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Record W2338480822 · doi:10.14288/1.0097134

Self-help in mental health : operationalizing a conceptual model

2010· article· en· W2338480822 on OpenAlexaboutno aff
Indra Pulcins

Bibliographic record

VenuecIRcle (University of British Columbia) · 2010
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsOperationalizationMental healthConceptual modelPsychologyComputer scienceSocial psychologyEpistemologyPsychotherapistPhilosophy

Abstract

fetched live from OpenAlex

This study aims to examine the self-help mode of care giving in mental health, especially the manner in which the working self-help model differs from its theoretical counterpart. For this purpose, a conceptual model of operationalizing self-help has been developed. This model traces the process of establishing self-help groups, from theory to practice, and incorporates the barriers such groups may face in becoming a viable alternative to the current health care system. These include the effects of public policy, the professional and the community. The results of this study, based on empirical evidence collected in Vancouver, B.C., suggest that at least to some extent, this model does accurately depict the processes involved with the operationalization of a self-help model, as well as the factors impinging on a full realization of self-help goals. Both public policy and professional influences serve to act as direct constraints to the full implementation of self-help. The community does not share this characteristic, partially due to favourable zoning policy in Vancouver. In spite of these barriers, self-help groups are able to function as an effective alternative. However, it is demonstrated that some of their original goals have not been fulfilled. In conclusion, a theoretical perspective, in the context of Marx and Weber, is outlined, thereby suggesting some of the broader issues associated with implementing a self-help model.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.003
Science and technology studies0.0020.016
Scholarly communication0.0070.008
Open science0.0030.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.271
Teacher spread0.250 · 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 designTheoretical or conceptual
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
Published2010
Admission routes1
Has abstractyes

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