Examining adolescents' experiences of distress when participating in research on well-being and early life adversity
Bibliographic record
Abstract
RATIONALE: Most child well-being and childhood adversity research is informed by proxy informants such as parents or teachers rather than children and youth. This may be due to concerns about perceived sensitivity, challenges accessing and engaging with children in research, ethical considerations, and apprehensions about causing undue harm and distress. This study aimed to understand adolescents' identification of, and reactions to, questions in the context of participating in a survey of well-being and adversity. OBJECTIVES: The aim of this study was to enhance our understanding of how adolescents identify and respond to potentially upsetting questions about well-being and life experiences, including childhood adversity. METHOD: Data were from 1002 adolescent respondents aged 14 to 17 years. The Well-being and Experiences (WE) survey assessed several domains of life, including general health and well-being and early life adversity. Data were analyzed using descriptive statistics, logistic regression models, and thematic analysis approaches. RESULTS: Few adolescent respondents reported feeling upset when completing the survey (11.2 %). Among those who reported feeling upset, 92.0 % indicated that it was still important to ask those upsetting questions, and only two respondents (1.8 %) thought upsetting questions should be removed. Ten themes emerged from the adolescents' reflections on self-reported upsetting questions, including identity and life satisfaction, motivation, mental health, and school; childhood adversity was not primarily identified. CONCLUSIONS: Findings indicate that conducting research on well-being and childhood adversity directly with adolescents is feasible and minimally distressing. Future research should consider how to engage youth directly in research to understand better the scope and outcomes associated with childhood adversity.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".