Predicting Mood Based on the Social Context Measured Through the Experience Sampling Method, Digital Phenotyping, and Social Networks.

Social interactions are essential for well-being. Therefore, researchers increasingly attempt to capture an individual's social context to predict well-being, including mood. Different tools are used to measure various aspects of the social context. Digital phenotyping is a commonly used technology to assess a person's social behavior objectively. The experience sampling method (ESM) can capture the subjective perception of specific interactions. Lastly, egocentric networks are often used to measure specific relationship characteristics. These different methods capture different aspects of the social context over different time scales that are related to well-being, and combining them may be necessary to improve the prediction of well-being. Yet, they have rarely been combined in previous research. To address this gap, our study investigates the predictive accuracy of mood based on the social context. We collected intensive within-person data from multiple passive and self-report sources over a 28-day period in a student sample (Participants: N = 11, ESM measures: N = 1313). We trained individualized random forest machine learning models, using different predictors included in each model summarized over different time scales. Our findings revealed that even when combining social interactions data using different methods, predictive accuracy of mood remained low. The average coefficient of determination over all participants was 0.06 for positive and negative affect and ranged from - 0.08 to 0.3, indicating a large amount of variance across people. Furthermore, the optimal set of predictors varied across participants; however, predicting mood using all predictors generally yielded the best predictions. While combining different predictors improved predictive accuracy of mood for most participants, our study highlights the need for further work using larger and more diverse samples to enhance the clinical utility of these predictive modeling approaches.

Feedback About a Person's Social Context - Personal Networks and Daily Social Interactions.

The social context of a person, meaning their social relationships and daily social interactions, is an important factor for understanding their mental health. However, personalised feedback approaches to psychotherapy do not consider this factor sufficiently yet. Therefore, we developed an interactive feedback prototype focusing specifically on a person's social relationships as captured with personal social networks (PSN) and daily social interactions as captured with experience sampling methodology (ESM). We describe the development of the prototype as well as two evaluation studies: Semi-structured interviews with students (N = 23) and a focus group discussion with five psychotherapy patients. Participants from both studies considered the prototype useful. The students considered participation in our study, which included social context assessment via PSN and ESM as well as a feedback session, insightful. However, it remains unclear how much insight the feedback procedure generated for the students beyond the insights they already gained from the assessments. The focus group patients indicated that in a clinical context, (social context) feedback may be especially useful to generate insight for the clinician and facilitate collaboration between patient and clinician. Furthermore, it became clear that the current feedback prototype requires explanations by a researcher or trained clinician and cannot function as a stand-alone intervention. As such, we discuss our feedback prototype as a starting point for future research and clinical implementation.

ESMvis: a tool for visualizing individual Experience Sampling Method (ESM) data.

PURPOSE: The experience sampling method (ESM) is used for intensive longitudinal time-series data collection during normal daily life. ESM data give information on momentary affect, activities and (social) context of, for example, patients suffering from mental disorders, and allows for person-specific feedback reports. However, current personalized feedback reports only display a selection of measured variables, and typically involve only summary statistics, thus not reflecting the dynamic fluctuations in affect and its influencing factors. To address this shortcoming, we developed a tool for dynamically visualizing ESM data. METHODS: We introduce a new framework, ESMvis, for giving descriptive feedback, focusing on direct visualization of the dynamic nature of raw data. In this ESM feedback approach, raw ESM data are visualized using R software. We applied ESMvis to data collected for over 52 weeks on a patient diagnosed with an obsessive-compulsive disorder with comorbid depression. RESULTS: We provided personalized feedback, in which both the overall trajectory and specific time moments were captured in a movie format. Two relapses during the study period could be visually determined, and subsequently confirmed by the therapist. The therapist and patient evaluated ESMvis as an insightful add-on tool to care-as-usual. CONCLUSION: ESMvis is a showcase on providing personalized feedback by dynamic visualization of ESM time-series data. Our tool is freely available and adjustable, making it widely applicable. In addition to potential applications in clinical practice, ESMvis can work as an exploratory tool that can lead to new hypotheses and inform more complex statistical techniques.

Assortative mating for human height: A meta-analysis.

OBJECTIVES: The study of assortative mating for height has a rich history in human biology. Although the positive correlation between the stature of spouses has often been noted in western populations, recent papers suggest that mating patterns for stature are not universal. The objective of this paper was to review the published evidence to examine the strength of and universality in assortative mating for height. METHODS: We conducted an extensive literature review and meta-analysis. We started with published reviews but also searched through secondary databases. Our search led to 154 correlations of height between partners. We classified the populations as western and non-western based on geography. These correlations were then analyzed via meta-analytic techniques. RESULTS: 148 of the correlations for partner heights were positive and the overall analysis indicates moderate positive assortative mating (r = .23). Although assortative mating was slightly stronger in countries that can be described as western compared to non-western, this difference was not statistically significant. We found no evidence for a change in assortative mating for height over time. There was substantial residual heterogeneity in effect sizes and this heterogeneity was most pronounced in western countries. CONCLUSIONS: Positive assortative mating for height exists in human populations, but is modest in magnitude suggesting that height is not a major factor in mate choice. Future research is necessary to understand the underlying causes of the large amount of heterogeneity observed in the degree of assortative mating across human populations, which may stem from a combination of methodological and ecological differences.

Does natural selection favour taller stature among the tallest people on earth?

The Dutch are the tallest people on earth. Over the last 200 years, they have grown 20 cm in height: a rapid rate of increase that points to environmental causes. This secular trend in height is echoed across all Western populations, but came to an end, or at least levelled off, much earlier than in The Netherlands. One possibility, then, is that natural selection acted congruently with these environmentally induced changes to further promote tall stature among the people of the lowlands. Using data from the LifeLines study, which follows a large sample of the population of the north of The Netherlands (n = 94 516), we examined how height was related to measures of reproductive success (as a proxy for fitness). Across three decades (1935-1967), height was consistently related to reproductive output (number of children born and number of surviving children), favouring taller men and average height women. This was despite a later age at first birth for taller individuals. Furthermore, even in this low-mortality population, taller women experienced higher child survival, which contributed positively to their increased reproductive success. Thus, natural selection in addition to good environmental conditions may help explain why the Dutch are so tall.

Taking the aggravation out of data aggregation: A conceptual guide to dealing with statistical issues related to the pooling of individual-level observational data.

Field data often include multiple observations taken from the same individual. In order to avoid pseudoreplication, it is commonplace to aggregate data, generating a mean score per individual, and then using these aggregated data in subsequent analyses. Aggregation, however, can generate problems of its own. Not only does it lead to a loss of information, it can also leave analyses vulnerable to the "ecological fallacy": the drawing of false inferences about individual behavior on the basis of population level ("ecological") data. It can also result in Simpson's paradox, where relationships seen at the individual level can be completely reversed when analyzed at the aggregate level. These phenomena have been documented widely in the medical and social sciences but tend to go unremarked in primatological studies that rely on observational data from the field. Here, we provide a conceptual guide that explains how and why aggregate data are vulnerable to the ecological fallacy and Simpson's paradox, illustrating these points using data on baboons. We then discuss one particular analytical approach, namely multi-level modeling, that can potentially eliminate these problems. By highlighting the issue of the ecological fallacy, and increasing awareness of how datasets are often organized into a number of different levels, we also highlight the manner in which researchers can more positively exploit the structure of their datasets, without any information loss. These analytical approaches may thus provide greater insight into behavior by permitting more thorough investigation of interactions and cross-level effects.

A statistical approach to distinguish telomere elongation from error in longitudinal datasets.

Telomere length and the rate of telomere attrition vary between individuals and have been interpreted as the rate at which individuals have aged. The biology of telomeres dictates shortening with age, although telomere elongation with age has repeatedly been observed within a minority of individuals in several populations. These findings have been attributed to error, rather than actual telomere elongation, restricting our understanding of its possible biological significance. Here we present a method to distinguish between error and telomere elongation in longitudinal datasets, which is easy to apply and has few assumptions. Using simulations, we show that the method has considerable statistical power (>80 %) to detect even a small proportion (6.7 %) of TL increases in the population, within a relatively small sample (N = 200), while maintaining the standard level of Type I error rate (α ≤ 0.05).

Non-linear associations between stature and mate choice characteristics for American men and their spouses.

OBJECTIVES: Although male height is positively associated with many aspects of mate quality, average height men attain higher reproductive success in US populations. We hypothesize that this is because the advantages associated with taller stature accrue mainly from not being short, rather than from being taller than average. Lower fertility by short men may be a consequence of their and their partner's lower scores on aspects of mate quality. Taller men, although they score higher on mate quality compared to average height men, may have lower fertility because they are more likely to be paired with taller women, who are potentially less fertile. METHODS: We analyzed data from The Integrated Health Interview Series (IHIS) of the United States (N = 165,606). Segmented regression was used to examine patterns across the height continuum. RESULTS: On all aspects of own and partner quality, shorter men scored lower than both average height and taller men. Height more strongly predicted these aspects when moving from short to average height, than when moving from average to taller heights. Women of a given height who scored lower on mate quality also had shorter partners. CONCLUSIONS: Shorter men faced a double disadvantage with respect to both their own mate quality and that of their spouses. Scores of taller men were only marginally higher than those of average height men, suggesting that being tall is less important than not being short. Although effect sizes were small, our results may partly explain why shorter and taller men have lower fertility than those of average stature.

Explaining uncertainty in women's fertility preferences.

People's fertility preferences are often considered an important determinant of fertility. What is often neglected in studies of preferred fertility, is the uncertainty that people may have about their preferences. In this study, using data on Dutch women through the Longitudinal Internet studies for the Social Sciences (collected early 2018), we examined women's fertility preferences and asked detailed questions about the certainty of these preferences. We also examined whether women agreed with their partner on preferred family size, and to what extent partner (dis)agreement shaped uncertainty. We show that Dutch women expressed much uncertainty about their fertility preferences, with only one-third feeling strongly about their preferences. Uncertainty strongly increased when women preferred higher numbers of children, whereas already having children reduced it. Women who wanted no children were most certain about their preference. Higher preferred family sizes also led to more disagreement with the partner about these preferences, and greater partner disagreement, in turn, led to more uncertainty. These findings imply that people are more likely to downgrade their fertility preferences than to increase them, as women are more certain about their preferences for lower numbers of children and are more open to family sizes below than above their preferred choice. Partner disagreement is often resolved by not having (more) children, lowering realised fertility. Hence, these findings provide another explanation for why many people have fewer children than desired.

Growing Up Together in Society (GUTS): A team science effort to predict societal trajectories in adolescence and young adulthood.

Our society faces a great diversity of opportunities for youth. The 10-year Growing Up Together in Society (GUTS) program has the long-term goal to understand which combination of measures best predict societal trajectories, such as school success, mental health, well-being, and developing a sense of belonging in society. Our leading hypothesis is that self-regulation is key to how adolescents successfully navigate the demands of contemporary society. We aim to test these questions using socio-economic, questionnaire (including experience sampling methods), behavioral, brain (fMRI, sMRI, EEG), hormonal, and genetic measures in four large cohorts including adolescents and young adults. Two cohorts are designed as test and replication cohorts to test the developmental trajectory of self-regulation, including adolescents of different socioeconomic status thereby bridging individual, family, and societal perspectives. The third cohort consists of an entire social network to examine how neural and self-regulatory development influences and is influenced by whom adolescents and young adults choose to interact with. The fourth cohort includes youth with early signs of antisocial and delinquent behavior to understand patterns of societal development in individuals at the extreme ends of self-regulation and societal participation, and examines pathways into and out of delinquency. We will complement the newly collected cohorts with data from existing large-scale population-based and case-control cohorts. The study is embedded in a transdisciplinary approach that engages stakeholders throughout the design stage, with a strong focus on citizen science and youth participation in study design, data collection, and interpretation of results, to ensure optimal translation to youth in society.

A data-driven approach shows that individuals' characteristics are more important than their networks in predicting fertility preferences.

People's networks are considered key in explaining fertility outcomes-whether people want and have children. Existing research on social influences on fertility is limited because data often come from small networks or highly selective samples, only few network variables are considered, and the strength of network effects is not properly assessed. We use data from a representative sample of Dutch women reporting on over 18 000 relationships. A data-driven approach including many network characteristics accounted for 0 to 40% of the out-of-sample variation in different outcomes related to fertility preferences. Individual characteristics were more important for all outcomes than network variables. Network composition was also important, particularly those people in the network desiring children or those choosing to be childfree. Structural network characteristics, which feature prominently in social influence theories and are based on the relations between people in the networks, hardly mattered. We discuss to what extent our results provide support for different mechanisms of social influence, and the advantages and disadvantages of our data-driven approach in comparison to traditional approaches.

Capturing the Dynamics of the Social Environment Through Experience Sampling Methods, Passive Sensing, and Egocentric Networks: Scoping Review.

BACKGROUND: Social interactions are important for well-being, and therefore, researchers are increasingly attempting to capture people's social environment. Many different disciplines have developed tools to measure the social environment, which can be highly variable over time. The experience sampling method (ESM) is often used in psychology to study the dynamics within a person and the social environment. In addition, passive sensing is often used to capture social behavior via sensors from smartphones or other wearable devices. Furthermore, sociologists use egocentric networks to track how social relationships are changing. Each of these methods is likely to tap into different but important parts of people's social environment. Thus far, the development and implementation of these methods have occurred mostly separately from each other. OBJECTIVE: Our aim was to synthesize the literature on how these methods are currently used to capture the changing social environment in relation to well-being and assess how to best combine these methods to study well-being. METHODS: We conducted a scoping review according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. RESULTS: We included 275 studies. In total, 3 important points follow from our review. First, each method captures a different but important part of the social environment at a different temporal resolution. Second, measures are rarely validated (>70% of ESM studies and 50% of passive sensing studies were not validated), which undermines the robustness of the conclusions drawn. Third, a combination of methods is currently lacking (only 15/275, 5.5% of the studies combined ESM and passive sensing, and no studies combined all 3 methods) but is essential in understanding well-being. CONCLUSIONS: We highlight that the practice of using poorly validated measures hampers progress in understanding the relationship between the changing social environment and well-being. We conclude that different methods should be combined more often to reduce the participants' burden and form a holistic perspective on the social environment.

Testing the combination of Feeling Safe and peer counselling against formulation-based cognitive behaviour therapy to promote psychological wellbeing in people with persecutory delusions: study protocol for a randomized controlled trial (the Feeling Safe-NL Trial).

BACKGROUND: Persecutory delusions are strong threat beliefs about others' negative intentions. They can have a major impact on patients' day-to-day life. The Feeling Safe Programme is a new translational cognitive-behaviour therapy that helps patients modify threat beliefs and relearn safety by targeting key psychological causal factors. A different intervention approach, with growing international interest, is peer counselling to facilitate personal recovery. Combining these two approaches is a potential avenue to maximize patient outcomes. This combination of two different treatments will be tested as the Feeling Safe-NL Programme, which aims to promote psychological wellbeing. We will test whether Feeling Safe-NL is more effective and more cost-effective in improving mental wellbeing and reducing persecutory delusions than the current guideline intervention of formulation-based CBT for psychosis (CBTp). METHODS: A single-blind parallel-group randomized controlled trial for 190 out-patients who experience persecutory delusions and low mental wellbeing. Patients will be randomized (1:1) to Feeling Safe-NL (Feeling Safe and peer counselling) or to formulation-based CBTp, both provided over a period of 6 months. Participants in both conditions are offered the possibility to self-monitor their recovery process. Blinded assessments will be conducted at 0, 6 (post-treatment), 12, and 18 months. The primary outcome is mental wellbeing. The overall effect over time (baseline to 18-month follow-up) and the effects at each timepoint will be determined. Secondary outcomes include the severity of the persecutory delusion, general paranoid ideation, patient-chosen therapy outcomes, and activity. Service use data and quality of life data will be collected for the health-economic evaluation. DISCUSSION: The Feeling Safe-NL Trial is the first to evaluate a treatment for people with persecutory delusions, while using mental wellbeing as the primary outcome. It will also provide the first evaluation of the combination of a peer counselling intervention and a CBT-based program for recovery from persecutory delusions. TRIAL REGISTRATION: Current Controlled Trials ISRCTN25766661 (retrospectively registered 7 July 2022).

Increased aggression during human group contests when competitive ability is more similar.

Theoretical analyses and empirical studies have revealed that conflict escalation is more likely when individuals are more similar in resource-holding potential (RHP). Conflicts can also occur between groups, but it is unknown whether conflicts also escalate more when groups are more similar in RHP. We tested this hypothesis in humans, using data from two professional sports competitions: football (the Bundesliga, the German first division of football) and basketball (the NBA, the North American National Basketball Association). We defined RHP based on the league ranks of the teams involved in the competition (i.e. their competitive ability) and measured conflict escalation by the number of fouls committed. We found that in both sports the number of fouls committed increased when the difference in RHP was smaller. Thus, we provide what is to our best knowledge the first evidence that, as in conflicts between individuals, conflicts escalate more when groups are more similar in RHP.

Intralocus sexual conflict over human height.

Intralocus sexual conflict (IASC) occurs when a trait under selection in one sex constrains the other sex from achieving its sex-specific fitness optimum. Selection pressures on body size often differ between the sexes across many species, including humans: among men individuals of average height enjoy the highest reproductive success, while shorter women have the highest reproductive success. Given its high heritability, IASC over human height is likely. Using data from sibling pairs from the Wisconsin Longitudinal Study, we present evidence for IASC over height: in shorter sibling pairs (relatively) more reproductive success (number of children) was obtained through the sister than through the brother of the sibling pair. By contrast, in average height sibling pairs most reproductive success was obtained through the brother relative to the sister. In conclusion, we show that IASC over a heritable, sexually dimorphic physical trait (human height) affects Darwinian fitness in a contemporary human population.

The effect of female height on reproductive success is negative in Western populations, but more variable in non-western populations.

OBJECTIVE: In this article we examine the association between female height and reproductive success in a US sample and present a review of previous studies on this association. We also outline possible biological explanations for our findings. METHODS: We used data from a long-term study of 5,326 female Wisconsin high school graduates to examine the association between female height and reproductive success. Twenty-one samples on this association were covered by our literature review. RESULTS: Shorter women had more children surviving to age 18 than taller women, despite increased child mortality in shorter women. Taller women had a higher age at first birth and age at first marriage and reached a higher social status, but the negative effect of height on reproductive success persisted after controlling for these variables. However, while these effects were quite consistent in Western populations, they were not consistently present in non-Western populations. Our review also indicated that child mortality was almost universally higher among shorter women. CONCLUSIONS: We conclude that shorter women have a higher number of live births but that final reproductive success depends on the positive effect of height on child survival.

Western scrub-jays conceal auditory information when competitors can hear but cannot see.

Western scrub-jays (Aphelocoma californica) engage in a variety of cache-protection strategies to reduce the chances of cache theft by conspecifics. Many of these strategies revolve around reducing visual information to potential thieves. This study aimed to determine whether the jays also reduce auditory information during caching. Each jay was given the opportunity to cache food in two trays, one of which was filled with small pebbles that made considerable noise when cached in ('noisy' tray), whereas the other one contained soil that made little detectable noise when cached in ('quiet' tray). When the jays could be heard, but not seen, by a competitor, they cached proportionally less food items in the 'noisy' substrate than when they cached alone in the room, or when they could be seen and heard by competitors. These results suggest that western scrub-jays know when to conceal auditory information, namely when a competitor cannot see but can hear the caching event.

Identifying the limits to socioeconomic influences on human growth.

Contemporary humans occupy the widest range of socioeconomic environments in their evolutionary history, and this has revealed unprecedented environmentally-induced plasticity in physical growth. This plasticity also has limits, and identifying those limits can help researchers: (1) parse when population differences arise from environmental inputs or not and (2) determine when it is possible to infer socioeconomic disparities from disparities in body form. To illustrate potential limits to environmental plasticity, we analyze body mass index (BMI) and height data from 1,768,962 women and 207,341 men (20-49 y) living in households exhibiting 1000-fold variation in household wealth (51 countries, 1985-2017, 164 surveys) across four world regions-sub-Saharan Africa, South Asia, Latin America, and North Africa and the Middle East. We find that relationships of environmental inputs with both mean height and BMI bottom out at roughly 100-700 USD per capita household wealth (2011 international units, PPP), but at different basal BMIs and basal heights for different regions. The relationship with resources tops out for BMI at around 20 K-35 K USD for women, with growth potential due to environmental inputs in the range of 6.2-8.4 kg/m2. By contrast, mean BMI for men and mean height for both sexes remains sensitive to environmental inputs even at levels far above the low- and middle-income samples studied here. This suggest that further work integrating comparable data from low- and high-income samples should provide a better picture of the full range of environmental inputs on human height and BMI. We conclude by discussing how neglecting such population-specific limits to human growth can lead to erroneous inferences about population differences.

Using Polygenic Scores in Social Science Research: Unraveling Childlessness.

Biological, genetic, and socio-demographic factors are all important in explaining reproductive behavior, yet these factors are typically studied in isolation. In this study, we explore an innovative sociogenomic approach, which entails including key socio-demographic (marriage, education, occupation, religion, cohort) and genetic factors related to both behavioral [age at first birth (AFB), number of children ever born (NEB)] and biological fecundity-related outcomes (endometriosis, age at menopause and menarche, polycystic ovary syndrome, azoospermia, testicular dysgenesis syndrome) to explain childlessness. We examine the association of all sets of factors with childlessness as well as the interplay between them. We derive polygenic scores (PGS) from recent genome-wide association studies (GWAS) and apply these in the Health and Retirement Study (N = 10,686) and Wisconsin Longitudinal Study (N = 8,284). Both socio-demographic and genetic factors were associated with childlessness. Whilst socio-demographic factors explain 19-46% in childlessness, the current PGS explains <1% of the variance, and only PGSs from large GWASs are related to childlessness. Our findings also indicate that genetic and socio-demographic factors are not independent, with PGSs for AFB and NEB related to education and age at marriage. The explained variance by polygenic scores on childlessness is limited since it is largely a behavioral trait, with genetic explanations expected to increase somewhat in the future with better-powered GWASs. As genotyping of individuals in social science surveys becomes more prevalent, the method described in this study can be applied to other outcomes.