Incorporation of a Stress Reducing Mobile App in the Care of Patients With Type 2 Diabetes: A Prospective Study

Smartphone application-based intervention to lower blood pressure: a systematic review and meta-analysis

Nowadays, the mHealth market is flooded with smartphone applications (apps) lacking validation for blood pressure (BP)-lowering effects and BP measurement accuracy. This systematic review for Guidelines for BP control using digital technologies of the Japanese Society of Hypertension aimed to assess the validation studies of apps. We searched eligible studies in Ovid MEDLINE, Cochrane Library, and Ichushi, focusing on randomized controlled trials and observational studies comparing the effects of smartphone app-based interventions with non-digital healthcare. Random effects models of meta-analysis were employed to estimate the pooled effects of mean BP change and 95% confidence intervals (CIs). Out of 7385 studies screened, 76 studies with 46,459 participants were included. The interventions were significantly associated with a reduction in office systolic and diastolic BP at six months (systolic BP, -2.76 mmHg, 95% CI: -3.94 to -1.58; diastolic BP, -1.23 mmHg, -1.80 to -0.67). Normotensives saw a significant reduction in office systolic BP at three-month (-4.44 mmHg, -6.96 to -1.92), diminishing afterward (six-month, 0.86 mmHg, -2.81 to 4.52; twelve-month, 0.86 mmHg, -2.81 to 4.52). Conversely, hypertensive participants experienced a significant reduction in office systolic BP at both three- and six-month (three-month, -7.71 mmHg, -10.63 to -4.79; six-month, -1.88 mmHg, -3.41 to -0.35), albeit with limited evidence thereafter. A larger BP reduction was observed among participants using apps with wireless transmission of BP measurements (P = 0.047 for interaction), while there was no clear difference in BP reduction according to the presence of other functions. Smartphone app-based interventions may hold the potential to improve BP levels.

The Vagal Nerve, Inflammation, and Diabetes-A Holy Triangle

Type 2 diabetic mellitus (T2DM) is a common chronic disease and a substantial risk factor of other fatal illnesses. At its core is insulin resistance, where chronic low-level inflammation is among its main causes. Thus, it is crucial to modulate this inflammation. This review paper provides scientific neuroimmunological evidence on the protective roles of the vagal nerve in T2DM. First, the vagus inhibits inflammation in a reflexive manner via neuroendocrine and neuroimmunological routes. This may also occur at the level of brain networks. Second, studies have shown that vagal activity, as indexed by heart-rate variability (HRV), is inversely related to diabetes and that low HRV is a predictor of T2DM. Finally, some emerging evidence shows that vagal nerve activation may reduce biomarkers and processes related to diabetes. Future randomized controlled trials are needed to test the effects of vagal nerve activation on T2DM and its underlying anti-inflammatory mechanisms.

The role of sleep and heart rate variability in metabolic syndrome: evidence from the Midlife in the United States study

STUDY OBJECTIVES

Poor sleep and autonomic dysregulation can both disrupt metabolic processes. This study examined the individual and combined effects of poor sleep and reduced heart rate variability (HRV) on metabolic syndrome among 966 participants in the Midlife in the United States II (MIDUS II) study.

METHODS

Self-reported sleep was assessed using the Pittsburgh Sleep Quality Index (PSQI). HRV was acquired from 11-minute resting heart rate recordings. Spearman correlations, general linear regression, and logistic regression models were used to examine the study hypotheses.

RESULTS

Poor sleep quality was associated with metabolic syndrome when global PSQI scores were evaluated as a continuous (odds ratio [OR]: 1.07, 95% confidence interval [CI]: 1.03 to 1.11) or categorical measure (cutoff > 5, OR: 1.58, 95% CI: 1.19 to 2.10), after adjustment for confounding. There also was an association between reduced HRV and metabolic syndrome (ln [HF-HRV] OR: 0.89, 95% CI: 0.80 to 0.99; ln [LF-HRV] OR: 0.82, 95% CI: 0.72 to 0.92; ln [SDRR] OR: 0.59, 95% CI: 0.43 to 0.79; ln [RMSSD] OR: 0.75, 95% CI: 0.60 to 0.94). When the combined effects of poor sleep and low HRV were examined, the association with metabolic syndrome was further strengthened relative to those with normal sleep and HRV.

CONCLUSIONS

To the best of the author's knowledge, this is the first study to suggest a combined effect of poor sleep and low HRV on the odds of metabolic syndrome.

Neuromodulation Applied to Diseases: The Case of HRV Biofeedback

The vagus or “wandering” nerve is the main branch of the parasympathetic nervous system (PNS), innervating most internal organs crucial for health. Activity of the vagus nerve can be non-invasively indexed by heart-rate variability parameters (HRV). Specific HRV parameters predict less all-cause mortality, lower risk of and better prognosis after myocardial infarctions, and better survival in cancer. A non-invasive manner for self-activating the vagus is achieved by performing a slow-paced breathing technique while receiving visual feedback of one’s HRV, called HRV-biofeedback (HRV-B). This article narratively reviews the biological mechanisms underlying the role of vagal activity and vagally mediated HRV in hypertension, diabetes, coronary heart disease (CHD), cancer, pain, and dementia. After searching the literature for HRV-B intervention studies in each condition, we report the effects of HRV-B on clinical outcomes in these health conditions, while evaluating the methodological quality of these studies. Generally, the levels of evidence for the benefits of HRV-B is high in CHD, pain, and hypertension, moderate in cancer, and poor in diabetes and dementia. Limitations and future research directions are discussed.

Stress-Reducing Psychological Interventions as Adjuvant Therapies for Diabetic Chronic Wounds

BACKGROUND

Diabetic foot ulcers (DFUs) are a major complication of diabetes mellitus and a leading cause of lower limb amputation. Interventions to reduce psychological stress may have the potential to improve self-care and greatly reduce the morbidity and mortality associated with DFU. This review is focused on the consequences of psychological stress in wound healing and reflects on the effects of currently used psychological stress-reducing interventions in patients with DFU, proposing new applications for currently used stress-reduction interventions.

RESULTS

Stress is a natural and fundamental survival mechanism that becomes harmful when chronic. DFU is associated with high levels of anxiety and chronic psychological stress. Chronic stressinduced cortisol and adrenaline release impair wound healing, independently of the stressor. Psychological stress-reducing interventions, such as relaxation with guided imagery, biofeedback-assisted relaxation, mindfulness-based strategies, and hypnosis, can lead to a reduction in perceived stress and improve wound healing by reducing wound inflammation and pain while improving glycemic control. All stress reduction interventions also lead to pain relief and improved patient's quality of life.

CONCLUSION

Psychological stress-reducing interventions are promising adjuvant therapies for DFU. Their clinical application can improve self-care by tackling patient's expectations, anxieties, and fears. They can also help patients manage stress and pain while reducing wound inflammation and improving wound healing.

Patent Landscape of Automated Systems for Personalized Health Management (ASHM): Features, Shortcomings, and Implications for Developing an Optimal ASHM

The current struggle of national health care systems against global epidemic of non-communicable diseases (NCD) is both clinically ineffective and cost ineffective. On the other hand, rapid development of systems biology, P4 medicine and new digital and communication technologies are good prerequisites for creating an affordable and scalable automated system for personalized health management (ASHM). The current practice of ASHM is better represented in patent literature (36 relevant documents found in Google Patents and USPTO) than in scientific papers (17 documents found in PubMed and Google Scholar). However, only a small fraction of publications disclose a complete self-sufficient system. Problems that authors of ASHM aim to address, methodological approaches, and the most important technical solutions are reviewed and discussed along with shortcomings and limitations. Technical solutions for ASHM currently commercialized or described in literature generally fail to enable practicable, scalable and affordable automated and individualized screening, monitoring, prevention and correction of human health conditions. They also fail to provide a decision support system to patients that would help effectively prevent major NCD and their complications, be accessible and cost effective, consider individual lifestyle factors and involve patients in management of their individual health. Based on analysis of the literature, models of health and care, we propose conceptual framework for developing an ASHM that would be free from the mentioned problems.

Moderation of the Stressor-Strain Process in Interns by Heart Rate Variability Measured with a Wearable and Smartphone App: a Within-Subject Design Using Continuous Monitoring

Background

The emergence of smartphones and wearable sensor technologies enables easy and unobtrusive monitoring of physiological and psychological data related to an individual’s resilience. Heart rate variability (HRV) is a promising biomarker for resilience based on between-subject population studies, but observational studies that apply a within-subject design and use wearable sensors in order to observe HRV in a naturalistic real-life context are needed.

Objective

This study aims to explore whether resting HRV and total sleep time (TST) are indicative and predictive of the within-day accumulation of the negative consequences of stress and mental exhaustion. The tested hypotheses are that demands are positively associated with stress and resting HRV buffers against this association, stress is positively associated with mental exhaustion and resting HRV buffers against this association, stress negatively impacts subsequent-night TST, and previous-evening mental exhaustion negatively impacts resting HRV, while previous-night TST buffers against this association.

Methods

In total, 26 interns used consumer-available wearables (Fitbit Charge 2 and Polar H7), a consumer-available smartphone app (Elite HRV), and an ecological momentary assessment smartphone app to collect resilience-related data on resting HRV, TST, and perceived demands, stress, and mental exhaustion on a daily basis for 15 weeks.

Results

Multiple linear regression analysis of within-subject standardized data collected on 2379 unique person-days showed that having a high resting HRV buffered against the positive association between demands and stress (hypothesis 1) and between stress and mental exhaustion (hypothesis 2). Stress did not affect TST (hypothesis 3). Finally, mental exhaustion negatively predicted resting HRV in the subsequent morning but TST did not buffer against this (hypothesis 4).

Conclusions

To our knowledge, this study provides first evidence that having a low within-subject resting HRV may be both indicative and predictive of the short-term accumulation of the negative effects of stress and mental exhaustion, potentially forming a negative feedback loop. If these findings can be replicated and expanded upon in future studies, they may contribute to the development of automated resilience interventions that monitor daily resting HRV and aim to provide users with an early warning signal when a negative feedback loop forms, to prevent the negative impact of stress on long-term health outcomes.

Assessment of Psychological Distress in Adults With Type 2 Diabetes Mellitus Through Technologies: Literature Review

Background

The use of technological devices can support the self-management of individuals with type 2 diabetes mellitus (T2DM), particularly in addressing psychological distress. However, there is poor consistency in the literature regarding the use of psychological instruments for the web-based screening of patients’ psychological distress and subsequent monitoring of their psychological condition during digital interventions.

Objective

This study aims to review previous literature on the types of psychological instruments delivered in digital interventions for assessing depression, anxiety, and stress in patients with T2DM.

Methods

The literature review was conducted using the PsycINFO, CINAHL and PubMed databases, in which the following terms were considered: diabetes mellitus, measure, assessment, self-care, self-management, depression, anxiety, stress, technology, eHealth, mobile health, mobile phone, device, and smartphone.

Results

In most studies, psychological assessments were administered on paper. A few studies deployed self-reporting techniques employing automated telephonic assessment, a call system for screening and monitoring patients’ conditions and preferences, or through telephone interviews via interactive voice response calls, a self-management support program leveraging tailored messages and structured emails. Other studies used simple telephone interviews and included the use of apps for tablets and smartphones to assess the psychological well-being of patients. Finally, some studies deployed mood rating scales delivered through tailored text message–based support systems.

Conclusions

The deployment of appropriate psychological tools in digital interventions allows researchers and clinicians to make the screening of anxiety, stress, and depression symptoms faster and easier in patients with T2DM. Data from this literature review suggest that mobile health solutions may be preferred tools to use in such digital interventions.

Obstacles to using online health services among adults age 50 and up and the role of family support in overcoming them

Background

Using Online Health Services (OHS) could benefit older adults greatly and could also reduce the burden on the health system. Yet invisible obstacles or barriers appear to impede mass adoption of these services among this population group. The aim of the current research is to provide a qualitative picture of these invisible obstacles and to profile their main features, with special attention to the role of family members in supporting OHS use among this population group.

Methods

This qualitative study entailed a series of in-depth, semi-structured, open phone interviews conducted with 31 individuals age 50 and up in Israel, who constituted a sample of OHS users and non-users among older adults.

Results

Four major themes and primary observations emerge from our data:

While older adults are aware of OHS to some extent, they often do not fully understand the specific benefits of using these services;

Older adults need to acquire much more experience with OHS use. OHS user interfaces still have a long way to go for older adults to feel comfortable using them. People age 50 and up seem to be less concerned about privacy and security issues than about seemingly more trivial issues such as recovering forgotten passwords;

Family members can play key roles in helping older adults adopt OHS by providing technical support as well as encouragement;

Older adults have worthwhile recommendations for innovations and policy improvements that would facilitate wider adoption of OHS.

Conclusions

The results of the current study reveal important nuances regarding the importance of awareness, user interface and experience for OHS use among older adults, as well as the critical role of family members in OHS adoption. Based on these findings, we recommend the following: expanding advertising on media channels to emphasize the benefits of OHS use; improving HMO websites to make them more user-friendly for older people; developing HMO-run community OHS guidance programs geared to older people to reduce the gap between required skills and user competencies, thus enabling older people to benefit from OHS use.

Combining Biofeedback with Stress Management Interventions: A Systematic Review of Physiological and Psychological Effects

Current mental healthcare systems experience difficulties meeting the challenges of a growing population with elevated stress symptoms. Outpatient stress management interventions have already proven to be effective in routine care and recent technological advances now allow to expand such interventions, for example by adding a physiological component like biofeedback. Adding biofeedback to stress management interventions appears promising, but there is a lack of insight into the general conceptualization and evaluation of the resulting interventions, both in relation to psychological and physiological stress indicators. A comprehensive literature search was performed to investigate stress management interventions with a biofeedback component. This systematic review provides an overview of these interventions and explores to what extent they can improve both physiological and psychological indicators of stress. Fourteen RCTs were included. A large diversity was observed in intervention design and effectiveness. Nevertheless, there is preliminary evidence that the use of biofeedback can improve both physiological and psychological indicators of stress. Biofeedback could provide an accessible and low-cost addition to stress interventions. Further research into the effectiveness of different components of biofeedback interventions is needed.

Methods and Measures Used to Evaluate Patient-Operated Mobile Health Interventions: Scoping Literature Review

BACKGROUND

Despite the prevalence of mobile health (mHealth) technologies and observations of their impacts on patients' health, there is still no consensus on how best to evaluate these tools for patient self-management of chronic conditions. Researchers currently do not have guidelines on which qualitative or quantitative factors to measure or how to gather these reliable data.

OBJECTIVE

This study aimed to document the methods and both qualitative and quantitative measures used to assess mHealth apps and systems intended for use by patients for the self-management of chronic noncommunicable diseases.

METHODS

A scoping review was performed, and PubMed, MEDLINE, Google Scholar, and ProQuest Research Library were searched for literature published in English between January 1, 2015, and January 18, 2019. Search terms included combinations of the description of the intention of the intervention (eg, self-efficacy and self-management) and description of the intervention platform (eg, mobile app and sensor). Article selection was based on whether the intervention described a patient with a chronic noncommunicable disease as the primary user of a tool or system that would always be available for self-management. The extracted data included study design, health conditions, participants, intervention type (app or system), methods used, and measured qualitative and quantitative data.

RESULTS

A total of 31 studies met the eligibility criteria. Studies were classified as either those that evaluated mHealth apps (ie, single devices; n=15) or mHealth systems (ie, more than one tool; n=17), and one study evaluated both apps and systems. App interventions mainly targeted mental health conditions (including Post-Traumatic Stress Disorder), followed by diabetes and cardiovascular and heart diseases; among the 17 studies that described mHealth systems, most involved patients diagnosed with cardiovascular and heart disease, followed by diabetes, respiratory disease, mental health conditions, cancer, and multiple illnesses. The most common evaluation method was collection of usage logs (n=21), followed by standardized questionnaires (n=18) and ad-hoc questionnaires (n=13). The most common measure was app interaction (n=19), followed by usability/feasibility (n=17) and patient-reported health data via the app (n=15).

CONCLUSIONS

This review demonstrates that health intervention studies are taking advantage of the additional resources that mHealth technologies provide. As mHealth technologies become more prevalent, the call for evidence includes the impacts on patients' self-efficacy and engagement, in addition to traditional measures. However, considering the unstructured data forms, diverse use, and various platforms of mHealth, it can be challenging to select the right methods and measures to evaluate mHealth technologies. The inclusion of app usage logs, patient-involved methods, and other approaches to determine the impact of mHealth is an important step forward in health intervention research. We hope that this overview will become a catalogue of the possible ways in which mHealth has been and can be integrated into research practice.

eHealth systems for the optimised care of patients with type 2 diabetes

BACKGROUND

Type 2 diabetes mellitus is one of the most common diseases worldwide. The demands on health services are rising as more people are diagnosed with the condition. In order to meet this demand, eHealth systems are increasingly being integrated into nursing care.

METHODS

Between November 2018 and February 2019, a literature search was carried out in the databases PubMed and CINAHL.

RESULTS

Twenty articles were found on nurses' use of eHealth systems, the majority with patients with diabetes. From this research, it would seem that eHealth systems have had a proven positive influence on patients' state of health and understanding of therapy. Subjectively perceived communication with the nursing staff also improved. Problems can arise in the implementation phase.

CONCLUSION

In the future, increasingly, nurses will have to integrate eHealth systems into the treatment of patients with type 2 diabetes. It is important that nurses understand such systems in order to guarantee a sustainable and successful implementation.

A Tablet-Based Assessment of Rhythmic Ability

The exponential rise in use of mobile consumer electronics has presented a great potential for research to be conducted remotely, with participants numbering several orders of magnitude greater than a typical research paradigm. Here, we attempt to demonstrate the validity and reliability of using a consumer game-engine to create software presented on a mobile tablet to assess sensorimotor synchronization, a proxy of rhythmic ability. Our goal was to ascertain whether previously observed research results can be replicated, rather than assess whether a mobile tablet achieves comparable performance to a desktop computer. To achieve this, younger (aged 18–35 years) and older (aged 60–80 years) adult musicians and non-musicians were recruited to play a custom-designed sensorimotor synchronization assessment on a mobile tablet in a controlled laboratory environment. To assess reliability, participants performed the assessment twice, separated by a week, and an intra-class correlation coefficient (ICC) was calculated. Results supported the validity of this approach to assessing rhythmic abilities by replicating previously observed results. Specifically, musicians performed better than non-musicians, and younger adults performed better than older adults. Participants also performed best when the tempo was in the range of previously-identified preferred tempos, when the stimuli included both audio and visual information, and when synchronizing on-beat compared to off-beat or continuation (self-paced) synchronization. Additionally, high ICC values (>0.75) suggested excellent test–retest reliability. Together, these results support the notion that consumer electronics running software built with a game engine may serve as a valuable resource for remote, mobile-based data collection of rhythmic abilities.

A Biofeedback App to Instruct Abdominal Breathing (Breathing-Mentor): Pilot Experiment

BACKGROUND

Deep and slow abdominal breathing is an important skill for the management of stress and pain. However, despite multiple proofs on the effectiveness of biofeedback, most breathing apps remain limited to pacing specific breathing patterns, without sensor feedback on the actual breathing behavior.

OBJECTIVE

To fill this gap, an app named Breathing-Mentor was developed. This app combines effective visualization of the instruction with biofeedback on deep abdominal breathing, based on the mobile phone's accelerometers. The aim of this pilot study was to investigate users' feedback and breathing behavior during initial contact with the app.

METHODS

To reveal the possible effects of biofeedback, two versions of the mobile app were developed. Both contained the same visual instruction, but only the full version included additional biofeedback. In total, 40 untrained participants were randomly assigned to one of the two versions of the app. They had to follow the app's instructions as closely as possible for 5 min.

RESULTS

The group with additional biofeedback showed an increased signal-to-noise ratio for instructed breathing frequency (0.1 Hz) compared with those using visual instruction without biofeedback (F1,37=4.18; P<.048). During this initial contact with the full version, self-reported relaxation effectivity was, however, lower than the group using visual instruction without biofeedback (t37=-2.36; P=.02), probably owing to increased cognitive workload to follow the instruction.

CONCLUSIONS

This study supports the feasibility and usefulness of incorporating biofeedback in the Breathing-Mentor app to train abdominal breathing. Immediate effects on relaxation levels should, however, not be expected for untrained users.

Biofeedback-Assisted Resilience Training for Traumatic and Operational Stress: Preliminary Analysis of a Self-Delivered Digital Health Methodology

Background

Psychological resilience is critical to minimize the health effects of traumatic events. Trauma may induce a chronic state of hyperarousal, resulting in problems such as anxiety, insomnia, or posttraumatic stress disorder. Mind-body practices, such as relaxation breathing and mindfulness meditation, help to reduce arousal and may reduce the likelihood of such psychological distress. To better understand resilience-building practices, we are conducting the Biofeedback-Assisted Resilience Training (BART) study to evaluate whether the practice of slow, paced breathing with or without heart rate variability biofeedback can be effectively learned via a smartphone app to enhance psychological resilience.

Objective

Our objective was to conduct a limited, interim review of user interactions and study data on use of the BART resilience training app and demonstrate analyses of real-time sensor-streaming data.

Methods

We developed the BART app to provide paced breathing resilience training, with or without heart rate variability biofeedback, via a self-managed 6-week protocol. The app receives streaming data from a Bluetooth-linked heart rate sensor and displays heart rate variability biofeedback to indicate movement between calmer and stressful states. To evaluate the app, a population of military personnel, veterans, and civilian first responders used the app for 6 weeks of resilience training. We analyzed app usage and heart rate variability measures during rest, cognitive stress, and paced breathing. Currently released for the BART research study, the BART app is being used to collect self-reported survey and heart rate sensor data for comparative evaluation of paced breathing relaxation training with and without heart rate variability biofeedback.

Results

To date, we have analyzed the results of 328 participants who began using the BART app for 6 weeks of stress relaxation training via a self-managed protocol. Of these, 207 (63.1%) followed the app-directed procedures and completed the training regimen. Our review of adherence to protocol and app-calculated heart rate variability measures indicated that the BART app acquired high-quality data for evaluating self-managed stress relaxation training programs.

Conclusions

The BART app acquired high-quality data for studying changes in psychophysiological stress according to mind-body activity states, including conditions of rest, cognitive stress, and slow, paced breathing.

Use of a Biofeedback Breathing App to Augment Poststress Physiological Recovery: Randomized Pilot Study

BACKGROUND

The speed of physiological recovery from stress may be a marker for cardiovascular disease risk. Stress management programs that incorporate guided breathing have been shown to moderate the stress response and augment recovery.

OBJECTIVE

The aim of this study was to examine the effectiveness of an app-based brief relaxation intervention (BioBase) for facilitating physiological recovery in individuals exposed to a brief psychological stressor.

METHODS

A total of 75 participants (44 women) completed a stressor speech task and were randomly assigned to one of three conditions: control, rumination, or an app-based relaxation breathing (BioBase) conditions. Heart rate variability (HRV) was assessed as a measure of autonomic function at baseline (6 min), during stress (6 min), and during recovery (6 min).

RESULTS

There was a significant increase in subjective stress following stress exposure, but the ratings returned to baseline after recovery in all three groups. In addition, there was a significant decrease in vagally mediated HRV in the poststress period. During recovery, the root mean square of successive differences (P<.001), the percentage of successive interbeat (RR) intervals that differ by >50 ms (pNN50; P<.001), and high-frequency (P<.02) HRV were significantly higher in the BioBase breathing condition than the rumination and control conditions. There was no difference in HRV values between the rumination and control conditions during recovery.

CONCLUSIONS

App-based relaxed breathing interventions could be effective in reducing cardiovascular disease risk. These results provide additional utility of biofeedback breathing in augmenting physiological recovery from psychological stress.

A Review of Apps for Calming, Relaxation, and Mindfulness Interventions for Pediatric Palliative Care Patients

Patients and families increasingly use mobile apps as a relaxation and distraction intervention for children with complex, chronic medical conditions in the waiting room setting or during inpatient hospitalizations; and yet, there is limited data on app quality assessment or review of these apps for level of engagement, functionality, aesthetics, or applicability for palliative pediatric patients. The pediatric palliative care study team searched smartphone application platforms for apps relevant to calming, relaxation, and mindfulness for pediatric and adolescent patients. Apps were reviewed using a systematic data extraction tool. Validated Mobile Application Rating Scale (MARS) scores were determined by two blinded reviewers. Apps were then characterized by infant, child, adolescent, and adult caregiver group categories. Reviewer discussion resulted in consensus. Sixteen of the 22 apps identified were included in the final analysis. The apps operated on either iOS or Android platforms. All were available in English with four available in Spanish. Apps featured a relaxation approach (12/16), soothing images (8/16), and breathing techniques (8/16). Mood and sleep patterns were the main symptoms targeted by apps. Provision of mobile apps resource summary has the potential to foster pediatric palliative care providers’ knowledge of app functionality and applicability as part of ongoing patient care.

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

BACKGROUND

China 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.

OBJECTIVE

We 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.

METHODS

Mobile 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.

RESULTS

Of 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.

CONCLUSIONS

Chinese 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.