Impact of parental socioeconomic status on offspring’s mental health: protocol for a longitudinal community-based study
Bibliographic record
Abstract
INTRODUCTION: Socioeconomic status (SES) affects physical and mental health and cognitive functioning. The association between SES changes (SES mobility) and health has ethical and political implications in that the pernicious effects of inequality and the differential impact on social classes of economic and social policies. There is a lack of research conducted to explore the intergenerational transmission of parental SES changes on the offspring's mental health and cognitive functioning. We aim to fill this gap and identify roles of parental SES changes in offspring's mental health and cognitive outcomes. METHODS AND ANALYSIS: This study will be based on a longitudinal cohort from the most populous municipality in the Canadian province of Quebec. Participants and their biological offspring will be invited to this study. For those with informed consent, we will collect their information on mental health, psychiatric disorders, cognitive functioning and early life experiences for offspring. Latent class growth analysis will be used to identify parental SES mobility groups. Multivariate regression analyses will be used to explore the roles of early life stress, parental SES mobility and their interactions in psychiatric disorders and cognitive functioning. Subgroup analyses (males and females) are also planned. ETHICS AND DISSEMINATION: This study has been given ethical approval by the Research Ethics Board of the Douglas Mental Health University Institute (IUSMD-18/17). Each participant will provide informed consent on participation. We will disseminate research findings through publication in peer-reviewed academic journals and presentations at conferences. Lay summaries of major research findings will also be shared annually with our partners in the health system and community agencies located in the catchment area.
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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 | 0.030 | 0.020 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.051 | 0.010 |
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".