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Record W7117293846 · doi:10.1002/alz70858_104577

Evaluating the Launch of CCSMH's Clinical Practice Guidelines for BPSD

2025· article· en· W7117293846 on OpenAlexaffabout
Stacey Hatch, J. C. Watt, Zahra Goodarzi, David Conn, Claire Checkland, Dallas Seitz

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsCentre for Addiction and Mental HealthHotchkiss Brain InstituteCanadian Mental Health AssociationBaycrest HospitalUniversity of CalgaryUniversity of Toronto
Fundersnot available
KeywordsClinical PracticeKnowledge translationSocial mediaInformation DisseminationValue (mathematics)Health professionalsHealth careSocial care

Abstract

fetched live from OpenAlex

BACKGROUND: In March 2024, the Canadian Coalition for Seniors Mental Health launched the Clinical Practice Guidelines (CPG) on the Assessment and Management of BPSD. The goal of our dissemination strategy over the subsequent nine months was to raise awareness of the CPG and enhance healthcare providers' understanding and application of its good practice principles and key recommendations. The primary objective of this poster is to present and evaluate our dissemination strategies. METHODS: Our knowledge translation approach utilized three strategies in English and French. Diffusion activities required minimal customization and included social media posts on LinkedIn, X, Facebook, announcements on CCSMH website, and press releases. Dissemination activities were tailored to audiences including seven scientific conferences, several webinars, and open-access publications. Application strategies were tailored to participants, such as academic education and training sessions. Evaluation measured cumulative reach of combined activities and synthesized participant feedback. RESULTS: Diffusion efforts reached approximately 29,481 individuals. The CCSMH website recorded nearly 12,000 visitors, with over 7,800 downloads of the CPG in English and French. Dissemination activities introduced the CPG through English and French webinars, which accumulated over 11,200 views, seven conference presentations attended by more than 900 participants, and open-access publications. Additionally, over 800 printed copies were distributed. Application strategies included seven academic education and training initiatives, including the 10-week Project ECHO (Extension of Community Health Outcomes) Care series with over 500 participants, grand rounds at Canadian hospitals and specialty clinics, academic detailing using case studies at conferences, a specialized virtual geriatrics course, and ongoing correspondence with end users. Overall, these knowledge translation activities reached approximately 42,200 individuals. Participant feedback will be presented as graphs. CONCLUSIONS: Feedback highlighted the need for scalable implementation strategies, such as developing clinical summaries in electronic and print formats in both English and French. Our findings emphasize the value of tailored dissemination strategies that engage healthcare providers where they seek evidence-based information (relevant websites and social media platforms), gather (scientific conferences), and learn (education series and grand rounds). Effective dissemination of the CPG was crucial for the rapid translation of research evidence into actionable recommendations in the assessment and management of BPSD.

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)0.416
metaresearch head score (Gemma)0.644
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score0.720

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4160.644
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.005
Science and technology studies0.0050.003
Scholarly communication0.0110.009
Open science0.0060.012
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.618
GPT teacher head0.652
Teacher spread0.034 · 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.

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

Citations0
Published2025
Admission routes2
Has abstractyes

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