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Record W4411171573 · doi:10.2196/72862

Digital Health Portals for Individuals Living With or Beyond Cancer: Patient-Driven Scoping Review

2025· article· en· W4411171573 on OpenAlexaffvenue
Steven Ouellet, Florian Naye, Wilfried Supper, Chloé Cachinho, Marie‐Pierre Gagnon, Annie LeBlanc, Marie-Claude Laferrière, Simon Décary, Maxime Sasseville

Bibliographic record

VenueJMIR Cancer · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsInstitut Universitaire en Santé Mentale de QuébecUniversité de SherbrookeUniversité Laval
Fundersnot available
KeywordsPreprintDigital healthCancerInternet privacyGerontologyMedicinePsychologyHealth careComputer scienceWorld Wide WebPolitical science

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.508
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.056
GPT teacher head0.509
Teacher spread0.454 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations3
Published2025
Admission routes2
Has abstractyes

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