European journal of cardiovascular nursing最新文献

Aims: Improved dietary habits are important for successful secondary prevention after myocardial infarction (MI), with counselling and support on healthy dietary habits constituting a cornerstone of cardiac rehabilitation (CR). However, there is limited knowledge on how to optimize CR organization to motivate patients to adopt healthy dietary habits. We aimed to explore associations between CR programme structure, processes, and self-reported dietary habits 1 year post-MI.

Methods and results: Organizational data from 73 Swedish CR centres and patient-level data from 5248 CR patients were analysed using orthogonal partial least squares discriminant analysis to identify predictors for healthy dietary habits. Variables of importance for the projection (VIP) values exceeding 0.80 were considered meaningful. Key predictors included the CR centre having a medical director [VIP (95% confidence interval)] [1.86 (1.1-2.62)], high self-reported team spirit [1.63 (1.29-1.97)], nurses have formal training in counselling methods [1.20 (0.75-1.65)], providing discharge information on risk factors [2.23 (1.82-2.64)] and lifestyle [1.81 (1.31-2.31)], time dedicated to patient interaction during follow-up [1.60 (0.80-2.40)], and centres aiming for patients to have the same nurse throughout follow-up [1.54 (1.17-1.91)]. The more positive predictors a CR centre reported to follow, the further improvement in patient-level dietary habits, were analysed by multivariable regression analysis [odds ratio for each additional positive predictor reported 1.03 (1.02-1.05), P < 0.001].

Conclusion: Several variables related to CR structure and processes were identified as predictors for patients reporting healthier dietary habits. These findings offer guidance for CR centres in resource allocation and optimizing patient benefits of CR attendance.

Aims: This study aimed to determine the effect of a multi-component mHealth intervention on patient activation and examine its predictors among older adults at risk of cardiovascular disease (CVD).

Methods and results: This pilot randomized controlled trial compared two groups: Get FIT (control), who received healthy lifestyle counselling from a licensed health coach, a mHealth app (MyFitnessPal) with push alerts, and an activity tracker, and Get FIT + (intervention), who received the same interventions and had personalized text messages with 3- and 6-month follow-up periods. Patient activation was measured using the 13-item Patient Activation Measure; higher scores indicated better activation. Linear mixed-effects models were used to investigate between-group changes in outcomes across time. The participants' (n = 54) mean age was 65.4 ± 6.0 years; 61% were female; and 61% were married. Baseline characteristics were comparable between groups. Significant improvements in mean patient activation scores were observed in the Get FIT + group at 3 months [mean 3.53 points, 95% confidence interval (CI) 0.11, 6.96; P = 0.043] and 6 months (mean 4.37 points, 95% CI 0.91, 7.83; P = 0.014), whereas improvements in the Get FIT group were non-significant. Adjusting for age, gender, education, employment, marital status, social support, smartphone confidence, and self-perceived health, we found that only social support was associated with higher patient activation overall (B = 5.14, 95% CI 1.00, 9.27; P = 0.015).

Conclusion: The findings indicate that personalized text messaging can improve the self-care of older adults at risk of CVD. Findings also emphasize the importance of social support in the success of mHealth interventions for older adults.

Registration: The study is registered in ClinicalTrials.gov (NCT03720327).

Aims: Patient activation (PA) is crucial for effective self-management of people with heart failure (HF). Clarifying factors associated with PA might be important to develop interventions to promote PA. This study aimed to explore context factors associated with PA in people with HF.

Methods and results: Two hundred and sixty-eight patients were enrolled in a cross-sectional study (median age = 65 years). We surveyed variables based on context factors of the individual and family self-management theory, including demographic and disease factors, quality of chronic care, family function, and depression. Correlation analysis was conducted for data analysis, and path analysis was used to verify our hypothesis model about context factors and PA. The median PA score was 51.10. Path analysis showed that age, educational level, living arrangement, device therapy, quality of chronic care, family function, and depression were directly or indirectly related to PA. The quality of chronic care mediated the associations between device therapy and educational level and PA. Age, educational level, living arrangement, and quality of chronic care affected family function and then affected activation. Depression mediated the relationships between the quality of chronic care, educational level, family function, and PA.

Conclusion: This study increased the understanding of factors associated with PA in the HF population. When assessing PA in people with HF, those who are older, have a low educational level, and living alone need more attention from healthcare professionals. Interventions focusing on improving the quality of chronic care, family function, and depression might help activate people to practice self-management.

Aims: In patients with aortic dissection (AD) after surgical repair, especially those with hypertension, better management of blood pressure is associated with better health outcomes. The aim of this study is to identify hypertension self-management trajectory patterns and associated factors among Chinese aortic dissection patients after surgical repair to assist in developing tailored behavioural interventions for this population.

Methods and results: 178 patients with aortic dissection who underwent surgical repair were followed for 3 months. Data on hypertension self-management, hypertension knowledge, self-efficacy, and social support were collected before discharge and at 1 and 3 months after discharge. Sociodemographic and clinical data were also collected. A latent class growth model and generalized estimating equations were used to explore hypertension self-management trajectory patterns and factors associated with each pattern. The participants' average age was 57.95 (± 11.27) years. Two hypertension self-management trajectory patterns were identified: 'rapid ascent then suppressed growth' (93.4%) and 'continuously slow ascent' (6.6%). For the 'rapid ascent then suppressed growth' pattern, age, educational background, type of health insurance, family monthly income, self-efficacy, and social support were associated with this pattern (P < 0.05).

Conclusion: Healthcare providers may prioritize hypertension self-management for patients who are younger, have lower educational levels, have resident or employee medical insurance and have a family monthly income between 5001 and 10 000 yuan. Self-efficacy and social support might serve as targets for future intervention to improve hypertension self-management.

Registration: ChiCTR2100050542.

Aims: A single-blinded, multicentred randomized controlled trial (RCT) was employed to examine the effectiveness of a 3-month telephone follow-up, a telephone follow-up with education before discharge, or education only before discharge on the heart failure (HF) knowledge, HF self-care management, and health-related quality of life (HR-QoL) in patients with HF by a nurse specialist.

Methods and results: This is a multicentre RCT with three different intervention groups (IGs) and one control group. Participants in the first IG received education on HF self-management principles before discharge. The second IGs were enrolled to a 3-month telephone follow-up educational programme in addition to the pre-discharge educational session. The third IG received the telephone follow-up intervention only for 3 months. A total of 357 patients with HF were enrolled to the study of whom 262 participants completed the intervention. Outcome measures included HF-related QoL, HF self-care, and HF-related knowledge. Intervention effects were analysed using the Cohen d (rm) coefficient for repeated measurements and ANCOVA. There was a significant improvement in the physical dimension of the HR-QoL (F = 2.7, df = 3, P = 0.046) between the control group and in-person education group. In HF-related self-care, the telephone component alone or in combination with in-person education led to greater improvement than the control group (F = 3, df = 3, P = 0.034). Self-care practices were improved in the education and telephone arms as compared to the control group (P = 0.002).

Conclusion: Education and telephone support on self-care management may improve the physical dimension of HR-QoL.

Registration: ClinicalTrials.gov: NCT01905176.

Aims: To investigate whether out-of-hospital cardiac arrest (OHCA) survivors had lower levels of self-reported physical activity compared to a non-cardiac arrest control group with myocardial infarction (MI), and to explore if symptoms of anxiety, depression, kinesiophobia (fear of movement) and fatigue were associated with a low level of physical activity.

Methods: Predefined case-control sub-study within the international Targeted Hypothermia versus Targeted Normothermia after Out-of-Hospital Cardiac Arrest (TTM2) trial. OHCA survivors at 8 of 61 TTM2 sites in Sweden, Denmark and the United Kingdom were invited. Participants were matched 1:1 to MI controls. Both OHCA survivors and MI controls answered two questions on self-reported physical activity, categorized as a low, moderate, or high level of physical activity, and questionnaires on anxiety and depression symptoms, kinesiophobia, and fatigue 7 months after the cardiac event.

Results: Overall, 106 of 184 (58%) eligible OHCA survivors were included and matched to 91 MI controls. In total, 25% of OHCA survivors and 20% of MI controls reported a low level of physical activity, with no significant difference (p=0.13). Symptoms of kinesiophobia and fatigue were significantly associated with a low level of physical activity in both groups. OHCA survivors had significantly more kinesiophobia compared to MI controls (18% versus 9%, p=0.04), while levels of anxiety and depression symptoms and fatigue were similar.

Conclusion: OHCA survivors had similar levels of physical activity compared to matched MI controls. High level of kinesiophobia and fatigue were associated with a low level of physical activity in both groups.