mHealth Technology Research Articles

Personalized interventions for behaviour change: A scoping review of just-in-time adaptive interventions.

Examine the development, implementation and evaluation of just-in-time adaptive interventions (JITAIs) in behaviour change and evaluate the quality of intervention reporting. A scoping review of JITAIs incorporating mobile health (mHealth) technologies to improve health-related behaviours in adults. We searched MEDLINE, Embase and PsycINFO using terms related to JITAIs, mHealth, behaviour change and intervention methodology. Narrative analysis assessed theoretical foundations, real-time data capturing and processing methods, outcome evaluation and summarized JITAI efficacy. Quality of intervention reporting was assessed using the template for intervention description and replication (TIDieR) checklist. Sixty-two JITAIs across physical activity, sedentary behaviour, dietary behaviour, substance use, sexual behaviour, fluid intake, treatment adherence, social skills, gambling behaviour and self-management skills were included. The majority (71%) aimed to evaluate feasibility, acceptability and/or usability. Supporting evidence for JITAI development was identified in 46 studies, with 67% applying this to develop tailored intervention content. Over half (55%) relied solely on self-reported data for tailoring, and 13 studies used only passive monitoring data. While data processing methods were commonly reported, 44% did not specify their techniques. 89% of JITAI designs achieved full marks on the TIDieR checklist and provided sufficient details on JITAI components. Overall, JITAIs proved to be feasible, acceptable and user-friendly across behaviours and settings. Randomized trials showed tailored interventions were efficacious, though outcomes varied by behaviour. JITAIs offer a promising approach to developing personalized interventions, with their potential effects continuously growing. The recommended checklist emphasizes the importance of reporting transparency in establishing robust intervention designs.

Protocol for a co-design study for the development of a chronotherapeutic mobile health behaviour change intervention targeting light exposure among older adults

Through its wide-ranging effects on human physiology and behaviour, daily light exposure is an important environmental modulator of healthy ageing. Integrating mobile health (mHealth) technology with behaviour change strategies offers a promising approach to optimise light exposure and positively impact sleep, rest-wake cycles, cognitive function, and mood at scale. This study aims to develop the LightSPAN mHealth behaviour change intervention to optimise light exposure across the lifespan. Employing a co-design methodology, the study comprises two distinct workstreams. The first focuses on conceptualising the theoretical framework and implementation strategies through a comprehensive review of light exposure interventions, behaviour change theories, mHealth user personas, and recommendations for designing mHealth interventions for older adults. The second workstream centres on co-designing the intervention, involving consultation with community service providers and engagement with older adults at ageing community centres (≥60 years of age). Community service providers will be consulted through open-ended discussions (target n=5). Older adult participants (n=20) will engage in telephone interviews, focus group discussions and prototyping workshops to explore older adult participants’ characteristics, needs, preferences, and mHealth intervention design elements and co-design the LightSPAN mHealth behaviour change intervention. The insights generated in these co-design components will ensure that the intervention addresses the needs of its future users.

Feasibility, usability and acceptability of a lifestyle-integrated multicomponent exercise delivered via a mobile health platform in community-dwelling pre-frail older adults: a short-term, mixed-methods, prospective pilot study

BackgroundPre-frailty is a window of opportunity for frailty reversal and can be enhanced by multicomponent exercise. The Lifestyle-integrated Functional Exercise (LiFE) program may be a promising alternative to overcome traditional exercise barriers. The latest advancements in mobile health (mHealth) technology have enabled individuals to retain the advantages of supervised exercise training within group settings while providing exercise programs that can be accessed and completed at home. This study aims to assess the feasibility, acceptability, and primary efficacy of the PF-Life program, which is the Lifestyle-Integrated Functional Exercise program for Pre-Frail supported by an mHealth platform.MethodsSixteen pre-frail adults aged ≥ 65 years were recruited from five community health centers in Fuzhou, China. All participants were prescribed the PF-Life program by geriatricians using the mhealth platform (web-based portal). Participants engaged in the customized exercises program following in-app video instructions and feedback on the mhealth platform (smartphone application). Physical activity (PA) and sedentary behavior (SB) were registered daily through wearable devices. Study endpoints were feasibility (retention rate, compliance rate, adverse events), usability (system usability scale), acceptability (qualitative interviews), changes in physical function (timed up and go (TUG), handgrip strength (HGS), and 30-second chair rise tests), PA and SB.ResultsThe intervention was feasible, 88% of participants adhered completely to the study protocol, and 95% had completed at least 75% of the prescribed experimental duration. System usability was high (85 out of 100 best imaginable). Changes were observed from baseline to follow-up for total HGS (21.41 ± 6.38 vs. 24.12 ± 6.62 kg, P < 0.05, d = 0.714), TUG (8.23 ± 1.33 vs. 7.48 ± 2.01 s, P < 0.01, d = 1.647) and 30-second chair rise test (17.13 ± 4.3 vs. 20.04 ± 4.54 repetitions, P < 0.01, d = 0.94). In addition, SB decreased by a mean of 33 min/day (P < 0.01), and low physical activity increased by 31 min/day (P < 0.01). No adverse events occurred. The majority of participants found the PF-Life program to be straightforward, adaptable, and easily integrable into their daily routines.ConclusionsPreliminary studies have demonstrated that the PF-life program exhibits good compliance, safety, and usability for the pre-frail elderly population. Large-scale randomized controlled trials are required to ascertain its long-term effectiveness.

Rural-Urban Disparities in Mobile Health Application Ownership and Utilization Among Cancer Survivors

Objective: Mobile health applications (mHealth apps) can provide health care and health-promoting information while contributing to improving cancer survivors’ quality of life and health outcomes. However, little is known about the rural-urban distribution of mHealth app ownership and utilization. In this study, we explore the characteristics of cancer survivors who own and use mHealth apps and examine rural-urban disparities in mHealth app ownership and utilization among cancer survivors. Methods: We utilized data from the “Health Information National Trends Survey–Surveillance, Epidemiology, and End Results” pilot study, fielded among cancer survivors from 3 U.S. cancer registries (Iowa, New Mexico, and California) in 2021. Our sample included 942 cancer survivors who reported owning a smart device (a smartphone and/or a tablet computer). The analyses included computing weighted proportions and fitting a multivariable regression model. Results: Overall, 60.3% of cancer survivors reported using mHealth apps, and 16.9% resided in rural areas. Approximately 45.0% of rural cancer survivors reported utilizing mHealth apps (vs 63.5% of urban survivors). Regression analysis revealed that rural cancer survivors had 46.0% lower odds of owning and using mHealth apps compared with their urban counterparts (adjusted odds ratio = 0.54; 95% CI: 0.36, 0.80). Conclusions: Rural cancer survivors were less likely to own and use mHealth apps compared with urban survivors. Rural cancer survivors usually face structural and health care system-related barriers to health care access and affordability. Leveraging mHealth technology as a tool could potentially contribute to improving health care delivery for rural cancer survivors, and help address existing structural and informational barriers to access.

Exploring the Needs of People With Chronic Low Back Pain and Health Care Professionals for mHealth Devices to Support Self-Managed Physical Activity and Pain: User-Centered Design Approach.

Chronic low back pain (CLBP) is a major economic and social problem worldwide. Despite the variety of recommended treatments, long-term self-management of this condition is complex and requires the development of innovative interventions. Mobile health (mHealth) technologies hold great promise for the management of chronic pain, particularly to support physical activity. However, their implementation is challenged by a lack of user compliance and limited engagement, which may be due to insufficient consideration of the needs of potential users during development. This study aims to explore the needs of people with CLBP and health care professionals regarding mHealth technologies to support self-managed physical activity, and to delineate design recommendations based on identified needs. A participatory study was conducted using a 3-phase, user-centered design approach: needs investigation with a group of experts in a workshop (phase 1), needs exploration with end users in focus groups (phase 2), and validation of needs using Delphi questionnaires followed by the development of a set of recommendations (phase 3). A total of 121 people with CLBP, expert patients, health care professionals, rehabilitation researchers, and biomechanical engineers participated in this study. The results indicated how technology could help people with CLBP overcome their difficulties with managing physical activity. Specific needs were formulated concerning device objectives, expected strategies, functionalities, technical features, conditions of use, and potential facilitators and barriers to use. These needs were validated by consensus from the potential end users and translated into design recommendations. This study provides design recommendations for the development of an mHealth device specifically adapted for people with CLBP.

Remote Patient Monitoring Using Mobile Health Technology in Cancer Care and Research: Patients' Views and Preferences.

There is an increasing interest in studying the potential of mobile health (mHealth) technologies, such as smartphone apps and wearables, as monitoring tools for patients with cancer during or after their treatment. However, little research is dedicated to exploring the opinions and concerns of patients regarding the adoption of these technologies. This study aimed to gain insight into patients' perspectives and preferences for participating in mHealth-based monitoring in cancer care. A qualitative study comprising semistructured interviews was conducted in the Netherlands between April and June 2023. Participants were eligible if they were 18 years or older with a current or past diagnosis of cancer. The interview guide was developed on the basis of the technology acceptance model, with main themes being use, communication, trust, privacy, and expectations. Thirteen participants with urologic primary cancer were interviewed. Most patients had already some familiarity with the use of digital monitoring devices or wearables. Main barriers included persistent reminders of the illness, receiving notifications deemed unnecessary or unwanted, and the acknowledgment that mHealth technology does not serve as a substitute for human doctors. Conversely, patients recognized the potential for time-savings through the utilization of mHealth, viewed active monitoring as nonburdensome, considered mHealth a tool for reducing the communication threshold with their doctor, and expressed willingness to adopt such a platform if they perceived personal or societal relevance. This study has elucidated which factors are important for successful development of mHealth for patients with cancer. While both barriers and facilitators play a role, patients' attitudes were positive toward the implementation of remote digital monitoring, showing promising prospects for future research of mHealth in oncology.

MOBILE HEALTH: ECG MONITORING FOR ATRIAL FIBRILLATION DETECTION

This systematic review examines the use of mobile health (mHealth) technologies, such as smartphone apps and wearable devices, for detecting atrial fibrillation (AF). The review includes studies assessing the quality and performance of mobile apps and smartwatch algorithms, as well as the clinical validity of ECG measurement and photoplethysmography technology. Findings suggest diverse results, with some studies indicating promising sensitivity and specificity for AF detection. However, there is a need for further research to develop reliable algorithms for diagnosing and managing cardiovascular conditions using mHealth technologies.

Perspectives on barriers to traditional sources of sexual and reproductive health information and services: Are mHealth technologies the answer?

Background: In Ghana, several qualitative studies have explored users’ perspectives on conventional sources of sexual and reproductive health (SRH) information and factors which influence provision of and access in rural settings. However, there is a dearth of qualitative studies on healthcare provider (HCP) perspectives on factors that deter access to conventional sources of SRH information among young people in rural Ghana and innovative ways for addressing barriers. This study explored perspectives on barriers to traditional sources of SRH information and services and innovative ways of using mHealth technologies for addressing provision and access challenges among young people in rural Ghana. Methods: This study used a qualitative approach using in-depth interviews. Semi-structured in-depth interviews were conducted with HCPs in rural areas in three regions of Ghana between May and August 2021. Participants were selected from rural communities using the convenience snowball sampling and were interviewed via Zoom. The interviews explored the experiences and perceptions of HCPs on conventional SRH information and services and young people’s access to this information and services. The interviews were audio recorded and transcribed verbatim. Data were analysed thematically using NVivo software version 12, following the approach outlined by Braun and Clarke. Results: Twenty HCPs were interviewed for this study. The participants identified different sources of SRH information and services used by rural young people. Peers or friends, health facilities, health providers, and community settings were reported as the main services and sources of SRH information. Participants reported several barriers and challenges to the provision of and access to SRH information to young people, including socio-cultural norms, religious beliefs, unfriendly health facility environments, negative health providers’ attitudes, lack of privacy and confidentiality resulting in unfriendly youth SRH services, distance, and financial challenges due to costs of transportation which limits rural young people’s access to, and use of, SRH services. All the participants indicated that in addressing provision and access barriers, the use of mobile phones could be beneficial. Conclusion: This study highlights several barriers and challenges that deter provision of, and access to, SRH information and services for young people in rural Ghana. The findings indicate the use of innovative mobile health (mHealth) technologies may be one solution to some of the barriers and challenges.

2SpamH: A Two-Stage Pre-Processing Algorithm for Passively Sensed mHealth Data.

Recent advancements in mobile health (mHealth) technology and the ubiquity of wearable devices and smartphones have expanded a market for digital health and have emerged as innovative tools for data collection on individualized behavior. Heterogeneous levels of device usage across users and across days within a single user may result in different degrees of underestimation in passive sensing data, subsequently introducing biases if analyzed without addressing this issue. In this work, we propose an unsupervised 2-Stage Pre-processing Algorithm for Passively Sensed mHealth Data (2SpamH) algorithm that uses device usage variables to infer the quality of passive sensing data from mobile devices. This article provides a series of simulation studies to show the utility of the proposed algorithm compared to existing methods. Application to a real clinical dataset is also illustrated.

Innovative healthcare solutions for resource-limited settings expanding pharmaceutical care to remote populations

Access to essential healthcare and pharmaceutical services remains a significant challenge in resource-limited settings. This paper explores innovative strategies for expanding pharmaceutical care to remote populations, focusing on the integration of mobile health technologies and community-based interventions. Mobile health (mHealth) technologies, including telemedicine and mobile pharmacies, offer a cost-effective means of delivering healthcare services, enhancing access, and improving real-time monitoring. Community-based interventions, such as the deployment of community health workers, health education campaigns, and peer support groups, play a critical role in addressing healthcare disparities and improving health literacy and medication adherence. The paper also discusses the integration of pharmaceutical care models, emphasizing the importance of collaboration among healthcare providers, pharmacists, and community health workers. Future directions highlight emerging innovations like AI and blockchain technology, while policy recommendations emphasize the need for investment in healthcare infrastructure, professional training, and regulatory support. By leveraging these strategies and innovations, healthcare outcomes and equity in resource-limited settings can significantly improve.

Psychometric Properties of the TWente Engagement with Ehealth Technologies Scale (TWEETS) Among Patients with Hypertension in Italy.

Engagement with mobile health (mHealth) technologies among patients with hypertension is linked to reduced blood pressure and improved patient understanding of the condition. This study aimed to evaluate the psychometric properties (validity and reliability) of the TWente Engagement with Ehealth Technologies Scale (TWEETS) in an Italian cohort with hypertension. This study is the first attempt to evaluate the psychometric characteristics of the TWEETS in this population. The study was conducted in three phases. The first phase encompassed the translation and cultural adaptation of the TWEETS to the Italian setting. The second phase involved an expert panel evaluating the instrument's face and content validities. The third phase wasa cross-sectional study aiming to test construct validity and reliability. Adults diagnosed with hypertension were eligible for participation. Additional inclusion criteria included stable antihypertensive treatment for at least 2 weeks before enrolment and the provision of written informed consent. Patients were taught how to use two mHealth devices using the teach-back method. A total of 131 patients were enrolled. Exploratory and confirmatory factor analyses revealed that the TWEETS had a one-factor structure and a good level of fit. Cronbach's alpha coefficients suggested good internal consistency. The findings indicate that the TWEETS is a valuable tool for assessing the engagement of patients with hypertension with mHealth devices. Further assessment is needed in various cohorts to confirm the psychometric equivalence of the construct across different groups with hypertension.

Exploring vocal biomarkers as non-invasive fine-tuning assays of cardiovascular health: heart failure model

Abstract Background Mobile health (mHealth) technologies offer a promising avenue for non-invasive heart failure monitoring through vocal biomarkers. The relationship between feature changes in anonymous and standardized voice recordings of heart failure patients and the NYHA scores of the same patients is assessed, aiming to identify vocal biomarkers as delicate indicators of chronic noncommunicable disease progression and/ or fluctuation. Methods In a cardiology outpatient setting, 55 chronic heart failure patients provided voice recordings via a mobile app, performing specific vocal tasks prospectively. We analyzed waveforms visually via Mel spectrograms and extracting features by audio processing, focusing on chroma centroids and tonnetz measurements across 147 clinical and laboratory parameters (Mean NYHA: 2.62, SD: 0.56). Applying Ordinary Least Squares (OLS) test, we assessed the relevance of spectral bandwidth mean (0.04), spectral bandwidth std (0.00), spectral roll-off std (0.011) between NYHA scores, given each p-score &amp;lt; 0.05. Results 147 voice recordings taken from 55 patients were analyzed to examine whether there were any correlations between changes in the voice recordings and NYHA scores. OLS test underscored the significance of spectral bandwidth mean (0.04), spectral bandwidth std (0.00), spectral roll-off std (0.011) between NYHA scores with p-value &amp;lt; 0.05. These findings show the potential role of multiple vocal features in reflecting heart failure progression and/or fluctuation. Analysis based on the clinical status progression from NYHA 2 to NYHA 3 over time showed notable changes in chroma centroids (mean = 0.006, std = 0.174, skew = 0.179, kurtosis = 0.205) and tonnetz (mean = 0.023, std = 0.131, skew = 0.023, kurtosis = 4.247). Conclusion This investigation highlights vocal biomarkers' potential in heart failure management, offering insights into non-invasive monitoring techniques and shows the importance of standardised recording procedures and patient engagement for data integrity. Future directions include quantifying vocal changes' correlation with clinical status and integrating additional parameters (e.g., edema, weight) to enhance predictive models for personalised care.Vocal features according to NYHA scores

Public Perceptions and Engagement in mHealth Across Eight European Countries

Abstract Background Mobile health technologies have the potential to revolutionize healthcare delivery and patient engagement. This study explores public attitudes toward health app usage and data sharing across eight European countries, addressing a significant gap in understanding the public’s perspective on mHealth adoption. Methods A cross-sectional survey was conducted involving 6,581 participants from Italy, the Netherlands, France, Germany, Spain, Poland, Romania, and Hungary. The survey assessed current health app usage, future interest, willingness to share health data, and concerns about data privacy and security. Results 21.87% of respondents currently use health apps, with 42.71% expressing interest in future use. Regarding data sharing, 52.82% are willing to share health data with healthcare providers, and 25.48% would share data with research institutions. However, 53.18% fear unauthorized use or hacking of their health data. Significant generational and geographical differences in mHealth engagement were observed, with older generations showing higher willingness to adopt health apps OR 1.22 (CI 1.03 - 1.46) for Baby Boomers, OR 1.45 (CI 0.97 - 2.16) for Silent Generation. Education level emerged as a crucial factor, with tertiary-educated individuals more likely to use health apps (OR 1.41 CI 1.24 - 1.58) and demand transparency (OR 1.61 CI 1.45 -1.78). Conclusions The findings underscore the need for targeted strategies to enhance digital literacy, ensure data privacy, and promote equitable access to mHealth technologies across Europe. Policymakers and healthcare stakeholders should prioritize these areas to foster greater public trust and engagement in mHealth, ultimately improving health outcomes and patient care. Key messages • Public attitudes toward mHealth vary significantly across generations, countries, and education levels in Europe. • Addressing data privacy concerns and enhancing digital literacy are crucial for widespread mHealth adoption.

Impact of an mHealth intervention on parents' emotional health and on the neurodevelopment of high-risk infants.

We assess the prenatal and postnatal effect of the High-Risk Pregnancy and Baby Parenting programme, which is complemented with two mHealth (app-based) resources. The GLM Repeated Measures Model technique was used to explore differences in the emotional health of the participants and in their infants' neurodevelopment, comparing programme versus usual care groups, composed of 150 and 195 participants, respectively. The mothers presented lower levels of depression (mean difference 1.74, p = 0.04, 95% CI 0.07, 3.40) and higher levels of resilience (mean difference 4.09, p = 0.004, 95% CI 1.40, 6.78). For the fathers, positive effects on resilience were recorded (p < 0.001). A positive treatment effect was perceived in the infants' cognitive (p = 0.014), language (p < 0.001) and motor (p = 0.006) development. These findings suggest application of the programme can benefit maternal emotional health and infant neurodevelopment. M-Health technology could make this programme more accessible.

Comprehensive synthesis of mHealth interventions in psychiatry: insights from systematic, scoping, narrative reviews and content analysis.

Mobile health (mHealth) technologies, including smartphone apps and wearables, have improved health care by providing innovative solutions for monitoring, education and treatment, particularly in mental health. This review synthesises findings from a series of reviews on mHealth interventions in psychiatry. Publications were systematically searched in PubMed, MEDLINE, PsycINFO, ScienceDirect, Scopus, Web of Science and Cochrane Library. Out of 2147 records, 111 studies from 2014 to 2024 focusing on anxiety and depression were included. These studies highlight the effectiveness of mHealth interventions in reducing symptoms through cognitive-behavioural therapy, mindfulness and psychoeducation, benefitting adolescents, perinatal women and marginalised groups. Additionally, mHealth shows promise in managing substance use disorders and severe mental illnesses like schizophrenia, bipolar disorder and psychosis. Despite positive outcomes, challenges such as data privacy, user engagement and healthcare integration persist. Further robust trials and evidence-based research are needed to validate the efficacy of mHealth technologies.

Exploratory analysis of blood alcohol concentration-related technology use and drinking outcomes among young adults.

Mobile health (mHealth) technology use may reduce alcohol use and related negative consequences; however, little is known about its efficacy without prompting from researchers or pay-per-use. This exploratory analysis assessed relationships between mHealth technology use frequency and alcohol-use outcomes. Young adults who drink heavily (N = 97, Mage = 23, 51% male, 64% non-Hispanic White, Mdrinks/week = 21) had the option to use three mHealth technologies (breathalyzer device/app, blood alcohol content estimator app, drink counting via text message) while drinking for 2 weeks. Relationships between alcohol-related outcomes and any, multiple, and specific mHealth technology use across study days and drinking days were evaluated via bivariate correlations and multiple regressions. Participants used one or more mHealth technologies on approximately 68% of drinking days (33% of field days), with multiple technologies used on 34% of drinking days. Bivariate correlations revealed that a higher percentage of study days with any mHealth technology use was related to higher mean weekly drinks. However, a higher percentage of drinking days with any mHealth technology use was related to lower mean weekly drinks, percent of heavy and high-intensity drinking days, and negative consequences. There were several significant, inverse correlations between alcohol variables and using the mHealth technologies that provided personalized feedback. Multiple regression analyses (holding sex and baseline alcohol variables constant) indicated that a higher percentage of drinking days with any mHealth technology use was related to lower mean weekly drinks and lower percentage of heavy drinking days. Using mHealth technologies to moderate drinking without direct prompting from the research team or per-use incentives was related to less overall alcohol use and heavy drinking. This indicates potential real-world engagement with mHealth apps to assist with in-the-moment drinking. Normalizing mHealth technology use during drinking could help curb the public health crisis around harmful alcohol use in young adult populations.

Acceptance and use of mobile health technology in post-abortion care

BackgroundAbortion and its complications have always been associated with challenges such as the lack of awareness, high cost of receiving in-person services, lack of access to the skilled healthcare workers, distance from healthcare centers in remote areas, and cultural sensitivities. Therefore, the use of mobile health technology in post-abortion care has been suggested. This study aimed to investigate factors influencing the acceptance and use of mhealth technology in post-abortion care.MethodA mixed-methods study was completed in 2023. Initially, a literature review was conducted. Then, a five-point Likert-scale questionnaire was designed based on the results of the literature review. The research participants were gynecologists (n = 24), midwives (n = 38), and women who had experience of abortion (n = 183). Data were analyzed using descriptive and inferential statistics.ResultsThe findings revealed that the participants had different opinions about the importance of motivating and inhibiting factors which included individual, technical, economic, organizational, and ethico-legal aspects. It seems that the individual, organizational, economic, and ethico-legal motivating factors as well as the ethico-legal inhibiting factors were more important than other factors and had higher mean values. In addition, there was a statistically significant difference between the mean values of gynecologists and patients regarding the individual motivating (P = 0.014) and technical inhibiting factors (P = 0.016). The gynecologists’ opinions regarding the technical motivating factors were also significantly different from midwives (P = 0.044) and patients (P = 0.010).ConclusionMultiple factors may influence the acceptance and use of mhealth technology in post-abortion care. Therefore, mhealth service developers must consider these factors to improve the quality of services and increase technology adoption. This will lead to saving costs, improving health, reducing abortion complications, and ultimately improving quality of life for women. However, further research in patient engagement and health interventions tailored to diverse cultural contexts are recommended.

Abstract B117: HT Helper Study: A phone application + patient navigation to improve medication adherence among Latina breast cancer patients experiencing social determinants of health

Abstract Background: Hormone therapy (HT) is highly effective for nearly all breast cancer patients with hormone receptor-positive tumors, which are about 80% of all breast cancer diagnoses. Long-term use of HT reduces cancer recurrence rates and cuts the risk of mortality nearly in half during the second decade after diagnosis. Despite proven benefits, 33% of women who are prescribed HT do not take it as prescribed by their doctor (&amp;lt;80% take their daily dosage). Latina patients are disproportionately affected by Social Determinants of Health (SDoH) that keep them from adhering to HT and are at higher risk of breast cancer recurrence and mortality. Objective: The goal of this 4-year randomized controlled study is to assess the effectiveness of the existing bilingual, culturally tailored, interactive HT Helper App, in combination with patient navigation (PN), on improving adherence to HT among Latina breast cancer patients experiencing SDoH barriers, i.e., income, health insurance, education, health literacy, and language, that impacts their medication adherence. This theory-based intervention will increase patient education, enhance self-efficacy, facilitate communication with the medical team and coordination of resources to address SDoH barriers and help patients develop self-care skills for optimal adherence to HT, ensuring patients the most equitable treatment outcomes possible, including improvement in quality of life, survival, and life expectancy. Study Design. The proposed study involves a parallel 3-group randomized controlled trial with 5-time assessments (baseline, 3, 6, 12, and 18 months) and will enroll 159 breast cancer patients who are prescribed HT and are attending the breast clinic at the Mays Cancer Center at UT Health San Antonio. Intervention components are based on Social Cognitive Theory and elements of Motivational Interviewing. Methods: We will compare the effectiveness of 3 groups on HT adherence: 1) the HT Helper App + PN group vs. the PN alone group vs. the usual care group, and will assess the effect of each study condition on patient self-efficacy to identify side effects, use self-care to manage side effects, and communicate with the medical team. We hypothesize that the HT Helper App + PN and the PN alone groups will have greater rates of HT adherence and higher patient self-efficacy than the usual care group, with the HT Helper App + PN achieving better results than both PN alone and the usual care groups. Conclusion: This proposed multi-level intervention involving a unique combination of mHealth technology + PN has the potential to improve adherence to HT by addressing SDoH and promote equitable breast cancer outcomes, including reduced recurrence and improved quality of life, overall survival and life expectancy among underserved Latina patients. The anticipated outcome is a scalable, evidence-based, and easily disseminated intervention with potentially broad use to patients using oral anticancer medications. Citation Format: Patricia Chalela, Vivian Cortez, Sandra Sivak, Armida Flores, Martha De La Mora, Zully Garcia, Byeongyeob Choi, Edgar Muñoz, Qurathul Ahmed, Audrey Cordova, Maria I Sung-Cuadrado, Asra Aslam, Cliff Despres, Alyssa Gonzales, Virginia G Kaklamani, Kate I. Lathrop, Marcela Mazo Canola, Devasena Inupakutika, David Akopian, Amelie G. Ramirez. HT Helper Study: A phone application + patient navigation to improve medication adherence among Latina breast cancer patients experiencing social determinants of health [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B117.

Bridge Nodes Linking Depression and Medication Taking Self-Efficacy Dimensions Among Persons With HIV: A Secondary Data Analysis.

Depression and low medication taking self-efficacy are among the most important mechanisms contributing to poor adherence to treatment and care for persons with HIV (PWH). While the overall negative relationship between depression and medication taking self-efficacy has been well established, little is known on the precise pathways linking depression and medication taking self-efficacy. Thus, it is critical to identify a specific item of depression and medication taking self-efficacy that derives the overall negative relationship. The current study is a secondary data analysis using the baseline data from a randomized controlled trial that aims to support PWH to self-manage antiretroviral therapy regimens via mHealth technology and community health workers to monitor their adherence using a self-management app. A total of 282 participants were included. The machine-learning based network analysis was conducted to explore the structure of the depression and medication taking self-efficacy network and to identify bridge nodes between depression and medication taking self-efficacy. Our study identified difficulty concentrating on things and confidence to stick to treatment schedule when not feeling well are important bridge nodes connecting the network of depression and medication taking self-efficacy. Future studies should focus on developing interventions that would target the bridge pathway and examine their effectiveness in reducing depression and increasing medication taking self-efficacy.

Disabled Individuals’ Negative Perceptions of Mobile Health Applications: Design Guidance for HFE Practitioners

Disabled individuals experience significant inequities in healthcare access, healthcare quality, social determinants of health, and health outcomes compared to non-disabled individuals. By including people with disabilities in the co-design of mobile health (MHealth) applications, we gain valuable insights to improve alignment between users’ needs and MHealth technologies. Through a secondary analysis of mixed-methods data, this paper investigates negative perceptions of disabled individuals regarding MHealth applications to inform MHealth application design guidance for human factors practitioners. Fifty participants with physical, cognitive, sensory, and/or mental health-related disabilities interacted with three MHealth applications during task analysis sessions, revealing concerns about data security, data privacy, and unnecessary patient work. Recommendations include clear articulation of security measures, clarifications that patient profiles are not publicly available, and simplified data entry processes. Implementing these recommendations may enhance the accessibility and usefulness of MHealth applications, promoting healthcare access for a broader range of individuals.