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Record W2980816850 · doi:10.1016/j.jalz.2019.06.3544

P3‐508: AN EVALUATION OF THE ALZHEIMER SOCIETY OF CANADA RESOURCE GUIDE TO SUPPORT RESEARCH RECRUITMENT

2019· article· en· W2980816850 on OpenAlexaffabout
Nalini Sen

Bibliographic record

VenueAlzheimer s & Dementia · 2019
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsAlzheimer Society of Canada
Fundersnot available
KeywordsResource (disambiguation)Qualitative researchProcess (computing)Qualitative propertyPopulationPsychologyData collectionKnowledge managementPublic relationsMedical educationMedicinePolitical scienceSociologyComputer scienceSocial science

Abstract

fetched live from OpenAlex

In 2016, the Alzheimer Society of Canada (ASC), along with its partners across the country, led the development of a Resource Guide for ethical recruitment of research volunteers within the client population. In late 2017, a qualitative, retrospective outcome evaluation was undertaken of the Resource Guide. The Resource Guide was produced to serve as a catalyst for discussion and self-directed action toward organizational change and cultivation of a positive research culture through the provision of evidence-informed and practical solutions to help organizations achieve this goal. A qualitative, retrospective outcome evaluation was undertaken to answer the following questions: 1. What practice changes were put in place to support research recruitment, following review of the Guide? 2. What features of the Guide, and / or supports provided during the review and feedback process contributed to practice changes to support research recruitment? 3. If other factors influenced practice changes to support research recruitment? An evaluation framework that aligned with these questions, with anticipated outcomes across the level of clients, the staff, and researcher involved in the development of the Resource Guide was used to organize data collection and analysis. Semi-structured telephone interviews were conducted. Content analysis was carried out on the open-ended data and using a directed approach, analysis began with the anticipated outcomes outlined in the evaluation framework. Frequencies and per cents were calculated for quantitative data. Overall, the findings demonstrate a strong positive trend with implementing practice changes to support research recruitment as a result of participating in the Guide developmental process. Many of the partners put in place new or updated practices that aligned with the anticipated outcomes of the Guide. The Guide is a valuable tool for ASC and its partners to begin building capacity to support research engagement. Notably, these findings align with key findings from prior consultation activities including feedback from people living with dementia and their care partners that placing a greater emphasis on sharing research funding and recruitment opportunities with the public is essential.

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)0.181
metaresearch head score (Gemma)0.253
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.942
Threshold uncertainty score0.960

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1810.253
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0090.003
Scholarly communication0.0060.003
Open science0.0070.008
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.002

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 head0.643
GPT teacher head0.584
Teacher spread0.059 · 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
DomainEvaluation
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
Published2019
Admission routes2
Has abstractyes

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