Effectiveness of My Tools for Care-in Care: A Pragmatic Randomized Controlled Trial
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".