Use of menstruation and fertility app trackers: a scoping review of the evidence

INTRODUCTION

There has been a phenomenal worldwide increase in the development and use of mobile health applications (mHealth apps) that monitor menstruation and fertility. Critics argue that many of the apps are inaccurate and lack evidence from either clinical trials or user experience. The aim of this scoping review is to provide an overview of the research literature on mHealth apps that track menstruation and fertility.

METHODS

This project followed the PRISMA Extension for Scoping Reviews. The ACM, CINAHL, Google Scholar, PubMed and Scopus databases were searched for material published between 1 January 2010 and 30 April 2019. Data summary and synthesis were used to chart and analyse the data.

RESULTS

In total 654 records were reviewed. Subsequently, 135 duplicate records and 501 records that did not meet the inclusion criteria were removed. Eighteen records from 13 countries form the basis of this review. The papers reviewed cover a variety of disciplinary and methodological frameworks. Three main themes were identified: fertility and reproductive health tracking, pregnancy planning, and pregnancy prevention.

CONCLUSIONS

Motivations for fertility app use are varied, overlap and change over time, although women want apps that are accurate and evidence-based regardless of whether they are tracking their fertility, planning a pregnancy or using the app as a form of contraception. There is a lack of critical debate and engagement in the development, evaluation, usage and regulation of fertility and menstruation apps. The paucity of evidence-based research and absence of fertility, health professionals and users in studies is raised.

Can caregivers trust information technology in the care of their patients? A systematic review

The Health Insurance Portability and Accountability Act of 1996 (HIPAA) requires that healthcare providers allow patients to engage in their healthcare by allowing access to their health records. Often patients need informal caregivers including family members or others to help them with their care. This paper explores whether trust is a key factor for informal caregivers' decision to use health information technologies (HIT) including electronic health records (EHR), patient portals, mobile apps, or other devices to care for their patient. Six reviewers conducted a comprehensive search of four literature databases using terms that pertained to a caregiver and trust to investigate the role trust plays when caregivers use HIT. While trust is a key factor for the use of HIT, it the researchers only identified ten articles that met the research question thresholds. Four main topics of trust surfaced including perceived confidentiality, perceived security, technological malfunction, and trustworthiness of the information. Trust is a critical factor for informal caregivers when using HIT to assist in the care of their patient (child, loved one, parent, or acquaintance). Based on the findings, it is clear that more research on the use of HIT by caregivers is needed.

Mobile apps for detecting falsified and substandard drugs: A systematic review

The use of substandard and counterfeit medicines (SCM) leads to significant health and economic consequences, like treatment failure, rise of antimicrobial resistance, extra expenditures of individuals or households and serious adverse drug reactions including death. Our objective was to systematically search, identify and compare relevant available mobile applications (apps) for smartphones and tablets, which use could potentially affect clinical and public health outcomes. We carried out a systematic review of the literature in January 2020, including major medical databases, and app stores. We used the validated Mobile App Rating Scale (MARS) to assess the quality of apps, (1 worst score, 3 acceptable score, and 5 best score). We planned to evaluate the accuracy of the mobile apps to detect SCM. We retrieved 335 references through medical databases and 42 from Apple, Google stores and Google Scholar. We finally included two studies of the medical database, 25 apps (eight from the App Store, eight from Google Play, eight from both stores, and one from Google Scholar), and 16 websites. We only found one report on the accuracy of a mobile apps detecting SCMs. Most apps use the imprint, color or shape for pill identification, and only a few offer pill detection through photographs or bar code. The MARS mean score for the apps was 3.17 (acceptable), with a maximum of 4.9 and a minimum of 1.1. The 'functionality' dimension resulted in the highest mean score (3.4), while the 'engagement' and 'information' dimensions showed the lowest one (3.0). In conclusion, we found a remarkable evidence gap about the accuracy of mobile apps in detecting SCMs. However, mobile apps could potentially be useful to screen for SCM by assessing the physical characteristics of pills, although this should still be assessed in properly designed research studies.

Improved readability and functions needed for mHealth apps targeting patients with heart failure: An app store review

To maintain their quality of life and avoid hospitalization and early mortality, patients with heart failure must recognize and respond to symptoms of exacerbation. A promising method for engaging patients in their self-care is through mobile health applications (mHealth apps). However, for mHealth to have its greatest chance for improving patient outcomes, the app content must be readable, provide useful functions and be based in evidence. The study aimed to determine: (1) readability, (2) types of functions, and (3) linkage to authoritative sources of evidence for self-care focused mHealth apps targeting heart failure patients that are available in the Apple and Google Play Stores. We systematically searched for mHealth apps targeting patients with heart failure in the Apple and Google Play Stores and applied selection criteria. Readability of randomly selected informational paragraphs were determined using Flesch-Kincaid grade level test tool in Microsoft Word. Ten mHealth apps met our criteria. Only one had a reading grade level at or below the recommended 6th grade reading level (average 9.35). The most common functions were tracking, clinical data feedback, and non-data-based reminders and alerts. Only three had statements that clearly linked the mHealth app content to trustworthy, evidence-based sources. Only two had interoperability with the electronic health record and only one had a communication feature with clinicians. Future mHealth designs that are tailored to patients' literacy level and have advanced functions may hold greater potential for improving patient outcomes.

Drivers of Acceptance of COVID-19 Proximity Tracing Apps in Switzerland: Panel Survey Analysis

BACKGROUND

Digital proximity tracing apps have been released to mitigate the transmission of SARS-CoV-2, the virus known to cause COVID-19. However, it remains unclear how the acceptance and uptake of these apps can be improved.

OBJECTIVE

This study aimed to investigate the coverage of the SwissCovid app and the reasons for its nonuse in Switzerland during a period of increasing incidence of COVID-19 cases.

METHODS

We collected data between September 28 and October 8, 2020, via a nationwide online panel survey (COVID-19 Social Monitor, N=1511). We examined sociodemographic and behavioral factors associated with app use by using multivariable logistic regression, whereas reasons for app nonuse were analyzed descriptively.

RESULTS

Overall, 46.5% (703/1511) of the survey participants reported they used the SwissCovid app, which was an increase from 43.9% (662/1508) reported in the previous study wave conducted in July 2020. A higher monthly household income (ie, income >CHF 10,000 or >US $11,000 vs income ≤CHF 6000 or

CONCLUSIONS

Eliminating technical hurdles and communicating the benefits of digital proximity tracing apps are crucial to promote further uptake and adherence of such apps and, ultimately, enhance their effectiveness to aid pandemic mitigation strategies.

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Key Words

• COVID-19
• SARS-CoV-2
• acceptance
• communication
• compliance
• digital contact tracing
• digital proximity tracing
• mHealth
• tracing
• uptake
• usability

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MESH Headings

• Adult
• Aged
• COVID-19/complications
• COVID-19/psychology
• COVID-19/transmission
• Contact Tracing/instrumentation
• Contact Tracing/trends
• Female
• Humans
• Male
• Middle Aged
• Mobile Applications/standards
• Mobile Applications/statistics & numerical data
• Physical Distancing
• Surveys and Questionnaires
• Switzerland

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Instant messaging application usage for clinical consultation among orthopedic surgery residents in Turkey: A survey study

OBJECTIVE

This study aimed to determine the characteristics of instant messaging application (IMA) usage for clinical consultation among orthopedic residents in Turkey and to explore their experiences and opinions concerning potential legal problems.

METHODS

A questionnaire titled "Instant messaging for consultation among orthopedic surgeons" consisting of 21 questions was applied to orthopedic surgery residents, and the results were analyzed. The questions were designed to obtain information on 4 categories: 1) demographics and professional experience, 2) attitudes on the use of cellular phones, 3) IMA usage for clinical consultation purposes, and 4) problems and comments on smartphone application usage for clinical consultation purposes. The participants who had no experience with a smartphone or IMA usage were excluded at the final analysis.

RESULTS

A total of 860 orthopedic residents (849 males [98.7%]; mean age=28.6 years; age range=22-44 years) participated in the survey (participation rate: 97.3%). The distribution of residency years was as follows: 1st year, 27%; 2nd year, 21.4%; 3rd year, 18.4%; 4th year, 17.4%; and 5th year, 49.9%. The most frequently used IMAs were WhatsApp (99.3%), Facebook Messenger (14.8%), Viber (8%), and Tango (1.3%). The rate of IMA usage for consultation was 95.3%. The most common reasons to prefer IMAs for consultation were being "fast" and "easy," but only 26.3% of the residents reported that they prefer the use of IMAs because they find them "reliable." Moreover, 41.7% of the respondents reported that they had an experience of misdiagnosis owing to the use of IMAs; 81.2% of the participants used the personal information of the patients during the consultation; 57.6% of the respondents considered that legal problems may arise because of the use of IMAs during the consultation; and 51.4% believed that an electronic platform, solely for consultation purposes, is required.

CONCLUSION

This survey has shown that it is necessary to make some legal regulations regarding the use of IMAs for consultation purposes and to develop applications only for medical consultation purposes. Most of the trainees make decisions using IMAs without a proper examination, putting the patients at the risk of misdiagnosis. Moreover, the confidentiality of the patient's personal information appears to be in danger when IMAs are used.

LEVEL OF EVIDENCE

Level IV, Diagnostic Study.

Mobile Health App With Social Media to Support Self-Management for Patients With Chronic Kidney Disease: Prospective Randomized Controlled Study

BACKGROUND

Chronic kidney disease (CKD) is a global health burden. Self-management plays a key role in improving modifiable risk factors.

OBJECTIVE

The aim of this study was to evaluate the effectiveness of wearable devices, a health management platform, and social media at improving the self-management of CKD, with the goal of establishing a new self-management intervention model.

METHODS

In a 90-day prospective experimental study, a total of 60 people with CKD at stages 1-4 were enrolled in the intervention group (n=30) and control group (n=30). All participants were provided with wearable devices that collected exercise-related data. All participants maintained dietary diaries using a smartphone app. All dietary and exercise information was then uploaded to a health management platform. Suggestions about diet and exercise were provided to the intervention group only, and a social media group was created to inspire the participants in the intervention group. Participants' self-efficacy and self-management questionnaire scores, Kidney Disease Quality of Life scores, body composition, and laboratory examinations before and after the intervention were compared between the intervention and control groups.

RESULTS

A total of 49 participants completed the study (25 in the intervention group and 24 in the control group); 74% of the participants were men and the mean age was 51.22 years. There were no differences in measured baseline characteristics between the groups except for educational background. After the intervention, the intervention group showed significantly higher scores for self-efficacy (mean 171.28, SD 22.92 vs mean 142.21, SD 26.36; P<.001) and self-management (mean 54.16, SD 6.71 vs mean 47.58, SD 6.42; P=.001). Kidney Disease Quality of Life scores were also higher in the intervention group (mean 293.16, SD 34.21 vs mean 276.37, SD 32.21; P=.02). The number of steps per day increased in the intervention group (9768.56 in week 1 and 11,389.12 in week 12). The estimated glomerular filtration rate (eGFR) of the intervention group was higher than that of the control group (mean 72.47, SD 24.28 vs mean 59.69, SD 22.25 mL/min/1.73m2; P=.03) and the decline in eGFR was significantly slower in the intervention group (-0.56 vs -4.58 mL/min/1.73m2). There were no differences in body composition between groups postintervention.

CONCLUSIONS

The use of wearable devices, a health management platform, and social media support not only strengthened self-efficacy and self-management but also improved quality of life and a slower eGFR decline in people with CKD at stages 1-4. These results outline a new self-management model to promote healthy lifestyle behaviors for patients with CKD.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04617431; https://www.clinicaltrials.gov/ct2/show/NCT04617431.

Evaluation of Four Artificial Intelligence-Assisted Self-Diagnosis Apps on Three Diagnoses: Two-Year Follow-Up Study

Background

Consumer-oriented mobile self-diagnosis apps have been developed using undisclosed algorithms, presumably based on machine learning and other artificial intelligence (AI) technologies. The US Food and Drug Administration now discerns apps with learning AI algorithms from those with stable ones and treats the former as medical devices. To the author’s knowledge, no self-diagnosis app testing has been performed in the field of ophthalmology so far.

Objective

The objective of this study was to test apps that were previously mentioned in the scientific literature on a set of diagnoses in a deliberate time interval, comparing the results and looking for differences that hint at “nonlocked” learning algorithms.

Methods

Four apps from the literature were chosen (Ada, Babylon, Buoy, and Your.MD). A set of three ophthalmology diagnoses (glaucoma, retinal tear, dry eye syndrome) representing three levels of urgency was used to simultaneously test the apps’ diagnostic efficiency and treatment recommendations in this specialty. Two years was the chosen time interval between the tests (2018 and 2020). Scores were awarded by one evaluating physician using a defined scheme.

Results

Two apps (Ada and Your.MD) received significantly higher scores than the other two. All apps either worsened in their results between 2018 and 2020 or remained unchanged at a low level. The variation in the results over time indicates “nonlocked” learning algorithms using AI technologies. None of the apps provided correct diagnoses and treatment recommendations for all three diagnoses in 2020. Two apps (Babylon and Your.MD) asked significantly fewer questions than the other two (P<.001).

Conclusions

“Nonlocked” algorithms are used by self-diagnosis apps. The diagnostic efficiency of the tested apps seems to worsen over time, with some apps being more capable than others. Systematic studies on a wider scale are necessary for health care providers and patients to correctly assess the safety and efficacy of such apps and for correct classification by health care regulating authorities.

Evaluation of the Design and Implementation of a Peer-To-Peer COVID-19 Contact Tracing Mobile App (COCOA) in Japan

We evaluate a Bluetooth-based mobile contact-confirming app, COVID-19 Contact-Confirming Application (COCOA), which is being used in Japan to contain the spread of COVID-19, the disease caused by the novel virus termed SARS-COV-2. The app prioritizes the protection of users' privacy from a variety of parties (eg, other users, potential attackers, and public authorities), enhances the capacity to balance the current load of excessive pressure on health care systems (eg, local triage of exposure risk and reduction of in-person hospital visits), increases the speed of responses to the pandemic (eg, automated recording of close contact based on proximity), and reduces operation errors and population mobility. The peer-to-peer framework of COCOA is intended to provide the public with dynamic and credible updates on the COVID-19 pandemic without sacrificing the privacy of their information. However, cautions must be exercised to address critical concerns, such as the rate of participation and delays in data sharing. The results of a simulation imply that the participation rate in Japan needs to be close 90% to effectively control the spread of COVID-19.

Changing Health Behavior with Social Technology? A Pilot Test of a Mobile App Designed for Social Support of Physical Activity

Mobile applications targeting people engaged in physical activity have increased. However, while research has identified social support as a key factor for people's engagement in physical activity, most mobile health (mHealth) applications are designed for individual use. In this paper, we report on a research study exploring opportunities for designing mHealth to facilitate social support around physical activity. A mHealth application was designed, and pilot tested for eight weeks with healthcare professionals (n = 3) and two groups of citizens (n = 20) who were motivated but challenged physically due to various health conditions. Data was collected via online monitoring of the use of the mHealth application during the pilot test and via qualitative interviews with the participants before and after. The results support the idea that designing for social health support is important but so is identifying key challenges related to (i) the facilitation of technology-mediated social health support, especially to a target group that is living with health challenges, and (ii) finding a balance between social and health agendas that bring social support to the foreground for the participants.

Validation of the Mobile Application Rating Scale (MARS)

BACKGROUND

Mobile health apps (MHA) have the potential to improve health care. The commercial MHA market is rapidly growing, but the content and quality of available MHA are unknown. Instruments for the assessment of the quality and content of MHA are highly needed. The Mobile Application Rating Scale (MARS) is one of the most widely used tools to evaluate the quality of MHA. Only few validation studies investigated its metric quality. No study has evaluated the construct validity and concurrent validity.

OBJECTIVE

This study evaluates the construct validity, concurrent validity, reliability, and objectivity, of the MARS.

METHODS

Data was pooled from 15 international app quality reviews to evaluate the metric properties of the MARS. The MARS measures app quality across four dimensions: engagement, functionality, aesthetics and information quality. Construct validity was evaluated by assessing related competing confirmatory models by confirmatory factor analysis (CFA). Non-centrality (RMSEA), incremental (CFI, TLI) and residual (SRMR) fit indices were used to evaluate the goodness of fit. As a measure of concurrent validity, the correlations to another quality assessment tool (ENLIGHT) were investigated. Reliability was determined using Omega. Objectivity was assessed by intra-class correlation.

RESULTS

In total, MARS ratings from 1,299 MHA covering 15 different health domains were included. Confirmatory factor analysis confirmed a bifactor model with a general factor and a factor for each dimension (RMSEA = 0.074, TLI = 0.922, CFI = 0.940, SRMR = 0.059). Reliability was good to excellent (Omega 0.79 to 0.93). Objectivity was high (ICC = 0.82). MARS correlated with ENLIGHT (ps<.05).

CONCLUSION

The metric evaluation of the MARS demonstrated its suitability for the quality assessment. As such, the MARS could be used to make the quality of MHA transparent to health care stakeholders and patients. Future studies could extend the present findings by investigating the re-test reliability and predictive validity of the MARS.

Impact of a medical mobile phone app (QUiPP) for predicting preterm birth on the anxiety and decisional conflicts faced by women in threatened preterm labour

BACKGROUND

The QUiPP app is a free, validated mobile phone application (app) that supports clinical decision-making for women in threatened preterm labour by providing an individualised risk of delivery within clinically important time points. Alongside generating a percentage risk score, the QUiPP app also provides the risk score in an infographic donut chart, allowing the clinician to communicate with the woman in an easy to understand format. Informing women of their risk status using the QUIPP app may help to reduce anxiety in women and decrease decisional conflict.

METHOD

A subset of participants from the EQUIPTT study [REC Ref. 17/LO/1802] were asked to complete a questionnaire booklet which was used to evaluate decisional conflict and anxiety. Seven sites were randomised to the QUiPP app intervention (to use as a decision and communication tool) and six sites were randomised to the control (continued their normal practice). The first section of the questionnaire booklet was completed by the woman before her assessment, and the second section after. The pre and postassessment anxiety scores utilised the Visual Analogue Scale for Anxiety (Hornblow and Kidson, 1976). The Decisional Conflict Scale (O'Connor, 1995) measured decisional conflict post assessment. The data were then analysed to determine the impact of the QUiPP App on the anxiety and decisional conflicts faced by women in threatened preterm labour.

RESULTS

Questionnaires were completed by 221 women from 12 of the potential 13 sites. After exclusions 202 questionnaires were included in the analysis. There was a significant reduction in difference between anxiety scores before and after clinical assessment. While there were reductions in anxiety and decisional conflict for women who were aware of the QUiPP app use, this failed to reach statistical significance.

CONCLUSIONS

The QUiPP app has potential to reduce anxiety and decisional conflict in women who are aware that it is being used in their care. Additional work is required to ensure clinicians are aware of the QUiPP app and optimise using it as a communication tool when counselling women.

Developing and Evaluating a Mobile Foot Care Application for Persons With Diabetes Mellitus: A Randomized Pilot Study

Ulceration of the foot is a major complication of diabetes mellitus, and optimal self-care may help prevent its development. Research suggests that mobile applications (apps) may affect behavioral change.

OBJECTIVE

The purpose of this study was to develop the Mobile Diabetic Foot Personal Care System (m-DAKBAS) and evaluate its effectiveness for patients with diabetes.

METHOD

During Phase 1, a mobile app that included communication features, remote patient monitoring, and information was developed and pilot-tested among 10 patients. The Phase 2 study, conducted from June 2017 to April 2018, used a 2-group, pre-test/post-test design to evaluate the effect of the app on patients' knowledge, behavior, and self-efficacy scores when used for 6 months. Both the experimental (app) and control groups participated in 1 education session at the start of the study.

RESULTS

Of 106 patients who enrolled, 88 completed the study (44 in the experimental group and 44 in the control group). Only 6 patients had received education about foot care previously. The average age of all participants was 51.63 years (SD = 8.08). There were significantly more women in the experimental group than in the control group (65% vs. 45.5%; P = 0.5). Each participant used the app for 24 weeks, and the data entry rate was 72.9%. Throughout the study, participants had 1977 data entries (blood glucose and foot observation) in total. Differences between pre- and post-intervention test scores were significantly higher for knowledge, behavior, and self-efficacy in both groups, but the difference was greater in the experimental group (P < .05). Only post-test knowledge scores were significantly higher in the experimental compared with the control group (P < .05). Compared to the start of the study, the proportion of participants with cracked/dry skin and inappropriate footwear was significantly lower in the experimental group but not in the control group.

CONCLUSION

In this study, education and follow-up via the mobile app and verbal-only instruction increased the knowledge, behavior, and self-efficacy scores of patients in both groups. Post-study knowledge scores were significantly higher in the experimental group than in the control group. Patient education remains a crucial component of optimal care, and further development, refinement, and testing of mobile applications to improve self-efficacy and reduce the risk of diabetic foot are warranted.

A detection method for android application security based on TF-IDF and machine learning

Android is the most widely used mobile operating system (OS). A large number of third-party Android application (app) markets have emerged. The absence of third-party market regulation has prompted research institutions to propose different malware detection techniques. However, due to improvements of malware itself and Android system, it is difficult to design a detection method that can efficiently and effectively detect malicious apps for a long time. Meanwhile, adopting more features will increase the complexity of the model and the computational cost of the system. Permissions play a vital role in the security of the Android apps. Term Frequency—Inverse Document Frequency (TF-IDF) is used to assess the importance of a word for a file set in a corpus. The static analysis method does not need to run the app. It can efficiently and accurately extract the permissions from an app. Based on this cognition and perspective, in this paper, a new static detection method based on TF-IDF and Machine Learning is proposed. The system permissions are extracted in Android application package’s (Apk’s) manifest file. TF-IDF algorithm is used to calculate the permission value (PV) of each permission and the sensitivity value of apk (SVOA) of each app. The SVOA and the number of the used permissions are learned and tested by machine learning. 6070 benign apps and 9419 malware are used to evaluate the proposed approach. The experiment results show that only use dangerous permissions or the number of used permissions can’t accurately distinguish whether an app is malicious or benign. For malware detection, the proposed approach achieve up to 99.5% accuracy and the learning and training time only needs 0.05s. For malware families detection, the accuracy is 99.6%. The results indicate that the method for unknown/new sample’s detection accuracy is 92.71%. Compared against other state-of-the-art approaches, the proposed approach is more effective by detecting malware and malware families.

Technology Evaluation and Assessment Criteria for Health Apps (TEACH-Apps): Pilot Study

BACKGROUND

Despite the emergence of app evaluation tools, there remains no well-defined process receptive to diverse local needs, rigorous standards, and current content. The need for such a process to assist in the implementation of app evaluation across all medical fields is evident. Such a process has the potential to increase stakeholder engagement and catalyze interest and engagement with present-day app evaluation models.

OBJECTIVE

This study aimed to develop and pilot test the Technology Evaluation and Assessment Criteria for Health apps (TEACH-apps).

METHODS

Tailoring a well-known implementation framework, Replicating Effective Programs, we present a new process to approach the challenges faced in implementing app evaluation tools today. As a culmination of our experience implementing this process and feedback from stakeholders, we present the four-part process to aid the implementation of mobile health technology. This paper outlines the theory, evidence, and initial versions of the process.

RESULTS

The TEACH-apps process is designed to be broadly usable and widely applicable across all fields of health. The process comprises four parts: (1) preconditions (eg, gathering apps and considering local needs), (2) preimplementation (eg, customizing criteria and offering digital skills training), (3) implementation (eg, evaluating apps and creating educational handouts), and (4) maintenance and evolution (eg, repeating the process every 90 days and updating content). TEACH-apps has been tested internally at our hospital, and there is growing interest in partnering health care facilities to test the system at their sites.

CONCLUSIONS

This implementation framework introduces a process that equips stakeholders, clinicians, and users with the foundational tools to make informed decisions around app use and increase app evaluation engagement. The application of this process may lead to the selection of more culturally appropriate and clinically relevant tools in health care.

A mobile app to capture EPA assessment data: Utilizing the consolidated framework for implementation research to identify enablers and barriers to engagement

INTRODUCTION

Mobile apps that utilize the framework of entrustable professional activities (EPAs) to capture and deliver feedback are being implemented. If EPA apps are to be successfully incorporated into programmatic assessment, a better understanding of how they are experienced by the end-users will be necessary. The authors conducted a qualitative study using the Consolidated Framework for Implementation Research (CFIR) to identify enablers and barriers to engagement with an EPA app.

METHODS

Structured interviews of faculty and residents were conducted with an interview guide based on the CFIR. Transcripts were independently coded by two study authors using directed content analysis. Differences were resolved via consensus. The study team then organized codes into themes relevant to the domains of the CFIR.

RESULTS

Eight faculty and 10 residents chose to participate in the study. Both faculty and residents found the app easy to use and effective in facilitating feedback immediately after the observed patient encounter. Faculty appreciated how the EPA app forced brief, distilled feedback. Both faculty and residents expressed positive attitudes and perceived the app as aligned with the department's philosophy. Barriers to engagement included faculty not understanding the EPA framework and scale, competing clinical demands, residents preferring more detailed feedback and both faculty and residents noting that the app's feedback should be complemented by a tool that generates more systematic, nuanced, and comprehensive feedback. Residents rarely if ever returned to the feedback after initial receipt.

DISCUSSION

This study identified key enablers and barriers to engagement with the EPA app. The findings provide guidance for future research and implementation efforts focused on the use of mobile platforms to capture direct observation feedback.

The Use of Augmented Reality to Raise Awareness of the Differences Between Osteoarthritis and Rheumatoid Arthritis

Arthritis is one of the most common disease states worldwide but is still publicly misunderstood and lacks engaging public awareness materials. Within the UK, the most prevalent types of arthritis are osteoarthritis (OA) and rheumatoid arthritis (RA). The two are commonly mistaken as the same disease but, in fact, have very different pathogenesis, symptoms and treatments. This chapter describes a study which aimed to assess whether an augmented reality (AR) application could be used to raise awareness about the difference between OA and RA.An application was created for Android tablets that included labelled 3D models, animations and AR scenes triggered from a poster. In total 11 adult participants tested the application taking part in a pretest and posttest which aim to measure the usability of the application and the acquisition of knowledge on OA and RA. A T-test was performed to assess the effectiveness of the application from the pretest and posttest questionnaire outcomes. Overall results were encouraging reporting a very significant acquisition of knowledge and a highly satisfactory user experience.

Effects of the e-Motivate4Change Program on Metabolic Syndrome in Young Adults Using Health Apps and Wearable Devices: Quasi-Experimental Study

BACKGROUND

The health behaviors of young adults lag behind those of other age groups, and active health management is needed to improve health behaviors and prevent chronic diseases. In addition, developing good lifestyle habits earlier in life could reduce the risk of metabolic syndrome (MetS) later on.

OBJECTIVE

The aim of this study is to investigate the effects of the e-Motivate4Change program, for which health apps and wearable devices were selected based on user needs. The program was developed for the prevention and management of MetS in young adults.

METHODS

This experimental study used a nonequivalent control group. In total, 59 students from 2 universities in Daegu, Korea participated in the study (experimental group n=30; control group n=29). Data were collected over 4 months, from June 1 to September 30, 2018. The experimental group received a 12-week e-Motivate4Change program intervention, and the control group received MetS education and booklets without the e-Motivate4Change program intervention.

RESULTS

After the program, the experimental group had significantly higher scores for health-related lifestyle (t=3.86; P<.001) and self-efficacy (t=6.00; P<.001) than did the control group. Concerning BMI, there were significant effects by group (F=1.01; P<.001) and for the group × time interaction (F=4.71; P=.034). Concerning cholesterol, there were significant main effects for group (F=4.32; P=.042) and time (F=9.73; P<.001).

CONCLUSIONS

The e-Motivate4Change program effectively improved participants' health-related lifestyle scores and self-efficacy, and significantly reduced their BMI and cholesterol levels. The program can be used to identify and prevent MetS among young adults.

Methods and Evaluation Criteria for Apps and Digital Interventions for Diabetes Self-Management: Systematic Review

BACKGROUND

There is growing evidence that apps and digital interventions have a positive impact on diabetes self-management. Standard self-management for patients with diabetes could therefore be supplemented by apps and digital interventions to increase patients' skills. Several initiatives, models, and frameworks suggest how health apps and digital interventions could be evaluated, but there are few standards for this. And although there are many methods for evaluating apps and digital interventions, a more specific approach might be needed for assessing digital diabetes self-management interventions.

OBJECTIVE

This review aims to identify which methods and criteria are used to evaluate apps and digital interventions for diabetes self-management, and to describe how patients were involved in these evaluations.

METHODS

We searched CINAHL, EMBASE, MEDLINE, and Web of Science for articles published from 2015 that referred to the evaluation of apps and digital interventions for diabetes self-management and involved patients in the evaluation. We then conducted a narrative qualitative synthesis of the findings, structured around the included studies' quality, methods of evaluation, and evaluation criteria.

RESULTS

Of 1681 articles identified, 31 fulfilled the inclusion criteria. A total of 7 articles were considered of high confidence in the evidence. Apps were the most commonly used platform for diabetes self-management (18/31, 58%), and type 2 diabetes (T2D) was the targeted health condition most studies focused on (12/31, 38%). Questionnaires, interviews, and user-group meetings were the most common methods of evaluation. Furthermore, the most evaluated criteria for apps and digital diabetes self-management interventions were cognitive impact, clinical impact, and usability. Feasibility and security and privacy were not evaluated by studies considered of high confidence in the evidence.

CONCLUSIONS

There were few studies with high confidence in the evidence that involved patients in the evaluation of apps and digital interventions for diabetes self-management. Additional evaluation criteria, such as sustainability and interoperability, should be focused on more in future studies to provide a better understanding of the effects and potential of apps and digital interventions for diabetes self-management.

Real-time tracking of self-reported symptoms to predict potential COVID-19

A total of 2,618,862 participants reported their potential symptoms of COVID-19 on a smartphone-based app. Among the 18,401 who had undergone a SARS-CoV-2 test, the proportion of participants who reported loss of smell and taste was higher in those with a positive test result (4,668 of 7,178 individuals; 65.03%) than in those with a negative test result (2,436 of 11,223 participants; 21.71%) (odds ratio = 6.74; 95% confidence interval = 6.31-7.21). A model combining symptoms to predict probable infection was applied to the data from all app users who reported symptoms (805,753) and predicted that 140,312 (17.42%) participants are likely to have COVID-19.

The Model of Gamification Principles for Digital Health Interventions: Evaluation of Validity and Potential Utility

BACKGROUND

Although gamification continues to be a popular approach to increase engagement, motivation, and adherence to behavioral interventions, empirical studies have rarely focused on this topic. There is a need to empirically evaluate gamification models to increase the understanding of how to integrate gamification into interventions.

OBJECTIVE

The model of gamification principles for digital health interventions proposes a set of five independent yet interrelated gamification principles. This study aimed to examine the validity and reliability of this model to inform its use in Web- and mobile-based apps.

METHODS

A total of 17 digital health interventions were selected from a curated website of mobile- and Web-based apps (PsyberGuide), which makes independent and unbiased ratings on various metrics. A total of 133 independent raters trained in gamification evaluation techniques were instructed to evaluate the apps and rate the degree to which gamification principles are present. Multiple ratings (n≥20) were collected for each of the five gamification principles within each app. Existing measures, including the PsyberGuide credibility score, mobile app rating scale (MARS), and the app store rating of each app were collected, and their relationship with the gamification principle scores was investigated.

RESULTS

Apps varied widely in the degree of gamification implemented (ie, the mean gamification rating ranged from 0.17≤m≤4.65 out of 5). Inter-rater reliability of gamification scores for each app was acceptable (κ≥0.5). There was no significant correlation between any of the five gamification principles and the PsyberGuide credibility score (P≥.49 in all cases). Three gamification principles (supporting player archetypes, feedback, and visibility) were significantly correlated with the MARS score, whereas three principles (meaningful purpose, meaningful choice, and supporting player archetypes) were significantly correlated with the app store rating. One gamification principle was statistically significant with both the MARS and the app store rating (supporting player archetypes).

CONCLUSIONS

Overall, the results support the validity and potential utility of the model of gamification principles for digital health interventions. As expected, there was some overlap between several gamification principles and existing app measures (eg, MARS). However, the results indicate that the gamification principles are not redundant with existing measures and highlight the potential utility of a 5-factor gamification model structure in digital behavioral health interventions. These gamification principles may be used to improve user experience and enhance engagement with digital health programs.

Combination of a Self-Regulation Module and Mobile Application to Enhance Treatment Outcome for Patients with Acne

Background and Objectives: Acne, an inflammatory disorder of the pilosebaceous unit associated with both physiological and psychological morbidities, should be considered a chronic disease. The application of self-regulation theory and therapeutic patient education has been widely utilized in different health-related areas to help patient with a chronic disease to attain better behavioral modification. The present study aims at investigating the treatment efficacy of combining a self-regulation-based patient education module with mobile application in acne patients. Materials and Methods: This was one-grouped pretest-posttest design at a single tertiary referral center with the enrollment of 30 subjects diagnosed with acne vulgaris. Relevant information was collected before (week 0) and after (week 4) treatment in the present study, including the Acne Self-Regulation Inventory (ASRI), Cardiff Acne Disability Index (CADI), and Dermatology Life Quality Index (DLQI) that involved a questionnaire-based subjective evaluation of the patient's ability in self-regulation and quality of life as well as clinical Acne Grading Scores (AGS) that objectively assessed changes in disease severity. To reinforce availability and feasibility, an individualized platform was accessible through mobile devices for real-time problem solving between hospital visits. Results: Thirty subjects completed the designed experiment. An analysis of the differences between scores of pretest and posttest of ASRI demonstrated substantial elevations (p < 0.001). The questionnaire survey of CADI and DLQI dropped significantly after the application of a self-regulation-based patient education module with a mobile application, revealing substantial reductions in both parameters (p < 0.001). The sign test demonstrated a remarkably significant difference in AGS (Z = -7.38, p < 0.001), indicating notable improvement in the clinical severity of acne after treatment. Conclusions: After incorporating modern mobile application, a self-regulation-based therapeutic patient education module could significantly improve treatment outcomes among acne patients.

Review of the Content and Quality of Mobile Applications About Alzheimer's Disease and Related Dementias

This study reviewed the content of mobile applications (apps) providing Alzheimer's disease or related dementias (ADRD) information and assessed quality of the apps. Characteristics, content, and technical aspects of 36 apps in the U.S. Google Play Store and App Store were coded, and quality of the apps was evaluated using the Mobile Application Rating Scale. Caregiving (62.1%) and disease management (55.6%) content was frequently provided. Few apps had an app community (8.3%) or a reminder function (8.3%). Overall, quality of the apps was acceptable; apps by health care-related developers had higher quality scores than those by non-health care-related developers. This analysis showed that ADRD-related apps provide a range of content and have potential to benefit caregivers, individuals with ADRD, health care providers, and the general public. Collaboration of ADRD experts and technology experts is needed to provide evidence-based information using effective technical functions that make apps to meet users' needs.

Influences on the Uptake of and Engagement With Health and Well-Being Smartphone Apps: Systematic Review

BACKGROUND

The public health impact of health and well-being digital interventions is dependent upon sufficient real-world uptake and engagement. Uptake is currently largely dependent on popularity indicators (eg, ranking and user ratings on app stores), which may not correspond with effectiveness, and rapid disengagement is common. Therefore, there is an urgent need to identify factors that influence uptake and engagement with health and well-being apps to inform new approaches that promote the effective use of such tools.

OBJECTIVE

This review aimed to understand what is known about influences on the uptake of and engagement with health and well-being smartphone apps among adults.

METHODS

We conducted a systematic review of quantitative, qualitative, and mixed methods studies. Studies conducted on adults were included if they focused on health and well-being smartphone apps reporting on uptake and engagement behavior. Studies identified through a systematic search in Medical Literature Analysis and Retrieval System Online, or MEDLARS Online (MEDLINE), EMBASE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsychINFO, Scopus, Cochrane library databases, DataBase systems and Logic Programming (DBLP), and Association for Computing Machinery (ACM) Digital library were screened, with a proportion screened independently by 2 authors. Data synthesis and interpretation were undertaken using a deductive iterative process. External validity checking was undertaken by an independent researcher. A narrative synthesis of the findings was structured around the components of the capability, opportunity, motivation, behavior change model and the theoretical domains framework (TDF).

RESULTS

Of the 7640 identified studies, 41 were included in the review. Factors related to uptake (U), engagement (E), or both (B) were identified. Under capability, the main factors identified were app literacy skills (B), app awareness (U), available user guidance (B), health information (E), statistical information on progress (E), well-designed reminders (E), features to reduce cognitive load (E), and self-monitoring features (E). Availability at low cost (U), positive tone, and personalization (E) were identified as physical opportunity factors, whereas recommendations for health and well-being apps (U), embedded health professional support (E), and social networking (E) possibilities were social opportunity factors. Finally, the motivation factors included positive feedback (E), available rewards (E), goal setting (E), and the perceived utility of the app (E).

CONCLUSIONS

Across a wide range of populations and behaviors, 26 factors relating to capability, opportunity, and motivation appear to influence the uptake of and engagement with health and well-being smartphone apps. Our recommendations may help app developers, health app portal developers, and policy makers in the optimization of health and well-being apps.

Smartphone apps on burns first aid: A review of the advice

AIMS

Many websites giving first aid advice are disappointingly inaccurate and at times dangerous in regard to burn injuries. With more patients relying on their smart phones to obtain online information the aim of this study was to compare first aid applications (apps) burn advice against those guidelines set by the British Burns Association (BBA).

METHOD

A content analysis of all freely available English written first aid apps from Google Play and the Apple Store was performed. The information was compared against BBA guidance which was split into 12 domains and scored appropriately.

RESULTS

61 of the 103 first aid apps included in the study, had information on the treatment of burn injuries. The mean score for all apps was 3.3 out of 12. 85% of apps postulated the need to cool the burn. However, only 11% of apps stipulated the need for 20min of cooling, while 3% suggested the burn can be cooled up to 3h post injury. Disappointingly even apps produced by reputable first aid charities scored poorly.

CONCLUSION

Burns first aid is documented as being poorly given in the community. With easy access to the internet and specifically smart device apps, more needs to be done to improve burn first aid information online.