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Record W6943993747 · doi:10.17605/osf.io/dzykb

Reporting of suicidal ideation/attempt during adolescence and young adulthood: A data linkage analysis of medical records and self-report questionnaires

2024· other· en· W6943993747 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Science Framework · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsConcordanceMedical recordSuicidal ideationGeneralizability theoryLongitudinal studyPoison controlSuicide preventionInjury prevention

Abstract

fetched live from OpenAlex

Surveys on adolescent suicidal ideation and attempts predominantly utilize self-report questionnaires (Hallford et al., 2023; Plöderl et al., 2011). Increasingly, these surveys are being complemented with linked medical records (Anderson et al., 2015; Nock et al., 2022; Schriver et al., 2020) of suicidal ideation/attempt. Despite this, concordance and discordance between self-report data and medically obtained information remains largely unexplored, with virtually all studies focusing on the agreement between self-reports, parental reports, and clinician assessments (Jones et al., 2019; Klaus et al., 2009; Lungu et al., 2019; Terrill et al., 2021; Vera-Varela et al., 2022). The notable exception is the Avon Longitudinal Study of Parents and Children (ALSPAC), where Mars et al. (2016) uniquely combined self-reported questionnaires on self-harm with hospital records, encompassing admissions for self-harm, outpatient visits, and emergency visits. This study found that non-completion of the self-harm questionnaire was associated with higher hospital admissions for self-harm. Additionally, it highlighted that around 20% of medically documented self-harm incidents were not reported by participants in their self-assessments. However, this study was limited by its inability to examine individual and familial characteristics associated with discordance between self-report and medical records or to detect differences between questionnaire responders and non-responders, due to low rates of self-harm recorded in medical records. Additionally, the study's generalizability is limited by its reliance on linked hospital self-harm admissions data for only 24% of a subsample who consented to data linkage. This study also only examined self-harm and did not include indices of ideation. Similar to ALSPAC, the Quebec Longitudinal Study of Child Development (QLSCD; Orri et al., 2021) a population-based study tracking 2,120 individuals from birth (late 1990s) to adulthood, collected multiple waves of self-reported data on suicidal ideation and attempts. This study was enriched by linking medical records on suicidal ideation and attempts for over 98% of the participants, along with data on key individual and familial characteristics to more accurately identify factors associated with self-reported and medically identified suicidal ideation/attempt. Using data from the Quebec Longitudinal Study of Child Development, which includes self-reported past-year suicidal ideation/attempts at ages 17, 20, and 23, along with corresponding medical records for suicidal ideation/attempts, our objectives are to: 1. Explore concordance and discordance in reporting of suicidal ideation/attempts as identified through self-reports and medical records across ages 17, 20 and 23 years. 2. Examine the association of individual factors (e.g., emotional/behavioral problems) and familial factors (e.g., family functioning) during childhood (6 to 12 years) with reporting concordance and discordance of suicidal ideation/ attempts, as identified through self-reports and medical records.

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)0.018
metaresearch head score (Gemma)0.029
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 score0.018
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.029
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.007
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.397
Teacher spread0.360 · 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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