SynthesisJournal of medical systems2017
A Systematic Review and Taxonomy of Published Quality Criteria Related to the Evaluation of User-Facing eHealth Programs.
Synthesis in Journal of medical systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Timing, Indicators, and Approaches to Digital Patient Experience Evaluation: Umbrella Systematic Review.Journal of medical Internet research · 2024Pooled it
- Digital Patient Experience: Umbrella Systematic Review.Journal of medical Internet research · 2022Pooled it
- Development and Evaluation of a Smartphone-Based Chatbot Coach to Facilitate a Balanced Lifestyle in Individuals With Headaches (BalanceUP App): Randomized Controlled Trial.Journal of medical Internet research · 2024Trial
- More than a chatbot: a practical framework to harness artificial intelligence across key components to boost digital therapeutics quality.Frontiers in digital health · 2025Article
- [Quality Indicators for Video Consultations in Primary Care - a Scoping Review].Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)) · 2023Article
- Assessing the Quality and Impact of eHealth Tools: Systematic Literature Review and Narrative Synthesis.JMIR human factors · 2023Review
- Mobile Health Apps for the Control and Self-management of Type 2 Diabetes Mellitus: Qualitative Study on Users' Acceptability and Acceptance.JMIR diabetes · 2023Article
- Effort-Optimized Intervention Model: Framework for Building and Analyzing Digital Interventions That Require Minimal Effort for Health-Related Gains.Journal of medical Internet research · 2021Article
- Usability and User Experience of Cognitive Intervention Technologies for Elderly People With MCI or Dementia: A Systematic Review.Frontiers in psychology · 2021Review
- Digital Micro Interventions for Behavioral and Mental Health Gains: Core Components and Conceptualization of Digital Micro Intervention Care.Journal of medical Internet research · 2020Article
- Feasibility study for supporting medication adherence for adults with cystic fibrosis: mixed-methods process evaluation.BMJ open · 2020Article
- Evaluation of a Mobile Phone App for Patients With Pollen-Related Allergic Rhinitis: Prospective Longitudinal Field Study.JMIR mHealth and uHealth · 2020Article
- Validation of the Mobile Application Rating Scale (MARS).PloS one · 2020Article
- ZIEL: Internet-Based Self-Help for Adjustment Problems: Results of a Randomized Controlled Trial.Journal of clinical medicine · 2019Article
- Objective User Engagement With Mental Health Apps: Systematic Search and Panel-Based Usage Analysis.Journal of medical Internet research · 2019Article
- Examining Predictors of Real-World User Engagement with Self-Guided eHealth Interventions: Analysis of Mobile Apps and Websites Using a Novel Dataset.Journal of medical Internet research · 2018Article
- Concussion Assessment With Smartglasses: Validation Study of Balance Measurement Toward a Lightweight, Multimodal, Field-Ready Platform.JMIR mHealth and uHealth · 2018Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The purpose of this review was to identify and classify key criteria concepts related to the evaluation of user-facing eHealth programs. In line with the PRISMA statement methodology, computer searches of relevant databases were conducted for studies published between January 1, 2000 and March 1, 2016 that contained explicit quality criteria related to mHealth and eHealth products. Reference lists of included articles, review articles, and grey literature (e.g., books, websites) were searched for additional sources. A team of nine experts led by the first author was gathered to support the classification of these criteria. Identified criteria were extracted, grouped and organized using an inductive thematic analysis. Eighty-four sources - emanating from 26 different courtiers - were included in this review. The team extracted 454 criteria that were grouped into 11 quality domains, 58 criteria concepts and 134 concepts' sub-groups. Quality domains were: Usability, Visual Design, User Engagement, Content, Behavior Change/Persuasive Design, Influence of Social Presence, Therapeutic Alliance, Classification, Credibility/Accountability, and Privacy/Security. Findings suggest that authors around the globe agree on key criteria concepts when evaluating user-facing eHealth products. The high proportion of new published criteria in the second half of this review time-frame (2008-2016), and more specifically, the high proportion of criteria relating to persuasive design, therapeutic alliance and privacy/security within this time-frame, points to the advancements made in recent years within this field.
Indexed as
Identifiers
28735372What OpenQuestion holds
Registered trials
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.