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Despite the plethora of evidence on mHealth interventions for patient education, there is a lack of information regarding their structures and delivery strategies.
This review aimed to investigate the structures and strategies of patient education programs delivered through smartphone apps for people with diverse conditions and illnesses. We also examined the aim of educational interventions in terms of health promotion, disease prevention, and illness management.
We searched PubMed, Cumulative Index to Nursing and Allied Health Literature, Embase, and PsycINFO for peer-reviewed papers that reported patient educational interventions using mobile apps and published from 2006 to 2016. We explored various determinants of educational interventions, including the content, mode of delivery, interactivity with health care providers, theoretical basis, duration, and follow-up. The reporting quality of studies was evaluated according to the mHealth evidence and reporting assessment criteria.
In this study, 15 papers met the inclusion criteria and were reviewed. The studies mainly focused on the use of mHealth educational interventions for chronic disease management, and the main format for delivering interventions was text. Of the 15 studies, 6 were randomized controlled trials (RCTs), which have shown statistically significant effects on patients’ health outcomes, including patients’ engagement level, hemoglobin A1c, weight loss, and depression. Although the results of RCTs were mostly positive, we were unable to identify any specific effective structure and strategy for mHealth educational interventions owing to the poor reporting quality and heterogeneity of the interventions.
Evidence on mHealth interventions for patient education published in peer-reviewed journals demonstrates that current reporting on essential mHealth criteria is insufficient for assessing, understanding, and replicating mHealth interventions. There is a lack of theory or conceptual framework for the development of mHealth interventions for patient education. Therefore, further research is required to determine the optimal structure, strategies, and delivery methods of mHealth educational interventions.
Health education is a key strategy in the process of acquisition of behaviors that promote and maintain health; it has serious implications for health promotion, disease prevention, and illness management. According to the World Health Organization, health promotion is defined as the process of enabling the general public to improve their own health and covers a broad range of social and environmental interventions. These interventions are developed to improve individuals’ health and quality of life by addressing and preventing the underlying causes of illnesses and not merely focusing on treatment and cure. Health promotion consists of educational strategies to inform people of what they can do to stay healthy and to address the issues in the community that influence mostly health and well-being [
Disease prevention is an individual or group-based intervention for primary and secondary prevention, which aims to decrease the burden of diseases and associated risk factors. While primary prevention is defined as actions taken to avoid the manifestation of a disease, secondary prevention consists of interventions for early detection, which may improve patients’ health outcomes [
For those with chronic diseases, patient education is focused on alleviating complications and optimizing the quality of life. Hence, patient education is directed toward behavioral change, and the development of essential skills and knowledge for self-management [
To manage chronic conditions, in addition to education, patients require long-term support to improve their self-management skills and achieve the desired behavioral change [
Information and communications technologies and digital devices, such as smartphones, offer a potentially powerful means for patient education and behavioral change reinforcements [
A number of systematic reviews and meta-analyses have investigated the effect of smartphone apps on patients and consumers health outcomes [
We conducted a comprehensive electronic search of 4 major biomedical databases (PubMed, Cumulative Index to Nursing and Allied Health Literature, Embase, and PsycINFO) for peer-reviewed papers published from 2006 to 2016. A sensitive search strategy was developed by a combination of controlled vocabulary (Medical Subject Headings terms) and free text terms according to recent recommendations for searching the PubMed database [
The criteria for considering studies for this review were as follows.
We considered peer-reviewed studies for inclusion. Primary or secondary studies reporting clinical trials were included regardless of their study design, except for case reports. We reviewed papers with a broad range of methodology, including qualitative and quantitative. However, conference abstracts, book reviews, letters, editorials, and unpublished studies were excluded.
We considered patients with diverse conditions regardless of their age, gender, or ethnicity in this review. However, the authors might have established the diagnostic criteria in their respective papers.
Any mHealth educational intervention designed or delivered for health promotion, disease prevention, or illness management was included. We considered interventions that consisted of educational modules or materials either as the main intervention or part of health care delivery for patients with chronic conditions.
Three reviewers extracted data from the final set of included papers. In case of discrepancy, the reviewers discussed the issues and reached an agreement. Owing to resource limitation, we excluded papers published in other than the English language. Data extracted from each paper were summarized in 3 separate tables.
The Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram was used to document the paper selection process (
Summary of the intervention and results of the included randomized controlled trials.
Study | Study design | Disease or condition | Primary outcome | Follow-up | Results |
Ledford et al, 2016 [ |
Pilot RCTa | Pregnancy | Patient activation | 32 weeks | There was a statistically significant difference in the patient activation between notebook and mobile groups ( |
Zhou et al, 2016 [ |
Open RCT | Diabetes | Hemoglobin A1c | 3 months | Diabetic patients in the intervention group (using the Welltang app) achieved statistically significant improvements in hemoglobin A1c ( |
Direito et al, 2015 [ |
RCT (3-arm) | Physical activity | Cardiorespiratory fitness | 8 weeks | There was no significant intervention effect on the primary outcome using either of the apps. |
Fukuoka et al, 2015 [ |
RCT | Overweight | Percentage change in weight and body mass index | 5 months | There was a statistically significant difference in weight loss between the intervention and control groups ( |
Depp et al, 2015 [ |
RCT | Bipolar disorder | Depressive symptoms | 24 weeks | Participants in the intervention group showed significantly greater reductions in depressive symptoms after 6 and 12 weeks (Cohen |
Ly et al, 2014 [ |
Open RCT | Depression | Depression | 6 months | No significant interaction effects of group and time on the Patient Health Questionnaire-9 and the Beck’s Depression Inventory-II were found between the groups, either from pretreatment to posttreatment. |
aRCT: randomized controlled trial.
Study flow diagram. CINAHL: Cumulative Index to Nursing and Allied Health Literature.
We graded the quality of the evidence using the new mHealth evidence and reporting assessment (mERA) checklist [
As shown in
Based on the mERA criteria for the quality of reporting in mHealth, (13/15, 86%) of included studies reported on the content of smartphones interventions, modes of delivery, and testing usability. Of 15, none of the studies reported on the measures taken to protect data security, privacy, and confidentiality. While (12/15, 80%) of studies reported on users’ feedback, (6/15, 40%) described patient or user satisfaction. Only (2/15, 13%) of the studies provided some level of information on the cost associated with the development or delivery of mHealth interventions (
Smartphone interventions identified in this review reflected on 3 different aspects of health education, including health promotion, disease prevention, and illness management.
A total of 3 smartphone interventions targeted health promotion in adolescent and pregnant women. It is evident that pregnant women who used a mobile app for prenatal education and engagement were more engaged than their control counterparts (pregnant women who used a notebook) [
Of the 15 studies, 2 aimed to reduce diseases’ risk factors (ie, primary prevention) using smartphone apps; these studies focused on overweight participants and showed a reduction in weight and blood glucose levels [
The mHealth evidence and reporting assessment checklist. mERA: mHealth evidence and reporting assessment.
Heart failure, coronary heart disease, diabetes, and asthma were the main chronic diseases reported in the included papers [
A total of 8 studies reported that their interventions were developed by the research team and health care professionals [
In total, 4 studies reported using a theory or a conceptual model to underpin the educational materials of smartphones apps [
This study reviewed 15 studies on innovative educational interventions using smartphone apps for participants with diverse conditions. Interventions that were identified in this review aimed to deliver educational materials through smartphones to promote health, prevent diseases, and manage chronic illnesses. The results of our review showed that mHealth interventions were mainly focused on the illness management of patients with chronic disease. Although we considered self-management as one of the key constructs of our search strategy, none of the studies included in this review formally assessed self-management as the primary outcome. However, behavioral change, as an indirect outcome of self-management, was assessed by a number of studies.
Although short message service were the most common format used to deliver educational materials through smartphones, 7 studies used audio or visual aids. The use of audio or visual format provides an additional means of communication for conveying educational information that may be difficult to communicate through words alone. Furthermore, audio or visual educational aids may increase patient understanding of a particular situation or specific procedure [
The findings from the reviewed studies highlighted the fact that there is insufficient evidence to inform the underpinning theory or framework in the development of current smartphones apps. In many studies, the theoretical rationale for the development of apps and various components of the intervention, including educational materials, were not reported (
Surprisingly, only 2 papers included in this review utilized measurement tools to assess participants’ knowledge following their interventions. As patients can control their illness and limit worsening symptoms when they understand the principles of chronic disease management and learn to undertake simple interventions [
As shown in
Of the 15 studies included in this review, 6 were RCTs that examined a range of health outcomes on patients with different conditions. The results of 4 RCTs showed statistically significant effects of smartphone-based interventions on health outcomes, including the patient engagement level, hemoglobin A1c, weight loss, and depression. However, the 3-arm RCT evaluating the smartphone intervention for improving young adults’ physical activity did not show statistically significant effect on cardiorespiratory fitness and physical activity level. Furthermore, a smartphone app based on the behavioral activation did not show a statistically significant reduction on major depression disorder.
Although the results of RCTs were mainly positive, studies varied significantly with regard to mHealth educational interventions. Furthermore, only one RCT reported the theoretical underpinning of the educational intervention, and this highlights the lack of theory in developing and evaluating mHealth interventions. As the reporting quality of reviewed studies was poor, it was impossible to compare the effects of interventions based on their educational interventions’ structures and strategies.
The results of this review generally support that patients with diverse conditions benefit from mobile-based educational interventions. However, we were unable to identify any effective specific structure or strategy for the delivery of such interventions owing to the scarcity of high-quality studies and suboptimal reporting quality of the reviewed papers. Thus, additional research is needed to determine the optimal structure, format, and delivery methods for educational instructions that are used in mHealth interventions for patient education. We strongly recommend adoption of standard tools, such as mERA essential criteria, for reporting mHealth interventions. This will facilitate better reporting and improve the ability to synthesize the evidence in future.
Medical Subject Headings (MeSH) terms and free-text keywords used for the PubMed search.
Characteristics of the included studies describing mobile apps for self-management education of chronic patients.
Description of the interventions strategies for self-management.
mHealth evidence and reporting assessment
randomized controlled trial
self-management education
This review was undertaken as part of the PhD project of NB funded by the Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation. FF received funding from the Queensland Government through Advance Queensland Research Fellowships.
None declared.