Incorporating Novel Mobile Health Technologies Into Management of Knee Osteoarthritis in Patients Treated With Intra-Articular Hyaluronic Acid: Rationale and Protocol of a Randomized Controlled Trial

Digital health technologies: opportunities and challenges in rheumatology

The past decade in rheumatology has seen tremendous innovation in digital health technologies, including the electronic health record, virtual visits, mobile health, wearable technology, digital therapeutics, artificial intelligence and machine learning. The increased availability of these technologies offers opportunities for improving important aspects of rheumatology, including access, outcomes, adherence and research. However, despite its growth in some areas, particularly with non-health-care consumers, digital health technology has not substantially changed the delivery of rheumatology care. This Review discusses key barriers and opportunities to improve application of digital health technologies in rheumatology. Key topics include smart design, voice enablement and the integration of electronic patient-reported outcomes. Smart design involves active engagement with the end users of the technologies, including patients and clinicians through focus groups, user testing sessions and prototype review. Voice enablement using voice assistants could be critical for enabling patients with hand arthritis to effectively use smartphone apps and might facilitate patient engagement with many technologies. Tracking many rheumatic diseases requires frequent monitoring of patient-reported outcomes. Current practice only collects this information sporadically, and rarely between visits. Digital health technology could enable patient-reported outcomes to inform appropriate timing of face-to-face visits and enable improved application of treat-to-target strategies. However, best practice standards for digital health technologies do not yet exist. To achieve the potential of digital health technology in rheumatology, rheumatology professionals will need to be more engaged upstream in the technology design process and provide leadership to effectively incorporate the new tools into clinical care.

Precision medicine in the care of rheumatoid arthritis: Focus on prediction and prevention of future clinically-apparent disease

There is an emerging understanding that an individual's risk for future rheumatoid arthritis (RA) can be determined using a combination of factors while they are still in a state where clinically-apparent inflammatory arthritis (IA) is not yet present. Indeed, this concept has underpinned several completed and ongoing prevention trials in RA. Importantly, risk factors can be divided into modifiable (e.g. smoking, exercise, dental care and diet) and non-modifiable factors (e.g. genetics, sex, age). In addition, there are now several biomarkers including autoantibodies, inflammatory markers and imaging techniques that are highly predictive of future clinically-apparent IA/RA. Although none of the prevention studies have yet provided major breakthroughs, several of them have provided valuable insights that can help to improve the design of future clinical trials and enable RA prevention. In aggregate, these findings suggest that the most accurate disease prediction models will require the combination of demographic and clinical information, biomarkers and potentially medical imaging data to identify individuals for intervention. This review summarizes some of the key aspects around precision medicine in RA with special focus on disease prediction and prevention.

Consumer-Based Wearable Activity Trackers Increase Physical Activity Participation: Systematic Review and Meta-Analysis

BACKGROUND

The range of benefits associated with regular physical activity participation is irrefutable. Despite the well-known benefits, physical inactivity remains one of the major contributing factors to ill-health throughout industrialized countries. Traditional lifestyle interventions such as group education or telephone counseling are effective at increasing physical activity participation; however, physical activity levels tend to decline over time. Consumer-based wearable activity trackers that allow users to objectively monitor activity levels are now widely available and may offer an alternative method for assisting individuals to remain physically active.

OBJECTIVE

This review aimed to determine the effects of interventions utilizing consumer-based wearable activity trackers on physical activity participation and sedentary behavior when compared with interventions that do not utilize activity tracker feedback.

METHODS

A systematic review was performed searching the following databases for studies that included the use of a consumer-based wearable activity tracker to improve physical activity participation: Cochrane Controlled Register of Trials, MEDLINE, PubMed, Scopus, Web of Science, Cumulative Index of Nursing and Allied Health Literature, SPORTDiscus, and Health Technology Assessments. Controlled trials of adults comparing the use of a consumer-based wearable activity tracker with other nonactivity tracker-based interventions were included. The main outcome measures were physical activity participation and sedentary behavior. All studies were assessed for risk of bias, and the Grades of Recommendation, Assessment, Development, and Evaluation system was used to rank the quality of evidence. The guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement were followed. A random-effects meta-analysis was completed on the included outcome measures to estimate the treatment effect of interventions that included an activity tracker compared with a control group.

RESULTS

There was a significant increase in daily step count (standardized mean difference [SMD] 0.24; 95% CI 0.16 to 0.33; P<.001), moderate and vigorous physical activity (SMD 0.27; 95% CI 0.15 to 0.39; P<.001), and energy expenditure (SMD 0.28; 95% CI 0.03 to 0.54; P=.03) and a nonsignificant decrease in sedentary behavior (SMD -0.20; 95% CI -0.43 to 0.03; P=.08) following the intervention versus control comparator across all studies in the meta-analyses. In general, included studies were at low risk of bias, except for performance bias. Heterogeneity varied across the included meta-analyses ranging from low (I²=3%) for daily step count through to high (I²=67%) for sedentary behavior.

CONCLUSIONS

Utilizing a consumer-based wearable activity tracker as either the primary component of an intervention or as part of a broader physical activity intervention has the potential to increase physical activity participation. As the effects of physical activity interventions are often short term, the inclusion of a consumer-based wearable activity tracker may provide an effective tool to assist health professionals to provide ongoing monitoring and support.

Consumer-Based Wearable Activity Trackers Increase Physical Activity Participation: Systematic Review and Meta-Analysis

BACKGROUND

The range of benefits associated with regular physical activity participation is irrefutable. Despite the well-known benefits, physical inactivity remains one of the major contributing factors to ill-health throughout industrialized countries. Traditional lifestyle interventions such as group education or telephone counseling are effective at increasing physical activity participation; however, physical activity levels tend to decline over time. Consumer-based wearable activity trackers that allow users to objectively monitor activity levels are now widely available and may offer an alternative method for assisting individuals to remain physically active.

OBJECTIVE

This review aimed to determine the effects of interventions utilizing consumer-based wearable activity trackers on physical activity participation and sedentary behavior when compared with interventions that do not utilize activity tracker feedback.

METHODS

A systematic review was performed searching the following databases for studies that included the use of a consumer-based wearable activity tracker to improve physical activity participation: Cochrane Controlled Register of Trials, MEDLINE, PubMed, Scopus, Web of Science, Cumulative Index of Nursing and Allied Health Literature, SPORTDiscus, and Health Technology Assessments. Controlled trials of adults comparing the use of a consumer-based wearable activity tracker with other nonactivity tracker-based interventions were included. The main outcome measures were physical activity participation and sedentary behavior. All studies were assessed for risk of bias, and the Grades of Recommendation, Assessment, Development, and Evaluation system was used to rank the quality of evidence. The guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement were followed. A random-effects meta-analysis was completed on the included outcome measures to estimate the treatment effect of interventions that included an activity tracker compared with a control group.

RESULTS

There was a significant increase in daily step count (standardized mean difference [SMD] 0.24; 95% CI 0.16 to 0.33; P<.001), moderate and vigorous physical activity (SMD 0.27; 95% CI 0.15 to 0.39; P<.001), and energy expenditure (SMD 0.28; 95% CI 0.03 to 0.54; P=.03) and a nonsignificant decrease in sedentary behavior (SMD -0.20; 95% CI -0.43 to 0.03; P=.08) following the intervention versus control comparator across all studies in the meta-analyses. In general, included studies were at low risk of bias, except for performance bias. Heterogeneity varied across the included meta-analyses ranging from low (I2=3%) for daily step count through to high (I2=67%) for sedentary behavior.

CONCLUSIONS

Utilizing a consumer-based wearable activity tracker as either the primary component of an intervention or as part of a broader physical activity intervention has the potential to increase physical activity participation. As the effects of physical activity interventions are often short term, the inclusion of a consumer-based wearable activity tracker may provide an effective tool to assist health professionals to provide ongoing monitoring and support.

A Physical Therapist-Administered Physical Activity Intervention After Total Knee Replacement: Protocol for a Randomized Controlled Trial

BACKGROUND

The definitive treatment for knee osteoarthritis is a total knee replacement, which results in a clinically meaningful improvement in pain and physical function. However, evidence suggests that physical activity (PA) remains unchanged after total knee replacement (TKR).

OBJECTIVE

The objective of this study is to investigate the efficacy, fidelity, and safety of a physical therapist-administered PA intervention for people after TKR.

DESIGN

This study will be a randomized controlled trial.

SETTING

The setting is an outpatient physical therapy clinic.

PARTICIPANTS

The participants are 125 individuals who are over the age of 45 and are seeking outpatient physical therapy following a unilateral TKR.

INTERVENTION

In addition to standardized physical therapy after TKR, the intervention group will receive, during physical therapy, a weekly PA intervention that includes a wearable activity tracking device, individualized step goals, and face-to-face feedback provided by a physical therapist.

CONTROL

The control group will receive standardized physical therapy alone after TKR.

MEASUREMENTS

The efficacy of the intervention will be measured as minutes per week spent in moderate to vigorous PA at enrollment, at discharge, and at 6 months and 12 months after discharge from physical therapy. The fidelity and safety of the intervention will be assessed throughout the study.

LIMITATIONS

Participants will not be masked, PA data will be collected after randomization, and the trial will be conducted at a single site.

CONCLUSIONS

The goal of this randomized controlled trial is to increase PA after TKR. A protocol for investigating the efficacy, fidelity, and safety of a physical therapist-administered PA intervention for people after TKR is presented. The findings will be used to support a large multisite clinical trial to test the effectiveness, implementation, and cost of this intervention.

Long-Term Health and Economic Value of Improved Mobility among Older Adults in the United States

BACKGROUND

Mobility impairments have substantial physical and mental health consequences, resulting in diminished quality of life. Most studies on the health economic consequences of mobility limitations focus on short-term implications.

OBJECTIVES

To examine the long-term value of improving mobility in older adults.

METHODS

Our six-step approach used clinical trial data to calibrate mobility improvements and estimate health economic outcomes using a microsimulation model. First, we measured improvement in steps per day calibrated with clinical trial data examining hylan G-F 20 viscosupplementation treatment. Second, we created a cohort of patients 51 years and older with osteoarthritis. In the third step, we estimated their baseline quality of life. Fourth, we translated steps-per-day improvements to changes in quality of life using estimates from the literature. Fifth, we calibrated quality of life in this cohort to match those in the trial. Last, we incorporated these data and parameters into The Health Economic Medical Innovation Simulation model to estimate how mobility improvements affect functional status limitations, medical expenditures, nursing home utilization, employment, and earnings between 2012 and 2030.

RESULTS

In our sample of 12.6 million patients, 66.7% were female and 70% had a body mass index of more than 25 kg/m2. Our model predicted that a 554-step-per-day increase in mobility would reduce functional status limitations by 5.9%, total medical expenditures by 0.9%, and nursing home utilization by 2.8%, and increase employment by 2.9%, earnings by 10.3%, and monetized quality of life by 3.2% over this 18-year period.

CONCLUSIONS

Interventions that improve mobility are likely to reduce long-run medical expenditures and nursing home utilization and increase employment.

Evaluating the Impact of Physical Activity Apps and Wearables: Interdisciplinary Review

Background

Although many smartphone apps and wearables have been designed to improve physical activity, their rapidly evolving nature and complexity present challenges for evaluating their impact. Traditional methodologies, such as randomized controlled trials (RCTs), can be slow. To keep pace with rapid technological development, evaluations of mobile health technologies must be efficient. Rapid alternative research designs have been proposed, and efficient in-app data collection methods, including in-device sensors and device-generated logs, are available. Along with effectiveness, it is important to measure engagement (ie, users’ interaction and usage behavior) and acceptability (ie, users’ subjective perceptions and experiences) to help explain how and why apps and wearables work.

Objectives

This study aimed to (1) explore the extent to which evaluations of physical activity apps and wearables: employ rapid research designs; assess engagement, acceptability, as well as effectiveness; use efficient data collection methods; and (2) describe which dimensions of engagement and acceptability are assessed.

Method

An interdisciplinary scoping review using 8 databases from health and computing sciences. Included studies measured physical activity, and evaluated physical activity apps or wearables that provided sensor-based feedback. Results were analyzed using descriptive numerical summaries, chi-square testing, and qualitative thematic analysis.

Results

A total of 1829 abstracts were screened, and 858 articles read in full. Of 111 included studies, 61 (55.0%) were published between 2015 and 2017. Most (55.0%, 61/111) were RCTs, and only 2 studies (1.8%) used rapid research designs: 1 single-case design and 1 multiphase optimization strategy. Other research designs included 23 (22.5%) repeated measures designs, 11 (9.9%) nonrandomized group designs, 10 (9.0%) case studies, and 4 (3.6%) observational studies. Less than one-third of the studies (32.0%, 35/111) investigated effectiveness, engagement, and acceptability together. To measure physical activity, most studies (90.1%, 101/111) employed sensors (either in-device [67.6%, 75/111] or external [23.4%, 26/111]). RCTs were more likely to employ external sensors (accelerometers: P=.005). Studies that assessed engagement (52.3%, 58/111) mostly used device-generated logs (91%, 53/58) to measure the frequency, depth, and length of engagement. Studies that assessed acceptability (57.7%, 64/111) most often used questionnaires (64%, 42/64) and/or qualitative methods (53%, 34/64) to explore appreciation, perceived effectiveness and usefulness, satisfaction, intention to continue use, and social acceptability. Some studies (14.4%, 16/111) assessed dimensions more closely related to usability (ie, burden of sensor wear and use, interface complexity, and perceived technical performance).

Conclusions

The rapid increase of research into the impact of physical activity apps and wearables means that evaluation guidelines are urgently needed to promote efficiency through the use of rapid research designs, in-device sensors and user-logs to assess effectiveness, engagement, and acceptability. Screening articles was time-consuming because reporting across health and computing sciences lacked standardization. Reporting guidelines are therefore needed to facilitate the synthesis of evidence across disciplines.

Usage of an Exercise App in the Care for People With Osteoarthritis: User-Driven Exploratory Study

Background

Exercise has proven to reduce pain and increase quality of life among people living with osteoarthritis (OA). However, one major challenge is adherence to exercise once supervision ends.

Objective

This study aimed to identify mental and physical barriers and motivational and social aspects of training at home, and to test or further develop an exercise app.

Methods

The study was inspired from participatory design, engaging users in the research process. Data were collected through focus groups and workshops, and analyzed by systematic text condensation.

Results

Three main themes were found: competition as motivation, training together, and barriers. The results revealed that the participants wanted to do their training and had knowledge on exercise and pain but found it hard to motivate themselves. They missed the observation, comments, and encouragement by the supervising physiotherapist as well as their peers. Ways to optimize the training app were identified during the workshops as participants shared their experience.

Conclusions

This study concludes that the long-term continuation of exercising for patients with OA could be improved with the use of a technology tailored to users’ needs, including motivational and other behavioral factors.