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Record W7030225746

MENTAL HEALTH LITERACY, SELF-STIGMA AND HEALTH SEEKING BEHAVIOUR AMONG UNDERGRADUATE MEDICAL STUDENTS IN UNIVERSITY OF SASKATCHEWAN, CANADA

2024· dissertation· en· W7030225746 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2024
Typedissertation
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthMental health literacyScale (ratio)StressorStigma (botany)Help-seekingHealth literacy
DOInot available

Abstract

fetched live from OpenAlex

Background: Canadian medical students have been previously found to be subjected to a high-pressure environment – with long clinical weeks and significant stressors – resulting in high levels of burnout. The reluctance of young adults to seek mental health treatment has been attributed to poor mental health literacy, stigma, preference for self-reliance and concerns about confidentiality. When a medical student does not seek help, mental health issues that might have been avoided earlier could become worsened and might eventually lead to premature withdrawal from medical school as well as other negative consequences.\nPurpose: To evaluate mental health literacy, self-stigma, and help-seeking behaviour among undergraduate medical students at the College of Medicine, University of Saskatchewan (U of S).\nMethods: This was a descriptive cross-sectional study that was conducted within the undergraduate medical education (UGME) program, College of Medicine, U of S. It reports the objective measures of students’ mental health literacy level and health-seeking behaviour of a sample of medical students (year1-year 4) who consented to participate in the study, using standardized questionnaires sent them online. Demographic information of the students was supplemented by the following scales: Mental Health Literacy Scale (MHLS), the Self Stigma of Seeking Psychological Help Scale (SSOSPH) and General Help-Seeking Questionnaire (GHSQ).\nResults & Conclusion: Out of 404 students in the entire college, a total of 102 participants responded to the survey questionnaires, but only 85 attempted and completed the survey questionnaires, thus giving a response rate of 25.2%. Almost all the participants reported high mental health literacy, with only 1.2% reporting low level of mental health literacy. The majority (88.2%) had low levels of self-stigma. There is an almost equal distribution among the participants in terms of health seeking behaviour, with 51.8% reporting high help seeking behaviour and 48.2% having low help seeking behaviour. Individuals with lower self-stigma towards seeking help are significantly more likely to engage in high HSB compared to those with high self-stigma, who predominantly fell into the low HSB category (90.0% low HSB vs. 10.0% high HSB).\nIn conclusion, this research emphasizes the crucial importance of reducing self-stigmatization among medical students, thorough curriculum revisions and supportive educational efforts as well as identifying other barriers to help seeking behaviour.

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)0.002
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 score0.049
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.008
GPT teacher head0.261
Teacher spread0.253 · 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
Published2024
Admission routes1
Has abstractyes

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