Evaluation of mHealth Applications Related to Cardiovascular Diseases: a Systematic Review

Villarreal, Vladimir; Berbey-Alvarez, Aranzazu

doi:10.5455/aim.2020.28.130-137

Cited by 24 publications

(31 citation statements)

References 35 publications

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“…Data from Pew Research Center have shown that internet use for racial and ethnic minorities is comparable to non-Hispanic whites [ 2 ]. As a result, health dissemination has become more streamlined, and use of the internet has become a popular tool for fostering complex conversations, increasing access to health information, and improving medical outcomes [ 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 ]. For example, systematic reviews of digital health interventions have found clinical benefits among individuals with musculoskeletal conditions and improved quality of life and mental health outcomes for cancer patients [ 7 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

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

Calixte

Rivera

Oridota

et al. 2020

IJERPH

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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.

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Section: Introductionmentioning

confidence: 99%

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

Calixte

Rivera

Oridota

et al. 2020

IJERPH

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show abstract

“…Although there has been a proliferation of mHealth tools for people with chronic health conditions, the acceptability and long-term use of mHealth tools have varied considerably across people with different chronic conditions [101,102]. Variability in mHealth tool use across people with chronic health conditions may be related to the quality of both the content and functionality of mHealth tools, as well as user-related preferences [103][104][105][106][107].…”

Section: Principal Resultsmentioning

confidence: 99%

Attitudes Toward Using COVID-19 mHealth Tools Among Adults With Chronic Health Conditions: Secondary Data Analysis of the COVID-19 Impact Survey (Preprint)

Camacho-Rivera¹,

Islam²,

Rivera³

et al. 2020

Preprint

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BACKGROUND Adults with chronic conditions are disproportionately burdened by COVID-19 morbidity and mortality. Although COVID-19 mobile health (mHealth) apps have emerged, research on attitudes toward using COVID-19 mHealth tools among those with chronic conditions is scarce. OBJECTIVE This study aimed to examine attitudes toward COVID-19, identify determinants of COVID-19 mHealth tool use across demographic and health-related characteristics, and evaluate associations between chronic health conditions and attitudes toward using COVID-19 mHealth tools (eg, mHealth or web-based methods for tracking COVID-19 exposures, symptoms, and recommendations). METHODS We used nationally representative data from the COVID-19 Impact Survey collected from April to June 2020 (n=10,760). Primary exposure was a history of chronic conditions, which were defined as self-reported diagnoses of cardiometabolic, respiratory, immune-related, and mental health conditions and overweight/obesity. Primary outcomes were attitudes toward COVID-19 mHealth tools, including the likelihood of using (1) a mobile phone app to track COVID-19 symptoms and receive recommendations; (2) a website to track COVID-19 symptoms, track location, and receive recommendations; and (3) an app using location data to track potential COVID-19 exposure. Outcome response options for COVID-19 mHealth tool use were extremely/very likely, moderately likely, or not too likely/not likely at all. Multinomial logistic regression was used to compare the likelihood of COVID-19 mHealth tool use between people with different chronic health conditions, with not too likely/not likely at all responses used as the reference category for each outcome. We evaluated the determinants of each COVID-19 mHealth intervention using Poisson regression. RESULTS Of the 10,760 respondents, 21.8% of respondents were extremely/very likely to use a mobile phone app or a website to track their COVID-19 symptoms and receive recommendations. Additionally, 24.1% of respondents were extremely/very likely to use a mobile phone app to track their location and receive push notifications about whether they have been exposed to COVID-19. After adjusting for age, race/ethnicity, sex, socioeconomic status, and residence, adults with mental health conditions were the most likely to report being extremely/very or moderately likely to use each mHealth intervention compared to those without such conditions. Adults with respiratory-related chronic diseases were extremely/very (conditional odds ratio 1.16, 95% CI 1.00-1.35) and moderately likely (conditional odds ratio 1.23, 95% CI 1.04-1.45) to use a mobile phone app to track their location and receive push notifications about whether they have been exposed to COVID-19. CONCLUSIONS Our study demonstrates that attitudes toward using COVID-19 mHealth tools vary widely across modalities (eg, web-based method vs app) and chronic health conditions. These findings may inform the adoption of long-term engagement with COVID-19 apps, which is crucial for determining their potential in reducing disparities in COVID-19 morbidity and mortality among individuals with chronic health conditions.

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“…E-Health: a type of medical informatics using electronic resources such as web-based technology and m-health (use of mobile devices, including wearable technologies) to monitor clinical signs, provide health information, and facilitate patient engagement in self-care for a healthier lifestyle and social support. [62][63][64] Health promotion (WHO definition): the process of enabling people to increase control over, and to improve, their health, usually through addressing behavioral risk factors. 1 Risk factor: Factors that increase the likelihood of people experiencing a health-related event.…”

Section: Definitions Of Key Terms and Concepts (The Following Section Should Go In A Box)mentioning

confidence: 99%

“…Provide patients with individualized follow-up feedback by using technology-based strategies. 38,[62][63][64]81 Nutrition/diet 1. Make nutrition recommendations for adults of all body sizes personally and culturally acceptable and affordable to the patient as well as nutritionally adequate to support long-term adherence.…”

Section: Overweight Patients With Weight-related Conditionsmentioning

confidence: 99%

The Role of Chiropractic Care in Providing Health Promotion and Clinical Preventive Services for Adult Patients with Musculoskeletal Pain: A Clinical Practice Guideline

Amorin-Woods

Evans

Whedon

et al. 2021

The Journal of Alternative and Complementary Medicine

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Objective: To develop evidence-based recommendations on best practices for delivery of clinical preventive services by chiropractors and to offer practical resources to empower provider applications in practice.Design: Clinical practice guideline based on evidence-based recommendations of a panel of practitioners and experts on clinical preventive services.Methods: Synthesizing the results of a literature search for relevant clinical practice guidelines and systematic reviews, a multidisciplinary steering committee with training and experience in health promotion, clinical prevention, and/or evidence-based chiropractic practice drafted a set of recommendations. A Delphi panel of

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Evaluation of mHealth Applications Related to Cardiovascular Diseases: a Systematic Review

Cited by 24 publications

References 35 publications

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

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

Attitudes Toward Using COVID-19 mHealth Tools Among Adults With Chronic Health Conditions: Secondary Data Analysis of the COVID-19 Impact Survey (Preprint)

The Role of Chiropractic Care in Providing Health Promotion and Clinical Preventive Services for Adult Patients with Musculoskeletal Pain: A Clinical Practice Guideline

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