Professional Support Through a Tailor-Made Mobile App to Reduce Stress and Depressive Symptoms Among Family Caregivers of People With Dementia: Mixed Methods Pilot Study
Bibliographic record
Abstract
Background: Providing informal care to people with dementia living at home can be challenging and may cause caregiver stress and depression. Interventions delivered through mobile apps provide innovative solutions for community-based social care professionals to address the increasing support needs of family caregivers (FCs) of people with dementia. Objective: This study aimed to examine, among FCs of people with dementia living at home, (1) the potential association between professional support provided through a mobile app and caregiver stress and depressive symptoms, (2) types of support provided through chat interactions between FCs and social care professionals, and (3) how support provided through a mobile app relates to changes in caregiver stress and depressive symptoms. Methods: A mixed methods pilot study integrated quantitative pre- and postintervention data with qualitative logged chat data. FCs of people with dementia living at home (n=35) were recruited to test a tailor-made mobile app over 8 weeks. The primary and secondary outcome measures were caregiver stress and depressive symptoms, respectively. Descriptive statistics were used to summarize sociodemographic factors; inferential statistics were used to analyze mean differences in outcomes pre- and postintervention. FCs were divided into 3 groups based on changes in caregiver stress scores between pre- and postintervention. Generalized linear model analyses determined the association between participation in the intervention and caregiver stress and depressive symptoms, adjusting for age, gender, and relationship to the person with dementia. Logged chat data were analyzed using summative content analysis to identify types of support provided and received. Changes in caregiver stress were integrated with chat data to determine patterns in types of support received. Results: The mean age of FCs was 69.4 (SD 11.9) years, with most being women (28/35, 80%), partners (24/35, 68.6%), and living with the person with dementia (26/35, 74%). The mean score of caregiver stress was marginally higher postintervention (24.1, SD 9.3) than preintervention (23.9, SD 9.2), whereas the mean score of depressive symptoms decreased from pre- (6.5, SD 5.1) to postintervention (6.2, SD 5.2). These differences were not statistically significant. Regression analyses showed that participation in the intervention was not statistically significantly associated with caregiver stress (β=0.171, α=.05; P=.86) or depressive symptoms (β=-0.293, α=.05; P=.75) after adjusting for age, gender, and relationship to the person with dementia. However, mixed methods analysis at the subgroup level suggested that frequent tailored support by social care professionals delivered through a mobile app may reduce caregiver stress among FCs of people with dementia living at home. Conclusions: The study highlights the importance of providing frequent and individualized support to meet the needs of FCs of people with dementia. Findings from this study may help community-based social care providers plan and organize digital support content provided to FCs of people with dementia living at home.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".