Mobile phone-based video messages for diabetes self-care support

Nurse-led remote digital support for adults with chronic conditions: A systematic synthesis without meta-analysis

AIM

The systematic review aims to synthesize the literature examining the effectiveness of nurse-led remote digital support on health outcomes in adults with chronic conditions.

BACKGROUND

Adults with chronic diseases have increased rates of mortality and morbidity and use health care resources at a higher intensity than those without chronic conditions-placing strain on the patient, their caregivers and health systems. Nurse-led digital health disease self-management interventions have potential to improve outcomes for patients with chronic conditions by facilitating care in environments other that the hospital setting.

DESIGN AND METHODS

We searched PubMed/MEDLINE, Embase, PsycINFO and Cochrane Central databases from inception to 7 December 2022. We included randomized controlled trials assessing the impact of nurse-led remote digital support interventions compared to usual care on health-related outcomes in adults with chronic illness. The Cochrane risk-of-bias tool was used to assess bias in studies. Outcomes were organized into four categories: self-management, clinical outcomes, health care resource use and satisfaction with care. Results are presented narratively based on statistical significance.

RESULTS

Forty-four papers pertaining to 40 unique studies were included. Interventions most targeted diabetes (n = 11) and cardiovascular disease (n = 8). Websites (n = 10) and mobile applications (n = 10) were the most used digital modalities. Nurses supported patients either in response to incoming patient health data (n = 14), virtual appointment (n = 8), virtual health education (n = 5) or through a combination of these approaches (n = 13). Positive impacts of nurse-led digital chronic disease support were identified in each outcome category. Mobile applications were the most effective digital modality.

CONCLUSION AND RELEVANCE TO CLINICAL PRACTICE

Results show that nurse-led remote digital support interventions significantly improve self-management capacity, clinical health outcomes, health care resource use and satisfaction with care. Such interventions have potential to support overall health for adults with chronic conditions in their home environments.

The use of videos for diabetes patient education: A systematic review

Diabetes prevalence is rising worldwide, calling for public health concerns and interventions to improve prevention and management. Self-care is an important component in reducing the incidence of complications from diabetes, but it must be taught. This systematic review aims to synthesise the evidence for education videos for people with diabetes. Electronic databases, including Ovid (Medline, Embase, EmCare), PsychInfo, CINAHL, Web of Science and Scopus, were searched for studies on educational videos for patients with diabetes that met the inclusion criteria. A total of 36 studies met the inclusion criteria. Data extracted were synthesised through narrative synthesis. Studies examined outcomes including biological (i.e., glycated haemoglobin (HbA1C), weight, BMI), non-biological (health literacy, self-efficacy) and subjective feedback (i.e., acceptability, cultural appropriateness). The most common length of video was ≤10 min. Online dissemination was the most common method of video distribution. A statistically significant decrease (ranging from -0.1% to -2.1%) in HbA1C was noted in 7 of 12 studies examining this outcome. Other studies also found evidence of improvement in health literacy, self-efficacy, physical activity, medication adherence and other outcomes. Feedback from participants was generally positive, and emphasis was placed on the need for cultural appropriateness and representation in the educational videos.

Video-Based Educational Interventions for Patients With Chronic Illnesses: Systematic Review

BACKGROUND

With rising time constraints, health care professionals increasingly depend on technology to provide health advice and teach patients how to manage chronic disease. The effectiveness of video-based tools in improving knowledge, health behaviors, disease severity, and health care use for patients with major chronic illnesses is not well understood.

OBJECTIVE

The aim of this study was to assess the current literature regarding the efficacy of video-based educational tools for patients in improving process and outcome measures across several chronic illnesses.

METHODS

A systematic review was conducted using CINAHL and PubMed with predefined search terms. The search included studies published through October 2021. The eligible studies were intervention studies of video-based self-management patient education for an adult patient population with the following chronic health conditions: asthma, chronic kidney disease, chronic obstructive pulmonary disease, chronic pain syndromes, diabetes, heart failure, HIV infection, hypertension, inflammatory bowel disease, and rheumatologic disorders. The eligible papers underwent full extraction of study characteristics, study design, sample demographics, and results. Bias was assessed with the Cochrane risk-of-bias tools. Summary statistics were synthesized in Stata SE (StataCorp LLC). Data reporting was conducted per the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist.

RESULTS

Of the 112 studies fully extracted, 59 (52.7%) were deemed eligible for inclusion in this review. The majority of the included papers were superiority randomized controlled trials (RCTs; 39/59, 66%), with fewer pre-post studies (13/59, 22%) and noninferiority RCTs (7/59, 12%). The most represented conditions of interest were obstructive lung disease (18/59, 31%), diabetes (11/59, 19%), and heart failure (9/59, 15%). The plurality (28/59, 47%) of video-based interventions only occurred once and occurred alongside adjunct interventions that included printed materials, in-person counseling, and interactive modules. The most frequently studied outcomes were disease severity, health behavior, and patient knowledge. Video-based tools were the most effective in improving patient knowledge (30/40, 75%). Approximately half reported health behavior (21/38, 56%) and patient self-efficacy (12/23, 52%) outcomes were improved by video-based tools, and a minority of health care use (11/28, 39%) and disease severity (23/69, 33%) outcomes were improved by video-based tools. In total, 48% (22/46) of the superiority and noninferiority RCTs and 54% (7/13) of the pre-post trials had moderate or high risk of bias.

CONCLUSIONS

There is robust evidence that video-based tools can improve patient knowledge across several chronic illnesses. These tools less consistently improve disease severity and health care use outcomes. Additional study is needed to identify features that maximize the efficacy of video-based interventions for patients across the spectrum of digital competencies to ensure optimized and equitable patient education and outcomes.

Estimating the impact of engagement with digital health interventions on patient outcomes in randomized trials

OBJECTIVE

Guidance is needed on studying engagement and treatment effects in digital health interventions, including levels required for benefit. We evaluated multiple analytic approaches for understanding the association between engagement and clinical outcomes.

MATERIALS AND METHODS

We defined engagement as intervention participants' response rate to interactive text messages, and considered moderation, standard regression, mediation, and a modified instrumental variable (IV) analysis to investigate the relationship between engagement and clinical outcomes. We applied each approach to two randomized controlled trials featuring text message content in the intervention: REACH (Rapid Encouragement/Education and Communications for Health), which targeted diabetes, and VERB (Vanderbilt Emergency Room Bundle), which targeted hypertension.

RESULTS

In REACH, the treatment effect on hemoglobin A1c was estimated to be -0.73% (95% CI: [-1.29, -0.21]; P = 0.008), and in VERB, the treatment effect on systolic blood pressure was estimated to be -10.1 mmHg (95% CI: [-17.7, -2.8]; P = 0.007). Only the IV analyses suggested an effect of engagement on outcomes; the difference in treatment effects between engagers and non-engagers was -0.29% to -0.51% in the REACH study and -1.08 to -3.25 mmHg in the VERB study.

DISCUSSION

Standard regression and mediation have less power than a modified IV analysis, but the IV approach requires specification of assumptions. This is the first review of the strengths and limitations of various approaches to evaluating the impact of engagement on outcomes.

CONCLUSIONS

Understanding the role of engagement in digital health interventions can help reveal when and how these interventions achieve desired outcomes.

Digital interventions self-management education for type 1 and 2 diabetes: A systematic review and meta-analysis

OBJECTIVE

To describe and assess digital health-led diabetes self-management education and support (DSMES) effectiveness in improving glycosylated hemoglobin, diabetes knowledge, and health-related quality of life (HrQoL) of Type 1 and 2 Diabetes in the past 10 years.

DESIGN

Systematic Review and Meta-Analysis. The protocol was registered on PROSPERO registration number CRD42019139884.

DATA SOURCES

PubMed, EMBASE, Cochrane library, Web of Science, and Scopus between January 2010 and August 2019. Study Selection and Appraisal: Randomized control trials of digital health-led DSMES for Type 1 (T1DM) or 2 (T2DM) diabetes compared to usual care were included. Outcomes were change in HbA1c, diabetes knowledge, and HrQoL. Cochrane Risk of Bias 2.0 tool was used to assess bias and GRADEpro for overall quality. The analysis involved narrative synthesis, subgroup and pooled meta-analyses.

RESULTS

From 4286 articles, 39 studies (6861 participants) were included. Mean age was 51.62 years, range (13-70). Meta-analysis revealed intervention effects on HbA1c for T2DM with difference in means (MD) from baseline -0.480% (-0.661, -0.299), I²75% (6 months), -0.457% (-0.761, -0.151), I² 81% (12 months), and for T1DM -0.41% (-1.022, 0.208) I² 83% (6 months), -0.03% (-0.210, 0.142) I² 0% (12 months). Few reported HrQoL with Hedges' g 0.183 (-0.039, 0.405), I² 0% (6 months), 0.153 (-0.060, 0.366), I² 0% (12 months) and diabetes knowledge with Hedges' g 1.003 (0.068, 1.938), I² 87% (3 months).

CONCLUSION

Digital health-led DSMES are effective in improving HbA1c and diabetes knowledge, notably for T2DM. Research shows non-significant changes in HrQoL. Intervention effect on HbA1c was more impressive if delivered through mobile apps or patient portals. Further research is needed on the impact of DSMES on these outcomes, especially for newly diagnosed diabetes patients.

Effects of a Video-Based mHealth Program for Homebound Older Adults: Study Protocol for a Pilot Randomized Controlled Trial

BACKGROUND

Although homebound older adults are among the highest users of hospital services, the existing health and social services that are provided to them in the community are limited and fragmented. This study attempts to bring this group of older adults to providers' attention by designing a health-social-oriented self-care mobile Health (mHealth) program and subjecting it to empirical testing. The aim of this study is to shift the current reactive, cure-oriented approach to a preventive and health-promoting model, empowering homebound older adults to take an active role in their health, be responsive to their care needs, and subsequently improve their holistic health.

METHODS

This is a pilot randomized controlled trial. The study is supported by 5 community centers with an estimated sample size of 68 subjects. The subjects will be randomly assigned to video-based mHealth or control groups when they (1) are aged 60 or over, (2) go outdoors less than once a week in the current 6 months, (3) live within the service areas, and (4) use a smartphone. Subjects in the video-based mHealth group will receive a 3-month program comprising 2 main interventions: nurse case management supported by a social service team and video messages covering self-care topics, delivered via smartphone. The control group will receive usual care. Data will be collected at 2 time points - pre-intervention (T1) and post-intervention (T2). The primary outcome will be self-efficacy, and secondary outcomes will include health outcomes (activities of daily living, instrumental activities of daily living, and medication adherence), perceived well-being outcomes (quality of life and depression), and health service utilization outcomes (outpatient clinic, emergency room, and hospital admission).

DISCUSSION

The current study will add to the knowledge gap in using mHealth supported by a health-social team to enhance quality of life and self-care and meet the needs of these particularly vulnerable older adults.

American Association of Clinical Endocrinology Clinical Practice Guideline: The Use of Advanced Technology in the Management of Persons With Diabetes Mellitus

OBJECTIVE

To provide evidence-based recommendations regarding the use of advanced technology in the management of persons with diabetes mellitus to clinicians, diabetes-care teams, health care professionals, and other stakeholders.

METHODS

The American Association of Clinical Endocrinology (AACE) conducted literature searches for relevant articles published from 2012 to 2021. A task force of medical experts developed evidence-based guideline recommendations based on a review of clinical evidence, expertise, and informal consensus, according to established AACE protocol for guideline development.

MAIN OUTCOME MEASURES

Primary outcomes of interest included hemoglobin A1C, rates and severity of hypoglycemia, time in range, time above range, and time below range.

RESULTS

This guideline includes 37 evidence-based clinical practice recommendations for advanced diabetes technology and contains 357 citations that inform the evidence base.

RECOMMENDATIONS

Evidence-based recommendations were developed regarding the efficacy and safety of devices for the management of persons with diabetes mellitus, metrics used to aide with the assessment of advanced diabetes technology, and standards for the implementation of this technology.

CONCLUSIONS

Advanced diabetes technology can assist persons with diabetes to safely and effectively achieve glycemic targets, improve quality of life, add greater convenience, potentially reduce burden of care, and offer a personalized approach to self-management. Furthermore, diabetes technology can improve the efficiency and effectiveness of clinical decision-making. Successful integration of these technologies into care requires knowledge about the functionality of devices in this rapidly changing field. This information will allow health care professionals to provide necessary education and training to persons accessing these treatments and have the required expertise to interpret data and make appropriate treatment adjustments.

Designing and evaluation of E-health educational intervention on students' physical activity: an application of Pender's health promotion model

BACKGROUND

The present study was conducted to design and evaluate the software and web-based curriculum based on Pender Model in order to promote students' physical activity.

METHODS

This is a quasi-experimental study conducted on 225 eligible students who were randomly divided into two groups of web and software-based intervention and control. The sample size of the study was selected using stratified sampling method. The evaluation was done with pre-test and post-test and follow-up, which were performed immediately two and six months following the intervention. The data were analyzed employing statistical software SPSS using descriptive statistics, chi-square, one way ANOVA, and repeated measures ANOVA.

RESULTS

The obtained results revealed that the level of physical activity after the intervention in the web and software groups significantly increased compared to the control group (p < 0.001). Moreover, the mean score of Pender model constructs, immediately two and six months after the intervention, was significantly different in the web and software groups (p < 0.001).

CONCLUSION

Our results indicated that, providing tailored message based on health promotion model's constructs has a positive effect on promoting physical activity of students.

TRIAL REGISTRATION

Name: Iranian Registry of Clinical Trials. Registration number: IRCT20181009041298N1 . Registration date: 2018-12-02 [retrospectively registered].

Aplicação de insulina passo a passo: construção de vídeos educativos para pacientes e cuidadores

RESUMO Objetivo descrever o processo de construção, avaliação e adequação de vídeos educativos sobre aplicação de insulina direcionados a pacientes adultos e cuidadores. Método estudo metodológico, de caráter descritivo, realizado em três fases: construção, avaliação e adequação. A construção dos vídeos foi realizada com base em revisão de literatura e no protocolo do município. A avaliação foi realizada com experts, por meio de um instrumento construído pelos pesquisadores. O nível de concordância entre os experts foi avaliado pelo índice de validade do conteúdo, que orientou o processo de adequação do material. Resultados os vídeos foram construídos contemplando os principais pontos críticos relacionados à aplicação de insulina. Os itens que obtiveram índice de validade de conteúdo < 0,8 foram reformulados. Conclusão e Implicações para a prática foram produzidos dois vídeos que abordam o transporte, armazenamento, preparo e aplicação da insulina, descarte de perfurocortantes e monitorização da glicemia. Os vídeos educativos construídos podem ser considerados ferramentas facilitadoras do processo de educação em diabetes mellitus e úteis na uniformização de orientações. A descrição do processo de construção, avaliação e adequação pode encorajar outros profissionais a desenvolver materiais que respondam às necessidades de seus contextos de trabalho e assim melhorar e qualificar o cuidado às pessoas.

An Umbrella Review of Text Message Programs for Adults With Type 2 Diabetes

Purpose

The purpose of this umbrella review was to synthesize the evidence from published systematic reviews on the effectiveness of text message programs for adults with type 2 diabetes (T2DM) on glycemic management (A1C), self-management, and other clinical outcomes. The effect of directionality of the program was also explored.

Methods

A systematic search was conducted using multiple databases. Inclusion criteria were systematic review of text message programs for adults with T2DM, evaluated A1C, and English language. Quality assessment was completed using AMSTAR-2 guidelines. Data were extracted by multiple coders, and results were synthesized.

Results

The final sample included 9 systematic reviews published between 2011 and 2019, with 72 unique international studies. Text message programs focused on diabetes self-management and reducing health risks through educational and motivational content with some providing personalized feedback. A meta-analysis of program effect on A1C was conducted in 5 reviews with a pooled difference in A1C from −0.38% to −0.8%. Adults with T2DM of shorter duration and lower A1C had better treatment effects. Evidence on unidirectional versus bidirectional programs is conflicting; however, both improve outcomes. Evidence of text message programs targeting medication engagement was inconclusive. Some programs improved blood pressure, lipids, self-management, self-efficacy, and health behaviors. High satisfaction and an average of 9.6% to 18.7% attrition was reported.

Conclusions

Text messaging programs can improve T2DM outcomes, are a highly accessible mode of communication, are relatively inexpensive, and are an underutilized adjunct to clinical care.

Effect of web-based and software-based educational intervention on stages of behavior change of students' physical activity

INTRODUCTION

The present study aims at designing and evaluating the effect of new educational media-based educational intervention on students' stages of behavior change of physical activity.

SUBJECTS AND METHODS

In the present interventional study, 225 students of medical sciences university were assigned into two experimental and one control groups using proportional stratified random sampling, where web-based and software-based educational interventions were used. Data were collected using International Physical Activity Questionnaire, Marcus's stages of change scales, and a self-made questionnaire including constructs of barriers, benefits, and self-efficacy. Evaluation was conducted through pretest and posttest and immediate and 2 and 6 months of follow-ups after the intervention. Data were analyzed by SPSS software using descriptive statistics and Chi-square, Friedman, one-way ANOVA, and ANOVA with repeated measure.

RESULTS

Based on the results, there was no significant difference between the experimental and control groups before the intervention (P = 0.37); however, immediately and 2 and 6 months after the intervention, there was a significant difference between the experimental and control groups in terms of stages of change (P < 0.001). Furthermore, in the experimental group, the educational intervention led to improvement of individuals in the stages of change of physical activity. At 6-month follow-up, 75.4% of the software group and 60.6% of the web group achieved the maintenance stage.

CONCLUSION

The results suggest that designing intervention based on people's level of preparation for changing behavior and using new educational methods such as web and software were effective on individuals' progress in different stages of change of physical activity behavior and physical activity rate.

Enhancing Patient Activation and Self-Management Activities in Patients With Type 2 Diabetes Using the US Department of Defense Mobile Health Care Environment: Feasibility Study

Background

Past mobile health (mHealth) efforts to empower type 2 diabetes (T2D) self-management include portals, text messaging, collection of biometric data, electronic coaching, email, and collection of lifestyle information.

Objective

The primary objective was to enhance patient activation and self-management of T2D using the US Department of Defense’s Mobile Health Care Environment (MHCE) in a patient-centered medical home setting.

Methods

A multisite study, including a user-centered design and a controlled trial, was conducted within the US Military Health System. Phase I assessed preferences regarding the enhancement of the enabling technology. Phase II was a single-blinded 12-month feasibility study that randomly assigned 240 patients to either the intervention (n=123, received mHealth technology and behavioral messages tailored to Patient Activation Measure [PAM] level at baseline) or the control group (n=117, received equipment but not messaging. The primary outcome measure was PAM scores. Secondary outcome measures included Summary of Diabetes Self-Care Activities (SDSCA) scores and cardiometabolic outcomes. We used generalized estimating equations to estimate changes in outcomes.

Results

The final sample consisted of 229 patients. Participants were 61.6% (141/229) male, had a mean age of 62.9 years, mean glycated hemoglobin (HbA_1c) of 7.5%, mean BMI of 32.7, and a mean duration of T2D diagnosis of 9.8 years. At month 12, the control group showed significantly greater improvements compared with the intervention group in PAM scores (control mean 7.49, intervention mean 1.77; P=.007), HbA_1c (control mean −0.53, intervention mean −0.11; P=.006), and low-density lipoprotein cholesterol (control mean −7.14, intervention mean 4.38; P=.01). Both groups showed significant improvement in SDSCA, BMI, waist size, and diastolic blood pressure; between-group differences were not statistically significant. Except for patients with the highest level of activation (PAM level 4), intervention group patients exhibited significant improvements in PAM scores. For patients with the lowest level of activation (PAM level 1), the intervention group showed significantly greater improvement compared with the control group in HbA_1c (control mean −0.09, intervention mean −0.52; P=.04), BMI (control mean 0.58, intervention mean −1.22; P=.01), and high-density lipoprotein cholesterol levels (control mean −4.86, intervention mean 3.56; P<.001). Significant improvements were seen in AM scores, SDSCA, and waist size for both groups and in diastolic and systolic blood pressure for the control group; the between-group differences were not statistically significant. The percentage of participants who were engaged with MHCE for ≥50% of days period was 60.7% (68/112; months 0-3), 57.4% (62/108; months 3-6), 49.5% (51/103; months 6-9), and 43% (42/98; months 9-12).

Conclusions

Our study produced mixed results with improvement in PAM scores and outcomes in both the intervention and control groups. Structural design issues may have hampered the influence of tailored behavioral messaging within the intervention group.

Trial Registration

ClinicalTrials.gov NCT02949037; https://clinicaltrials.gov/ct2/show/NCT02949037

International Registered Report Identifier (IRRID)

RR2-10.2196/resprot.6993

Development and evaluation educational videos of diabetic foot care in traditional languages to enhance knowledge of patients diagnosed with diabetes and risk for diabetic foot ulcers

AIM

This study aimed to develop an educational video for diabetic foot care in the traditional languages (Buginese and Makassarese) and evaluate the change in the patients' knowledge level after they viewed the video.

METHODS

The study was performed in the following three phases: development of the video content using a Delphi Study that involved wound-care nurses, evaluation of the video's content validity by the expert panel, and evaluation of the video in the community setting by showing it to patients who spoke the traditional languages, were diagnosed with diabetes mellitus (DM), and were at risk of diabetic foot ulcers (DFU).

RESULTS

Five themes emerged from the Delphi study, including observation of pre-ulcer signs, washing feet, cutting toenails, wearing socks, and checking footwear. Content validity evaluation recommended these items to be constructed for video education using the traditional languages. Evaluation in the community setting confirmed that there was a significant improvement (p = 0.001) in the knowledge about foot care among patients diagnosed with diabetes and at risk of DFU.

CONCLUSION

This study produced an educational video that used the trans-cultural approach by using traditional languages to overcome the communication barrier in the process of knowledge transfer. We found that the educational video in traditional languages enhanced the patients' knowledge about diabetic foot care and thus could enable them to detect the risks for DFU and prevent DFU.

Exploring app features with outcomes in mHealth studies involving chronic respiratory diseases, diabetes, and hypertension: a targeted exploration of the literature

Objectives

Limited data are available on the correlation of mHealth features and statistically significant outcomes. We sought to identify and analyze: types and categories of features; frequency and number of features; and relationship of statistically significant outcomes by type, frequency, and number of features.

Materials and Methods

This search included primary articles focused on app-based interventions in managing chronic respiratory diseases, diabetes, and hypertension. The initial search yielded 3622 studies with 70 studies meeting the inclusion criteria. We used thematic analysis to identify 9 features within the studies.

Results

Employing existing terminology, we classified the 9 features as passive or interactive. Passive features included: 1) one-way communication; 2) mobile diary; 3) Bluetooth technology; and 4) reminders. Interactive features included: 1) interactive prompts; 2) upload of biometric measurements; 3) action treatment plan/personalized health goals; 4) 2-way communication; and 5) clinical decision support system.

Discussion

Each feature was included in only one-third of the studies with a mean of 2.6 mHealth features per study. Studies with statistically significant outcomes used a higher combination of passive and interactive features (69%). In contrast, studies without statistically significant outcomes exclusively used a higher frequency of passive features (46%). Inclusion of behavior change features (ie, plan/goals and mobile diary) were correlated with a higher incident of statistically significant outcomes (100%, 77%).

Conclusion

This exploration is the first step in identifying how types and categories of features impact outcomes. While the findings are inconclusive due to lack of homogeneity, this provides a foundation for future feature analysis.

Efficacy, acceptability and feasibility of daily text-messaging in promoting glycaemic control and other clinical outcomes in a low-resource setting of South Africa: A randomised controlled trial

South Africa is confronted with a high burden of diabetes, the majority of which are poorly controlled. The use of mHealth, specifically text messaging for fostering health, is evolving and studies on its efficacy, the majority of which were conducted in developed countries, have documented mixed findings. There is no such study done amongst patients living with diabetes in the resource-poor settings of South Africa. The aim of this study is to determine the efficacy, acceptability and feasibility of text-messaging in improving glycaemic control and other clinical outcomes among individuals living with diabetes in low-resource settings in Eastern Cape, South Africa. The study adopted a multi-centre, two-arm, parallel, randomised-controlled trial design. The study was conducted amongst patients with an uncontrolled glycaemic status. Participants were randomly assigned to the intervention (n = 108) and the control arm (n = 108). Participants in the intervention arm received daily educational text messages on diabetes for six months. Data was collected at baseline and six months post-intervention. Blood glucose, blood pressure and anthropometric measurements followed standard procedure. Mixed-model analysis was used to assess the impact of the text messages on blood glucose while linear regression was used to assess its effect on other clinical outcomes such as weight, body mass index, systolic and diastolic blood pressure. The mean age of the participants was 60.64 (SD± 11.58) years. The majority of the participants had a secondary level of education (95.3%) and earned 104.80 to 991.42 USD per month (67.7%). Both arms of the study showed improvement in their blood glucose levels, but the intervention did not have any significant effect, the mean adjusted change in blood glucose was 0.26 (-0.81 to 1.32), p = 0.634. Also, the intervention did not have any significant effect on weight, body mass index, systolic and diastolic blood pressure. Almost all participants (90.74%) were pleased with the intervention and felt it was helpful. Of those who participated in the intervention, 91% completed the follow-up after 6 months. Unidirectional text-messaging was acceptable and feasible amongst adults living with diabetes in this setting. However, its efficacy in improving glycaemic status and other clinical outcomes remains doubtful. Trial Registration: Pan African Clinical Trial Registry PACTR201810599931422.

mHealth Interventions for Disadvantaged and Vulnerable People with Type 2 Diabetes

BACKGROUND

Mobile- and Internet-delivered (collectively, digital) interventions are widely used by persons with diabetes (PWD) to assist with self-management and improve/maintain glycemic control (hemoglobin A1c [A1c]). However, evidence concerning the acceptance and benefits of such interventions among disadvantaged/vulnerable PWD is still quite limited.

PURPOSE OF REVIEW

We reviewed studies published from 2011-April 2019 evaluating the impact of diabetes self-management interventions delivered via mobile device and/or Internet on glycemic control of disadvantaged/vulnerable adults with type 2 diabetes (T2D). Included studies reported ≥ 50% of the sample having a low socioeconomic status and/or being a racial/ethnic minority, or living in a rural setting or low-/middle-income country (LMIC). We identified 21 studies evaluating a digital intervention among disadvantaged/vulnerable PWD.

RECENT FINDINGS

Although many digital interventions found within-group A1c improvements (16 of 21 studies), only seven of the seventeen studies with a control group found between-group differences in A1c. Three studies found reductions in emergency room (ER) visits and hospitalizations. We synthesize this information, and provide recommendations for increasing access, and improving the design and usability of such interventions. We also discuss the role of human support in digital delivery, issues related to study design, reporting, economic value, and available research in LMICs. There is evidence suggesting that digital interventions can improve diabetes control, healthcare utilization, and healthcare costs. More research is needed to substantiate these early findings, and many issues remain in order to optimize the impact of digital interventions on the health outcomes of disadvantaged/vulnerable persons with diabetes.

Effect of mobile learning (application) on self-care behaviors and blood glucose of type 2 diabetic patients

Purpose

More than 70% of the health expenditure is related to chronic diseases. Therefore, an efficient managerial program can markedly reduce medical and administrative costs and benefit both patients and service providers. The use of mobile technologies can be very helpful in this regard. This study was conducted to determine the effect of mobile learning (application) on self-care behaviors and blood glucose control of type 2 diabetic patients attending the Diabetes Clinic of Imam Khomeini Hospital Complex.

Methods

This interventional, quasi-experimental study was conducted on 51 diabetic patients. The patients were randomly assigned to case and control groups, and a specifically designed application was used in the case group for three months. Self-care behavior, FBS, and HbA₁C were assessed in both groups before and three months after the intervention, and the results were analyzed after the intervention. The Summary of Diabetes Self-Care Activities (SDSCA) measure and medical records was used for data collection. Descriptive and inferential statics (paired t test, ANCOVA analysis) were used for data analysis.

Results

The Mean ± SD of the self-care posttest score, FBS, and HbA₁C was 76.95 ± 7.94 vs. 43.4 ± 9.74 (P = 0.001), 143.58 ± 23.39 vs. 171.81 ± 36.98 (P = 0.001), and 6.84 ± 0.63 vs. 8.10 ± 0.10 (P = 0,001), in the case and control group respectively, indicating a difference in all cases.

Conclusions

The results indicated the positive effect of the mobile application on self-care behavior, FBS, and HbA₁C.

Digital health technology and mobile devices for the management of diabetes mellitus: state of the art

Diabetes mellitus is a disease that can be difficult to manage and requires high levels of health literacy and numeracy, self-monitoring and frequent contact with clinicians. If not optimally controlled, diabetes can lead to kidney failure, blindness and cardiovascular complications, which, in turn, contribute to increasing healthcare costs. Although not yet widely used, mobile health (mHealth) tools have enhanced diabetes management and prevention and are likely to play an increasing role with the growth of smartphone ownership and medical device innovations. Recent mHealth interventions targeting type 1 and type 2 diabetes are diverse in their goals and components, and include insulin management applications, wearable blood glucose meters, automated text messages, health diaries and virtual health coaching. In this paper, we review the modalities and components of various impactful interventions for insulin management, diabetes education, self-management and prevention. More work is needed to investigate how individual demographic, socioeconomic, behavioural and clinical characteristics contribute to patient engagement and the efficacy of mHealth tools for diabetes.

Technical Guidance for Clinicians Interested in Partnering With Engineers in Mobile Health Development and Evaluation

The explosion of mobile health (mHealth) interventions has prompted significant investment and exploration that has extended past industry into academia. Although research in this space is emerging, it focuses on the clinical and population level impact across different populations. To realize the full potential of mHealth, an intimate understanding of how mHealth is being used by patients and potential differences in usage between various demographic groups must also be prioritized. In this viewpoint, we use our experiences in building an mHealth intervention that incorporates an iOS app, Bluetooth-enabled blood pressure cuff, and Apple Watch to share knowledge on (1) how user interaction data can be tracked in the context of health care privacy laws, (2) what is required for effective, nuanced communication between clinicians and engineers to design mHealth interventions that are patient-centered and have high clinical impact, and (3) how to handle and set up a process to handle user interaction data efficiently.

Design and patient characteristics of the randomized controlled trial TExT-MED + FANS A test of mHealth augmented social support added to a patient-focused text-messaging intervention for emergency department patients with poorly controlled diabetes

Although diabetes is a nationwide epidemic, US Latinos are a particularly vulnerable population. Culturally appropriate interventions can combat this disparity, especially those that increase social support. However, these interventions face significant cost and time barriers, which mHealth (mobile health) may overcome. This trial examines the benefit of adding social support to an existing text-message based, patient-focused mHealth intervention for emergency department patients with poorly controlled diabetes. Family members and friends of patients were randomized to mHealth augmented social support training (daily text-messages that synchronize with the patient messages) or a pamphlet based training (the same content mailed to their house.) We hypothesize that patients who received mHealth augmented social support will have a larger improvement in diabetes management (glycosylated hemoglobin or A1C) than those receiving standard support at six-months, and that improvement will be sustained at twelve-months. Secondary patient outcomes are clinical (weight, blood pressure), behavioral (medication adherence, self-care activities) and psychosocial (general and diabetes-specific social support, self-efficacy, diabetes-related distress, depression, fatalism and quality of life). We screened 2004 patients and enrolled 166 patient/supporter dyads. 70% of patients are Spanish-speaking, 51% female, with a mean A1C of 10.8. We employed innovative measures to remotely enroll family members and support a bilingual population, which will assist other investigators in design of similar trials. The findings of our trial will have real-world applicability for clinicians, health system administrators, health educators and mHealth developers who aim to improve the health of this vulnerable population.

Effect of Health Information Technologies on Cardiovascular Risk Factors among Patients with Diabetes

PURPOSE OF REVIEW

To identify a common effect of health information technologies (HIT) on the management of cardiovascular disease (CVD) risk factors among people with type 2 diabetes (T2D) across randomized control trials (RCT).

RECENT FINDINGS

CVD is the most frequent cause of morbidity and mortality among patients with diabetes. HIT are effective in reducing HbA1c; however, their effect on cardiovascular risk factor management for patients with T2D has not been evaluated. We identified 21 eligible studies (23 estimates) with measurement of SBP, 20 (22 estimates) of DBP, 14 (17 estimates) of HDL, 14 (17 estimates) of LDL, 15 (18 estimates) of triglycerides, and 10 (12 estimates) of weight across databases. We found significant reductions in SBP, DBP, LDL, and TG, and a significant improvement in HDL associated with HIT. As adjuvants to standard diabetic treatment, HIT can be effective tools for improving CVD risk factors among patients with T2D, especially in those whose CVD risk factors are not at goal.

The Comparative Effectiveness of Mobile Phone Interventions in Improving Health Outcomes: Meta-Analytic Review

Background

As mobile technology continues expanding, researchers have been using mobile phones to conduct health interventions (mobile health—mHealth—interventions). The multiple features of mobile phones offer great opportunities to disseminate large-scale, cost-efficient, and tailored messages to participants. However, the interventions to date have shown mixed results, with a large variance of effect sizes (Cohen d=−0.62 to 1.65).

Objective

The study aimed to generate cumulative knowledge that informs mHealth intervention research. The aims were twofold: (1) to calculate an overall effect magnitude for mHealth interventions compared with alternative interventions or conditions, and (2) to analyze potential moderators of mHealth interventions’ comparative efficacy.

Methods

Comprehensive searches of the Communication & Mass Media Complete, PsycINFO, Web of Knowledge, Academic Search Premier, PubMed and MEDLINE databases were conducted to identify potentially eligible studies in peer-reviewed journals, conference proceedings, and dissertations and theses. Search queries were formulated using a combination of search terms: “intervention” (Title or Abstract) AND “health” (Title or Abstract) AND “*phone*” OR “black-berr*” (OR mHealth OR “application*” OR app* OR mobile OR cellular OR “short messag*” OR palm* OR iPhone* OR MP3* OR MP4* OR iPod*) (Title or Abstract). Cohen d was computed as the basic unit of analysis, and the variance-weighted analysis was implemented to compute the overall effect size under a random-effects model. Analysis of variance–like and meta-regression models were conducted to analyze categorical and continuous moderators, respectively.

Results

The search resulted in 3424 potential studies, the abstracts (and full text, as necessary) of which were reviewed for relevance. Studies were screened in multiple stages using explicit inclusion and exclusion criteria, and citations were evaluated for inclusion of qualified studies. A total of 64 studies were included in the current meta-analysis. Results showed that mHealth interventions are relatively more effective than comparison interventions or conditions, with a small but significant overall weighted effect size (Cohen d=0.31). In addition, the effects of interventions are moderated by theoretical paradigm, 3 engagement types (ie, changing personal environment, reinforcement tracking, social presentation), mobile use type, intervention channel, and length of follow-up.

Conclusions

To the best of our knowledge, this is the most comprehensive meta-analysis to date that examined the overall effectiveness of mHealth interventions across health topics and is the first study that statistically tested moderators. Our findings not only shed light on intervention design using mobile phones, but also provide new directions for research in health communication and promotion using new media. Future research scholarship is needed to examine the effectiveness of mHealth interventions across various health issues, especially those that have not yet been investigated (eg, substance use, sexual health), engaging participants using social features on mobile phones, and designing tailored mHealth interventions for diverse subpopulations to maximize effects.

Effect of Multimedia Education on Nutritional Behaviour for Colorectal Cancer Prevention: An Application of Health Belief Model

Background

Colorectal cancer is a major public health problem. A way to decrease this cancer is through dietary behavioural changes. The aim of this study was to determine the effects of education on dietary behaviour based on the health belief model (HBM) using multimedia.

Methods

In this clinical trial study, 98 participants were randomly allocated to an HBM group (n = 48) and a control group (n = 50). The HBM group received an audiovisual compact disc (CD) that contained information about nutritional behaviour of colorectal cancer (CRC) prevention based on HBM that lasted 45 min. Both groups completed questionnaires regarding demographic factors, knowledge and HBM constructs, and a three-day dietary recall at the beginning of the study, 1 week after, and 3 months after the education. The outcome of this study was measured by the amount of food servings consumed and dietary micronutrient intake.

Results

At the baseline, there were no significant differences between groups regarding demographic factors. Findings showed that self-efficacy (P < 0.001), severity (P < 0.001), and benefits (P < 0.001) were perceived to be higher, and knowledge (P < 0.001) was increased in the HBM group compared to control group 3 months after education. There was a significant increase in fruit and vegetable (P < 0.001) and dairy (P = 0.001) intake and a significant decrease in red meat servings (P = 0.016) in the HBM group compared to the control group. Also, intake of vitamin D (P < 0.001), folate (P < 0.001), calcium (P = 0.008), and dietary fibre (P < 0.001) was increased in the HBM group compared to the control group 3 months after education.

Conclusion

Education plans based on HBM and implemented through multimedia can change nutritional beliefs and behaviours for the prevention of colorectal cancer.

Improving Self-Management Skills Among People With Spinal Cord Injury: Protocol for a Mixed-Methods Study

Background

Most people with spinal cord injury will develop secondary complications with potentially devastating consequences. Self-management is a key prevention strategy for averting the development of secondary complications and their recurrence. Several studies have shown that self-management programs improve self-management behaviors and health outcomes in individuals living with chronic conditions such as asthma, diabetes, hypertension, and arthritis. Given the burgeoning health care costs related to secondary complications, we developed an alternative electronic health–based implementation to facilitate the development of self-management skills among people with spinal cord injury.

Objective

This study aims to evaluate the efficacy of a self-management app in spinal cord injury populations. The primary outcome is attainment of self-selected, self-management goals. Secondary outcomes include increases in general and self-management self-efficacy and reductions in self-reported health events, health care utilization, and secondary complications related to spinal cord injury. This study also aims to explore how the intervention was implemented and how the app was experienced by end users.

Methods

This study will employ a mix of qualitative and quantitative methods. The quantitative portion of our study will involve a rater-blinded, randomized controlled trial with a stepped wedge design (ie, delayed intervention control group). The primary outcome is successful goal attainment, and secondary outcomes include increases in self-efficacy and reductions in self-reported health events, health care utilization, and secondary conditions related to spinal cord injury. The qualitative portion will consist of semistructured interviews with a subsample of the participants.

Results

We expect that the mobile self-management app will help people with spinal cord injury to attain their self-management goals, improve their self-efficacy, reduce secondary complications, and decrease health care utilization.

Conclusions

If the results are positive, this study will produce credible new knowledge describing multiple outcomes that people with spinal cord injury realize from an app-based self-management intervention and support its implementation in clinical practice.

Trial Registration

ClinicalTrials.gov NCT03140501; http://clinicaltrials.gov/ct2/show/NCT03140501 (Archived by WebCite at http://www.webcitation.org/73Gw0ZlWZ)

International Registered Report Identifier (IRRID)

PRR1-10.2196/11069

Perceptions of Family Among Low-Income Patients With Diabetes in a Text-Based Mobile Health Intervention

BACKGROUND

Diabetes disproportionately affects the US Latino population, due to socioeconomic pressures, genetics, reduced access to care and cultural practices. While efforts to improve self-care through interventions incorporating family are highly rated by Latinos, family can be both supportive and obstructive. To develop effective interventions, this role needs clarification.

METHODS

We conducted group interviews in Spanish and English with 24 participants with diabetes from a mobile health diabetes self-care intervention. We imported transcripts into Dedoose, a qualitative computer analysis program and analyzed them with a modified grounded theory technique. Utilizing an iterative process, we reexamined transcripts with new codes derived in each round of analysis until saturation was reached. We employed techniques to improve trustworthiness (co-coding, member checking). Broad categorical themes arose from the initial codes and were developed into a conceptual model of barriers to and strategies for diabetes management.

RESULTS

Family and family responsibilities emerged as both a supportive and obstructive force for diabetes self-care. While the desire to care for family motivated patients, food at family gatherings and pressure from managing multiple family responsibilities contributed to poor diet choices. Yet, some patients believed their diabetes caused their immediate family to make healthier choices.

CONCLUSIONS

Among these predominantly Latino patients, family and family responsibilities were key motivators as well as obstacles to self-care, particularly regarding nutrition. Finding the ideal design for social support mHealth-based interventions will require careful study and creation of culturally based programs to match the needs of specific populations, and may require educating family members to provide effective social support.

Effect of Health Information Technologies on Glycemic Control Among Patients with Type 2 Diabetes

PURPOSE OF REVIEW

This study was to present meta-analysis findings across selected clinical trials for the effect of health information technologies (HITs) on glycemic control among patients with type 2 diabetes.

RECENT FINDINGS

HITs may be promising in diabetes management. However, findings on effect size of glycated hemoglobin level (HbA1c) yielded from HITs varied across previous studies. This is likely due to heterogeneity in sample size, adherence to standard quantitative method, and/or searching criteria (e.g., type of HITs, type of diabetes, specification of patient population, randomized vs. nonrandomized trials). We systematically searched Medline, Cumulative Index of Nursing and Allied Health Literature (CINAHL), and the Cochrane Library for peer-reviewed randomized control trials that studied the effect of HITs on HbA1c reduction. We also used Google Scholar and a hand search to identify additional studies. Thirty-four studies (40 estimates) met the criteria and were included in the analysis. Overall, introduction of HITs to standard diabetes treatment resulted in a statistically and clinically reduced HbA1c. The bias adjusted HbA1c reduction due to the combined HIT interventions was - 0.56 [Hedges' g = - 0.56 (- 0.70, - 0.43)]. The reduction was significant across each of the four types of HIT intervention under review, with mobile phone-based approaches generating the largest effects [Hedges' g was - 0.67 (- 0.90, - 0.45)]. HITs can be an effective tool for glycemic control among patients with type 2 diabetes. Future studies should examine long-term effects of HITs and explore factors that influence their effectiveness.

Clinical Effectiveness of Telemedicine in Diabetes Mellitus: A Meta-Analysis of 42 Randomized Controlled Trials

Background: Telemedicine is instrumental in improving diabetes patient care, as well as providing significant cost benefits. This meta-analysis was conducted to compare the effectiveness of telemedicine intervention with usual care in diabetes patients. Methods: Randomized controlled trials (RCTs) reporting a change in HbA1c after usual care and telemedicine intervention were retrieved from electronic databases. Results: Data on 6,170 participants (mean age 13.3 to 71.0 years), with 3,128 randomized to usual care and 3,042 to telemedicine intervention, were retrieved from 42 RCTs. Eight studies used teleconsultation, while 34 used telemonitoring (device based). Nine studies enrolled both type 1 and type 2 diabetes patients, 21 focused on type 2 diabetes patients, and 12 on type 1 diabetes patients. The mean reduction in HbA1c was significantly higher in the telemedicine groups (Hedges' g = -0.37, p < 0.001). Type 2 diabetes patients experienced a higher reduction in HbA1c compared to type 1 diabetes patients (Hedges' g = -0.48, p < 0.001 vs. -0.26, p < 0.05; Q = 1935.75, p < 0.0001). Older patients (41-50 years, Hedges' g = -1.82, p < 0.001; >50 years, Hedges' g = -1.05, p < 0.001) benefited more than their younger counterparts (Hedges' g = -0.84, p = 0.07). Telemedicine programs lasting >6 months produced a significantly greater reduction in HbA1c levels (Hedges' g = -2.24 vs. -0.66, p < 0.001). Conclusion: Telemedicine interventions are more effective than usual care in managing diabetes, especially type 2 diabetes. Furthermore, older patients and a longer duration of intervention provide superior results.

Impact of Short Message Service (SMS) Education Based on a Health Promotion Model on the Physical Activity of Patients with Type II Diabetes

INTRODUCTION

Physical activity is the most important self-management behaviour in diabetes. The aim of this study was to evaluate the impact of a short message service (SMS) based on a health promotion model (HPM) on the physical activity of diabetic patients.

METHODS

This quasi-experimental study consisted of 37 type II diabetes patients in an SMS group and 36 type II diabetes patients in a control group. The patients in both groups completed written consent forms and questionnaires at the beginning of the study. The patients in the SMS group received training messages within two weeks (two or three messages daily) in the field of physical activity based on HPM constructs. Both groups completed questionnaires in three stages (at the beginning of the study, four weeks after the first visit, and three months later) comprising demographic factors, questions regarding the constructs, and 7-day physical activity recall. After data collection, statistical analysis was conducted using an independent t-test, a Chi-square test, and a repeated measures analysis of variance (ANOVA).

RESULTS

As compared with the control group, changes in mean scores of perceived self-efficacy (P = 0.001) and family support (P = 0.046) of physical activity in the training group were significantly greater and perceived barriers (P < 0.001) were significantly lower over time. The physical activity performance of the SMS group was better three months after training as compared with that of the control group (P < 0.001).

CONCLUSION

The results demonstrated the efficacy of training messages in changing the beliefs and physical activity behaviours of diabetic patients.

Video-based patient decision aids: A scoping review

OBJECTIVE

This study reviews the published literature on the use of video-based decision aids (DA) for patients. The authors describe the areas of medicine in which video-based patient DA have been evaluated, the medical decisions targeted, their reported impact, in which countries studies are being conducted, and publication trends.

METHOD

The literature review was conducted systematically using Medline, Embase, CINAHL, PsychInfo, and Pubmed databases from inception to 2016. References of identified studies were reviewed, and hand-searches of relevant journals were conducted.

RESULTS

488 studies were included and organized based on predefined study characteristics. The most common decisions addressed were cancer screening, risk reduction, advance care planning, and adherence to provider recommendations. Most studies had sample sizes of fewer than 300, and most were performed in the United States. Outcomes were generally reported as positive. This field of study was relatively unknown before 1990s but the number of studies published annually continues to increase.

CONCLUSION

Videos are largely positive interventions but there are significant remaining knowledge gaps including generalizability across populations.

PRACTICE IMPLICATIONS

Clinicians should consider incorporating video-based DA in their patient interactions. Future research should focus on less studied areas and the mechanisms underlying effective patient decision aids.

A Mobile App to Improve Self-Management of Individuals With Type 2 Diabetes: Qualitative Realist Evaluation

BACKGROUND

The increasing use of Web-based solutions for health prevention and promotion presents opportunities to improve self-management and adherence to guideline-based therapy for individuals with type 2 diabetes (T2DM). Despite promising preliminary evidence, many users stop using Web-based solutions due to the burden of data entry, hidden costs, loss of interest, and a lack of comprehensive features. Evaluations tend to focus on effectiveness or impact and fail to evaluate the nuanced variables that may interact to contribute to outcome success (or failure).

OBJECTIVE

This study aimed to evaluate a Web-based solution for improving self-management in T2DM to identify key combinations of contextual variables and mechanisms of action that explain for whom the solution worked best and in what circumstances.

METHODS

A qualitative realist evaluation was conducted with one-on-one, semistructured telephonic interviews completed at baseline, and again toward the end of the intervention period (3 months). Topics included participants' experiences of using the Web-based solution, barriers and facilitators of self-management, and barriers and facilitators to effective use. Transcripts were analyzed using thematic analysis strategies, after which the key themes were used to develop statements of the relationships between the key contextual factors, mechanisms of action, and impact on the primary outcome (glycated hemoglobin, HbA_1c).

RESULTS

Twenty-six interviews (14 baseline, 12 follow-up) were completed with 16 participants with T2DM, and the following 3 key groups emerged: the easiest fit, the best fit, and those who failed to activate. Self-efficacy and willingness to engage with the solution facilitated improvement in HbA_1c, whereas competing priorities and psychosocial issues created barriers to engagement. Individuals with high baseline self-efficacy who were motivated, took ownership for their actions, and prioritized diabetes management were early and eager adopters of the app and recorded improvements in HbA_1c over the intervention period. Individuals with moderate baseline self-efficacy and no competing priorities, who identified gaps in understanding of how their actions influence their health, were slow to adopt use but recorded the greatest improvements in HbA_1c. The final group had low baseline self-efficacy and identified a range of psychosocial issues and competing priorities. These participants were uncertain of the benefits of using a Web-based solution to support self-management, ultimately resulting in minimal engagement and no improvement in HbA_1c.

CONCLUSIONS

Self-efficacy, competing priorities, previous behavior change, and beliefs about Web-based solutions interact to determine engagement and impact on the clinical outcomes. Considering the balance of these patient characteristics is likely to help health care providers identify individuals who are apt to benefit from a Web-based solution to support self-management of T2DM. Web-based solutions could be modified to incorporate the existing screening measures to identify individuals who are at risk of suboptimal adherence to inform the provision of additional support(s) as needed.

Effects of consumer-oriented health information technologies in diabetes management over time: a systematic review and meta-analysis of randomized controlled trials

Objective

To reveal the effects of consumer-oriented health information technologies (CHITs) on patient outcomes in diabetes management over time through systematic review and meta-analysis.

Methods

We searched 5 electronic databases (from database inception to July 2016) for studies that reported on randomized controlled trials examining the effects of CHITs on glycemic control and other patient outcomes in diabetes management. Data were analyzed using either meta-analysis or a narrative synthesis approach.

Results

Eighty randomized controlled trial studies, representing 87 individual trials, were identified and included for analysis. Overall, the meta-analysis showed that the use of CHITs resulted in significant improvement in glycemic control compared to usual care (standardized mean difference = -0.31%, 95% confidence interval -0.38 to -0.23, P  < .001) in patients with diabetes. Specifically, improvement in glycemic control was significant at intervention durations of 3, 6, 8, 9, 12, 15, 30, and 60 months, while no significant differences were found at other time points reported. The narrative synthesis provided mixed effects of CHITs on other clinical, psychosocial, behavioral, and knowledge outcomes.

Conclusions

The use of CHITs appears to be more effective than usual care in improving glycemic control for patients with diabetes. However, their effectiveness did not remain consistent over time and in other patient outcomes. Further efforts are required to examine long-term effects of CHITs and to explore factors that can moderate the effects over time.

Effect of Telephone Follow-up by Nurses on Self-care in Children with Diabetes

Background

Diabetes is a serious chronic disease during childhood. Because of the chronic nature of the disease, self-care is necessary. Education alone is not effective in providing care. Misunderstanding by the patients regarding diabetes during the training programs render telephone follow-up after training essential.

Materials and Methods

This quasi-experimental study with two groups (experimental and control) was conducted in two phases in 2014. The study population consisted of 70 children of 10-18 years of age with type I diabetes (35 patients in the experimental group and 35 in the control group). The participants were randomly selected from the patients referring to the Sedigheh Tahereh Diabetic Research and Treatment Center in Isfahan, Iran. Data were collected using a researcher-made questionnaire on self-care and a glycosylated hemoglobin recording form. The experimental group received 12 weeks of telephone follow-up training by the center, whereas the control group received no follow-up.

Results

The results showed that, after intervention, the total mean score of self-care in all aspects of diabetes care for children was significantly higher in the experimental group (p < 0.001). In addition, a statistically significant difference was observed between the experimental and control groups in terms of mean glycosylated hemoglobin after the intervention (p = 0.030).

Conclusions

It can be concluded that telephone follow-up by a nurse can improve total self-care and glycosylated hemoglobin in patients with type I diabetes.

Effect of electronic education based on health promotion model on physical activity in diabetic patients

BACKGROUND

By high prevalence of inactivity, particularly in diabetic patients, the need to effective interventions to promote physical activity is essential. The aim of this study was to determine the effects of education based on health promotion model (HPM) through multimedia on the physical activity in diabetic patients.

METHOD

In this quasi-experimental study, 76 patients with type II diabetes were evaluated (40 patents in intervention group and 36 patients in control group). The intervention group members and a friend or a family member, that could be supportive in physical activity, received teaching CD based on health promotion model. Both group members at the beginning of the study, two weeks and three months after the training, completed questionnaires. After data collection, statistical analysis was conducted using independent T-test, chi-square test, and repeated measurement of ANOVA.

RESULTS

Finding showed that self-efficacy (P<0.001), health status (p=0.032), benefits (P<0.001) and friends support in physical activity (P<0.001) were perceived to be higher, and barrier of physical activity (P<0.001) was perceived to be lower in multimedia group compared to control group 3 months after training. There was a significant difference in average of metabolic equivalent of task (MET) between two groups after the intervention (P<0.001).

CONCLUSION

Planning of education based on the HPM and implementation through multimedia can change belief about physical activity and increase participation in physical activity.

Using Mobile Health to Improve Social Support for Low-Income Latino Patients with Diabetes: A Mixed-Methods Analysis of the Feasibility Trial of TExT-MED + FANS

BACKGROUND

Social support interventions can improve diabetes self-care, particularly for Latinos, but are time and resource intensive. Mobile health may overcome these barriers by engaging and training supporters remotely.

METHODS

We conducted a randomized controlled feasibility trial of emergency department patients with diabetes to determine the feasibility of enrolling patients and supporters, acceptability of the intervention, and preliminary efficacy results to power a larger trial. All patients received an existing mHealth curriculum (TExT-MED). After identifying a supporter, patients were randomized to intervention: supporters receiving FANS (family and friends network support), a text message support curriculum synchronized to patient messages, or control: supporters receiving a mailed pamphlet of the same information. Participants followed up at 3 months. FANS intervention participants came to postintervention interviews as part of a qualitative analysis.

RESULTS

We enrolled 44 patients (22 per arm) and followed up 36 at 3 months. Participants were positive about the program. FANS intervention improved HbA1c (intervention mean decreased from 10.4% to 9.0% vs. from 10.1% to 9.5%, delta -0.8%, confidence interval [CI] -0.4 to 2, P = 0.30), self-monitoring of glucose (intervention increased 1.6 days/week vs. control decreased 2 days/week, delta 2.3 days/week, CI 4-0.6, P = 0.02), and physical activity (mean Godin leisure time activity score improved 16.1 vs. decreased 9.6 for control, delta 25.7, CI 49.2-2.3, P = 0.10). In qualitative analysis, patients reported improved motivation, behaviors, and relationships. Supporters reported making healthier decisions for themselves.

CONCLUSIONS

mHealth is a feasible, acceptable, and promising avenue to improve social support and diabetes outcomes.

Characterising smoking cessation smartphone applications in terms of behaviour change techniques, engagement and ease-of-use features

The aim of this study was to assess whether or not behaviour change techniques (BCTs) as well as engagement and ease-of-use features used in smartphone applications (apps) to aid smoking cessation can be identified reliably. Apps were coded for presence of potentially effective BCTs, and engagement and ease-of-use features. Inter-rater reliability for this coding was assessed. Inter-rater agreement for identifying presence of potentially effective BCTs ranged from 66.8 to 95.1 % with ‘prevalence and bias adjusted kappas’ (PABAK) ranging from 0.35 to 0.90 (p < 0.001). The intra-class correlation coefficients between the two coders for scores denoting the proportions of (a) a set of engagement features and (b) a set of ease-of-use features, which were included, were 0.77 and 0.75, respectively (p < 0.001). Prevalence estimates for BCTs ranged from <10 % for medication advice to >50 % for rewarding abstinence. The average proportions of specified engagement and ease-of-use features included in the apps were 69 and 83 %, respectively. The study found that it is possible to identify potentially effective BCTs, and engagement and ease-of-use features in smoking cessation apps with fair to high inter-rater reliability.

Using Mobile Health (mHealth) Technology in the Management of Diabetes Mellitus, Physical Inactivity, and Smoking

PURPOSE OF REVIEW

Cardiovascular mortality remains high due to insufficient progress made in managing cardiovascular risk factors such as diabetes mellitus, physical inactivity, and smoking. Healthy lifestyle choices play an important role in the management of these modifiable risk factors. Mobile health or mHealth is defined as the use of mobile computing and communication technologies (i.e., mobile phones, wearable sensors) for the delivery of health services and health-related information. In this review, we examine some recent studies that utilized mHealth tools to improve management of these risk factors, with examples from developing countries where available.

RECENT FINDINGS

The mHealth intervention used depends on the availability of resources. While developing countries are often restricted to text messages, more resourceful settings are shifting towards mobile phone applications and wearable technology. Diabetes mellitus has been extensively studied in different settings, and results have been encouraging. Tools utilized to increase physical activity are expensive, and studies have been limited to resource-abundant areas and have shown mixed results. Smoking cessation has had promising initial results with the use of technology, but mHealth's ability to recruit participants beyond those actively seeking to quit has not been established. mHealth interventions appear to be a potential tool in improving control of cardiovascular risk factors that rely on individuals making healthy lifestyle choices. Data related to clinical impact, if any, of commercially available tools is lacking. More studies are needed to assess interventions that target multiple cardiovascular risk factors and their impact on hard cardiovascular outcomes.

mHealth Application Areas and Technology Combinations*. A Comparison of Literature from High and Low/Middle Income Countries

BACKGROUND

With the continuous and enormous spread of mobile technologies, mHealth has evolved as a new subfield of eHealth. While eHealth is broadly focused on information and communication technologies, mHealth seeks to explore more into mobile devices and wireless communication. Since mobile phone penetration has exceeded other infrastructure in low and middle-income countries (LMICs), mHealth is seen as a promising component to provide pervasive and patient-centered care.

OBJECTIVES

The aim of our research work for this paper is to examine the mHealth literature to identify application areas, target diseases, and mHealth service and technology types that are most appropriate for LMICs.

METHODS

Based on the 2011 WHO mHealth report, a combination of search terms, all including the word "mHealth", was identified. A literature review was conducted by searching the PubMed and IEEE Xplore databases. Articles were included if they were published in English, covered an mHealth solution/ intervention, involved the use of a mobile communication device, and included a pilot evaluation study. Articles were excluded if they did not provide sufficient detail on the solution covered or did not focus on clinical efficacy/effectiveness. Cross-referencing was also performed on included articles.

RESULTS

842 articles were retrieved and analyzed, 255 of which met the inclusion criteria. North America had the highest number of applications (n=74) followed by Europe (n=50), Asia (n=44), Africa (n=25), and Australia (n=9). The Middle East (n=5) and South America (n=3) had the least number of studies. The majority of solutions addressed diabetes (n=51), obesity (n=25), CVDs (n=24), HIV (n=18), mental health (n=16), health behaviors (n=16), and maternal and child's health (MCH) (n=11). Fewer solutions addressed asthma (n=7), cancer (n=5), family health planning (n=5), TB (n=3), malaria (n=2), chronic obtrusive pulmonary disease (COPD) (n=2), vision care (n=2), and dermatology (n=2). Other solutions targeted stroke, dental health, hepatitis vaccination, cold and flu, ED prescribed antibiotics, iodine deficiency, and liver transplantation (n=1 each). The remainder of solutions (n=14) did not focus on a certain disease. Most applications fell in the areas of health monitoring and surveillance (n=93) and health promotion and raising awareness (n=88). Fewer solutions addressed the areas of communication and reporting (n=11), data collection (n=6), telemedicine (n=5), emergency medical care (n=3), point of care support (n=2), and decision support (n=2). The majority of solutions used SMS messaging (n=94) or mobile apps (n=71). Fewer used IVR/phone calls (n=8), mobile website/email (n=5), videoconferencing (n=2), MMS (n=2), or video (n=1) or voice messages (n=1). Studies were mostly RCTs, with the majority suffering from small sample sizes and short study durations. Problems addressed by solutions included travel distance for reporting, self-management and disease monitoring, and treatment/medication adherence.

CONCLUSIONS

SMS and app solutions are the most common forms of mHealth applications. SMS solutions are prevalent in both high and LMICs while app solutions are mostly used in high income countries. Common application areas include health promotion and raising awareness using SMS and health monitoring and surveillance using mobile apps. Remaining application areas are rarely addressed. Diabetes is the most commonly targeted medical condition, yet remains deficient in LMICs.

Improving Glycemic Control With a Standardized Text-Message and Phone-Based Intervention: A Community Implementation

Background

Type II diabetes mellitus (T2DM) presents a major disease burden in the United States. Outpatient glycemic control among patients with T2DM remains difficult. Telemedicine shows great potential as an adjunct therapy to aid in glycemic control in real-world settings.

Objective

We aimed to explore the effectiveness of EpxDiabetes, a novel digital health intervention, in improving hemoglobin A1c (HbA1c) and fasting blood glucose (FBG) among patients with uncontrolled diabetes.

Methods

We recruited 396 patients from a community clinic in St. Louis, Missouri, from a database of patients diagnosed with T2DM and with a most recent HbA1c >7% as part of a quality improvement project. An automated call or text-messaging system was used to monitor patient-reported FBG. If determined to be elevated, care managers were notified by email, text, or electronic medical record alert. Participants self-reported their FBG data by replying to EpxDiabetes automated phone calls or text messages. Data were subsequently analyzed, triaged, and shared with providers to enable appropriate follow-up and care plan adjustments. Absolute HbA1c reduction, patient engagement, and absolute patient-reported FBG reduction were examined at approximately 6 months post implementation.

Results

EpxDiabetes had an average 95.6% patient response rate to messages at least once per month and an average 71.1% response rate to messages at least once per week. Subsequent HbA1c drop with EpxDiabetes use over 4 months was -1.15% (95% CI -1.58 to -0.71) for patients with HbA1c >8% at baseline compared to the change in HbA1c over 4 months prior to the implementation of EpxDiabetes of only -0.005 points (95% CI -0.28 to 0.27), P=.0018.

Conclusions

EpxDiabetes may help reduce HbA1c in patients with high HbA1c baselines (>8%). The intervention demonstrates high patient engagement sustainable for at least 6 months.

Comparison of the Acceptance of Telemonitoring for Glucose Management Between South Korea and China

BACKGROUND

Telemonitoring is used for glucose management and support in many countries. A better understanding of the differences in telemonitoring acceptance based on regional characteristics is needed. Therefore, we compared the acceptance of telemonitoring for glucose management among patients in South Korea and China.

MATERIALS AND METHODS

This study used data from Korean (n = 81) and Chinese (n = 92) subjects with type 2 diabetes. We used two independent sample t-tests to compare patients' perceptions of telemonitoring and multiple regression analysis to determine the factors that affected their behavioral intentions to use telemonitoring. We conducted Wilcoxon signed rank tests to assess the differences in hemoglobin A1c (HbA1c) levels from baseline to follow-up.

RESULTS

Although Korean and Chinese patients had positive perceptions of the services, different factors influenced their behavioral intentions to use them. In South Korea, performance expectations and social influences were significantly associated with intention to use telemonitoring. Patients younger than 50 years showed a significant decrease in HbA1c levels at month 6 (p < 0.05). In China, effort expectancy and facilitating conditions were significantly associated with intention to use. In addition, subjects in all age groups exhibited a significant decrease in HbA1c levels at all follow-up points (p < 0.001).

CONCLUSION

Telemonitoring was a supportive intervention in improving blood sugar levels among patients with diabetes in South Korea and China, but the factors influencing its use varied. We provide practical guidance for developing telemonitoring for glucose management that considers the distinct characteristics of different countries.

A Systematic Review of Application and Effectiveness of mHealth Interventions for Obesity and Diabetes Treatment and Self-Management

The use of mobile and wireless technologies and wearable devices for improving health care processes and outcomes (mHealth) is promising for health promotion among patients with chronic diseases such as obesity and diabetes. This study comprehensively examined published mHealth intervention studies for obesity and diabetes treatment and management to assess their effectiveness and provide recommendations for future research. We systematically searched PubMed for mHealth-related studies on diabetes and obesity treatment and management published during 2000-2016. Relevant information was extracted and analyzed. Twenty-four studies met inclusion criteria and varied in terms of sample size, ethnicity, gender, and age of the participating patients and length of follow-up. The mHealth interventions were categorized into 3 types: mobile phone text messaging, wearable or portable monitoring devices, and applications running on smartphones. Primary outcomes included weight loss (an average loss ranging from -1.97 kg in 16 wk to -7.1 kg in 5 wk) or maintenance and blood glucose reduction (an average decrease of glycated hemoglobin ranging from -0.4% in 10 mo to -1.9% in 12 mo); main secondary outcomes included behavior changes and patient perceptions such as self-efficacy and acceptability of the intervention programs. More than 50% of studies reported positive effects of interventions based on primary outcomes. The duration or length of intervention ranged from 1 wk to 24 mo. However, most studies included small samples and short intervention periods and did not use rigorous data collection or analytic approaches. Although some studies suggest that mHealth interventions are effective and promising, most are pilot studies or have limitations in their study designs. There is an essential need for future studies that use larger study samples, longer intervention (≥ 6 mo) and follow-up periods (≥ 6 mo), and integrative and personalized innovative mobile technologies to provide comprehensive and sustainable support for patients and health service providers.

Mobile health as a viable strategy to enhance stroke risk factor control: A systematic review and meta-analysis

BACKGROUND

With the rapid growth worldwide in cell-phone use, Internet connectivity, and digital health technology, mobile health (mHealth) technology may offer a promising approach to bridge evidence-treatment gaps in stroke prevention. We aimed to evaluate the effectiveness of mHealth for stroke risk factor control through a systematic review and meta-analysis.

METHODS

We searched PubMed from January 1, 2000 to May 17, 2016 using the following keywords: mobile health, mHealth, short message, cellular phone, mobile phone, stroke prevention and control, diabetes mellitus, hypertension, hyperlipidemia and smoking cessation. We performed a meta-analysis of all eligible randomized control clinical trials that assessed a sustained (at least 6months) effect of mHealth.

RESULTS

Of 78 articles identified, 13 met eligibility criteria (6 for glycemic control and 7 for smoking cessation) and were included for the final meta-analysis. There were no eligible studies for dyslipidemia or hypertension. mHealth resulted in greater Hemoglobin A1c reduction at 6months (6 studies; 663 subjects; SMD: -0.44; 95% CI: [-0.82, -0.06], P=0.02; Mean difference of decrease in HbA1c: -0.39%; 95% CI: [-0.74, -0.04], P=0.03). mHealth also lead to relatively higher smoking abstinence rates at 6months (7 studies; 9514 subjects; OR: 1.54; 95% CI: [1.24, 1.90], P<0.0001).

CONCLUSIONS

Our meta-analysis supports that use of mHealth improves glycemic control and smoking abstinence rates.

Effect of telemedicine on glycated hemoglobin in diabetes: a systematic review and meta-analysis of randomized trials

BACKGROUND

Telemedicine, the use of telecommunications to deliver health services, expertise and information, is a promising but unproven tool for improving the quality of diabetes care. We summarized the effectiveness of different methods of telemedicine for the management of diabetes compared with usual care.

METHODS

We searched MEDLINE, Embase and the Cochrane Central Register of Controlled Trials databases (to November 2015) and reference lists of existing systematic reviews for randomized controlled trials (RCTs) comparing telemedicine with usual care for adults with diabetes. Two independent reviewers selected the studies and assessed risk of bias in the studies. The primary outcome was glycated hemoglobin (HbA1C) reported at 3 time points (≤ 3 mo, 4-12 mo and > 12 mo). Other outcomes were quality of life, mortality and episodes of hypoglycemia. Trials were pooled using randomeffects meta-analysis, and heterogeneity was quantified using the I2 statistic.

RESULTS

From 3688 citations, we identified 111 eligible RCTs (n = 23 648). Telemedicine achieved significant but modest reductions in HbA1C in all 3 follow-up periods (difference in mean at ≤ 3 mo: -0.57%, 95% confidence interval [CI] -0.74% to -0.40% [39 trials]; at 4-12 mo: -0.28%, 95% CI -0.37% to -0.20% [87 trials]; and at > 12 mo: -0.26%, 95% CI -0.46% to -0.06% [5 trials]). Quantified heterogeneity (I2 statistic) was 75%, 69% and 58%, respectively. In meta-regression analyses, the effect of telemedicine on HbA1C appeared greatest in trials with higher HbA1C concentrations at baseline, in trials where providers used Web portals or text messaging to communicate with patients and in trials where telemedicine facilitated medication adjustment. Telemedicine had no convincing effect on quality of life, mortality or hypoglycemia.

INTERPRETATION

Compared with usual care, the addition of telemedicine, especially systems that allowed medication adjustments with or without text messaging or a Web portal, improved HbA1C but not other clinically relevant outcomes among patients with diabetes.

Barriers to Remote Health Interventions for Type 2 Diabetes: A Systematic Review and Proposed Classification Scheme

Background

Diabetes self-management involves adherence to healthy daily habits typically involving blood glucose monitoring, medication, exercise, and diet. To support self-management, some providers have begun testing remote interventions for monitoring and assisting patients between clinic visits. Although some studies have shown success, there are barriers to widespread adoption.

Objective

The objective of our study was to identify and classify barriers to adoption of remote health for management of type 2 diabetes.

Methods

The following 6 electronic databases were searched for articles published from 2010 to 2015: MEDLINE (Ovid), Embase (Ovid), CINAHL, Cochrane Central, Northern Light Life Sciences Conference Abstracts, and Scopus (Elsevier). The search identified studies involving remote technologies for type 2 diabetes self-management. Reviewers worked in teams of 2 to review and extract data from identified papers. Information collected included study characteristics, outcomes, dropout rates, technologies used, and barriers identified.

Results

A total of 53 publications on 41 studies met the specified criteria. Lack of data accuracy due to input bias (32%, 13/41), limitations on scalability (24%, 10/41), and technology illiteracy (24%, 10/41) were the most commonly cited barriers. Technology illiteracy was most prominent in low-income populations, whereas limitations on scalability were more prominent in mid-income populations. Barriers identified were applied to a conceptual model of successful remote health, which includes patient engagement, patient technology accessibility, quality of care, system technology cost, and provider productivity. In total, 40.5% (60/148) of identified barrier instances impeded patient engagement, which is manifest in the large dropout rates cited (up to 57%).

Conclusions

The barriers identified represent major challenges in the design of remote health interventions for diabetes. Breakthrough technologies and systems are needed to alleviate the barriers identified so far, particularly those associated with patient engagement. Monitoring devices that provide objective and reliable data streams on medication, exercise, diet, and glucose monitoring will be essential for widespread effectiveness. Additional work is needed to understand root causes of high dropout rates, and new interventions are needed to identify and assist those at the greatest risk of dropout. Finally, future studies must quantify costs and benefits to determine financial sustainability.

A Systematic Review of mHealth-Based Heart Failure Interventions

BACKGROUND

The popularity of mobile phones and similar mobile devices makes it an ideal medium for delivering interventions. This is especially true with heart failure (HF) interventions, in which mHealth-based HF interventions are rapidly replacing their telephone-based predecessors.

PURPOSE

This systematic review examined the impact of mHealth-based HF management interventions on HF outcomes. The specific aims of the systematic review are to (1) describe current mHealth-based HF interventions and (2) discuss the impact of these interventions on HF outcomes.

METHODS

PubMed, CINAHL Plus, EMBASE, PsycINFO, and Scopus were systematically searched for randomized controlled trials or quasi-experimental studies that tested mHealth interventions in people with HF using the terms Heart Failure, Mobile Health, mHealth, Telemedicine, Text Messaging, Texting, Short Message Service, Mobile Applications, and Mobile Apps.

CONCLUSIONS

Ten articles, representing 9 studies, were included in this review. The majority of the studies utilized mobile health technology as part of an HF monitoring system, which typically included a blood pressure-measuring device, weighing scale, and an electrocardiogram recorder. The impact of the mHealth interventions on all-cause mortality, cardiovascular mortality, HF-related hospitalizations, length of stay, New York Heart Association functional class, left ventricular ejection fraction, quality of life, and self-care were inconsistent at best.

IMPLICATIONS

Further research is needed to conclusively determine the impact of mHealth interventions on HF outcomes. The limitations of the current studies (eg, inadequate sample size, quasi-experimental design, use of older mobile phone models, etc) should be taken into account when designing future studies.

Social Networking Services-Based Communicative Care for Patients with Diabetes Mellitus in Korea

OBJECTIVES

Social networking services (SNS)-based online communities are good examples of improving quality of care by incorporating information technology into medicine. Therefore, we created an SNS-based community care webpage for communication among patients with diabetes mellitus (DM). We aimed to identify what diabetic patients wanted to know and were interested in by analyzing their posts and classified content in which users were interested.

METHODS

As opposed to the existing physician-focused health information websites, we built a patient-focused experience exchange website, "I love insulin (http://www.iloveinsulin.co.kr)." The DM communication webpage was divided into "My Web-Chart," "My community-free board," and "Life & Health." The contents analysis targeted users' postings, and replies were classified by theme from May 2012 to June 2013. The data included number of questions asked, answers, and question-to-answer (QA) ratio in each category.

RESULTS

A total of 264 patients registered on the "I Love Insulin" website. The most frequent topic of posts classified as questions were about diabetes itself (23%), diet (22%), and glucose levels (19%). Conversely, most answers and information provided by users were about daily life with no relationship to diabetes mellitus (54%). While there were many questions about diet, there were very few answers (2%). Whereas there was much provision of knowledge about general DM, sharing diet information was rare. The ratios of answers to questions on diet (ratio=0.059, 1/17), glucose level (ratio=0.067, 1/15), insulin regulation (ratio=0.222, 2/9) and webpage (ratio=0.167, 1/6) were significantly low compared to DM itself (all p < 0.001).

DISCUSSION

Patients in Korea with DM tend to have insufficient knowledge about diet and insulin regulation; continuously providing diet and insulin regulation information are desirable. It is hoped that the patients would be motivated to participate actively by "knowledge sharing." Through this process, patients learn about their diseases not from the physicians but from among themselves.

Gerontechnologies for Older Patients with Heart Failure: What is the Role of Smartphones, Tablets, and Remote Monitoring Devices in Improving Symptom Monitoring and Self-Care Management?

Older adults with heart failure have multiple chronic conditions and a large number and range of symptoms. A fundamental component of heart failure self-care management is regular symptom monitoring. Symptom monitoring can be facilitated by cost-effective, easily accessible technologies that are integrated into patients' lives. Technologies that are tailored to older adults by incorporating gerontological design principles are called gerontechnologies. Gerontechnology is an interdisciplinary academic and professional field that combines gerontology and technology with the goals of improving prevention, care, and enhancing the quality of life for older adults. The purpose of this article is to discuss the role of gerontechnologies, specifically the use of mobile applications available on smartphones and tablets as well as remote monitoring systems, for outpatient disease management among older adults with heart failure. While largely unproven, these rapidly developing technologies have great potential to improve outcomes among older persons.

A systematic review on incentive-driven mobile health technology: As used in diabetes management

Introduction Mobile health (mHealth) technologies have been shown to improve self-management of chronic diseases, such as diabetes. However, mHealth tools, e.g. apps, often have low rates of retention, eroding their potential benefits. Using incentives is a common mechanism for engaging, empowering and retaining patients that is applied by mHealth tools. We conducted a systematic review aiming to categorize the different types of incentive mechanisms employed in mHealth tools for diabetes management, which we defined as incentive-driven technologies (IDTs). As an auxiliary aim, we also analyzed barriers to adoption of IDTs. Methods Literature published in English between January 2008-August 2014 was identified through searching leading publishers and indexing databases: IEEE, Springer, Science Direct, NCBI, ACM, Wiley and Google Scholar. Results A total of 42 articles were selected. Of these, 34 presented mHealth tools with IDT mechanisms; Education was the most common mechanism ( n = 21), followed by Reminder ( n = 11), Feedback ( n = 10), Social ( n = 8), Alert ( n = 5), Gamification ( n = 3), and Financial ( n = 2). Many of these contained more than one IDT ( n = 19). The remaining eight articles, from which we defined barriers for adoption, were review papers and a qualitative study of focus groups and interviews. Discussion While mHealth technologies have advanced over the last five years, the core IDT mechanisms have remained consistent. Instead, IDT mechanisms have evolved with the advances in technology, such as moving from manual to automatic content delivery and personalization of content. Conclusion We defined the concept of IDT to be core features designed to act as motivating mechanisms for retaining and empowering users. We then identified seven core IDT mechanisms that are used by mHealth tools for diabetes management and classified 34 articles into these categories.