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Record W4407190399 · doi:10.1016/j.jamda.2025.105484

Effectiveness of My Tools for Care-in Care: A Pragmatic Randomized Controlled Trial

2025· article· en· W4407190399 on OpenAlexafffund
Hannah M. O’Rourke, Jennifer Swindle, Pamela Baxter, Shelley Peacock, Genevieve Thompson, Sunita Ghosh, Dorothy Chacinski, Jayna Holroyd‐Leduc, Véronique Dubé, Wendy Austin

Bibliographic record

VenueJournal of the American Medical Directors Association · 2025
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of ManitobaMcMaster UniversityUniversity of CalgaryUniversité de MontréalUniversity of SaskatchewanUniversity of Alberta
FundersPublic Health AgencyPublic Health Agency of Canada
KeywordsMedicineRandomized controlled trialLonelinessDementiaIntervention (counseling)Social supportMental healthGerontologyHealth careFamily medicineNursingPsychiatryPsychology

Abstract

fetched live from OpenAlex

OBJECTIVES: Few supports exist for family/friend care partners when the care recipient is a person living with dementia in a care home. This study assessed the effectiveness of My Tools for Care-In Care (MT4C-In Care), a self-administered, web-based psychoeducational intervention. DESIGN: The overall study was a mixed methods pragmatic randomized controlled trial, with concurrent process evaluation and an active (educational) control. The intervention group received a link to MT4C-In Care for 2 months. SETTING AND PARTICIPANTS: Participants were eligible if they were an adult (aged ≥18 years) who provided care to an older person (aged ≥65 years) living with dementia in a care home in Canada (Alberta, Saskatchewan, Manitoba, or Ontario). An email address and internet access were required to participate. METHODS: Process evaluation included a study participation tracking form and a checklist to assess use of MT4C-In Care. We completed telephone interviews (February 2020 to October 2021) at baseline, 2 months, and 4 months to assess outcomes of social support, hope, grief, self-efficacy, loneliness, and mental health. In an intention-to-treat analysis, generalized estimating equations models were used to assess intervention impact, adjusting for covariates. Sensitivity analysis assessed whether exclusion of nonusers impacted the results. RESULTS: Participants (N = 234) were primarily white women, and spouses or an adult child of the person living with dementia. No effect between groups was observed for the primary outcome (mental health). We observed a small benefit of MT4C-In Care for a secondary outcome, social support. Use of MT4C-In Care within the intervention group was low (∼1 h/mo). Dropping nonusers from the analysis did not have a substantial impact on the main conclusions. CONCLUSIONS AND IMPLICATIONS: Future research will explore use of MT4C-In Care by more diverse participant groups, and will clarify its core mechanisms, advancing understanding of impacts of psychoeducational interventions.

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)0.021
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 score0.015
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.021
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0090.009
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0030.004
Open science0.0020.002
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0150.001

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 head0.005
GPT teacher head0.333
Teacher spread0.328 · 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

Citations3
Published2025
Admission routes2
Has abstractno

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Same venueJournal of the American Medical Directors AssociationSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207