Effect of Mobile Health Interventions on the Secondary Prevention of Cardiovascular Disease: Systematic Review and Meta-analysis

Gandhi, Sumeet; Chen, Shu; Hong, Louisa; Sun, Kelly; Gong, Enying; Li, Chaoyun; Yan, Lijing L.; Schwalm, Jon-David

doi:10.1016/j.cjca.2016.08.017

Cited by 165 publications

(135 citation statements)

References 23 publications

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“…Telephone follow-up is an effective method of increasing quality of life and self-efficacy, reducing stress and avoiding recurrent hospitalisations (7,10,11). Recent meta-analyses of RCTs have reported that telephone follow-up interventions are associated with improvements in adaptation and lifestyle changes (12)(13)(14). To reduce the rate of repeated cardiovascular events and improve adaptation, single methods are commonly used in the literature, but it is thought that the use of theoretical intervention applications in combination with other methods based on evidence to improve adaptation may be more effective.…”

Section: Introductionmentioning

confidence: 99%

The effect of education and telephone follow‐up intervention based on the Roy Adaptation Model after myocardial infarction: randomised controlled trial

Kavradım

Özer

2019

Scandinavian Caring Sciences

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Background Patients’ lifestyle changes after myocardial infarction reduce the risk of infarction. Nursing interventions are important for the initiation and maintenance of lifestyle adaptation. Aim The aim of this study was to evaluate the effect of education and telephone follow‐up intervention based on the Roy Adaptation Model for improving myocardial infarction patients’ self‐efficacy, quality of life and lifestyle adaptation. Method In this parallel, randomised controlled trial, patients were randomly allocated to a control group or an intervention group (n = 33/group). The control group received routine care, while the intervention group received routine care plus a telephone follow‐up intervention, which consisted of a predischarge education programme and three telephone follow‐up sessions. Data were collected before discharge, in the 12th week after discharge between April 2016 and August 2017. All outcomes were assessed at baseline and at 12 weeks, and included quality of life, coping adaptation process, self‐efficacy and lifestyle changes. The CONSORT checklist was used in the study. Results In the 12th week after discharge, patients in the intervention group had significant improvements in self‐efficacy, quality of life and coping adaptation process compared with the control group. The intervention group also had more adaptation lifestyle changes concerning patients nutrition and physical activity in the 12‐week follow‐up. Conclusion This study demonstrated that education and telephone follow‐up intervention based on Roy Adaptation Model was had positive and significant results after 12 weeks compared with usual care. The findings of this study are important for supporting nursing practice and health professionals who care for individuals with myocardial infarction to develop nursing care.

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Section: Introductionmentioning

confidence: 99%

The effect of education and telephone follow‐up intervention based on the Roy Adaptation Model after myocardial infarction: randomised controlled trial

Kavradım

Özer

2019

Scandinavian Caring Sciences

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“…Meanwhile, there is a severe shortage of doctors in China, where the doctor-patient ratio is 1.4 doctors per 1000 patients [ 3 ]. Mobile health (mHealth) apps therefore hold promise for delivering health information and services to Chinese patients, especially for chronic conditions like CVD, which require extensive self-management [ 4 ]. Self-management is key to person-centered care [ 5 ], but its support requires an understanding of individual preferences for different types of health information and decision-making autonomy [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Chinese Cardiovascular Disease Mobile Apps’ Information Types, Information Quality, and Interactive Functions for Self-Management: Systematic Review

Xie¹,

Su²,

Zhang³

et al. 2017

JMIR Mhealth Uhealth

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BackgroundChina has a large population with cardiovascular disease (CVD) that requires extensive self-management. Mobile health (mHealth) apps may be a useful tool for CVD self-management. Little is currently known about the types and quality of health information provided in Chinese CVD mobile apps and whether app functions are conducive to promoting CVD self-management.ObjectiveWe undertook a systematic review to evaluate the types and quality of health information provided in Chinese CVD mobile apps and interactive app functions for promoting CVD self-management.MethodsMobile apps targeting end users in China with CVD conditions were selected in February 2017 through a multi-stage process. Three frameworks were used to evaluate the selected apps: (1) types of health information offered were assessed using our Health Information Wants framework, which encompasses 7 types of information; (2) quality of information provided in the apps was assessed using the 11 guidelines recommended by the National Library of Medicine of the National Institutes of Health; and (3) types of interactive app functions for CVD self-management were assessed using a 15-item framework adapted from the literature, including our own prior work.ResultsOf 578 apps identified, 82 were eligible for final review. Among these, information about self-care (67/82, 82%) and information specifically regarding CVD (63/82, 77%) were the most common types of information provided, while information about health care providers (22/82, 27%) and laboratory tests (5/82, 6%) were least common. The most common indicators of information quality were the revealing of apps’ providers (82/82, 100%) and purpose (82/82, 100%), while the least common quality indicators were the revealing of how apps’ information was selected (1/82, 1%) and app sponsorship (0/82, 0%). The most common interactive functions for CVD self-management were those that enabled user interaction with the app provider (57/82, 70%) and with health care providers (36/82, 44%), while the least common interactive functions were those that enabled lifestyle management (13/82, 16%) and psychological health management (6/82, 7%). None of the apps covered all 7 types of health information, all 11 indicators of information quality, or all 15 interactive functions for CVD self-management.ConclusionsChinese CVD apps are insufficient in providing comprehensive health information, high-quality information, and interactive functions to facilitate CVD self-management. End users should exercise caution when using existing apps. Health care professionals and app developers should collaborate to better understand end users’ preferences and follow evidence-based guidelines to develop mHealth apps conducive to CVD self-management.

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“…Holistic wellbeing (for Māori participants only): Tūhononga (cultural connections), Mauri (life force or essence), wellbeing, whanaungatanga (family wellbeing and social connectedness) and Rangatiratanga (self-determination, motivation, and management), measured by 16 questions informed by Māori health models Te Whare Tapa Whā [30] and Te Pae Mahutonga [27] and adapted in part from the Hua Oranga Māori mental health assessment questionnaire [31]. Answers are measured on a 6-point Likert scale.…”

Section: Methodsmentioning

confidence: 99%

“…mHealth programs (ie, the usage of mobile and wireless technologies designed to achieve medical objectives) [20] have been shown to effectively help people change various health behaviors [19,21-26] and improve other secondary risk factors for cardiovascular diseases, such as blood pressure and medication adherence [27]. Nevertheless, most mHealth programs are designed with minimal input from end-users and lack tailoring to cultural needs.…”

Section: Introductionmentioning

confidence: 99%

A Co-Designed, Culturally-Tailored mHealth Tool to Support Healthy Lifestyles in Māori and Pasifika Communities in New Zealand: Protocol for a Cluster Randomized Controlled Trial

Verbiest¹,

Borrell²,

Dalhousie³

et al. 2018

JMIR Res Protoc

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BackgroundNew Zealand urgently requires scalable, effective, behavior change programs to support healthy lifestyles that are tailored to the needs and lived contexts of Māori and Pasifika communities.ObjectiveThe primary objective of this study is to determine the effects of a co-designed, culturally tailored, lifestyle support mHealth tool (the OL@-OR@ mobile phone app and website) on key risk factors and behaviors associated with an increased risk of noncommunicable disease (diet, physical activity, smoking, and alcohol consumption) compared with a control condition.MethodsA 12-week, community-based, two-arm, cluster-randomized controlled trial will be conducted across New Zealand from January to December 2018. Participants (target N=1280; 64 clusters: 32 Māori, 32 Pasifika; 32 clusters per arm; 20 participants per cluster) will be individuals aged ≥18 years who identify with either Māori or Pasifika ethnicity, live in New Zealand, are interested in improving their health and wellbeing or making lifestyle changes, and have regular access to a mobile phone, tablet, laptop, or computer and to the internet. Clusters will be identified by community coordinators and randomly assigned (1:1 ratio) to either the full OL@-OR@ tool or a control version of the app (data collection only plus a weekly notification), stratified by geographic location (Auckland or Waikato) for Pasifika clusters and by region (rural, urban, or provincial) for Māori clusters. All participants will provide self-reported data at baseline and at 4- and 12-weeks postrandomization. The primary outcome is adherence to healthy lifestyle behaviors measured using a self-reported composite health behavior score at 12 weeks that assesses smoking behavior, fruit and vegetable intake, alcohol intake, and physical activity. Secondary outcomes include self-reported body weight, holistic health and wellbeing status, medication use, and recorded engagement with the OL@-OR@ tool.ResultsTrial recruitment opened in January 2018 and will close in July 2018. Trial findings are expected to be available early in 2019.ConclusionsCurrently, there are no scalable, evidence-based tools to support Māori or Pasifika individuals who want to improve their eating habits, lose weight, or be more active. This wait-list controlled, cluster-randomized trial will assess the effectiveness of a co-designed, culturally tailored mHealth tool in supporting healthy lifestyles.Trial RegistrationAustralia New Zealand Clinical Trials Register ACTRN12617001484336; http://www.ANZCTR.org.au/ACTRN12617001484336.aspx (Archived by WebCite at http://www.webcitation.org/71DX9BsJb)Registered Report IdentifierRR1-10.2196/10789

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Effect of Mobile Health Interventions on the Secondary Prevention of Cardiovascular Disease: Systematic Review and Meta-analysis

Cited by 165 publications

References 23 publications

The effect of education and telephone follow‐up intervention based on the Roy Adaptation Model after myocardial infarction: randomised controlled trial

The effect of education and telephone follow‐up intervention based on the Roy Adaptation Model after myocardial infarction: randomised controlled trial

Chinese Cardiovascular Disease Mobile Apps’ Information Types, Information Quality, and Interactive Functions for Self-Management: Systematic Review

A Co-Designed, Culturally-Tailored mHealth Tool to Support Healthy Lifestyles in Māori and Pasifika Communities in New Zealand: Protocol for a Cluster Randomized Controlled Trial

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