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Record W2071914771 · doi:10.1016/s0924-9338(13)75719-5

295 – Gender Differences in Determinants of Suicidal Ideation in French Speaking Community Living Older Adults in Canada

2013· article· en· W2071914771 on OpenAlexaffabout
Helen‐Maria Vasiliadis, S. Gagné, Michel Préville

Bibliographic record

VenueEuropean Psychiatry · 2013
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Wellbeing Research
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsSuicidal ideationPsychologyIdeationClinical psychologyGerontologyPsychiatryMedicineEnvironmental healthSuicide preventionPoison control

Abstract

fetched live from OpenAlex

Background: Determinants of suicidal ideation in females and males may differ in older adults. Objectives: To ascertain gender specific determinants of suicidal ideation. Methods: Data used in this study was from the ESA survey on a large representative sample of community dwelling older adults (n=2494). Multivariate logistic regression analysis was used to study the association between suicidal ideation, mental health service and antidepressant use and a number of clinical and socio-demographic factors. Results: The prevalence of suicidal ideation reached 6.3%. The findings of this study show that the presence of suicidal ideation in females is associated with younger age, single or widowed status, the reporting of daily life stressors and chronic conditions as well as the presence of depression. In males, suicidal ideation is associated with older age, single or widowed status and depression. Furthermore, suicidal ideation is significantly associated with antidepressant use in females but not males and this after controlling for a number of clinical factors. Conclusion: Although no gender differences are observed between suicidal ideation and mental health service use, females with suicidal ideation are more likely to be dispensed antidepressants than males with suicidal ideation. The more prevalent use of antidepressants in females with suicidal ideation may lead to better management of symptoms related to depression and their consequences at an earlier stage of the disorder.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.015
Threshold uncertainty score0.661

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.050
GPT teacher head0.364
Teacher spread0.314 · 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 teacher head, 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
Published2013
Admission routes2
Has abstractyes

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