Understanding Disengagement in AI-based Just-in-Time Mobile Health Interventions

Perinatal mental health problems, such as anxiety, stress, and depression, warrant particularly close monitoring and intervention, but they are often unaddressed in both obstetric and psychiatric clinics, with limited accessibility and treatment resources. Mobile health interventions may provide an effective and more accessible solution for addressing perinatal mental health. Development and evaluation of a mobile mental health intervention specifically for pregnant women are warranted. This study aimed to evaluate the effectiveness of a 4-week, self-administered mobile mindfulness intervention in reducing anxiety, depression, and stress, and improving emotional well-being, maternal-fetal attachment, and mindfulness skills in a general population of pregnant women. Pregnant women were recruited and randomized to an intervention or a wait-list control group. The intervention group participated in a self-administered 4-week smartphone-based mindfulness program. Anxiety, depression, and stress were assessed as primary outcomes at baseline and postintervention. Secondary outcomes were mental health well-being, maternal-fetal attachment, and skills of mindfulness. The usability of the mobile intervention was also evaluated. A total of 133 pregnant women were randomly assigned to the intervention (n=66) or the control group (n=67). The overall dropout rate was 30% (39/133). Anxiety scores of the intervention group significantly decreased from baseline to postintervention (P=.03, Wilcoxon Signed-Rank test), whereas no significant changes were observed in the control group. Depression and stress scores showed no significant changes. Emotional well-being significantly improved in the intervention group (P=.01). Improvements were observed in maternal-fetal attachment, particularly in attributing characteristics to the fetus (P=.003) and in differentiating the self from the fetus (P=.006). Mindfulness awareness also showed significant improvement (P=.008). Significant between-group effects were identified for mindfulness awareness (P=.006) and attributing characteristics to the fetus (P=.002). After applying the false discovery rate corrections, within-group improvements in emotional well-being, maternal-fetal attachment, and mindfulness awareness remained significant, while between-group differences for emotional well-being and differentiation were not significant. A mobile mindfulness program effectively reduced anxiety and improved emotional well-being, maternal-fetal attachment, and mindfulness awareness in the general population of pregnant women. Mobile interventions may offer a cost-effective and feasible method for promoting perinatal mental health. Clinical Research Information Service KCT0007166; https://tinyurl.com/458vfc4r.

Non- Communicable Diseases (NCDs) such as hypertension and diabetes have continued to impose a significant health burden in Low and Middle-Income Countries (LMICs), where treatment compliance remains critically low. Systemic barriers including limited healthcare infrastructure, inadequate follow-up mechanisms, and sociocultural factors have impeded patients’ ability to adhere to long-term treatment regimens. While mobile health (mHealth) and digital interventions have emerged as potential tools to enhance medication adherence, their effectiveness in LMICs remains uneven and context-dependent. This study aimed to assess the role of health system factors in promoting treatment compliance among patients with NCDs through mobile platforms in LMICs, with a particular focus on Kenya. A qualitative literature review was conducted using purposive sampling of 20 peer-reviewed articles published between 2020 and 2025. The studies were selected based on their focus on health system factors, treatment compliance, and digital or mobile health interventions in LMICs. Data were extracted and analyzed thematically to identify patterns across health system components, digital health strategies, and patient adherence outcomes. The review revealed that systemic barriers including shortages of healthcare personnel, poor digital infrastructure, low health literacy, and financial constraints consistently undermined treatment compliance in LMICs. However, digital tools such as SMS reminders, mHealth apps, and teleconsultations demonstrated improved patient adherence, especially when culturally adapted and integrated into community health frameworks. In Kenya and similar settings, mobile interventions linked with community health workers showed greater success in sustaining long-term engagement. Nonetheless, disparities persisted in digital access, gender equity, and scalability due to infrastructural limitations and weak policy integration. Mobile and digital health platforms offered a promising avenue for improving treatment compliance among NCD patients in LMICs. Their effectiveness was significantly influenced by the readiness of local health systems, sociocultural adaptability, and the extent of integration with human health resources. Despite their potential, many digital interventions remained fragmented, donor-driven, and unsustainable without supportive infrastructure and policy frameworks. To optimize the impact of mobile health (mHealth) interventions, policymakers should invest in digital infrastructure, integrate mHealth into national health systems, and prioritize the training and deployment of community health workers. Future research should include longitudinal and experimental designs to assess long-term outcomes and cost-effectiveness, and emphasize inclusive, culturally tailored approaches to improve equitable access to care.

Studies have linked the large percentage of maternal and neonatal mortality that occur in postnatal period to low uptake of postnatal care (PNC) services. Mobile health (mHealth) intervention through message reminders has resulted in significant increase in antenatal care utilisation in previous studies. However, its use in PNC services’ uptake has not been adequately investigated in Nigeria. This study aimed to evaluate the effect of a mobile health intervention on PNC attendance among mothers in selected primary healthcare facilities in Osun State, Nigeria. A quasi-experimental research design was utilised. Participants were allocated to Intervention Group and Control Group. One hundred and ninety pregnant mothers were recruited in each group. A mobile health intervention software was developed and used to send educational and reminder messages to mothers in the intervention group from the 35th week of pregnancy to six weeks after delivery. Uptake of PNC services was assessed at birth, 3 days, 10 days and 42 days after delivery. Data were analysed using descriptive statistics, chi-square and logistic regression models. About one-third (30.9%) of respondents in the intervention group had four postnatal care visits while only 3.7% in the control group had four visits (p < 0.001). After controlling for the effect of confounding variables, group membership remained a significant predictor of PNC uptake. (AOR: 10.869, 95% CI: 4.479–26.374). Mobile health intervention significantly improved utilisation of the recommended four postnatal care visits.

Breast cancer is affecting millions of people worldwide. If not appropriately handled, the side effects of different modalities of cancer treatment can negatively impact patients' quality of life and cause treatment interruptions. In recent years, mobile health (mHealth) interventions have shown promising opportunities to support breast cancer care. Numerous studies implemented mobile health interventions aiming to support patients with breast cancer, for example, through physical activity promotion or educational content. Nonetheless, current literature reveals that real-world evidence for the actual benefits remains unclear. In this systematic review, we focus on analyzing the methodology used in recent studies to determine the effects of mHealth applications and wearable devices on the outcome of patients with breast cancer. We followed the PRISMA guideline for the selection, analysis, and reporting of relevant studies found in the databases of Medline, Scopus, Web of Science, and Cochrane Library. A total of 276 unique records were identified, and 20 studies met the inclusion criteria. Study quality was assessed with the Effective Public Health Practice Project (EPHPP) Quality Assessment Tool for Quantitative Studies. While many of the studies used standardized questionnaires as patient-reported outcome measures, there was minimal use of objective measurements, such as activity sensors. Adoption, drop-out rates, and usage behavior of users of the mobile health intervention were often not reported. Future work should clearly define the focus and desired outcome of mHealth interventions and select outcome measures accordingly. Greater transparency facilitates the interpretation of results and conclusions about the real-world evidence of mobile health in breast cancer care.

Mobile health interventions are increasingly popular in pediatrics; however, it is unclear how effective these interventions are in changing health outcomes. To determine the effectiveness of mobile health interventions for improving health outcomes in youth 18 years or younger. Studies published through November 30, 2016, were collected through PubMed, Cumulative Index to Nursing and Allied Health Literature, Educational Resources Information Center, and PsychINFO. Backward and forward literature searches were conducted on articles meeting study inclusion criteria. Search terms included telemedicine, eHealth, mobile health, mHealth, app, and mobile application. Search results were limited to infants, children, adolescents, or young adults when possible. Studies were included if quantitative methods were used to evaluate an application of mobile intervention technology in a primary or secondary capacity to promote or modify health behavior in youth 18 years or younger. Studies were excluded if the article was an unpublished dissertation or thesis, the mean age of participants was older than 18 years, the study did not assess a health behavior and disease outcome, or the article did not include sufficient statistics. Inclusion and exclusion criteria were applied by 2 independent coders with 20% overlap. Of 9773 unique articles, 36 articles (containing 37 unique studies with a total of 29 822 participants) met the inclusion criteria. Of 9773 unique articles, 36 articles (containing 37 unique studies) with a total of 29 822 participants met the inclusion criteria. Effect sizes were calculated from statistical tests that could be converted to standardized mean differences. All aggregate effect sizes and moderator variables were tested using random-effects models. Change in health behavior or disease control. A total of 29 822 participants were included in the studies. In studies that reported sex, the total number of females was 11 226 (53.2%). Of those reporting age, the average was 11.35 years. The random effects aggregate effect size of mobile health interventions was significant (n = 37; Cohen d = 0.22; 95% CI, 0.14-0.29). The random effects model indicated that providing mobile health intervention to a caregiver increased the strength of the intervention effect. Studies that involved caregivers in the intervention produced effect sizes (n = 16; Cohen d = 0.28; 95% CI, 0.18-0.39) larger than those that did not include caregivers (n = 21; Cohen d = 0.13; 95% CI, 0.02-0.25). Other coded variables did not moderate study effect size. Mobile health interventions appear to be a viable health behavior change intervention modality for youth. Given the ubiquity of mobile phones, mobile health interventions offer promise in improving public health.

Enablers and barriers to the acceptability of mHealth for maternal healthcare in rural Edo, Nigeria.

Just-in-time (JIT) intervention aims to proactively detect a user's problematic behaviors and deliver interventions at an opportune moment to facilitate target behaviors. However, prior studies have shown that JIT intervention may suffer from user disengagement, a phenomenon in which a user's level of engagement with intervention apps and target behaviors declines over time. In this study, we aimed to deepen our understanding of disengagement in a mobile JIT intervention system. As a case study, we conducted a user study with college students (n = 54) for eight weeks to understand how disengagement appears over time and what factors influence user disengagement. Our findings reveal that personal traits, such as boredom proneness and self-control issues, are closely related to disengagement, with key factors including 1) boredom and habituation related to repetitive and monotonous JIT interventions, 2) inopportune alarm, 3) distrust for the JIT feedback mechanism, and 4) a lack of motivation due to low rewards. We provide theoretical and practical design guidelines for follow-up studies on JIT intervention system design.

BackgroundChanging lifestyle patterns over the last decades have seen growing numbers of people in Asia affected by non-communicable diseases and common mental health disorders, including diabetes, cancer, and/or depression. Interventions targeting healthy lifestyle behaviours through mobile technologies, including new approaches such as chatbots, may be an effective, low-cost approach to prevent these conditions. To ensure uptake and engagement with mobile health interventions, however, it is essential to understand the end-users’ perspectives on using such interventions. The aim of this study was to explore perceptions, barriers, and facilitators to the use of mobile health interventions for lifestyle behaviour change in Singapore.MethodsSix virtual focus group discussions were conducted with a total of 34 participants (mean ± SD; aged 45 ± 3.6 years; 64.7% females). Focus group recordings were transcribed verbatim and analysed using an inductive thematic analysis approach, followed by deductive mapping according to perceptions, barriers, facilitators, mixed factors, or strategies.ResultsFive themes were identified: (i) holistic wellbeing is central to healthy living (i.e., the importance of both physical and mental health); (ii) encouraging uptake of a mobile health intervention is influenced by factors such as incentives and government backing; (iii) trying out a mobile health intervention is one thing, sticking to it long term is another and there are key factors, such as personalisation and ease of use that influence sustained engagement with mobile health interventions; (iv) perceptions of chatbots as a tool to support healthy lifestyle behaviour are influenced by previous negative experiences with chatbots, which might hamper uptake; and (v) sharing health-related data is OK, but with conditions such as clarity on who will have access to the data, how it will be stored, and for what purpose it will be used.ConclusionsFindings highlight several factors that are relevant for the development and implementation of mobile health interventions in Singapore and other Asian countries. Recommendations include: (i) targeting holistic wellbeing, (ii) tailoring content to address environment-specific barriers, (iii) partnering with government and/or local (non-profit) institutions in the development and/or promotion of mobile health interventions, (iv) managing expectations regarding the use of incentives, and (iv) identifying potential alternatives or complementary approaches to the use of chatbots, particularly for mental health.

The use of mobile health (mHealth) interventions has risen dramatically over the past two decades. It is important to consider mHealth intervention research within the broader therapy outcome literature. Among other key findings, this broader literature suggests that common relationship factors such as empathy, positive regard, and genuineness may play a critical role in therapy effectiveness. These findings raise intriguing questions for mobile interventions. For example, can mobile interventions incorporate aspects of common factors to augment their efficacy? Will the absence of relationship-based common factors make mobile interventions less effective? This viewpoint paper addresses these questions as well as related issues such as how to operationalize relationship qualities in the context of a mobile intervention and whether common relationship factors apply to computers or computerized narrators. The paper concludes by outlining a future research agenda guided by theory and empirical studies.

The technological capabilities of mobile phones have made them a useful tool for delivering interventions, but additional research is needed to determine the mechanisms underlying the comparative effectiveness of mobile health interventions. This meta-analysis analyzes the relative effectiveness of mobile phone-based health interventions relative to comparison/control groups (e.g., eHealth interventions, standard of care, etc.), the utility of the theory of planned behavior in mobile phone-based health interventions, and the roles of various moderators. One hundred eighteen studies met inclusion criteria and contributed to an overall effect size of d = 0.27 (95% CI [.22, .32]). Findings indicate that mobile phone-based health interventions are significantly more effective than comparison/control conditions at improving health behaviors. Additionally, perceived behavioral control was a significant moderator providing some support for the usefulness of theory of planned behavior in mobile phone-based health interventions.

BackgroundPrenatal diagnostics is a crucial process for ensuring the health of both pregnant women and their fetuses. However, the participation rate of high-risk pregnant women in prenatal diagnostics is often influenced by various factors, including anxiety, depression, and lack of family support. In recent years, mobile health (mHealth) interventions have become an important tool in improving maternal health management, especially in terms of behavior change. The Behavior Change Wheel (BCW) theory and the Family Health Theory (FHT) have been applied in various health interventions, but there are limited studies focusing on prenatal diagnostics.ObjectiveThe study aims to evaluate the impact of a mobile health intervention based on the Behavior Change Wheel theory and Family Health Theory on prenatal diagnostic participation rates and pregnancy outcomes in high-risk pregnant women, while exploring the role of family member involvement in improving maternal psychological health and pregnancy outcomes.MethodsThe study outlines a single-blind, interventional, randomized controlled trial conducted at the Inner Mongolia Maternity and Child Health Care Hospital. A total of 58 high-risk pregnant women will be included and randomly assigned to either the intervention group (29 participants) or the standard care group (29 participants). The intervention group will receive a 12-week mHealth intervention via the WeChat platform, including health education, emotional support, behavioral feedback, and family member participation. The standard care group will receive standard prenatal care. Primary outcomes include prenatal diagnostic needs and pregnancy outcomes, while secondary outcomes include health knowledge, anxiety and depression levels, decision conflict, and other factors. This study uses IBM SPSS Statistics 24.0 for data analysis, employing descriptive statistics, normality tests, Mann–Whitney U, Wilcoxon, and chi-square tests.DiscussionThe study proposes that a mobile health intervention based on the Behavior Change Wheel theory and Family Health Theory may effectively increase prenatal diagnostic participation and improve the psychological health and pregnancy outcomes of high-risk pregnant women. The active participation and emotional support of family members are expected to be key components in achieving these improvements. This research provides new insights and evidence for the application of mHealth interventions in prenatal screening.

Mobile Health in Solid Organ Transplant: The Time Is Now.

Effectiveness of mobile health interventions on physical activity management in adults with hypertension: A systematic review and meta-analysis.

BackgroundMobile-cellular subscriptions have increased steadily over the past decade. The accessibility of SMS messages over existing mobile networks is high and has almost universal availability even on older and unsophisticated mobile phones and in geographic settings where wireless coverage is weak. There is intensive exploration of this inexpensive mobile telecommunication technology to improve health services and promote behavior change among vulnerable populations. However, a neglected area of research is the documentation and critical analysis of the formative research process required in the development and refinement of effective SMS messages.ObjectiveThe objective of this qualitative research study was to identify major factors that may impact on the effectiveness of evidence-based SMS messages designed to reduce health inequities in hypertension management in low resource settings, including Aboriginal populations in high-income countries and rural populations in low-income countries. Specifically, we were interested in uncovering the range of mediators that impact on appropriate message content transmission and, ultimately, on health behavior improvements in a range of these sociocultural settings.MethodsCollaborative qualitative research with Canadian Aboriginal and Tanzanian participants was conducted to deconstruct the content and transmission of evidence-based health information contained in SMS messages in the context of an international research project designed to address health inequalities in hypertension, and to develop a grounded theory of the major factors that mediate the effectiveness of this communication. We also examined the interrelationship of these mediators with the three essential conditions of the behavior system of the Behavioral Change Wheel model (capability, opportunity, and motivation) and cultural safety.ResultsFour focus groups with a total of 45 participants were conducted. Our grounded theory research revealed how discrepancies develop between the evidence-based text message created by researchers and the message received by the recipient in mobile health interventions. These discrepancies were primarily generated by six mediators of meaning in SMS messages: (1) negative or non-affirming framing of advocacies, (2) fear- or stress-inducing content, (3) oppressive or authoritarian content, (4) incongruity with cultural and traditional practices, (5) disconnect with the reality of the social determinants of health and the diversity of cultures within a population, and (6) lack of clarity and/or practicality of content. These 6 mediators of meaning provide the basis for sound strategies for message development because they impact directly on the target populations’ capability, opportunity, and motivation for behavior change.ConclusionsThe quality of text messages impacts significantly on the effectiveness of a mobile health intervention. Our research underscores the urgent need for interventions to incorporate and evaluate the quality of SMS messages and to examine the mediators of meaning within each targeted cultural and demographic group. Reporting on this aspect of mobile health intervention research will allow researchers to move away from the current black box of SMS text message development, thus improving the transparency of the process as well as the quality of the outcomes.

This study reviews the quality of evidence reported in mobile health intervention literature in the context of developing countries. A systematic search of renowned databases was conducted to find studies related to mobile health applications published between a period of 2013 and 2018. After a methodological screening, a total of 31 studies were included for data extraction and synthesis. The mobile health Evidence Reporting and Assessment checklist developed by the World Health Organization was then used to evaluate the rigor and completeness in evidence reporting. We report several important and interesting findings. First, there is a very low level of familiarity with the mobile health Evidence Reporting and Assessment checklist among the researchers and mobile health intervention designers from developing countries. Second, most studies do not adequately meet the essential criteria of evidence reporting mentioned in the mobile health Evidence Reporting and Assessment checklist. Third, there is a dearth of application of design science-based methods and theory-based frameworks in developing mobile health interventions. Fourth, most of the mobile health interventions are not ready for interoperability and to be integrated into the existing health information systems. Based on these findings, we recommend for robust and inclusive study plans to deliver highly evidence-based reports by mobile health intervention studies that are conducted in the context of developing countries.