Digital Health Portals for Individuals Living With or Beyond Cancer: Patient-Driven Scoping Review
Bibliographic record
Abstract
BACKGROUND: Digital health portals are online platforms allowing individuals to access their personal information and communicate with health care providers. While digital health portals have been associated with improved health outcomes and more streamlined health care processes, their impact on individuals living with or beyond cancer remains underexplored. OBJECTIVE: This scoping review aimed to (1) identify the portal functionalities reported in studies involving individuals living with or beyond cancer, as well as the outcomes assessed, and (2) explore the diversity of participant characteristics and potential factors associated with portal use. METHODS: We conducted a scoping review in accordance with the JBI methodology (formerly the Joanna Briggs Institute) and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. We included primary research studies published between 2014 and 2024 that involved participants living with or beyond cancer, had access to personal health information, and assessed at least one outcome related to health or the health care system. We searched the Embase, Web of Science, MEDLINE (Ovid), and CINAHL Plus with Full Text databases. Five reviewers independently screened all titles, abstracts, and full texts in duplicate using Covidence. We extracted data on study design, participant characteristics, portal functionalities, outcomes assessed, and PROGRESS-Plus (place of residence; race, ethnicity, culture, or language; occupation; gender or sex; religion; education; socioeconomic status; and social capital-Plus) equity factors. RESULTS: We included 44 studies; most were conducted in the United States (n=30, 68%) and used quantitative (n=23, 52%), mixed methods (n=11, 25%), or qualitative (n=10, 23%) designs. The most common portal features were access to test results (28/44, 64%) and secure messaging (30/44, 68%). Frequently reported services included appointment-related functions (19/44, 43%), educational resources (13/44, 30%), and prescription management features (11/44, 25%). Behavioral and technology-related outcomes were the most frequently assessed (37/44, 84%), followed by system-level (19/44, 43%), psychosocial (16/44, 36%), and clinical outcomes (5/44, 11%). Overall, 43% (19/44) of the studies addressed PROGRESS-Plus factors. Age was the most frequently reported (13/19, 68%), followed by socioeconomic status (10/19, 53%), race or ethnicity (7/19, 37%), and gender or sex (7/19, 37%). Social capital (2/19, 11%), occupation (1/19, 5%), and disability (1/19, 5%) were rarely considered, and religion was not reported in any study. CONCLUSIONS: While digital health portals enhance patient engagement, their clinical impact and equity implications remain insufficiently evaluated. We found disparities in functionalities, outcomes, and PROGRESS-Plus representation. To promote equitable benefits, future studies should adopt inclusive designs and evaluation strategies that address diverse outcomes and integrate social determinants of health.
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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 | 0.038 | 0.153 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.022 | 0.022 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".