The Relationship Between Negative Affectivity and Accuracy of Symptom Perception in Patients with Heart Failure

Lee, Kyoung Suk

Purpose:

Delay in seeking care significantly contributes to poor outcomes in heart failure (HF). Accurately perceiving changes in symptoms is the first step for patients to take action in a timely manner to prevent HF exacerbation and readmissions. As negative affectivity, such as depressive symptoms (DS) and anxiety, influences information processing, it can be hypothesized that HF patients with negative affectivity experience difficulty in accurately perceiving symptoms.The purpose of this study was to determine whether DS and trait anxiety were associated with symptom perception in HF patients.

Methods:

A total of 35 stable HF patients (63 years, 31% NYHA III) were asked to rate shortness of breath (SOB) with the modified Borg scale immediately after a 6-minute walk test, which was used to provoke SOB. An experienced nurse rated patients’ SOB with the same scale simultaneously based on observable cues of SOB (e.g., breathing pattern). Patients were categorized into accurate and inaccurate symptom perception groups based on the discrepancy in SOB ratings between the patient and nurse. Univariate logistic regression was used to test whether DS (measured with the Patient Health Questionniare-9) and trait anxiety (measured with the State-Trait Anxiety Inventory) predicted accuracy of symptom perception.

Results:

Of 35 patients 25 (71%) had accurate symptom perception. There was a non-significant tendency that patients with accurate symptom perception had higher scores for DS (6.4 vs. 3.3; p=.11) and trait anxiety (33.2 vs. 28.9; p=.23) than patients with inaccurate symptom perception. DS or trait anxiety did not predict accuracy of symptom perception (p-value= .13 and .19, respectively).

Conclusion:

We did not find a significant relationship between negative affectivity and symptom perception in HF. Further research is needed to identify factors related to symptom perception to improve outcomes in HF with a large sample.