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Record W2202081054 · doi:10.5770/cgj.18.197

The Fountain of Health: Bringing Seniors’ Mental Health Promotion into Clinical Practice

2015· article· en· W2202081054 on OpenAlexafffundvenue
Vanessa Thoo, Janya Freer, Keri-Leigh Cassidy

Bibliographic record

VenueCanadian Geriatrics Journal · 2015
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsDalhousie University
FundersDalhousie University
KeywordsMedicineMental healthKnowledge translationPromotion (chess)Presentation (obstetrics)Session (web analytics)Knowledge transferFamily medicineMedical educationNursingPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: The Fountain of Health (FoH) initiative offers valuable evidence-based mental health knowledge and provides clinicians with evaluated tools for translating knowledge into practice, in order to reduce seniors' risks of mental disorders, including dementia. METHODS: A presentation on mental health promotion and educational materials were disseminated to mental health clinicians including physicians and other allied health professionals either in-person or via tele-education through a provincial seniors' mental health network. Measures included: 1) a tele-education quality evaluation form, 2) a knowledge transfer questionnaire, 3) a knowledge translation-to-practice evaluation tool, and 4) a quality assurance questionnaire. RESULTS: A total of 74 mental health clinicians received the FoH education session. There was a highly significant (p < .0001) difference in clinicians' knowledge transfer questionnaire scores pre- and post-educational session. At a two-month follow-up, 19 (25.7%) participants completed a quality assurance questionnaire, with all 19 (100%) of respondents stating they would positively recommend the FoH information to colleagues and patients. Eleven (20.4%) translation-to-practice forms were also collected at this interval, tracking clinician use of the educational materials. CONCLUSIONS: The use of a formalized network for knowledge transfer allows for education and evaluation of health-care practitioners in both acquisition of practical knowledge and subsequent clinical behavior change.

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)0.010
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.707
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.092
GPT teacher head0.435
Teacher spread0.343 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations9
Published2015
Admission routes3
Has abstractyes

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