User experience testing of the mobile pulmonary rehabilitation (m-PR™) app in people with chronic obstructive pulmonary disease.

Objective: Mobile health (mHealth) technologies are emerging to support the delivery of pulmonary rehabilitation (PR). This study aimed to explore the ease of use, satisfaction and acceptability of an Australian mobile pulmonary rehabilitation app (m-PR™) in people with chronic obstructive pulmonary disease (COPD). Methods: In this mixed methods observational study, participants with COPD were recruited following PR assessment. Participants were educated on m-PR™ which contained symptom monitoring, individualised exercise training with exercise videos, education videos, goal setting, health notifications and medication action plan. Participants used m-PR™ for 4-8 weeks. At baseline, participants were surveyed to assess level of technology engagement. At follow-up, participants completed the system usability survey (SUS), a satisfaction survey and a semi-structured interview. Results: Fifteen participants (mean age 70 [SD 10] years, 53% female) completed the study. Technology usage was high with 73% (n = 11) self-rating their technology competence as good or very good. The SUS score of 71 (SD 16) demonstrated above average perceived usability of m-PR™. The satisfaction survey indicated that 67% (n = 10) enjoyed m-PR™ and 33% (n = 5) were neutral. Most participants found the different m-PR™ components somewhat easy or very easy to use (range 69-100%) and somewhat helpful or very helpful (range 76-100%). Interview responses revealed that m-PR™ elicited divergent feelings among participants, who reported both positive and negative feelings towards the app's features, the effort required to use it and data security. Conclusion: The majority of participants found m-PR™ enjoyable, easy to use and helpful in managing their COPD. Further research is warranted to understand the effectiveness of mHealth to deliver PR.

A Pragmatic Informatics Approach to Develop Knowledge Tools for Supporting Cardiac Surgical Patients' Mental Health Needs.

A pragmatic informatics approach was developed to create knowledge tools for co-design of a new model of mental healthcare in cardiac surgery The real-world evidence generation leverages existing technological platforms and routine data collections plus tailored brief tools, surveys and qualitative data.

PD-Buddy: A Feasibility Study of Mobile Health to Support the Management of Peritoneal Dialysis.

People experiencing peritoneal dialysis (PD) are expected to document considerable clinical information at home, yet timely and accurate data collection, and sharing of data with their health team is associated with challenges. Mobile health technologies present an opportunity to bridge home and hospital care. PD-Buddy is a novel smartphone and web-based platform which guides people experiencing PD through their dialysis treatment. The platform was tested in a feasibility study with (n=33) people attending a Peritoneal Dialysis Clinic in Brisbane, Australia. The study evaluated adoption and satisfaction of the system among users (patients and clinicians), as well as infection rates. Findings indicate PD-Buddy to be a user-friendly solution that could expand access to, and improve, the quality of healthcare for people experiencing PD. It could reduce burdens for regional and remote populations, such as travelling to receive specialty care, and improve monitoring, timeliness, and communications with and within their care teams.

Informing Personalised Gamification Interventions Through a Novel Gamified Quiz.

Nonadherence to medical interventions and other advice leads to increased care costs and poorer health outcomes across a range of medical fields. An approach to increasing adherence is gamification. To maximize the benefits of gamification, a more structured and informed implementation is required. In this paper, a novel web-based personality determiner has been outlined, the integration of which could provide the personalisation required for an optimized gamification implementation.

The Significance and Limitations of Sensor-based Agitation Detection in People Living with Dementia.

Agitation, a commonly observed behaviour in people living with dementia (PLwD), is frequently interpreted as a response to physiological, environmental, or emotional stress. Agitation has the potential to pose health risks to both individuals and their caregivers, and can contribute to increased caregiver burden and stress. Early detection of agitation can facilitate with timely intervention, which has the potential to prevent escalation to other challenging behaviors. Wearable and ambient sensors are frequently used to monitor physiological and behavioral conditions and the collected signals can be engaged to detect the onset of an agitation episode. This paper delves into the current sensor-based methods for detecting agitation in PLwD, and reviews the strengths and limitations of existing works. Future directions to enable real-time agitation detection to empower caregivers are also deliberated, with a focus on their potential to reduce caregiver burden by facilitating early support, assistance and interventions to timely manage agitation episodes in PLwD.

A novel, multidomain, primary care nurse-led and mHealth-assisted intervention for dementia risk reduction in middle-aged adults (HAPPI MIND): study protocol for a cluster randomised controlled trial.

INTRODUCTION: Middle-aged multidomain risk reduction interventions targeting modifiable risk factors for dementia may delay or prevent a third of dementia cases in later life. We describe the protocol of a cluster randomised controlled trial (cRCT), HAPPI MIND (Holistic Approach in Primary care for PreventIng Memory Impairment aNd Dementia). HAPPI MIND will evaluate the efficacy of a multidomain, nurse-led, mHealth supported intervention for assessing dementia risk and reducing associated risk factors in middle-aged adults in the Australian primary care setting. METHODS AND ANALYSIS: General practice clinics (n≥26) across Victoria and New South Wales, Australia, will be recruited and randomised. Practice nurses will be trained to implement the HAPPI MIND intervention or a brief intervention. Patients of participating practices aged 45-65 years with ≥2 potential dementia risk factors will be identified and recruited (approximately 15 patients/clinic). Brief intervention participants receive a personalised report outlining their risk factors for dementia based on Australian National University Alzheimer's Disease Risk Index (ANU-ADRI) scores, education booklet and referral to their general practitioner as appropriate. HAPPI MIND participants receive the brief intervention as well as six individualised dementia risk reduction sessions with a nurse trained in motivational interviewing and principles of behaviour change, a personalised risk reduction action plan and access to the purpose-built HAPPI MIND smartphone app for risk factor self-management. Follow-up data collection will occur at 12, 24 and 36 months. Primary outcome is ANU-ADRI score change at 12 months from baseline. Secondary outcomes include change in cognition, quality of life and individual risk factors of dementia. ETHICS AND DISSEMINATION: Project approved by Monash University Human Research Ethics Committee (ID: 28273). Results will be disseminated in peer-reviewed journals and at healthcare conferences. If effective in reducing dementia risk, the HAPPI MIND intervention could be integrated into primary care, scaled up nationally and sustained over time. TRIAL REGISTRATION NUMBER: ACTRN12621001168842.

Remote blood pressure monitoring in high risk pregnancy - study protocol for a randomised controlled trial (REMOTE CONTROL trial).

BACKGROUND: Pregnant women at high risk for developing a hypertensive disorder of pregnancy require frequent antenatal assessments, especially of their blood pressure. This expends significant resources for both the patient and healthcare system. An alternative to in-clinic assessments is a remote blood pressure monitoring strategy, in which patients self-record their blood pressure at home using a validated blood pressure machine. This has the potential to be cost-effective, increase patient satisfaction, and reduce outpatient visits, and has had widespread uptake recently given the increased need for remote care during the ongoing COVID-19 pandemic. However robust evidence supporting this approach over a traditional face-to-face approach is lacking, and the impact on maternal and foetal outcomes has not yet been reported. Thus, there is an urgent need to assess the efficacy of remote monitoring in pregnant women at high risk of developing a hypertensive disorder of pregnancy. METHODS: The REMOTE CONTROL trial is a pragmatic, unblinded, randomised controlled trial, which aims to compare remote blood pressure monitoring in high-risk pregnant women with conventional face-to-face clinic monitoring, in a 1:1 allocation ratio. The study will recruit patients across 3 metropolitan Australian teaching hospitals and will evaluate the safety, cost-effectiveness, impact on healthcare utilisation and end-user satisfaction of remote blood pressure monitoring. DISCUSSION: Remote blood pressure monitoring is garnering interest worldwide and has been increasingly implemented following the COVID-19 pandemic. However, robust data regarding its safety for maternofoetal outcomes is lacking. The REMOTE CONTROL trial is amongst the first randomised controlled trials currently underway, powered to evaluate maternal and foetal outcomes. If proven to be as safe as conventional clinic monitoring, major potential benefits include reducing clinic visits, waiting times, travel costs, and improving delivery of care to vulnerable populations in rural and remote communities. TRIAL REGISTRATION: The trial has been prospectively registered with the Australian and New Zealand Clinical Trials Registry (ACTRN12620001049965p, on October 11th, 2020).

Mobile Health Pulmonary Rehabilitation Compared to a Center-Based Program for Cost-Effectiveness and Effects on Exercise Capacity, Health Status, and Quality of Life in People With Chronic Obstructive Pulmonary Disease: A Protocol for a Randomized Controlled Trial.

OBJECTIVE: The use of digital health is a novel way to improve access to comprehensive pulmonary rehabilitation for people with chronic obstructive pulmonary disease (COPD). This study aims to determine if a home-based pulmonary rehabilitation program supported by mobile health (mHealth) technology is equivalent to center-based pulmonary rehabilitation in terms of improvements in exercise capacity and health status in people with COPD. METHODS: This study is a prospective, multicenter, equivalence randomized controlled trial (RCT) with intention-to-treat analysis. A hundred participants with COPD will be recruited from 5 pulmonary rehabilitation programs. Following randomization, participants will be assigned in a concealed manner to receive either home-based pulmonary rehabilitation supported by mHealth or center-based pulmonary rehabilitation. Both programs will be 8 weeks and will include progressive exercise training, disease management education, self-management support, and supervision by a physical therapist. Co-primary outcome measures will be the 6-Minute Walk Test and the COPD Assessment Test. Secondary outcome measures will include the St George's Respiratory Questionnaire, the EuroQol 5 Dimension 5 Level, the modified Medical Research Council dyspnea scale, the 1-minute sit-to-stand test, the 5 times sit-to-stand test, the Hospital Anxiety and Depression Scale, daily physical activity levels, health care utilization, and costs. Outcomes will be measured at baseline and at the end of the intervention. Participant experience will be assessed through semi-structured interviews at the end of the intervention. Utilization of health care and costs will be measured again after 12 months. IMPACT: This study will be the first rigorous RCT to examine the effects of a home-based pulmonary rehabilitation program supported by mHealth technology that includes comprehensive clinical outcome evaluation, assessment of daily physical activity, a health economic analysis, and qualitative analysis. If findings demonstrate that there is equivalence in clinical outcomes, that the mHealth program costs the least amount (and is thus cost-effective), and that the mHealth program is acceptable to participants, such programs should be widely implemented to improve access to pulmonary rehabilitation.

Clinical utility of a mHealth assisted intervention for activity modulation in chronic pain: The pilot implementation of pain ROADMAP.

BACKGROUND: Being able to successfully self-regulate one's activity levels is a key adaptation strategy for many people with chronic pain. This study aimed to explore the clinical utility of a mobile health platform (Pain ROADMAP) for assisting with the delivery of a tailored activity modulation intervention for people with persistent pain. METHODS: Twenty adults with chronic pain undertook 1-week monitoring intervals which involved wearing an Actigraph activity monitor and entering pain, opioid use, and activity participation data into a custom-made phone app. The Pain ROADMAP online portal integrated and analysed the data to detect activities that caused a severe pain exacerbation and provided summary statistics pertaining the data collected. As part of a 15-week treatment protocol, participants received feedback from three dispersed Pain ROADMAP monitoring periods. Treatment focused on adapting pain-provoking activities, gradually increase goal-related activity and optimizing routine. RESULTS: Results revealed good participant acceptability of monitoring procedures and reasonable adherence to both monitoring procedures and clinical follow-up appointments. Preliminary efficacy was established through clinically meaningful decreases in overactivity behaviour, pain variation, opioid use, depression, activity avoidance, and increases in productivity. No adverse outcomes were observed. CONCLUSION: The results of this study provide initial support for the clinical utility of mHealth assisted activity modulation interventions that involve remote monitoring. SIGNIFICANCE: This is the first study to demonstrate how mHealth innovations that utilise ecological momentary assessment can be successfully integrated with wearable technologies to provide a tailored activity modulation intervention that is both highly valued by people with chronic pain and assists individuals to make constructive behavioural changes. Adaptions such as low costs sensors, increased customisability and gamification may be important for enhanced uptake, adherence and scalability.

Mobile Health Use by Older Individuals at Risk of Cardiovascular Disease and Type 2 Diabetes Mellitus in an Australian Cohort: Cross-sectional Survey Study.

BACKGROUND: The digital transformation has the potential to change health care toward more consumers' involvement, for example, in the form of health-related apps which are already widely available through app stores. These could be useful in helping people understand their risk of chronic conditions and helping them to live more healthily. OBJECTIVE: With this study, we assessed mobile health app use among older Australians in general and among those who were at risk of cardiovascular disease or type 2 diabetes mellitus. METHODS: In this cross-sectional analysis, we used data from the second follow-up wave of the 45 and Up Study. It is a cohort study from New South Wales, Australia, with 267,153 participants aged 45 years and older that is based on a random sample from the Services Australia (formerly the Australian Government Department of Human Services) Medicare enrollment database. The 2019 follow-up questionnaire contained questions about technology and mobile health use. We further used data on prescribed drugs and hospitalizations to identify participants who already had cardiovascular disease or diabetes or who were at risk of these conditions. Our primary outcome measure was mobile health use, defined as having used a mobile health app before. We used descriptive statistics and multivariate logistic regression to answer the research questions. RESULTS: Overall, 31,946 individuals with a median age of 69 (IQR 63-76) years had completed the follow-up questionnaire in 2019. We classified half (16,422/31,946, 51.41%) of these as being at risk of cardiovascular disease or type 2 diabetes mellitus and 38.04% (12,152/31,946) as having cardiovascular disease or type 1 or type 2 diabetes mellitus. The proportion of mobile health app users among the at-risk group was 31.46% (5166/16,422) compared to 29.16% (9314/31,946) in the total sample. Those who used mobile health apps were more likely to be female, younger, without physical disability, and with a higher income. People at risk of cardiovascular disease or type 2 diabetes mellitus were not statistically significantly more likely to use mobile health than were people without risk (odds ratio 1.06, 95% CI 0.97-1.16; P=.18; adjusted for age, sex, income, and physical disability). CONCLUSIONS: People at risk of cardiovascular disease or type 2 diabetes mellitus were not more likely to use mobile health apps than were people without risk. Those who used mobile health apps were less likely to be male, older, with a physical disability, and with a lower income. From the results, we concluded that aspects of equity must be considered when implementing a mobile health intervention to reach all those that can potentially benefit from it.

Remotely Conducted App-Based Intervention for Cardiovascular Disease and Diabetes Risk Awareness and Prevention: Single-Group Feasibility Trial.

BACKGROUND: Cardiovascular disease and type 2 diabetes mellitus are two of the most prevalent chronic conditions worldwide. An unhealthy lifestyle greatly contributes to someone's risk of developing these conditions. Mobile health is an emerging technology that can help deliver health promotion interventions to the population, for example, in the form of health apps. OBJECTIVE: The aim of this study was to test the feasibility of an app-based intervention for cardiovascular and diabetes risk awareness and prevention by measuring nonusage, dropout, adherence to app use, and usability of the app over 3 months. METHODS: Participants were eligible if they were aged 45 years or older, resided in Australia, were free of cardiovascular disease and diabetes, were fluent in English, and owned a smartphone. In the beginning, participants received an email with instructions on how to install the app and a user guide. After 3 months, they received an email with an invitation to an end-of-study survey. The survey included questions about general smartphone use and the user version of the Mobile Application Rating Scale. We analyzed app-generated and survey data by using descriptive and inferential statistics as well as thematic analysis for open-text comments. RESULTS: Recruitment took place between September and October 2021. Of the 46 participants who consented to the study, 20 (44%) never used the app and 15 (33%) dropped out. The median age of the app users at baseline was 62 (IQR 56-67) years. Adherence to app use, that is, using the app at least once a week over 3 months, was 17% (8/46) of the total sample and 31% (8/26) of all app users. The mean app quality rating on the user version of the Mobile Application Rating Scale was 3.5 (SD 0.6) of 5 points. The app scored the highest for the information section and the lowest for the engagement section of the scale. CONCLUSIONS: Nonusage and dropouts were too high, and the adherence was too low to consider the intervention in its current form feasible. Potential barriers that we identified include the research team not actively engaging with participants early in the study to verify that all participants could install the app, the intervention did not involve direct contact with health care professionals, and the app did not have enough interactive features.

A Mobile App for Prevention of Cardiovascular Disease and Type 2 Diabetes Mellitus: Development and Usability Study.

BACKGROUND: Cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM) are posing a huge burden on health care systems worldwide. Mobile apps can deliver behavior change interventions for chronic disease prevention on a large scale, but current evidence for their effectiveness is limited. OBJECTIVE: This paper reported on the development and user testing of a mobile app that aims at increasing risk awareness and engaging users in behavior change. It would form part of an intervention for primary prevention of CVD and T2DM. METHODS: The theoretical framework of the app design was based on the Behaviour Change Wheel, combined with the capability, opportunity, and motivation for behavior change system and the behavior change techniques from the Behavior Change Technique Taxonomy (version 1). In addition, evidence from scientific literature has guided the development process. The prototype was tested for user-friendliness via an iterative approach. We conducted semistructured interviews with individuals in the target populations, which included the System Usability Scale. We transcribed and analyzed the interviews using descriptive statistics for the System Usability Scale and thematic analysis to identify app features that improved utility and usability. RESULTS: The target population was Australians aged ≥45 years. The app included 4 core modules (risk score, goal setting, health measures, and education). In these modules, users learned about their risk for CVD and T2DM; set goals for smoking, alcohol consumption, diet, and physical activity; and tracked them. In total, we included 12 behavior change techniques. We conducted 2 rounds of usability testing, each involving 5 participants. The average age of the participants was 58 (SD 8) years. Totally, 60% (6/10) of the participants owned iPhone Operating System phones, and 40% (4/10) of them owned Android phones. In the first round, we identified a technical issue that prevented 30% (3/10) of the participants from completing the registration process. Among the 70% (7/10) of participants who were able to complete the registration process, 71% (5/7) rated the app above average, based on the System Usability Scale. During the interviews, we identified some issues related to functionality, content, and language and clarity. We used the participants' feedback to improve these aspects. CONCLUSIONS: We developed the app using behavior change theory and scientific evidence. The user testing allowed us to identify and remove technical errors and integrate additional functions into the app, which the participants had requested. Next, we will evaluate the feasibility of the revised version of the app developed through this design process and usability testing.

The Smarter Safer Homes Solution to Support Older People Living in Their Own Homes Through Enhanced Care Models: Protocol for a Stratified Randomized Controlled Trial.

BACKGROUND: An aging population, accompanied by the prevalence of age-related diseases, presents a significant burden to health systems. This is exacerbated by an increasing shortage of aged care staff due to the existing workforce entering their retirement and fewer young people being attracted to work in aged care. In line with consumer preferences and potential cost-efficiencies, government and aged care providers are increasingly seeking options to move care and support to the community or home as opposed to residential care facilities. However, compared to residential care, home environments may provide limited opportunity for monitoring patients' progression/decline in functioning and therefore limited opportunity to provide timely intervention. To address this, the Smarter Safer Homes (SSH) platform was designed to enable self-monitoring and/or management, and to provide aged care providers with support to deliver their services. The platform uses open Internet of Things communication protocols to easily incorporate commercially available sensors into the system. OBJECTIVE: Our research aims to detail the benefits of utilizing the SSH platform as a service in its own right as well as a complementary service to more traditional/historical service offerings in aged care. This work is anticipated to validate the capacity and benefits of the SSH platform to enable older people to self-manage and aged care service providers to support their clients to live functionally and independently in their own homes for as long as possible. METHODS: This study was designed as a single-blinded, stratified, 12-month randomized controlled trial with participants recruited from three aged care providers in Queensland, Australia. The study aimed to recruit 200 people, including 145 people from metropolitan areas and 55 from regional areas. Participants were randomized to the intervention group (having the SSH platform installed in their homes to assist age care service providers in monitoring and providing timely support) and the control group (receiving their usual aged care services from providers). Data on community care, health and social-related quality of life, health service utilization, caregiver burden, and user experience of both groups were collected at the start, middle (6 months), and end of the trial (12 months). RESULTS: The trial recruited its first participant in April 2019 and data collection of the last participant was completed in November 2020. The trial eventually recruited 195 participants, with 98 participants allocated to the intervention group and 97 participants allocated to the control group. The study also received participants' health service data from government data resources in June 2021. CONCLUSIONS: A crisis is looming to support the aging population. Digital solutions such as the SSH platform have the potential to address this crisis and support aged care in the home and community. The outcomes of this study could improve and support the delivery of aged care services and provide better quality of life to older Australians in various geographical locations. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12618000829213; https://tinyurl.com/2n6a75em. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/31970.

The Significance and Limitations of Monitoring Sleep during Pregnancy.

Sleep patterns often change during pregnancy and postpartum. However, if severe and persistent, these changes can depict a risk factor for significant health complications. It is thus essential to identify and understand changes in women's sleeping pattern over the course of pregnancy and postpartum, to offer an appropriate and timely intervention if necessary. In this paper, we discuss sleep disturbances during pregnancy and their association with pregnancy complications. We also review the state-of-the-art digital devices for real-time sleep assessment, and highlight their strengths and limitations.Clinical Relevance-This review highlights an importance of an individualized holistic pregnancy care program which engages both the healthcare professionals and the obstetric population, together with an educational module to increase the user awareness on the importance of sleep disturbances and their consequences during and after pregnancy.

Users' Perceptions Toward mHealth Technologies for Health and Well-being Monitoring in Pregnancy Care: Qualitative Interview Study.

BACKGROUND: Mobile health (mHealth) technologies, such as wearable sensors, smart health devices, and mobile apps, that are capable of supporting pregnancy care are emerging. Although mHealth could be used to facilitate the tracking of health changes during pregnancy, challenges remain in data collection compliance and technology engagement among pregnant women. Understanding the interests, preferences, and requirements of pregnant women and those of clinicians is needed when designing and introducing mHealth solutions for supporting pregnant women's monitoring of health and risk factors throughout their pregnancy journey. OBJECTIVE: This study aims to understand clinicians' and pregnant women's perceptions on the potential use of mHealth, including factors that may influence their engagement with mHealth technologies and the implications for technology design and implementation. METHODS: A qualitative study using semistructured interviews was conducted with 4 pregnant women, 4 postnatal women, and 13 clinicians working in perinatal care. RESULTS: Clinicians perceived the potential benefit of mHealth in supporting different levels of health and well-being monitoring, risk assessment, and care provision in pregnancy care. Most pregnant and postnatal female participants were open to the use of wearables and health monitoring devices and were more likely to use these technologies if they knew that clinicians were monitoring their data. Although it was acknowledged that some pregnancy-related medical conditions are suitable for an mHealth model of remote monitoring, the clinical and technical challenges in the introduction of mHealth for pregnancy care were also identified. Incorporating appropriate health and well-being measures, intelligently detecting any abnormalities, and providing tailored information for pregnant women were the critical aspects, whereas usability and data privacy were among the main concerns of the participants. Moreover, this study highlighted the challenges of engaging pregnant women in longitudinal mHealth monitoring, the additional work required for clinicians to monitor the data, and the need for an evidence-based technical solution. CONCLUSIONS: Clinical, technical, and practical factors associated with the use of mHealth to monitor health and well-being in pregnant women need to be considered during the design and feasibility evaluation stages. Technical solutions and appropriate strategies for motivating pregnant women are critical to supporting their long-term data collection compliance and engagement with mHealth technology during pregnancy.

Home telemonitoring for chronic disease management: Perceptions of users and factors influencing adoption.

Home telemonitoring has been used as a solution to support the care of individuals living with chronic disease. While effectiveness of telemonitoring have been widely studied, more research is needed to understand the perceptions among patients and clinicians in incorporating telemonitoring into their daily routine and practices. This paper presents an investigation of patients' and clinicians' experiences in a care augmenting telemonitoring service, their perceived impact delivered through the service, and clinicians' perceptions on how the service was introduced in their organizations. This work was embedded in a large multi-site trial of home telemonitoring using a mixed method approach for evaluation. Interviews with clinicians involved in the study were conducted at multiple time points during the trial. Questionnaires were administered to clinicians and patients at the end of the trial. Results showed that both patients and clinicians recognized the benefits of patient empowerment through telemonitoring, and patient-clinician interactions. Results identified the needs of a dedicated telemonitoring clinical care coordinator role, guidelines that translate telemonitoring services into clinical pathways and engagement of different healthcare providers, especially general practitioners, to support the integration of telemonitoring into chronic disease management programs and long-term organizational strategic plans.

Validation of a lifestyle-based risk score for type 2 diabetes mellitus in Australian adults.

The study aimed to assess the performance of a lifestyle-based prognostic risk model (Diabetes Lifestyle Score) for the prediction of 5-year risk of type 2 diabetes mellitus. The model comprises nine self-reported predictors (sex, age, antihypertensive drugs, body mass index, family history of diabetes, physical activity, fruits, vegetables, and wholemeal/brown bread). We conducted an external validation and update of the model in an Australian cohort including 97,615 residents of New South Wales aged 45 years and older who were free of type 1 and 2 diabetes mellitus at baseline. Of all participants, 4,741 developed type 2 diabetes mellitus over 5 years. We conducted the statistical analyses in RStudio using the programming language R. The area under the receiver operating characteristic curve (AUC) of the original model was 0.726 (95% confidence interval: 0.719, 0.733). After adjusting the calibration intercept and slope, the original model performed reasonably well in the external cohort. The best performance was measured by using the numerical predictors as continuous variables and refitting all coefficients (AUC: 0.741, 95% confidence interval: 0.734, 0.748). The results of the original model after calibration were comparable to those received from the AUSDRISK score which is routinely used in Australian clinical practice. Hence, the lifestyle-based model might be a reasonable alternative for laypersons since the required information is most likely known by these. Further, the risk score may communicate the message about the importance of a healthy diet to reduce the risk of diabetes.

Overactivity assessment in chronic pain: The development and psychometric evaluation of a multifaceted self-report assessment.

BACKGROUND: Overactivity in the context of chronic pain (i.e. activity engagement that significantly exacerbates pain) is an important clinical issue that has gained empirical attention in the last decade. Current assessment concepts of overactivity tend to focus on frequency to quantify the severity of the pain behaviour. This study aimed to develop and validate a more comprehensive self-assessment, the Overactivity in Persistent Pain Assessment (OPPA). METHODS: A sample of 333 individuals with chronic pain completed the OPPA. A subset of 202 individuals also completed a set of existing measures of pain-related outcomes and activity patterns. The remaining 131 participants were provided with a second copy of the OPPA to fill in one week following their initial assessment. RESULTS: A principal component analysis confirmed that the OPPA items were best represented by a single construct. The OPPA was found to correlate with pain-related measures in an expected way that is supported by both theory and qualitative data. When compared to existing overactivity measures, the OPPA was the only measure to contribute significantly to the regression models predicting higher levels of pain severity, more pain interference and lower levels of activity participation after controlling for age, gender and activity avoidance. In addition, the OPPA scale exhibited acceptable internal consistency and good test-retest reliability. CONCLUSION: The results of this study reinforce the potentially important role of overactivity in the maintenance of pain-related suffering and supports a corresponding assessment tool with preliminary psychometric evidence for clinical and research applications. SIGNIFICANCE: This study deconstructs the overactivity concept and develop a corresponding assessment based on five quantifiable severity features: severity of pain exacerbation, maladaptive coping strategies used, impact on occupational performance, recovery time and frequency. Results of the psychometric evaluation indicate that this comprehensive assessment of overactivity severity features may be necessary to understand the impact of overactivity on pain severity and physical functioning from both a clinical and research perspective.

M♡THer, an mHealth System to Support Women with Gestational Diabetes Mellitus: Feasibility and Acceptability Study.

Background: Gestational diabetes mellitus (GDM) is defined as glucose intolerance first identified during pregnancy. Delays in diagnosis and challenges in management can lead to serious adverse outcomes for the mother and child. As rates of GDM diagnosis increase worldwide, health systems and maternity services have become increasingly strained, especially with new restrictions around in-person care due to the current COVID-19 pandemic. Mobile health (mHealth) has increasingly shown promise for management of chronic disease, driven by smartphone adoption and increased internet connectivity. The aim of this work was to evaluate the adoption and multidisciplinary care coordination of an mHealth platform called M♡THer in a cohort of women with first-time diagnosis of GDM. Methods: The mHealth platform for GDM management was developed incorporating a smartphone application, clinician portal, and secure cloud data storage. Forty participants with a first-time diagnosis of GDM were recruited to use the app during their pregnancy. User attitudes from clinicians and women were captured through post-hoc surveys, and app-usage metrics. Results: Clinicians and women indicated satisfaction and ease of use of the mHealth platform, with some technological challenges around wireless connectivity. Blood glucose reviews and antenatal contact were higher with use of the M♡THer app compared with a matched historical sample. Conclusion: The M♡THer mHealth platform is a new comprehensive tool for health care of women with GDM, and may provide an effective new avenue to enhance multidisciplinary care in the face of COVID-19 disruptions and challenges to traditional care pathways.