Limitations of two time point data for understanding individual differences in longitudinal modeling - What can difference reveal about change?

Emerging neuroimaging studies investigating changes in the brain aim to collect sufficient data points to examine trajectories of change across key developmental periods. Yet, current studies are often constrained by the number of time points available now. We demonstrate that these constraints should be taken seriously and that studies with two time points should focus on particular questions (e.g., group-level or intervention effects), while complex questions of individual differences and investigations into causes and consequences of those differences should be deferred until additional time points can be incorporated into models of change. We generated underlying longitudinal data and fit models with 2, 3, 4, and 5 time points across 1000 samples. While fixed effects could be recovered on average even with few time points, recovery of individual differences was particularly poor for the two time point model, correlating at r = 0.41 with the true individual parameters - meaning these scores share only 16.8% of variance As expected, models with more time points recovered the growth parameter more accurately; yet parameter recovery for the three time point model was still low, correlating around r = 0.57. We argue that preliminary analyses on early subsets of time points in longitudinal analyses should focus on these average or group-level effects and that individual difference questions should be addressed in samples that maximize the number of time points available. We conclude with recommendations for researchers using early time point models, including ideas for preregistration, careful interpretation of 2 time point results, and treating longitudinal analyses as dynamic, where early findings are updated as additional information becomes available.

Same sex-attraction as a predictor of suicide and self-harm behaviours: The role of bullying and social support.

Sexual minority youth are at higher risk of self-harming than heterosexual adolescents. Understanding why sexual minority youth are more vulnerable to poor mental health and identifying factors that might buffer against this risk is important for developing targeted interventions. We used the Millennium Cohort Study to investigate whether same-sex attraction at age 14 is associated with suicide attempts and self-harm at age 17. Additionally, we tested whether bullying victimisation might mediate any observed associations, and whether social support might protect against any increased risk. Sexual minority youth were 2.44 times more likely to attempt suicide and 2.59 times more likely to self-harm aged 17. There was no evidence for an association between greater social support and lower levels of self-harm. However, greater social support in sexual minority youth is associated with reduced risk for suicide attempt. Bullying partially mediated the relationship between same-sex attraction and mental health. Greater levels in bullying in sexual minority youth were associated with 1.32 times higher risk for suicide and 1.30 times higher risk for self-harm. Social support was not associated with reduced risk of suicide attempt or self-harm among bullied sexual minority youth. Sexual minority youth in the UK are at higher risk for suicide attempt and self-harm. To address this disparity, health and educational practitioners should understand this heightened risk for poor mental health, and address bullying as one risk factor. Further interventions are needed to assist sexual minority youth beyond social support provision through friends and family.

The effects of life experiences and polygenic risk for depression on the development of positive and negative cognitive biases across adolescence: The CogBIAS hypothesis.

The Cognitive Bias (CogBIAS) hypothesis proposes that cognitive biases develop as a function of environmental influences (which determine the valence of biases) and the genetic susceptibility to those influences (which determines the potency of biases). The current study employed a longitudinal, polygenic-by-environment approach to examine the CogBIAS hypothesis. To this end, measures of life experiences and polygenic scores for depression were used to assess the development of memory and interpretation biases in a three-wave sample of adolescents (12-16 years) (N = 337). Using mixed effects modeling, three patterns were revealed. First, positive life experiences (PLEs) were found to diminish negative and enhance positive forms of memory and social interpretation biases. Second, and against expectation, negative life experiences and depression polygenic scores were not associated with any cognitive outcomes, upon adjusting for psychopathology. Finally, and most importantly, the interaction between high polygenic risk and greater PLEs was associated with a stronger positive interpretation bias for social situations. These results provide the first line of polygenic evidence in support of the CogBIAS hypothesis, but also extend this hypothesis by highlighting positive genetic and nuanced environmental influences on the development of cognitive biases across adolescence.