Dementia Care Apps for People with Dementia and Informal Caregivers: A Systematic Review Protocol
Bibliographic record
Abstract
Dementia drastically impacts the quality of life (QOL) of both people living with dementia (PLwD) and their family caregivers. As dementia progresses and care needs escalate, the likelihood of institutionalization is increased, which is counter to the wishes of the majority of older adults and their family members. Dementia care apps can provide critical support and have the potential to improve the QOL of both PLwD and their family caregivers and reduce perceived caregivers' burden. However, there is a lack of understanding of the needs of both PLwD and their family caregivers related to dementia care apps. There is also a gap in understanding the privacy concerns in relation to the apps among older adults with dementia and their caregivers. As such, the main aims of this systematic review are to understand the landscape of dementia mobile apps targeting PLwD and their caregivers with respect to the features of the apps, usability testing, and the privacy and security aspects of the app from the perspective of both app developers/researchers and the end users (PLwD and family caregivers who provide care of PLwD). Extensive databases, including ACM Digital Library, Cochrane Central Register of Controlled Trials, Compendex, Embase, Inspec, Ovid MEDLINE(R) Daily, Proquest Dissertations and These Global, PsycINFO, and Scopus, have been searched. All searches are from the inception of the databases. All peer-reviewed studies and articles written in the English language are included. Two reviewers will independently screen and select the studies with the involvement of a third reviewer for disagreements. Data will be abstracted using a custom data extraction form that is made based on the research questions. Critical Appraisal Skills Programme (CASP) checklists will be used to assess the study quality. As the first review of its kind, the findings from this review will provide valuable insights related to the needs of the dementia care apps for both PLwD and their family caregivers. The review will be relevant to health providers who are interested in using technologies to promote the independence of PLwD and reduce the stress experienced from caregivers of PLwD. The review will also serve as a guide to app developers and researchers to design usable and acceptable apps. In addition, the review will provide critical knowledge of the privacy and security features of the app to reveal the valid concerns from the end users and thus help with the uptake and adoption of the dementia care apps.
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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 | 0.054 | 0.047 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.020 | 0.015 |
| Bibliometrics | 0.016 | 0.012 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.087 | 0.011 |
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".