Features of virtual navigation systems for health care and social services that impact patient outcomes: Protocol for a scoping review (Preprint)
Bibliographic record
Abstract
Background: Patient navigation is a critical component of health care delivery, facilitating connections with appropriate services. A new era of virtual navigation systems has emerged, with systems that can be accessed through websites or smartphone apps. However, it is unknown which features of these novel systems impact patient outcomes. Objective: The objective of this scoping review is to understand the current landscape of existing virtual navigation systems. In this review, we will determine the features of these systems, as well as the patient outcomes and accessibility barriers associated with them that have been reported in the literature. Methods: This review will follow the guidelines for scoping reviews outlined by the Joanna Briggs Institute methodology. This will include systems that provide recommendations for health care, mental health and addiction services, and social services. This will include systems designed for patients, caregivers, and/or care providers. A search strategy will be used to locate both published and unpublished literature. The databases to be searched include PubMed, PsycINFO (ProQuest), Cochrane Library, Web of Science Core Collection (Clarivate), Cumulative Index of Nursing and Allied Health Literature (EBSCO), ScienceDirect, IEEE Xplore, and ACM Digital Library. Papers will be screened and selected, and data will be extracted by 2 independent members of the research team. The extracted data will primarily focus on outcomes and features of the virtual navigation systems. This will include the information they ask of users and the content and format of the information on services they provide. Results: Funding for this project was received in May 2024. As of June 2026, abstract and full-text screening have been completed, data extraction is underway, and data analysis has not begun yet. Our search resulted in the retrieval of 14,461 studies that were eligible for screening. We anticipate that the full scoping review manuscript will be prepared for submission by winter 2027. Results will be presented in tabular format and accompanied by a narrative summary. Conclusions: This review will synthesize the current literature on virtual navigation systems that aim to connect patients to appropriate health care services. By identifying trends and gaps, this review will provide critical information for the development of new and innovative systems that can support health care and public health systems.
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 | 0.143 | 0.283 |
| Meta-epidemiology (narrow) | 0.005 | 0.007 |
| Meta-epidemiology (broad) | 0.010 | 0.015 |
| Bibliometrics | 0.016 | 0.012 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.068 | 0.013 |
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".