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Identification of child sexual abuse and prevention of psychiatric morbidity

2016· article· en· W2278839610 on OpenAlexaff
Avinash Desousa, Sagar Karia, Nilesh Shah, Amresh Shrivastava

Bibliographic record

VenueInternational Journal of Contemporary Pediatrics · 2016
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsLawson Health Research InstituteWestern University
Fundersnot available
KeywordsMedicinePsychiatryDepression (economics)Sexual abuseSubstance abuseBorderline personality disorderPersonality disordersPersonalityClinical psychologySuicide preventionPoison controlPsychologyMedical emergency

Abstract

fetched live from OpenAlex

Child sexual abuse (CSA) is a hidden and under-reported problem in psychiatry. CSA has been studied in various epidemiological data based studies and has been found to be a significant risk factor for the development of psychiatric illness in later life. Depression, suicide and suicidal attempts as well as self-injurious behaviour have all been reported to be significantly greater in patients than have been exposed to CSA versus those who have not been exposed to the same. There are studies that demonstrate higher rates of substance abuse, body image disturbances, eating disorders and cluster B personality traits in patients that have been exposed to CSA. The paper looks at the available data on lifetime occurrence of psychiatric disorders in patients that have been exposed to CSA. The various mechanisms by which CSA exposure can lead to psychiatric disorders in adulthood are discussed and the need for identification, assessment and clinically evaluating the presence of CSA in patients in routine clinical practice is highlighted.

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)0.005
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.319
Teacher spread0.290 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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