Influence of Personal Traits, Social Relationships, and External Resources on the Development of Emotional Resilience in Children From East London: Protocol for an Observational Accelerated Longitudinal Cohort Study
Bibliographic record
Abstract
BACKGROUND: Emotional resilience is a dynamic process by which individuals may prevent, overcome, and thrive following challenging events. Emotional resilience can be defined as absence of negative outcomes (ie, symptoms of psychopathology) and/or the presence of adaptive outcomes (ie, well-being). Despite the wealth of research tracking the nature of and contributions to emotional resilience in adolescence and adulthood, there is a dearth of evidence on the nature of resilience and its development during preadolescent childhood despite this being an important preventative period for later mental health difficulties and a period when emotional experiences change. OBJECTIVE: Our primary study objectives are 3-fold: to explore how preadolescent children growing up in deprived areas of London may operationalize resilience, evaluate whether there are differences in the development or trajectories of resilience among our target population, and understand what contributes to resilience pathways over time. Additionally, our research aims to better understand the psychometric properties of resilience measures used in a preadolescent sample and assess the feasibility of developing a longitudinal cohort study of preadolescent children in East London. METHODS: We will conduct an accelerated longitudinal cohort study in primary schools across the broad geographical area of East London. The multimethod approach will span across 3 data collection arms: (1) child cognitive tasks and psychometric questionnaires in classroom settings, (2) teacher ratings, including teacher assessments of school mental health provisions, and (3) parent questionnaires. We aim to recruit approximately 1200 children aged 7-11 years at baseline across UK school years 3, 4, and 5. Our measures will span themes of resilience and mental health, as well as personal, social, and community resources available to the children. We will collect quantitative data via questionnaires from children, their parents, and school staff. We will collect qualitative data from the children through paper-based tasks. RESULTS: Study recruitment commenced in October 2022 and continued till December 2023. Baseline testing commenced in October 2022 and continued till December 2023; 873 students were enrolled at baseline. Follow-up is anticipated to continue at least annually until June 2027. CONCLUSIONS: This study will assess the feasibility of conducting a longitudinal cohort study on preadolescent children in East London. Alongside evaluating the psychometric properties of resilience measures used in this age group, this study will explore how resilience develops in children across time and relate this to other outcome measures. By identifying how personal, social, and community resources may affect resilience in preadolescent children, we will enhance the understanding of how emotional resilience develops in preadolescent children, and future studies will be able to develop interventions to boost resilience by targeting young and diverse populations. TRIAL REGISTRATION: ISRCTN ISRCTN12430839; https://www.isrctn.com/ISRCTN12430839. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/70797.
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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 | 0.027 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.025 | 0.006 |
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".