Background Approximately 50% of cardiovascular disease (CVD) cases are attributable to lifestyle risk factors. Despite widespread education, personal knowledge, and efficacy, many individuals fail to adequately modify these risk factors, even after a cardiovascular event. Digital technology interventions have been suggested as a viable equivalent and potential alternative to conventional cardiac rehabilitation care centers. However, little is known about the clinical effectiveness of these technologies in bringing about behavioral changes in patients with CVD at an individual level. Objective The aim of this study is to identify and measure the effectiveness of digital technology (eg, mobile phones, the internet, software applications, wearables, etc) interventions in randomized controlled trials (RCTs) and determine which behavior change constructs are effective at achieving risk factor modification in patients with CVD. Methods This study is a systematic review and meta-analysis of RCTs designed according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analysis) statement standard. Mixed data from studies extracted from selected research databases and filtered for RCTs only were analyzed using quantitative methods. Outcome hypothesis testing was set at 95% CI and P=.05 for statistical significance. Results Digital interventions were delivered using devices such as cell phones, smartphones, personal computers, and wearables coupled with technologies such as the internet, SMS, software applications, and mobile sensors. Behavioral change constructs such as cognition, follow-up, goal setting, record keeping, perceived benefit, persuasion, socialization, personalization, rewards and incentives, support, and self-management were used. The meta-analyzed effect estimates (mean difference [MD]; standard mean difference [SMD]; and risk ratio [RR]) calculated for outcomes showed benefits in total cholesterol SMD at −0.29 [−0.44, −0.15], P<.001; high-density lipoprotein SMD at –0.09 [–0.19, 0.00], P=.05; low-density lipoprotein SMD at −0.18 [−0.33, −0.04], P=.01; physical activity (PA) SMD at 0.23 [0.11, 0.36], P<.001; physical inactivity (sedentary) RR at 0.54 [0.39, 0.75], P<.001; and diet (food intake) RR at 0.79 [0.66, 0.94], P=.007. Initial effect estimates showed no significant benefit in body mass index (BMI) MD at −0.37 [−1.20, 0.46], P=.38; diastolic blood pressure (BP) SMD at −0.06 [−0.20, 0.08], P=.43; systolic BP SMD at −0.03 [−0.18, 0.13], P=.74; Hemoglobin A1C blood sugar (HbA1c) RR at 1.04 [0.40, 2.70], P=.94; alcohol intake SMD at −0.16 [−1.43, 1.10], P=.80; smoking RR at 0.87 [0.67, 1.13], P=.30; and medication adherence RR at 1.10 [1.00, 1.22], P=.06. Conclusions Digital interventions may improve healthy behavioral factors (PA, healthy diet, and medication adherence) and are even more potent when used to treat multiple behavioral outcomes (eg, medication adherence plus). However, they did not appear to reduce unhealthy behavioral factors (smoking, alcohol intake, and unhealthy diet) and clinical outcomes (BMI, triglycerides, diastolic and systolic BP, and HbA1c).
Introduction: Demographic changes and shifting populations mean growing numbers of older people are living alone in rural areas. General practitioner (GP) out-of-hours (GPOOH) services have an essential role in supporting older people to remain living in their own homes and communities for as long as possible, but little is known about use of GPOOH services by this cohort. This research examines how rurality impacts accessibility and utilisation of GPOOH services by people aged 65 years or more in rural Ireland. Methods: Conducted in the mainly rural counties of Cavan and Monaghan in the north-east of Ireland, this research used a mixed methods approach. Questionnaires and focus groups were conducted with 48 older people in six locations across both counties. A thematic analysis was conducted on the data using NVivo software. Results:The challenge for older rural populations includes difficulties accessing transport and the limited availability of support networks during times of a health crisis, especially at night. The present findings show such challenges are further compounded by a lack of information about available services. Rurality complicates each of these challenges, because it adds to the vulnerability of older adults. This is most acutely felt by those who live alone and those living the furthest from GPOOH treatment centres. The most important concern for older people, when unwell outside doctor surgery hours, is the need for access to medical care as quickly as possible. Inability to use GPOOH services leads many older people to seek help from accident and emergency departments, where faster access to clinical care is sometimes assumed. Conclusions: For rural-dwelling older people, becoming ill Rural and Remote Health rrh.org.au James Cook University ISSN 1445-6354 1 2 1, 2outside GP surgery hours is complex and the barriers faced are often insurmountable at times of greatest need. Worries about accessibility and lack of information give rise to a hesitancy to use GPOOH services in a population that is already known to be reluctant to ask for help, even when such help is justified. In turn, the lack of familiarity with what is a fundamental community health service further impacts the willingness of older adults to call on GPOOH services for help when needed. Addressing the impact of rurality on access and use of out-of-hours medical services is essential to enable more older adults to live longer in their rural homes and communities, supported by services that are responsive to their needs regardless of where they live. Given GPOOH is the only current alternative out-of-hours medical service to accident and emergency departments, more research is urgently needed on both accessibility of GPOOH services by older adults and the impact of inaccessibility on use of emergency services by older people in rural areas.
Aims and objectives:To report the development, testing and validation of an instrument to assess the stressors experienced by student nurses during their older adult clinical placements. Background:The world's population of older adults is accelerating rapidly, with associated increased healthcare demands and a growing need for skilled nursing staff.However, this sector fails to attract adequate numbers of nursing graduates which is leading to a significant gap between nursing supply and demand. Older adult care is considered to be less attractive than other specialties and accompanied by more sources of stress.Design: A quantitative design was used.Methods: Data were collected from a cohort of Irish student nurses (n = 242) completing older adult clinical placements as part of their undergraduate degree.Exploratory and confirmatory factor analysis examined the instrument's underlying latent structure. Discriminant validity was investigated using a confirmatory factor analysis model with covariates. STROBE guidelines for cross-sectional studies informed reporting of this paper's research. Results:Factor analyses identified two factors relating to "Knowledge and Workload" and "Resources," which were assessed by nine and six items, respectively. Discriminant validity analyses found a significant relationship between age and the workload and knowledge factor, and between year of programme and the resources factor. The new instrument was labelled the Student Nurse Stressor-15 (SNS-15) Scale. Conclusions:The SNS-15 contained some overlap with stressors from extant general student nurse stress instruments and a number of unique stressors encountered in older adult care. Future research directions are discussed.Relevance to clinical practice: The SNS-15 may assist stakeholders in nurse education and practice with the development of undergraduate degree programmes and clinical placements, and ultimately, in improving patient care and student retention. K E Y W O R D Sclinical placements, older adults, stress, stressors, student nurses | 1337 SHERIDAN Et Al.
Background Managing the care of older adults with heart failure (HF) largely centers on medication management. Because of frequent medication or dosing changes, an app that supports these older adults in keeping an up-to-date list of medications could be advantageous. During the COVID-19 pandemic, HF outpatient consultations are taking place virtually or by telephone. An app with the capability to share a patient’s medication list with health care professionals before consultation could support clinical efficiency, for example, by reducing consultation time. However, the influence of apps on maintaining an up-to-date medication history for older adults with HF in Ireland remains largely unexplored. Objective The aims of this review are twofold: to review apps with a medication list functionality and to assess the quality of the apps included in the review using the Mobile App Rating Scale (MARS) and the IMS Institute for Healthcare Informatics functionality scale. Methods A systematic search of apps was conducted in June 2019 using the Google Play Store and iTunes App Store. The MARS was used independently by 4 researchers to assess the quality of the apps using an Android phone and an iPad. Apps were also evaluated using the IMS Institute for Healthcare Informatics functionality score. Results Google Play and iTunes App store searches identified 483 potential apps (292 from Google Play and 191 from iTunes App stores). A total of 6 apps (3 across both stores) met the inclusion criteria. Of the 6 apps, 4 achieved an acceptable MARS score (3/5). The Medisafe app had the highest overall MARS score (4/5), and the Medication List & Medical Records app had the lowest overall score (2.5/5). On average, the apps had 8 functions based on the IMS functionality criteria (range 5-11). A total of 2 apps achieved the maximum score for number of features (11 features) according to the IMS Institute for Healthcare Informatics functionality score, and 2 scored the lowest (5 features). Peer-reviewed publications were identified for 3 of the apps. Conclusions The quality of current apps with medication list functionality varies according to their technical aspects. Most of the apps reviewed have an acceptable MARS objective quality (ie, the overall quality of an app). However, subjective quality (ie, satisfaction with the apps) was poor. Only 3 apps are based on scientific evidence and have been tested previously. A total of 2 apps featured all the IMS Institute for Healthcare Informatics functionalities, and half did not provide clear instructions on how to enter medication data, did not display vital parameter data in an easy-to-understand format, and did not guide users on how or when to take their medication.
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