Evidence map›Paper›PMID 40875981›Full record

ArticleJournal of medical Internet research2025

Digital Health Interventions Providing Behavioral Assessment and Goal Prioritization Support: Scoping Review.

Ilona Margaret McNeill, Ron Borland, Charles Abraham

Abstract readScoping Review
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ilona Margaret McNeillDepartment of Psychological Sciences, School of Health Sciences, Swinburne University of Technology, Hawthorn, Australia.ORCID https://orcid.org/0000-0001-9766-1099
Ron BorlandSchool of Psychology, Deakin University, Geelong, Australia.ORCID https://orcid.org/0000-0003-0059-178X
Charles AbrahamSchool of Psychology, Deakin University, Geelong, Australia.ORCID https://orcid.org/0000-0002-0901-1975

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAffordability of health care systems depends on populations' engagement in preventive health behavior and appropriate self-management of long-term conditions. Digital health interventions (DHIs) could facilitate this by prompting and supporting individual health behavior change. Behavior change is often undermined by suboptimal prioritization of goals. Therefore, DHIs aiming to promote behavior change should help users identify behavior patterns that need changing and scaffold goal prioritization.

objectiveThis scoping review explores the extent to which DHIs are supporting users to identify and prioritize goals relevant to managing and improving health.

methodsThe review followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. Web of Science (Core Collection), Scopus, Ovid (Embase, MEDLINE, PsycINFO, and Global Health), and EBSCOHOST (Academic Search Complete and CINAHL Complete) were searched for literature on the development and evaluation of digital interventions that (1) assess users' current health or health-related behaviors and (2) offer support on prioritization of health-related goals.

resultsFifty-six papers were included. These identified 19 unique DHIs. Targeted populations included the general population (n=10), those at risk of or diagnosed with cardiovascular disease (n=4), those at risk of or diagnosed with diabetes (n=2), those diagnosed with cancer (n=2), or those diagnosed with HIV (n=1). One DHI targeted preconception among African American women. All DHIs targeted physical activity and most (n=17) targeted diet and smoking, closely followed by alcohol use (n=15) and mental health (n=13). Social wellbeing (n=5), sleep (n=4), and pain (n=1) were less commonly included. All 19 DHIs included a health risk assessment with feedback identifying health domains in need of improvement, but only four asked users to select a prioritized change goal. Outcome evaluations were conducted for most (n=14), with nine DHIs evaluated using at least one randomized control trial (RCT). Almost half of all DHIs (n=9) reported at least one evaluation of behavioral outcomes, mostly employing RCTs (7/9). Six of 19 reported at least one evaluation of psychological health outcomes, again mostly employing RCTs (5/6). Among the seven DHIs for which behavioral outcomes were evaluated using a RCT, effects were mixed, with only one DHI showing significant effects across all assessed behavioral outcomes. Three found significant effects for some, but not all, outcomes or timepoints, and three found no significant effects.

conclusionsAlthough all 19 DHIs provided some advice about which health-related goals to prioritize, most did not actively prompt users to set such priorities. DHIs showing the most promise in terms of health behavior change were those that explicitly promoted users to prioritize changing specified health behaviors. This review highlights how DHIs could provide greater behavior change support and provides the basis for designing more effective DHIs.

Indexed as

GoalsHealth BehaviorDigital HealthHumansaffordabilitybehavioral assessmentbehavioral changebehavior changebehavior patternsDHIsdigital coachdigital health interventiongoal prioritizationhealth behaviorhealth care systemhealth self-managementmHealth interventionspersonalized supportscoping reviewself-assessmentsystematic review

Identifiers

PMID40875981
PMCPMC12426573

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.