MétaCan
Menu
Back to cohort
Record W2024567043 · doi:10.1037/h0094747

Barriers to exercise among people with severe mental illnesses.

2013· article· en· W2024567043 on OpenAlex
Crystal M. Glover, Joelle C. Ferron, Rob Whitley

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePsychiatric Rehabilitation Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
FundersSubstance Abuse and Mental Health Services Administration
KeywordsThematic analysisPsychological interventionMental healthMedicinePopulationPsychologyMental illnessPsychiatryQualitative research

Abstract

fetched live from OpenAlex

OBJECTIVE: Lack of exercise is a risk factor for various negative health outcomes. Some research suggests people with severe mental illnesses are less likely to engage in exercise than the general population. The purpose of this report is to document, analyze, and understand self-identified barriers to exercise that may be especially specific to people living with serious mental illnesses. Producing such knowledge can assist in the development of effective interventions. METHODS: Thirty-one people with serious mental illnesses participated in in-depth one-on-one interviews to discuss health behaviors in general and exercise more specifically. The authors then engaged in thematic analysis of data to identify common barriers to exercise. RESULTS: Participants reported psychiatric medication side effects, symptoms related to SMI, and physical comorbidities as barriers. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: Clinicians should incorporate physical health goals as a part of treatment planning. Agencies also can play a role in increasing exercise through the implementation of programs.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.260
Teacher spread0.255 · 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