Self-Management Systems for Patients and Clinicians in Parkinson Care: Protocol for an Integrated Scoping Review, Product Search, and Evaluation
Bibliographic record
Abstract
BACKGROUND: Parkinson disease (PD) poses emotional and financial challenges to patients, families, caregivers, and health care systems. Self-management systems show promise in empowering people with PD and enabling more control over their treatment. The collaborative nature of PD care requires communication between patients and health care professionals. While past reviews explored self-management systems in PD diagnosis and symptom management with a focus on patient portals, there is limited research addressing the interconnectivity of systems catering to the needs of both patients and clinicians. A system's acceptability and usability for clinicians are pivotal for enabling comprehensive data collection and supporting clinical decision-making, which can enhance patient care and treatment outcomes. OBJECTIVE: This review study aims to assess PD self-management systems that include a clinician portal and to determine which features enhance acceptability and usability for clinicians. The primary aim is to assess evidence of clinicians' acceptability and usability of self-management systems with a focus on the integration of systems into clinical workflows, data collection points, monitoring, clinical decision-making support, and extended education and training. METHODS: The review will entail 3 separate stages: a literature review following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, a product search, and an evaluation of the level of evidence for the identified products. For the first stage, 5 databases will be searched: PubMed, CINAHL, Scopus, ACM digital library, and IEEE Xplore. Studies eligible for inclusion will be qualitative, quantitative, and mixed methods studies examining patients' and clinician's perceptions of the acceptability and usability of digital health interventions, synthesized by a narrative qualitative analysis. A web search in the iOS Apple App Store and Android Google Play Store will identify currently available tools; the level of evidence for these will then be assessed using the Oxford Centre for Evidence-Based Medicine guidelines. RESULTS: Literature search and screening began soon after submission of the protocol, and the review is expected to be completed by end of September 2024. CONCLUSIONS: This review will examine currently available self-management systems in PD care, focusing on their acceptability and usability. This is significant because there is limited research addressing the integration of clinicians into these systems. The findings from this study may provide critical knowledge and insight to help inform future research and will contribute to the design of self-management systems that promote collaborative efforts in PD care. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/58845.
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 | 0.115 | 0.109 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.019 | 0.021 |
| Bibliometrics | 0.020 | 0.020 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.007 | 0.010 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.072 | 0.014 |
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".