Self-assessment tool of disease activity of rheumatoid arthritis by using a smartphone application

Toward Telemonitoring in Immune-Mediated Inflammatory Diseases: Protocol for a Mixed Attention Model Study

BACKGROUND

Rheumatic and musculoskeletal diseases (RMDs) are chronic diseases that may alternate between asymptomatic periods and flares. These conditions require complex treatments and close monitoring by rheumatologists to mitigate their effects and improve the patient's quality of life. Often, delays in outpatient consultations or the patient's difficulties in keeping appointments make such close follow-up challenging. For this reason, it is very important to have open communication between patients and health professionals. In this context, implementing telemonitoring in the field of rheumatology has great potential, as it can facilitate the close monitoring of patients with RMDs. The use of these tools helps patients self-manage certain aspects of their disease. This could result in fewer visits to emergency departments and consultations, as well as enable better therapeutic compliance and identification of issues that would otherwise go unnoticed.

OBJECTIVE

The main objective of this study is to evaluate the implementation of a hybrid care model called the mixed attention model (MAM) in clinical practice and determine whether its implementation improves clinical outcomes compared to conventional follow-up.

METHODS

This is a multicenter prospective observational study involving 360 patients with rheumatoid arthritis (RA) and spondylarthritis (SpA) from 5 Spanish hospitals. The patients will be followed up by the MAM protocol, which is a care model that incorporates a digital tool consisting of a mobile app that patients can use at home and professionals can review asynchronously to detect incidents and follow patients' clinical evolution between face-to-face visits. Another group of patients, whose follow-up will be conducted in accordance with a traditional face-to-face care model, will be assessed as the control group. Sociodemographic characteristics, treatments, laboratory parameters, assessment of tender and swollen joints, visual analog scale for pain, and electronic patient-reported outcome (ePRO) reports will be collected for all participants. In the MAM group, these items will be self-assessed via both the mobile app and during face-to-face visits with the rheumatologist, who will do the same for patients included in the traditional care model. The patients will be able to report any incidence related to their disease or treatment through the mobile app.

RESULTS

Participant recruitment began in March 2024 and will continue until December 2024. The follow-up period will be extended by 12 months for all patients. Data collection and analysis are scheduled for completion in December 2025.

CONCLUSIONS

This paper aims to provide a detailed description of the development and implementation of a digital solution, specifically an MAM. The goal is to achieve significant economic and psychosocial impact within our health care system by enhancing control over RMDs.

TRIAL REGISTRATION

ClinicalTrials.gov NCT06273306; https://clinicaltrials.gov/ct2/show/NCT06273306.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/55829.

Comparison of Remotely Applied and Face-to-Face Disease Activity Scores in Saudi Arabian Patients With Rheumatoid Arthritis: A Prospective Cohort Study

OBJECTIVES

 This study aimed to assess the disease activity indices (DAI) of rheumatoid arthritis (RA) by telephone-based tele-visits compared to face-to-face clinic encounters.

METHODS

Patients with RA attending outpatient clinics between December 2021 and May 2022 were prospectively recruited. Disease activity assessments were initially performed in the clinic using the disease activity score 28-C-reactive protein (DAS28-CRP) and disease activity score 28-erythrocyte sedimentation rate (DAS28-ESR). Within two weeks of the clinic visit, a telephone-based assessment gathered information on demographics, Routine Assessment of Patient Index Data 3 (RAPID3) score, and satisfaction. Disease activity scores were dichotomized into remission or low disease activity and moderate to high disease activity.

RESULTS

 A total of 78 patients completed the two-point interview. Of those, 62 (79.49%) were women, with a mean age of 54.73±13.71 years. Seropositivity for rheumatoid factor and/or anti-citrullinated peptide was observed in 51 (83.61%) participants. Twenty-seven percent of the patients were classified as in remission or low disease activity by RAPID3. This was 71% for DAS28-CRP and 33% for DAS28-ESR. Based on the dichotomized disease activity classification, the agreement percentage between RAPID3 and DAS28-ESR was 78.08%, while it was 47.22% between RAPID3 and DAS28-CRP, which resulted in kappa statistic values of 0.48 (moderate agreement) and 0.14 (low agreement), respectively. Satisfaction rates were low.

CONCLUSION

 Telephone-based RAPID3 showed a low-moderate agreeability compared to DAS28 and had low satisfaction rates. This suggests that tele-rheumatology care by this means was not feasible for following up with patients with RA and warrants further development.

Stepping Beyond Counts in Recovery of Total Hip Arthroplasty: A Prospective Study on Passively Collected Gait Metrics

Gait quality parameters have been used to measure recovery from total hip arthroplasty (THA) but are time-intensive and previously could only be performed in a lab. Smartphone sensor data and algorithmic advances presently allow for the passive collection of qualitative gait metrics. The purpose of this prospective study was to observe the recovery of physical function following THA by assessing passively collected pre- and post-operative gait quality metrics. This was a multicenter, prospective cohort study. From six weeks pre-operative through to a minimum 24 weeks post-operative, 612 patients used a digital care management application that collected gait metrics. Average weekly walking speed, step length, timing asymmetry, and double limb support percentage pre- and post-operative values were compared with a paired-sample t-test. Recovery was defined as the post-operative week when the respective gait metric was no longer statistically inferior to the pre-operative value. To control for multiple comparison error, significance was set at p < 0.002. Walking speeds and step length were lowest, and timing asymmetry and double support percentage were greatest at week two post-post-operative (p < 0.001). Walking speed (1.00 ± 0.14 m/s, p = 0.04), step length (0.58 ± 0.06 m/s, p = 0.02), asymmetry (14.5 ± 19.4%, p = 0.046), and double support percentage (31.6 ± 1.5%, p = 0.0089) recovered at 9, 8, 7, and 10 weeks post-operative, respectively. Walking speed, step length, asymmetry, and double support all recovered beyond pre-operative values at 13, 17, 10, and 18 weeks, respectively (p < 0.002). Functional recovery following THA can be measured via passively collected gait quality metrics using a digital care management platform. The data suggest that metrics of gait quality are most negatively affected two weeks post-operative; recovery to pre-operative levels occurs at approximately 10 weeks following primary THA, and follows a slower trajectory compared to previously reported step count recovery trajectories.

Stepping beyond Counts in Recovery of Total Knee Arthroplasty: A Prospective Study on Passively Collected Gait Metrics

Advances in algorithms developed from sensor-based technology data allow for the passive collection of qualitative gait metrics beyond step counts. The purpose of this study was to evaluate pre- and post-operative gait quality data to assess recovery following primary total knee arthroplasty. This was a multicenter, prospective cohort study. From 6 weeks pre-operative through to 24 weeks post-operative, 686 patients used a digital care management application to collect gait metrics. Average weekly walking speed, step length, timing asymmetry, and double limb support percentage pre- and post-operative values were compared with a paired-samples t-test. Recovery was operationally defined as when the respective weekly average gait metric was no longer statistically different than pre-operative. Walking speed and step length were lowest, and timing asymmetry and double support percentage were greatest at week two post-operative (p < 0.0001). Walking speed recovered at 21 weeks (1.00 m/s, p = 0.063) and double support percentage recovered at week 24 (32%, p = 0.089). Asymmetry percentage was recovered at 13 weeks (14.0%, p = 0.23) and was consistently superior to pre-operative values at week 19 (11.1% vs. 12.5%, p < 0.001). Step length did not recover during the 24-week period (0.60 m vs. 0.59 m, p = 0.004); however, this difference is not likely clinically relevant. The data suggests that gait quality metrics are most negatively affected two weeks post-operatively, recover within the first 24-weeks following TKA, and follow a slower trajectory compared to previously reported step count recoveries. The ability to capture new objective measures of recovery is evident. As more gait quality data is accrued, physicians may be able to use passively collected gait quality data to help direct post-operative recovery using sensor-based care pathways.

Design theory to better target public health priorities: An application to Lyme disease in France

In the context of complex public health challenges led by interdependent changes such as climate change, biodiversity loss, and resistance to treatment, it is important to mobilize methods that guide us to generate innovative interventions in a context of uncertainty and unknown. Here, we mobilized the concept-knowledge (CK) design theory to identify innovative, cross-sectoral, and cross-disciplinary research and design programs that address the challenges posed by tick-borne Lyme disease in France, which is of growing importance in the French public health and healthcare systems. Within the CK methodological framework, we developed an iterative approach based on literature analysis, expert interviews, analysis of active French research projects, and work with CK experts to contribute to design "an action plan against Lyme disease." We produced a CK diagram that highlights innovative concepts that could be addressed in research projects. The outcome is discussed within four areas: (i) effectiveness; (ii) environmental sustainability in prevention actions; (iii) the promotion of constructive involvement of citizens in Lyme challenges; and (iv) the development of care protocols for chronic conditions with an unknown diagnosis. Altogether, our analysis questioned the health targets ranging from population to ecosystem, the citizen involvement, and the patient consideration. This means integrating social and ecological science, as well as the multidisciplinary medical patient journey, from the start. CK theory is a promising framework to assist public health professionals in designing programs for complex yet urgent contexts, where research and data collection are still not sufficient to provide clear guidance.

Future challenges in rheumatology – is telemedicine the solution?

The COVID-19 pandemic has become an unprecedented facilitator of rapid telehealth expansion within rheumatology. Due to demographic shifts and workforce shortages in the future, new models of rheumatology care will be expected to emerge, with a growing footprint of telehealth interventions. Telehealth is already being used to monitor patients with rheumatic diseases and initial studies show good results in terms of safety and disease progression. It is being used as a tool for appointment prioritization and triage, and there is good evidence for using telehealth in rehabilitation, patient education and self-management interventions. Electronic patient-reported outcomes (ePROs) offer a number of long-term benefits and opportunities, and a routine collection of ePROs also facilitates epidemiological research that can inform future healthcare delivery. Telehealth solutions should be developed in close collaboration with all stakeholders, and the option of a telehealth visit must not deprive patients of the possibility to make use of a conventional ‘face-to-face’ visit. Future studies should especially focus on optimal models for rheumatology healthcare delivery to patients living in remote areas who are unable to use or access computer technology, and other patient groups at risk for disparity due to technical inequity and lack of knowledge.

[Telemedical care and IT-based systems in rheumatology]

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic and also the ever-increasing demands on the healthcare system, have led to a focus on the further development of telemedical services in rheumatology.

OBJECTIVE

What is the evidence for telemedical services in rheumatology?

MATERIAL AND METHODS

Narrative review of existing literature on telemedicine in rheumatology.

RESULTS

Electronic patient reported outcomes (ePROs) can be determined by patients from their home and sent electronically to the rheumatologist. In future, ePROs may help with the decision whether a patient needs to attend the clinic for a visit or the visit can be rescheduled due to remission and well-being. Telemedicine has already been used for well-controlled patients with rheumatic diseases with good results in terms of safety and disease activity compared to conventional face-to-face visits. Telemedicine represents an interesting tool for appointment prioritization and triaging, while automated algorithm-based applications are currently too imprecise for routine clinical use. The role of smartphone applications in the care of patients with rheumatic diseases is still unclear.

DISCUSSION

Telemedicine represents an interesting option for certain patient populations with rheumatic diseases. Apart from research on the effectiveness and safety of telemedical interventions, decision makers need to set clear rules on how telemedicine should be used to provide the best possible care for the individual patient.

Review of Wearable Devices and Data Collection Considerations for Connected Health

Wearable sensor technology has gradually extended its usability into a wide range of well-known applications. Wearable sensors can typically assess and quantify the wearer’s physiology and are commonly employed for human activity detection and quantified self-assessment. Wearable sensors are increasingly utilised to monitor patient health, rapidly assist with disease diagnosis, and help predict and often improve patient outcomes. Clinicians use various self-report questionnaires and well-known tests to report patient symptoms and assess their functional ability. These assessments are time consuming and costly and depend on subjective patient recall. Moreover, measurements may not accurately demonstrate the patient’s functional ability whilst at home. Wearable sensors can be used to detect and quantify specific movements in different applications. The volume of data collected by wearable sensors during long-term assessment of ambulatory movement can become immense in tuple size. This paper discusses current techniques used to track and record various human body movements, as well as techniques used to measure activity and sleep from long-term data collected by wearable technology devices.

An m-Health Intervention for Rheumatoid Arthritis in China ("Rheumatism Center" app): Study Protocol for a Prospective Randomized Controlled Trial

AIM

To study the feasibility and effectiveness of a m-Health app in improving the management of rheumatoid arthritis.

DESIGN

Randomized controlled trial.

METHODS

Sixty rheumatoid arthritis participants will be recruited for a 6-month feasibility study. Patients meeting the inclusion criteria will be randomly allocated to receive standard care or standard care plus the m-Health intervention. The primary outcome is the feasibility of a randomized controlled trial. In addition, we will investigate patient satisfaction in using the "Rheumatism Center" app in the intervention group. The secondary outcomes include the scores for the simplified disease activity index, clinical disease activity index, disease activity score 28, health assessment questionnaire and 6-item self-efficacy scale for chronic diseases. The assessments will be performed at baseline and at 4 weeks, 3 months and 6 months after the study is initiated. At the end of the study, we will also collect user views of the app through qualitative interviews.

RESULTS

This study is ongoing. The findings of this study will determine the feasibility and effectiveness of m-Health intervention in the management of rheumatoid arthritis, hoping to enhance the awareness of disease management and quality of life for rheumatoid arthritis patients.

Remote Measurement in Rheumatoid Arthritis: Qualitative Analysis of Patient Perspectives

BACKGROUND

Rheumatoid arthritis (RA) is characterized by recurrent fluctuations in symptoms such as joint pain, swelling, and stiffness. Remote measurement technologies (RMTs) offer the opportunity to track symptoms continuously and in real time; therefore, they may provide a more accurate picture of RA disease activity as a complement to prescheduled general practitioner appointments. Previous research has shown patient interest in remote symptom tracking in RA and has provided evidence for its clinical validity. However, there is a lack of co-design in the current development of systems, and the features of RMTs that best promote optimal engagement remain unclear.

OBJECTIVE

This study represents the first in a series of work that aims to develop a multiparametric RMT system for symptom tracking in RA. The objective of this study is to determine the important outcomes for disease management in patients with RA and how these can be best captured via remote measurement.

METHODS

A total of 9 patients (aged 23-77 years; mean 55.78, SD 17.54) with RA were recruited from King's College Hospital to participate in two semistructured focus groups. Both focus group discussions were conducted by a facilitator and a lived-experience researcher. The sessions were recorded, transcribed, independently coded, and analyzed for themes.

RESULTS

Thematic analysis identified a total of four overarching themes: important symptoms and outcomes in RA, management of RA symptoms, views on the current health care system, and views on the use of RMTs in RA. Mobility and pain were key symptoms to consider for symptom tracking as well as symptom triggers. There is a general consensus that the ability to track fluctuations and transmit such data to clinicians would aid in individual symptom management and the effectiveness of clinical care. Suggestions for visually capturing symptom fluctuations in an app were proposed.

CONCLUSIONS

The findings support previous work on the acceptability of RMT with RA disease management and address key outcomes for integration into a remote monitoring system for RA self-management and clinical care. Clear recommendations for RMT design are proposed. Future work will aim to take these recommendations into a user testing phase.

Managing patients using telerheumatology: Lessons from a pandemic

The coronavirus disease 2019 (COVID-19) pandemic has presented unique challenges to rheumatology provision. Measures to control the pandemic have limited face-to-face contact with rheumatology healthcare professionals. One innovation has been the widespread adoption of telerheumatology to assist in the care of patients with rheumatic and musculoskeletal diseases, building on an existing evidence base in rheumatology. Widespread adoption has only occurred following the COVID-19 pandemic. We discuss the evidence supporting telerheumatology adoption prior to the pandemic, and outline several innovative approaches used to assist in the care of rheumatology patients that have been introduced. Alongside the advantages of these interventions, we discuss the limitations and regulatory challenges. Advances must be balanced, considering wider issues of equity of access, implementation, adoption, and sustainability of telerheumatology post-pandemic. We propose it is not ‘if’, but ‘how’ rheumatologists embrace newer telerheumatology technology, outlining practice points and future research agenda.

Asynchronous mHealth Interventions in Rheumatoid Arthritis: Systematic Scoping Review

BACKGROUND

Mobile devices such as smartphones and tablets have surged in popularity in recent years, generating numerous possibilities for their use in health care as mobile health (mHealth) tools. One advantage of mHealth is that it can be provided asynchronously, signifying that health care providers and patients are not communicating in real time. The integration of asynchronous mHealth into daily clinical practice might therefore help to make health care more efficient for patients with rheumatoid arthritis (RA). The benefits have been reviewed in various medical conditions, such as diabetes and asthma, with promising results. However, to date, it is unclear what evidence exists for the use of asynchronous mHealth in the field of RA.

OBJECTIVE

The objective of this study was to map the different asynchronous mHealth interventions tested in clinical trials in patients with RA and to summarize the effects of the interventions.

METHODS

A systematic search of Pubmed, Scopus, Cochrane, and PsycINFO was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Studies were initially screened and later assessed by two independent researchers. Disagreements on inclusion or exclusion of studies were resolved by discussion.

RESULTS

The literature search yielded 1752 abstracts. After deduplication and screening, 10 controlled intervention studies were included. All studies were assessed to be at risk for bias in at least one domain of the Cochrane risk-of-bias tool. In the 10 selected studies, 4 different types of mHealth interventions were used: SMS reminders (to increase medication adherence or physical activity; n=3), web apps (for disease monitoring and/or to provide medical information; n=5), smartphone apps (for disease monitoring; n=1), and pedometers (to increase and track steps; n=1). Measured outcomes varied widely between studies; improvements were seen in terms of medication compliance (SMS reminders), reaching rapid remission (web app), various domains of physical activity (pedometer, SMS reminders, and web apps), patient-physician interaction (web apps), and self-efficacy (smartphone app).

CONCLUSIONS

SMS reminders, web apps, smartphone apps, and pedometers have been evaluated in intervention studies in patients with RA. These interventions have been used to monitor patients or to support them in their health behavior. The use of asynchronous mHealth led to desirable outcomes in nearly all studies. However, since all studies were at risk of bias and methods used were very heterogeneous, high-quality research is warranted to corroborate these promising results.

Automated Text Message-Enhanced Monitoring Versus Routine Monitoring in Early Rheumatoid Arthritis: A Randomized Trial

OBJECTIVE

Frequent monitoring of patients with early rheumatoid arthritis (RA) is required for achieving good outcomes. This study was undertaken to investigate the influence of text message (SMS)-enhanced monitoring on early RA outcomes.

METHODS

We randomized 166 patients with early, disease-modifying antirheumatic drug-naive RA to receive SMS-enhanced follow-up or routine care. All patients attended visits at 0, 3, and 6 months, and a follow-up visit at 12 months. Treatment was at the physicians' discretion. The intervention included 13 SMSs during weeks 0-24 with questions concerning medication problems (yes/no) and disease activity (patient global assessment [PtGA], scale 0-10). Patients were contacted if response SMSs indicated medication problems or PtGA exceeded predefined thresholds. Primary outcome was 6-month Boolean remission (no swollen or tender joints and normal C-reactive protein levels). Quality of life (QoL; measured by the Short Form 36 survey) and Disease Activity Score in 28 joints (DAS28) were assessed.

RESULTS

Six and 12-month follow-up data were available for 162 and 157 patients, respectively. In the intervention group, 46% of the patients (38 of 82) reported medication problems and 49% (40 of 82) reported text message PtGAs above the alarm limit. Remission rates at 6 months (P = 0.34) were 51% in the intervention group and 42% in the control group. These rates were 57% and 43% at 12 months (P = 0.17) in the intervention and control groups, respectively. The respective mean ± SD DAS28 scores for the intervention and control groups were 1.92 ± 1.12 and 2.22 ± 1.11 at 6 months (P = 0.09); and 1.79 ± 0.91 and 2.08 ± 1.22 at 12 months (P = 0.28). No differences in QoL were observed.

CONCLUSION

The study did not meet the primary outcome despite a trend favoring the intervention group. This may be explained by the notably high overall remission rates.

Outcomes, Satisfaction, and Costs of a Rheumatology Telemedicine Program: A Longitudinal Evaluation

OBJECTIVES

Rural veterans with inflammatory arthritis (IA) lack medical access because of geographic barriers. Telemedicine (TM) holds great promise in relieving these disparities. We have prospectively measured patient-centered data surrounding a TM care program at a federal health system and compared these with usual care (UC).

METHODS

Veterans with previously established IA were enrolled in TM follow-up. Data collected longitudinally before and after entering the program included Routine Assessment of Patient Index Data 3 (RAPID-3), out-of-pocket visit costs and distances traveled, and patient satisfaction instruments. Demographics were recorded. Similar data were collected on a convenience sample of concurrent IA patients receiving UC.

RESULTS

Eighty-five patients were observed, including 25 receiving TM care and 60 receiving UC. No differences in demographics, satisfaction scores, or RAPID-3 were noted at baseline between groups. Univariate linear regression of cross-sectional baseline data suggests satisfaction instrument scores were predicted by RAPID-3 (β = -0.64/10 points, p = 0.01), as well as distance (β = -0.19/100 miles, p = 0.02) and cost (β = -0.37/$100, p = 0.05). A multivariate model indicates both distance (β = -0.17/100 miles, p = 0.02) and RAPID-3 (β = -0.47/10 points, p < 0.03) were predictors for visit satisfaction. In longitudinal follow-up via TM, satisfaction (Δ = 0.03, p = 0.94) and RAPID-3 (Δ = 0.27, p = 0.89) remained similar to baseline among TM patients, whereas distance traveled (Δ = -384.8 miles/visit, p < 0.01) and visit costs (Δ = -$113.8/visit, p < 0.01) were reduced.

CONCLUSIONS

Patient-reported outcomes for care delivered via TM were similar to UC, with significant cost and distance savings. Patient-centered factors such as distance to care should be considered in design care delivery models, as they appear to drive patient satisfaction in conjunction with disease control.

Mobile Health Apps for Self-Management of Rheumatic and Musculoskeletal Diseases: Systematic Literature Review

BACKGROUND

Although the increasing availability of mobile health (mHealth) apps may enable people with rheumatic and musculoskeletal diseases (RMDs) to better self-manage their health, there is a general lack of evidence on ways to ensure appropriate development and evaluation of apps.

OBJECTIVE

This study aimed to obtain an overview on existing mHealth apps for self-management in patients with RMDs, focusing on content and development methods.

METHODS

A search was performed up to December 2017 across 5 databases. For each publication relevant to an app for RMDs, information on the disease, purpose, content, and development strategies was extracted and qualitatively assessed.

RESULTS

Of 562 abstracts, 32 were included in the analysis. Of these 32 abstracts, 11 (34%) referred to an app linked to a connected device. Most of the apps targeted rheumatoid arthritis (11/32, 34%). The top three aspects addressed by the apps were pain (23/32, 71%), fatigue (15/32, 47%), and physical activity (15/32, 47%). The development process of the apps was described in 84% (27/32) of the articles and was of low to moderate quality in most of the cases. Despite most of the articles having been published within the past two years, only 5 apps were still commercially available at the time of our search. Moreover, only very few studies showed improvement of RMD outcome measures.

CONCLUSIONS

The development process of most apps was of low or moderate quality in many studies. Owing to the increasing RMD patients' willingness to use mHealth apps for self-management, optimal standards and quality assurance of new apps are mandatory.

Digital Tracking of Rheumatoid Arthritis Longitudinally (DIGITAL) Using Biosensor and Patient-Reported Outcome Data: Protocol for a Real-World Study

Background

Rheumatoid arthritis (RA) is a condition with symptoms that vary over time. The typical 3- to 6-month interval between physician visits may lead to patients failing to recall or underreporting symptoms experienced during the interim. Wearable digital technology enables the regular passive collection of patients’ biometric and activity data. If it is shown to be strongly related to data captured by patient-reported outcome (PRO) measures, information collected passively from wearable digital technology could serve as an objective proxy or be complementary to patients’ subjective experience of RA symptoms.

Objective

The goal of this study is to characterize the extent to which digital measures collected from a consumer-grade smartwatch agree with measures of RA disease activity and other PROs collected via a smartphone app.

Methods

This observational study will last 6 months for each participant. We aim to recruit 250 members of the ArthritisPower registry with an RA diagnosis who will receive a smartwatch to wear for the period of the study. From the ArthritisPower mobile app on their own smartphone device, participants will be prompted to answer daily and weekly electronic PRO (ePRO) measures for the first 3 months.

Results

The study was launched in December 2018 and will require up to 18 months to complete. Study results are expected to be published by the end of 2021.

Conclusions

The completion of this study will provide important data regarding the following: (1) the relationship between passively collected digital measures related to activity, heart rate, and sleep collected from a smartwatch with ePROs related to pain, fatigue, physical function, and RA flare entered via smartphone app; (2) determine predictors of adherence with smartwatch and smartphone app technology; and (3) assess the effect of study-specific reminders on adherence with the smartwatch.

International Registered Report Identifier (IRRID)

DERR1-10.2196/14665

Mobile Apps for Individuals With Rheumatoid Arthritis: A Systematic Review

BACKGROUND

Mobile health applications (apps) have the potential to help individuals with chronic illnesses learn about, monitor, and manage their condition, but these apps are largely unexamined, with the state and direction of development unclear.

OBJECTIVE

We performed a systematic review of publicly available apps, directed toward individuals with rheumatoid arthritis (RA); described their current features; and determined areas of unmet need.

METHODS

We searched the iTunes and Google Play App Stores for the term "arthritis" and reviewed the descriptions of these apps for specific mentions of RA. Applications that met inclusion criteria were downloaded and reviewed. Using a set of quality measures identified from literature review, we assessed each app for 4 features: basic characteristics, content source, functionality, and security. Frequencies for each feature were recorded, and percentages were calculated.

RESULTS

Twenty apps intended for use by RA patients were identified in December 2016. Fifty percent of apps (n = 10) offered only symptom tracking. Five (20%) provided only information about RA, and 5 (20%) engaged patients by providing both symptom tracking and educational information. Fewer than 50% of apps provided means to contact health care providers or link to an online community, and only 6 (30%) offered security protection for the user.

CONCLUSIONS

Most current RA apps do not provide a comprehensive experience for individuals with RA. Areas for optimization include the implementation of smartphone accessibility features and secure methods of protecting individual health information.

Pharmacodynamic Monitoring of Biological Therapies in Chronic Inflammatory Diseases

BACKGROUND

Psoriasis, psoriatic arthritis, spondyloarthritis, rheumatoid arthritis, ulcerative colitis, and Crohn disease share similar underlying pathophysiological processes, providing the opportunity to treat the patients using similar biological therapies. Failure of biological treatments due to underexposure can be managed by therapeutic drug monitoring. Adjusting the treatment based on pharmacokinetic monitoring can be further improved by taking pharmacodynamic parameters such as clinical and molecular markers into account.

METHODS

Here, we critically evaluate the existing evidence, the hurdles to be taken, and the opportunities for a widespread implementation of pharmacodynamic monitoring.

RESULTS

Pharmacodynamic monitoring typically is the monitoring of biochemical markers. A pharmacodynamic marker preferably is specific for the pharmacological action of a drug, but most of the time nonspecific pharmacodynamic markers are used, such as C-reactive protein and the erythrocyte sedimentation rate. Clinical pharmacodynamic markers typically evaluate physical variables or symptoms. Although physician-reported outcomes have been studied for a longer time and often have been shown to correlate well with molecular pharmacodynamic markers and treatment outcomes, the introduction of mobile health or mHealth technologies caused a shift toward patient-reported outcomes, with the associated challenge to consistently reflect the inflammatory state, thereby preventing undertreatment or unnecessary overdosing of patients.

CONCLUSIONS

The primary goal of pharmacodynamic monitoring is to optimize the response, but it can also have an impact on safety, costs, patient adherence, etc. Ideally, the constant remote monitoring of patient-reported disease activity is expected to become the standard, facilitated by mHealth technologies.

Assessing prognosis and prediction of treatment response in early rheumatoid arthritis: systematic reviews

BACKGROUND

Rheumatoid arthritis (RA) is a chronic, debilitating disease associated with reduced quality of life and substantial costs. It is unclear which tests and assessment tools allow the best assessment of prognosis in people with early RA and whether or not variables predict the response of patients to different drug treatments.

OBJECTIVE

To systematically review evidence on the use of selected tests and assessment tools in patients with early RA (1) in the evaluation of a prognosis (review 1) and (2) as predictive markers of treatment response (review 2).

DATA SOURCES

Electronic databases (e.g. MEDLINE, EMBASE, The Cochrane Library, Web of Science Conference Proceedings; searched to September 2016), registers, key websites, hand-searching of reference lists of included studies and key systematic reviews and contact with experts.

STUDY SELECTION

Review 1 - primary studies on the development, external validation and impact of clinical prediction models for selected outcomes in adult early RA patients. Review 2 - primary studies on the interaction between selected baseline covariates and treatment (conventional and biological disease-modifying antirheumatic drugs) on salient outcomes in adult early RA patients.

RESULTS

Review 1 - 22 model development studies and one combined model development/external validation study reporting 39 clinical prediction models were included. Five external validation studies evaluating eight clinical prediction models for radiographic joint damage were also included. c-statistics from internal validation ranged from 0.63 to 0.87 for radiographic progression (different definitions, six studies) and 0.78 to 0.82 for the Health Assessment Questionnaire (HAQ). Predictive performance in external validations varied considerably. Three models [(1) Active controlled Study of Patients receiving Infliximab for the treatment of Rheumatoid arthritis of Early onset (ASPIRE) C-reactive protein (ASPIRE CRP), (2) ASPIRE erythrocyte sedimentation rate (ASPIRE ESR) and (3) Behandelings Strategie (BeSt)] were externally validated using the same outcome definition in more than one population. Results of the random-effects meta-analysis suggested substantial uncertainty in the expected predictive performance of models in a new sample of patients. Review 2 - 12 studies were identified. Covariates examined included anti-citrullinated protein/peptide anti-body (ACPA) status, smoking status, erosions, rheumatoid factor status, C-reactive protein level, erythrocyte sedimentation rate, swollen joint count (SJC), body mass index and vascularity of synovium on power Doppler ultrasound (PDUS). Outcomes examined included erosions/radiographic progression, disease activity, physical function and Disease Activity Score-28 remission. There was statistical evidence to suggest that ACPA status, SJC and PDUS status at baseline may be treatment effect modifiers, but not necessarily that they are prognostic of response for all treatments. Most of the results were subject to considerable uncertainty and were not statistically significant.

LIMITATIONS

The meta-analysis in review 1 was limited by the availability of only a small number of external validation studies. Studies rarely investigated the interaction between predictors and treatment.

SUGGESTED RESEARCH PRIORITIES

Collaborative research (including the use of individual participant data) is needed to further develop and externally validate the clinical prediction models. The clinical prediction models should be validated with respect to individual treatments. Future assessments of treatment by covariate interactions should follow good statistical practice.

CONCLUSIONS

Review 1 - uncertainty remains over the optimal prediction model(s) for use in clinical practice. Review 2 - in general, there was insufficient evidence that the effect of treatment depended on baseline characteristics.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42016042402.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

Using a ResearchKit Smartphone App to Collect Rheumatoid Arthritis Symptoms From Real-World Participants: Feasibility Study

Background

Using smartphones to enroll, obtain consent, and gather self-reported data from patients has the potential to enhance our understanding of disease burden and quantify physiological impact in the real world. It may also be possible to harness integral smartphone sensors to facilitate remote collection of clinically relevant data.

Objective

We conducted the Patient Rheumatoid Arthritis Data From the Real World (PARADE) observational study using a customized ResearchKit app with a bring-your-own-device approach. Our objective was to assess the feasibility of using an entirely digital approach (social media and smartphone app) to conduct a real-world observational study of patients with rheumatoid arthritis.

Methods

We conducted this observational study using a customized ResearchKit app with a bring-your-own-device approach. To recruit patients, the PARADE app, designed to guide patients through a series of tasks, was publicized via social media platforms and made available for patients in the United States to download from the Apple App Store. We collected patient-reported data, such as medical history, rheumatoid arthritis-related medications (past and present), and a range of patient-reported outcome measures. We included in the assessment a joint-pain map and a novel objective assessment of wrist range of movement, measured by the smartphone-embedded gyroscope and accelerometer.

Results

Within 1 month of recruitment via social media campaigns, 399 participants self-enrolled, self-consented, and provided complete demographic data. Joint pain was the most frequently reported rheumatoid arthritis symptom to bother study participants (344/393, 87.5%). Severe patient-reported wrist pain appeared to be inversely linked with the range of wrist movement measured objectively by the app. At study entry, 292 of 399 participants (73.2%) indicated a preference for participating in a mobile app–based study. The number of participants in the study declined to 45 of 399 (11.3%) at week 12.

Conclusions

Despite the declining number of participants over time, the combination of social media and smartphone app with sensor integration was a feasible and cost-effective approach for the collection of patient-reported data in rheumatoid arthritis. Integral sensors within smartphones can be harnessed to provide novel end points, and the novel wrist range of movement test warrants further clinical validation.

A Novel Mobile App and Population Management System to Manage Rheumatoid Arthritis Flares: Protocol for a Randomized Controlled Trial

Background

Rheumatoid arthritis flares have a profound effect on patients, causing pain and disability. However, flares often occur between regularly scheduled health care provider visits and are, therefore, difficult to monitor and manage. We sought to develop a mobile phone app combined with a population management system to help track RA flares between visits.

Objective

The objective of this study is to implement the mobile app plus the population management system to monitor rheumatoid arthritis disease activity between scheduled health care provider visits over a period of 6 months.

Methods

This is a randomized controlled trial that lasts for 6 months for each participant. We aim to recruit 190 patients, randomized 50:50 to the intervention group versus the control group. The intervention group will be assigned the mobile app and be prompted to answer daily questionnaires sent to their mobile devices. Both groups will be assigned a population manager, who will communicate with the participants via telephone at 6 weeks and 18 weeks. The population manager will also communicate with the participants in the intervention group if their responses indicate a sustained increase in rheumatoid arthritis disease activity. To assess patient satisfaction, the primary outcomes will be scores on the Treatment Satisfaction Questionnaire for Medication as well as the Perceived Efficacy in Patient-Physician Interactions questionnaire at 6 months. To determine the effect of the mobile app on rheumatoid arthritis disease activity, the primary outcome will be the Clinical Disease Activity Index at 6 months.

Results

The trial started in November 2016, and an estimated 2.5 years will be necessary to complete the study. Study results are expected to be published by the end of 2019.

Conclusions

The completion of this study will provide important data regarding the following: (1) the assessment of validated outcome measures to assess rheumatoid arthritis disease activity with a mobile app between routinely scheduled health care provider visits, (2) patient engagement in monitoring their condition, and (3) communication between patients and health care providers through the population management system.

Trial Registration

ClinicalTrials.gov NCT02822521, http://clinicaltrials.gov/ct2/show/NCT02822521 (Archived by WebCite at http://www.webcitation.org/6xed3kGPd)

IMPLEMENTATION OF A SMARTPHONE AS A WIRELESS ACCELEROMETER PLATFORM FOR QUANTIFYING HEMIPLEGIC GAIT DISPARITY IN A FUNCTIONALLY AUTONOMOUS CONTEXT

The utility of the smartphone, such as the iPhone, constitutes considerable potential for the advancement of the biomedical and healthcare industry. A notable feature of the iPhone is the capacity to combine the internal accelerometer sensor with a software application to enable the functionality of a wireless accelerometer platform. Preliminary research has demonstrated the iPhone’s ability to quantify features of healthy gait. The research applies a single iPhone mounted proximal to the lateral malleolus of the affected leg and subsequently the unaffected leg to ascertain quantified disparity of hemiplegic gait from an engineering proof of concept perspective. In order to maintain a consistent gait velocity, a constant velocity treadmill is incorporated into the research endeavor. Post-processing of the gait acceleration waveform is greatly facilitated through the use of a software automation program using Matlab that emphasizes on the rhythmicity of gait. Two gait parameters were obtained: stance-to-stance temporal disparity and stance-to-stance time-averaged acceleration, and demonstrated considerable accuracy, consistency, and reliability. As noted per the constant treadmill velocity, stance-to-stance temporal disparity for the affected and unaffected legs was established as not statistically significant. A statistical significance was determined for the stance-to-stance time-averaged acceleration regarding the affected and unaffected legs. The iPhone application represents a wireless accelerometer platform capable of identifying statistically significant and quantified disparity of hemiplegic gait features through automated post-processing in a functionally autonomous environment.

Evidence assessing the diagnostic performance of medical smartphone apps: a systematic review and exploratory meta-analysis

OBJECTIVE

The number of mobile applications addressing health topics is increasing. Whether these apps underwent scientific evaluation is unclear. We comprehensively assessed papers investigating the diagnostic value of available diagnostic health applications using inbuilt smartphone sensors.

METHODS

Systematic Review-MEDLINE, Scopus, Web of Science inclusive Medical Informatics and Business Source Premier (by citation of reference) were searched from inception until 15 December 2016. Checking of reference lists of review articles and of included articles complemented electronic searches. We included all studies investigating a health application that used inbuilt sensors of a smartphone for diagnosis of disease. The methodological quality of 11 studies used in an exploratory meta-analysis was assessed with the Quality Assessment of Diagnostic Accuracy Studies 2 tool and the reporting quality with the 'STAndards for the Reporting of Diagnostic accuracy studies' (STARD) statement. Sensitivity and specificity of studies reporting two-by-two tables were calculated and summarised.

RESULTS

We screened 3296 references for eligibility. Eleven studies, most of them assessing melanoma screening apps, reported 17 two-by-two tables. Quality assessment revealed high risk of bias in all studies. Included papers studied 1048 subjects (758 with the target conditions and 290 healthy volunteers). Overall, the summary estimate for sensitivity was 0.82 (95 % CI 0.56 to 0.94) and 0.89 (95 %CI 0.70 to 0.97) for specificity.

CONCLUSIONS

The diagnostic evidence of available health apps on Apple's and Google's app stores is scarce. Consumers and healthcare professionals should be aware of this when using or recommending them.

PROSPERO REGISTRATION NUMBER

42016033049.

Telemedicine for patients with rheumatic diseases: Systematic review and proposal for research agenda

OBJECTIVE

To systematically review the scientific literature regarding tele-rheumatology and draw conclusions about feasibility, effectiveness, and patient satisfaction.

METHODS

PubMed, Scopus, and Cochrane database searches were performed (April 2016) using relevant MeSH and keyword terms for telemedicine and rheumatic diseases. Articles were selected if reporting outcomes for feasibility, effectiveness, and patient satisfaction and methodologically appraised using the Cochrane Collaboration's tool for assessing risk of bias and a modified version of CONSORT 2010 Statement.

RESULTS

A total of 177 articles were screened, 23 were selected for the present review but only 9 were RCTs. Five studies reported on feasibility, 14 effectiveness, and 9 satisfaction rates for different tele-rheumatology interventions grouped in synchronous (remotely delivered consultation) and asynchronous (remote disease activity assessment; tele-monitoring of treatment strategies or rehabilitation; and remotely delivered self-management programs). Seven studies (30.4%) were on rheumatoid arthritis, 2 (8.7%) were on systemic sclerosis (1 including also rheumatoid arthritis patients), 5 (21.7%) on fibromyalgia, 2 (8.7%) on osteoarthritis, 3 (13.0%) on juvenile idiopathic arthritis and 4 (17.4%) on mixed disease cohorts. Interventions and outcomes heterogeneity prevented meta-analysis of results. Overall, feasibility and patient satisfaction rates were high or very high across intervention types. Effectiveness was equal or higher than standard face-to-face approach in controlled trials which, however, were affected by small sample size and lack of blinding participants according to appraisal tools.

CONCLUSION

Telemedicine may provide a well-accepted way to remotely deliver consultation, treatment and monitoring disease activity in rheumatology. Higher quality RCTs demonstrating effectiveness of different tele-rheumatology interventions are needed.

Apps for People With Rheumatoid Arthritis to Monitor Their Disease Activity: A Review of Apps for Best Practice and Quality

Background

Rheumatoid arthritis (RA) is a chronic inflammatory arthritis requiring long-term treatment with regular monitoring by a rheumatologist to achieve good health outcomes. Since people with RA may wish to monitor their own disease activity with a smartphone app, it is important to understand the functions and quality of apps for this purpose.

Objective

The aim of our study was to assess the features and quality of apps to assist people to monitor their RA disease activity by (1) summarizing the available apps, particularly the instruments used for measurement of RA disease activity; (2) comparing the app features with American College of Rheumatology and European League against Rheumatism (ACR and EULAR) guidelines for monitoring of RA disease activity; and (3) rating app quality with the Mobile App Rating Scale (MARS).

Methods

Systematic searches of the New Zealand iTunes and Google Play app stores were used to identify all apps for monitoring of RA disease activity that could be used by people with RA. The apps were described by both key metadata and app functionality. App adherence with recommendations for monitoring of RA disease activity in clinical practice was evaluated by identifying whether apps included calculation of a validated composite disease activity measure and recorded results for future retrieval. App quality was assessed by 2 independent reviewers using the MARS.

Results

The search identified 721 apps in the Google Play store and 216 in the iTunes store, of which 19 unique apps met criteria for inclusion (8 from both app stores, 8 iTunes, and 3 Google Play). In total, 14 apps included at least one validated instrument measuring RA disease activity; 7 of 11 apps that allowed users to enter a joint count used the standard 28 swollen and tender joint count; 8 apps included at least one ACR and EULAR-recommended RA composite disease activity (CDA) measure; and 10 apps included data storage and retrieval. Only 1 app, Arthritis Power, included both an RA CDA measure and tracked data, but this app did not include the standard 28 tender and swollen joint count. The median overall MARS score for apps was 3.41/5. Of the 6 apps that scored ≥4/5 on the overall MARS rating, only 1 included a CDA score endorsed by ACR and EULAR; however, this app did not have a data tracking function.

Conclusions

This review found a lack of high-quality apps for longitudinal assessment of RA disease activity. Current apps fall into two categories: simple calculators primarily for rheumatologists and data tracking tools for people with RA. The latter do not uniformly collect data using validated instruments or composite disease activity measures. There is a need for appropriate, high-quality apps for use by rheumatologists and patients together in co-management of RA.

The Role of Gait Analysis in the Evaluation of Patients with Cervical Myelopathy: A Literature Review Study

BACKGROUND

Gait analysis represents one of the newest methodologies used in the clinical evaluation of patients with cervical myelopathy (CM).

OBJECTIVE

To describe the role of gait analysis in the clinical evaluation of patients with CM, as well as its potential role in the evaluation of the functional outcome of any surgical intervention.

METHODS

A literature review was performed in the PubMed, OVID, and Google Scholar medical databases, from January 1995 to August 2016, using the terms "analysis," "anterior," "cervical myelopathy," "gait," "posterior," and "surgery." Clinical series comparing the gait patterns of patients with CM with healthy controls, as well as series evaluating gait and walk changes before and after surgical decompression, were reviewed. Case studies were excluded.

RESULTS

Nine prospective and 3 retrospective studies were found. Most of the retrieved studies showed the presence of characteristic, abnormal gait patterns among patients with CM, consisting of decreased gait speed, cadence, step length, stride length, and single-limb support time. In addition, patients with CM routinely present increased step and stride time, double-limb support time, and step width, and they have altered knee and ankle joint range of motion, compared with healthy controls. Moreover, gait and walk analysis may provide accurate functional assessment of the functional outcome of patients with CM undergoing surgical decompression.

CONCLUSIONS

Gait analysis may well be a valuable and objective tool along with other parameters in the evaluation of functionality in patients with CM, as well as in the assessment of the outcome of any surgical intervention in these patients.

Wearable inertial sensors for human movement analysis

INTRODUCTION

The present review aims to provide an overview of the most common uses of wearable inertial sensors in the field of clinical human movement analysis.

AREAS COVERED

Six main areas of application are analysed: gait analysis, stabilometry, instrumented clinical tests, upper body mobility assessment, daily-life activity monitoring and tremor assessment. Each area is analyzed both from a methodological and applicative point of view. The focus on the methodological approaches is meant to provide an idea of the computational complexity behind a variable/parameter/index of interest so that the reader is aware of the reliability of the approach. The focus on the application is meant to provide a practical guide for advising clinicians on how inertial sensors can help them in their clinical practice. Expert commentary: Less expensive and more easy to use than other systems used in human movement analysis, wearable sensors have evolved to the point that they can be considered ready for being part of routine clinical routine.

Self-assessment of Rheumatoid Arthritis Disease Activity Using a Smartphone Application. Development and 3-month Feasibility Study

INTRODUCTION

This article is part of the Focus Theme of Methods of Information in Medicine on "Methodologies, Models and Algorithms for Patients Rehabilitation".

BACKGROUND

Rheumatoid arthritis (RA) is a progressive inflammatory disease that causes damage to multiple joints, decline in functional status, and premature mortality. Thus, effective and frequent objective assessments are necessary. Then, we developed a self-assessment system for RA patients based on a smartphone application.

OBJECTIVE

The purpose of this study was to investigate the feasibility of a self-assessment system for RA patients using a smartphone application.

METHODS

We measured daily disease activity in nine RA patients who used the smartphone application for a period of three months. A disease activity score (DAS28) predictive model was used and feedback comments relating to disease activity were shown to patients via the smartphone application each day. To assess participants' RA disease activity, the DAS28 based on the C-reactive protein level was measured by a rheumatologist during monthly clinical visits.

RESULTS

The disease activity measured by the application correlated well with the patients' actual disease activity during the 3-month period, as assessed by clinical examination. Furthermore, most participants gave favourable responses to a questionnaire administered at the end of the 3-month period containing questions relating to the ease of use and usefulness of the system.

CONCLUSIONS

The results of this feasibility study indicated that the DAS28 predictive model can longitudinally predict DAS28 and may be an acceptable and useful tool for assessment of RA disease activity for both patients and healthcare providers.

Comparison of self-administered survey questionnaire responses collected using mobile apps versus other methods

BACKGROUND

Self-administered survey questionnaires are an important data collection tool in clinical practice, public health research and epidemiology. They are ideal for achieving a wide geographic coverage of the target population, dealing with sensitive topics and are less resource-intensive than other data collection methods. These survey questionnaires can be delivered electronically, which can maximise the scalability and speed of data collection while reducing cost. In recent years, the use of apps running on consumer smart devices (i.e., smartphones and tablets) for this purpose has received considerable attention. However, variation in the mode of delivering a survey questionnaire could affect the quality of the responses collected.

OBJECTIVES

To assess the impact that smartphone and tablet apps as a delivery mode have on the quality of survey questionnaire responses compared to any other alternative delivery mode: paper, laptop computer, tablet computer (manufactured before 2007), short message service (SMS) and plastic objects.

SEARCH METHODS

We searched MEDLINE, EMBASE, PsycINFO, IEEEXplore, Web of Science, CABI: CAB Abstracts, Current Contents Connect, ACM Digital, ERIC, Sociological Abstracts, Health Management Information Consortium, the Campbell Library and CENTRAL. We also searched registers of current and ongoing clinical trials such as ClinicalTrials.gov and the World Health Organization (WHO) International Clinical Trials Registry Platform. We also searched the grey literature in OpenGrey, Mobile Active and ProQuest Dissertation & Theses. Lastly, we searched Google Scholar and the reference lists of included studies and relevant systematic reviews. We performed all searches up to 12 and 13 April 2015.

SELECTION CRITERIA

We included parallel randomised controlled trials (RCTs), crossover trials and paired repeated measures studies that compared the electronic delivery of self-administered survey questionnaires via a smartphone or tablet app with any other delivery mode. We included data obtained from participants completing health-related self-administered survey questionnaire, both validated and non-validated. We also included data offered by both healthy volunteers and by those with any clinical diagnosis. We included studies that reported any of the following outcomes: data equivalence; data accuracy; data completeness; response rates; differences in the time taken to complete a survey questionnaire; differences in respondent's adherence to the original sampling protocol; and acceptability to respondents of the delivery mode. We included studies that were published in 2007 or after, as devices that became available during this time are compatible with the mobile operating system (OS) framework that focuses on apps.

DATA COLLECTION AND ANALYSIS

Two review authors independently extracted data from the included studies using a standardised form created for this systematic review in REDCap. They then compared their forms to reach consensus. Through an initial systematic mapping on the included studies, we identified two settings in which survey completion took place: controlled and uncontrolled. These settings differed in terms of (i) the location where surveys were completed, (ii) the frequency and intensity of sampling protocols, and (iii) the level of control over potential confounders (e.g., type of technology, level of help offered to respondents). We conducted a narrative synthesis of the evidence because a meta-analysis was not appropriate due to high levels of clinical and methodological diversity. We reported our findings for each outcome according to the setting in which the studies were conducted.

MAIN RESULTS

We included 14 studies (15 records) with a total of 2275 participants; although we included only 2272 participants in the final analyses as there were missing data for three participants from one included study.Regarding data equivalence, in both controlled and uncontrolled settings, the included studies found no significant differences in the mean overall scores between apps and other delivery modes, and that all correlation coefficients exceeded the recommended thresholds for data equivalence. Concerning the time taken to complete a survey questionnaire in a controlled setting, one study found that an app was faster than paper, whereas the other study did not find a significant difference between the two delivery modes. In an uncontrolled setting, one study found that an app was faster than SMS. Data completeness and adherence to sampling protocols were only reported in uncontrolled settings. Regarding the former, an app was found to result in more complete records than paper, and in significantly more data entries than an SMS-based survey questionnaire. Regarding adherence to the sampling protocol, apps may be better than paper but no different from SMS. We identified multiple definitions of acceptability to respondents, with inconclusive results: preference; ease of use; willingness to use a delivery mode; satisfaction; effectiveness of the system informativeness; perceived time taken to complete the survey questionnaire; perceived benefit of a delivery mode; perceived usefulness of a delivery mode; perceived ability to complete a survey questionnaire; maximum length of time that participants would be willing to use a delivery mode; and reactivity to the delivery mode and its successful integration into respondents' daily routine. Finally, regardless of the study setting, none of the included studies reported data accuracy or response rates.

AUTHORS' CONCLUSIONS

Our results, based on a narrative synthesis of the evidence, suggest that apps might not affect data equivalence as long as the intended clinical application of the survey questionnaire, its intended frequency of administration and the setting in which it was validated remain unchanged. There were no data on data accuracy or response rates, and findings on the time taken to complete a self-administered survey questionnaire were contradictory. Furthermore, although apps might improve data completeness, there is not enough evidence to assess their impact on adherence to sampling protocols. None of the included studies assessed how elements of user interaction design, survey questionnaire design and intervention design might influence mode effects. Those conducting research in public health and epidemiology should not assume that mode effects relevant to other delivery modes apply to apps running on consumer smart devices. Those conducting methodological research might wish to explore the issues highlighted by this systematic review.

Predictors of students' self-reported adoption of a smartphone application for medical education in general practice

BACKGROUND

Smartphones and related applications are increasingly gaining relevance in the healthcare domain. We previously assessed the demands and preferences of medical students towards an application accompanying them during a course on general practice. The current study aims to elucidate the factors associated with adoption of such a technology. Therefore we provided students with a prototype of an application specifically related to their studies in general practice.

METHODS

A total estimation among students participating in a general practice examination at the Leipzig Medical School was conducted in May 2014. Students were asked to answer a structured self-designed questionnaire. Univariable comparisons were made to identify significant differences between those students who reported to have used the application frequently and those who did not. Multivariable binary logistic regression was used to reveal independent predictors of frequent application usage.

RESULTS

The response rate was 99.3 % (n = 305/307). The majority (59 %, n = 180/305) were female students. The mean age was 24.5 years and 79.9 % (n = 243/304) owned a smartphone or tablet computer. Regarding the usage of the provided application, 2.3 % (n = 7/303) did not use the app while 68.0 % (n = 206/303) replied to have used it more than five times. Frequent users significantly differed from non-frequent users with regard to being female rather than male, higher mobile device ownership, more frequent exchange about obtaining the course certificate, higher personal interest in new technologies, larger enjoyment of the technology, lower intention to not use smartphone applications in the future, better opinion towards smartphone applications for the profession of a doctor, higher perceived importance of medical applications on the job, higher compatibility of smartphone applications with personal work style, higher perceived relevance of university support and personal benefit of use. Multivariable analysis revealed a set of four variables independently predicting frequent usage: being female, a higher perceived benefit of the supplied application, a higher personal interest in new technologies, and a higher perceived impact of previous experiences on smartphone adoption (Pseudo-R(2)(Nagelkerke) = 0.245).

CONCLUSIONS

Understanding medical students' adoption of smartphone applications used for educational purposes may provide useful information to guide the implementation process as well as the design of respective applications.

Smartphone application for rheumatoid arthritis self-management: cross-sectional study revealed the usefulness, willingness to use and patients' needs

Patient-centered smartphone applications have potential to support rheumatoid arthritis (RA) self-management but remain almost unexplored in literature. Therefore, this study evaluated the usefulness of a smartphone application to support RA self-management, the willingness of RA patients to use and pay for it and the features the application should have. In this cross-sectional study, a questionnaire was developed to collect information on population, device ownership, usefulness and willingness to use and pay for a RA self-management application and application features. Descriptive statistics, Chi-square, Fisher's exact test, t test or Mann-Whitney's test and multivariate analysis were used. One hundred RA patients answered the questionnaire. Patients' mean age was 57 ± 11.9 years, most were females (91 %), with multiple drug regimens and a 40 % treatment non-compliance rate. Most patients believed that could have a more active role in self-management (94 %) and reported it would be useful to develop a RA self-management application (86 %). Patients willing to use an application (83 %) were younger, with a possible more active role in self-management, with access to a smartphone, and using short message service, electronic mail and Internet. Multivariate analysis confirmed these results, except the associations regarding access to a smartphone and use of electronic mail and Internet. Fifty-eight patients (82 %) were willing to pay for a RA self-management application and the most requested feature for it was information in a simple format. This study suggested the usefulness and patients' willingness to use and pay for a RA self-management application and provided insight on patients' needs.