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Interdependencies Among Family and Friends: Personality Differences and Associations with Affective Well-Being in Daily Life

Study within the SCARS project to examine neural and behavioral responses to social exclusion, measured through the fMRI Cyberball task and questionnaires afterwards, and how these responses relate to victimization experiences.

The second preregistration in this project concerns the final report and is a continuation of the brief report (for the preregistration of the brief report see https://osf.io/dr57w/). The main question in the larger project is: How do people deal with the Dutch government's social-distancing measures and what are the consequences for loneliness during the coronavirus outbreak? This project was financed by the Dutch Ministry of Health, Welfare and Sport.

The preregistered study (brief report) aims to describe loneliness and the social and non-social coping strategies that individuals use to deal with the Dutch government's social-distancing measures during the coronavirus pandemic. This brief report was financed by the Dutch Ministry of Health, Welfare and Sport and uses data from the Longitudinal Internet Studies for the Social Sciences (LISS) panel. The current study is part of a larger project that aims to describe the changes in the quantity, quality and ways of social contact during the first phase of social distancing, the social and non-social coping strategies to deal with these changes and to examine the relationship between these social changes, coping strategies, loneliness and psychological adjustment.

Pre-analysis preregistration for project: Social challenges: Loneliness in the transition from primary to secondary education during the COVID-19 pandemic Based on the template https://osf.io/t6m9v/, adapted for pre-analysis purposes. A. HYPOTHESIS Early adolescence is characterized by many challenges. The transition from primary to secondary education is one of the most significant challenges. The transition to secondary education entails entering a large, new peer environment which may disrupt existing social relationships and can lead to feelings of loneliness in the new peer group (Benner & Graham, 2009; Felmlee et al., 2018). This social challenge could be especially difficult during the COVID-19 pandemic, in which adolescents were temporarily physically isolated from their peers. Already in the early stages of COVID-19, government agencies, media and healthcare workers expressed their concerns about rising loneliness (Singh & Singh, 2020), in particular for early adolescents (YoungMinds, 2020). Thus, early adolescents transitioning to secondary education during the COVID-19 may be at particular risk for increased loneliness. Despite the increasing attention for loneliness during the COVID-19 pandemic, existing studies show mixed results leaving room for ambiguity. Moreover, studies on loneliness among children and (early) adolescents during the COVID-19 pandemic are limited (see for an exception: Ellis, Dumas, & Forbes, 2020). Adding to this, most studies focused on general changes in loneliness over the COVID-19 pandemic, not taking into account individual differences in social status. We argue that the magnitude of the risk on increased loneliness may depend on peer status pre-corona. Besides the social challenges that COVID-19 has brought, early adolescents also have to face other social challenges, such as the transition from primary to secondary education. We argue that early adolescents with a higher peer status in terms of acceptance, and popularity rather than rejection and victimization may react differently to these social challenges compared with early adolescents with an average or lower peer status. In addition, the magnitude of the risk on increased loneliness may relate to the amount and type of contact early adolescents had with their friends during the COVID-19 pandemic. Feelings of loneliness might increase especially for early adolescents who had little contact with friends or more online compared rather than face to face contact with friends during physical isolation. Figure 1 visualizes the research model. We use data of two waves. The first wave was conducted in January and February 2020 when the early adolescents were in their last year of primary education (T1). At this time, the schools were still open. The second wave was conducted in October and November 2020, roughly six weeks after the early adolescents transitioned to secondary education. Wave two included questions about two time-points. First, retrospective questions were included on the school closure in primary education due to COVID-19 in March, April, and May 2020 (T2). Second, questions were asked regarding the moment of undertaking the survey (T3). We aim to examine whether peer status predicts trajectories of loneliness in early adolescence in the transition from primary to secondary education during the COVID-19 pandemic. First, we will examine the general development of loneliness over the school closure during COVID-19 and the transition from primary to secondary education. Second, we will estimate different peer groups based on peer acceptance, peer rejection, popularity, and peer victimization at T1. Third, we will examine how these peer groups differ in trajectories of loneliness in the transition from primary to secondary education during the COVID-19 pandemic. Fourth, we will explore whether different profiles of amount and type of contact during the school closure can be distinguished, and if so, we will explore how these adolescents with different contact profiles differ in trajectories of loneliness in the transition from primary to secondary education during the COVID-19 pandemic. Hypotheses Measures of physical isolation such as the school closure complicate social contact and therefore may lead to increased loneliness. Already in the early stages of COVID-19, government agencies, media and healthcare workers expressed their concerns about rising loneliness (Singh & Singh, 2020), in particular for early adolescents (YoungMinds, 2020). However, current scientific evidence on the development of loneliness during the COVID-19 pandemic shows mixed results. Whereas some studies find an increase in loneliness during the COVID-19 pandemic, these studies often have major limitations such as comparing cross-sectional data with a pre-existing different sample (Killgore et al., 2020), using qualitative measures (Idoiaga Mondragon et al., 2020), using online searchers rather than self-reports (Brodeur et al., 2020) or consisting of a literature review of pre-existing literature on the effects of quarantine (Brooks et al., 2020). Other studies found no increases in loneliness (Folk et al., 2020; Fried et al., 2020; Luchetti et al., 2020; Tull et al., 2020), (very) small increases (Jacobson et al., 2020; Lee et al., 2020; McGinty et al., 2020) or temporary increases in loneliness during physical isolation (Buecker et al., 2020). Nevertheless, studies on loneliness of early adolescents during the pandemic are limited. Considering that younger adults report more loneliness during the pandemic than older adults (Luchetti et al., 2020; McGinty et al., 2020) and the belief that only young adults but also early adolescents would be worse off, we expect a small general increase in loneliness for early adolescents during the school closure. Regarding the transition to secondary education, we expect an increase in loneliness after the transition to secondary education compared to the first measure in primary education. Although entering secondary education might create opportunities for establishing new friendships, research shows that the transition to secondary education generally disrupts existing social relationships and can lead to feelings of loneliness in the new peer group (Benner & Graham, 2009; Felmlee et al., 2018). We expect a small general increase in loneliness during the school closure during physical isolation measures that were taken to reduce the spread of COVID-19 (Hypothesis 1). Regarding the division of peer groups based on peer status, we expect to find three groups at T1. Namely, (a) an unpopular-disliked-victimized group characterized by higher levels of rejection and victimization and lower levels of popularity, (b) a normative group characterized by moderate levels of acceptance, rejection, popularity, and victimization and (c) a popular-liked group characterized by higher levels of acceptance and popularity and low levels of rejection and victimization (Engels et al., 2019; van den Berg, Burk, & Cillessen, 2015) (Hypothesis 2). Although being liked is not the same as being popular, we do not expect to find separate liked and popular groups, because liked peers are generally the same peers as popular peers in primary education (van den Berg, Lansu, & Cillessen, 2020). We expect the normative peer group to have average levels of loneliness compared with other peer groups (Engels et al., 2019). We expect the normative peer group to follow the average loneliness trajectory as posted in H1 (Hypothesis 3). We expect the unpopular-disliked-victimized peer group to have the highest average levels of loneliness. Adolescents who are rejected and unpopular are, on average, more lonely (Buhs & Ladd, 2001; Engels et al., 2019). These adolescents may have fewer social skills resulting in fewer and less satisfactory friendships and more loneliness (Segrin & Flora, 2000; Spithoven et al., 2017). Moreover, affiliating with unpopular or victimized peers is a social risk which may result in peers avoiding unpopular or victimized adolescents. Avoidance may in turn increase feelings of loneliness (Schmidt & Bagwell, 2011; Woodhouse, Dykas, & Cassidy, 2012). Our expectations on the trajectories of the unpopular-disliked-victimized group are twofold. On the one hand, following social development theories, this group might have a poorer social development which is reflected by their negative peer status. Lacking social skills makes it harder to cope with social challenges such as the school closure or the transition from primary to secondary education. Early adolescents with fewer social skills may have a smaller and lower quality social network and may be less equipped to maintain this social network and keep on receiving social support over the school closure. Moreover, adolescents with fewer social skills may have more difficulties establishing new friendships in their new peer group in secondary education. Thus, we expect loneliness to increase during the school closure and after the transition (Hypothesis 4a). This means risk factors for loneliness are similar before as well during the COVID-19 pandemic (Bu, Steptoe, & Fancourt, 2020). On the other hand, the unpopular-disliked-victimized group may become less lonely during the school closure (Hypothesis 4b). For these early adolescents, a decrease in peer contact may result in a decrease in negative peer experiences, and therefore result in decreases in loneliness. For instance, less situations might arise wherein early adolescents feel excluded or abandoned by classmates. The school closure might thus give these early adolescents a break from their negative peer experiences such as being bullied. Moreover, whereas this peer group was already more lonely in January, during the school closure more people became lonely, making these early adolescents relatively less lonely than before compared to their peer group (Kaufman et al., 2018). We expect the popular-liked group to experience the lowest average levels of loneliness compared with the other peer groups (Engels et al., 2019). These early adolescents feel like they belong to their peer group resulting in less perceived loneliness (Baumeister & Leary, 1995). Furthermore, accepted early adolescents more often show prosocial behavior leading to more social interaction and less loneliness (Woodhouse et al., 2012). Our expectations on the trajectories of the liked-popular group are twofold. On the one hand, following social development theories, this group has better social skills which are reflected by their positive peer status. These skills help to overcome social challenges such as the school closure or the transition to secondary education. Moreover, these early adolescents have a larger peer network which they may manage to maintain over the school closure. Therefore, for these early adolescents it might be easier to substitute offline social contact by online social contact, combatting loneliness. Early adolescents in the liked-popular group may also be motivated to compensate offline by online contact to maintain their high status in their peer group. Thus, feelings of loneliness may not increase for the liked-popular peer group (Hypothesis 5a). On the other hand, this peer group is rewarded for going to school in terms of affection and status. These early adolescents have more to lose socially when it comes to a school closure. Therefore, these early adolescents might be socially harmed by school closure and loneliness may increase. This means having a stronger social network before the COVID-19 pandemic may be a risk for social disruption during the COVID-19 pandemic (Lee, Cadigan, & Rhew, 2020) (Hypothesis 5b). Additionally, we will explore if the amount and type of contact with friends during the school closure is associated with different trajectories of loneliness. To combat loneliness, early adolescents were advised to stay socially connected online during isolation (NJI, 2020). In line with this recommendation, maintaining online social contact during COVID-19 isolation was found to protect from mental health issues such as alienation (Pancani et al., 2020). However, a study on online social contact during COVID-19 isolation showed mixed results for adolescent adjustment. Spending time online texting and video chatting with friends was related to lower levels of loneliness but higher levels of depression (Ellis et al., 2020). Moreover, COVID-19 stress related to more loneliness and depression, especially for adolescents who spend more time on social media. This might be explained by risk factors of social media use, such as upward social comparison and being confronted with pandemic-related news (Ellis et al., 2020). Considering the scarcity in studies on the effect of (online) social contact on loneliness during the COVID-19 pandemic, we explore (1) different contact profiles of amount and type of social contact during the school closure and (2) if these contact profiles are associated with different loneliness trajectories. B. METHODS Description of variables Independent variables Peer acceptance, peer rejection and popularity were assessed using classroom-based peer nominations. Early adolescents nominated an unlimited number of classmates they liked, disliked, and found popular. Received nominations will be divided by the total number of classmates (minus 1) to account for differences in class size. Scores for peer acceptance, peer rejection and popularity thus will be proportions ranging from 0 to 1 with higher scores indicating more nominations. Victimization was measured by asking ‘Can you indicate how often you have been bullied at school in the past months?’. The question was answered on a 5-point scale ranging from 1 (never) to 5 (several times a week). Before asking this question, early adolescents saw an introduction clip providing the definition of bullying according to Olweus, 1996 (cf. Kaufman, Kretschmer, Huitsing, & Veenstra, 2018). Dependent variables Loneliness was measured using the subscale of peer-related loneliness of the Loneliness and Aloneness Scale for Children and Adolescents (LACA; Marcoen, Goossens, & Caes, 1987). The scale consisted of 5 items, a sample item being ‘I feel left out by my friends’. Early adolescents rated the items as 1 = never, 2 = sometimes, 3 = often and 4 = always. The scale was assessed at both waves with the second wave consisting of a retrospective scale about the school closure at T2. The items of the retrospective scale were slightly adapted to suit the circumstances of the school closure. The item ‘I feel alone at school’ was changed to ‘I felt alone’. The other items were rephrased to past tense. The retrospective items followed after the introduction: ‘The following questions are about the school closure due to the corona virus. Think back to the time you could not go to school because of the corona virus.’ Frequency and type of contact with friends during the school closure will be used for exploratory analysis. Early adolescents indicated how often they have seen friends face to face during the school closure, how often they (video)called with friends during the school closure and how often they chatted online with friends during the school closure. Answer categories consisted of 1 = daily, 2 = once or several times a week, 3 = once or several times a month, 4 = less than once a month, 5 = never. Covariates Gender will be included in the model as a to control the relation with peer status (Engels et al., 2019) (0 = boy; 1 = girl). The percentage of boys and girls will be described for each peer group. Considering there is no relation between gender and loneliness, gender will not be included in the trajectories (Maes et al., 2019). SES socioeconomic status will be included in the model as a control variable. The average SES will be described for each peer group. Furthermore, SES will be included in the loneliness trajectories. Socioeconomic status is measured combining mothers’ and fathers’ educational level and occupational level and household income. However, the PRIMS-data only includes parental occupation. The complete PRIMS-data can be combined with data of the NCO (Nationaal Cohortonderzoek Onderwijs) from October 2021 onwards. The NCO-data includes parental level of education and household income. Therefore, we will only use parental occupation as a proxy for SES in our analysis until October 2021. Parental occupation is measured by coding open answers to the questions about parents’ job into ISEI scores (ISEI, Ganzeboom & Treiman, 1996). We asked early adolescents ‘Which job does your father/mother have at the moment? ‘and ‘Describe the job of your father/mother as precisely as possible’. Using a PRIMS subsample the correlation between parental occupation as measured in PRIMS and parental level of education in NCO is 0,45 for mothers and 0,52 for fathers. Sample The data for this study were already collected. Data stem from the first cohort of the PRIMS project (an acronym for transitioning from PRIMary to Secondary education). PRIMS was designed to investigate peer relations in the transition from primary to secondary education. We will use two waves of the first cohort of PRIMS. The first wave was collected in January-February 2020. The second wave was conducted in October-November 2020 and included current measures as well as retrospective measure on the school closure between March-June 2020. For the PRIMS-project, schools were selected based on a stratified sample design with the sample frame consisting of the full population of primary schools in The Netherlands. We excluded special needs schools and schools that recently closed. In total, 339 schools were sampled and approached for participation in the study. Sixty-six schools (19,5%) with 105 classes participated in wave 1, resulting in a representative sample at the school level. Within the participating schools, all students from grade 6 (11-12 years old) were invited to participate. Conducting active parental consent resulted in 1,545 of all 2,489 (62,1%) early adolescents with permission to take part in the survey. A total of 1,474 early adolescents filled out the first survey with the remaining students not conducting the survey because they were not present at school or experienced technical issues with the online survey. Early adolescents filled out the online questionnaire during regular school hours under the supervision of their teacher. The survey took approximately 45 minutes. The second wave of PRIMS was conducted in October-November 2020, after the early adolescents transitioned from primary to secondary education. All 905 students who participated in the first wave and who previously provided a valid home address and/or email address were invited to participate in the second wave. As an incentive, participants could join a lottery to win one of five Nintendo Switches. In total, 596 early adolescents (65,9%) filled out the second survey. Early adolescents filled out the online questionnaire at home, which took approximately 15 minutes. C. ANALYSIS PLAN Confirmatory analyses First, we will calculate descriptive statistics and correlations for all study variables. Second, the hypotheses will be tested using the analyses described below. Third, exploratory analysis will be performed to test if the amount and type of contact with friends during the school closure is associated with different trajectories of loneliness. Analysis H1: To test the first hypothesis a latent growth curve model will be conducted. This way, we test if there is a significant change in the mean slope over time. Analysis H2: To test the second hypothesis latent class analysis will be conducted to classify early adolescents into different peer status groups. The classes are made using the variables acceptance, rejection, popularity, and victimization as described under B2. ANOVA’s will be conducted to examine if the peer status groups significantly differ from each other in terms of trajectories of loneliness. Analysis H3-H5: Hypothesis 3, 4 and 5 will be tested using multigroup latent growth curve analysis. The independent variables are the peer groups based on H2. The dependent variable is the trajectory of loneliness measured on three time points as described under B2. The intercept and slope will be controlled for gender using ANOVA’s. Exploratory analysis: We perform the exploratory analyses in two steps. First, we explore different contact profiles of amount and type of social contact during the school closure using latent class analysis. The classes are made using the three variables on frequency and type of contact with friends during the school closure. Second, we will explore if different contact profiles are associated with different loneliness trajectories using multigroup latent growth curve analysis. The dependent variable is the trajectory of loneliness measured on three time points as described under B2. The intercept and slope will be controlled for gender using ANOVA’s. Alternative plan Hypothesis 3-5 can only be tested if we find peer groups that were predicted in hypothesis 2. If we do not find these peer groups we perform this alternative plan consisting of two options. Option 1: We may find slightly different groups than the three groups we hypothesized. We foresee two likely alternatives. First, it could be that although liked peers are generally not separated from popular peers in primary education, we nevertheless find two distinct groups, namely a ‘popular-liked’ and a ‘unpopular-liked’ group. This would result in four rather than three groups. In this case, we add this peer group to our analysis. Second, it could be that adding popularity to the classes does not add to the fit based on the Bayesian Information Criterion (BIC), entropy (E), and Lo-Mendell-Rubin Likelihood Ratio Test (LMR-LRT). The classifications might be more accurate without popularity because acceptance, rejection and victimization might mainly predict the trajectories. If latent class analysis suggests classes without the popularity variable based on the BIC, E and LMR-LRT we will remove this variable from our analysis. We test this by comparing the fit scores for models with and without popularity. Option 2: We may find that a variable centered approach is preferred over a person centered approach. Although a person centered approach is desired when studying group differences in developmental trajectories (Laursen & Hoff, 2006), it could be that the latent class analysis provides classed without a good fit based on BIC, E and LMR-LRT or classed that are theoretically meaningless. Classes are theoretically meaningless for example when they are solely based on the different variables rather than a combination of variables. In this case, we will use a variable centered approach including acceptance, rejection, popularity and victimization as continuous predictors for the loneliness trajectories estimated with latent growth curve analysis. We will adjust the hypothesis creating a hypothesis per predictor using the same theoretical foundations. In addition, latent growth curve analysis can only be estimated over three waves for linear trajectories. Latent growth curves of loneliness are generally linear. However, if the latent growth curve cannot be estimated due to curvilinearity, we use the three loneliness measures as three separate dependent variables. Method of missing data handling We expect two types of missing data in our study. First, to obtain a reliable view of early adolescents’ in-class peer status, at least 60% of the early adolescents in the classroom had to participate in the peer nominations (Marks et al., 2013). Therefore, classrooms with a lower participation rate will be excluded from the analyses. This missing data is planned due to selection by researchers. Second, we expect missing data by non-response. We expect unit non-response at both waves in classrooms with participation rates between 60-100% and unit non-response due to attrition at the second wave. Furthermore, there might be unit non-response for some variables. We will perform sensitivity analyses to give insights into the characteristics that are related to the missing data due to attrition at the second wave. We analyze if the participants who participated in both waves, significantly differ from participants who only participated in wave 1. We analyze differences in gender, SES, acceptance, rejection, popularity, victimization and loneliness at T1 using t-tests. Missing data due to attrition over time will be handled by using the full information maximum likelihood estimate (FIML; Parker, Marsh, Morin, Seaton, & Van Zanden, 2015). This method maximizes the available data without imputing missing values. Assumptions of analyses To use growth models, the sample size must be sufficient, there must at least be three repeated measures, the change in type of trajectory for all individuals must be similar and the measures must be continuous and normally distributed (Curran et al., 2010). With 1474 early adolescents participating in the first wave and 596 early adolescents participating in the both waves, the sample size is adequate (Curran et al., 2010). There are three repeated measures of the LACA-scale of which one is retrospective with slightly adapted items. We test the measurement invariance to test if the same construct of loneliness is measured in the retrospective scale. To test if the assumption of similar trajectories for all individuals is met, we evaluate the model fit of the baseline. Furthermore, the LACA-scale is continuous on a 4-point scale. Loneliness is generally not normally distributed. We use the maximum likelihood estimator (MLR) and full information maximum likelihood (FILM) to handle these non-normal distributions (Curran et al., 2010). FINAL COMMENTS Answer the following final questions: Has data collection begun for this project? o No, data collection has not begun x Yes, data collection is underway or complete If data collection has begun, have you looked at the data? x Yes o No The (estimated) start and end dates for this project are (optional): The data were collected between January and November 2020. This study started in October 2020 and will last approximately until July 2021. Any additional comments before I pre-register this project (optional): As stated above the data was already collected. The main researchers in this study contributed to collecting data in the longitudinal PRIMS-study. This included adapting surveys for upcoming waves and data cleaning. Therefore, researchers were aware of the means and reliability scores of the variables in the study. However, no preparatory analysis giving information on relations between variables in this study were conducted. Furthermore, all hypotheses are based on theory and not on the mean scores of the variables. Therefore, this pre-registration may be considered valid as a pre-analysis pre-registration for longitudinal data. References Benner, A. D., & Graham, S. (2009). The transition to high school as a developmental process among multiethnic urban youth. Child Development, 80(2), 356–376. Brodeur, A., Clark, A. E., Fleche, S., & Powdthavee, N. (2020). Assessing the impact of the coronavirus lockdown on unhappiness, loneliness, and boredom using Google Trends. ArXiv Preprint ArXiv:2004.12129. Brooks, S. K., Webster, R. K., Smith, L. E., Woodland, L., Wessely, S., Greenberg, N., & Rubin, G. J. (2020). The psychological impact of quarantine and how to reduce it: rapid review of the evidence. 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Learning and Individual Differences, 75, 101759. Felmlee, D., McMillan, C., Inara Rodis, P., & Osgood, D. W. (2018). Falling behind: Lingering costs of the high school transition for youth friendships and grades. Sociology of Education, 91(2), 159–182. Folk, D., Okabe-Miyamoto, K., Dunn, E., & Lyubomirsky, S. (2020). Did Social Connection Decline During the First Wave of COVID-19?: The Role of Extraversion. Collabra: Psychology, 6(1), 37. Fried, E. I., Papanikolaou, F., & Epskamp, S. (2020). Mental health and social contact during the COVID-19 Pandemic: An ecological momentary assessment study. PsyArXiv. Ganzeboom, H. B. G., & Treiman, D. J. (1996). Internationally comparable measures of occupational status for the 1988 International Standard Classification of Occupations. Social Science Research, 25(3), 201–239. Idoiaga Mondragon, N., Berasategi Sancho, N., Dosil Santamaria, M., & Eiguren Munitis, A. (2020). 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Increases in loneliness among young adults during the COVID-19 pandemic and association with increases in mental health problems. Journal of Adolescent Health, 67(5), 714–717. Luchetti, M., Lee, J. H., Aschwanden, D., Sesker, A., Strickhouser, J. E., Terracciano, A., Sutin, A. R., Brodeur, A., Clark, A. E., Fleche, S., & Powdthavee, N. (2020). Assessing the impact of the coronavirus lockdown on unhappiness, loneliness, and boredom using Google Trends. American Psychologist. Maes, M., Qualter, P., Vanhalst, J., Van den Noortgate, W., Goossens, L., & Kandler, C. (2019). Gender Differences in Loneliness across the Lifespan: A Meta–Analysis. European Journal of Personality, 33(6), 642–654. Marks, P. E. L., Babcock, B., Cillessen, A. H. N., & Crick, N. R. (2013). The effects of participation rate on the internal reliability of peer nomination measures. Social Development, 22(3), 609–622. McGinty, E. E., Presskreischer, R., Han, H., & Barry, C. L. (2020). Psychological Distress and Loneliness Reported by US Adults in 2018 and April 2020. Jama, 324(1), 93–94. Pancani, L., Marinucci, M., Aureli, N., & Riva, P. (2020). Forced social isolation and mental health: A study on 1006 Italians under COVID-19 quarantine. Singh, J., & Singh, J. (2020). COVID-19 and its impact on society. Electronic Research Journal of Social Sciences and Humanities, 2. Tull, M. T., Edmonds, K. A., Scamaldo, K., Richmond, J. R., Rose, J. P., & Gratz, K. L. (2020). Psychological Outcomes Associated with Stay-at-Home Orders and the Perceived Impact of COVID-19 on Daily Life. Psychiatry Research, 113098. YoungMinds. (2020). Coronavirus: Impact on young people with mental health needs. https://youngminds.org.uk/media/3708/coronavirus-report_march2020.pdf

Parenting a teen can be a challenge. Depression, substance use, and minor delinquency steeply increase during adolescence. Although parents are in a unique position to counter these adaptation problems, there aren’t simple pieces of parenting advice that work for every family. Tailoring advice to the family-specific needs and strengths may help parents in their important task of promoting adolescent behavioral and emotional well-being, but requires a more in-depth understanding how parenting works in individual families. In the ADAPT-program, researchers will assess how parenting affects every adolescent’s well-being in a different way, using smart phone applications with micro-questionnaires. This will answer questions, such as: In how many families do general parenting principles apply? What explains heterogeneity in parenting processes? How can being strict initially trigger resistance, but lead to better adaptation in the longer run? These new theoretical insights can help to tailor future parenting advice to the family’s specific needs and strengths.

Here you can find the pre-registrations for all theses of Bachelor students developmental psychology in the academic year 2018-2019

Dutch Report for the Ministry of Health, Welfare and Sport. Dutch title: Eenzaamheid voorkomen in een periode van social distancing (COVID-19). This project was a collaborative effort, all authors equally contributed to the report.

Study within the SCARS project to examine how emotions of others are processed, both with a behavioral task as well as an fMRI task, and how it relates to the negative experience of being bullied.

Supplemental Material for Modeling social interaction dynamics measured with smartphone sensors: An ambulatory assessment study on social interactions and loneliness by Timon Elmer and Gerine Lodder in Journal of Social and Personal Relationships