Open Access
FATIGUE AND ANXIETY IN BREAST CANCER: THE RELATIONSHIP WITH INTERPRETATION BIAS
Author(s) -
Nidhi Vedd
Publication year - 2021
Publication title -
psychological applications and trends
Language(s) - English
Resource type - Conference proceedings
ISSN - 2184-3414
DOI - 10.36315/2021inpact018
Subject(s) - breast cancer , anxiety , confounding , hospital anxiety and depression scale , clinical psychology , population , medicine , psychology , cancer , psychiatry , environmental health
"Background: Research has highlighted both fatigue and anxiety to be two of the most debilitating symptoms of breast cancer that prevail for years into its survivorship, and suggests that these symptoms influence how people interpret information. Harbouring negative interpretation biases also helps to maintain self-destructive beliefs resulting in increased severity of symptoms and disability in those already affected by the illness. This study is the first utilizing an experimental measure of assessing interpretation bias in a population of breast cancer to investigate the contribution of fatigue and anxiety. Method: A cross-sectional study design was used. 53 breast cancer survivors and 62 female healthy controls were recruited via opportunistic sampling. Participants completed an online questionnaire assessing basic demographics, fatigue via the Chalder Fatigue Questionnaire (CFQ) and anxiety using the Hospital Anxiety and Depression Scale (HADS). Following this, an in-person testing session assessed interpretation bias (IB) using a computerised task. Results: Independent sample t-tests found a non-significant result in the comparison of IB indices between populations (t(112.60) =.28, p=.783; d=.05). Significant differences were observed in mean fatigue and anxiety scores in the breast cancer population compared to the healthy controls. Pearson correlation identified a statistically significant positive correlation between CFQ scores and negative interpretation bias (r=.34, n=53, p=.013), however not for anxiety. Hierarchical multiple regression was calculated to predict negative interpretation biases based on potential confounding variables (age, relationship status and level of education), CFQ, HADS anxiety scores (separately). All four regression models were non-significant. The only significant predictor of negative interpretation bias was fatigue (ß =.39, t(53)=2.71, p=.009). Conclusion: The identified significant correlation between fatigue and negative interpretation bias in this study corroborates findings from existing literature. However other results proved inconsistent with the vast body of research suggesting that breast cancer survivors would make more negative interpretations of ambiguous stimuli on an IB task compared to healthy controls. These results highlight the potential for future research investigating strategies of inherent self-adaptive and coping mechanisms that are or could be adopted by these participants to overcome this cognitive bias."