Social and Neurobiological Mechanisms of Risk and Resilience in Young People: The Longitudinal THRIVE-study
Bibliographic record
Abstract
IntroductionChildhood adversity (CA) is among the strongest predictors of mental health problems. CA refers to experiences that are likely to require significant adaptation by an average child and that represent a deviation from the expectable environment. CA-related alterations in social and cognitive functioning may result in the thinning of social networks and increases in stressful peer interactions, which subsequently lead to mental health problems. The THRIVE study takes a longitudinal approach to investigate these proposed prospective relationships by examining whether and how social, cognitive, and neurobiological mechanisms interact to shape friendship support, stressful peer interactions, and mental health functioning over time.Methods and analysisThe ongoing THRIVE study aims to recruit 288 participants aged 18-24 years who retrospectively self-report CA. This longitudinal study comprises six sessions in total. Participants complete an online baseline assessment of mental health, social support, stress experiences, and early life experiences, followed by an in-unit deep-phenotyping session. Assessments include self-report measures, cortisol measures, computerized cognitive tasks, and functional neuroimaging paradigms assessing stress and social evaluation. Participants subsequently complete four online follow-up assessments at 3-month intervals. Using data collected at the in-unit session, we aim to test whether CA is associated with biased emotion processing, blunted feedback learning and enhanced stress responses, and whether social support from peers may moderate these effects. The longitudinal design further enables us to test whether CA contributes to mental health problems through its impact on cognitive functioning, which over time leads to reduced social support and increased social stress. By elucidating how cognitive and social functioning contribute to mental health outcomes following CA, the THRIVE study aims to inform the development of interventions that foster resilience in young people.Ethics and disseminationThe THRIVE study was approved by the Medical Ethics Committee Leiden-The Hague-Delft (NL80017.058.21). The study was co-created with the Augeo Youth Task Force, a panel of young adults with lived experience of CA, who contribute throughout the research process. Findings will be disseminated through scientific publications, conference presentations, preprints, and public engagement activities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".