Construct validity of probable child maltreatment indicators using prospectively recorded information in a longitudinal cohort of Canadian children
Bibliographic record
Abstract
BACKGROUND: Officially reported and self-reported measures of child maltreatment show poor agreement and may differentially predict psychosocial problems in adulthood. However, research remains primarily based on retrospective self-reports, warranting examination of the validity of prospective assessments of maltreatment. OBJECTIVE: To assess the construct validity of prospective indicators of child maltreatment using a longitudinal cohort of Canadian children. PARTICIPANTS AND SETTING: The population-based cohort comprises 2120 participants born between 1997 and 1998 in Quebec, Canada. METHODS: Maternal and familial risk factors (maternal age, depressive symptoms, and antisocial behaviors, socioeconomic status, and single-parent home) and early adulthood functioning difficulties (depression, anxiety, suicidality, alcohol misuse, and unemployment status) were assessed across various time points (0-23 years). Associations between factors and prospective and retrospective maltreatment indicators were appraised. RESULTS: Most maternal and familial risk factors (80 %) showed associations with indicators of prospective maltreatment (ΔM = +/-0.04 to 0.72; p < 0.05). Several early adulthood functioning difficulties (30 %) showed associations with physical (ΔM = 0.05 to 0.22; p < 0.05) and sexual abuse (ΔM = 0.33 to 0.34; p < 0.05), while emotional, supervisory, and physical neglect were only associated with educational/employment status (ΔM = 0.04 to 0.10; p < 0.05). Cumulatively assessed maltreatment also showed a dose-response relationship with maternal and familial risk factors/functioning difficulties. CONCLUSIONS: The strong construct validity exhibited by our prospective indicators highlights the need to assess child maltreatment multi-modally. Our findings further contribute to the wider discussion surrounding the measurement of child maltreatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".