MétaCan
Menu
Back to cohort
Record W2037635265 · doi:10.1108/17556221211230561

Type of community as confounding variable in the satisfaction of rural child and youth mental health clinicians: implications for evidence‐based workforce development

2012· article· en· W2037635265 on OpenAlexaffabout
Judy Gillespie, Rhea Redivo

Bibliographic record

VenueThe Journal of Mental Health Training Education and Practice · 2012
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMental healthWorkforceNursingDiversity (politics)Variety (cybernetics)Rural areaMedicinePsychologyWorkforce developmentMedical educationPsychiatryPolitical science

Abstract

fetched live from OpenAlex

Purpose This paper seeks to present findings from a study soliciting the perspectives of child and youth mental health clinicians practising in rural/remote settings in British Columbia, Canada. Satisfaction is assessed in four areas: lifestyle, practice, preparation for practice, and fit of organizational standards. Design/methodology/approach An online survey using a variety of closed and open‐ended questions was administered to clinicians practising in four distinct settings: small rural, large rural, small remote, and large remote. Closed questions were analyzed using SPSS 17.0 while open ended questions were analyzed using manual open and axial coding. Findings Findings indicate moderate to high levels of satisfaction in all areas. Satisfaction with rural lifestyle and professional practice was strongest for clinicians recruited from within the community. However, clinicians from small remote communities indicated much lower levels of satisfaction in all four areas. Originality/value The study underscores the importance of understanding the diversity of rural practice settings in mental health workforce development. In particular it highlights the need for greater attention to evidence based approaches to support mental health practitioners in small remote settings.

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)0.021
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.159
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.355
GPT teacher head0.568
Teacher spread0.213 · 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 designQualitative
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

Citations6
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Mental Health Training Education and PracticeSame topicGlobal Health Workforce IssuesFrench-language works237,207