Willingness to pay for health apps, its sociodemographic correlates, and reasons for being unwilling to pay.

Background: Knowledge about whether, how much, and why individuals are willing to pay for health apps is limited. Objectives: This study aimed to examine (1) the proportion of individuals willing to pay for health apps, (2) their willingness to pay (WTP; i.e. the maximum price the individual is willing to pay) for health apps, (3) the sociodemographic correlates determining whether individuals are willing to pay for these apps, (4) the sociodemographic correlates of their WTP, and (5) reasons for being unwilling to pay. Methods: Six hundred adults were invited to participate in a questionnaire survey examining their sociodemographic characteristics, WTP for health apps, and reasons for being unwilling to pay. Sociodemographic characteristics and WTP for health apps were analyzed using descriptive statistics. Logistic regression was applied to examine the sociodemographic variables correlated with whether individuals were willing to pay for health apps. Among those who were willing to pay, log-linear regression was conducted to examine the sociodemographic correlates of their WTP. The reasons for unwillingness to pay were descriptively analyzed. Results: A total of 577 individuals completed the questionnaire. Of them, 58.9% were willing to pay for health apps. Their median WTP was HK$50 (HK$1 ≈ US$0.13). Participants with a bachelor's degree or higher and those who had previously installed health apps were more inclined to pay for health apps. WTP was positively associated with the maximum price previously paid for a health app. The most frequently cited reasons for being unwilling to pay were the belief that the government should provide free health apps, distrust in health apps, and a lack of awareness of health apps and their benefits. Conclusions: This study provides insights that can inform strategies to enhance the marketability, affordability, and accessibility of health apps.

The mental workload of ICU nurses performing human-machine tasks and associated factors: A cross-sectional questionnaire survey.

AIMS: To assess the level of mental workload (MWL) of intensive care unit (ICU) nurses in performing different human-machine tasks and examine the predictors of the MWL. DESIGN: A cross-sectional questionnaire study. METHODS: Between January and February 2021, data were collected from ICU nurses (n = 427) at nine tertiary hospitals selected from five (east, west, south, north, central) regions in China through an electronic questionnaire, including sociodemographic questions, the National Aeronautics and Space Administration Task Load Index, General Self-Efficacy Scale, Difficulty-assessing Index System of Nursing Operation Technique, and System Usability Scale. Descriptive statistics, t-tests, one-way ANOVA and multiple linear regression models were used. RESULTS: ICU nurses experienced a medium level of MWL (score 52.04 on a scale of 0-100) while performing human-machine tasks. ICU nurses' MWL was notably higher in conducting first aid and life support tasks (using defibrillators or ventilators). Predictors of MWL were task difficulty, system usability, professional title, age, self-efficacy, ICU category, and willingness to study emerging technology actively. Task difficulty and system usability were the strongest predictors of nearly all typical tasks. CONCLUSION: ICU nurses experience a medium MWL while performing human-machine tasks, but higher mental, temporal, and effort are perceived compared to physical demands. The MWL varied significantly across different human-machine tasks, among which are significantly higher: first aid and life support and information-based human-machine tasks. Task difficulty and system availability are decisive predictors of MWL. IMPACT: This is the first study to investigate the level of MWL of ICU nurses performing different representative human-machine tasks and to explore its predictors, which provides a reference for future research. These findings suggest that healthcare organizations should pay attention to the MWL of ICU nurses and develop customized management strategies based on task characteristics to maintain a moderate level of MWL, thus enabling ICU nurses to perform human-machine tasks better. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

From Skin Movement to Wearable Robotics: The Case of Robotic Gloves.

Previous research on wearable robotics focused on developing actuation mechanisms while overlooking influences of skin movement. During finger flexion, skins on the opisthenar and finger back are stretched. Impeding such skin movement will obstruct normal finger motions. In this research, a statistical study on skin movement is proposed and conducted to quantify skin movement on human hands. Results of 30 subjects (15 men and 15 women) reveal that skin at the finger back extends by an average of 29.3 ± 7.2% in fist clenching. Based on this study, design guidelines for robotic gloves are proposed, and nominal strain values at different hand regions are tabulated for references in robotic glove design. To explore the influence of skin movement on wearable robotics, an elastomer-constrained flat tube actuator is proposed based on which two prototype robotic gloves are developed: one with an ergonomic strap interface that has small constraint to skin motion, and the other based on the commonly used fabric glove that is supposed to have large constraint to skin motion. With the same power input to the robotic gloves, the strap-based design achieves a finger motion range of 2.5 times and a gripping force of 4.3 times that of the conventional fabric glove.

Automated machine learning-based prediction of the progression of knee pain, functional decline, and incidence of knee osteoarthritis in individuals at high risk of knee osteoarthritis: Data from the osteoarthritis initiative study.

Objective: This study aimed to examine the performance of machine learning models in predicting the progression of knee pain, functional decline, and incidence of knee osteoarthritis (OA) in high-risk individuals, with automated machine learning (AutoML) being used to automate the prediction process. Design: There were four stages in the process of our AutoML-integrated prediction. Stage 1-Data preparation: The data of 3200 eligible individuals in the Osteoarthritis Initiative (OAI) study who were considered at high risk of knee OA at the baseline visit were extracted and used. Specifically, 1094 variables from the OAI study were used to predict the changes in knee pain, physical function, and incidence of knee OA (i.e. the first occurrence of frequent knee symptoms and definite tibial osteophytes (Kellgren and Lawrence grade ≥2)) over a 9-year period. Stage 2-Model training: The AutoML approach was used to automatically train nine widely used machine learning (ML) models. Stage 3-Model testing: The AutoML approach was used to automatically test the performance of the ML models. Stage 4-Selection of important input variables: The AutoML approach automated the process of computing the importance scores of all input variables and identifying the most important ones, using the technique of permutation feature importance. Results: Using the AutoML approach, the weighted ensemble model and the CatBoost model showed the best performance among all nine ML models. For the prediction of each outcome in each year, the five most important input variables were identified, most of which were obtained from self-reported questionnaire surveys and radiographic imaging reports. Conclusion: The AutoML approach has shown potential in automating the process of using ML models to predict long-term changes in knee OA-related outcomes. Its use could support the deployment of ML solutions, facilitating the provision of personalized interventions to prevent the deterioration of knee health and incident knee OA.

Consumers' Preferences for Purchasing mHealth Apps: Discrete Choice Experiment.

Background: There is growing interest in mobile health apps; however, not all of them have been successful. The most common issue has been users' nonadoption or abandonment of health apps because the app designs do not meet their preferences. Therefore, to facilitate design-preference fit, understanding consumers' preferences for health apps is necessary, which can be accomplished by using a discrete choice experiment. Objective: This study aims to examine consumer preferences for health apps and how these preferences differ across individuals with different sociodemographic characteristics and health app usage and purchase experiences. Methods: A cross-sectional discrete choice experiment questionnaire survey was conducted with 593 adults living in Hong Kong. A total of 7 health app attributes that might affect consumers' preferences for health apps were examined, including usefulness, ease of use, security and privacy, health care professionals' attitudes, smartphone storage consumption, mobile data consumption, and cost. Mixed-effect logit regressions were used to examine how these attributes affected consumer preferences for health apps. Fixed effects (coefficient ß) of the attributes and random effects of individual differences were modeled. Subgroup analyses of consumer preferences by sex, age, household income, education level, and health app usage and purchase experiences were conducted. Results: Cost was the attribute that had the greatest effect on consumers' choice of health apps (compared to HK $10 [US $1.27]-HK $50 [US $6.37]: ß=-1.064; P<.001; HK $100 [US $12.75]: ß=-2.053; P<.001), followed by security and privacy (compared to no security insurance-some security policies: ß=.782; P<.001; complete security system: ß=1.164; P<.001) and usefulness (compared to slightly useful-moderately useful: ß=.234; P<.001; very useful: ß=.979; P=.007), mobile data consumption (compared to data-consuming-a bit data-consuming: ß=.647; P<.001; data-saving: ß=.815; P<.001), smartphone storage consumption (compared to >100 MB-around 38 MB: ß=.334; P<.001; <10 MB: ß=.511; P<.001), and attitudes of health care professionals (compared to neutral-moderately supportive: ß=.301; P<.001; very supportive: ß=.324; P<.001). In terms of ease of use, consumers preferred health apps that were moderately easy to use (compared to not easy to use-moderately easy to use: ß=.761; P<.001; very easy to use: ß=.690; P<.001). Our results also showed that consumers with different sociodemographic characteristics and different usage and purchase experiences with health apps differed in their preferences for health apps. Conclusions: It is recommended that future health apps keep their mobile data and phone storage consumption low, include a complete security system to protect personal health information, provide useful content and features, adopt user-friendly interfaces, and involve health care professionals. In addition, health app developers should identify the characteristics of their intended users and design and develop health apps to fit the preferences of the intended users.

Effectiveness, safety and patients' perceptions of an immersive virtual reality-based exercise system for poststroke upper limb motor rehabilitation: A proof-of-concept and feasibility randomized controlled trial.

Objective: This study aimed to examine the effectiveness, safety and patients' perceptions of an immersive virtual reality (VR)-based exercise system for poststroke upper limb rehabilitation. Methods: A proof-of-concept, 2-week randomized controlled trial was conducted. Fifty stroke patients were randomly assigned to either use the immersive VR-based exercise system to perform upper limb exercises for 2 weeks (intervention) or play commercial games (control). Effectiveness, safety and patients' perceptions of the exercise system were assessed at baseline and at 1- and 2-week follow-ups. Results: Intention-to-treat analysis revealed that after 2 weeks, statistically significant improvements in shoulder flexion active range of motion (AROM), shoulder abduction AROM, perceived upper limb motor function and quality of life (QoL) were observed in one or both groups, but not between the groups. Per-protocol analysis showed that after 2 weeks: (i) statistically significant improvement in shoulder abduction AROM was obtained in the intervention group, and the difference in the mean changes between the groups was statistically significant; (ii) statistically significant improvements in coordination/speed (Fugl-Meyer Assessment for Upper Extremity), shoulder flexion AROM, perceived upper limb motor function and QoL were obtained in one or both groups, but not between the groups. Conclusions: The immersive VR-based exercise system is a potentially effective, safe and acceptable approach for supporting poststroke motor rehabilitation. These findings can serve as a basis for larger-scale studies on the application of VR for poststroke exercises.

Perceptions of a machine learning-based lower-limb exercise training system among older adults with knee pain.

Objective: To facilitate the older adults with knee pain to perform exercises and improve knee health, we proposed the design of a machine learning-based system for lower-limb exercise training that features three main components: video demonstration of exercises, real-time movement feedback, and tracking of exercise progress. At this early stage of design, we aimed to examine the perceptions of a paper-based prototype among older adults with knee pain and investigate the factors that may influence their perceptions of the system. Methods: A cross-sectional survey of the participants' (N = 94) perceptions of the system was conducted using a questionnaire, which assessed their perceived effects of the system, perceived ease of use of the system, attitude toward the system, and intention to use the system. Ordinal logistic regression was conducted to examine whether the participants' perceptions of the system were influenced by their demographic and clinical characteristics, physical activity level, and exercise experience. Results: The participants' responses to the perception statements exhibited consensus agreement (≥ 75%). Age, gender, duration of knee pain, knee pain intensity, experience with exercise therapy, and experience with technology-supported exercise programs were significantly associated with the participants' perceptions of the system. Conclusions: Our results demonstrate that the system appears promising for use by older adults to manage their knee pain. Therefore, it is needed to develop a computer-based system and further investigate its usability, acceptance, and clinical effectiveness.

A discrete choice experiment to examine the factors influencing consumers' willingness to purchase health apps.

Background: The benefits of health apps can only be realized when consumers purchase them for use. Thus, it is important to understand what factors influence consumers' willingness to purchase health apps. Therefore, this study aimed to examine the influence of health app attributes and sociodemographic characteristics on consumers' willingness to purchase health apps, and how the value of the health app attributes varies for individuals with different sociodemographic characteristics. Methods: A questionnaire-based discrete choice experiment (DCE) was conducted with a random sample of 561 adults. A standard logit regression was applied to assess the influence of health app attributes and sociodemographic characteristics on consumers' willingness to purchase health apps, and marginal willingness to pay (MWTP) was calculated for each factor using regression coefficients. Interaction effects were also examined to determine how the value of health app attributes varies by sociodemographic characteristics. Results: Usefulness, ease of use, security and privacy, and attitudes of healthcare professionals toward consumers' use of health apps were the attributes of health apps that positively influenced consumers' willingness to purchase them. Conversely, smartphone storage consumption, mobile Internet data consumption, and app price negatively influenced consumers' willingness to purchase the apps. For sociodemographic characteristics, being male, having a household size greater than three, having a monthly household income of HK$30,000 or more, having a lower education level (below diploma), having previously used health apps, and having previously purchased health apps were associated with a higher willingness to purchase health apps. Conclusions: Health app attributes that influenced consumers' willingness to purchase the apps and populations that were less willing to purchase health apps were identified. Efforts should be made to improve health app attributes and enhance the promotion of health apps among these underserved populations.

Consumers' Willingness to Pay for eHealth and Its Influencing Factors: Systematic Review and Meta-analysis.

BACKGROUND: Despite the great potential of eHealth, substantial costs are involved in its implementation, and it is essential to know whether these costs can be justified by its benefits. Such needs have led to an increased interest in measuring the benefits of eHealth, especially using the willingness to pay (WTP) metric as an accurate proxy for consumers' perceived benefits of eHealth. This offered us an opportunity to systematically review and synthesize evidence from the literature to better understand WTP for eHealth and its influencing factors. OBJECTIVE: This study aimed to provide a systematic review of WTP for eHealth and its influencing factors. METHODS: This study was performed and reported as per the Cochrane Collaboration and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. PubMed, CINAHL Plus, Cochrane Library, EconLit, and PsycINFO databases were searched from their inception to April 19, 2022. We conducted random-effects meta-analyses to calculate WTP values for eHealth (at 2021 US dollar rates) and meta-regression analyses to examine the factors affecting WTP. RESULTS: A total of 30 articles representing 35 studies were included in the review. We found that WTP for eHealth varied across studies; when expressed as a 1-time payment, it ranged from US $0.88 to US $191.84, and when expressed as a monthly payment, it ranged from US $5.25 to US $45.64. Meta-regression analyses showed that WTP for eHealth was negatively associated with the percentages of women (ß=-.76; P<.001) and positively associated with the percentages of college-educated respondents (ß=.63; P<.001) and a country's gross domestic product per capita (multiples of US $1000; ß=.03; P<.001). Compared with eHealth provided through websites, people reported a lower WTP for eHealth provided through asynchronous communication (ß=-1.43; P<.001) and a higher WTP for eHealth provided through medical devices (ß=.66; P<.001), health apps (ß=.25; P=.01), and synchronous communication (ß=.58; P<.001). As for the methods used to measure WTP, single-bounded dichotomous choice (ß=2.13; P<.001), double-bounded dichotomous choice (ß=2.20; P<.001), and payment scale (ß=1.11; P<.001) were shown to obtain higher WTP values than the open-ended format. Compared with ex ante evaluations, ex post evaluations were shown to obtain lower WTP values (ß=-.37; P<.001). CONCLUSIONS: WTP for eHealth varied significantly depending on the study population, modality used to provide eHealth, and methods used to measure it. WTP for eHealth was lower among certain population segments, suggesting that these segments may be at a disadvantage in terms of accessing and benefiting from eHealth. We also identified the modalities of eHealth that were highly valued by consumers and offered suggestions for the design of eHealth interventions. In addition, we found that different methods of measuring WTP led to significantly different WTP estimates, highlighting the need to undertake further methodological explorations of approaches to elicit WTP values.

Feasibility and acceptability of electronic EQ-5D-5L for routine measurement of HRQOL in patients with chronic musculoskeletal problems in Hong Kong primary care.

BACKGROUND: Information on HRQOL can enhance patient diagnosis and management but it is rarely available in routine clinical practice. This mixed-method study evaluated the feasibility and acceptability of the electronic EQ-5D-5L measurement of HRQOL in patients with chronic musculoskeletal problems in primary care. METHODS: In three primary care clinics, 665 patients with musculoskeletal problems completed the electronic EQ-5D-5L and Visual Analogue Scale (e-EQ-5D-5L/VAS), and a questionnaire on socio-demographics, perceived ease of use (PEOU), and perceived usefulness (PU) at baseline and two follow-ups. Patient completion and response rates, and time to complete the e-EQ-5D-5L/VAS were measured. During the same consultations, 49 doctors reviewed the e-EQ-5D-5L/VAS reports and completed a clinician questionnaire on PEOU, PU, and time spent to address each report. Individual interviews along with focus group discussions were conducted on patients, doctors, and research assistants for further exploration. RESULTS: Mean completion time reduced from baseline to first and second follow-up (120.66, 83.99, and 105.22 s, respectively). Completion and response rates were high at each follow-up visit (> 99.8% and > 91.11%, respectively). Doctors needed less than 2 min to read the report but felt the time required to address the report was a significant barrier. Some patients had difficulties using e-platforms, in understanding or answering questions; but, PEOU improved with time (p < 0.001). Most patients found the e-platforms useful (> 85.3%). Clinicians agreed a great majority of the reports were easy to use (76.0-85.1%) and useful (69.2-72.0%), particularly aiding with a holistic view of the patient's musculoskeletal problem. CONCLUSION: The e-EQ-5D-5L/VAS is a feasible and acceptable measurement of HRQOL of patients with chronic musculoskeletal problems in routine primary care in Hong Kong which can assist real-time management decisions. TRIAL REGISTRATION: NCT03609762.

Effectiveness of Using Virtual Reality-Supported Exercise Therapy for Upper Extremity Motor Rehabilitation in Patients With Stroke: Systematic Review and Meta-analysis of Randomized Controlled Trials.

BACKGROUND: In recent years, efforts have been made to implement virtual reality (VR) to support the delivery of poststroke upper extremity motor rehabilitation exercises. Therefore, it is important to review and analyze the existing research evidence of its effectiveness. OBJECTIVE: Through a systematic review and meta-analysis of randomized controlled trials, this study examined the effectiveness of using VR-supported exercise therapy for upper extremity motor rehabilitation in patients with stroke. METHODS: This study followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The CINAHL Plus, MEDLINE, Web of Science, Embase, and Cochrane Library databases were searched on December 31, 2021. Changes in outcomes related to impairments in upper extremity functions and structures, activity limitations, and participation restrictions in life situations from baseline to after intervention, after intervention to follow-up assessment, and baseline to follow-up assessment were examined. Standardized mean differences (SMDs) were calculated using a random-effects model. Subgroup analyses were performed to determine whether the differences in treatment outcomes depended on age, stroke recovery stage, VR program type, therapy delivery format, similarities in intervention duration between study groups, intervention duration in VR groups, and trial length. RESULTS: A total of 42 publications representing 43 trials (aggregated sample size=1893) were analyzed. Compared with the control groups that used either conventional therapy or no therapy, the intervention groups that used VR to support exercise therapy showed significant improvements in upper extremity motor function (Fugl-Meyer Assessment-Upper Extremity; SMD 0.45, 95% CI 0.21-0.68; P<.001), range of motion (goniometer; SMD 1.01, 95% CI 0.50-1.52; P<.001), muscle strength (Manual Muscle Testing; SMD 0.79, 95% CI 0.28-1.30; P=.002), and independence in day-to-day activities (Functional Independence Measure; SMD 0.23, 95% CI 0.06-0.40; P=.01, and modified Rankin Scale; SMD 0.57, 95% CI 0.01-1.12; P=.046). Significant subgroup differences were observed in hand dexterity (Box and Block Test), spasticity (Ashworth Scale or modified Ashworth Scale), arm and hand motor ability (Wolf Motor Function Test and Manual Function Test), hand motor ability (Jebsen Hand Function Test), and quality of life (Stroke Impact Scale). There was no evidence that the benefits of VR-supported exercise therapy were maintained after the intervention ended. CONCLUSIONS: VR-supported upper extremity exercise therapy can be effective in improving motor rehabilitation results. Our review showed that of the 12 rehabilitation outcomes examined during the course of VR-based therapy, significant improvements were detected in 2 (upper extremity motor function and range of motion), and both significant and nonsignificant improvements were observed in another 2 (muscle strength and independence in day-to-day activities), depending on the measurement tools or methods used. TRIAL REGISTRATION: PROSPERO CRD42021256826; https://tinyurl.com/2uarftbh.

A longitudinal examination of tablet self-management technology acceptance by patients with chronic diseases: Integrating perceived hand function, perceived visual function, and perceived home space adequacy with the TAM and TPB.

BACKGROUND: Health information technologies (HITs) are increasingly being used to support the self-management of chronic diseases. However, patients' initial or continued acceptance of such technologies is not always achieved. OBJECTIVE: The aim of this study was to develop a theory-driven HIT acceptance model to examine factors affecting acceptance of HIT (measured by behavioral intention; BI) for disease self-management among patients with chronic diseases, in which we also focused on three additional, previously unexplored factors related to perceived hand function (PHF), perceived visual function (PVF), and perceived space adequacy (PSA) and a longitudinal scrutinization of changes in the effects of these factors on acceptance over time. METHODS: The theoretical basis of our acceptance model was drawn from the technology acceptance model and the theory of planned behavior. The model was further extended by including patients' PHF, PVF (related to patients with chronic diseases who are mostly elderly), and PSA (related to the patients' home environment). The model was tested in the context of type 2 diabetes and hypertension self-management via a touchscreen tablet-based system over a 24-week period. A questionnaire was administered at four time points (baseline and 8, 16, and 24 weeks after implementation) to collect data from 151 patients with coexisting type 2 diabetes and hypertension. We tested the model at each time point using partial least squares structural equation modeling. RESULTS: Perceived usefulness of the self-management system influenced BI directly at 8 and 24 weeks and indirectly at 8, 16, and 24 weeks. Perceived ease of use indirectly affected BI at 8, 16, and 24 weeks. Attitude directly affected BI at 8, 16, and 24 weeks. Perceived behavioral control directly influenced BI at baseline and 8 and 16 weeks. Subjective norms indirectly influenced BI at 8, 16, and 24 weeks. PHF and PVF indirectly influenced BI over the entire study period. PSA influenced BI directly at 16 weeks and indirectly at 8, 16, and 24 weeks. CONCLUSION: The effects of the proposed factors in our model on patient-focused HIT acceptance changed over a longer time period, emphasizing the importance of further investigation of the longitudinal mechanisms influencing technology acceptance behavior. It is recommended that healthcare practitioners consider such changes when implementing comparable technologies. Moreover, beyond technology attributes, the characteristics, needs, and limitations of older adults and elderly patient users and their home environments should also be considered in the design and implementation of patient-focused HIT systems for chronic disease self-management at home.

A pilot study on the validity and psychometric properties of the electronic EQ-5D-5L in routine clinical practice.

BACKGROUND: Electronic measurement of health-related quality of life (HRQOL) may facilitate timely and regular assessments in routine clinical practice. This study evaluated the validity and psychometric properties of an electronic version of the EQ-5D-5L (e-EQ-5D-5L) in Chinese patients with chronic knee and/or back problems. METHODS: 151 Chinese subjects completed an electronic version of the Chinese (Hong Kong) EQ-5D-5L when they attended a primary care or orthopedics specialist out-patient clinic in Hong Kong. They also completed the Chinese Western Ontario and McMaster University Osteoarthritis Index (WOMAC), a Pain Rating Scale, and a structured questionnaire on socio-demographics, co-morbidities and health service utilization. 32 subjects repeated the e-EQ-5D-5L two weeks after the baseline. 102 subjects completed e-EQ-5D-5L and 99 completed the Global Rating on Change Scale at three-month clinic follow up. Construct validity was assessed by the association of EQ-5D-5L scores with external criterion of WOMAC scores. We tested mean differences of WOMAC scores between adjacent response levels of the EQ-5D-5L dimensions by one-way ANOVA, test-retest reliability by intra-class correlation, sensitivity by known group comparisons and responsiveness by changes in EQ-5D-5L scores over 3 months. RESULTS: There was an association between EQ-5D-5L and WOMAC scores. Mean WOMAC scores increased with the increase in adjacent response levels of EQ-5D-5L dimensions. Test-retest intraclass correlation coefficient (ICC) of EQ-5D-5L utility and EQ-VAS scores were 0.76 and 0.83, respectively, indicating good reliability. There were significant differences in the proportions reporting limitations in the EQ-5D-5L dimensions, the utility and VAS scores between the mild and severe pain groups (utility = 0.28, p = 0.001; VAS = 11.46, p < 0.001), and between primary care and specialist out-patient clinic patients (utility = 0.15, p = 0.001; VAS = 10.21, p < 0.001), supporting sensitivity. Among those reporting 'better' global health at three-months, their EQ-5D-5L utility and EQ-VAS scores were significantly increased from baseline (utility = 0.18, p < 0.001; VAS = 10.75, p = 0.005). CONCLUSIONS: The electronic version of the EQ-5D-5L is valid, reliable, sensitive and responsive in the measurement of HRQOL in Chinese patients with chronic knee or back pain in routine clinical practice.

Effects of interventions to reduce the negative consequences of interruptions on task performance: A systematic review, meta-analysis, and narrative synthesis of laboratory studies.

A systematic review was conducted to examine the effects of interventions aimed at reducing the negative consequences of interruptions on task performance. Medline, PsycINFO, PsycARTICLES, and the ABI/INFORM Collection were searched for relevant publications. Thirty-three laboratory-based experiments, containing 49 interventions, were reviewed. Seven types of interventions were identified. Overall, the use of interventions significantly increased primary task accuracy (standardized mean difference (SMD) = 1.03, P = 0.001) and reduced resumption lag (SMD = -0.51, P < 0.001), whereas no significant difference was observed for interrupting task accuracy. Subgroup analyses indicated that intervention effects varied by (i) the type of intervention and (ii) the type of primary task (procedural, decision-making, or problem-solving tasks). The narrative synthesis provided additional evidence regarding interruption lag and time spent on a primary task. In sum, this review identified the types of interventions that were particularly effective and provided implications for application and further investigation.

Effects of technology-supported exercise programs on the knee pain, physical function, and quality of life of individuals with knee osteoarthritis and/or chronic knee pain: A systematic review and meta-analysis of randomized controlled trials.

OBJECTIVE: The study sought to examine the effects of technology-supported exercise programs on the knee pain, physical function, and quality of life of individuals with knee osteoarthritis and/or chronic knee pain by a systematic review and meta-analysis of randomized controlled trials. MATERIALS AND METHODS: We searched MEDLINE, EMBASE, CINAHL Plus, and the Cochrane Library from database inception to August 2020. A meta-analysis and subgroup analyses, stratified by technology type and program feature, were conducted. RESULTS: Twelve randomized controlled trials were reviewed, all of which implemented the programs for 4 weeks to 6 months. Telephone, Web, mobile app, computer, and virtual reality were used to deliver the programs. The meta-analysis showed that these programs were associated with significant improvements in knee pain (standardized mean difference [SMD] = -0.29; 95% confidence interval [CI], -0.48 to -0.10; P = .003) and quality of life (SMD = 0.25; 95% CI, 0.04 to 0.46; P = .02) but not with significant improvement in physical function (SMD = 0.22; 95% CI, 0 to 0.43; P = .053). Subgroup analyses showed that some technology types and program features were suggestive of potential benefits. CONCLUSIONS: Using technology to deliver the exercise programs appears to offer benefits. The technology types and program features that were associated with health values have been identified, based on which suggestions are discussed for the further research and development of such programs.

Development and pilot evaluation of a mobile app on parent-child exercises to improve physical activity and psychosocial outcomes of Hong Kong Chinese children.

BACKGROUND: Parent-child exercises involve children and parents to do workout together and have positive effects on physical and mental health. We developed a mobile app on parent-child exercises called Family Move, which combines coaching videos with game features such as points and level system to enhance the health and wellbeing of both children and parents through parent-child exercises. This pilot pre-post study investigated whether the Family Move app-based intervention had a positive effect on children's health-related quality of life (HRQOL), psychosocial wellbeing, and physical activity (PA) level. METHODS: We recruited 67 parent-child pairs. During the 8-week intervention, these pairs were invited to perform parent-child exercises using the Family Move app. Points were automatically added to the user account after viewing a coaching video. In-game ranking was available to enhance user engagement. Parent proxy-report questionnaires on children's HRQOL, psychosocial wellbeing, and PA were administered at baseline and 1- and 6-month follow-up. Paired samples t-tests were conducted to evaluate post-intervention changes in child outcomes (HRQOL, psychosocial wellbeing, and PA). Multiple linear regressions were used to examine these changes as a function of in-game ranking. RESULTS: 52 (78%) viewed at least one coaching video in the Family Move app. Children's PA level significantly increased at 1-month (d = 0.32, p = 0.030) and 6-month (d = 0.30, p = 0.042) follow-up, whereas their psychosocial problems declined at 6-month follow-up (d = 0.35, p = 0.005). Higher in-game ranking was significantly associated with fewer psychosocial problems at 1-month follow-up (ß = - 0.15, p = 0.030). CONCLUSIONS: Our findings suggest that the Family Move app could be a possible intervention to increase children's PA level and psychosocial wellbeing through parent-child exercise. TRIAL REGISTRATION: ClinicalTrials.gov number, NCT03279354 , registered September 11, 2017 (Prospectively registered).

Correction: Effectiveness of Mobile App-Assisted Self-Care Interventions for Improving Patient Outcomes in Type 2 Diabetes and/or Hypertension: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

[This corrects the article DOI: 10.2196/15779.].

An examination of the socio-demographic correlates of patient adherence to self-management behaviors and the mediating roles of health attitudes and self-efficacy among patients with coexisting type 2 diabetes and hypertension.

BACKGROUND: Patients with coexisting type 2 diabetes and hypertension generally exhibit poor adherence to self-management, which adversely affects their disease control. Therefore, identification of the factors related to patient adherence is warranted. In this study, we aimed to examine (i) the socio-demographic correlates of patient adherence to a set of self-management behaviors relevant to type 2 diabetes and hypertension, namely, medication therapy, diet therapy, exercise, tobacco and alcohol avoidance, stress reduction, and self-monitoring/self-care, and (ii) whether health attitudes and self-efficacy in performing self-management mediated the associations between socio-demographic characteristics and adherence. METHODS: We performed a secondary analysis of data collected in a randomized controlled trial. The sample comprised 148 patients with coexisting type 2 diabetes mellitus and hypertension. Data were collected by a questionnaire and analyzed using logistic regression. RESULTS: Female patients were found to be less likely to exercise regularly (odds ratio [OR] = 0.49, P = 0.03) and more likely to avoid tobacco and alcohol (OR = 9.87, P < 0.001) than male patients. Older patients were found to be more likely to adhere to diet therapy (OR = 2.21, P = 0.01) and self-monitoring/self-care (OR = 2.17, P = 0.02). Patients living with family or others (e.g., caregivers) were found to be more likely to exercise regularly (OR = 3.44, P = 0.02) and less likely to avoid tobacco and alcohol (OR = 0.10, P = 0.04) than those living alone. Patients with better perceived health status were found to be more likely to adhere to medication therapy (OR = 2.02, P = 0.03). Patients with longer diabetes duration (OR = 2.33, P = 0.01) were found to be more likely to adhere to self-monitoring/self-care. Self-efficacy was found to mediate the association between older age and better adherence to diet therapy, while no significant mediating effects were found for health attitudes. CONCLUSIONS: Adherence to self-management was found to be associated with socio-demographic characteristics (sex, age, living status, perceived health status, and diabetes duration). Self-efficacy was an important mediator in some of these associations, suggesting that patient adherence may be improved by increasing patients' self-management efficacy, such as by patient empowerment, collaborative care, or enhanced patient-physician interactions.

Effectiveness of Mobile App-Assisted Self-Care Interventions for Improving Patient Outcomes in Type 2 Diabetes and/or Hypertension: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: Mobile app-assisted self-care interventions are emerging promising tools to support self-care of patients with chronic diseases such as type 2 diabetes and hypertension. The effectiveness of such interventions requires further exploration for more supporting evidence. OBJECTIVE: A systematic review and meta-analysis of randomized controlled trials (RCTs) were conducted to examine the effectiveness of mobile app-assisted self-care interventions developed for type 2 diabetes and/or hypertension in improving patient outcomes. METHODS: We followed the Cochrane Collaboration guidelines and searched MEDLINE, Cochrane Library, EMBASE, and CINAHL Plus for relevant studies published between January 2007 and January 2019. Primary outcomes included changes in hemoglobin A1c (HbA1c) levels, systolic blood pressure (SBP), and diastolic blood pressure (DBP). Changes in other clinical-, behavioral-, knowledge-, and psychosocial-related outcomes were included as secondary outcomes. Primary outcomes and objective secondary outcomes that were reported in at least two trials were meta-analyzed; otherwise, a narrative synthesis was used for data analysis. RESULTS: A total of 27 trials were identified and analyzed. For primary outcomes, the use of mobile app-assisted self-care interventions was associated with significant reductions in HbA1c levels (standardized mean difference [SMD] -0.44, 95% CI -0.59 to -0.29; P<.001), SBP (SMD -0.17, 95% CI -0.31 to -0.03, P=.02), and DBP (SMD -0.17, 95% CI -0.30 to -0.03, P=.02). Subgroup analyses for primary outcomes showed that several intervention features were supportive of self-management, including blood glucose, blood pressure, and medication monitoring, communication with health care providers, automated feedback, personalized goal setting, reminders, education materials, and data visualization. In addition, 8 objective secondary outcomes were meta-analyzed, which showed that the interventions had significant lowering effects on fasting blood glucose levels and waist circumference. A total of 42 secondary outcomes were narratively synthesized, and mixed results were found. CONCLUSIONS: Mobile app-assisted self-care interventions can be effective tools for managing blood glucose and blood pressure, likely because their use facilitates remote management of health issues and data, provision of personalized self-care recommendations, patient-care provider communication, and decision making. More studies are required to further determine which combinations of intervention features are most effective in improving the control of the diseases. Moreover, evidence regarding the effects of these interventions on the behavioral, knowledge, and psychosocial outcomes of patients is still scarce, which warrants further examination.

Improving Self-Care in Patients With Coexisting Type 2 Diabetes and Hypertension by Technological Surrogate Nursing: Randomized Controlled Trial.

BACKGROUND: Technological surrogate nursing (TSN) derives from the idea that nurse-caregiver substitutes can be created by technology to support chronic disease self-care. OBJECTIVE: This paper begins by arguing that TSN is a useful and viable approach to chronic disease self-care. The analysis then focuses on the empirical research question of testing and demonstrating the effectiveness and safety of prototype TSN supplied to patients with the typical complex chronic disease of coexisting type 2 diabetes and hypertension. At the policy level, it is shown that the data allow for a calibration of TSN technology augmentation, which can be readily applied to health care management. METHODS: A 24-week, parallel-group, randomized controlled trial (RCT) was designed and implemented among diabetic and hypertensive outpatients in two Hong Kong public hospitals. Participants were randomly assigned to an intervention group, supplied with a tablet-based TSN app prototype, or to a conventional self-managing control group. Primary indices-hemoglobin A1c, systolic blood pressure, and diastolic blood pressure-and secondary indices were measured at baseline and at 8, 12, 16, and 24 weeks after initiation, after which the data were applied to test TSN effectiveness and safety. RESULTS: A total of 299 participating patients were randomized to the intervention group (n=151) or the control group (n=148). Statistically significant outcomes that directly indicated TSN effectiveness in terms of hemoglobin 1c were found in both groups but not with regard to systolic and diastolic blood pressure. These findings also offered indirect empirical support for TSN safety. Statistically significant comparative changes in these primary indices were not observed between the groups but were suggestive of an operational calibration of TSN technology augmentation. Statistically significant changes in secondary indices were obtained in one or both groups, but not between the groups. CONCLUSIONS: The RCT's strong behavioral basis, as well as the importance of safety and effectiveness when complex chronic illness is proximately self-managed by layperson patients, prompted the formulation of the empirical joint hypothesis that TSN would improve patient self-care while satisfying the condition of patient self-safety. Statistical and decision analysis applied to the experimental outcomes offered support for this hypothesis. Policy relevance of the research is demonstrated by the derivation of a data-grounded operational calibration of TSN technology augmentation with ready application to health care management. TRIAL REGISTRATION: ClinicalTrials.gov NCT02799953; https://clinicaltrials.gov/ct2/show/NCT02799953.