Use of Digital Health Technology Among Older Adults With Cancer in the United States: Findings From a National Longitudinal Cohort Study (2015-2021).

BACKGROUND: Despite the benefits of digital health technology use, older adults with cancer (ie, aged 65 years) have reported challenges to technology adoption. However, there has been a lack of a good understanding of their digital health technology use patterns and the associated influential factors in the past few years. OBJECTIVE: This study aimed to examine the trends in and factors associated with digital health technology use among older adults with cancer. METHODS: The National Health and Aging Trends Study (NHATS) data set is a national longitudinal cohort study with annual survey waves of Medicare beneficiaries 65 years and older. Participants were community-dwelling older adults who self-reported previous or current cancer diagnoses in each round. The study sample size of each round ranged from 1996 (2015) to 1131 (2021). Digital health technology use was defined as using the internet or online in the last month to order or refill prescriptions, contact medical providers, handle Medicare or other insurance matters, or get information about their health conditions. The association of sociodemographics, clinical factors (self-rated health, chronic conditions, difficulties in activities of daily living, dementia, anxiety, and depression), and physical function (Short Physical Performance Battery and grip strength) with digital health technology use was examined using design-based logistic regression. All statistical analyses accounted for the complex sample design. RESULTS: The prevalence of any digital health technology use increased from 36% in 2015 to 45% in 2019. In 2020-2021, which was amid the COVID-19 pandemic, it ranged from 51% to 52%. In terms of each digital health technology use behavior, in 2015, overall, 28% of older cancer survivors used digital health technology to obtain health information, followed by contacting clinicians (19%), filling prescriptions (14%), and handling insurance (11%). Greater use of digital health technology was associated with younger age, being White, having a college or higher education, having a higher income, having more comorbidities, nondementia, and having a higher gait speed. CONCLUSIONS: Digital health technology use in older adults with cancer has gradually increased, particularly during the COVID-19 pandemic. However, socioeconomic and racial disparities have remained in older cancer survivors. Additionally, older adults with cancer may have some unique features associated with digital health technology use; for example, their use of digital health may be increased by their comorbidities (ie, health care needs) and reduced by their frailty.

Effectiveness of telehealth-based exercise interventions on pain, physical function and quality of life in patients with knee osteoarthritis: A meta-analysis.

OBJECTIVE: The objective of the study was to evaluate the effectiveness of telehealth-based exercise intervention on pain, physical function and quality of life in patients with knee osteoarthritis. DESIGN: A systematic review and meta-analysis of randomised controlled trials (RCTs). METHODS: Six databases (PubMed, Embase, Cochrane Library, CINAHL, PEDro and Web of Science Core Collection) were searched for relevant randomised controlled trials published from database inception to 3 June 2021. Reviewers independently screened the literature, extracted data and used the Cochrane Collaboration Risk of Bias Tool for quality assessment. A meta-analysis and subgroup analyses, stratified by control condition, intervention duration and delivery type, were conducted by Revman 5.4. The study was reported in compliance with PRISMA statement. RESULTS: A total of 9 independent RCTs with 861 participants were included. The meta-analysis showed that the telehealth-based exercise interventions significantly reduced pain in KOA patients (SMD = -0.28, 95% CI [-0.49, -0.08], p < .01) and produced similar effects to controls in terms of physical function and quality of life. Subgroup analysis revealed that telehealth-based exercise interventions were superior to the use of exercise booklet and usual care in terms of pain and physical function and were similar to face-to-face exercise treatment; a long-term (>3 months) intervention and the use of web and smartphone APPs to deliver exercise interventions were associated with better pain relief and physical function. CONCLUSIONS: Telehealth-based exercise intervention is an effective strategy for KOA management during the COVID-19 epidemic, and it is significantly better than usual care in reducing knee pain and improving physical function and was able to achieve the effects of traditional face-to-face exercise treatment. Although the duration and type of delivery associated with the effect of the intervention have been identified, patient preference and acceptability need to be considered in practice.

Comparison of Augmented Reality-assisted and Instructor-assisted Cardiopulmonary Resuscitation: A Simulated Randomized Controlled Pilot Trial.

Background: A trained lay rescuer is the most important determinant of survival from sudden cardiac arrest. Augmented Reality (AR) device may represent a powerful instrument for CPR assistance and self-training especially during the COVID-19 pandemic. Methods: A prospective, parallel, 1:1 pilot randomized clinical trial was designed. An AR CPR app was developed and 28 participants were randomly allocated into AR-assisted group and instructor-assisted group. Acceptability, usability, and mean per minute/per cycle chest compression depth, rate and accuracy were measured. Results: The mean scores for acceptability and usability were all rated good in each group. Comparing real-time AR-assisted CPR to instructor-assisted CPR, the mean difference of compression depth was 0.18 (95% CI: -0.18-0.53) cm and rate was -1.58 (95% CI: -6.11-2.95) min-1. Comparing AR self-training to instructor training, the AR group was not significantly different between two groups regarding both compression depth, rate and accuracy (p > .05). Conclusion: We found that the AR CPR app was an acceptable and usable tool both in real-time-assisted CPR and self-training CPR.