<i>5Minutes4Myself:</i> Development of a Wellness Program for Caregivers of Children with Autism
Bibliographic record
Abstract
Background. Many caregivers of autistic children experience increased stress, and diminished health often due to the caregiving demands. Purpose. The project aim was to design a feasible and sustainable wellness program tailored to these caregivers’ lives. Methods. In this collaborative research-informed project, participants (N = 28) were mostly female, white, and well-educated. In focus groups, we delineated lifestyle issues, then designed, delivered and assessed an initial program with one cohort; and repeated this process with a second group. Findings. Focus group data were transcribed then coded qualitatively to inform following steps. Data analysis identified lifestyle issues key to program design, desired program elements, and after program delivery, affirmed elements and recommended changes. The team used meta-inferences to guide program revisions after each cohort. Implications. Caregivers viewed resulting 5Minutes4Myself program as filling a significant service gap; its hybrid design used in-person coaching and a habit-building app with mindfulness content to support lifestyle change.
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 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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".