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.

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.

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.

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.

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).

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.

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.

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.

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.

Hidden heritability due to heterogeneity across seven populations.

Meta-analyses of genome-wide association studies (GWAS), which dominate genetic discovery are based on data from diverse historical time periods and populations. Genetic scores derived from GWAS explain only a fraction of the heritability estimates obtained from whole-genome studies on single populations, known as the 'hidden heritability' puzzle. Using seven sampling populations (N=35,062), we test whether hidden heritability is attributed to heterogeneity across sampling populations and time, showing that estimates are substantially smaller from across compared to within populations. We show that the hidden heritability varies substantially: from zero (height), to 20% for BMI, 37% for education, 40% for age at first birth and up to 75% for number of children. Simulations demonstrate that our results more likely reflect heterogeneity in phenotypic measurement or gene-environment interaction than genetic heterogeneity. These findings have substantial implications for genetic discovery, suggesting that large homogenous datasets are required for behavioural phenotypes and that gene-environment interaction may be a central challenge for genetic discovery.

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.

The Reproductive Ecology of Industrial Societies, Part II : The Association between Wealth and Fertility.

Studies of the association between wealth and fertility in industrial populations have a rich history in the evolutionary literature, and they have been used to argue both for and against a behavioral ecological approach to explaining human variability. We consider that there are strong arguments in favor of measuring fertility (and proxies thereof) in industrial populations, not least because of the wide availability of large-scale secondary databases. Such data sources bring challenges as well as advantages, however. The purpose of this article is to illustrate these by examining the association between wealth and reproductive success in the United States, using the National Longitudinal Study of Youth 1979. We conduct a broad-based exploratory analysis of the relationship between wealth and fertility, employing both cross-sectional and longitudinal approaches, and multiple measures of both wealth (income and net worth) and fertility (lifetime reproductive success and transitions to first, second and third births). We highlight the kinds of decisions that have to be made regarding sample selection, along with the selection and construction of explanatory variables and control measures. Based on our analyses, we find a positive effect of both income and net worth on fertility for men, which is more pronounced for white men and for transitions to first and second births. Income tends to have a negative effect on fertility for women, while net worth is more likely to positively predict fertility. Different reproductive strategies among different groups within the same population highlight the complexity of the reproductive ecology of industrial societies. These results differ in a number of respects from other analyses using the same database. We suggest this reflects the impossibility of producing a definitive analysis, rather than a failure to identify the "correct" analytical strategy. Finally, we discuss how these findings inform us about (mal)adaptive decision-making.

The Reproductive Ecology of Industrial Societies, Part I : Why Measuring Fertility Matters.

Is fertility relevant to evolutionary analyses conducted in modern industrial societies? This question has been the subject of a highly contentious debate, beginning in the late 1980s and continuing to this day. Researchers in both evolutionary and social sciences have argued that the measurement of fitness-related traits (e.g., fertility) offers little insight into evolutionary processes, on the grounds that modern industrial environments differ so greatly from those of our ancestral past that our behavior can no longer be expected to be adaptive. In contrast, we argue that fertility measurements in industrial society are essential for a complete evolutionary analysis: in particular, such data can provide evidence for any putative adaptive mismatch between ancestral environments and those of the present day, and they can provide insight into the selection pressures currently operating on contemporary populations. Having made this positive case, we then go on to discuss some challenges of fertility-related analyses among industrialized populations, particularly those that involve large-scale databases. These include "researcher degrees of freedom" (i.e., the choices made about which variables to analyze and how) and the different biases that may exist in such data. Despite these concerns, large datasets from multiple populations represent an excellent opportunity to test evolutionary hypotheses in great detail, enriching the evolutionary understanding of human behavior.

Wealth, fertility and adaptive behaviour in industrial populations.

The lack of association between wealth and fertility in contemporary industrialized populations has often been used to question the value of an evolutionary perspective on human behaviour. Here, we first present the history of this debate, and the evolutionary explanations for why wealth and fertility (the number of children) are decoupled in modern industrial settings. We suggest that the nature of the relationship between wealth and fertility remains an open question because of the multi-faceted nature of wealth, and because existing cross-sectional studies are ambiguous with respect to how material wealth and fertility are linked. A literature review of longitudinal studies on wealth and fertility shows that the majority of these report positive effects of wealth, although levels of fertility seem to fall below those that would maximize fitness. We emphasize that reproductive decision-making reflects a complex interplay between individual and societal factors that resists simple evolutionary interpretation, and highlight the role of economic insecurity in fertility decisions. We conclude by discussing whether the wealth-fertility relationship can inform us about the adaptiveness of modern fertility behaviour, and argue against simplistic claims regarding maladaptive behaviour in humans.

Evolutionary perspectives on human height variation.

Human height is a highly variable trait, both within and between populations, has a high heritability, and influences the manner in which people behave and are treated in society. Although we know much about human height, this information has rarely been brought together in a comprehensive, systematic fashion. Here, we present a synthetic review of the literature on human height from an explicit evolutionary perspective, addressing its phylogenetic history, development, and environmental and genetic influences on growth and stature. In addition to presenting evidence to suggest the past action of natural selection on human height, we also assess the evidence that natural and sexual selection continues to act on height in contemporary populations. Although there is clear evidence to suggest that selection acts on height, mainly through life-history processes but perhaps also directly, it is also apparent that methodological factors reduce the confidence with which such inferences can be drawn, and there remain surprising gaps in our knowledge. The inability to draw firm conclusions about the adaptiveness of such a highly visible and easily measured trait suggests we should show an appropriate degree of caution when dealing with other human traits in evolutionary perspective.

Body height preferences and actual dimorphism in stature between partners in two non-Western societies (Hadza and Tsimane').

Body height influences human mate preferences and choice. A typical finding in Western societies is that women prefer men who are taller than themselves and, equivalently, men prefer women who are shorter than themselves. However, recent reports in non-Western societies (e.g., the Himba in Namibia) challenge the view on the universality of such preferences. Here we report on male and female height preferences in two non-Western populations--the Hadza (Tanzania) and the Tsimane' (Bolivia)--and the relationships between body height preferences and the height of actual partners. In the Hadza, most individuals preferred a sexual dimorphism in stature (SDS) with the man being much taller than the woman. Preferences for SDS and actual partner SDS were positively and significantly correlated in both men and women, suggesting that people who preferred larger height differences also had larger height differences with their partners. In the Tsimane', the majority of men preferred an SDS with the man being taller than the woman, but women did not show such a preference. Unlike in the Hadza, SDS preference was not significantly correlated to actual partner SDS. We conclude that patterns of height preferences and choices in the Hadza and Tsimane' are different than those observed in Western societies, and discuss possible causes for the observed differences between non-Western and Western societies.