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Record W3022614824 · doi:10.1080/07448481.2020.1751173

The prevalence of anxiety, stress and depressive symptoms in undergraduate students at the Canadian Memorial Chiropractic College

2020· article· en· W3022614824 on OpenAlexaffabout
Christine Meckamalil, Lydia Brodie, Sheilah Hogg‐Johnson, Linda Carroll, Craig Jacobs, Pierre Côté

Bibliographic record

VenueJournal of American College Health · 2020
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsCanadian Memorial Chiropractic CollegeOntario Tech UniversityUniversity of AlbertaCentre for Disability Prevention and RehabilitationPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsAnxietyDepression (economics)MedicineChiropracticCross-sectional studyDepressive symptomsClinical psychologyPsychiatryPhysical therapyDemographyAlternative medicine

Abstract

fetched live from OpenAlex

Objective (1) Determine the one-week prevalence of moderate to extreme symptoms of anxiety, stress and depression in chiropractic undergraduate students. (2) Determine whether the prevalence varies across gender and year of study. Participants: Undergraduate students at the Canadian Memorial Chiropractic College (CMCC). Methods: A cross-sectional study was conducted in fall 2017 to measure self-reported symptoms of anxiety, stress and depression using the DASS-21. Results: The participation rate was 67.0% (510/766). The one-week prevalence of moderate to extreme symptoms was 19.0% (95% CI: 13.0–25.0) for depression; 32.6% (95% CI: 24.7–40.3) for anxiety and 21.8% (95% CI: 15.6–28.1) for stress. The prevalence of stress varied significantly across gender: 25.4% (95% CI: 20.5–30.3) for females versus 16.3% (95% CI: 11.2–21.3) for males. The one-week prevalence of depressive (24.8%; 95% CI: 17.6–32.0) and anxiety (40.9%; 95% CI: 32.6–49.1) symptoms peaked in second year. Conclusions: Self-reported symptoms of anxiety, stress and depression are common in CMCC students.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.033
GPT teacher head0.397
Teacher spread0.364 · 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.

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

Citations25
Published2020
Admission routes2
Has abstractyes

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