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Record W2158636313 · doi:10.1186/s40814-015-0012-4

Exploring the Determinants of Suicidal Behavior: Conventional and Emergent Risk (DISCOVER): a feasibility study

2015· article· en· W2158636313 on OpenAlexafffundabout
Zainab Samaan, Monica Bawor, Brittany B. Dennis, Wala El-Sheikh, Jane DeJesus, Sumathy Rangarajan, Judith Vair, Heather Sholer, Nicole Hutchinson, Elizabeth Iordan, Pam Mackie, Shofiqul Islam, Mahshid Deghan, Jennifer Brasch, Lehana Thabane

Bibliographic record

VenuePilot and Feasibility Studies · 2015
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsHamilton Health SciencesSt. Joseph’s Healthcare HamiltonMcMaster UniversityPopulation Health Research Institute
FundersMcMaster UniversityHamilton Health Sciences
KeywordsMedicinePsychiatrySuicide preventionInjury preventionPoison controlSuicide attemptOccupational safety and healthClinical psychologyMedical emergency

Abstract

fetched live from OpenAlex

BACKGROUND: Suicidal behavior is a growing public health concern resulting in morbidity and premature death. Although certain factors such as age, sex, and psychiatric disorders have been consistently reported to be associated with suicidal behavior, other factors including biological markers, diet, and physical activity may also influence suicidal behavior. The purpose of this pilot study was to evaluate the feasibility of conducting a full-scale study to identify the conventional and novel risk factors of suicidal behavior in individuals who made a recent suicide attempt. METHODS: This pilot study was a case-control study of participants with recent (within 1 month of admission) suicide attempts admitted to hospital and compared to two control groups: 1) psychiatric inpatient participants without a history of suicide attempts and 2) community-based controls. We collected information on demographic variables, circumstances of suicide attempts (for cases), medical and psychiatric diagnoses, behavioral patterns, physical measurements, and social factors. Blood and urine samples were also collected for biological markers. Feasibility outcomes are as follows: 1) 50 % of all eligible cases will consent to participate, 2) 50 cases and 100 controls per year can be recruited, and 3) at least 80 % of the participants will provide blood samples for DNA and biological markers. RESULTS: We recruited 179 participants in total; 51 cases, 57 psychiatric controls without suicide attempt, and 71 non-psychiatric controls in Hamilton, Ontario. Recruitment rate was 70 % (213/304), and we obtained urine and blood specimens from 90 % (191/213) of participants. Questionnaire completion rates were high, and data quality was very good with few data-related queries to resolve. We learned that cases tended to be hospitalized for long periods of time and the suicide attempt occurred more than a month ago in many of the cases; therefore, we expanded our inclusion criterion related to timing of suicide attempt to 3 months instead of 1 month. CONCLUSIONS: The study procedures needed certain modifications including extending the time between suicide attempt and date of recruitment, and more detailed questionnaires related to diet were necessary while other questionnaires such as social support needed to be shortened. Overall, this study showed that it is feasible to conduct a larger-scale study.

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)0.004
metaresearch head score (Gemma)0.006
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 score0.024
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.579
GPT teacher head0.462
Teacher spread0.117 · 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

Citations22
Published2015
Admission routes3
Has abstractyes

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