Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 11 appraisals
BMC health services research
Anticipated barriers and facilitators of implementing a digital behavioral treatment for chronic pain: a qualitative interview study
BACKGROUND: In digital health innovations, sustainable implementation should be considered from the initiation of the development to ensure that the solution fits into the existing healthcare system. This study aims at identifying barriers and facilitators for the prospective implementation of a digital behavioral intervention for chronic pain in the Swedish healthcare system, as perceived by key stakeholders. METHODS: Eight semi-structured individual interviews were conducted with stakeholders (n = 2 IT developers, n = 4 healthcare managers, n = 2 healthcare professionals). Qualitative data were analyzed using a framework analysis following the Consolidated Framework for Implementation Research (CFIR). RESULTS: A total of 86 facilitators and 38 barriers to prospective implementation were identified across stakeholder interviews. Facilitators included perceived relevance of the digital intervention and organizational readiness. Identified barriers primarily related to insufficient training and supervision, unclear decision-making processes (e.g., specific actions, responsibilities of stakeholders), and the lack of systematic needs assessment to guide implementation planning. CONCLUSION: Overall, findings indicate a high level of openness toward digital interventions within the implementation context. While implementation context largely demonstrates readiness, successful integration will depend on proactively addressing identified barriers. Awareness of these factors enhances the likelihood of successful and sustainable implementation.
1 June 2026
Read appraisal →JMIR formative research
Conceptualizing Acceptance and Knowledge as Process Variables in Internet-Delivered and Therapist-Supported Cognitive Behavioral Therapy and Acceptance and Commitment Therapy in Primary Care for Insomnia: Pilot Feasibility and Process-Oriented Randomized Controlled Trial
BACKGROUND: Internet-based interventions for insomnia show promise, but understanding the process variables, such as knowledge acquisition and psychological acceptance, is crucial for enhancing digital adherence and clinical effectiveness. OBJECTIVE: This study aimed to evaluate the feasibility, adherence, and preliminary clinical signals of 2 therapist-assisted interventions-internet-delivered cognitive behavioral therapy (iCBT) and internet-delivered acceptance and commitment therapy (iACT)-for insomnia in a primary care setting. METHODS: This was a pilot randomized controlled trial. Adults seeking help for insomnia (n=18) were recruited via primary care and randomized to either a 5-module iCBT or iACT program delivered via a secure digital platform with weekly therapist feedback. Blinding of participants and therapists was not possible due to the nature of the interventions. Primary outcomes included the Insomnia Severity Index; secondary outcomes included the 9-item Patient Health Questionnaire, 7-item Generalized Anxiety Disorder, and WHO Disability Assessment Schedule. A novel sleep knowledge test was used as a process variable. The data were analyzed using split-plot analyses of variance (intention-to-treat or last observation carried forward and complete case analysis) and nonparametric Friedman and Kruskal-Wallis tests. RESULTS: A total of 18 participants were randomized (iCBT: n=9; iACT: n=9). High attrition was observed, with only 33.3% (n=3) of iCBT and 55.6% (n=5) of iACT participants completing all modules. The iACT group demonstrated a significant within-group reduction in insomnia severity (P=.01, Friedman test), whereas iCBT results were nonsignificant (P=.10, Friedman test). No significant between-group differences were found for any clinical or process variables. Participants rated both treatments as credible (Credibility/Expectancy Questionnaire scores remained stable), though qualitative feedback indicated a need for more flexible, less burdensome content. CONCLUSIONS: This pilot study demonstrates that while internet-delivered insomnia treatments are feasible and credible in primary care, high attrition remains a significant barrier. Preliminary signals suggest that iACT may be a viable alternative to iCBT, potentially offering better adherence. Larger, fully powered pilot randomized controlled trials (estimated N=404) with refined recruitment and automated retention strategies are required to determine definitive comparative efficacy and the mediating role of sleep knowledge and acceptance.
22 May 2026
Read appraisal →Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer
Effects of activity pacing-related interventions on cancer-related fatigue and classification of behavior change techniques: A systematic review and meta-analysis
PURPOSE: Although physical activity is recommended for managing cancer-related fatigue (CRF), activity pacing (AP) and energy conservation are also implemented to balance activity and rest. This systematic review assessed the effectiveness of AP-related interventions and behavior change techniques (BCTs) employed in AP-related interventions for CRF management. METHODS: We searched PubMed, CINAHL, CENTRAL, and Ichu-shi databases for articles published up to February 28, 2026. After assessing the risk of bias, we performed meta-analyses for quantitative synthesis. We also identified and classified BCTs using data from the Behavior Change Technique Taxonomy version 1. RESULTS: Among the 1257 identified studies, 10 (7 randomized controlled trials [RCTs] and 3 non-RCTs) met the inclusion criteria. The effect size was small but not significant (standardized mean differences [SMD] = - 0.36; 95% confidence intervals [CI]: - 0.73 to 0.00; 5 studies; 617 participants), with substantial heterogeneity (I2 = 66%). Compared with controls, the intervention showed a moderate, statistically significant effect in the subgroup of patients undergoing chemotherapy (SMD = - 0.58; 95% CI: - 0.87 to - 0.29; three studies; 197 participants with breast cancer). The primary BCTs used in AP-related interventions were "goal setting," "social support," and "graded tasks." CONCLUSION: AP-related interventions may provide some benefit in improving CRF, particularly during chemotherapy. However, the certainty of the current evidence is extremely low. Although these interventions represent useful approaches, further RCTs are needed, and digitization of AP-related intervention programs incorporating effective BCTs may be beneficial.
17 May 2026
Read appraisal →JMIR mHealth and uHealth
Engagement of Users in Digital Health Applications: Scoping Review
BACKGROUND: Mobile health (mHealth) uses mobile technology as a tool for prevention and health promotion. Research indicates that user engagement is crucial for effective mHealth interventions and improved health outcomes. However, many studies report low adoption rates, rapid decline after initial use, and a lack of acknowledgment of user implications in achieving outcomes. Thus, conceptualizing participation in mHealth is essential to identify key determinants for engaging users. OBJECTIVE: This scoping review aims to identify and characterize the attributes and definitions of user engagement in mHealth, examine engagement methods, and analyze barriers and facilitators influencing participation. METHODS: Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, Scopus, Web of Science, and PubMed databases were searched for publications between 2000 and 2025 with a 2-stage selection process. RESULTS: Out of 2489 articles identified, 1416 were screened, and 52 met the inclusion criteria. Half were recently published in the last 5 years (2020-2025). Existing literature focused on digital interventions for specific populations and health topics. Analysis revealed four main perspectives on engagement in mHealth: (1) usage metrics, (2) subjective user experiences, (3) a hybrid approach that combines both, and (4) a goal-oriented perspective (behavior change or health outcomes). CONCLUSIONS: To understand the complexity and multifactorial nature of participation, it is relevant to conceptualize it as a dynamic mechanism enabling users to achieve their objectives. Both quantitative use and subjective user experience should be integrated to reach the optimal intervention dose. Recognizing users' evolving needs, uniqueness, and their socioenvironmental context interdependence, it is essential to involve users in all stages (design, implementation, and iterative evaluation of mHealth). Findings will inform an e-Delphi study to establish consensus on engagement criteria.
16 May 2026
Read appraisal →JMIR mental health
Therapeutic Interventions Targeted at Problematic Use of Digital Technology: Systematic Review and Meta-Analysis of Evidence
BACKGROUND: Problematic use of digital technology has increased across the world. Despite growing research, evidence on treatment effectiveness across digital behaviors remains fragmented. OBJECTIVE: This study aimed to systematically evaluate and compare the effectiveness of therapeutic interventions targeted at problematic use of digital technology across various behavioral domains. METHODS: A systematic review and meta-analysis was conducted in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines (PROSPERO: CRD420251052442). Electronic searches of PubMed, Scopus, and Embase (up to April 2025) were conducted. It identified 125 eligible studies, including 73 randomized controlled trials (RCTs), 32 non-RCTs, 14 pre-post studies, and 6 pilot studies. The interventions that were assessed in these studies included psychological therapies, digital or web-based programs, exercise-based interventions, pharmacological treatments, neuromodulation, parent-focused programs, virtual reality-based interventions, educational programs, and multicomponent approaches. Random-effects meta-analyses using standardized mean differences (SMDs) were performed. RESULTS: For problematic internet use, psychological treatments showed a strong effect (effect size=-2.68; P<.001). Digital interventions also showed significant benefit (effect size=-1.16; P<.001). For smartphone addiction, psychological treatments (effect size=-1.49; P<.001) and exercise-based programs (effect size=-3.07; P=.001) showed significant improvement. For gaming disorder, psychological treatments showed improvement (effect size=-1.01; P=.02), but results were mixed. There were limited studies to calculate pooled results for social media addiction, pornography use, gambling, screen time, and over-the-top content watching. No treatment studies were found for problematic over-the-top content watching. High heterogeneity and evidence of small-study effects were observed in several studies. CONCLUSIONS: Overall, structured psychological therapies showed the most consistent benefit. These findings support structured interventions that aim for control of use and reduce cues linked to high use. Evidence remains limited for several emerging digital behaviors. More high-quality studies are needed in clinical settings and for less-studied forms of digital addiction.
14 May 2026
Read appraisal →Journal of medical Internet research
Barriers and Facilitators to Patient Acceptance of Artificial Intelligence in Health Care: Systematic Review
BACKGROUND: Artificial intelligence (AI) in the domain of health care is increasing in prominence. Acceptance is an indispensable prerequisite for the widespread implementation of AI. OBJECTIVE: This study aimed to explore barriers and facilitators influencing patients' acceptance of AI. METHODS: We conducted a systematic review following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Nine databases, including PubMed, Web of Science, and Embase, were comprehensively searched from inception to December 23, 2025. We included qualitative, quantitative, and mixed methods studies investigating adult patients' attitudes toward medical AI. Two researchers independently screened records, extracted data, and appraised methodological quality using the Mixed Methods Appraisal Tool. Following the Joanna Briggs Institute convergent integrated approach, data synthesis was guided by integrating the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and the Theoretical Domains Framework (TDF). Factors were mapped to behavior change techniques (BCTs) and evaluated for practical feasibility using the Affordability, Practicability, Effectiveness and cost-effectiveness, Acceptability, Side-effects/safety, and Equity criteria. RESULTS: A total of 61 studies met the inclusion criteria out of 7452 search results. Study designs included qualitative (n=20), quantitative (n=35), and mixed methods (n=6). Performance and effort expectancies were the primary determinants of acceptance. Major barriers comprised perceived operational complexity, lack of algorithmic trust, reduced interpersonal interaction, privacy vulnerabilities, and high costs. Facilitators included transparent data governance, interpretability of AI decisions, improved clinician-patient communication, and human-centered design. Education level and disease severity emerged as key moderating variables. Through UTAUT2-TDF mapping, we identified 25 distinct BCTs (6 high, 14 medium, and 5 low feasibility) and formulated 40 actionable intervention strategies. CONCLUSIONS: This study innovatively integrates the UTAUT2 and TDF frameworks to evaluate patient acceptance of medical AI. Unlike existing reviews that predominantly evaluate isolated psychosocial factors or purely technical attributes, this transtheoretical approach differentiates itself by merging technology adoption mechanisms directly with behavioral drivers. Consequently, it contributes to the field by systematically identifying multilevel factors influencing acceptance, including performance expectancy, effort expectancy, and ethical security, and translating these into 40 actionable BCTs. In real-world clinical practice, these findings provide a feasible, prioritized blueprint for clinicians and administrators to design patient-centered interventions, enhancing the clinical integration and long-term effectiveness of medical AI.
12 May 2026
Read appraisal →JMIR human factors
Personalizing Mobile Apps for Health Behavioral Change According to Personality: Cross-Sectional Validation of a Preference Matrix
BACKGROUND: Mobile health (mHealth) apps are increasingly used to support healthy lifestyle behaviors through features such as health tracking and personalized reminders. Personalized messaging, tailored to users' profiles, has been shown to improve engagement and retention in health-related contexts. Prior research has linked personality traits, based on the Big Five model, to preferences for specific app mechanisms, leading to the development of a preference matrix for personalizing mHealth apps. This matrix comprises 15 mechanisms derived from behavior change techniques and gamification elements, intended to guide developers in optimizing engagement according to user profiles. OBJECTIVE: This study aimed to validate this preference matrix by examining whether the associations between mechanisms and Big Five personality traits reported in the literature align with user preferences observed in an experimental setting. METHODS: A cross-sectional study was conducted using an online survey that collected demographic data, mHealth app usage, and personality traits. Participants were presented with mockups illustrating 15 mechanisms and were asked to select their preferred options. Logistic regression and ordinal logistic regression analyses were performed to examine associations between personality traits, mechanism selection, and motivation scores. All analyses were adjusted using the Bonferroni correction to account for multiple comparisons. RESULTS: A total of 214 participants completed the survey (mean age 29.42, SD 10.41 y; n=118, 55.1% women; n=89, 41.6% men; n=5, 2% identifying as other; and n=2, 1% nonrespondents). Higher conscientiousness significantly increased the likelihood of selecting the collection mechanism (eg, collecting badges or points; odds ratio [OR] 1.87, 95% CI 1.27-2.75). For competition (eg, competing with other users), conscientiousness (OR 3.22, 95% CI 1.73-6.00) and agreeableness (OR 1.93, 95% CI 1.08-3.45) were significant predictors. Preferences for rewards (eg, virtual incentives such as points or virtual currency) were associated with conscientiousness (OR 2.36, 95% CI 1.53-3.63) and neuroticism (OR 1.97, 95% CI 1.36-2.86). Additionally, 4 mechanisms-self-monitoring, progression, challenge, and quest-were selected by more than half of the participants, independent of personality traits. CONCLUSIONS: The findings partially validate the proposed preference matrix. Conscientiousness consistently emerged as a key predictor of preference across multiple mechanisms, highlighting its central role in engagement with gamified mHealth features. While some mechanisms appear to have universal appeal, others show personality-specific preferences, underscoring the value of combining baseline mechanisms with targeted personalization strategies in mHealth app design.
25 Apr 2026
Read appraisal →JMIR formative research
Development of iGET Living, a Digital Graded Exposure Intervention for Youth With Chronic Pain: Multiphase User-Centered Design and Pilot Study
BACKGROUND: Pediatric chronic pain affects up to one-third of youth and is associated with significant disruptions in social, emotional, and behavioral functioning. Although behavioral treatments are effective, access remains limited due to geographic, financial, and systemic barriers. Digital behavioral health interventions offer a promising solution, but many lack user-centered design, iterative refinement, and implementation-informed development strategies that support usability and scalability. OBJECTIVE: This study aimed to develop and iteratively refine iGET Living, a digital graded exposure intervention for youth with chronic pain, using a combined user-centered and implementation-informed framework, and to evaluate its preliminary acceptability, feasibility, and user-perceived success. METHODS: Guided by the Consolidated Framework for Implementation Research (CFIR) and the mHealth (mobile health) Agile Development and Lifecycle model, intervention development proceeded through 3 phases. Phase 0 translated an evidence-based in-person graded exposure treatment (GET Living) into an initial digital prototype. Phase 1 involved iterative user-centered refinement across 3 cycles of qualitative development sessions with youth with chronic pain (n=15), incorporating think-aloud usability testing, Likert-rated feedback, and rapid qualitative analysis mapped to CFIR constructs to guide real-time modifications to content, design, and functionality. Phase 2 piloted the refined intervention with a new sample of youth (n=38, n=30 completers) recruited from a tertiary pediatric pain clinic to evaluate feasibility, acceptability, treatment credibility and expectancy, and user-perceived functional improvements. Quantitative outcomes were summarized descriptively, and qualitative exit interview data were analyzed using rapid qualitative analysis. RESULTS: Across development cycles, youth feedback informed substantive refinements to the intervention, including reducing text density, incorporating animated educational videos, enhancing interactive features, and improving navigation and layout. These changes resulted in progressive improvements in clarity, satisfaction, and acceptability across prototypes. In the Phase 2 pilot study, participants reported moderate-to-high treatment credibility (mean of 19.71 out of 30) and expectancy (mean of 17.96 out of 30), as well as high satisfaction (mean of 46.12 out of 60). Acceptability ratings across domains of the Theoretical Framework of Acceptability were favorable. Qualitative exit interviews highlighted the interventions' perceived role in helping youth re-engage in valued activities. CONCLUSIONS: Using a combined CFIR and agile development approach, iGET Living emerged as a feasible, acceptable, engaging digital graded exposure intervention for youth with chronic pain. These findings highlight the value of integrating implementation frameworks and participatory design early in digital intervention development and support further evaluation in a preliminary efficacy trial.
18 Apr 2026
Read appraisal →JMIR formative research
Real-World Data From a Group Parent Management Training Program Enhanced Using Artificial Intelligence: Qualitative Study
BACKGROUND: Parent management training (PMT) is an evidence-based intervention for children with disruptive behavior problems. However, access to care is often limited by cost, availability of clinicians, scheduling, and transportation barriers. Integrating artificial intelligence (AI) into group PMT may improve accessibility, personalization, and adherence, while preserving therapeutic quality. OBJECTIVE: This study explored caregivers' experiences with a hybrid PMT program that combined live therapist-led group sessions with asynchronous support from Pat, an AI conversational agent designed to augment the therapists' support to caregivers. METHODS: A total of 88 caregivers of children aged 3-14 years (mean 7.98, SD 2.45 years) from Argentina and Paraguay participated in eight weekly online group sessions led by human therapists and supplemented by Pat. Caregivers were asked to provide the net promoter score (NPS) and their perceived contribution of their experience in remote group sessions and with Pat. Caregiver perspectives were analyzed using thematic analysis by multiple coders with consensus and interrater reliability assessment. RESULTS: The average NPS was 76.92, indicating excellent satisfaction. Regarding participants' perceptions of the overall program, the most frequent theme was useful strategies (73/202, 36.1%), reflecting the value placed on clear, structured, and practical tools to address everyday parenting challenges. Most comments about Pat were positive (156/164, 95.1%), particularly highlighting its 24/7 accessibility and constant availability (69/164, 42.1%). Recommendations for improvement mainly focused on enhancing the user experience and incorporating additional functionalities. Regarding perceived contribution to progress, caregivers attributed, on average, 61% to Pat and 46% to the group sessions. CONCLUSIONS: Combining therapist-led PMT group sessions with AI support appears feasible, acceptable, and valued by caregivers and may expand reach without sacrificing quality. Overall, caregivers valued the useful strategies and the professional and peer support and reported positive changes. Regarding Pat, the most valued aspect is the constant and immediate support. This model integrates human expertise with the accessibility and continuity provided by AI, reducing barriers, such as time, cost, and clinician availability.
8 Apr 2026
Read appraisal →Journal of medical Internet research
Effectiveness of the Components of a Digital Multiple Health Behavior Change Intervention Among Individuals Seeking Help Online (Coach): Factorial Randomized Trial
BACKGROUND: Extant digital multiple health behavior change interventions have shown promise in various populations; however, evidence for a broader approach among the general population is lacking. Moreover, existing interventions often contain several components but are typically assessed as a whole, meaning it remains unclear to what extent individual components contribute to intervention effects and how they may interact to influence health outcomes. OBJECTIVE: This study estimates the effects of 6 components of a digital health behavior change intervention on alcohol, diet, physical activity, and smoking outcomes among individuals searching for help online. METHODS: A double-blind randomized factorial trial design with 6 two-level factors was used. Adults from the general public in Sweden who were seeking help to change their behaviors were recruited through web searches and social media. Participants were eligible if they were 18 years or older and had at least one health behavior classified as unhealthy. Effects of 6 components were estimated: screening/feedback, goal-setting/planning, motivation, skills/know-how, mindfulness, and self-authored SMS text messages. Primary outcomes were weekly alcohol consumption and frequency of heavy episodic drinking, average daily fruit and vegetable consumption, weekly moderate-to-vigorous physical activity, and 4-week point-prevalence smoking. RESULTS: A total of 5419 individuals were randomized. Overall, the screening/feedback component was the most effective for changing health behaviors, along with goal-setting/planning and motivation to change. In particular, there was evidence that screening/feedback increased average daily portions of fruit and vegetables at 2 months (mean difference 0.17, compatibility interval [CoI] 0.09-0.25, probability of effect [POE] >99.9%) and at 4 months (mean difference 0.13, CoI 0.04-0.21, POE 99.9%) and reduced the frequency of heavy episodic drinking at 4 months (incidence rate ratio 0.91, CoI 0.81-1.03, POE 94.2%). Components also interacted to further improve health outcomes, most notably the combination of screening/feedback with motivation to change, which further increased fruit and vegetable consumption (2 months: mean difference 0.20, CoI 0.09-0.30, POE >99.9%; 4 months: mean difference 0.17, CoI 0.05-0.29, POE 99.8%). CONCLUSIONS: The results from this study contribute to the development of more effective interventions by providing novel insights into the effects of individual and pairwise components of complex digital health behavior change interventions. TRIAL REGISTRATION: ISRCTN Registry ISRCTN16420548; http://www.isrctn.com/ISRCTN16420548. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2022-061024.
4 Apr 2026
Read appraisal →Journal of behavioral addictions
Gambling in women: A systematic review of interventions and prevention approaches
BACKGROUND: Gambling disorder (GD) is a behavioral addiction with significant psychological, social, and economic consequences. Despite growing female participation and distinct gambling characteristics, research and interventions largely male-centered, overlooking women-specific factors. OBJECTIVES: This systematic review synthesizes evidence on prevention and treatment interventions for women with GD, assessing their effectiveness on gambling behaviors, cognitive and psychological outcomes, and identifying barriers related to access, adherence, and gender-sensitive design. METHOD: A systematic search in PubMed, PsycINFO, and Web of Science (up to September 2025) identified quantitative studies reporting female-specific outcomes in gambling prevention or treatment. Study quality was appraised using National Heart, Lung, and Blood Institute tools, and data on intervention characteristics, outcomes, and participant profiles were extracted. RESULTS: Eighteen studies met the inclusion criteria (five prevention, thirteen treatment). Prevention programs, mostly universal and adolescent-focused, improved gambling knowledge, cognitive distortions, and short term gambling frequency; however, socioemotional effects were inconsistent. Only one study included follow-up assessment. Treatment studies, predominantly cognitive behavioral therapy (CBT)-based, reduced gambling severity and psychological distress, although dropout and relapse rates were higher among women with greater psychopathology or limited support. Person-centered approaches benefited of tailoring interventions to individual profiles. No studies systematically applied gender-sensitive frameworks or disaggregated outcomes by sex in prevention. DISCUSSION AND CONCLUSION: Prevention and treatment programs can benefit women, but standard interventions insufficiently address their unique needs. Gender-sensitive, individualized strategies, inclusion of socioemotional factors, and long-term evaluations are essential to enhance outcomes and inform inclusive public health policies.
4 Apr 2026
Read appraisal →