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Record W4205982403 · doi:10.1101/2022.01.06.22268834

Association between child sexual abuse and mid-life employment earnings

2022· preprint· en· W4205982403 on OpenAlexafffundabout
Samantha Bouchard, Rachel Langevin, Francis Vergunst, Melissa Commisso, Pascale Domond, Martine Hébert, Isabelle Ouellet‐Morin, Frank Vitaro, Richard E. Tremblay, Sylvana M. Côté, Massimiliano Orri, Marie‐Claude Geoffroy

Bibliographic record

VenuemedRxiv · 2022
Typepreprint
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsConcordia UniversityUniversité de MontréalUniversité du Québec à MontréalCentre Hospitalier Universitaire Sainte-JustineDouglas Mental Health University InstituteMcGill University
FundersFonds de Recherche du Québec - SantéSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health Research
KeywordsSexual abuseRetrospective cohort studyMedicineSocioeconomic statusDemographyEarningsPopulationChild sexual abusePsychiatryPoison controlInjury preventionEnvironmental healthFinance

Abstract

fetched live from OpenAlex

Abstract Importance Individuals who have been sexually abused are at a greater risk for poor health, but associations with economic outcomes in mid-life have been overlooked. Objectives We investigated associations between child sexual abuse (≤18 years) and economic outcomes at 33-37 years, while considering type of report (official/retrospective) and characteristics of abuse (type, severity, and chronicity). Design This cohort study used data collected for the Quebec Longitudinal Study of Kindergarten Children. Setting The Quebec Longitudinal Study of Kindergarten Children is a population-based sample. Participants Participants were 3,020 boys and girls attending kindergarten in the Canadian Province of Quebec in 1986/88 and followed up until 2017. Main outcome/Measures Child sexual abuse (0-18 years old) was assessed using both retrospective self-report questionnaires and objective reports (notification to Child Protection Services). Information on employment earnings was obtained from government tax return records. Tobit regressions were used to test associations of sexual abuse with earnings adjusting for sex and family socioeconomic background. Results Of the 3,020 participants 1,320 [43.7%] self-reported no sexual abuse, 1,340 [44.3%] had no official report but were missing on the retrospective questionnaire, 340 [11.3%] reported retrospective sexual abuse, and 20 [0.7%] had official report. In the fully adjusted model, individuals who retrospectively reported being sexually abused earned US$4,031 (CI=-7,134 to -931) less per year at age 33-37 years, while those with official reports earned US$16,042 (CI=-27,465 to -4,618) less, compared to participants who were not abused. Among individuals with retrospectively reported abuse, those who experienced intra-familial abuse earned US$4,696 (CI=-9,316 to -75) less than individuals who experienced extra-familial abuse, while participants who experienced penetration earned US$6,188 (CI=-12,248 to -129) less than those who experienced non-contact abuse. Conclusion and Relevance Child sexual abuse puts individuals at risk for lasting reductions in employment earnings in adulthood. Early identification and support for sexual abuse victims could help reduce the economic gap and improve long-term outcomes. Key Points Question Is child sexual abuse associated with lower mid-life employment earnings? Findings In a large population-based cohort (n=3,020), children exposed to sexual abuse had lower annual employment earnings from age 33-37 years than children nonexposed, after adjustment for childhood socioeconomic circumstances. These differences were more pronounced for individuals with official Child Protection Service reports compared to those with retrospective reports, and for individuals who experienced more severe forms of sexual abuse (i.e., penetration, intra-familial). Meaning Children exposed to sexual abuse are at risk of poor socioeconomic outcomes in mid-adulthood; interventions and support to improve long-term economic participation should be considered.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.396
Threshold uncertainty score0.788

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.033
GPT teacher head0.304
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2022
Admission routes3
Has abstractyes

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