Article

Day-of-week mood patterns in the United States: On the existence of ‘Blue Monday’, ‘Thank God it's Friday’ and weekend effects

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Abstract

There are many beliefs about the patterning of positive and negative mood over the course of the week. Support has been found for ‘Blue Monday’, ‘Thank God it's Friday’ and Weekdays versus Weekend effects, although in relatively small studies and often with student samples. Using telephone questionnaire data from a large national survey (N = 340,000), we examined day-of-week (DOW) effects on positive and negative moods. Unlike prior studies, we also tested the potential moderating effects of four demographic variables on DOW. Strong support was found for better mood on weekends and Fridays, but there was minimal support for a Blue Monday effect and no differences were observed between Saturdays and Sundays. Demographics moderated some DOW effects: DOW effects were diminished for older and retired respondents, but there was little DOW difference by gender or presence of a partner. DOW is associated with mood, but not always in ways we believe.

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... Again, these line up as expected, with the weekends rated as least stressful, and stress then rising over the week to peak on Friday (e.g. Stone et al., 2012). Overall, these results show good support for my model and theories. ...
... I start by looking at the idea of a "weekly mood cycle" (Stone et al., 2012), which is a well-established theory of mood fluctuation. There is good evidence, for example, for the 'weekend effect' of increased positive emotions (Harvey et al., 2015). ...
... There is good evidence, for example, for the 'weekend effect' of increased positive emotions (Harvey et al., 2015). But, in spite of these similarities, specific observed effects often vary with other factors such as age and working status (Stone et al., 2012). In this study, therefore, I propose day of the week simply as a frame linked to non-specific change in the ebb and flow of mood over time, without making stronger claims about particular weekday effects. ...
Thesis
Research on methods is a vital part of social science, but many desirable techniques come with high outlays. Adapting mobile technology for research offers new possibilities, including the promise of reduced costs, and access to hard-to-reach groups. However, these claims have been difficult to verify empirically. This thesis contributes to the literature in two fields. The first is psychology, where I investigate the parts and processes of experience formation in states of stress. Although there have been momentary studies of stress in everyday life, relatively few have looked at the interactions between dynamic and stable influences using the same instrument. I also address the comparability and generalisability of situations across persons, and the function of trait. My studies also make a methodological contribution to the field of experiential data measurement. The approach is based on experience-sampling, a well-established but traditionally hard-to-implement technique for assessing events as they occur. I describe the process of developing, administering, and evaluating a mobile version through case studies on divers populations. Throughout the studies, I examine whether technical advances can compensate for the increased burden of intensive self-report. I look at implications for researchers interested in working with experience sampling, and I aim to broaden access to such methods by setting out practical guidelines. I encourage researchers to consider the suitability of such methods for their work by demonstrating usability and flexibility. To do this, I carry out two exploratory studies, two multiple-subject substantive studies, and one single subject investigation. The evidence presented builds on research on state and temperament, and supports the idea that careful use of mobile technology can improve formerly cumbersome techniques, and apply them to varied populations. It demonstrates that adding momentary and situational information need not add substantially to costs. Finally, it implies cautions and recommendations for future development.
... These weekly patterns are intuitively expected, since as was mentioned by Mayor and Bietti [155], weekly patterns are generally associated with cultural traditions and the cultural distinction between weekdays and weekends in modern societies regulating social practices and behaviors. Similar results were reported for other countries both in the framework of traditional sociological research (e.g., [159,160]) and research based on digital traces (e.g., [24,156]). ...
... As for the weekly pattern, we clearly saw that weekends have higher levels of observable PA than weekdays. This result agrees with existing survey-based SWB [159,160] and OSWB [24,156] studies, since weekly patterns are generally associated with cultural traditions and the cultural distinction between weekdays and weekends in modern societies regulating social practices and behaviours [155]. Thus, in addition to the high level of correlation of observable PA with VCIOM Happiness, our daily and weekly patterns are also aligned with the existing body of research. ...
Article
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Policymakers and researchers worldwide are interested in measuring the subjective well-being (SWB) of populations. In recent years, new approaches to measuring SWB have begun to appear, using digital traces as the main source of information, and show potential to overcome the shortcomings of traditional survey-based methods. In this paper, we propose the formal model for calculation of observable subjective well-being (OSWB) indicator based on posts from a social network, which utilizes demographic information and post-stratification techniques to make the data sample representative by selected characteristics of the general population. We applied the model on the data from Odnoklassniki, one of the largest social networks in Russia, and obtained an OSWB indicator representative of the population of Russia by age and gender. For sentiment analysis, we fine-tuned several language models on RuSentiment and achieved state-of-the-art results. The calculated OSWB indicator demonstrated moderate to strong Pearson’s (r=0.733, p=0.007, n=12) correlation and strong Spearman’s (rs=0.825, p=0.001, n=12) correlation with a traditional survey-based Happiness Index reported by Russia Public Opinion Research Center, confirming the validity of the proposed approach. Additionally, we explored circadian (24 h) and circaseptan (7 day) patterns, and report several interesting findings for the population of Russia. Firstly, daily variations were clearly observed: the morning had the lowest level of happiness, and the late evening had the highest. Secondly, weekly patterns were clearly observed as well, with weekends being happier than weekdays. The lowest level of happiness occurs in the first three weekdays, and starting on Thursday, it rises and peaks during the weekend. Lastly, demographic groups showed different levels of happiness on a daily, weekly, and monthly basis, which confirms the importance of post-stratification by age group and gender in OSWB studies based on digital traces.
... Weekdays may call for greater regulation because of demands related to work and school, whereas individuals are likely less constrained by these sorts of professional contexts over the weekends. People also tend to feel more positive, on average, during weekends compared with weekdays (Stone et al., 2012) which may underlie less of a need to regulate on weekends compared with weekdays. ...
... Students likely encounter more stressors during the week as they attend to educational goals, potentiating the need for additional ER attempts on weekdays versus weekend days. In support of this idea, and in line with prior research (e.g., Stone et al., 2012) participants across both studies reported more negative affect on weekdays compared to weekends. Just as employees tend to use weekends and time away from work to recharge and de-stress, leading to an increase in positive emotions (Fuller et al., 2003), college students likely prioritize weekdays to make progress on their education, leaving weekends to socialize and engage in other activities (e.g., hobbies, time with family, etc.). ...
Article
Introduction: The current studies examined how smartphone-assessed contextual features (i.e., location, time-of-day, social situation, and affect) contribute to the relative likelihood of emotion regulation strategy endorsement in daily life. Methods: Emotion regulation strategy endorsement and concurrent contextual features were assessed either passively (e.g., via GPS coordinates) or via self-report among unselected (Study 1: N = 112; duration = 2 weeks) and socially anxious (Study 2: N = 106; duration = 5 weeks) young adults. Results: An analysis of 2,891 (Study 1) and 12,289 (Study 2) mobile phone survey responses indicated small differences in rates of emotion regulation strategy endorsement across location (e.g., home vs. work/education settings), time-of-day (e.g., afternoon vs. evening), time-of-week (i.e., weekdays vs. weekends) and social context (e.g., with others vs. alone). However, emotion regulation patterns differed markedly depending on the set of emotion regulation strategies examined, which likely partly explains some inconsistent results across the studies. Also, many observed effects were no longer significant after accounting for state affect in the models. Discussion: Results demonstrate how contextual information collected with relatively low (or no) participant burden can add to our understanding of emotion regulation in daily life, yet it is important to consider state affect alongside other contextual features when drawing conclusions about how people regulate their emotions.
... They documented that people tend to be more positive on weekends and early in the morning, and less on Mondays. Similar results are also reported in other studies (e.g., [52,53]). Ref. [54] showed that investors' moods, captured by Facebook status updates, deteriorate on Mondays, mainly for small capitalization indices and countries in which there is a greater desire to avoid uncertainty. ...
... In parallel, we do not reject the hypothesis that the happiness values on Monday equal those on Tuesday. These observations are in line with [52,65]. Both studies maintain that participants' mood on Monday is not significantly different from that observed on Tuesday. ...
Article
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We conduct a strict and broad analysis of the 30-day expected volatility (VIX) of five very active individual US stocks, three US domestic indices, and that of 10-year US Treasury notes. We find prominent non-random movement patterns mainly on Mondays and Fridays. Furthermore, significant leaps in expected volatility on Monday occur primarily in the first two and the fifth Mondays of the month. We also document that higher values for the 30-day expected volatility on Mondays are more likely when there was a negative change in the volatility on the preceding Fridays. This pattern does not occur on other subsequent days of the week. The results are robust through time and different subsamples and are not triggered by outliers or the week during which the options on the underlying assets expire. Rational and irrational drivers are suggested to explain the findings. Given that, to date, no one has conducted such an examination, our findings are important for investors interested in buying or selling volatility instruments.
... Yet, findings have been mixed regarding the exact pattern of change. Some scholars found clear patterns of increasing positive affect and/or decreasing negative affect over the week (Csikszentmihalyi & Hunter, 2003;Jones & Fletcher, 1996;Larsen & Kasimatis, 1990;Proudfoot et al., 2014), whereas others found a week versus weekday effect but only limited evidence for a trend over the days of the workweek (Areni & Burger, 2008;Stone et al., 1985Stone et al., , 2012. Notably, however, with one recent exception (Beal & Ghandour, 2011) these studies have been conducted using nonwork samples, that is, student samples (e.g., Egloff et al., 1995;Larsen & Kasimatis, 1990;Ram et al., 2005), clinical samples (Proudfoot et al., 2014), children (Csikszentmihalyi & Hunter, 2003), or samples drawn from the general population (e.g., Areni & Burger, 2008;Golder & Macy, 2011;Stone et al., 2012). ...
... Some scholars found clear patterns of increasing positive affect and/or decreasing negative affect over the week (Csikszentmihalyi & Hunter, 2003;Jones & Fletcher, 1996;Larsen & Kasimatis, 1990;Proudfoot et al., 2014), whereas others found a week versus weekday effect but only limited evidence for a trend over the days of the workweek (Areni & Burger, 2008;Stone et al., 1985Stone et al., , 2012. Notably, however, with one recent exception (Beal & Ghandour, 2011) these studies have been conducted using nonwork samples, that is, student samples (e.g., Egloff et al., 1995;Larsen & Kasimatis, 1990;Ram et al., 2005), clinical samples (Proudfoot et al., 2014), children (Csikszentmihalyi & Hunter, 2003), or samples drawn from the general population (e.g., Areni & Burger, 2008;Golder & Macy, 2011;Stone et al., 2012). Their generalizability to the working population is therefore limited. ...
Article
Affective well-being of employees is a key outcome in the occupational health literature. Yet, researchers of emotions and affect have long called for a better understanding of the dynamic nature of such experiences. Directly addressing this call, we have built on temporal schema theories and the notion of temporal depth to develop and test the anticipation of work account as a theoretical explanation of systematic weekly change patterns in positive and negative affect. Using a 7-day experience-sampling design and latent growth curve modeling, we hypothesized and found that anticipation of work linearly decreased over the course of the workweek, so did negative affect. Supporting our hypothesis that change patterns in work anticipation drive change patterns in evening affect, the linear change trajectory of anticipation was significantly related to change trajectories in positive and negative affect. Furthermore, we identified the structure of the workweek and chronic workload as boundary conditions that interact in shaping weekly change patterns in anticipation. Specifically, patterns of decreasing anticipation were most pronounced for employees with a regular Monday-Friday workweek and high chronic levels of workload, while they were weakest for employees with a regular workweek but low levels of chronic workload. Taken together, our results highlight the role of work itself and working conditions in dynamic aspects of affect. They yield theoretical and practical implications for the study of affect and its work-related experiential and behavioral consequences. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
... In surveys, participants are typically asked to report on general statements regarding how they typically see themselves (I usually try to help others), or regarding hypothetical acts (we should allow more refugees into our country). However, it is unclear if these statements translate to how individuals actually behave in specific situations, and may be particularly susceptible to outside influence (Areni, 2008;Barrett et al., 1998;Stone et al., 2012). ...
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The use of art installations to mediate people’s responses toward societal challenges— climate change, refugees, general prosocialness—is emerging as a main interest for arts institutions, artists, policy, and, recently, empirical study. However, there is still much need for data regarding whether and in what ways we might find detectable change. Even more, important questions concern whether typical methods, with two data points and theoretical question constructs, can reliably detect subtle impacts and, even if we do find change, how long effects last—a question which is almost completely unanswered in empirical research. We assessed an exhibition focused on power imbalances and acceptance for refugees, employing both a pre-post design (Study 1) and (Study 2) a daily diary method, which tracked participants’ reports, over two weeks, regarding how they had actually felt or acted each day and employing multilevel modeling to assess estimating changes from a first baseline week. The pre-post paradigm detected some reduction in self-assessed xenophobia and increased negative mood. However, effects were small/inconsistent with also some intriguing suggestions that people self-assessed as less empathic/prosocial than before visiting. The diary detected, inversely, several significant quadratic trends involving increased empathic concern and prosocialness-related thoughts and actions, but which returned to baseline by the next day. Only ‘trying to consider others feelings’ and ‘reflecting about oneself’ showed increases into the following week. Although non- significant, the diary changes also suggested some negative relations with the hypothetical self- assessment answers for the same questions, within participants, providing intriguing findings for much future research.
... Nielsen and Kaszniak (2007) proposed that those participants who are more emotionally aware are better emotion regulators, and those who underwent an emotion-related formal training may be more aware of their affective experiences than others. Gray and Watson (2007), in turn, observed that, unlike "high awareness" participants, those insensitive to changes in their affective state may rely on cultural and gender stereotypes when rating their current mood (e.g., see the Blue Monday and Thank God it's Friday effects; Stone et al., 2012). ...
Article
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Mood (i.e., our current background affective state) often unobtrusively yet pervasively affects how we think and behave. Typically, theoretical frameworks position it as an embodied source of information (i.e., a biomarker), activating thinking patterns that tune our attention, perception, motivation, and exploration tendencies in a context-dependent manner. Growing behavioural and electrophysiological research has been exploring the mood–language interactions, employing numerous semantics-oriented experimental paradigms (e.g., manipulating semantic associations, congruity, relatedness, etc.) along with mood elicitation techniques (e.g., affectively evocative film clips, music, pictures, etc.). Available behavioural and electrophysiological evidence has suggested that positive and negative moods differently regulate the dynamics of language comprehension, mostly due to the activation of mood-dependent cognitive strategies. Namely, a positive mood has been argued to activate global and heuristics-based processing and a negative mood – local and detail-oriented processing during language comprehension. Future research on mood–language interactions could benefit greatly from (i) a theoretical framework for mood effects on semantic memory, (ii) measuring mood changes multi-dimensionally, (iii) addressing discrepancies in empirical findings, (iv) a replication-oriented approach, and (v) research practices counteracting publication biases.
... People are happier on weekends than on weekdays (Stone et al., 2012), which is attributable to the fact that, compared to work, weekend activities provide higher autonomy and relatedness (Ryan et al., 2010). However, the affective experience associated with the weekend is not restricted to events that take place on Saturday and Sunday. ...
... Oppositely, previous studies highlighted an increase in vitality on weekend days due to a higher fulfillment of basic needs (Ryan et al., 2010;Weigelt et al., 2021). We assume that due to the high rate of days off in our sample, effects like Thank Goodness it's Friday or Blue Monday (Stone et al., 2012) are not strong enough to be influential in a more complex model. Experience-sampling studies that focused on the relationship between vitality and fatigue demonstrated that vitality decreases with an increase in experienced fatigue (Smolders et al., 2013;Weigelt et al., 2021). ...
Article
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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.
... In comparison to experience sampling methods that rely on repeatedly probing in real-time, the day reconstruction method is non-disruptive, places less burden on respondents, and provides an assessment of the experience of whole days instead of momentary snapshots. It has been used in research to study for example the experience of pain 31 , the relationship of socio-economic status to the prevalence of a number of common illnesses 32 , the influence of age on psychological well-being 33 and weekly affect patterns 34 . We used the proportion of "good" or "somewhat good" responses from among all responses in a day as our independent variable, measuring an aggregate of mood per day. ...
Article
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Measuring sentiment in social media text has become an important practice in studying emotions at the macroscopic level. However, this approach can suffer from methodological issues like sampling biases and measurement errors. To date, it has not been validated if social media sentiment can actually measure the temporal dynamics of mood and emotions aggregated at the level of communities. We ran a large-scale survey at an online newspaper to gather daily mood self-reports from its users, and compare these with aggregated results of sentiment analysis of user discussions. We find strong correlations between text analysis results and levels of self-reported mood, as well as between inter-day changes of both measurements. We replicate these results using sentiment data from Twitter. We show that a combination of supervised text analysis methods based on novel deep learning architectures and unsupervised dictionary-based methods have high agreement with the time series of aggregated mood measured with self-reports. Our findings indicate that macro level dynamics of mood expressed on an online platform can be tracked with social media text, especially in situations of high mood variability.
... We begin from the general observation that individual beliefs and behaviors often modulate based on specific temporal patterns. For example, across Germany, the UK, and the United States, happiness, stress, and job satisfaction systematically correlate to days of the week, in particular, to whether individuals are interviewed as the weekend approaches or ends (Akay and Martinsson 2009;Helliwell and Wang 2015;Stone, Schneider, and Harter 2012;Taylor 2006;Tumen and Zeydanli 2014). Closer to our specific research question, the Islamic holy month of Ramadan induces changes in individuals, including heightening prosocial and cooperative beliefs and behaviors Martinsson 2013, Akay, Karabulut, andMartinsson 2015;Seyyed, Abraham, and Al-Hajji 2005). ...
Article
Does attending communal religious services heighten the tendency to express exclusionary attitudes? Drawing on responses from thousands of Muslims, we identify how the ritual Friday Prayer systematically influences congregants' political and social attitudes. To isolate the independent role of this religious behavior, we exploit day-of-the-week variation in survey enumeration, which we assume to be plausibly uncorrelated with likely confounders, including self-reported religiosity. In our primary analysis, six variables charting various modes of intolerance each indicate that frequent attenders interviewed on Fridays (that is, proximate to the weekly communal prayer) were significantly more likely to express sectarian and antisecular attitudes than their counterparts. To test the potential mechanism behind this tendency, we rely on a controlled comparison between Egyptian and Algerian subgroups, as well as an original survey experiment in Lebanon. Evidence from both analyses is consistent with arguments that elite political messaging embedded in religious rituals spurs much of the observed variation.
... These findings propose that negative affect and mental distress may happen together on a peak day of the week. Stone et al. [37] reported better moods on Friday and weekends compared with weekdays. Similar results were reported by Ryan et al. [38] who described that mood variability during weekdays is highly associated with the type of work, and that this pattern was observed in both men and women. ...
Background: The purpose of the study was to assess the effect of diet quality and physical fitness on saliva cortisol, mood, and mental distress. These relationships were compared between a peak weekday (Wednesday) and a weekend day (Saturday) when mood may fluctuate. Methods: Forty-eight healthy college students participated in the study. Participants completed the Mood and Anxiety Symptom (MASQ) and Kessler Psychological Distress Scale 10 questionnaires on Wednesday and Saturday and recorded their diet for three days. Saliva was collected before and after a workout for cortisol extraction. Results: SA had significantly higher saliva cortisol levels post-workout but lower MASQ scores on Saturday (p < 0.05). There was a very significant association between MASQ scores on Wednesday (p = 0.005), which became less significant on Saturday. In addition, lower BMI values and high-fat consumption were associated with higher cortisol levels after exercise (p < 0.05). Conclusions: There is a strong link between dietary factors, cortisol levels, mood, and time of the week. In addition, our results suggest that saliva cortisol levels may not be directly linked to negative affect but are influenced by diet quality when mental distress exists. In addition, physical fitness may play a role in improving mood during weekends.
... Participants chose Tuesday, Wednesday, or Thursday for their day of participation. We decided to exclude Mondays and Fridays because of their unique characteristics regarding the week's rhythm, e.g., lower mood on Mondays (Areni et al., 2011) and higher mood on Fridays (Stone et al., 2012). Moreover, after-work free-time activities for Fridays may differ from those from Monday through Thursday, as plans for Fridays can include activities that last for the entire weekend. ...
Article
Previous research has shown that after-work free-time activities can enhance employees’ work engagement and positively affect their general well-being and health. This study investigates whether the anticipation of an after-work free-time activity boosts employees’ work engagement. Building on the conservation of resources (COR) theory, we assumed that employees’ pleasant anticipation of an after-work free-time activity positively relates to work engagement within and between persons. Furthermore, we examined the moderating role of recovery-related self-efficacy (RRSE). In Study 1, 85 employees completed three questionnaires (morning, noon, and afternoon) on one workday, and we expanded the design to a one-week diary in Study 2 (N = 56). Findings from (hierarchical) linear modeling supported the positive relationship between pleasant anticipation and work engagement between but not within persons. Moreover, RRSE was not found to be a moderator. Overall, our study demonstrated that employees vary in their pleasant anticipation, partly explaining differences in work engagement.
... We conducted the same analyses as described above by testing two repeated-measures logistic regression models with the outcome variable defined as the likelihood that a prompt yielded NA or PA. We tested a generalized linear mixed model with day of week to test day-specific effects on affective yield (Stone et al., 2012). Since participants only reported on social context if they endorsed any affect, it could not serve as a predictor variable. ...
Article
Background Ecological momentary assessment (EMA) is a high-frequency ambulatory data collection approach that has come to be widely used in emotion research. It therefore is timely to examine two features of EMA needed for a successful study: compliance with survey prompts and high affective yield (survey prompts that capture affect experience). We posit that compliance may be subject to temporal variation (time-of-day, days in study) and individual differences (depression history), and that affective yield may also differ by social context. Methods We examined these issues in a sample of 318 young adults (Mage = 24.7 years, SD = 2.7), including those with current depression (n = 28), remitted depression (n = 168) and never-depressed controls (n = 122) who participated in a 7-day EMA protocol of negative and positive affect (NA and PA, respectively). Results The overall compliance rate was 91% and remained stable across the survey week. However, subjects were significantly less likely to respond to the first daily prompt compared to those that followed. The likelihood of capturing NA and PA decreased with each EMA protocol day, and affective yield across social contexts differed by participants' depression status. Limitations The sample was largely comprised of White young adults. Relative to the remitted and control groups, the sample size for the currently depressed was unbalanced. Conclusion Researchers can optimize compliance and affective yield within EMA by considering depression, time-of-day, study duration, and social context. Clinicians using EMA to monitor affect may benefit from considering these parameters.
... There is also a complex literature on the effects of the day of the week when respondents were interviewed upon the measurement of variables of interest, inter alia:Taylor (2006);Akay and Martinsson (2009);Stone et al. (2012);Helliwell and Wang (2015);Tumen and Zeydanli (2014). ...
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We employ regression analysis of 2017 survey data from 4,067 Bangladeshis to exposit the lineaments of individual support for domestic Islamist violence. Our dependent variables derive from measures of public support for the stated goals and violent means of three Bangladeshi Islamist terrorist groups. Our study variables include participation in communal Friday prayer; indexed measures of other pietic practices; preferences for Shari'a and secularism; and gender. We include several well-established control variables. We find that participation in communal Friday prayers significantly correlates with diminished support for militant groups while having no effect upon support for their violent means. In four (of 10) models, we find that respondents who view Shari'a as being coterminous with scriptural literalism and harsh physical punishments are significantly more likely to support the groups' goals. Finally, we find women to be consistently more likely to support the goals and means of the militant groups.
... Notes 1 There is also a complex literature on the effects of the day of the week when respondents were interviewed upon the measurement of variables of interest, inter alia: Taylor (2006); Akay and Martinsson (2009) ;Stone, Schneider and Harter (2012), Helliwell and Wang (2015); Tumen and Zeydanli (2014). ...
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We employ regression analysis of 2017 survey data from 4,067 Bangladeshis to exposit the lineaments of individual support for domestic Islamist violence. Our dependent variables derive from measures of public support for the stated goals and violent means of three Bangladeshi Islamist terrorist groups. Our study variables include participation in communal Friday prayer; indexed measures of other pietic practices; preferences for Shari'a and secularism; and gender. We include several well-established control variables. We find that participation in communal Friday prayers significantly correlates with diminished support for militant groups' while having no effect upon support for their violent means. In four (of ten) models, we find that respondents who view Shari'a as being coterminous with scriptural literalism and harsh physical punishments are significantly more likely to support the groups' goals. Finally, we find women to be consistently more likely to support the goals and means of the militant groups.
... For example, demonstrating that more participants reported drinking and higher levels of drinking on Fridays and Saturdays compared to other days would provide basic evidence of Prolific's utility, as would finding that participants with more selfreported alcohol problems at baseline drink more across the 5-day study period. Other examples of theoretically consistent patterns of results would include participants reporting higher average levels of positive mood and lower levels of negative mood on weekend days and Fridays compared to other days of the week (Stone et al., 2012). ...
Article
The Prolific platform offers a potentially useful and efficient crowdsourcing option for repeated assessment substance use research, including for psychometric research requiring large samples. We present both (a) a series of practical recommendations for using Prolific and (b) data from multiple samples demonstrating Prolific's potential for efficiently collected repeated measures data. First, we present data from a 5-day daily diary protocol. We recruited a large sample (N = 321 at Day 1) screened for a history of self-identified mental health issues and weekly alcohol use. Participant adherence was good (82%) even without in-person contact. Alcohol use patterns conformed to theoretical expectations: Participants were more likely to drink on Fridays and Saturdays than other days, men drank more than women, and higher Alcohol Use Disorders Identification Test (AUDIT; Saunders et al., 1993) scores were associated with an increased likelihood of use and more overall drinking on a given day. Second, we present data from 429 Prolific participants screened for a history of mental health issues who completed assessments 2 weeks apart with strong retention (N = 377; 88%). We compare these data with the data from undergraduates (N = 529) to demonstrate Prolific's utility for conducting psychometrically oriented substance use research. Internal consistency estimates for measures from the Prolific data matched or exceeded those from the undergraduate data. Furthermore, measure scores showed strong temporal stability, and factor structures (e.g., AUDIT item-level structures) conformed to theoretical expectations. Collectively, these findings indicate that Prolific can be used successfully for repeated measures data collection. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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This article is about the impact of a four-day, five-day, and six-day school a week on the productivity and academic achievement of students, as well as their morale. We considered such extremely important components of education, for example, as study time and effort, which affects the process of reflection, and therefore these components determine how well and deeply a student will assimilate the knowledge acquired at the university. As part of the research, a survey was also conducted, in which 165 students from various faculties of the V.N. Karazin Kharkiv National University. Respondents expressed their judgments about the six-day school week, its impact on their productivity, physical, neuropsychological and moral-emotional state. We conducted an analysis of previous works and determined that academic success does not depend on the amount of study time spent on study, but on the contrary, this process is related to motivation, good mood, neuropsychological state, degrees of fatigue and the ability to rest. We also did not ignore the aspect of anxiety, so we interviewed students about this phenomenon. 62% of respondents noted that with the beginning of the six-day study at the university, the level of anxiety increased significantly. Which certainly has a negative impact on the academic performance of students, as well as directly on the learning process.
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The present study was aimed at analyzing differences between weekdays and weekends in psychological well-being, relationship satisfaction, and dyadic coping, as well as their associations, before and during the first COVID-19 lockdown in Italy. Individuals in a couple's relationship completed an online questionnaire before (N = 76) and during (N = 50) the COVID-19 lockdown. With regard to the first aim, participants in the COVID condition reported greater psychological well-being during weekends than during weekdays. In addition, participants showed greater relationship satisfaction during weekdays than during weekends, independently of the COVID-19 condition. As for the dyadic coping process, only in the Pre-COVID group, individuals communicated their stress more frequently during weekdays than during weekends. Finally, regardless of the COVID condition, they reported higher positive and common dyadic coping responses during weekends than during weekdays. As for the second aim, a positive effect of common dyadic coping responses on both psychological well-being and relationship satisfaction emerged during weekdays and weekends. Positive dyadic coping positively predicted relationship satisfaction during weekdays and weekends. Higher negative dyadic coping was associated with lower psychological well-being (in the Pre-COVID group only) and lower relationship satisfaction during weekends.
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Organisations consist of people and people are beings guided not only by rational cognitive processes but also by emotions and seemingly irrational motives based on affect. This chapter elucidates the matter of intra-and interpersonal emotion regulation at work through the prism of employees and their leaders. It provides a critical overview of multiple aspects of the topic, outlining their importance in terms of subjective wellbeing in the workplace and objective performance at work as well as contemporary theoretical frameworks and empirically-based practical solutions. It helps readers to understand conscious and subconscious processes of regulating own and others' emotions in occupational settings and explain various subsequent outcomes for organisations and their employees.
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Mood is an important ingredient of decision-making. Human beings are immersed into a sea of emotions where episodes of high mood alternate with episodes of low mood. While changes in mood are well characterized, little is known about how these fluctuations interact with metacognition, and in particular with confidence about our decisions. We evaluated how implicit measurements of confidence are related with mood states of human participants through two online longitudinal experiments involving mood self-reports and visual discrimination decision-making tasks. Implicit confidence was assessed on each session by monitoring the proportion of opt-out trials when an opt-out option was available, as well as the median reaction time on standard correct trials as a secondary proxy of confidence. We first report a strong coupling between mood, stress, food enjoyment, and quality of sleep reported by participants in the same session. Second, we confirmed that the proportion of opt-out responses as well as reaction times in non-opt-out trials provided reliable indices of confidence in each session. We introduce a normative measure of overconfidence based on the pattern of opt-out selection and the signal-detection-theory framework. Finally and crucially, we found that mood, sleep quality, food enjoyment, and stress level are not consistently coupled with these implicit confidence markers, but rather they fluctuate at different time scales: mood-related states display faster fluctuations (over one day or half-a-day) than confidence level (two-and-a-half days). Therefore, our findings suggest that spontaneous fluctuations of mood and confidence in decision making are independent in the healthy adult population.
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Organisations consist of people, and people are beings guided not only by rational cognitive processes but also by emotions and seemingly irrational motives based on affect. This chapter elucidates the matter of intra- and interpersonal emotion regulation at work through the prism of employees and their leaders. It provides a critical overview of multiple aspects of the topic, outlining their importance in terms of subjective wellbeing in the workplace and objective performance at work as well as contemporary theoretical frameworks and empirically-based practical solutions. It helps readers to understand conscious and subconscious processes of regulating own and others' emotions in occupational settings, and the authors explain various subsequent outcomes for organisations and their employees.
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The present research explored whether the well‐established U‐shaped relationship between age and happiness varied with personality. Individuals ranging from 15 to 75 years of age (N = 10,456, 84.9% female) completed online surveys of subjective well‐being (i.e. life satisfaction, positive affect, and negative affect) and the Big Five personality traits (International Personality Item Pool [IPIP]). The results of hierarchical multiple regression using the PROCESS macro not only supported the prediction of a U‐shaped relationship between age and well‐being but also revealed that the quadratic relationship is moderated by agreeableness and neuroticism. Specifically, well‐being did not bounce back in later adulthood on the well‐being curve across different age groups with low agreeableness and high neuroticism. Moreover, positive affect did not increase and even decreased in later adulthood among those with low agreeableness. This study discusses the potential mechanisms.
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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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Ambulatory assessment methods used to capture “real-world” microprocesses through self-report or passive data collection are used to assess child and adolescent behavior in context. This chapter begins by introducing the researcher to ambulatory assessment methods and describes these methods for use in child and adolescent developmental and behavioral research. Next, the importance of attention to timing is discussed. We then suggest appropriate analytic methods for putting ambulatory assessment data to best use to answer developmental research questions. We end with comments on the ethics of ambulatory assessment data and some concluding remarks for researchers wanting to use these methods in their own work.
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This study examined the relationship between time of day, day of the week, and two measures of positive affect (PA). According to previous research and the circumplex model of affect, one scale was designed to assess the activation component of PA, and the other one measured the pleasantness aspect. Subjects rated their mood three times a day for 7 consecutive days. Consistent with our hypotheses, PA-Pleasantness showed a peak on the weekend, whereas PA-Activation remained stable throughout the week. Regarding time of day, maximum PA-Activation was reached in the afternoon. In contrast, the Pleasantness component of PA increased from morning to evening. Implications of these results as well as other findings concerning the differential content of PA measures are discussed regarding the fact that a certain scale is most appropriate and maximally valid for representing certain aspects of affective experience.
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Two studies (N = 171) examined the prediction of 2 measures of daily mood, D. Watson's Positive and Negative Affect Schedule (PANAS; see record 1988-32714-001) and the Mood Adjective Checklist (MACL), by daily desirable and undesirable events and by day of the week. Both measures had similar and expected associations with daily events, although the MACL scale generally had stronger associations with events. Surprisingly, the pattern of day of the week effects for positive, yet not negative, mood were different for the 2 measures. MACL positive affect increased on weekends, relative to weekdays, whereas PANAS positive mood decreased on weekends. Also, for both positive and negative affect scales, the MACL scales had stronger associations with day of the week than did the PANAS scales.
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This paper uses the Experience Sampling Method data drawn from a national sample of American youth. It examines the proximal environmental factors as well as behaviors and habits that correlate to personal happiness. Momentary-level scores show that reported happiness varies significantly both by day of week and time of day. Furthermore, particular activities are associated with varying degrees of happiness. School activities rate below average scores in happiness, while social, active and passive leisure activities are above average. Particular companions also correlate to differing level of happiness. Being alone rates the lowest levels of happiness, while being with friend corresponds to the highest. Person-level averages of happiness suggest that both higher social class and age correlate with lower levels of happiness, while gender and race do not. Paradoxically, youth who spend more time in school and social activities are happier than those who spend less. Unexpectedly, students who spend more time pleasure reading report lower levels of happiness. Finally, feeling good about the self, excited, proud, sociable, active as well as being in the conditions for flow experience are the strongest predictors of trait happiness.
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The authors present in this study a damped oscillator model that provides a direct mathematical basis for testing the notion of emotion as a self-regulatory thermostat. Parameters from this model reflect individual differences in emotional lability and the ability to regulate emotion. The authors discuss concepts such as intensity, rate of change, and acceleration in the context of emotion, and they illustrate the strengths of this approach in comparison with spectral analysis and growth curve models. The utility of this modeling approach is illustrated using daily emotion ratings from 179 college students over 52 consecutive days. Overall, the damped oscillator model provides a meaningful way of representing emotion regulation as a dynamic process and helps identify the dominant periodicities in individuals' emotions.
Book
Autobiographical Memory and the Validity of Retrospective Reports presents the collaborative efforts of cognitive psychologists and research methodologists in the area of autobiographical memory. The editors have included an esteemed group of researchers whose work covers a wide range of issues related to autobiographical memory and the validity of retrospective reports, reflecting the diverse traditions in cognitive psychology and survey research. The first part of the book provides different theoretical perspectives on retrospective reports, along with supporting experimental evidence. The second part of this volume focuses specifically on retrospective reports of behaviors, including recall of the frequency and intensity of physical pain, of the number of cigarettes smoked, of dietary habits, and of child support payments. The following sections address the cognitive processes involved in event dating and time estimation, and a discussion of the differences between self and proxy reports. The final part extends the discussion of autobiographical memories in different directions, including the impact of autobiographical memories on individuals' assessment of their current life, the assessment of social change on the basis of retrospective reports, and the issue of collective memories. This book, an indispensable and timely resource for researchers and students of cognitive psychology as well as to survey methodologists and statisticians, demonstrates the considerable progress made in understanding the cognitive dynamics of retrospective reports.
Article
An Introduction to Survey Participation. A Conceptual Framework for Survey Participation. Data Resources for Testing Theories of Survey Participation. Influences on the Likelihood of Contact. Influences of Household Characteristics on Survey Cooperation. Social Environmental Influences on Survey Participation. Influences of the Interviewers. When Interviewers Meet Householders: The Nature of Initial Interactions. Influences of Householder-Interviewer Interactions on Survey Cooperation. How Survey Design Features Affect Participation. Practical Survey Design Acknowledging Nonresponse. References. Index.
Article
Based on concomitant time-series analyses, the results of this study support distinct social interaction correlates for the mood dimensions of negative affect (NA) and positive affect (PA). Participants (N = 25) completed structured diaries three times daily for 4 weeks assessing their PA, NA, and participation in five types of social interaction. A significant number of participants' data series evidenced significant positive correlations between PA and fun/active and necessary/informational types of social interaction, and between NA and arguing/confronting and receiving help/support, during synchronous diary periods. Providing help/support was not related to NA or PA. No hypothesized time-lagged relations between mood and social interaction variables were present suggesting that, if these associations exist, they may be at intervals shorter than the one third day recording frequency used in this study. Results are discussed in the context of research on mood, social interaction, and time-series analysis.
Article
Mood fluctuations in women and men were studied both prospectively and retrospectively to determine whether cyclic changes occur over phases of the menstrual cycle, lunar cycle, and/or days of the week. The participants (15 women using oral contraceptives, 12 normally cycling women, and 15 men), who did not know the purpose of the study, recorded the pleasantness, arousal, and stability of their moods daily for 70 days (concurrent data). Later they recalled (retrospective data) their average mood for each day of the week and phase of the menstrual cycle (women only). The only evidence of mood fluctuation over the menstrual cycle in the concurrent reports was that normally cycling women reported more pleasant moods in the follicular and menstrual phase than did men and women on oral contraceptives. Women's moods fluctuated less over the menstrual cycle than over days of the week. Recollections of menstrual mood changes differed from actual changes: Women recalled more pleasant moods in the follicular phase and more unpleasant moods in the premenstrual and menstrual phases than they had reported concurrently. Bias also was evident in recollections of weekday mood fluctuations: Weekend highs were exaggerated and Monday blues were reported even though they were not reported concurrently. There was no evidence of mood fluctuations over the lunar cycle and the groups did not differ in mood stability. The retrospective reporting bias for both the menstrual cycle and days of week suggests the influence of stereotypes about moods. Implications for research and practice are discussed.
Article
An Internet survey revealed that day-of-the-week (DOW) stereotypes (i.e., “Monday blues”, “Wednesday hump day”, “TGIF”, etc.) were pronounced when subjects predicted their moods for each day of the upcoming week, less obvious when they remembered their moods from each day of the preceding week, and least apparent in the momentary moods they actually experienced on each day. In a second study involving 2-hour, in-home interviews, subjects reporting looking forward to weekends because of the lack of structure and discipline and the freedom to choose activities, yet much of their weekend time was spent fulfilling a need to be productive, which often involved activities that, in many ways, simulated paid work. The content of these interviews suggested that people tend to overvalue future discretionary time on the weekend, assuming that two days of uninterrupted idle time will be more enjoyable than it actually is. In a more general sense, these results suggest that the predicted and remembered moods in the initial survey were driven by DOW stereotypes, which facilitated rapid judgements given the simple scaled response format. However, the depth interviews revealed that moods experienced throughout the week are more nuanced in terms of how they are remembered, described, and linked to recently passed, current, and immediately anticipated events, perhaps explaining why DOW stereotypes were less obvious in the reported momentary moods.
Article
Investigated perceptions of work characteristics and the effects of work on partners' physical and psychological well-being. 21 full-time working couples (married or cohabiting) completed daily questionnaires measuring sleep quality, work and domestic stressors, cognitive symptoms, mood, communication, and daily incidents for 3 wks. Mood and sleep fluctuated systematically over a week for both men and women. Significant correlations between home and work stressors and evening mood were found for both men and women. There was a significant difference between men and women in the number of interpersonal events reported. Results provide evidence of spillover effects from home to work. The daily diary questionnaire is said to offer potential for exploring detailed relationships between stressors and strains not offered by cross-sectional surveys. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Article
Conducted 3 studies, 2 using prospective and 1 using cross-sectional methods, to examine mood variation in married men over the days of the week. In Study 1, 46 Ss (mean age 42 yrs) kept a record of daily events, illnesses, and moods for 90 consecutive days. In Study 2, 58 Ss (mean age 43 yrs) also kept records, but for 112 days; severe dysphoric mood was also measured. 57 Ss in Study 2 also were asked on the telephone about which days of the week were worst and best for their mood. 21 Ss from this study also participated in a study in which they reported on their mood 5 times/day for 2 wks. In Study 3, 616 Ss (aged 18–60 yrs) completed 1 depressed mood scale. Although Ss thought that their mood was lowest on Monday, mood measures collected on a daily basis did not support the belief. Monday's mood was not different than mood on Tuesday, Wednesday, or Thursday, but positive mood was higher and negative mood was lower on the weekend; measures of depressed mood did not vary by day of the week. (14 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Article
The role of expectations based on the Monday-blues stereotype was explored in self-reports of mood throughout the week. Participants (N= 66) were allocated to 3 matched groups. Expectations were manipulated in 2 experimental groups: 1 in support of Monday blues and 1 against them. All participants completed the Positive and Negative Affect Schedule (PANAS) daily for 2 weeks, and ranked the days of the week in terms of mood after completion. While there were no effects on negative affect, the pro-blues group reported lower positive affect on Monday. All 3 groups recalled Monday as the worst day in terms of mood. This suggests that expectations have subtle effects on the experience of Monday blues, and highlights the discrepancies between prospective and retrospective self-reports.
Article
We examine the effects of weekend versus weekday and work versus nonwork experiences on mood and other well-being indicators in a sample of 74 men and women employed in a wide variety of occupations. It was hypothesized that both weekends and nonworking times would be associated with enhanced well-being, and that these relations would be mediated by greater satisfaction of autonomy and relatedness needs. In addition, we hypothesized that much of the weekend effect would be accounted for by the work versus nonwork contrast, given that work activities are expected to be associated with a lower sense of autonomy and relatedness than nonwork activities. Results supported these hypotheses, showing that for both male and female workers, weekend and nonwork activities were associated with several indicators of well-being, and these relations were partially or fully mediated by basic psychological need satisfaction. The findings are discussed in terms of mood variability and the implications of free time and work for workers' well-being.
Article
daily variations may be understood in terms of the degree to which three basic needs, autonomy, competence, and related-ness, are satisfied in daily activity. Hierarchical linear models were used to examine this hypothesis across 2 weeks of daily activ-ity and well-being reports controlling for trait-level individual differences. Results strongly supported the hypothesis. The authors also examined the social activities that contribute to sat-isfaction of relatedness needs. The best predictors were meaning-ful talk and feeling understood and appreciated by interaction partners. Finally, the authors found systematic day-of-the-week variations in emotional well-being and need satisfaction. These results are discussed in terms of the importance of daily activities and the need to consider both trait and day-level determinants of well-being.
Article
In a survey of 202 participants, Monday was cited most frequently as the worst morning (65%) and evening (35%); whereas Friday (43%) and Saturday (45%) were the best evening and morning, respectively. Test–retest reliability was higher for worst morning (.89) and evening (.83) judgments, compared to best morning (.44) and evening (.61) judgments. In a second survey of 353 participants, ratings of typical moods were lowest on Monday, rising to a peak on Saturday, but actual momentary moods showed little or no variation by day. Remembered moods from the previous Monday were more strongly related to typical moods than to actual moods, but the reverse was true of remembered moods from the previous Friday and Saturday.
Article
Self-determination theory (SDT) maintains that an understanding of human motivation requires a consideration of innate psychological needs for competence, autonomy, and relatedness. We discuss the SDT concept of needs as it relates to previous need theories, emphasizing that needs specify the necessary conditions for psychological growth, integrity, and well-being. This concept of needs leads to the hypotheses that different regulatory processes underlying goal pursuits are differentially associated with effective functioning and well-being and also that different goal contents have different relations to the quality of behavior and mental health, specifically because different regulatory processes and different goal contents are associated with differing degrees of need satisfaction. Social contexts and individual differences that support satisfaction of the basic needs facilitate natural growth processes including intrinsically motivated behavior and integration of extrinsic motivations, whereas those that forestall autonomy, competence, or relatedness are associated with poorer motivation, performance, and well-being. We also discuss the relation of the psychological needs to cultural values, evolutionary processes, and other contemporary motivation theories.
Article
Contents: Norbert Schwarz, Seymour Sudman: Introduction and overview (1-8); Part I. Perspectives on retrospective reports – William F. Brewer: Autobiographical memory and survey research (11-20); Douglas J. Herrmann: The validity of retrospective reports as a function of the directness of retrieval processes (21-38); Kurt W. Back: Accuracy, truth, and meaning in autobiographical reports (39-54); Michael Ross, Roger Buehler: On authenticating and using personal recollections (55-70); Mahzarin R. Banaji, Curtis: Affect and memory in retrospective reports (71-86). Part II. Retrospective reports of behaviors - Peter Salovey, William J. Sieber, Jared B. Jobe, Gordon B. Willis: The recall of physical pain (89-106); Barbara Means, Gary E. Swan, Jared B. Jobe, James L. Esposito: The effects of estimation strategies on the accuracy of respondents' reports of cigarette smoking (107-120); Albert F. Smith, Jared B. Jobe: Validity of reports of long-term dietary memories: data and a model (121-140); Nora Cate Schaeffer: Errors of experience: response errors in reports about child support and their implications for questionnaire design (141-160); Geeta Menon: Judgments of behavorial frequencies: memory search and retrieval strategies (161-172); Edward Blair, Kathleen Williamson: On providing population data to improve respondents' estimates of autobiographical frequencies (173-186); Norbert Schwarz, Hans-J. Hippler, Elisabeth Noelle-Neumann: Retrospective reports: the impact of response formats (187-199). Part III. Event dating and time estimation - Norman M. Bradburn, Janellen Huttenlocher, Larry Hedges: Telescoping and temporal memory (203-216); John J. Skowronski, Andrew L. Betz, Charles P. Thompson, W. Richard Walker, Laura Shannon: The impact of differing memory domains on event-dating processes in self and proxy reports (217-231). Part IV. Comparisons of self and proxy reports - David J. Mingay, Steven K. Shevell, Norman M. Bradburn, Carl Ramirez: Self and proxy reports of everyday events (235-250); Seymour Sudman, Barbara Bickart, Johnny Blair, Geeta: The effect of participation level on reports of behavior and attitudes by proxy reporters (251-266); Diane Holmberg, John G. Holmes: Reconstruction of relationship memories: a mental models approach (267-289). Part V. Memories of the past and judgment of personal and social change - Leslie F. Clark, James E. Collins II, Susan M. Henry: Biasing effects of retrospective reports on current self-assessments (291-304); Karl-Heinz Reuband: Reconstructing social change through retrospective questions: methodological problems and prospects (305-312); Howard Schuman, Cheryl Rieger, Vladas Gaidys: Collective memories in the United States and Lithuania (313-333).
Article
Green, Goldman, and Salovey (1993) challenged the view that "positive affect" and "negative affect" are largely uncorrelated dimensions. On the basis of factor analytic studies of happiness and sadness, and of positive and negative emotional activation (PA and NA), they claimed that a "largely bipolar structure of affect" (p. 1029) emerges when random and nonrandom error are taken into account. A reappraisal of their own findings and confirmatory analysis of additional data do not support this claim. Happiness and sadness form a largely unidimensional bipolar structure, but PA and NA are relatively independent. However, exploratory analyses yield a three-level hierarchy incorporating in one structure a general bipolar Happiness-Versus-Unhappiness dimension, the relatively independent PA and NA dimensions at the level below it, and discrete emotions at the base. We emphasize the heuristic value of a hierarchical perspective.
Article
This study addressed two questions: Do daily fluctuations in mood exhibit a 7-day (circaseptum) cycle, and are there reliable individual differences in how entrained people's moods are to such a weekly cycle? Spectral analysis of daily mood over 84 occasions revealed a strong weekly rhythm in the temporal organization of mood in a sample of 74 undergraduates. A sine wave with a period of 7 days accounted for 40% of the variance in the daily mood data. Individual differences were also found in how entrained subjects' moods were to this weekly rhythm. We predicted that extraverts (compared with introverts) should be less entrained to a weekly cycle. Results suggest that the novelty- and sensation-seeking behavior of extraverts most likely serves to lessen the cyclical predictability of their day-to-day moods. The origin and psychological meaning of the 7-day week are discussed.
Article
Seasonal variations in mood (seasonality) appear to be entrained to light, a physical zeitgeber. We hypothesised that people high in seasonality may be responsive to a range of zeitgebers, because of greater mood variability. We investigated whether the moods of people high in seasonality were more strongly entrained to the calendar week, a social zeitgeber, and whether any such effect was dependent on variability of mood. 53 participants (14 male, 39 female; overall mean age=30) completed a daily mood report, over 56 consecutive days. Participants also completed the Seasonality Score Index (SSI) of the Seasonal Pattern Assessment Questionnaire. Each participant's time series of daily mood was analysed by spectral analysis to quantify the strength of their weekly mood cycle. Participants with high SSI scores (> or =11) had significantly stronger weekly mood cycles than those with low SSI scores (<11), and significantly greater variability in mood. Covarying for mood variability reduced the difference between high and low SSI groups in mean strength of weekly mood cycle to non-significance. Limitations: The time series of moods obtained was relatively short, and moods among high seasonal participants may have been affected by seasonal weather variability. People high in seasonality appear to be more responsive to external zeitgebers, and this could be linked to their greater variability in mood. The integration of research on mood variability with research on SAD appears to be warranted.
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  • A A Stone
A.A. Stone et al. Downloaded by [Virginia Commonwealth University Libraries] at 23:49 04 October 2013
Psychological need satisfactions and day of week effects on mood, vitality, and physical symptoms
  • Work Weekends
Weekends, work, and well-being: Psychological need satisfactions and day of week effects on mood, vitality, and physical symptoms. Journal of Social and Clinical Psychology, 29, 95-122.