellbeing, which describe it in terms of its constituents [4][5][6]. Imagine defining a modern smartphone to someone in 1970 by simply saying it is a hand-held electronic device (a qualitative definition) that consists of a case, battery, electrical components, and glass (a quantitative definition). Such a definition fails to convey the important knowledge of how it functions and why it is useful, and wellbeing definitions often fall short in a similar way. ...
... Based on the reviews of Hone et al. [4], Longo et al. [5], and Martela and Sheldon [6], Table 2 shows terms relevant to wellbeing (i.e., wellbeing constituents) within nine aspects. The nine aspects were developed iteratively by the author to thematically group all the wellbeing terms identified in these reviews. ...
... Vitality Physically capable of agency to increase fitness Vitality [5,72,73] Energy [74] Engagement Behaviour is likely to be increasing fitness (through learning, skill development, use of skills, etc.) ...
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A new model provides insight into the ‘how’ and ‘why’ of wellbeing to better understand the ‘what’. Informed by evolutionary psychology and neuroscience, it proposes that systems for adaptive motivation underpin experiential and reflective wellbeing. The model proposes that the brain learns to predict situations, and errors arise between the predictions and experience. These prediction errors drive emotional experience, learning, motivation, decision-making, and the formation of wellbeing-relevant memories. The model differentiates four layers of wellbeing: objective, experiential, reflective, and narrative, which relate to the model in different ways. Constituents of wellbeing, human motives, and specific emotions integrate into the model. A simple computational implementation of the model reproduced several established wellbeing phenomena, including: the greater frequency of pleasant to unpleasant emotions, the stronger emotional salience of unpleasant emotions, hedonic adaptation to changes in circumstances, heritable influences on wellbeing, and affective forecasting errors. It highlights the importance of individual differences, and implies that high wellbeing will correlate with the experience of infrequent, routine, and predictable avoidance cues and frequent, varied, and novel approach cues. The model suggests that wellbeing arises directly from a system for adaptive motivation. This system functions like a mental dashboard that calls attention to situational changes and motivates the kinds of behaviours that gave humans a relative advantage in their ancestral environment. The model offers a set of fundamental principles and processes that may underlie diverse conceptualisations of wellbeing.
... Fourth, we examined divergent and convergent construct validity by comparing related measures to the SVS-GM. Since subjective vitality is often described as an indicator of well-being (Guerin, 2012;Longo et al., 2017), we chose the construct of subjective well-being, which is described by life satisfaction and the balance between positive and negative affect (Diener, 1984). We hypothesized a moderate positive correlation between life satisfaction, positive affect, and subjective vitality (convergent validity), and a low to moderate negative relationship between negative affect and subjective vitality (divergent validity) (Hypothesis 4, H4). ...
... Construct validity was established by comparing the SVS-GM with convergent and divergent constructs. Our findings are in line with previous comparisons to positive affect (Martela and Ryan, 2016;Bertrams et al., 2020), negative affect (Ryan and Frederick, 1997;Bertrams et al., 2020), satisfaction with life (Ryan and Frederick, 1997;Castillo et al., 2017;Kawabata et al., 2017;Çelik, 2017;Goldbeck et al., 2019;Bertrams et al., 2020), and fatigue (Ryan and Frederick, 1997;Longo et al., 2017). Overall, the correlations show that the SVS-GM is related similarly to the important constructs used in other studies (H4, H7). ...
... Furthermore, the SVS-GM can be differentiated from optimism (H6), indicated by a low correlation between LOT-R and SVS-GM. Comparable findings (Huppert and So, 2013), and also higher correlations, between optimism and subjective vitality (Longo et al., 2017) are found in the literature. Optimism and generalized selfefficacy beliefs are said to be stable personality characteristics (Schwarzer, 1994;Glaesmer et al., 2008). ...
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Subjective vitality describes the positive feeling of experiencing physical and mental energy, which can lead to purposive actions, but no German instruments exist with action-oriented verbiage: This work supports the development and modification of already existing German Subjective Vitality Scales and provides further evidence for its psychometric properties. In a first step (N = 56) two modified (action-oriented) short-forms were developed. An extension of time perspectives (past, present, future) should also enrich the scale by enhancing the accuracy of self-reports. Study 1 (N = 183) then examined the psychometric properties for each time perspective. Study 2 (N = 27) was a 6-day diary study to identify the reliability of within- and between-person differences in vitality over time and working days with responses recorded three times per day. The exploratory factor analysis from study 1 revealed a three-factor solution with three items each. Test-retest reliability was moderate for the past and future time perspective and less stable for state subjective vitality. The modified German Subjective Vitality Scale (SVS-GM) showed divergent validity with fatigue, negative affect, and optimism, and convergent but distinguishable validity with life satisfaction, positive affect, and perceived self-efficacy. High reliability for daily vitality measures (with lower vitality rates in the morning) was found in study 2, but no substantial variation was found between working days and days off. The SVS-GM shows good psychometric properties in different settings and provides researchers with a 3-item (for cross-sectional or longitudinal studies) and 1-item (for short screenings) version to measure subjective vitality in German-speaking populations.
... Further, since these constructs were of different response format (i.e., five-point Likert scale type, six-point Likert scale, seven-point Likert scale type, 11-point Likert scale types, and 20-point Likert-scale), they were initially transformed to Z-score before combinations of scores were done (De Vaus, 2002;Harrison and McLaughlin, 1996). Also, a test of perceived value (seven-point Likert scale) of each construct was conducted to know the actual impact and relevance of construct to participant's life (Longo et al., 2017). These constructs were chosen based on four criteria namely, conceptual and general definition of wellbeing, commonalities in the conceptual definitions of construct review of psychometric attributes of previous constructs and shortcomings of previous measure of constructs (Longo et al., 2017;Chen et al., 2013). ...
... Also, a test of perceived value (seven-point Likert scale) of each construct was conducted to know the actual impact and relevance of construct to participant's life (Longo et al., 2017). These constructs were chosen based on four criteria namely, conceptual and general definition of wellbeing, commonalities in the conceptual definitions of construct review of psychometric attributes of previous constructs and shortcomings of previous measure of constructs (Longo et al., 2017;Chen et al., 2013). ...
... Though the current study is able to establish the link between deprivation and physical and mental health through SWB, further studies could be conducted to investigate the link between SWB and health through relative deprivation. Second, though the measurement of variables used in this study been proved to have high and acceptable internal consistency and validity [relative deprivation (Callan et al., 2008), MHI-5 (Ware et al., 1994, 1993Ayuso-Mateos et al., 1999), physical health (Rogers and Kelloway, 1997;Kelloway, 2000, 2003), SWB (Longo et al., 2017;Diener et al., 1985;Ryff, 1989;Keyes, 1998)], other approaches could be adopted to measure the variables. Besides, participant's ability to fully remember and give accurate picture on previous state of standard of living for assessing inter-temporal deprivation could be a major concern; notwithstanding, all items used to measure inter-temporal deprivation had high internal and external validity. ...
... Further, since these constructs were of different response format (i.e., five-point Likert scale type, six-point Likert scale, seven-point Likert scale type, 11-point Likert scale types, and 20-point Likert-scale), they were initially transformed to Z-score before combinations of scores were done (De Vaus, 2002;Harrison and McLaughlin, 1996). Also, a test of perceived value (seven-point Likert scale) of each construct was conducted to know the actual impact and relevance of construct to participant's life (Longo et al., 2017). These constructs were chosen based on four criteria namely, conceptual and general definition of wellbeing, commonalities in the conceptual definitions of construct review of psychometric attributes of previous constructs and shortcomings of previous measure of constructs (Longo et al., 2017;Chen et al., 2013). ...
... Also, a test of perceived value (seven-point Likert scale) of each construct was conducted to know the actual impact and relevance of construct to participant's life (Longo et al., 2017). These constructs were chosen based on four criteria namely, conceptual and general definition of wellbeing, commonalities in the conceptual definitions of construct review of psychometric attributes of previous constructs and shortcomings of previous measure of constructs (Longo et al., 2017;Chen et al., 2013). ...
... Though the current study is able to establish the link between deprivation and physical and mental health through SWB, further studies could be conducted to investigate the link between SWB and health through relative deprivation. Second, though the measurement of variables used in this study been proved to have high and acceptable internal consistency and validity [relative deprivation (Callan et al., 2008), MHI-5 (Ware et al., 1994, 1993Ayuso-Mateos et al., 1999), physical health (Rogers and Kelloway, 1997;Kelloway, 2000, 2003), SWB (Longo et al., 2017;Diener et al., 1985;Ryff, 1989;Keyes, 1998)], other approaches could be adopted to measure the variables. Besides, participant's ability to fully remember and give accurate picture on previous state of standard of living for assessing inter-temporal deprivation could be a major concern; notwithstanding, all items used to measure inter-temporal deprivation had high internal and external validity. ...
... Some studies have even found that models with a single factor show similarly good or superior fit to the data (Böhnke & Croudace, 2016;Burns, 2020;K. Kim et al., 2016;Longo et al., 2016Longo et al., , 2017. These studies converge to suggest that the underlying structure of wellbeing may, at least in part, consist of one or a few general wellbeing factors. ...
... All first-order factors loaded strongly on a higher-order wellbeing factor (the hfactor). This corroborates findings from several studies which have found evidence for a general higher-order factor in hierarchical or bifactor models of wellbeing (Chen et al., 2013;de Bruin & du Plessis, 2015;Gallagher et al., 2009;Gatt et al., 2014;Goodman et al., 2018;Hides et al., 2016;Jovanović, 2015;Longo et al., 2016Longo et al., , 2017. The hierarchical model can be interpreted as nested within the bifactor model, with relationships between the higher-order factor and observed items fully mediated by the first-order factors (Chen et al., 2006;Watkins, 2020;Yung et al., 1999). ...
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The structure of wellbeing has been debated for millennia. Dominant conceptualisations, such as the hedonic and eudaimonic models, emphasise different constituents of the wellbeing construct. Some previous studies have suggested that the underlying structure of wellbeing may consist of one or a few general wellbeing factors. We conducted three studies to advance knowledge on the structure of wellbeing comprising more than 21,500 individuals, including a genetically informative twin sample. In Study 1, we used hierarchical exploratory factor analysis to identify wellbeing factors in a population-based sample of Norwegian adults. We identified six wellbeing factors which all loaded on a single higher-order factor. This higher-order factor may represent a general “happiness factor”, i.e., an h-factor, akin to the p-factor in psychopathology research. In Study 2, we tested the fit of the identified factor model in an independent sample and obtained excellent fit. In Study 3, we examined genetic and environmental influences on wellbeing factors. All wellbeing factors showed modest genetic and substantial non-shared environmental influence, with heritability estimates ranging from 27-44%. Heritability was highest for the higher-order general happiness factor. Our findings yield novel insights into the structure of wellbeing and genetic and environmental influences on general wellbeing factors, with implications for wellbeing and mental health research, including genetically informative studies.
... Positive functioning means how well individuals are doing in managing own environment, achieving long-term purposes, making good relationships, and having high self-acceptance, contributing to self-actualization or personal growth. Additionally, a series of concepts in the literature have tried to capture as best as possible what it means for an individual to feel psychologically well: general WB (Longo et al., 2016(Longo et al., , 2017(Longo et al., , 2018, subjective WB (Diener, 2000;Lucas et al., 1996), psychological WB (Ryff, 1995(Ryff, , 2018, social WB (Keyes, 1998), positive mental health (Keyes, 2013), mental WB (Tennant & Conaghan, 2007), spiritual WB (Ellison, 1983;Fisher et al., 2000;Gomez & Fisher, 2003), and flourishing (Diener et al., 2010). Longo et al. (2018) highlight in a meta-analysis the existence of 14 main conceptualizations of WB in the literature: happiness, vitality, calmness, optimism, involvement, self-awareness, self-acceptance, self-worth, competence, development, purpose, significance, congruence, and connection. ...
... The items of the SDHS fit into the hedonic approach of WB, because they underlie the affective component of WB. The same researchers proposed a more comprehensive scale (Longo et al., 2017(Longo et al., , 2018 to measure WB, more precisely general WB. It is more comprehensive measure of WB, since it combines both hedonic with eudaimonic approaches of WB. ...
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Existing literature on measuring well-being (WB) indicates that The Short Depression-Happiness Scale (SDHS) is the only measure built on the negative–positive affect continuum. However, since the previous studies highlighted the psychometric properties of the SDHS exclusively using classical test theory (CTT), this research aims to fill this gap. By investigating the validity of this scale using both CTT and item response theory (IRT) approaches, this study aims to identify the precision of SDHS measurement. The sample consisted of 1326 Romanian participants (44.26% males, ages ranging from 18 to 64 years, Mage = 34.09, SD = 9.4). Results confirmed construct, convergent, and concurrent validity of the SDHS Romanian version. CFA replicated the unidimensionality found in the original study. The investigation of the scale precision through IRT showed that the SDHS is a highly reliable and accurate tool for capturing clinically low and moderate levels of WB, namely in the area of − 3.5 SD and + 1 SD from the mean of the latent trait. However, the scale does not perform well for higher levels of WB because there is no reliable information in the range between + 2 SD and + 3 SD of the latent trait continuum. Previous literature emphasized a similar pattern when measuring WB using the Warwick–Edinburgh Mental Well-Being Scale (WEMWBS). Additionally, the current study found that the SDHS has the advantage of measuring clinically low WB while the WEMWBS does not. The present research proposes a preliminary cut-off (< 7), before clinical assessment confirmation. Future clinical studies are needed. The findings of the current research should be useful for further psychometric developments of WB scales. Adding items of high difficulty would contribute to more measurement precision for higher levels of WB.
... Previous studies, however, are often limited by the focus on genetic overlap between specific Big Five factors (mostly Extraversion, Neuroticism, and Conscientiousness; Hahn et al., 2013;Røysamb et al., 2018) and/or specific well-being measurements (e.g., life satisfaction; Hahn et al., 2013;Røysamb et al., 2018). In addition, it is well known that self-reported personality traits share part of their variance (Kallio Strand et al., 2021;Schimmack & Kim, 2020;van der Linden et al., 2010), and the same holds for self-reports of different well-being measures (Bartels & Boomsma, 2009;Longo et al., 2017). By investigating the genetic overlap between specific traits (e.g., Neuroticism-life satisfaction), previous studies have failed to control for these common variances, which may have led to conflated estimates of the genetic associations. ...
... As noted, the most common distinction is made between SWB and PWB, but a proliferation of well-being models and measures have been developed over the years combining elements of both, and to which new elements are sometimes also added (Cooke et al., 2016). It has become increasingly clear that a strong general well-being factor underlies all the different well-being models and measures (Longo et al., 2017). Multiple lines of evidence lead to this conclusion. ...
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In the current study, common and unique genetic and environmental influences on personality and a broad range of well-being measures were investigated. Data on the Big Five, life satisfaction, quality of life, self-rated health, loneliness, and depression from 14,253 twins and their siblings (age M: 31.82, SD: 14.41, range 16–97) from the Netherlands Twin Register were used in multivariate extended twin models. The best-fitting theoretical model indicated that genetic variance in personality and well-being traits can be decomposed into effects due to one general, common factor ( Mdn: 60%, range 15%–89%), due to personality-specific ( Mdn: 2%, range 0%–78%) and well-being-specific ( Mdn: 12%, range 4%–35%) factors, and trait-specific effects ( Mdn: 18%, range 0%–65%). Significant amounts of non-additive genetic influences on the traits’ (co)variances were found, while no evidence was found for quantitative or qualitative sex differences. Taken together, our study paints a fine-grained, complex picture of common and unique genetic and environmental effects on personality and well-being. Implications for the interpretation of shared variance, inflated phenotypic correlations between traits and future gene finding studies are discussed.
... Alanyazında ruh sağlığını iyi olma halleri üzerinden ele alan farklı çalışmalar (Diener ve ark., 2010;Diener ve ark., 2009;Hills ve Argyle, 2002;International Wellbeing Group, 2013;Seligman, 2011;Smith ve ark., 2008;Tennatt ve ark., 2007) bulunmaktadır. Longo, Coyne ve Joseph (2017) tarafından geliştirilen ve 14 boyut ile iyi olmayı ölçümleyen "Genel İyi Oluş Ölçeği" ve Keyes (2002) tarafından geliştirilen ve ruh sağlığını duygusal, psikolojik, sosyal iyi olma üzerinden ölçümleyen "Ruh Sağlığı Sürekliliği Kısa Formu" geçerlik ve güvenirliği sağlanmış çok boyutlu önemli çalışmalardır. ...
Article
Bu araştırmada ruh sağlığı ve ölüm kavramı arasındaki ilişkiler ve yordayıcı etkiler alanyazındaki çalışmalardan farklı olarak çalışılmamış boyutlar üzerinden incelenmiştir. Bu doğrultuda ölüm kavramının farklı boyutları ele alınarak duygusal, psikolojik ve sosyal iyi olma üzerindeki etkilerinin ortaya konması amaçlanmıştır. Araştırma Antalya ilinde faaliyet gösteren CMB Yachts ve İstanbul ilinde faaliyet gösteren PwC şirketlerinde görev alan mavi ve beyaz yaka çalışanlar ve araştırmacının iletişimde olduğu sosyal kurumlardaki çalışmayanlar içerisinden rastgele örneklem seçimiyle 346 (kadın n = 207; erkek n = 139) gönüllü katılımcıyla gerçekleştirilmiştir. Araştırmada ölçme aracı olarak Ruh Sağlığı Sürekliliği Kısa Formu ve Çok Boyutlu Ölüm Farkındalığı Ölçeği kullanılmıştır. Araştırma analizleri SPSS ve AMOS programları kullanılarak korelasyon ve yapısal eşitlik modellemesi yöntemleriyle yapılmıştır. Araştırma bulgularına göre ölüm farkındalığının ruh sağlığı üzerinde anlamlı düzeyde negatif yordayıcı etkiye; ölüm mirasının psikolojik ve sosyal iyi olma üzerinde anlamlı düzeyde pozitif yönde yordayıcı etkiye sahip olduğu tespit edilmiştir. Öte yandan ölüm korkusu, ölümü kabul etme, ölümü güçsüzleştirme ve ölümü düşünmeme boyutlarının duygusal, psikolojik ve sosyal iyi olma üzerinde anlamlı düzeyde yordayıcı etkiye sahip olmadığı saptanmıştır. Çalışmada ölüm mirasının psikolojik ve sosyal iyi olma üzerindeki pozitif yordayıcı etkisi ve ölüm farkındalığının ruh sağlığı üzerindeki negatif yordayıcı etkisi ortaya konmuştur. Araştırmanın bulguları ilgili alanyazın çerçevesinde tartışılmış ve öneriler sunulmuştur.
... Given that we found both domain satisfaction and happiness also belong to subjective well-being, this begs the question: what other dimensions also belong to the construct? See Longo et al. (2017) for an initial attempt to do this. ...
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In homage to the life and work of Ed Diener (1946–2021), the present study assessed the dimensions of the tripartite model (positive affect, negative affect, and life satisfaction) and two additional dimensions (domain satisfaction and happiness) to investigate the structure of subjective well-being using exploratory factor analysis and the bifactor model. Specifically, we tested whether these five dimensions belong to an essentially unidimensional subjective well-being construct. Towards this goal, we used a large, previously collected dataset closely matched to the U.S. census (N = 2,000, ages 18–65+ ; 52.4% female; 66.3% White; 14.9% Hispanic; 12% Black) and selected 24 items representing the five dimensions. Our results showed that all 24 items were internally consistent and highly correlated. Exploratory factor analyses revealed there were five underlying factors best characterizing the data. When fit to the bifactor model, a strong underlying general subjective well-being factor emerged. Additionally, general factor scores were highly reliable according to conventional reliability standards. A confirmatory factor analysis also supported the bifactor structure of subjective well-being. Overall, our findings suggest all 24 items from the five dimensions reflect one essentially unidimensional construct, which can be combined into a single subjective well-being score. Domain satisfaction and subjective happiness both belong to subjective well-being in the same way that the original three dimensions of life satisfaction, negative affect, and positive affect do.
... There is also evidence for a similar relationship between mindfulness and measures of self-congruency. Specifically, Longo et al. (2017) found that higher levels of mindful awareness and acceptance were associated with greater self-perceived congruency between one's behaviours and sense of self. Further, Crane et al. (2008) showed that participation in Mindfulness-Based Cognitive Therapy (MBCT) lead to decreases in discrepancies between ideal self and actual self, compared to a waitlist control group. ...
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Instructed retrieval of positive autobiographical memories typically improves mood for healthy individuals, but not always for depressed individuals. No mood improvement may occur when depressed individuals retrieve positive memories that are self-incongruent, or when they ruminate upon positive memory retrieval. Mindfulness is associated with lower self-incongruency and rumination. The present study examined whether recurrent depression predicted emotional experience upon involuntary and voluntary retrieval of positive memories, and whether recurrent depression and trait mindfulness were associated with emotional experience upon positive memory retrieval through state rumination and self-incongruency. Recurrently and never-depressed individuals completed measures of depression, trait mindfulness, and a diary for reporting on everyday positive memories. Recurrently depressed individuals reported diminished happiness upon retrieving involuntary and voluntary positive memories compared to never-depressed individuals; and greater sadness upon involuntary positive memory retrieval, independent of current depression. Recurrent depression was associated with diminished happiness upon involuntary memory retrieval and greater sadness upon involuntary and voluntary positive memory retrieval, through state brooding, self-incongruency, or both. Higher trait mindfulness was associated with lower sadness upon involuntary and voluntary positive memory retrieval through state brooding and reflection. These findings highlight potential mechanisms in the relationship between depression vulnerability and emotional processing of positive autobiographical memories.
... Moreover, research was confirmed that individual spirituality influenced psychological wellbeing, happiness, resilience, self-esteem, efficacy, development, connection, congruence, vitality, and calmness, as well as optimism (Basileyo, 2019;Fukofuka, 2007;Ho et al., 2010;Joseph, 2017;Longo et al., 2017). However, Arin (2012) stated that hardiness in personality should include spiritual belief since the spiritual belief has an impact on people in collectivist cultures, especially in predominantly Buddhist countries (Myanmar, Laos, Cambodia, and Thailand). ...
Article
The objective of this study was to develop an influential model of work behavior encompassing the emotional intelligence, personality, and work environment of village health volunteers working under outbreak circumstances, with psychological capital as a mediator, during the COVID-19 pandemic in Thailand. A cohort of 425 village health volunteers (VHVs) was included in the research conducted in lower northern central Thailand. The data were analyzed using descriptive and inferential statistics, namely confirmatory factor analysis, correlation coefficients, and structural equation modeling. The results reveal that the measurement model fitted with the empirical data of χ2 = 119.78, df = 106, p = .17, CFI = 1.00, NNFI = 1.00, GFI = .98, AGFI = .93, RMSEA = .01, and χ2/df = 1.13. These findings indicate that psychological capital influenced the personality of VHVs. Furthermore, the work behavior of VHVs was also significantly influenced by EQ and the working environment (p = .01). Local administration and healthcare agencies should promote a conducive work environment and EQ to enhance VHVs’ psychological capital and work behavior for unanticipated crises in the future.
... In the context of strengthening the significant gains and contribution of organizational commitment on employee and organizational effectiveness, it is indispensable to discrimina profound state of work attitude characterized by vigor, dedication and absorption [46]. Quality of life is described to be the holistic wellness of persons and communities encompassing their physical health, material wealth, spiritual sensibilities, economic life and overall state of the environment [33]. Organizational commitment is a strong feeling of being involved, of being attached to an organization amidst unfavorable conditions and environment [6]. ...
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The purpose of this study was to determine the best fit model of organizational commitment among Certified Public Accountants. Employing the explanatory sequential mixed methods, stratified sampling, systematic selection approach, structural equation modeling technique and thematic analysis, data were obtained from 418 CPAs across sectors in Region XI. From the results of the study, it was found that the exogenous variables: self-efficacy, work engagement and quality of life are correlated with the endogenous variable that is organizational commitment. In addition, the results revealed that the standardized model 5 is the best fit model indicating the importance of work engagement and quality of life as predictors of organizational commitment among accounting professionals. These findings were further substantiated through the essential themes: work engagement as predictor of organizational commitment; quality of life as predictor of organizational commitment; affective commitment as observed variable of OC; normative commitment as observed variable of OC; and exclusion of self-efficacy as predictor of OC which were established from the experiences and insights of study participants.
... Alanyazında iyi oluşun pozitif duygu ve pozitif işlevsellik faktörlerinin genellikle farklı kavramlar olarak modellendiği ancak son zamanlarda yapılan bazı çalışmalar olumlu duygu ve olumlu işleyiş unsurlarının tek bir genel faktörle yeterince açıklandığını göstermiştir. Bu amaçla yola çıkan araştırmacılar tek bir genel iyi oluş faktörünün yeterliliğini, yüksek dereceli ve çift faktörlü modeller kullanarak test etmeye başlamış ve olumlu sonuçlar ortaya elde etmişlerdir (Longo, Coyne & Joseph, 2017). Örneğin, Huppert ve So (2013) iki faktöre yüklenen on maddeli iyi oluş modelini önermiştir. ...
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... In comparison, the eudemonic approach includes life domains, for example, the Psychological Theory of Wellbeing [19]. A commonality across wellbeing constructs is that they have a subjective experiential nature [47] and wellbeing is defined by a collection of indicators, not a single indicator [48]. See the review by Cooke and colleagues for a review of the measures of wellbeing [49]. ...
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Background Siblings of children with Prader-Willi syndrome (PWS) may be at elevated risk for poor psychological adjustment (Mazaheri, M. M., Rae-Seebach, R. D., Preston, H. E., Schmidt, M., Kountz-Edwards, S., Field, N., Cassidy, S., Packman, Wet al. (2013). The impact of Prader-Willi syndrome on the family’s quality of life and caregiving, and the unaffected siblings’ psychosocial adjustment. Journal of Intellectual Disability Research, 57(9), 861–873. ; O’Neill, L. P., & Murray, L. E. (2016). Anxiety and depression symptomatology in adult siblings of individuals with different developmental disability diagnoses. Research in Developmental Disabilities, 51, 116–125. ). The current study describes psychological distress and symptoms of post-traumatic stress disorder (PTSD) in non-disabled siblings. Method Fifty-eight siblings and 86 parents participated. Results Parents reported that almost 40% of siblings had psychological symptoms that exceeded clinical cut-off scores; 58.9% of siblings reported symptoms of PTSD that exceeded diagnostic cut-off scores. Symptoms were significantly related to family organisation and control per parent report and negative affect per sibling report. Conclusion Growing up with a sibling with PWS may challenge adaptive resources of non-disabled siblings, leaving them vulnerable to psychological distress. Those who care for children with PWS are in a unique position to educate families about the potential vulnerability of non-disabled siblings. We encourage routine screening and support for affected family members, especially siblings.
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Describes technological methods and tools for objective and quantitative assessment of quality of life (QoL) Appraises technology-enabled methods for incorporating QoL measurements in medicine Highlights the success factors for adoption and scaling of technology-enabled methods
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Pain is experienced either due to a physical condition, where it represents associated with actual or potential tissue damage, or due to a psychological situation, implying mental suffering, mental torment. Acute pain lasts for a limited amount of time and is provoked by a specific cause, while chronic pain is a long-term condition that drastically decreases quality of life and may affect patients absent from any biological cause. Chronic pain can affect cognitive functions (e.g., reasoning ability, attention, working memory), mood, sleep quality, sexual functions, and overall mental health. Generally, chronic pain therapy requires a multidisciplinary and complex approach. This chapter proposes a system called iSenseYourPain that continuously assesses chronic pain by leveraging ubiquitous sensor-based behavior assessment techniques. Based on findings from previous research and focusing on qualitative and quantitative assessment of patients’ behavior over time, the iSenseYourPain system is designed to automatically collect data from ubiquitous and everyday smart devices and identify pain-based behavior changes (e.g., changes in sleep duration and social interactions). It facilitates the providing of immediate assistance for pain and discomfort reduction by informing relatives and medical staff of the likelihood of potentially critical health situations. The overall goal of the iSenseYourPain system is to identify pain-related behavior changes in an accurate and timely manner in order to support patients and physicians, allowing the latter to have constant and accurate data on the patient’s condition.
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Similar to the concept of general well-being for individuals and societies, researchers have proposed various approaches to the concepts of personal beliefs and quality of life (QoL). In this chapter, QoL is discussed from an individual, subjective, cognitive and behavioral perspective with a focus on personal beliefs. More specifically, we present stress management as an endeavor in which yoga and personal beliefs can be applied to improve QoL. Stress management is recognized as a major health factor influencing an individual’s QoL. Empowered behavior to manage stress is discussed using a four-step model (involving thoughts, beliefs, emotions and behavior), that describes how human behavior is shaped by habits formed through individual experiences that unconsciously influence one’s thoughts, belief systems and emotions. Interventions such as yoga and meditation lead practitioners to question and alter thoughts in ways that can lead to improvements in QoL. Studies have indicated that when yoga and meditation are practiced regularly, the body implements stress-reducing processes automatically and unconsciously when a stressful situation arises. Therefore, this chapter contributes to the literature by demonstrating how yoga and meditation intervene in the mechanisms by which thoughts, beliefs and feelings shape behavior, as have been detailed in recent studies. In addition to the implementation of yoga and meditation, the possible use of technology and other tools for the quantitative assessment of states as a means of facilitating self-empowered behavior is discussed.
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In the WHO definition of Quality of Life, the environmental domain includes a subdomain called Opportunities for acquiring new information and skills . The information landscape has drastically changed over the past three decades, and now offers opportunities for acquiring information to almost everybody at any time, as the more recent technologies penetrated worldwide. It is thus worth evaluating if and how this change is reflected into the specific subdomain at stake and into the way it is measured. Before and while the information revolution was happening, the subdomain has been classically measured by giving as much attention to the accessibility of information as to the capability of acquiring it . We argue that these two components do not have the same weight nowadays, and that measurements should reflect this conceptual consideration. The more accessible information is indeed also often becoming overwhelming, and it is calling for an improved ability to appraise it. Technologies can help not just measuring the capability to appraise this information, but first and foremost they could build on individually acquired data to make the information more tailored to the user. This is done in other domains than health, and specifically in the marketing field, which has been already an inspiration for the health communication field and could contribute to advancements in the health behavioral domain. Therefore, after discussing how the concept of health literacy could inform the conceptual refinement of the subdomain at stake, this chapter will focus on how personal Internet-enabled technologies could contribute to its measurement in real-time, helping healthcare institutions and policy-makers to make health information more tailored and more accessible to the users.
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Daily behaviors influence an individual’s health and, in turn, all the domains of their quality of life (QoL). Accurately quantifying these behaviors may allow individuals to improve their overall awareness of these behaviors, make necessary habit changes, and receive more individualized treatment approaches. Currently, self-reported patient-reported outcomes (PROs) are the most common means of assessing daily behaviors. However, this method has multiple limitations, including the infrequency of collection, its subjective nature, its reliance on memory recall, and the influence of social norms. In comparison with PROs, using personalized and miniaturized technological innovations, including smartphones, mobile applications, and wearables, can enable the continuous assessment of daily life behaviors that contribute to or result from an individual’s QoL in a more accurate and timely manner. These technologies have the potential to transform the current state of quantifying QoL, allowing for improved research and the implementation of more individualized approaches to prevention and treatment. This chapter thus presents potential areas of future research and development opened by the use of these technologies in the field of QoL.
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Transportation has been recently recognized as a key element in the study of individual Quality of Life (QoL). However, relatively little is known about the interconnectedness between various transport dimensions and wellbeing measures. In scoping the existing literature, the chapter identifies studies reporting on a link between one of the seven transport indicators (mobility, affordability, accessibility, connectivity, externality, travel needs, and attitudes) and QoL. Based on the scoping review, a conceptual framework (TRAWEL) was deductively developed to understand wellbeing measures in five broader dimensions of transportation: transportation infrastructure, the built environment, and transport externalities at a societal level, travel and time use, and travel satisfaction at the individual level. Furthermore, the data requirements for accurate quantification and the possible study groups of interest are also discussed. The chapter concludes by summarizing the key points of the framework and by highlighting policy implications and areas for future research.
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Sleep is critical for a healthy, engaged and satisfying life. A large proportion of our lives is spent asleep, and a large proportion of our housing, resources, expenditure, and attention are dedicated to it. Good sleep strongly predicts better outcomes across a very broad range of life-long health, social, and industrial indices. Poor sleep has very significant and costly impacts upon physical and mental health (including metabolic health, depression, and anxiety), learning and education outcomes, and work-related outcomes (including stress, absenteeism, safety and performance). The social importance of good sleep can be seen in robust associations between sleep and loneliness, isolation, perceived social support, family and interpersonal relationships, and broader community participation and engagement. The availability and power of new sleep tracking devices mean that access and opportunity for satisfactory, satisfying, and sufficient sleep could be greatly increased. In this Chapter, we discuss the importance of sleep for quality of life and the limitations of existing monitoring technologies. We then introduce new tracking technologies and consider their benefits as well as potential pitfalls.
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Personal interactions are an important element of an individual’s health and life quality in the long term. As the site of many interpersonal interactions has been moved to the digital domain, human society has never been more intertwined. The digital footprints of interpersonal interactions can be quantified and measured via smartphones and wearables, providing more objective, quantitative, and accurate measurements. This chapter focuses on quantifying personal relationships in the context of quality of life, specifically focusing on novel technology-based quantification solutions. It first analyzes traditional qualitative quality of life measures based on subjective self-reporting that include measures of personal relationships, specifically the WHOQOL-BREF, WHOQOL-100, RAND-36, KIDSCREEN-27, SWLS, and Beach Center FQOL, as well as other non-validated measures. The chapter then proposes novel technological solutions for data gathering and analysis by introducing the concept of digital item representation, a process that leverages personal datasets originating from smartphones and wearables. The chapter also discusses issues relating to users’ privacy that influence the acceptance of such everyday technologies as well as the quality of data collected in the long term.
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Energy and fatigue carry important implications for vitality and overall quality of life. Lacking energy and experiencing fatigue can be both burdensome as well as adaptive. This chapter first classifies energy and fatigue and then reviews their measurement. This chapter closes with opportunities for future directions. Energy and fatigue are present under varying conditions including in daily performance, during and after acute physical or mental strain (capacity), and in the context of chronic conditions. Energy and fatigue have been measured both subjectively and objectively. Subjective outcomes can be derived from self-reported scales and prompts; objective outcomes may be derived from performance and capacity tasks and technology-reported physiological, biological, and behavioural markers. The scales and tasks employed to measure energy have been traditionally validated but may lack daily life context and ecological validity. Prompts and behavioural monitoring methods are emerging as promising alternatives. Energy and fatigue have also been routinely monitored for specific diseases and occupations. However, fewer studies monitor healthy individuals through consumer technology in daily life contexts. More research is needed for an objective, unobtrusive, longitudinal, and contextual measurement of energy and fatigue in the healthy general population, in service of improving health, wellbeing, and quality of life.
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This chapter provides an overview of the evidence linking mobility to quality of life (QoL). The findings showed that the operationalization of QoL varied across studies covering measures of physical or mental health, general health perception, life satisfaction, participation, illness intrusiveness, health-related QoL (HRQL) and global quality of life. These outcomes are sometimes single items or uni-dimensional constructs and sometimes profile measures, rendering the interpretation of findings in our context difficult. This complexity led to a revelation that one could think of QOL of the person differently from the QoL of the body. QoL of the person is best reflected through global QOL measures including those of life satisfaction whereas QoL of the body is reflected in outcomes related to aspects of function including physical, emotional, or psychological impairments, activity limitations and participation restrictions. This chapter will focus on the general construct of mobility, which is considered an activity limitation, and on the causes of limited mobility, impairments of structures and functions needed for mobility. A distinction is made between the between the person’s QoL and the body’s QoL. While the person’s QOL is best self-expressed, the body’s QOL could be monitored in real-time with the assistance of a growing portfolio of personal, wearable technologies. The chapter ends with thoughts about how QoL of the body, and especially mobility, could be monitored and what that future may look like.
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Sexual activity is an important facet of social functioning and quality of life (QoL) reflected in its inclusion in the World Health Organization’s generic, 26-item, quality of life instrument, the WHOQOL-BREF, in the item “how satisfied are you with your sex life?” Several instruments designed to assess sexual activity, function or QoL have been developed, varying in their scope, measurement properties, and applicability to certain populations. Evidence from literature reviews of instruments was synthesized to (a) identify generic self-administered instruments, which have been developed for research or clinical practice in adults and (b) to investigate their scope, psychometric properties, and applicability. We then considered these methods together with emerging Quality of Life Technologies. In total, 110 instruments were identified via nine reviews and 31 generic instruments were retained. There was a good evidence of the instruments’ internal consistency and reliability, but limited evidence of their responsiveness to change. While 31 instruments provide an adequate assessment of function/sexual QoL, fitting with COSMIN guidance, their scope varied and only three of these were developed since the revision of the definition of sexual dysfunction in 2013. Computerized self-reported measures may facilitate data collection yet were rarely discussed by authors. This meta-review has compiled evidence on generic instruments that can improve the collection of data on sexual function/QoL in research and clinical practice. We also discuss the emerging use of applications, connected wearables and devices that may provide another less invasive avenue for the assessment of sexual function/QoL at the individual and population level.
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Mobile network connectivity enables individuals to use various Internet-based applications and is nowadays an integral part of the physical environment. More specifically, this connectivity shapes individuals’ modes of gathering information and their communication capabilities. In turn, this impacts the individual’s decision-making and, in the long term, may influence their health and quality of life (QoL). This chapter focuses on longitudinal modeling of the availability of mobile connectivity such as Wi-Fi and 3G or 4G for individuals living in the Geneva area (Switzerland). We analyze connectivity over 5 years (2015–2020) based on data collected from 110 mQoL (mobile QoL) Living Lab participants. The participants are from three different cohorts corresponding to distinct data collection periods (2015–2017, 2018–2019, 2020). We derive four features that quantify an individual’s connectivity level: the network access technology (Wi-Fi or cellular), signal strength, the overall data consumption (upload and download), and the participants’ mobility patterns while connected. We also compare the connectivity levels of the three cohorts over time. Our findings reflect the relations between mobile connectivity and the smartphone network activity of the mQoL study cohorts during their daily activities, which may impact their QoL. We summarize the results and conclude this chapter by exploring the different QoL technologies and services enabled by mobile connectivity. However, the effects of connectivity on specific QoL domains, such as psychological aspects (i.e., positive/negative feelings) or social relationships, should be investigated further.
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An essential objective of preventive healthcare is to assess the lifestyle of citizens and identify those with health risk behaviors long time before they develop a lifestyle-related disease. In spite of lasting attempts to support preventive healthcare services in reaching individuals at risk through information campaigns, systematic health check programs, and more recently, data-driven approaches, citizens remain at a distance to the preventive healthcare services. The purpose of this chapter is to investigate the reasons for this distance between citizens and preventive care offers and the potential of quantified-self technologies for decreasing this. The analysis shows that while data-driven approaches to lifestyle assessment do assist preventive care services in screening a large population, they do not solve the fundamental challenge; that citizens are often challenged in relating to the risk assessment and in the consequences of their current behaviors on a long timescale. Based on these findings, two design implications are elicited to guide design of systems based on quantified-self to support early assessment and improvement of potentially unhealthy lifestyle, potentially improving health and quality of life in the long term.
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This chapter will discuss the usage of more objective and unobtrusive ways technology can be used to assess leisure activities. It is well known that leisure activities are positively correlated with measures of quality of life and subjective well-being. How we spend our free time has a great deal of influence on how we subjectively assess the quality of our lives. One aspect of our leisure time, which is gaining more and more interest, is the use of smartphones and wearables. According to global statistics, almost half of the global population spends more than 5 h a day using their smartphones. The use of technology has a profound effect on the way we spend our lives, socialize and entertain. Because our use of technology leaves a massive amount of digital data, we are now able to search for patterns of digital behaviour and use them as proxies or predictors for real life behaviours, bypassing or complementing self-reports and subjective measures. Our discussion revolves around several aspects of technology and leisure time. First, how technology use relates to leisure activities and what alternative unobtrusive measures could be developed to measure or predict leisure activities. Second, we will discuss the positive and negative aspects of technology use.
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Educational efforts and achievement in an individual’s youth influence their life-long social status and quality of life. Historically, higher education’s teaching relied on passive learning of hour’s long monologues delivered in person. This system puts in clear disadvantage and reduces the quality of life of many students who cannot attend lectures or keep up with the pace of learning. Fortunately, the current technology-led paradigm shift in undergraduate teaching and learning, addresses these challenges. Here we investigated: (1) what are the current assessment methods for cognitive state, memory and learning in healthy populations? (2) What types of platforms and tools offer alternative ways of learning and interacting in classrooms?; How can these platforms (3) support assessment of students’ cognitive state and learning process? and (4) support students with specific needs? To answer (1), we conducted scoping review on the current instruments and scales.; for (2) we interviewed digital learners, researchers, and faculty and created a list of platforms and tools, which were further analyzed to answer the last questions. We found that digital tools allow students to: (a) access course material remotely, (b) engage with classmates in groups/forums (c) work collaboratively on shared documents and (d) provide feedback and communicate anonymously with classmates and lecturers during and/or after lectures. We show that, while learning platforms and tools can adapt learning to the students’ abilities, learners and lectures require additional training/paradigm shift to fully benefit. We present results and discuss design implications for technologies, which, could boost learning and attainment of educational goals, particularly for “non-traditional” learners.
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An individual’s financial resources are directly related to their ability to meet current and future needs. Higher levels of financial assets and lower debt have been found to be positively associated with financial satisfaction. On the other hand, inadequate financial resources can lead to financial strain and financial distress. According to the WHOQOL theoretical model, financial resources refer to a person’s view of how his/her financial resources, the extent to which these resources meet the needs for a healthy and comfortable lifestyle, and what the person can afford or cannot afford which might affect quality of life. Few studies have addressed the impact of financial resources and financial burden on quality of life and the role of QoL technology-enabled tools for measuring and managing financial resource and improving quality of life. This chapter reviews the literature about (1) the effects of financial resources and financial burden on treatment outcomes and overall quality of life; (2) the state-of-art tools for measuring financial resources by individuals and financial and health professionals; (3) the evaluation of Web-based interventions for enhancing financial resource management; and (4) the behavioral and technology-related factors for successful adoption of QoL technology-enabled methods and financial resource management tools for improving individual life satisfaction and financial well-being.
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This chapter will detail how the advent of the internet and smartphones has fundamentally transformed the nature of social support and its effects on quality of life and health. Technological change has altered: (1) The ways in which we assess social support, (2) The perception and effects of social support. First, we will examine how recent technological innovations have allowed for more detailed, objective, and accurate assessments of social support. Digital technology has enabled us to go beyond simple self-report measures to assess social support and quality of life in unprecedented ways. By leveraging big data across several accessible technological platforms, researchers can begin to understand how social support processes unfold in real time and the myriad ways technology can be used to measure meaningful aspects of social support. In the second section, we will discuss how the concept of social support has changed in the age of digital communication. We will focus on how the presence and use of technological devices influences face-to-face interactions, online groups, and family dynamics. Taken together, this chapter will recognize the changes in social assessment afforded by technology and consider several important areas in which technological tools have transformed social support.
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Activities of Daily Living (ADL) has become a clinical de facto instrument to assess older people’s daily functional status living independently at home. This chapter focuses on a ‘smart home environment’ that contributes to the individual’s QoL and leverages a novel objective ADL assessment technology embedded in the home. This objective ADL (OADL) assessment is achieved through fusing data from simple, non-intrusive, always-on, wireless sensors placed in a home environment. To evaluate the OADL in older people, we conducted a 10-month pilot study with five eligible participants between 79 and 88 years old. In each participant’s home, we installed a smart home system. We presented OADL assessment to participants daily through a tablet app for self-management and caregivers through a web portal for decision-making. We then compare the similarity between OADL assessment and traditional self-reported Barthel ADL from participants. Initial study results demonstrated the great potential of the OADL as an effective daily functional status index and management instrument for caregivers to support beloved ones remotely and enable timely and early interventions when necessary. This chapter presents state of art in that domain and reflects on other design implications for a home environment, facilitating better health and life quality in the long term.
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Artificial Intelligence (AI) paves the way for many innovations and undoubtedly impacts individuals’ quality of life (QoL). It is also a risk factor, especially when it comes to personal safety and security. In today’s world, however, every person has a role to play in identifying and managing the risks of using AI, not only the AI experts. The first essential step in identifying those risks is to know individuals’ attitudes and motivations regarding the use of AI and the behaviors and practices of AI use (or non-use) they engage in. In 2016 and 2017, we surveyed 1000 bachelor’s and master’s students from various academic departments in Western Switzerland. We aimed to explore their current attitudes and motivations and outline scenarios for possible futures focusing on AI, security, safety, and QoL in Switzerland. This chapter summarizes the survey results and discusses individuals’ behaviors and interactions in the context of the identified scenarios. Based on the scenarios, we attempted to determine how businesses and governments in the present might seize future opportunities offered by AI while also addressing some of the implications of AI for individuals’ QoL. Our research results may serve as starting points to enrich discussion concerning AI and QoL and help individuals, along with businesses and governments, make better decisions in an increasingly connected world.
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Fitness technology, including trackers and smartphone applications (apps), has become increasingly popular for measuring and encouraging physical activity in recent years. Physical activity is closely linked with health and well-being; however, many Americans do not engage in regular exercise. This trend of inactivity increases with age and can interfere with an individual’s capacity to work. The benefits of physical activity and fitness extend beyond job performance and physical aspects of work capacity and include longer life and enhanced quality of life. This literature review addresses the question: How does the use of self-management QoL technologies affect work capacity and reported quality of life? It examines (1) the factors associated with variations in work capacity and quality of life; (2) the state-of-art of personalized, miniaturized computing QoL technologies for measuring and improving physical activity and fitness levels; (3) the use of activity trackers to quantify work capacity; and (4) strategies to enhance use of Web-based tools and fitness technology for behavioral change, health management, and rehabilitation interventions for the self-management of work capacity and enhancement of health-related quality of life across the lifespan. This chapter concludes with recommendations for future development of tools for the assessment and improvement of working capacity.
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Quality of life (QoL) refers to an individual’s well-being including their physical and psychological health, social relationships, and environmental domains. Current assessments of QoL are mostly qualitative and infrequent, following a self-reported approach. However, the recent widespread availability of personalized and miniaturized technological innovations, including mobile devices and applications, has enabled the continuous assessment of daily life behaviors that contribute to or result from the individual’s QoL. The continuous assessment of behaviors facilitates an enhanced understanding of an individual’s short-term as well as long-term health and QoL. This chapter outlines the World Health Organization Quality of Life (WHOQOL, and specifically the WHOQOL-BREF) instrument, which provides a way to categorize the behaviors and aspects of daily life that contribute to an individual’s QoL. As a result, the WHOQOL-BREF presented here serves as the organizational method for this book. Additionally, this chapter presents 71 technology-enabled daily life assessment studies conducted by “quantified-selfers” across the span of the last 6 years, and draws lessons learned by the community. Overall, this chapter illustrates how technology-enabled assessments of an individual’s daily life behaviors and QoL can complement current self-reported QoL assessments. Following this, each chapter within this book elaborates on technology-enabled assessments of a specific dimension of an individual’s QoL.
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Quality of life (QoL) is a subjective term often determined by various aspects of living, such as personal well-being, health, family, and safety. QoL is challenging to capture objectively but can be anticipated through a person’s emotional state; especially positive emotions indicate an increased QoL and may be a potential indicator for other QoL aspects (such as health, safety). Affective computing is the study of technologies that can quantitatively assess human emotions from external clues. It can leverage different modalities including facial expression, physiological responses, or smartphone usage patterns and correlate them with the person’s life quality assessments. Smartphones are emerging as a main modality, mostly because of their ubiquitous availability and use throughout daily life activities. They include a plethora of onboard sensors (e.g., accelerometer, gyroscope, GPS) and can sense different user activities passively (e.g., mobility, app usage history). This chapter presents a research study (here referred to as the TapSense study) that focuses on assessing the individual’s emotional state from the smartphone usage patterns. In this TapSense study, the keyboard interaction of n = 22 participants was unobtrusively monitored for 3 weeks to determine the users’ emotional state (i.e., happy, sad, stressed, relaxed) using a personalized machine learning model. TapSense can assess emotions with an average AUCROC of 78%(±7% std). We summarize the findings and reflect upon these in the context of the potential developments within affective computing at large, in the long term, indicating a person’s quality of life.
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Self-esteem, a person’s overall evaluation that she is valued and accepted vs. devalued and rejected by others, is crucial for people quality of life. As such, self-esteem has been central in the social-psychological literature since the late eighteenth century. However, its relevance is coupled with lack of agreement on how self-esteem is best conceived and assessed. Here we review definitions and measures of self-esteem in relation to quality of life in order (a) to understand how self-esteem has been defined, operationalized and assessed, and (b) to clarify which facets of self-esteem have been overlooked and need further study. Although we found multiple definitions of self-esteem, which led to a series of measures ranging from single item to multi-dimensional measures of state, trait and contingent self-esteem, the motivational component of self-esteem and its in-context behavioral correlates have yet to be operationalized. What follows, is that whether people think, feel, or behave in particular ways is caused by, concomitant with, or causes self-esteem, is still not understood. Because self-esteem is an emotionally laden system monitoring one’s relational value to others, we suggest that future research could use new technology-based research methods and eventually grasp real-time self-report and behavioral assessment of self-esteem. This appears a promising approach to overcome the limitations of self-esteem’s current theorizations and operationalizations. Thus, a new line of research considering the momentary experience of self-esteem, its behavioral components and its social context, could potentially unveil novel processes and mechanisms linking self-esteem and quality of life that have yet to be discovered and understood.
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Activities of Daily Living (ADLs) refers to the fundamental skills required to care for one-self and live independently and includes dressing, feeding, personal hygiene, continence and transferring. Assessing ADLs is therefore essential, especially for vulnerable population who may need assistance in performing these activities. As current validated scales to measure ADLs capacity are often dependent of an informant or a caregiver and are mainly performed in the controlled settings of the hospital, using technology-enabled tools could benefit individual’s health in terms of disease prevention and treatment but would also enhance individual’s quality of life and independence. This chapter presents 4 standard validated scales for ADLs and the current research activities on the use of technologies to assess one’s ability to perform ADLs, mainly indoor-outdoor mobility and nutrition. A nutrition assessment use case through a conversational agent is presented in the second part of the chapter. Future opportunities for technology-enabled ADL assessment are discussed.
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According to the literature, mindful self-care and resilience have a positive effect on psychological well-being both before and during COVID-19 pandemic. However, studies on mindful self-care are limited especially in a Turkish sample. In this paper, the relationship between mindful self-care, resilience, psychological well-being, and COVID-19 anxiety were discussed.
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Well-being is typically defined as positive feeling (e.g. happiness), positive functioning (e.g. competence, meaning) or a combination of the two. Recent evidence indicates that well-being indicators belonging to different categories can be explained by single “general” factor of well-being (e.g. Jovanovic, 2015). We further test this hypothesis using a recent well-being scale, which includes indicators of positive feeling and positive functioning (Huppert & So, 2013). While the authors of the scale originally identified a two-factor structure, in view of recent evidence, we hypothesize that the two-factor solution may be due to a method effect of different items being measured with different rating scales. In study 1, we use data from the European Social Survey round 3 (n = 41,461) and find that two factors have poor discriminant validity and, after using a bifactor model to account for different rating scales, only the general factor is reliable. In study 2, we eliminate method effects by using the same rating scale across items, recruit a new sample (n = 507), and find that a one-factor model fits the data well. The results support the hypothesis that well-being indicators, typically categorized as “positive feeling” and “positive functioning,” reflect a single general factor.
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The Dirty Dozen is a recently developed, concise measure of the Dark Triad (i.e., narcissism, psychopathy, & Machiavellianism). However, recent evidence has questioned the validity of this scale. In two studies we provide details about this measure in as much as it relates to the Big Five (i.e., Extraversion, Agreeableness, Conscientiousness, Emotional Stability, and Openness) whilst controlling for the shared variance amongst the three (Study 1: N = 123) and examining meta-traits and aspects of the Big Five (Study 2; N = 290). The Dirty Dozen subscales share an unstable core, which was localized to limited emotional stability, conscientiousness, and agreeableness. Each of the Dark Triad traits, however, was associated with unique aspects of the Big Five providing evidence that each trait measures something slightly different. For instance, psychopathy was linked to agreeableness through limited compassion but Machiavellianism was linked through limited politeness. In a series of factor analyses the scale is best explained by a bifactor model. Results provide multifaceted definitions of each of the aspects of the Dirty Dozen and evidence of its structural properties.
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Internationally, there is increasing interest in, and analysis of, human wellbeing and the economic, social, environmental, and psychological factors that contribute to it. Current thinking suggests that to measure social progress and national wellbeing we need more than GDP. Experts across a range of disciplines have increasingly highlighted a number of key values and domains of measurement that are influencing the way governments in different countries are thinking about wellbeing measures and policies. Most agree that it is important to involve citizen consultation in the design of wellbeing measures and policies. There is no real consensus on how to best do so. There are, however, the warnings of recent case studies that underscore the dangers of failing to consult with citizens adequately. The current paper examines the value of citizen consultations and considers how best to optimize deliberation and co-design by experts, citizens, and politicians using systems science tools that facilitate collective intelligence and collective action. The paper opens with an overview of the international wellbeing movement and highlights key issues in the design and application of wellbeing measures in policy practice. Next, an applied system science methodology, Interactive Management (IM), is described and affordances of IM considered in relation to the challenge of facilitating citizen consultations in relation to wellbeing measurement and policy design. The method can be used to provide insight into the values, goals, and preferences of citizens; engaging all stakeholders in a democratic, consensus building process that facilitates buy-in and enhances the legitimacy of decision-making groups; facilitating transparent understanding of the reasoning that informs the systems thinking of groups. A recent application of our applied system science methodology to the design of a notional national wellbeing index for Ireland is outlined. The paper closes by highlighting the importance of adopting a wider social science toolkit to the challenge of facilitating social progress.
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As Amazon’s Mechanical Turk (MTurk) has surged in popularity throughout political science, scholars have increasingly challenged the external validity of inferences made drawing upon MTurk samples. At workshops and conferences experimental and survey-based researchers hear questions about the demographic characteristics, political preferences, occupation, and geographic location of MTurk respondents. In this paper we answer these questions and present a number of novel results. By introducing a new benchmark comparison for MTurk surveys, the Cooperative Congressional Election Survey, we compare the joint distributions of age, gender, and race among MTurk respondents within the United States. In addition, we compare political, occupational, and geographical information about respondents from MTurk and CCES. Throughout the paper we show several ways that political scientists can use the strengths of MTurk to attract respondents with specific characteristics of interest to best answer their substantive research questions.
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Well-being theory (WBT) proposes five indicators of well-being [i.e., positive emotion, engagement, relationships, meaning, achievement (PERMA)] that are, independently , empirically supported predictors of flourishing (i.e., an optimal level of well-being; Seligman in Flourish: a visionary new understanding of happiness and well-being. Free Press, NY, 2011). However, there is limited empirical support for the multidimensional model suggested by WBT. Two studies sought to test and validate the higher-order factor structure of the five components of PERMA and PERMA's ability to predict concurrent and prospective flourishing outcomes (e.g., physical health, college success). In Study 1, a longitudinal examination of college students, participants completed measures of well-being (including four of the five PERMA indicators), physical health, and college success at the end of their sophomore, junior, and senior years. In Study 2, a larger, cross-sectional study was conducted online to further validate the PERMA model with a broader sample and all five PERMA indicators. Participants completed measures similar to those administered at Study 1 and other measures used to validate Study 1 measures. Results from Study 2 further validated the PERMA model by comparing Study 1 measures to established measures and by adding meaning to the model. Study 1 and Study 2 PERMA models predicted markers of well-being (e.g., vitality, life satisfaction) and flourishing (e.g., physical health). The two studies reported here provide cross-sectional and longitudinal support that WBT is useful for predicting flourishing.
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Many psychologists still regard correlations with social desirability (SD) scales as evidence of the invalidity of measures, despite 20 years of research showing that this interpretation is usually unjustified. Although items or scales may be characterized as high or low in SD, there is little evidence that individuals differentially respond to this property when completing self-report questionnaires under normal instructional conditions. In an attempt to separate substance from style in SD scales, self-reports from 215 adult men and women were compared to the external criterion of spouse ratings on a range of personality traits in the domains of neuroticism, extraversion, and openness to experience. When self-reports were 'corrected' using scores from the Eysenck Personality Inventory Lie scale and the Marlowe-Crowne SD scale, validity coefficients decreased, rather than increased, in most cases. Both scales were shown to be substantively related to neuroticism and, to a lesser degree, to extraversion and closedness. These results suggest that correlations with SD scales should be given substantive rather than artifactual interpretations and that the widespread practice of correcting scores for lying, defensiveness, or SD should be questioned.
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In structural equation modeling (SEM), researchers need to evaluate whether item response data, which are often multidimensional, can be modeled with a unidimensional measurement model without seriously biasing the parameter estimates. This issue is commonly addressed through testing the fit of a unidimensional model specification, a strategy previously determined to be problematic. As an alternative to the use of fit indexes, we considered the utility of a statistical tool that was expressly designed to assess the degree of departure from unidimensionality in a data set. Specifically, we evaluated the ability of the DETECT “essential unidimensionality” index to predict the bias in parameter estimates that results from misspecifying a unidimensional model when the data are multidimensional. We generated multidimensional data from bifactor structures that varied in general factor strength, number of group factors, and items per group factor; a unidimensional measurement model was then fit and parameter bias recorded. Although DETECT index values were generally predictive of parameter bias, in many cases, the degree of bias was small even though DETECT indicated significant multidimensionality. Thus we do not recommend the stand-alone use of DETECT benchmark values to either accept or reject a unidimensional measurement model. However, when DETECT was used in combination with additional indexes of general factor strength and group factor structure, parameter bias was highly predictable. Recommendations for judging the severity of potential model misspecifications in practice are provided.
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The satisfaction and frustration of the psychological needs for autonomy, relatedness and competence predict well-being and ill-being outcomes. However, research within educational and work contexts is stifled by the lack of an exhaustively validated measure. Following extensive preparatory and pilot work, the present three studies (total N = 762) aimed to develop such a measure and validate it against the Basic Need Satisfaction at Work Scale (Deci et al. in Personal Soc Psychol Bull 27(8):930–942, 2001) and an adapted version of the Balanced Measure of Psychological Needs (Sheldon and Hilpert in Motivation Emot 36(4):439–451, 2012). The Need Satisfaction and Frustration Scale demonstrated a better factor structure and internal reliability than its predecessors, and good criterion validity. This improvement was due to the exclusion of ambiguous items and items measuring antecedents of need satisfaction and frustration. The results also strengthen current evidence showing that need satisfaction and frustration are distinct but related constructs, and each better predicts well-being and psychological health problems, respectively
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Internationally, there is increasing interest in, and analysis of, human wellbeing and the economic, social, environmental, and psychological factors that contribute to it. Current thinking suggests that to measure social progress and national wellbeing we need more than GDP. Experts across a range of disciplines have increasingly highlighted a number of key values and domains of measurement that are influencing the way govern-ments in different countries are thinking about wellbeing measures and policies. Most agree that it is important to involve citizen consultation in the design of wellbeing mea-sures and policies. There is no real consensus on how to best do so. There are, however, the warnings of recent case studies that underscore the dangers of failing to consult with citizens adequately. The current paper examines the value of citizen consultations and considers how best to optimize deliberation and co-design by experts, citizens, and poli-ticians using systems science tools that facilitate collective intelligence and collective action. The paper opens with an overview of the international wellbeing movement and highlights key issues in the design and application of wellbeing measures in policy practice. Next, an applied system science methodology, Interactive Management (IM), is described and affordances of IM considered in relation to the challenge of facilitating citizen consultations in relation to wellbeing measurement and policy design. The method can be used to provide insight into the values, goals, and preferences of citizens; engaging all stakeholders in a democratic, consensus building process that facilitates buy-in and enhances the legitimacy of decision-making groups; facilitating transparent understanding of the reasoning that informs the systems thinking of groups. A recent application of our applied system science methodology to the design of a notional national wellbeing index for Ireland is outlined. The paper closes by highlighting the importance of adopting a wider social science toolkit to the challenge of facilitating social progress.
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In questionnaires, items can be presented in a grouped format (same-scale items are presented in the same block) or in a randomized format (items from one scale are mixed with items from other scales). Some researchers have advocated the grouped format because it enhances discriminant validity. The current study demonstrates that positioning items in separate blocks of a questionnaire may indeed lead to increased discriminant validity, but this can happen even in instances where discriminant validity should not be present. In particular, the authors show that splitting an established unidimensional scale into two arbitrary blocks of items separated by unrelated buffer items results in the emergence of two clearly identifiable but artificial factors that show discriminant validity.
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Discriminant validity assessment has become a generally accepted prerequisite for analyzing relationships between latent variables. For variance-based structural equa-tion modeling, such as partial least squares, the Fornell-Larcker criterion and the examination of cross-loadings are the dominant approaches for evaluating discriminant validity. By means of a simulation study, we show that these ap-proaches do not reliably detect the lack of discriminant valid-ity in common research situations. We therefore propose an alternative approach, based on the multitrait-multimethod ma-trix, to assess discriminant validity: the heterotrait-monotrait ratio of correlations. We demonstrate its superior performance by means of a Monte Carlo simulation study, in which we compare the new approach to the Fornell-Larcker criterion and the assessment of (partial) cross-loadings. Finally, we provide guidelines on how to handle discriminant validity issues in variance-based structural equation modeling.
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Structural equation modeling (SEM) is a vast field and widely used by many applied researchers in the social and behavioral sciences. Over the years, many software pack-ages for structural equation modeling have been developed, both free and commercial. However, perhaps the best state-of-the-art software packages in this field are still closed-source and/or commercial. The R package lavaan has been developed to provide applied researchers, teachers, and statisticians, a free, fully open-source, but commercial-quality package for latent variable modeling. This paper explains the aims behind the develop-ment of the package, gives an overview of its most important features, and provides some examples to illustrate how lavaan works in practice.
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The single-item measure of general happiness has been widely used in questionnaires due to the advantages of easy implementation in surveys for comparison across time and culture. The balanced response scale that includes equal positive and negative response categories based on Likert-type response format has been commonly applied. However, the possibility of using an unbalanced response scale for happiness, for instance, more choices on the happy side, has not been fully examined. This study aims to explore the optimal number of response categories and the corresponding labels for general happiness by using telephone survey data in Taiwan. Six types of response scales with different combinations of response number and response labels were examined to distinguish both the intensity and direction of responses. A completely randomized experimental design using computer-assisted telephone interviewing system was conducted to collect data from representative samples aged 18 years or older. Individual characteristics among the six groups indicated that all of the sub-samples were similar in terms of gender, age, education, marital status, working status, and monthly income. Results of the graded response model suggested that a scale with at least three response categories on the positive side and no more than two on the negative side will be suitable for the single measure of general happiness. Findings of ordered logit regression on happiness were also in favor of an unbalanced response design. A discussion of the result is provided.
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Data quality is one of the major concerns of using crowdsourcing websites such as Amazon Mechanical Turk (MTurk) to recruit participants for online behavioral studies. We compared two methods for ensuring data quality on MTurk: attention check questions (ACQs) and restricting participation to MTurk workers with high reputation (above 95% approval ratings). In Experiment 1, we found that high-reputation workers rarely failed ACQs and provided higher-quality data than did low-reputation workers; ACQs improved data quality only for low-reputation workers, and only in some cases. Experiment 2 corroborated these findings and also showed that more productive high-reputation workers produce the highest-quality data. We concluded that sampling high-reputation workers can ensure high-quality data without having to resort to using ACQs, which may lead to selection bias if participants who fail ACQs are excluded post-hoc.
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Developed, on the basis of responses from 608 undergraduate students to the 33-item Marlowe-Crowne Social Desirability Scale, three short forms of 11, 12, and 13 items. The psychometric characteristics of these three forms and three other short forms developed by Strahan and Gerbasi (1972) were investigated and comparisons made. Results, in the form of internal consistency reliability, item factor loadings, short form with Marlowe-Crowne total scale correlations, and correlations between Marlowe-Crowne short forms and the Edwards Social Desirability Scale, indicate that psychometrically sound short forms can be constructed. Comparisons made between the short forms examined in this investigation suggest the 13-item form as a viable substitute for the regular 33-item Marlowe-Crowne scale.
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The statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined. A drawback of the commonly applied chi square test, in addition to the known problems related to sample size and power, is that it may indicate an increasing correspondence between the hypothesized model and the observed data as both the measurement properties and the relationship between constructs decline. Further, and contrary to common assertion, the risk of making a Type II error can be substantial even when the sample size is large. Moreover, the present testing methods are unable to assess a model's explanatory power. To overcome these problems, the authors develop and apply a testing system based on measures of shared variance within the structural model, measurement model, and overall model.
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Much of the research in the last few years has linked the Dark Triad traits (narcissism, psychopathy, and Machiavellianism) to negative outcomes. In a sample of Polish undergraduate students, we examined how the Dark Triad traits differ in their relationships with eudaimonic and hedonic well-being. Narcissism was positively related to both variants of well-being, and after controlling for its shared variance with the other two dark traits its relations to well-being outcomes have noticeably increased. While psychopathy was related to lower levels of both eudaimonic and hedonic well-being, Machiavellianism was generally unrelated to well-being outcomes. The Dark Triad managed to predict unique variance in most of well-being scales, beyond broad personality factors. This research, depicting independent contributions of the Dark Triad traits to eudaimonic and hedonic well-being, suggested that having a sub-clinical narcissistic personality is helpful for living a good, full functioning life, and may even be useful for well-being of others.
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The primary purpose of this study was to profile the health-related quality of life (HRQoL) in a sample of secondary school-aged children in Australia. The secondary purpose was to contribute to the international literature on the HRQoL of adolescents using the KIDSCREEN instrument. The KIDSCREEN-27 Questionnaire was completed by 1111 adolescents aged between 11 and 17 from six Australian secondary schools. MANCOVA analysis was employed to examine age and gender differences. Over 70 % of participants reported high levels of HRQoL across all five dimensions. Age patterns were identified with younger adolescents reporting greater HRQoL than older adolescents. Similarly, gender differences were noted with male adolescents reporting higher scores than female adolescents on three out of five dimensions of HRQoL. This is the first study to measure HRQoL in Australian adolescents using the KIDSCREEN instrument. Consistent with previous research, gender and age differences were found across most dimensions of HRQoL. These results highlight the importance of comprehensively measuring the HRQoL in adolescents to capture developmental shifts and to inform preventative and supportive programs as needed.
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This article defines the construct of self-compassion and describes the development of the Self-Compassion Scale. Self-compassion entails being kind and understanding toward oneself in instances of pain or failure rather than being harshly self-critical; perceiving one's experiences as part of the larger human experience rather than seeing them as isolating; and holding painful thoughts and feelings in mindful awareness rather than over-identifying with them. Evidence for the validity and reliability of the scale is presented in a series of studies. Results indicate that self-compassion is significantly correlated with positive mental health outcomes such as less depression and anxiety and greater life satisfaction. Evidence is also provided for the discriminant validity of the scale, including with regard to self-esteem measures.
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Given that the root mean square error of approximation (RMSEA) is currently one of the most popular measures of goodness-of-model fit within structural equation modeling (SEM), it is important to know how well the RMSEA performs in models with small degrees of freedom (df). Unfortunately, most previous work on the RMSEA and its confidence interval has focused on models with a large df. Building on the work of Chen et al. to examine the impact of small df on the RMSEA, we conducted a theoretical analysis and a Monte Carlo simulation using correctly specified models with varying df and sample size. The results of our investigation indicate that when the cutoff values are used to assess the fit of the properly specified models with small df and small sample size, the RMSEA too often falsely indicates a poor fitting model. We recommend not computing the RMSEA for small df models, especially those with small sample sizes, but rather estimating parameters that were not originally specified in the model.
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-This report examined the factor structure of the Mental Health Continuum-Short Form (MHC-SF) using bifactor analysis to evaluate a general well-being factor and the three group factors that correspond with emotional, social, and psychological well-being. Using a sample of 902 South African psychology students (M age = 21.1 yr., SD = 2.7), the MHC-SF was examined using confirmatory factor models, (1) a one-factor model conceptualizing well-being as unidimensional, (2) a correlated three-factor model corresponding with Keyes' model, and (3) a bifactor solution with a general well-being factor and three orthogonalized group factors. The bifactor solution fitted the best and evidenced a strong general well-being factor and three comparatively weak residualized group factors. These findings contribute to the literature by facilitating an examination of the strength of a general well-being factor as contrasted with the multidimensional components of emotional, social, and psychological well-being and advance a case for the interpretation of both the general and multidimensional components. The results inform considerations regarding the employ of the scale in statistical procedures such as multiple regression analysis and structural equation modeling.
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This article reports the development and validation of a scale to measure global life satisfaction, the Satisfaction With Life Scale (SWLS). Among the various components of subjective well-being, the SWLS is narrowly focused to assess global life satisfaction and does not tap related constructs such as positive affect or loneliness. The SWLS is shown to have favorable psychometric properties, including high internal consistency and high temporal reliability. Scores on the SWLS correlate moderately to highly with other measures of subjective well-being, and correlate predictably with specific personality characteristics. It is noted that the SWLS is suited for use with different age groups, and other potential uses of the scale are discussed.
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The proposal of five dimensions of social well-being, social integration, social contribution, social coherence, social actualization, and social acceptance, is theoretically substantiated. The theoretical structure, constructure, construct validity, and the social structural sources of the dimensions of social well-being are investigated in two studies. Item and confirmatory factor analyses in both studies corroborate the theoretical model of social well-being. The new scales correlate convergently with measures of anomie, generativity, perceived social constraints, community involvement and neighborhood quality. The new scales correlate discriminantly with measures of dysphoria, global well-being, physical health and optimism. Multivariate analyses in both studies substantiate the claim that social well-being is an achievement, facilitated by educational attainment and age. The state and direction of the study of adult functioning are discussed.
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The Mental Health Continuum-Short Form (MHC-SF) is a growingly popular questionnaire designed to assess three components of well-being: emotional, social, and psychological. The main goal of the present study was to evaluate the structural validity of the MHC-SF and test the bifactor model of the MHC-SF, which includes one general factor and three specific factors of well-being. Sample 1 consisted of 1095 Serbian students (aged 18–26 years), while Sample 2 included 325 Serbian adults (aged 27–63 years). The bifactor model of the MHC-SF yielded the best fit to the data across the two samples. The results showed that the general factor of well-being accounted for substantially greater amount of variance of the MHC-SF than three specific factors of well-being. After controlling for the general factor, three specific factors explained a small portion of variance in well-being. In addition, the three subscales of the MHC-SF showed low reliability as estimated by omega-subscale coefficients, indicating that these subscales comprise too small amount of reliable variance to interpret. The present findings suggest that researchers should not calculate separate scores for three types of well-being when using the MHC-SF and that alternative measures of specific components of well-being should be considered.
Article
Survey respondents differ in their levels of attention and effort when responding to items. There are a number of methods researchers may use to identify respondents who fail to exert sufficient effort in order to increase the rigor of analysis and enhance the trustworthiness of study results. Screening techniques are organized into three general categories, which differ in impact on survey design and potential respondent awareness. Assumptions and considerations regarding appropriate use of screening techniques are discussed along with descriptions of each technique. The utility of each screening technique is a function of survey design and administration. Each technique has the potential to identify different types of insufficient effort. An example dataset is provided to illustrate these differences and familiarize readers with the computation and implementation of the screening techniques. Researchers are encouraged to consider data screening when designing a survey, select screening techniques on the basis of theoretical considerations (or empirical considerations when pilot testing is an option), and report the results of an analysis both before and after employing data screening techniques. Copyright © 2014 John Wiley & Sons, Ltd.
Article
Features the essential methodologies and statistical tools for developing reliable and valid survey questionnaires Modern survey design requires the consideration of many variables that will ultimately impact the quality of the collected data. Design, Evaluation, and Analysis of Questionnaires for Survey Research outlines the important decisions that researchers need to make throughout the survey design process and provides the statistical knowledge and innovative tools that are essential when approaching these choices. Over fifteen years of survey design research has been referenced in order to conduct a meta-analysis that not only unveils the relationship between individual question characteristics and overall questionnaire quality, but also assists the reader in constructing a questionnaire of the highest relevance and accuracy. Among the book's most outstanding features is its introduction of Survey Quality Prediction (SQP), a computer program that predicts the validity and accuracy of questionnaires based on findings from the meta-analysis. Co-developed by the authors, this one-of-a-kind software is available via the book's related Web site and provides a valuable resource that allows researchers to estimate a questionnaire's level of quality before its distribution. In addition to carefully outlining the criteria for high quality survey questions, this book also: Defines a three-step procedure for generating questions that measure, with high certainty, the concept defined by the researcher Analyzes and details the results of studies that used Multitrait-Multimethod (MTMM) experiments to estimate the reliability and validity of questions Provides information to correct measurement error in survey results, with a chapter focusing specifically on cross-cultural research Features practical examples that illustrate the pitfalls of traditional questionnaire design Includes exercises that both demonstrate the methodology and help readers master the presented techniques Design, Evaluation, and Analysis of Questionnaires for Survey Research succeeds in illustrating how questionnaire design influences the overall quality of empirical research. With an emphasis on a deliberate and scientific approach to developing questionnaires, this book is an excellent text for upper-level undergraduate or beginning graduate-level survey research courses in business and the social sciences, and it also serves as a self-contained reference for survey researchers in any field.
Article
Purpose: The current study mainly aimed to investigate the impact of social desirability in predicting life satisfaction in cognitively healthy elderly people. Methods: One hundred and seventy-eight 65- to 99-year-old adults were recruited in Sardinia, an Italian Isle known for the longevity of its inhabitants, and were presented a battery of questionnaires assessing subjective well-being, metacognitive efficiency, depressive symptoms and socially desirable responding style. Results: An analysis of covariance and a hierarchical regression analysis showed that the social desirable style does have a marginal impact on self-referent measures of life satisfaction. Indeed, only 5 % of the variance in life satisfaction was predicted by self-rated social desirability. Conclusions: Social desirability does not seem to bias the self-assessment of an important aspect of quality of life in late adulthood. That is, life satisfaction of Italian elderly people does not seem to be impacted by the tendency to present themselves in a more favourable way.
Book
Chapter 1: Introductory Factor Analysis Concepts Chapter 2: Requirements for and Decisions in Choosing Exploratory Common Factor Analysis Chapter 3: Requirements and Decisions for Implementing Exploratory Common Factor Analysis Chapter 4: Factor Analysis Assumptions Chapter 5: Implementing and Interpreting Exploratory Factor Analysis Chapter 6: Summary, Conclusions, and Recommendations
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The current studies examined the adverse effects of inattentive responding on compliance with study tasks, data quality, correlational analyses, experimental manipulations, and statistical power. Results suggested that 3–9% of respondents engaged in highly inattentive responding, forming latent classes consistent with prior work that converged across existing indices (e.g., long-string index, multivariate outliers, even–odd consistency, psychometric synonyms and antonyms) and new measures of inattention (the Attentive Responding Scale and the Directed Questions Scale). Inattentive respondents provided self-report data of markedly poorer quality, sufficient to obscure meaningful regression results as well as the effects of experimental manipulations. Screening out inattentive respondents improved statistical power, helping to mitigate the notable drops in power and estimated effect sizes caused by inattention.
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Psychological need constructs have received increased attention within self-determination theory research. Unfortunately, the most widely used need-satisfaction measure, the Basic Psychological Needs Scale (BPNS; Gagné in Motiv Emot 27:199–223, 2003), has been found to be problematic (Johnston and Finney in Contemp Educ Psychol 35:280–296, 2010). In the current study, we formally describe an alternate measure, the Balanced Measure of Psychological Needs (BMPN). We explore the factor structure of student responses to both the BPNS and the BMPN, followed by an empirical comparison of the BPNS to the BMPN as predictors of relevant outcomes. For both scales, we tested a model specifying three latent need factors (autonomy, competence, and relatedness) and two latent method factors (satisfaction and dissatisfaction). By specifying and comparing a series of nested confirmatory factor analytic models, we examine the theoretical structure of the need satisfaction variables and produce evidence for convergent and discriminant validity of the posited constructs. The results of our examination suggest that the three need variables should not be combined into one general need factor and may have separate satisfaction and dissatisfaction dimensions. Our model comparisons also suggest the BMPN may be an improved instrument for SDT researchers.
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Researchers often debate about whether there is a meaningful differentiation between psychological well-being and subjective well-being. One view argues that psychological and subjective well-being are distinct dimensions, whereas another view proposes that they are different perspectives on the same general construct and thus are more similar than different. The purpose of this investigation was to examine these two competing views by using a statistical approach, the bifactor model, that allows for an examination of the common variance shared by the two types of well-being and the unique variance specific to each. In one college sample and one nationally representative sample, the bifactor model revealed a strong general factor, which captures the common ground shared by the measures of psychological well-being and subjective well-being. The bifactor model also revealed four specific factors of psychological well-being and three specific factors of subjective well-being, after partialling out the general well-being factor. We further examined the relations of the specific factors of psychological and subjective well-being to external measures. The specific factors demonstrated incremental predictive power, independent of the general well-being factor. These results suggest that psychological well-being and subjective well-being are strongly related at the general construct level, but their individual components are distinct once their overlap with the general construct of well-being is partialled out. The findings thus indicate that both perspectives have merit, depending on the level of analysis.