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Record W4399367730 · doi:10.2196/preprints.62708

The Behaviours in Dementia Toolkit: A descriptive study on the reach and early impact of a digital health resource library about dementia-related mood and behaviour changes (Preprint)

2024· preprint· en· W4399367730 on OpenAlexaffabout
Lauren Albrecht, Nick Ubels, Brenda Martinussen, Gary Naglie, Mark Rapoport, Stacey Hatch, Dallas Seitz, Claire Checkland, David Conn

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsPreprintDementiaResource (disambiguation)MoodPsychologyGerontologyComputer scienceMedicinePsychiatryWorld Wide WebDisease

Abstract

fetched live from OpenAlex

BACKGROUND Dementia is a syndrome with a high global prevalence that includes a number of progressive diseases of the brain affecting various cognitive domains such as memory and thinking, and the performance of daily activities. It manifests as symptoms across a number of domains, which often include significant mood and behaviour changes. Changed moods and behaviours due to dementia may reflect distress, they are highly varied, and may be stressful for both the person living with dementia and their informal and formal carers. To provide dementia care support specific to mood and behaviour changes, the Behaviours in Dementia Toolkit website was developed using human-centered design principles. The Behaviours in Dementia houses a user-friendly, digital library of over 300 free, practical and evidence-informed resources to help all care partners better understand and compassionately respond to behaviours in dementia so they can support people with dementia to live well. OBJECTIVE To determine whether the development and implementation of the Behaviours in Dementia Toolkit was successful in creating website users and to understand the platform’s early impact. METHODS A multi-method, descriptive study was conducted in the early post-launch period to examine reach, engagement, knowledge change, behaviour change, and website impact outcomes and measures via Google Analytics and an electronic survey of website users. RESULTS From February 4 to March 31, 2024 there were 76,890 unique visitors to the Behaviours in Dementia Toolkit from 109 countries. Of 76,890 unique visitors to the Behaviours in Dementia Toolkit during this period, 16,626 were engaged users (21.6%) from 80 countries. The highest number of unique engaged users were from Canada (n=8,124) with an engagement rate of 37.7%. From March 5, 2024 to March 31, 2024, 100 electronic surveys were completed by website users and included in the analysis. Website users indicated that the Toolkit validated or increased their dementia-care knowledge, beliefs, and activities (82.0%) and they reported that the website validated their current care approaches or increased their ability to provide care (78.0%). Further, 77.0% of respondents indicated that they intend to continue using the Toolkit and 81.6% said they would recommend it to others to review and adopt. CONCLUSIONS The Behaviours in Dementia Toolkit is a promising tool for sharing practical and evidence-informed information resources to support people experiencing dementia related mood and behaviour changes. Early evaluation of the website has demonstrated significant reach and engagement with users in Canadian and internationally. Survey data also demonstrated high ratings of website relevance, feasibility, intention to use, knowledge change, practice support, and its contribution to dementia guidance.

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)0.011
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.029
GPT teacher head0.326
Teacher spread0.297 · 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".

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Citations0
Published2024
Admission routes2
Has abstractyes

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