“You Don’t Feel Alone”: Perceptions of the My Tools 4 Care-In Care Web-Based Interactive Toolkit
Bibliographic record
Abstract
With the physical and mental impacts of caregiving being well-documented, there is an emphasis on creating interventions to support family carers and enhance their wellbeing. Many of these have been shifting toward accessible, web-based interventions. My Tools for Care (MT4C)-In Care is a self-administered, web-based intervention for carers of persons living with dementia residing in long-term care (LTC). The objectives of the current study were to understand the acceptability, usability, and usefulness of the MT4C-In Care toolkit. Using qualitative description, semi-structured interviews with family carers ( n = 39) were completed across Canadian study sites in four provinces. Interviews were analyzed using deductive content analysis. Participants found the toolkit to be a suitable and adequate tool to support them as carers of persons living with dementia residing in LTC. They also perceived the online format easy to use, although there were barriers, outside of the intervention, to using the tool. The perceived usefulness was described by participants in three ways. The toolkit: (1) validated and normalized feelings, (2) provided permission for self-care and mental well-being, and (3) strengthened their caregiving knowledge. The MT4C-In Care interactive toolkit provided support that participants perceived as acceptable, easy to use, and meaningful.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".