Background: Remote coaching might be suited for providing information and support to patients with coronary artery disease (CAD) in the vulnerable phase between hospital discharge and the start of cardiac rehabilitation (CR).Objective: The goal of the research was to explore and summarize information and support needs of patients with CAD and develop an early remote coaching program providing tailored information and support.Methods: We used the intervention mapping approach to develop a remote coaching program. Three steps were completed in this study: (1) identification of information and support needs in patients with CAD, using an exploratory literature study and semistructured interviews, (2) definition of program objectives, and (3) selection of theory-based methods and practical intervention strategies.Results: Our exploratory literature study (n=38) and semistructured interviews (n=17) identified that after hospital discharge, patients with CAD report a need for tailored information and support about CAD itself and the specific treatment procedures, medication and side effects, physical activity, and psychological distress. Based on the preceding steps, we defined the following program objectives: (1) patients gain knowledge on how CAD and revascularization affect their bodies and health, (2) patients gain knowledge about medication and side effects and adhere to their treatment plan, (3) patients know which daily physical activities they can and can’t do safely after hospital discharge and are physically active, and (4) patients know the psychosocial consequences of CAD and know how to discriminate between harmful and harmless body signals. Based on the preceding steps, a remote coaching program was developed with the theory of health behavior change as a theoretical framework with behavioral counseling and video modeling as practical strategies for the program.Conclusions: This study shows that after (acute) cardiac hospitalization, patients are in need of information and support about CAD and revascularization, medication and side effects, physical activity, and psychological distress. In this study, we present the design of an early remote coaching program based on the needs of patients with CAD. The development of this program constitutes a step in the process of bridging the gap from hospital discharge to start of CR.
BACKGROUND: The number of mobile apps that support smoking cessation is growing, indicating the potential of the mobile phone as a means to support cessation. Knowledge about the potential end users for cessation apps results in suggestions to target potential user groups in a dissemination strategy, leading to a possible increase in the satisfaction and adherence of cessation apps.OBJECTIVE: This study aimed to characterize potential end users for a specific mobile health (mHealth) smoking cessation app.METHODS: A quantitative study was conducted among 955 Dutch smokers and ex-smokers. The respondents were primarily recruited from addiction care facilities and hospitals through Web-based media via websites and forums. The respondents were surveyed on their demographics, smoking behavior, and personal innovativeness. The intention to use and the attitude toward a cessation app were determined on a 5-point Likert scale. To study the association between the characteristics and intention to use and attitude, univariate and multivariate ordinal logistic regression analyses were performed.RESULTS: The multivariate ordinal logistic regression showed that the number of previous quit attempts (odds ratio [OR] 4.1, 95% CI 2.4-7.0, and OR 3.5, 95% CI 2.0-5.9) and the score on the Fagerstrom Test of Nicotine Dependence (OR 0.8, 95% CI 0.8-0.9, and OR 0.8, 95% CI 0.8-0.9) positively correlates with the intention to use a cessation app and the attitude toward cessation apps, respectively. Personal innovativeness also positively correlates with the intention to use (OR 0.3, 95% CI 0.2-0.4) and the attitude towards (OR 0.2, 95% CI 0.1-0.4) a cessation app. No associations between demographics and the intention to use or the attitude toward using a cessation app were observed.CONCLUSIONS: This study is among the first to show that demographic characteristics such as age and level of education are not associated with the intention to use and the attitude toward using a cessation app when characteristics related specifically to the app, such as nicotine dependency and the number of quit attempts, are present in a multivariate regression model. This study shows that the use of mHealth apps depends on characteristics related to the content of the app rather than general user characteristics.
Background: The need for effective continuing education is especially high in in-hospital geriatric care, as older patients have a higher risk of complications, such as falls. It is important that nurses are able to prevent them. However, it remains unknown which interventions change the behavior of nurses. Therefore, the aim of this study is to identify intervention options to change the behavior of hospital nurses regarding fall prevention among older hospitalized patients. Methods: This study used a mixed method design. The Behavior Change Wheel (BCW) was used to identify intervention functions and policy categories to change the behavior of nurses regarding fall prevention. This study followed the eight steps of the BCW and two methods of data collection were used: five focus groups and three Delphi rounds. The focus groups were held with hospital nurses (n = 26). Geriatric experts (n = 11), managers (n = 13) and educators (n = 13) were included in the Delphi rounds. All data were collected within ten tertiary teaching hospitals in the Netherlands. All participants were included based on predefined in- and exclusion criteria and availability. Results: In Geriatric experts’ opinions interventions targeting behavior change of nurses regarding fall prevention should aim at ‘after-care’, ‘estimating fall risk’ and ‘providing information’. However, in nurses’ opinions it should target; ‘providing information’, ‘fall prevention’ and ‘multifactorial fall risk assessment’. Nurses experience a diversity of limitations relating to capability, opportunity and motivation to prevent fall incidents among older patients. Based on these limitations educational experts identified three intervention functions: Incentivisation, modelling and enablement. Managers selected the following policy categories; communication/marketing, regulation and environmental/social planning. Conclusions: The results of this study show there is a discrepancy in opinions of nurses, geriatric experts, managers and educators. Further insight in the role and collaboration of managers, educators and nurses is necessary for the development of education programs strengthening change at the workplace that enable excellence in nursing practice. DOI: https://doi.org/10.1186/s12912-021-00598-z
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