Designing and Personalising Hybrid Health Explanations for Lay Users

Despite the acknowledgment that the perception of explanations may vary considerably between end-users, explainable recommender systems (RS) have traditionally followed a one-size-fits-all model, whereby the same explanation level of detail is provided to each user, without taking into consideration individual user's context, i.e., goals and personal characteristics. To fill this research gap, we aim in this paper at a shift from a one-size-fits-all to a personalized approach to explainable recommendation by giving users agency in deciding which explanation they would like to see. We developed a transparent Recommendation and Interest Modeling Application (RIMA) that provides on-demand personalized explanations of the recommendations, with three levels of detail (basic, intermediate, advanced) to meet the demands of different types of end-users. We conducted a within-subject study (N=31) to investigate the relationship between user's personal characteristics and the explanation level of detail, and the effects of these two variables on the perception of the explainable RS with regard to different explanation goals. Our results show that the perception of explainable RS with different levels of detail is affected to different degrees by the explanation goal and user type. Consequently, we suggested some theoretical and design guidelines to support the systematic design of explanatory interfaces in RS tailored to the user's context.

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.

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

The aging population places increasing demands on our healthcare system. Mobile health offers the potential to reduce this burden. The aim of this systematic review is to thematically synthesize qualitative evidence of older adults' user engagement toward mobile health, and to generate relevant recommendations for intervention developers. A systematic literature search was performed in Medline, Embase, and Web of Science electronic databases from inception until February 2021. Papers on qualitative and mixed-methods studies that investigated older adults' user engagement with a mobile health intervention were included. Relevant data were extracted and analyzed using thematic analysis. The Critical Appraisal Skills Program Qualitative Checklist was used to assess the quality of the included studies. Thirty-two articles were deemed eligible for inclusion in the review. Three overarching analytical themes emerged from the 25 descriptive themes generated by the line-by-line coding: the limited capabilities, the prerequisite of motivation, and the importance of social support. Successful development and implementation of future mobile health intervention for older adults will be challenging given the physical and psychological limitations and motivational barriers that older adults experience. Design adaptations and well-thought-out blended alternatives (i.e., combining mobile health with face-to-face support) might be potential solutions to improve older adults' user engagement with mobile health interventions.

An increasing number of recommender systems enable conversational interaction to enhance the system’s overall user experience (UX). However, it is unclear what qualities of a conversational recommender system (CRS) are essential to determine the success of a CRS. This paper presents a model to capture the key qualities of conversational recommender systems and their related user experience aspects. Our model incorporates the characteristics of conversations (such as adaptability, understanding, response quality, rapport, humanness, etc.) in four major user experience dimensions of the recommender system: User Perceived Qualities, User Belief, User Attitudes, and Behavioral Intentions. Following the psychometric modeling method, we validate the combined metrics using the data collected from an online user study of a conversational music recommender system. The user study results 1) support the consistency, validity, and reliability of the model that identifies seven key qualities of a CRS; and 2) reveal how conversation constructs interact with recommendation constructs to influence the overall user experience of a CRS. We believe that the key qualities identified in the model help practitioners design and evaluate conversational recommender systems.

The high prevalence among elderly individuals and potential adverse impact on their overall life quality make chronic musculoskeletal pain a significant public health concern. Chronic musculoskeletal pain is an important cause of self-medication, which must be addressed to avoid various side effects and improve elderly health. This study aimed to determine the prevalence of chronic musculoskeletal pain and its associated factors among individuals (age ≥60 years) in rural West Bengal and explore their perspectives and perceived barriers regarding pain and its management. This mixed-method study was conducted in rural West Bengal from December 2021 to June 2022. The quantitative strand was conducted by interviewing 255 elderly participants (age ≥60 years) using a structured questionnaire. The qualitative strand was conducted via in-depth interviews of 10 patients with chronic pain. Quantitative data were analyzed using SPSS version 16, and chronic pain-related factors were analyzed using logistic regression models. Qualitative data were analyzed thematically. Among the participants, 56.8% reported chronic musculoskeletal pain. The most frequently affected site was the knee joint. Comorbidity (adjusted odds ratio [aOR]=7.47, 95% confidence interval [CI]=3.2-17.5), age (aOR=5.16, 95% CI=2.2-13.5), depression (aOR=2.96, 95% CI=1.2-6.7) and over-the-counter drug usage (aOR=2.51, 95% CI=1.1-6.4) were significantly associated with chronic pain. Analgesic dependency, lack of motivation to adopt lifestyle modifications, lack of knowledge on analgesic side effects were considered pain management barriers. Managing comorbidities, providing mental support, generating awareness of analgesic side effects, strengthening healthcare facilities should be prioritized for holistic chronic musculoskeletal pain management.

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.

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

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.

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.

Introduction Mobile health has a promising future in the healthcare system in most developed countries. China’s rapidly developing mobile technology infrastructure offers an unprecedented opportunity for wide adoption of mobile health interventions in the delivery of effective and timely healthcare services. However, there is little data on the current extent of the mobile health landscape in China. The aim of this study was to systematically review the existing mobile health initiatives in China, characterise the technology used, disease categories targeted, location of the end user (urban versus rural), and examine the potential effects of mobile health on health system strengthening in China. Furthermore, we identified gaps in development and evaluation of the effectiveness of mobile health interventions. Methods A systematic review of the literature published from 18 December 2015 – 3 April 2019 was conducted and yielded 2863 articles from English and Chinese retrieval database and trial registries, including PubMed, EMBASE, China National Knowledge of Infrastructure and World Health Organization International Clinical Trials Registry Platform. Studies were included if they used mobile health to support patient healthcare outcomes. Results A total of 1129 full-text articles were assessed and 338 were included in this study. The review found that most studies targeted client education and behaviour change via applications (apps) (65.4%), including WeChat, and text messaging (short text messages) (19.8%) to improve patient medical treatment outcomes such as compliance and appointment reminders. The most common disease-specific mobile health interventions focused primarily on chronic disease management and behaviour change in cardiology (13.3%), endocrinology/diabetes (12.1%), behavioural health (11.8%), oncology (11.2%) and neurology (6.8%). The mobile health interventions related to nutrition (0.6%) and chronic respiratory diseases (1.6%) are underrepresented in mobile health in comparison to the burden of disease in China. The majority (90.0%) of the mobile health interventions were conducted exclusively in urban areas, with few opportunities reaching rural populations. Conclusions Overall, mobile health has a promising future in China, with recent rapid growth in initiatives. The majority are focused on education and behaviour change in the realm of chronic diseases and target patients in urban areas. The imbalance in mobile health between the urban and rural areas, as well as between population disease spectrum and health service delivery, pose substantial dilemmas. However, mobile health may be redirected to correct this imbalance, possibly improving access to healthcare services, and filling the gaps in order to improve health equity for the underserved populations in China.

BackgroundSubstantial recent research examines the efficacy of many types of complementary and alternative (CAM) therapies. However, outcomes associated with the "real-world" use of CAM has been largely overlooked, despite calls for CAM therapies to be studied in the manner in which they are practiced. Americans seek CAM treatments far more often for chronic musculoskeletal pain (CMP) than for any other condition. Among CAM treatments for CMP, acupuncture and chiropractic (A/C) care are among those with the highest acceptance by physician groups and the best evidence to support their use. Further, recent alarming increases in delivery of opioid treatment and surgical interventions for chronic pain--despite their high costs, potential adverse effects, and modest efficacy--suggests the need to evaluate real world outcomes associated with promising non-pharmacological/non-surgical CAM treatments for CMP, which are often well accepted by patients and increasingly used in the community.Methods/DesignThis multi-phase, mixed methods study will: (1) conduct a retrospective study using information from electronic medical records (EMRs) of a large HMO to identify unique clusters of patients with CMP (e.g., those with differing demographics, histories of pain condition, use of allopathic and CAM health services, and comorbidity profiles) that may be associated with different propensities for A/C utilization and/or differential outcomes associated with such care; (2) use qualitative interviews to explore allopathic providers' recommendations for A/C and patients' decisions to pursue and retain CAM care; and (3) prospectively evaluate health services/costs and broader clinical and functional outcomes associated with the receipt of A/C relative to carefully matched comparison participants receiving traditional CMP services. Sensitivity analyses will compare methods relying solely on EMR-derived data versus analyses supplementing EMR data with conventionally collected patient and clinician data.DiscussionSuccessful completion of these aggregate aims will provide an evaluation of outcomes associated with the real-world use of A/C services. The trio of retrospective, qualitative, and prospective study will also provide a clearer understanding of the decision-making processes behind the use of A/C for CMP and a transportable methodology that can be applied to other health care settings, CAM treatments, and clinical populations.Trial registrationClinicalTrials.gov: NCT01345409

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.

Advances in mobile computing offer the potential to change when, where, and how health interventions are delivered. Rather than relying on occasional in-clinic interactions, mobile health (mHealth) interventions may overcome constraints due to limited clinician time, poor patient adherence, and inability to provide meaningful interventions at the most appropriate time. Technological capability, however, does not equate with user acceptance and adoption. How then can we ensure that mobile technologies for behavior change meet the needs of their target audience? In this paper, we argue that overcoming acceptance and adoption barriers requires interdisciplinary collaborations, bringing together not only technologists and health researchers but also human-computer interaction (HCI) experts. We discuss the value of human-computer interaction research to the nascent field of mHealth and demonstrate how research from HCI can offer complementary insights on the creation of mobile health interventions. We conclude with a discussion of barriers to interdisciplinary collaborations in mobile health and suggest ways to overcome them.

Antenatal care (ANC) is essential in maternal and child health since it provides care to pregnant women from conception through to labour in order to ensure a safe pregnancy and childbirth. In recent years, mobile health (mHealth) interventions have emerged as a promising solution to improve maternal and child health outcomes in low- and middle-income countries (LMICs). The present study aimed to conduct a systematic review and meta-analysis of trials to evaluate the effectiveness of mHealth interventions to monitor prenatal care among pregnant women in LMICs. A systematic literature review was conducted using the databases CINHAL, Embase, MEDLINE, and PsycINFO on the effectiveness of mHealth interventions in monitoring the antenatal care of pregnant women. The study selection, data extraction of the included articles, and quality appraisal were assessed. Our study included six studies considering 7886 participants. All articles were from low- and middle-income countries (LMICs). Antenatal mothers who used a mobile health intervention were more likely (RR = 1.66, 95%CI = 1.07–2.58, I2 = 98%) to attend ANC check-ups when compared with the women who did not use any mobile health applications or did not receive any short message services. mHealth technologies are being utilised more and more to increase care accessibility and improve maternal and fetal health. Policymakers should prioritise the integration of mHealth interventions into maternal healthcare services in LMICs, ensuring that they are cost-effective, accessible, and sustainable and that healthcare workers are trained to deliver these interventions effectively.