A Comparison of Users and Nonusers of a Web-Based Intervention for Carers of Older Persons With Alzheimer Disease and Related Dementias: Mixed Methods Secondary Analysis
Bibliographic record
Abstract
BACKGROUND: A self-administered Web-based intervention was developed to help carers of persons with Alzheimer disease and related dementias (ADRD) and multiple chronic conditions (MCC) deal with the significant transitions they experience. The intervention, My Tools 4 Care (MT4C), was evaluated during a pragmatic mixed methods randomized controlled trial with 199 carers. Those in the intervention group received free, password-protected access to MT4C for three months. MT4C was found to increase hope in participants at three months compared with the control group. However, in the intervention group, 22% (20/92) did not use MT4C at all during the three-month period. OBJECTIVE: This mixed methods secondary analysis aimed to (1) examine differences at three months in the outcomes of hope, self-efficacy, and health-related quality of life (HRQOL) scores in users (ie, those who used MT4C at least once during the three-month period) compared with nonusers and (2) identify reasons for nonuse. METHODS: Data from the treatment group of a pragmatic mixed methods randomized controlled trial were used. Through audiotaped telephone interviews, trained research assistants collected data on participants' hope (Herth Hope Index; HHI), self-efficacy (General Self-Efficacy Scale; GSES), and HRQOL (Short-Form 12-item health survey version 2; SF-12v2) at baseline, one month, and three months. Treatment group participants also provided feedback on MT4C through qualitative telephone interviews at one month and three months. Analysis of covariance was used to determine differences at three months, and generalized estimating equations were used to determine significant differences in HHI, GSES, and SF-12v2 between users and nonusers of MT4C from baseline to three months. Interview data were analyzed using content analysis and integrated with quantitative data at the result stage. RESULTS: Of the 101 participants at baseline, 9 (9%) withdrew from the study, leaving 92 participants at three months of which 72 (78%) used MT4C at least once; 20 (22%) participants did not use it at all. At baseline, there were no statistically significant differences in demographic characteristics and in outcome variables (HHI, GSES, and SF-12v2 mental component score and physical component score) between users and nonusers. At three months, participants who used MT4C at least once during the three-month period (users) reported higher mean GSES scores (P=.003) than nonusers. Over time, users had significantly higher GSES scores than nonusers (P=.048). Reasons for nonuse of MT4C included the following: caregiving demands, problems accessing MT4C (poor connectivity, computer literacy, and navigation of MT4C), and preferences (for paper format or face-to-face interaction). CONCLUSIONS: Web-based interventions, such as MT4C, have the potential to increase the self-efficacy of carers of persons with ADRD and MCC. Future research with MT4C should consider including educational programs for computer literacy and providing alternate ways to access MT4C in addition to Web-based access. TRIAL REGISTRATION: ClinicalTrials.gov NCT02428387; https://clinicaltrials.gov/ct2/show/NCT02428387.
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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 | 0.023 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".