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Record W7117319089 · doi:10.1002/alz70858_103426

Feasibility and Acceptability of iGeriCare: A Pilot Randomized Controlled Trial of Web‐Based Dementia Education for Care Partners

2025· article· en· W7117319089 on OpenAlexaff
Anthony J Levinson, Stephanie Ayers, Sandra Clark, Rebekah Woodburn, Maureen Markle‐Reid, Brian McKenna, Doug Oliver, Αλεξάνδρα Παπαϊωάννου, Sarah Payne, Demetrios J. Sahlas, David L. Streiner, Dima Hadid, Amy Schneeberg, Henry Siu

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRandomized controlled trialDementiaIntervention (counseling)Pilot trialHealth careMEDLINE

Abstract

fetched live from OpenAlex

BACKGROUND: Dementia is a significant global health challenge, with rising prevalence worldwide. Family and friend care partners play a critical role in supporting individuals with dementia but often lack adequate knowledge, leading to increased stress and burden. Web-based interventions show promise in improving care partners' mental health, yet few have been widely adopted or rigorously studied for knowledge outcomes. To address these gaps, iGeriCare was developed as a scalable dementia education platform, offering 12 multimedia lessons and email-based micro-learning to enhance care partner knowledge, self-efficacy, and caregiving skills. METHOD: A two-arm pilot feasibility randomized controlled trial (RCT) was conducted to evaluate feasibility, acceptance, and effectiveness among dementia care partners. Participants were randomized to either 1. iGeriCare e-learning or 2. alternative e-learning. Outcomes (adherence, study methods feasibility, participant feedback, dementia knowledge, self-efficacy, and burden) were assessed at baseline and 8-weeks. Challenges during the first recruitment cohort, including protocol deviations and fraudulent participation, informed refinements for a second cohort recruited via a paid panel. Qualitative thematic analysis of responses provided insights into barriers/facilitators, and care partner needs. RESULT: Cohort 1 (n = 125) began September 2022, with data collection concluding in January 2023. Cohort 2 (n = 100) was recruited in June 2023. Participants found the e-learning content relevant, clear, and beneficial. They reported that the duration of the intervention was appropriate and the study methods acceptable. Preliminary results indicated significant knowledge gains in the intervention group among older care partners (≥45 years) with a mean increase of 13.9 points on a 50-point scale compared to the control group. Self-efficacy and burden differences between groups were not statistically significant. Thematic analysis revealed needs for skills in managing aggressive behaviors, communication, future care planning, emotional coping strategies for younger care partners (≤44), and practical caregiving strategies for older participants (≥45). CONCLUSION: This pilot study demonstrates the feasibility and acceptability of iGeriCare as a scalable, web-based educational intervention for dementia care partners. Preliminary findings highlight the potential to improve knowledge and meet other needs. Lessons learned will inform the design of a larger RCT to evaluate long-term impact on care partner outcomes, including knowledge self-efficacy, and burden.

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)0.011
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.019
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0130.001

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 head0.036
GPT teacher head0.379
Teacher spread0.344 · 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 designRandomized trial
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 routes1
Has abstractyes

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