Use Of mHealth Technologies Research Articles

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.

Use of mHealth Technologies to Increase Sleep Quality among Older Adults: A Scoping Review.

Sleep disorders increase with age and are known risk factors for several mental and physical diseases. They also significantly contribute to a lower quality of life. Nonpharmaceutical approaches, such as cognitive behavioral therapy for insomnia, sleep hygiene advice, relaxation exercises, and physical activity programs, can be delivered directly to patients via mHealth technologies, thereby increasing the accessibility of such interventions and reducing health care-related costs. This scoping review aims to evaluate the effectiveness of mHealth interventions for improving sleep quality among older adults. Published studies in the last 10 years (2013-2023) were identified by searching electronic medical databases (PubMed, PsycINFO, CINAHL, and Scopus) in July 2023 and were independently reviewed by two different authors. The analysis of the data was performed in 2023. The research retrieved 693 records; after duplicates were removed, 524 articles were screened based on their title and abstract, and 28 of them were assessed in full text. A total of 23 studies were excluded because they did not meet the inclusion criteria in terms of population age (60 years or over) or type of intervention (mHealth-based) or because they addressed secondary insomnia. A total of five studies were included in this review, and all of them reported improvements in subjective sleep quality after the application of the mHealth interventions. Two studies also conducted objective assessments of sleep outcomes using actigraphy, reporting improvements only in some of the variables considered. Despite the limited number of available studies, these results are promising and encourage further research.

Using Mobile Health (mHealth) Applications to Improve Access to Healthcare in Afghanistan

This study investigates the utilization of mobile health (mHealth) applications to improve healthcare access in Afghanistan. The research employs a mixed-methods approach, combining qualitative interviews and quantitative surveys with healthcare providers, patients, technology experts, and health administrators at Sehat Hospital in Kabul. Through thematic analysis of interview data and descriptive and inferential analysis of survey responses, the study explores the current landscape of mHealth applications, including their availability, features, usage patterns, and perceived impact on healthcare delivery and patient outcomes. The findings reveal diverse perceptions among participants regarding the accessibility, relevance, and effectiveness of mHealth interventions in Afghanistan. Challenges related to security, cultural adaptation, and user awareness are identified, alongside opportunities for enhancing the design and implementation of mHealth solutions. The study contributes valuable insights into the potential of mHealth applications to address healthcare disparities and improve patient outcomes in resource-constrained settings like Afghanistan. Recommendations for policymakers, healthcare providers, and technology developers are provided to optimize the use of mHealth technologies and maximize their impact on healthcare delivery. Overall, this research underscores the importance of contextually relevant and user-centered approaches in leveraging technology to advance healthcare access and quality in Afghanistan.

P114 Promoting physical activity using mobile health technology in people living with Rheumatoid Arthritis: MOTIVATE RA

Abstract Background/Aims People living with rheumatoid arthritis (RA) tend to be less active than the general population which may be due to RA associated musculoskeletal pain, stiffness and fatigue. The health benefits of physical activity (PA) are widely recognised in the general population and studies in RA have also highlighted improvement in RA associated symptoms. However, encouraging increased PA in people living with RA is challenging and adherence to PA is usually low. Mobile health (mHealth) technology (i.e., fitness watches and apps) may provide an effective and economical solution to promoting PA in this high-risk population. The aims of the current study were to assess whether use of mHealth technology in RA i) increases PA levels and ii) reduces RA disease activity. Methods People with RA were randomised to either the MOTIVATE (mHealth intervention) or conventional care (CC) groups. The CC group were provided with online educational materials, as provided in routine care (e.g., PA information leaflets), to increase PA whereas the MOTIVATE group were provided with a personalised, progressive walking programme delivered via mHealth technology with ongoing, individualised support throughout the 12-week intervention. All participants received a self-testing kit, via mail, at baseline (week 0) and post-intervention (12 weeks). Measures included anthropometrics, blood pressure, PA monitoring, health questionnaires and all were requested to self-report RA disease activity using RADAI-5. Change data between weeks 0 and 12 were compared between groups using One-Way ANCOVA, controlling for baseline, and reported as mean difference (95% CI). Results Of 50 participants, 25 were randomised to the MOTIVATE group (age 50±11years; BMI 29±7kg/m2; females n=23), and 25 to CC (n=25, age 50±11years; BMI 26±6 kg/m2; females n=24). An increase in moderate-to-vigorous PA was observed in the MOTIVATE group, compared to a decrease in CC [81min (1, 160) vs. -35min (-123, 53); P=0.09)]. This was accompanied by an increase in steps per day in the MOTIVATE group, and a decrease in CC [763 (-432, 1957) vs. -76 (-1267, 1115); P=0.40]. A reduction in PHQ-9 depression score was evident in the MOTIVATE group whilst CC were unchanged [-2 (-2, -3) vs. 0 (-2, 0); P=0.07]. RADAI-5 decreased in the MOTIVATE group and stayed the same in CC [-2 (-2, 0) vs. 0(-2, 0), P=0.27]. Conclusion These findings identify the potential effectiveness of an mHealth PA programme to increase PA levels in people living with RA. Use of remote PA monitoring, with support from exercise specialists, may be an effective strategy to improve engagement in exercise and PA in the RA population. Data is suggestive this could improve RA related symptoms, although we did not observe statistical significance. Disclosure D.J. Bannell: Grants/research support; Research grant from the Aintree Arthritis Trust. M. France-Ratcliffe: None. K.L. Hesketh: None. M. Cocks: None. N. Goodson: None. C. Taylor: None. T. Pecanha: None. H. Jones: None. D.A. Low: None. V.S. Sprung: None.

Feasibility and acceptability of measuring prenatal stress in daily life using smartphone-based ecological momentary assessment and wearable physiological monitors.

High levels of stress during pregnancy can have lasting effects on maternal and offspring health, which disproportionately impacts families facing financial strain, systemic racism, and other forms of social oppression. Developing ways to monitor daily life stress during pregnancy is important for reducing stress-related health disparities. We evaluated the feasibility and acceptability of using mobile health (mHealth) technology (i.e., wearable biosensors, smartphone-based ecological momentary assessment) to measure prenatal stress in daily life. Fifty pregnant women (67% receiving public assistance; 70% Black, 6% Multiracial, 24% White) completed 10 days of ambulatory assessment, in which they answered smartphone-based surveys six times a day and wore a chest-band device (movisens EcgMove4) to monitor their heart rate, heart rate variability, and activity level. Feasibility and acceptability were evaluated using behavioral meta-data and participant feedback. Findings supported the feasibility and acceptability of mHealth methods: Participants answered approximately 75% of the surveys per day and wore the device for approximately 10hours per day. Perceived burden was low. Notably, participants with higher reported stressors and financial strain reported lower burden associated with the protocol than participants with fewer life stressors, highlighting the feasibility of mHealth technology for monitoring prenatal stress among pregnant populations living with higher levels of contextual stressors. Findings support the use of mHealth technology to measure prenatal stress in real-world, daily life settings, which shows promise for informing scalable, technology-assisted interventions that may help to reduce health disparities by enabling more accessible and comprehensive care during pregnancy.

Mobile Technologies for Monitoring Sleep Time: A Systematic Search of App Stores in Brazil

Abstract Introduction Decreased sleep time is detrimental to physical and mental health, exerting negative impacts on daily functioning and quality of life. Mobile health (mHealth) applications can be useful for improving sleep quality. Objective To perform a systematic search of mHealth applications for monitoring sleep time at Brazilian online stores and evaluate the selected applications in terms of engagement, functionality, aesthetics, and quality of information. Methods A systematic search was performed at the Google Play Store and the App Store developed or updated between 2020 and 2022. The mobile app rating scale (MARS) was used to assess their quality. The characteristics and information of these applications were presented. Data were analyzed descriptively. Results Among the 2,264 relevant mHealth apps identified, 11 were eligible for inclusion. There was one app that offered only sleep time recordings, three offered sleep recordings and educational content, three monitored sleep time with audiovisual resources, two offered sleep time recordings with a focus on monitoring snoring, and two offered sleep time monitoring with individual content customizations. The apps scored fair on MARS, with a mean of 3.5 points (standard deviation: 0.8) on a scale of 1 to 5. Most apps scored low due to poor evidence-based information, aesthetics, and engagement. Conclusion Although the use of mHealth technologies for monitoring sleep time has considerable potential for investigation, it is a relatively new, underexplored topic. Collaboration between researchers, clinical professionals, patients, and application developers is necessary for the creation of new evidence-based mHealth applications focused on Brazilian users.

A randomized controlled trial of the dissemination of an mHealth intervention for improving health outcomes: the WiseApp for Spanish-speakers living with HIV study protocol

BackgroundWhile there is no cure for HIV, adherence to antiretroviral therapy can extend the lifespan and improve the quality of life of people with HIV. Despite the global reduction of HIV infection rates in recent years, New York City and La Romana, Dominican Republic, continue to report high infection rates among Latino populations. Many people with HIV remain virally unsuppressed in these geographic hotspots, suggesting a need for additional interventions to overcome medication adherence barriers. Tailored and culturally appropriate mobile health (mHealth) technology can be an engaging way to improve adherence. The primary objective of this trial is to test the effectiveness of an mHealth tool to improve HIV medication adherence among Spanish-speaking people living in New York City and the Dominican Republic.MethodsThe WiseApp study is a two-arm randomized controlled trial among 248 people with HIV across the New York and Dominican Republic sites over the course of 12 months. Participants are randomly assigned to either receive a CleverCap pill bottle that is linked to the WiseApp (intervention) or standard of care (control). All participants complete surveys at baseline, 3-month, 6-month, and 12-month follow-up visits and the study team obtains HIV-1 viral load and CD4 count results through blood draw at each study timepoint.DiscussionThe use of mHealth technologies to improve medication adherence among people with HIV has been implemented in recent years. Although some studies have found improvement in adherence to antiretroviral therapy in the short term, there is limited information about how these interventions improve adherence among Spanish-speaking populations. Disproportionate rates of HIV infection among Latinos in New York City suggest an existing inequitable approach in reaching and treating this population. Due to a lack of mHealth studies with Latino populations, and apps tailored to Spanish-speakers, the WiseApp study will not only demonstrate the effectiveness of this particular mHealth app but will also contribute to the mHealth research community as a whole.Trial registrationThis trial was registered with Clinicaltrials.gov (NCT05398185) on 5/31/2022.

Use of mHealth technology for improving exercise adherence in patients with heart failure: a systematic review (Preprint)

Use of mHealth technology for improving exercise adherence in patients with heart failure: a systematic review (Preprint)

Evaluation of Mobile Health Technology Interventions for the Postdischarge Management of Patients With Head and Neck Cancer: Scoping Review.

Patients with head and neck cancer (HNC) often experience various types and degrees of complications and functional impairment following surgery or radiotherapy. Consequently, these patients require extensive postdischarge rehabilitation, either at home or in the community. Numerous studies have shown the advantages of mobile Health (mHealth) technology in assisting patients with cancer with self-management and rehabilitation during the postdischarge period. However, few reviews have focused on the intervention, management, and evaluation of mHealth technology in postdischarge patients with HNC. This study aimed to conduct a scoping review of mHealth technology apps and interventions currently available to patients discharged from hospitals after receiving treatment for HNC. This study sought to identify and summarize the types and effectiveness of existing mHealth interventions as well as the differences in their outcome assessments. The PubMed, Embase, Web of Science, and CINAHL databases were used to identify studies with no publication time limits. The keywords "mobile health technology" and "head and neck cancer" were combined to address the main concepts of the research questions. Of the 1625 papers identified, 13 (0.8%) met the inclusion and exclusion criteria. Most studies (n=8, 61.5%) were randomized controlled trials (RCTs) and cohort studies. These studies were conducted in 6 countries. The main aims of the mHealth interventions in these studies are as follows: (1) symptom monitoring and assessment, (2) rehabilitation training, (3) access to medical health information, (4) telehealth advisers, (5) peer communication and support, and (6) follow-up/review reminders. The outcome evaluations of the 13 included studies were grouped into 4 categories: (1) technology usability and patient satisfaction, (2) self-management of symptoms and patient-reported outcome-related indicators, (3) adherence, and (4) health-related quality of life. A limited number of studies have investigated the use of mHealth technology in the postdischarge self-management of patients with HNC. The existing literature suggests that mHealth technology can effectively assist patients with HNC in self-management and postdischarge interventions. It plays an important role in addressing patients' health information needs, reducing both their somatic and psychological burdens, and improving their overall quality of life. Future research should prioritize conducting additional high-quality RCTs to evaluate the usability and analyze the cost-effectiveness of mHealth technology.

Racial Disparities in Shared Decision-Making and the Use of mHealth Technology Among Adults With Hypertension in the 2017-2020 Health Information National Trends Survey: Cross-Sectional Study in the United States.

Mobile health (mHealth) technology has the potential to support shared decision-making (SDM) and improve hypertension control. However, our understanding of the variations in individuals' involvement in SDM and mHealth usage across different racial and ethnic groups in the United States is still limited. This study aimed to investigate the extent of involvement in SDM and the usage of mHealth technology in health-related activities among US adults with hypertension from diverse racial and ethnic backgrounds and to examine whether the mHealth usage differed by individuals' level of engagement in SDM. This study used cross-sectional data from the 2017 to 2020 Health Information National Trends Survey, which was conducted on US adults with self-reported hypertension, and race and ethnicity data were included. The exposure of interest was race and ethnicity. The outcomes were SDM and mHealth usage. SDM was assessed using an item: "In the past 12 months, how often did your health professional: involve you in decisions about your healthcare as much as you wanted?" mHealth usage was defined as using a smartphone or tablet to engage in (1) making health decisions, (2) discussing health decisions with health providers, (3) tracking health progress, and (4) sharing health information. Weighted multivariable logistic regression models were used to examine the association between race and ethnicity and SDM or mHealth usage adjusted for covariates and stratified by the level of engagement in SDM. This study included 4893 adults with hypertension, and the mean age was 61 (SD 13) years. The sample was 53% female, 61% (n=3006) non-Hispanic White, 19% (n=907) non-Hispanic Black or African American, 12% (n=605) Hispanic, 4% (n=193) non-Hispanic Asian, and 4% (n=182) non-Hispanic other. Compared to the non-Hispanic White adults, non-Hispanic Black adults were more likely to use mHealth to make health decisions (adjusted odds ratio [aOR] 1.70, 95% CI 1.23-2.34), share health information (aOR 1.46, 95% CI 1.02-2.08), and discuss health decisions with health providers (aOR 1.38, 95% CI 1.02-1.87). Significant associations were observed specifically among those who were always involved in SDM. Asian adults were less likely to be involved in SDM (aOR 0.51, 95% CI 0.26-0.99) and were more likely to use mHealth to track progress on a health-related goal (aOR 2.07, 95% CI 1.28-3.34) than non-Hispanic White adults. Hispanic adults were less likely to use mHealth to share health information (aOR 0.47, 95% CI 0.33-0.67) and discuss health decisions with health providers (aOR 0.65, 95% CI 0.46-0.94) compared to non-Hispanic White adults. This study observed racial and ethnic disparities in SDM and mHealth usage among US adults with hypertension. These findings emphasize the significance of comprehending the involvement of SDM and the usage of mHealth technology within racially and ethnically diverse populations.

Differing Effects of Implementation Leadership Characteristics on Nurses' Use of mHealth Technologies in Clinical Practice: Cross-Sectional Survey Study.

Leadership has been consistently identified as an important factor in shaping the uptake and use of mobile health (mHealth) technologies in nursing; however, the nature and scope of leadership remain poorly delineated. This lack of detail about what leadership entails limits the practical actions that can be taken by leaders to optimize the implementation and use of mHealth technologies among nurses working clinically. This study aimed to examine the effects of first-level leaders' implementation leadership characteristics on nurses' intention to use and actual use of mHealth technologies in practice while controlling for nurses' individual characteristics and the voluntariness of use, perceived usefulness, and perceived ease of use of mHealth technologies. A cross-sectional exploratory correlational survey study of registered nurses in Canada (n=288) was conducted between January 1, 2018, and June 30, 2018. Nurses were eligible to participate if they provided direct care in any setting and used employer-provided mHealth technologies in clinical practice. Hierarchical multiple regression analyses were conducted for the 2 outcome variables: intention to use and actual use. The implementation leadership characteristics of first-level leaders influenced nurses' intention to use and actual use of mHealth technologies, with 2 moderating effects found. The final model for intention to use included the interaction term for implementation leadership characteristics and education, explaining 47% of the variance in nurses' intention to use mHealth in clinical practice (F10,228=20.14; P<.001). An examination of interaction plots found that implementation leadership characteristics had a greater influence on the intention to use mHealth technologies among nurses with a registered nurse diploma or a bachelor of nursing degree than among nurses with a graduate degree or other advanced education. For actual use, implementation leadership characteristics had a significant influence on the actual use of mHealth over and above the control variables (nurses' demographic characteristics, previous experience with mHealth, and voluntariness) and other known predictors (perceived usefulness and perceived ease of use) in the model without the implementation leadership × age interaction term (β=.22; P=.001) and in the final model that included the implementation leadership × age interaction term (β=-.53; P=.03). The final model explained 40% of the variance in nurses' actual use of mHealth in their work (F10,228=15.18; P<.001). An examination of interaction plots found that, for older nurses, implementation leadership characteristics had less of an influence on their actual use of mHealth technologies. Leaders responsible for the implementation of mHealth technologies need to assess and consider their implementation leadership behaviors because these play a role in influencing nurses' use of mHealth technologies. The education level and age of nurses may be important factors to consider because different groups may require different approaches to optimize their use of mHealth technologies in clinical practice.

Healthiness as a Virtue: The Healthism of mHealth and the Challenges to Public Health

Abstract Mobile health (mHealth) technologies for self-monitoring health-relevant parameters such as heart frequency, sleeping patterns or exercise regimes aim at fostering healthy behavior change and increasing the individual users to promote and maintain their health. We argue that this aspect of mHealth supports healthism, the increasing shift from institutional responsibility for public health toward individual engagement in maintaining health as well as mitigating health risks. Moreover, this healthist paradigm leads to a shift from understanding health as the absence of illness to regarding health as the performance of certain rituals in order to project healthiness. By drawing from the analogy between healthiness and traditional virtues, we evaluate the promises made by proponents of mHealth technologies for self-monitoring. We argue that the implementation and use of mHealth risk entrenching existing inequalities and, more particularly, tend to exclude populations situated at the losing end of those inequalities from participating in the quasi-virtue of healthiness. Consequently, the implementation and use of mHealth technologies not only present challenges for social justice but also undermine their primary societal goal—to promote public health. Finally, we offer several suggestions on how to realize the potential benefit of mHealth.

Behavioral intention to use mobile health (mHealth) technologies among caregivers of cancer patients

INTRODUCTION: According to an analysis by the World Health Organization (WHO), thenumber of deaths caused by cancer has increased every year from 1990 to 2017. Mobile health(mHealth) technologies are powerful tools to improve cancer awareness by providing educationalinformation. Therefore, the aim of this study was to examine factors affecting the behaviorsamong caregivers of cancer patients in Malaysia using mHealth technologies.METHODS: The study applied the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2)model as a theoretical framework, with the I-Change Model (ICM) to extend the UTAUT2. Thepopulation element in this research study focused on caregivers of cancer patients who own asmartphone capable of accessing the internet and can download mobile applications. SmartPLSwas used for model and construct testing. A total of 131 sets of valid data were collected from thetarget population through an online survey.RESULTS: Results showed Effort Expectancy (EE), Facilitating Condition (FC), Habit (HT),Awareness Factor (AWN), and Perceived Privacy Risk (PPR) were found to be significant constructs.Performance Expectancy (PE), Social Influence (SI), Hedonic Motivation (HM), and Price Value (PV)were not significant constructs.CONCLUSION: This study provided baseline data on the use of mHealth technologies to thecaregivers of cancer patients in Malaysia to reduce their caregiving burden.

#3563 VALIDATION OF AN M-HEALTH TECHNOLOGY TO SUPPORT PATIENTS UNDERGOING PERITONEAL DIALYSIS

Abstract Background and Aims A global increase in the prevalence of chronic kidney disease (CKD) and, consequently, in the number of individuals submitted to renal replacement therapy (RRT) has been observed. In Brazil, there was an increase from 46,557 to 144,779 (&amp;gt;310%) in the number of people on dialysis between the years 2001 and 2020, respectively. Although peritoneal dialysis (PD) is a safe, low-cost and less aggressive dialysis method when compared to hemodialysis (HD) and can be performed at the home, HD remains the most common RRT type in Brazil (92.2%). This study aimed to validate a PD section incorporated into an existing m-Health application (app) called 'Renal Health®'. Method This is a methodological study, with a quantitative and applied approach. For internal validation of the app usability, ten specialists/researchers in the study topic from the Nursing Nephrology participated in the study, hereafter referred to as ‘judges’, who carried out the validation process of the content to be inserted into the Renal Health® app. The validation instrument was sent to them electronically, organized according to a Likert scale following a four-degree gradation. Based on the specialists’ answers, the means of agreement were calculated, which ranged from –1 for a negative evaluation; 0 (zero) for a neither positive nor negative evaluation; and, +1 when the evaluation was positive. Data evaluation was done using descriptive statistics and the calculation of the content validity index (CVI). Each item of the validation instrument was analyzed in relation to these obtained averages, which, if they were less than 80%, would indicate the need for modifications. An evaluation instrument was created with 22 items arranged in three domains: objectives (4), structure and presentation (15), and relevance (3), aiming to reflect the app functionality, usability and appearance. Results Regarding the objectives related to the PD section, none of items received an “irrelevant” assessment and its CVI ranged from 0.90 to 1.0, with an overall CVI of 0.95. The sub-items with the highest scores were related to the text being compatible with the target audience and the PD section of the app having adequate information/content to guide the patients. Among the 15 sub-items related to the structure and presentation of the PD section, six showed 90% agreement among the judges and were distributed as follows: they indicated that the information directed to the object of interest was sufficient and adequate; stated that the colors applied to the text were relevant and facilitated its use; that the subtitles applied were adequate and helped the user to understand the image; confirmed that the amount of illustration was adequate for the content of the material; that the illustrations were clear and easy to understand and that they were relevant to the content of the material and elucidated the content. The other sub-items had a maximum CVI (1.0) and the overall CVI for this domain was 0.95. Finally, regarding the relevance of the PD section, all sub-items showed 100% agreement among the participants, so that the overall CVI was 1.0. Regarding the qualitative analysis of the instrument, there was no disagreement between the judges and/or suggestions for changes in the PD section. Conclusion The present study allowed the validation of the PD section in the Renal Health® app, which showed good reliability and could promote the use of m-Health technology to support users undergoing this type of dialysis.

A meta-analysis of a comprehensive m-health technology acceptance

PurposeThe evolution of e-health technologies presents promising alternatives for health-care excellence. Despite the benefits arising from mobile e-health (m-health) and wearables technologies, the literature stands many contradictories signs regarding how users accept and engage in using these technologies. This study aims to synthesize the estimations about m-health user acceptance technologies.Design/methodology/approachA meta-analytic structural equation modeling was carried out using the 778 relationships estimated by 100 previous research. The estimations follow the relations and constructs proposed in the UTAUT2 technological acceptance model.FindingsThe results indicate the performance expectancy, effort expectancy, social influence and habit constructs are most important for predicting the behavioral intention of use of m-health technologies. The Latin American users of e-health technologies are still underestimated in the literature.Originality/valueThe study presents a guide to understanding the acceptance process of m-health technologies and delivers a general orientation for developing new m-health devices considering their acceptance by users.

Association of mobile health (mHealth) use with health status and COVID-19-related concerns by people with mobility impairments

Purpose Mobile health (mHealth) technology has increased dramatically in the wake of the pandemic. Less research has focused on people with mobility impairing (PMI) disabilities. This study determined the prevalence of mHealth use among PMI adults during the COVID-19 escalation and examines demographic, health and COVID-19 concerns correlates. Methods PMI adults (N = 304) completed an online survey investigating mHealth use and COVID-19 concerns related to food access in June of 2020. Smartphone and mHealth use were measured with an adapted version of the survey used in the Pew Internet & American Life project. Descriptive and multivariable analyses were conducted to determine associations of demographics, health status, and COVID-19 concerns with mHealth use. About two-thirds (N = 201) of the sample were mHealth users (owned a smartphone and engaged in health-promoting behaviors with the smartphone; e.g., sought online information, tracked health behaviors, used patient portals). Results Having hypertension was associated with higher mHealth use, and having higher COVID-19 concerns about food access was associated with higher mHealth use. Those who used mHealth were also more engaged with smartphone apps for communication, services, and entertainment. Only the association between educational attainment and mHealth use remained significant after adjusting for other covariates in multivariable logistic regression models. Discussion PMIs continue to need support in the use of mHealth technology to help maximize access to potentially important tools for rehabilitation and health management. There is a need to continue to investigate mHealth and its applications for people with disabilities. Implications for Rehabilitation Many people with mobility impairing disabilities may be missing opportunities for mHealth rehabilitation and healthcare. COVID-19 has widened existing gaps in access and use of mHealth technology among people with mobility impairing disabilities. Focused education is needed to help people with disabilities exploit the full range of services of their smartphones to increase access to care, social connectivity, and other important goods and services to enhance rehabilitation and health management.

S-47-6: BIG DATA AND REAL-WORLD DATA FOR HYPERTENSION MANAGEMENT IN THE ERA OF DIGITAL HEALTH

There has been an increasing number of research papers on hypertension studies using healthcare big data. Real-world data (RWD) is a term used for observational studies in a way that appears similar to big data, and is considered as the data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources including EHRs, claims and billing activities, product and disease registries, patient-generated data in home-use settings, data gathered from other sources that can inform on health status such as mobile devices, as described by the U.S. FDA. For the purpose of this presentation, the term RWD will be used regardless of big data or not, unless a distinction between big data and RWD is necessary. In the era of Digital Health, recent hypertension management research shows a prominent trend towards the use of mobile technology that enables self-management of hypertension. By digital health, we mean eHealth and mHealth collectively. We have conducted literature search on digital health studies that targeted hypertension management using PubMed. There are many studies on mHealth for improving lifestyle where smartphone is considered a convenient tool to aid in the treatment of hypertension through the use of apps targeting self-management behavior for blood pressure control. In some studies, data obtained from the apps are combined with clinical data or linked to existing databases for cohort studies. Other studies focus on the use of mHealth technologies for medication adherence, improved communication between clinicians and patients, and or education to patients and to their family. Studies have shown potential of digital interventions in self-management, changing the behavior of people with chronic conditions, with discussions of the feasibility, acceptability, and effectiveness. Effectiveness of digital interventions has been assessed in many trials although most of the studies are small scale. There are also some studies on digital therapeutics (DTx) and their trials for hypertension, where DTx are digital health tools for therapeutic interventions. In this presentation, we provide an overview of on-going efforts to obtain evidence to determine the overall effect of digital health technology on blood pressure control, medication adherence, and lifestyle changes for people with hypertension. Then we discuss barriers to and enablers of adoption of technology-based interventions, and need of more large-scale well-designed epidemiological research.

Systematic Review of mHealth Interventions for Adolescent and Young Adult HIV Prevention and the Adolescent HIV Continuum of Care in Low to Middle Income Countries

Adolescents and young adults (AYA) in low to middle income countries (LMIC) have poorer outcomes along each step in the HIV continuum of prevention and care compared to younger children or older adults. The use of mHealth technology provides a potentially promising implementation strategy for interventions to remedy these disparities. We therefore conducted a systematic review of the English literature and conference proceedings from January 1, 2000 to April 1, 2021 evaluating mHealth interventions targeting AYA along each step of the HIV continuum of care in LMIC. We identified 27 mHealth interventions across the HIV continuum, with no interventions addressing transition from pediatric to adult care. The majority of studies were single arm, uncontrolled or underpowered, with few randomized trials resulting in mixed and inconclusive outcomes. mHealth interventions have potential to remedy disparities along the HIV continuum of care for AYA in LMIC but larger, powered randomized trials are needed.

The law of non-usage attrition in a technology-based behavioral intervention for black adults with poor cardiovascular health.

Digital health innovations, such as telehealth and remote monitoring, have shown promise in addressing patient barriers to accessing evidence-based programs and providing a scalable path for tailored behavioral interventions that support self-management skills, knowledge acquisition and promotion of relevant behavioral change. However, significant attrition continues to plague internet-based studies, a result we believe can be attributed to characteristics of the intervention, or individual user characteristics. In this paper, we provide the first analysis of determinants of non usage attrition in a randomized control trial of a technology-based intervention for improving self-management behaviors among Black adults who face increased cardiovascular risk factors. We introduce a different way to measure nonusage attrition that considers usage over a specific period of time and estimate a cox proportional hazards model of the impact of intervention factors and participant demographics on the risk of a nonusage event. Our results indicated that not having a coach (compared to having a coach) decreases the risk of becoming an inactive user by 36% (HR = .63, P = 0.04). We also found that several demographic factors can influence Non-usage attrition: The risk of nonusage attrition amongst those who completed some college or technical school (HR = 2.91, P = 0.04) or graduated college (HR = 2.98, P = 0.047) is significantly higher when compared to participants who did not graduate high school. Finally, we found that the risk of nonsage attrition among participants with poor cardiovascular from "at-risk" neighborhoods with higher morbidity and mortality rates related to CVD is significantly higher when compared to participants from "resilient" neighborhoods (HR = 1.99, P = 0.03). Our results underscore the importance of understanding challenges to the use of mhealth technologies for cardiovascular health in underserved communities. Addressing these unique barriers is essential, because a lack of diffusion of digital health innovations exacerbates health disparities.