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Record W4391676961 · doi:10.1123/jcsp.2023-0028

Self-Reported Depression in Collegiate Athletes: The Effect of Privacy on Symptom Disclosure

2024· article· en· W4391676961 on OpenAlexaff
Chloe M. Ouellet-Pizer, Sebastian Harenberg, Justine Vosloo, Barbara B. Meyer

Bibliographic record

VenueJournal of Clinical Sport Psychology · 2024
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsAthletesPsychologyDepression (economics)Self-disclosureClinical psychologyPhysical therapySocial psychologyMedicine

Abstract

fetched live from OpenAlex

Prevalence studies on depressive symptoms in collegiate athletes have yielded varied estimations, which may be due, in part, to survey administration privacy. However, the influence of survey administration privacy (i.e., anonymous and confidential) on depressive symptom disclosure remains unknown in sport. The purposes of the current study, therefore, were twofold: (a) compare depressive symptoms reported under high- and low-privacy conditions and (b) examine factors associated with underreporting (i.e., social desirability). College athletes ( N = 123) were randomly assigned to high- and low-privacy conditions. Results indicated no significant difference, F (1, 120) = 0.59, p = .446, between the prevalence of depressive symptoms reported across conditions when controlling for sex, and no significant correlation between depressive symptoms and social desirability ( r = −.01, p = .886). Taken together, results indicated that survey administration privacy did not impact depressive symptom disclosure in the current sample.

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)0.006
metaresearch head score (Gemma)0.001
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 score0.044
Threshold uncertainty score0.651

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.055
GPT teacher head0.458
Teacher spread0.403 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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