Use of Tablets and Smartphones to Support Medical Decision Making in US Adults: Cross-Sectional Study

Characterizing perceived usability and its correlation with smoking cessation: An analysis of user assessments of the smoking cessation app quitSTART

Background

As smartphone ownership has become common in all demographic groups in the United States, smartphone applications (apps) for smoking cessation have grown in popularity due to their potential for supporting the diverse populations in the United States who are attempting to quit smoking. Usability is commonly assessed in mobile health (mHealth) technology as an important aspect of the user experience that could influence users' adherence to a health app and health outcomes. However, the variation of perceived usability across demographic groups, and the implications of that variation for app success, have not been well studied.

Objective

The aims of this study were to characterize variation in the perceived usability of the National Cancer Institute Smokefree.gov Initiative smoking cessation app quitSTART across demographic groups, and to assess the correlation between perceived usability and short-term smoking cessation.

Methods

We conducted a secondary analysis of data from a randomized controlled trial conducted from 2020 to 2021, which used a 16-item modified version of the mHealth App Usability Questionnaire (MAUQ) to quantify perceived usability four weeks after app download among 131 smokers attempting to quit. Responses were coded on a 5-point Likert-type scale ranging from strongly disagree (1) to strongly agree (5) and total perceived usability was calculated as the sum of all 16 items (range: 16-80). Associations between participant demographic characteristics (gender, race, education level, age, etc.) and total usability were determined using an ANCOVA model. A multivariable logistic regression model was used to assess the association between usability and smoking cessation, also assessed 4 weeks after app download.

Results

The ANCOVA model demonstrated that race was associated with perceived usability, with participants from a racial minority group reporting higher total usability than White participants (p < 0.001). White participants had an adjusted mean total usability of 55.8 (95 % CI: 52.8, 58.8) while racial minority group participants had an adjusted mean total usability of 66.5 (95 % CI: 61.2, 71.6). Other participant demographic characteristics, such as gender and sexual minority status, were not associated with mean total usability. Total usability was positively associated with smoking cessation (OR: 1.04, 95 % CI: 1.00, 1.08, p = 0.031).

Conclusions

Total perceived usability of quitSTART was higher among adults from a racial minority group compared to White adults, and perceived usability was positively associated with cessation success. These findings emphasize the importance of ensuring high usability of mHealth smoking cessation apps for diverse populations.

mHealth Apps Use and Their Associations With Healthcare Decision-Making and Health Communication Among Informal Caregivers: Evidence From the National Cancer Institute's Health Information National Trends Survey

PURPOSE

The current study investigates associations between mHealth apps and healthcare decision-making and health communication among informal caregivers in the US.

DESIGN

Cross-sectional study employing secondary data.

SETTING

The Health Information National Trends Survey (HINTS5, Cycles 2 through 4, 2018 - 2020).

SAMPLE

Self-identified informal caregivers (n = 1386; had mHealth apps = 61.3%, female = 63.2%, some college or more in education = 80.3%) who reported owning at least a smartphone or a tablet computer (i.e., ownership of a "smart device").

MEASURES

Sociodemographic characteristics, reports of having mHealth apps, smart device utilization in healthcare decision-making and health communication.

ANALYSIS

Accounting for the complex design features of the HINTS data, we constructed multiple hierarchical logistic regressions to compute adjusted odds ratios (aOR) and their 95% confidence intervals (CI).

RESULTS

Compared to caregivers without mHealth apps, those with the apps had higher odds of utilizing their smart devices to make a health-related decision, such as how to treat a disease or a medical condition (aOR = 1.65; 95% CI: 1.13-2.39, P < .01), or engage in health-related discussions with a healthcare provider (aOR = 2.36; 95% CI: 1.54-3.61, P < .001).

CONCLUSION

Having mHealth apps was associated with a higher likelihood of using smart devices in healthcare decision-making and health communication by informal caregivers. Empowering caregivers to make informed health-related decisions and communicate effectively with healthcare providers are both crucial to health promotion and well-being. Future studies should investigate facilitators as well as barriers to using mHealth apps and smart devices in health-promoting strategies involving informal caregivers.

Mobile Postoperative Symptom Intervention Tool and Biometric Monitoring After Radical Cystectomy: Pilot Study Evaluating Feasibility, Usability, and Potential Utility

PURPOSE

Mobile health technology and integration of patient-reported outcome measures into clinical interventions have the potential to transform patient care. Though patient-reported outcome measure management has been shown to improve outcomes in ambulatory care settings, few studies have examined remote patient-reported outcome measure assessment after major cancer surgery.

MATERIALS AND METHODS

A multiphased feasibility and usability study was designed. A mobile app-based postoperative symptom intervention tool was developed and evaluated by a focus group of bladder cancer patients and caregivers. Patients were prospectively accrued prior to cystectomy and asked to complete the daily mobile postoperative symptom intervention tool and wear biometric monitoring devices for 30 days post discharge. Retention, postoperative symptom intervention tool completion, and usability were assessed. Exploratory analysis of daily symptoms and patient-generated health information correlated signals with postsurgical complications and hospital readmission.

RESULTS

Fifteen patients with a median age of 72 years completed 78% of daily surveys over the 30-day recovery period. Average time to complete the postoperative symptom intervention tool was 152 seconds. All patients agreed that the daily survey was easy to use, and most reported it would be a better way to communicate with the care team about symptoms than calling the clinic. Frequency and severity of patient-reported symptoms appeared to cluster prior to or at the time of complication or unplanned health care encounters on visual-analogue mapping.

CONCLUSIONS

Using smartphone and wearable technology to capture patient-reported symptoms and biometric data is feasible and rated as highly usable by bladder cancer patients after cystectomy. Symptom scores may signal developing complications and help clinicians identify postsurgical patients who may benefit from intervention.

User satisfaction and the readiness-to-use e-health applications in the future in Polish society in the early phase of the COVID-19 pandemic: A cross-sectional study

Introduction

The COVID-19 pandemic resulted in the rapid expansion of e-health services in Poland. The main aim of the study was to assess the determinants of user satisfaction and the readiness-to-use e-health applications in Polish society.

Patients and methods

The paper presents the results of the analysis of the data obtained through a computer-assisted web interviewing survey in a representative sample of 1002 adult Internet users in Poland. The survey was based on a questionnaire consisting of 55 items. The determinants of user satisfaction and the readiness-to-use of e-health solutions were assessed with univariable and hierarchical logistic regression models.

Results

E-health services had been used by 60.6% of respondents from the beginning of the epidemic state in Poland to June 2020, when the survey was performed. The hierarchical model showed that user satisfaction with e-health interactions was significantly associated with HL (Health Literacy) and eHL (e-Health Literacy), COVID-19-related conspiracy beliefs score, and using a televisit because of acute symptoms not suggesting COVID-19. Readiness-to-use e-health in the future showed a significant relationship with place of residence, marital status, eHL, the self-assessment of knowledge about preventing COVID-19, the use of televisits for renewing prescriptions, and the level of satisfaction with e-health services.

Conclusions

Satisfaction with e-health services depends mainly on the HL, eHL, and conspiracy beliefs of patients. Readiness-to-use e-health in the future is associated with the level of eHL and sociodemographic characteristics, but previous experience with e-health services seems to be the main predictor.

Digital Technologies for Health Promotion and Disease Prevention in Older People: Protocol for a Scoping Review

BACKGROUND

Digital technologies could contribute to health promotion and disease prevention. It is unclear if and how such digital technologies address the health needs of older people in nonclinical settings (ie, daily life).

OBJECTIVE

This study aims to identify digital technologies for health promotion and disease prevention that target the needs of older people in nonclinical settings by performing a scoping review of the published literature. The scoping review is guided by the framework of Arksey and O'Malley.

METHODS

Our scoping review follows the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. The information sources are bibliographic databases (MEDLINE, PsycINFO, CINAHL, and SCOPUS) and bibliographies of any included systematic reviews. Manual searches for additional studies will be performed in Google Scholar and most relevant journals. The electronic search strategy was developed in collaboration with a librarian who performed the search for studies on digital technologies for health promotion and disease prevention targeting the needs of older people. Study selection and data coding will be performed independently by 2 authors. Consensus will be reached by discussion. Eligibility is based on the PCC (Population, Concept, and Context) criteria as follows: (1) older people (population); (2) any digital (health) technology, such as websites, smartphone apps, or wearables (concept); and (3) health promotion and disease prevention in nonclinical (daily life, home, or community) settings (context). Primary studies with any design or reviews with a systematic methodology published in peer-reviewed academic journals will be included. Data items will address study designs, PCC criteria, benefits or barriers related to digital technology use by older people, and evidence gaps. Data will be synthesized using descriptive statistics or narratively described by identifying common themes. Quality appraisal will be performed for any included systematic reviews, using a validated instrument for this study type (A Measurement Tool to Assess Systematic Reviews, version 2 [AMSTAR2]).

RESULTS

Following preliminary literature searches to test and calibrate the search syntax, the electronic literature search was performed in March 2022 and manual searches were completed in June 2022. Study selection based on titles and abstracts was completed in July 2022, and the full-text screen was initiated in July 2022.

CONCLUSIONS

Our scoping review will identify the types of digital technologies, health targets in the context of health promotion and disease prevention, and health benefits or barriers associated with the use of such technologies for older people in nonclinical settings. This knowledge could guide further research on how digital technologies can support healthy aging.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/37729.

A Nationwide Natural Experiment of e-Health Implementation during the COVID-19 Pandemic in Poland: User Satisfaction and the Ease-of-Use of Remote Physician’s Visits

The COVID-19 pandemic resulted in a considerable increase in the use of e-health applications. Shortly after confirmation of the first case of COVID-19 in Poland, the Ministry of Health allowed for the general use of remote physician’s visits (RPVs) as a substitute for traditional visits to the physician’s office. It was estimated that during the first year of the pandemic, as many as 80% of primary care visits were provided remotely, mainly by phone. This study’s main aim was to assess the use of e-health services in the initial phase of the COVID-19 pandemic. Furthermore, the factors related to user satisfaction and positive assessment of the ease-of-use of RPVs were analyzed. The analysis was based on data obtained from a computer-assisted web-based interviewing (CAWI) survey among 2410 adult Internet users in Poland. The questionnaire consisted of 55 items, including a 16-item European Health Literacy Questionnaire, an 8-item e-Health Literacy scale, a set of questions about the use of and experience with e-health services during the pandemic, and items exploring the sociodemographic characteristics of the respondents. Univariate logistic regression models were developed for variables reflecting user satisfaction and the assessment of the ease-of-use of RPVs. The use of RPVs increased during the pandemic by about 200%. Higher health literacy and e-health literacy, older age, higher income, a greater number of e-health services used before the pandemic, and telephone-based remote visits were significantly associated with higher user satisfaction and ease-of-use of RPVs. Respondents using RPVs for renewal of prescriptions were more favorable in assessing satisfaction and ease-of-use. A less positive assessment of satisfaction and ease-of-use was provided by students and vocationally passive persons in comparison to the employed. Finally, the perception of the threat of COVID-19 was associated with higher satisfaction and better assessment of ease-of-use. Persons declaring the intention to be vaccinated against COVID-19 were more likely to be satisfied with remote visits. User satisfaction and the feeling of ease-of-use in the case of remote advice provided by a physician depend on many factors. Significant predictors include selected sociodemographic and economic variables, determinants associated with the perception of the threat of COVID-19, the aims and tools used for the RPVs, and earlier experience with e-health services.

Enrollment and retention of participants in remote digital health studies: a scoping review and framework proposal (Preprint)

Background

Objective

Methods

Results

Conclusions

Development of a Mobile App for Clinical Research: Challenges and Implications for Investigators

Advances in mobile app technologies offer opportunities for researchers to feasibly collect a large amount of patient data that were previously inaccessible through traditional clinical research methods. Collection of data via mobile devices allows for several advantages, such as the ability to continuously gather data outside of research facilities and produce a greater quantity of data, making these data much more valuable to researchers. Health services research is increasingly incorporating mobile health (mHealth), but collecting these data in current research institutions is not without its challenges. Our paper uses a specific example to depict specific challenges of mHealth research and provides recommendations for investigators looking to incorporate digital app technologies and patient-collected digital data into their studies. Our experience describes how clinical researchers should be prepared to work with variable software and mobile app development timelines; research institutions that are interested in participating in mHealth research need to invest in supporting information technology infrastructures in order to be a part of the growing field of mHealth and gain access to valuable patient-collected data.

Mobile health strategies for blood pressure self-management in urban populations with digital barriers: systematic review and meta-analyses

Mobile health (mHealth) technologies improve hypertension outcomes, but it is unknown if this benefit applies to all populations. This review aimed to describe the impact of mHealth interventions on blood pressure outcomes in populations with disparities in digital health use. We conducted a systematic search to identify studies with systolic blood pressure (SBP) outcomes located in urban settings in high-income countries that included a digital health disparity population, defined as mean age ≥65 years; lower educational attainment (≥60% ≤high school education); and/or racial/ethnic minority (<50% non-Hispanic White for US studies). Interventions were categorized using an established self-management taxonomy. We conducted a narrative synthesis; among randomized clinical trials (RCTs) with a six-month SBP outcome, we conducted random-effects meta-analyses. Twenty-nine articles (representing 25 studies) were included, of which 15 were RCTs. Fifteen studies used text messaging; twelve used mobile applications. Studies were included based on race/ethnicity (14), education (10), and/or age (6). Common intervention components were: lifestyle advice (20); provision of self-monitoring equipment (17); and training on digital device use (15). In the meta-analyses of seven RCTs, SBP reduction at 6-months in the intervention group (mean SBP difference = -4.10, 95% CI: [-6.38, -1.83]) was significant, but there was no significant difference in SBP change between the intervention and control groups (p = 0.48). The use of mHealth tools has shown promise for chronic disease management but few studies have included older, limited educational attainment, or minority populations. Additional robust studies with these populations are needed to determine what interventions work best for diverse hypertensive patients.

Patterns and Influencing Factors of eHealth Tools Adoption Among Medicaid and Non-Medicaid Populations From the Health Information National Trends Survey (HINTS) 2017-2019: Questionnaire Study

BACKGROUND

Evidence suggests that eHealth tools adoption is associated with better health outcomes among various populations. The patterns and factors influencing eHealth adoption among the US Medicaid population remain obscure.

OBJECTIVE

The objective of this study is to explore patterns of eHealth tools adoption among the Medicaid population and examine factors associated with eHealth adoption.

METHODS

Data from the Health Information National Trends Survey from 2017 to 2019 were used to estimate the patterns of eHealth tools adoption among Medicaid and non-Medicaid populations. The effects of Medicaid insurance status and other influencing factors were assessed with logistic regression models.

RESULTS

Compared with the non-Medicaid population, the Medicaid beneficiaries had significantly lower eHealth tools adoption rates for health information management (11.2% to 17.5% less) and mobile health for self-regulation (0.8% to 9.7% less). Conversely, the Medicaid population had significantly higher adoption rates for using social media for health information than their counterpart (8% higher in 2018, P=.01; 10.1% higher in 2019, P=.01). Internet access diversity, education, and cardiovascular diseases were positively associated with health information management and mobile health for self-regulation among the Medicaid population. Internet access diversity is the only factor significantly associated with social media adoption for acquisition of health information (OR 1.98, 95% CI 1.26-3.11).

CONCLUSIONS

Our results suggest digital disparities in eHealth tools adoption between the Medicaid and non-Medicaid populations. Future research should investigate behavioral correlates and develop interventions to improve eHealth adoption and use among underserved communities.

Social and Demographic Patterns of Health-Related Internet Use Among Adults in the United States: A Secondary Data Analysis of the Health Information National Trends Survey

National surveys of U.S. adults have observed significant increases in health-related internet use (HRIU), but there are documented disparities. The study aims to identify social and demographic patterns of health-related internet use among U.S. adults. Using data from the Health Information National Trends Survey (HINTS) 4 cycle 3 and HINTS 5 cycle 1, we examined HRIU across healthcare, health information seeking, and participation on social media. Primary predictors were gender, race/ethnicity, age, education, income, and nativity with adjustments for smoking and survey year. We used multivariable logistic regression with survey weights to identify independent predictors of HRIU. Of the 4817 respondents, 43% had used the internet to find a doctor; 80% had looked online for health information. Only 20% had used social media for a health issue; 7% participated in an online health support group. In multivariable models, older and low SES participants were significantly less likely to use the internet to look for a provider, use the internet to look for health information for themselves or someone else, and less likely to use social media for health issues. Use of the internet for health-related purposes is vast but varies significantly by demographics and intended use.