Quality Assessment of Digital Health Applications: Protocol for a Scoping Review
Bibliographic record
Abstract
BACKGROUND: All over the world, development and usage of mobile health (mHealth) apps is increasing. While apps offer numerous opportunities to improve health care, there are associated problems that differ significantly from those of traditional health care services. Further investigations on the quality of mHealth apps are needed to address these problems. OBJECTIVE: This study aims to identify and map research on quality assessment and quality assurance of mHealth apps and their transferability to continuous quality assurance of mHealth apps. METHODS: The scoping review will follow published methodological frameworks for scoping studies as well as Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews criteria. Electronic databases (Medline, EMBASE, and PsycINFO), reference lists of relevant articles, and websites of relevant institutions will be searched. Two reviewers will independently assess eligibility of articles. Therefore, a 2-stage (title and abstract, followed by full text) screening process was conducted. Quality management systems and quality assessment tools will be analyzed and included in our review. Particular focus is placed on quality dimensions. RESULTS: This scoping review provides an overview of the available evidence and identifies research gaps regarding continuous quality assessment of mHealth apps. Thereby, relevant quality dimensions and criteria can be identified and their eligibility and relevance for the development of a continuous quality assurance system of mHealth apps can be determined. Our results are planned to be submitted to an indexed, peer-reviewed journal in the second half of 2022. CONCLUSIONS: This is the first review in the context of continuous quality assurance of mHealth apps. Our results will be used within the research "Continuous quality assurance of Digital Health Applications" ("QuaSiApps") project funded by the German Federal Joint Committee. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/36974.
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 | 0.162 | 0.177 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.013 | 0.018 |
| Bibliometrics | 0.020 | 0.020 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.102 | 0.020 |
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".