OBJECTIVES: Guidelines advocate goal setting for promoting lifestyle changes in cardiovascular disease (CVD) patients. This study investigates 1) preferences in health and life goal domains in CVD patients, 2) the impact of linking life goals to health goals on intention-to-change-lifestyle and explores 3) socio-demographic and health-related variables influencing intention-to-change-lifestyle. DESIGN: Online experimental study. METHODS: Patients (N = 629, mean age 66.6; 39% female) were randomized to health-goal-group (HG) or life-and-health-goal-group (LHG). HG set a health goal, and LHG first established a life goal and then set a supporting health goal. Directly after goal setting, the primary outcome, intention-to-change-lifestyle, was measured and analysed using logistic regression (high: 9-10 vs. lower: ≤8.5), as were the secondary outcomes. RESULTS: Exercise goals were most frequently selected in LHG (66.0%) and HG (66.9%). Preference for selecting stress management was significantly higher in LHG (17.3%) than HG (9.3%), χ2(1) = 8.85, p = .003; OR = 2.05, 95%CI [1.27-3.30]. The direct effect of goal-setting condition on intention-to-change-lifestyle was non-significant (OR = .98, 95%CI [.71-1.34], p = .88). In exploratory analyses, lower- and medium-educated patients showed significantly higher intention when life and health goals were linked (OR = 2.55, 95%CI [1.03-6.27], p = .04, and OR = 2.47, 95%CI [1.15-5.30], p = .02, respectively). Perceived meaning in life was positively associated with intention. CONCLUSIONS: No main effect of goal-setting condition on intention-to-change-lifestyle was found. Linking life goals to health goals increased preference for stress management and, in exploratory analyses, was associated with higher intention-to-change-lifestyle among lower- and medium-educated patients. Findings emphasize the relevance of personalized, value-based goal setting within cardiac rehabilitation.

Objective
Communicating risk information and offering lifestyle advice are important goals in cardiac rehabilitation. However, the most effective way and the most effective source to communicate this information are not yet known. Therefore, we examined the effect of source (cardiologist, physiotherapist) and framing (gain, loss) of brief lifestyle advice on patients’ intention-to-change-lifestyle.

Methods
In an online experimental study, 636 cardiac patients (40% female, 67 (10) yrs.) were randomly assigned to one of four textual vignettes. Effect of source and framing on intention-to-change-lifestyle (assessed using a 5-point Likert scale) was analysed using analysis of covariance (ANCOVA).

Results
Patients expressed positive intention-to-change-lifestyle after receiving advice from the cardiologist (M = 4.1) and physiotherapist (M = 3.9). However, patients showed significantly higher intention-to-change-lifestyle after receiving advice from the cardiologist (0.58 [0.54–0.61]) when compared with the physiotherapist (0.52 [0.48–0.56]), (F[1,609] = 7.06, P = 0.01). Gain-framed and loss-framed advice appeared equally effective. However, communicating risks (loss) was remembered by only 9% of patients, whereas 89% remembered benefits (gain).

Conclusions
Our study shows the value of cardiologists and physiotherapists communicating brief lifestyle advice, as cardiac patients expressed positive intention for lifestyle change after receiving advice, irrespective of framing. Lifestyle advice should include benefits due to better recall.

Background: Lifestyle support is essential in preventing and treating cardiovascular diseases (CVD), and eHealth may be an easy and affordable solution to provide this support. However, CVD patients vary in their ability and interest to use eHealth. This study investigates demographic characteristics determining CVD patients' online and offline lifestyle support preferences. Methods: We used a cross-sectional study design. 659 CVD patients (Harteraad panel) completed our questionnaire. We assessed demographic characteristics and preferred lifestyle support type (coach, eHealth, family/friends, self-supportive). Results: Respondents mostly preferred being self-supportive (n = 179, 27.2%), and a coach in a group or individually (n = 145, 22.0%; n = 139, 21.1%). An app/internet to work independently (n = 89, 13.5%) or being in touch with other CVD patients (n = 44, 6.7%) was least preferred. Men were more likely to prefer being supported by family/friends (p = .016) or self-supportive (p < .001), while women preferred a coach individually or via an app/internet (p < .001). Older patients mostly preferred self-support (p = .001). Patients with low social support were more likely to prefer being coached individually (p < .001), but not support from family/friends (p = .002). Conclusion: Men and older patients are more interested in being self-supportive, and patients with lower levels of social support could need extra support outside their social network. eHealth could provide a solution, but attention should be paid to spike interest for digital interventions among certain groups.