In the formal experiment, a total of 421 valid datasets were collected. The overall Cronbach’s α coefficient for the entire scale good internal consistency, with a value of 0.766. The Kaiser-Meyer-Olkin (KMO) measure for the total scale was 0.735, further validating the quality of the questionnaire. Among the 421 patients with heart failure who participated in this study, 230 (54.6%) were male, 165 (39.2%) were aged 70–79 years, 300 (71.3%) had primary school education and below, 230 (54.6%) were retired, 217 (51.5%) had a BMI of 20–24 kg/m2, 265 (62.9%) had suffered from heart failure for more than 18 months, 174 (41.3%) had chronic heart failure, and 236 (56.1%) were classified as NYHA Class 3. The median [interquartile range] scores for knowledge, attitudes, and practices were 12.00 [10.00, 13.00] (possible range: 1–18), 20.00 [19.00, 21.00] (possible range: 5–25), and 16.00 [15.00, 17.00] (possible range: 5–22), respectively. Significant differences in knowledge scores were observed among patients with different age (P < 0.001), education (P = 0.001), work status (P = 0.001), BMI (P = 0.007), and current heart failure symptom pattern (P < 0.001). Significant differences in attitude scores were also identified among patients with different age (P = 0.002), diabetes status (P = 0.011), and COPD status (P = 0.001). Differences in practice scores were more likely to be found among patients with different age (P < 0.001), education (P = 0.003), work status (P < 0.001), monthly household income (P < 0.001), BMI (P = 0.001), and COPD status (P = 0.005) (as shown in Table 1).
The distribution of knowledge scores indicated that the majority of patients mistakenly believed that physical activity should be avoided (K3), with 68.4%. The question receiving the highest number of “Unsure” responses was “The only dietary restriction for heart failure patients is to avoid adding salt (40.6%)” (K2). Only a small percentage of individuals are aware of the importance of regularly checking their weight, with 20.7% (K6). However, over half correctly identified waking up at night feeling out of breath as a sign of increased heart failure (59.4%), as shown in Table 2.
Responses to the attitude dimension showed that 60.6% strongly agreed that taking medication correctly and avoiding overdosing is necessary to prevent aggravation of heart failure (A5). In terms of preventing heart failure recurrence, 60.3% were willing to adjust their diet (A2). Regarding the impact of medical infrastructure and care quality of the outpatient clinic on their motivation for treatment (A4), 38.2% said it does, 22.8% were neutral, while 23% said it does not (as shown in Table 3).
When it comes to related practices, 54.6% always took their medication on time (P4), 39.7% often sought treatment proactively after sensing heart failure symptoms (P1), and 48.2% agreed to follow up with their doctors regularly after discharge from the hospital (P2). However, 33.7% seldom and 38.2% hardly engaged in appropriate exercise to improve cardiorespiratory fitness to prevent heart failure recurrence (P3). Additionally, only 5.7% consumed more than 2000 mL of water per day (P6) (as shown in Table 4).
Correlation analyses showed significant positive correlations between knowledge and attitude (r = 0.183, P < 0.001) as well as between knowledge and practice (r = 0.169, P < 0.001). There was also a correlation between attitude and practice (r = 0.245, P < 0.001) (as shown in Table 5).
Using 60% of the total practical score as the cut-off value for grouping patients, 253 (60.1%) had a score less than the cut-off value. Multivariate logistic regression showed that attitude score (OR = 1.238, 95% CI: [1.099, 1.396], P < 0.001), living in a suburb (OR = 2.524, 95% CI: [1.282, 4.969], P = 0.007), having a monthly household income of more than 5000 RMB (OR = 3.539, 95% CI: [1.517, 8.257], P = 0.003), having a BMI of less than 20 kg/m2 (OR = 2.155, 95% CI: [1.080, 4.299], P = 0.029), having a BMI of 20–24 kg/m2 (OR = 2.387, 95% CI: [1.112, 5.122], P = 0.026), and having a BMI of 25–29 kg/m2 (OR = 4.063, 95% CI: [1.359, 12.146], P = 0.012) were independently associated with proactive practice (as shown in Table 6).
The fit indices of the SEM model indicated a good model fit (as shown in Fig. 1). Path analysis (as shown in Table S1 and Fig. 1) and analysis of direct and indirect effects (as shown in Table S2) revealed that age (β = -0.146, P = 0.004), education (β = 0.134, P = 0.009), employment (β = -0.161, P = 0.001), and BMI (β = 0.118, P = 0.014) directly influenced knowledge. Knowledge (β = 0.192, P < 0.001), age (β = -0.124, P = 0.010), and COPD (β = -0.120, P = 0.011) directly impacted attitude, while age (β = -0.028, P = 0.019), education (β = 0.026, P = 0.029), employment (β = -0.031, P = 0.010), and BMI (β = 0.023, P = 0.037) indirectly affected attitude. Attitude (β = 0.218, P < 0.001), employment (β = -0.165, P = 0.003), BMI (β = 0.093, P = 0.045), and income (β = 0.290, P < 0.001) directly influenced practice, while knowledge (β = 0.042, P = 0.002), age (β = -0.044, P = 0.003), and COPD (β = -0.026, P = 0.025) indirectly affected practice.
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