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Record W2011140591 · doi:10.1037/h0095083

An evaluation of the social recreation component of a community mental health program.

2001· article· en· W2011140591 on OpenAlexaff
Pauline Petryshen, J. D. Hawkins, Tabatha A. Fronchak

Bibliographic record

VenuePsychiatric Rehabilitation Journal · 2001
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsProvidence Health Care
Fundersnot available
KeywordsLonelinessRecreationMental healthPsychologyComponent (thermodynamics)Applied psychologyLife satisfactionFocus groupClinical psychologyGerontologySocial psychologyPsychiatryMedicineSociology

Abstract

fetched live from OpenAlex

The paper describes the results of an evaluation designed to determine the effectiveness of the social recreation component of a community-based mental health program. The program is for individuals with serious mental health problems, with a particular focus on those who perceive deficiencies in their social relationships. Findings showed that the individuals who participated in the program, in varying frequency, reported significant improvements in their self-ratings of loneliness, self-esteem, social functioning, satisfaction with social relations and leisure activities, as well as general life satisfaction. The association between particular program- or client-related factors and the outcome variables were examined to provide insights into why people changed. The merits and limitations of the evaluation methodology are discussed.

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)0.004
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.054
GPT teacher head0.429
Teacher spread0.375 · 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

Citations33
Published2001
Admission routes1
Has abstractyes

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