Predicting worries about health after breast cancer surgery
Abstract
Given the widespread worries about future health in women with breast cancer, it is important to understand the predictors of such fear so that possible avenues for intervention can be formulated. In this longitudinal study of 44 women who had undergone breast cancer surgery, we look at demographic variables, cancer and treatment related symptoms, and denial coping measured post-surgery and their ability to predict future health fears at 6-weeks and 12-weeks post-surgery. At both follow-up periods, around 1 in 5 women had strong worries about their future health, and post-surgery future health fears significantly predicted future health fears. In a hierarchical multiple regression, controlling for post-surgery health fears, future health fears at both follow-up periods were predicted only by denial coping. Cross-lag analyses suggested that these relationships were causal. Findings suggest that denial coping is a powerful predictor of future health fears, with this relationship growing stronger over time. Future research should investigate which interventions can decrease denial, and whether this then decreases health fears in the aftermath of breast cancer surgery.
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Low adherence can moderate intervention outcomes, with longer exposure to an intervention yielding greater benefits.
“Low adherence has clear implications for research and clinical practice, as it can: (i) skew interpretations of efficacy if not clearly measured and reported, and (ii) moderate intervention outcomes, with longer exposure to an intervention yielding greater benefits [20, 23-26].”
From Uptake and adherence to an online intervention for cancer-related distress: older age is not a barrier to adherence but may be a barrier to uptake (2017) · cites this paper as [24]
Low adherence can skew interpretations of efficacy if it is not clearly measured and reported.
“Low adherence has clear implications for research and clinical practice, as it can: (i) skew interpretations of efficacy if not clearly measured and reported, and (ii) moderate intervention outcomes, with longer exposure to an intervention yielding greater benefits [20, 23-26].”
From Uptake and adherence to an online intervention for cancer-related distress: older age is not a barrier to adherence but may be a barrier to uptake (2017) · cites this paper as [24]
Control group membership has been reported as a predictor of adherence of online interventions.
“Control group membership has been reported as a predictor of adherence of online interventions [24]”
From Uptake and adherence to an online intervention for cancer-related distress: older age is not a barrier to adherence but may be a barrier to uptake (2017) · cites this paper as [24]
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Self-citation
- Authors
- Wade, T. D., Nehmy, T., & Koczwara, B.
- Affiliations
- Flinders University (AU)
- Flinders Medical Centre (AU)
- Corresponding author
- Wade, Tracey D.
- Venue
- Psycho-Oncology
- Publisher
- Wiley
- Published
- 2005
- Volume
- 14
- Issue
- 6
- Pages
- 503-509
- ISSN
- 1057-9249 (ISSN-L)
- 1099-1611
- OpenAlex
- W1982964729
- Cited by
- 46
- References
- 27
- Citations by year
- 2022: 1 · 2021: 4 · 2019: 1 · 2018: 2 · 2017: 3 · 2016: 1 · 2015: 4 · 2014: 2 · 2013: 2 · 2012: 7
- FWCI
- 0.48
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psycho-Oncology (publishedVersion)
- PubMed (publishedVersion)
- Flinders Academic Commons (Flinders University) (submittedVersion)
- Topics
- Health Sciences › Medicine › Oncology › Cancer survivorship and care
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Women's cancer prevention and management
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Childhood Cancer Survivors' Quality of Life
- Keywords
- breast cancer surgery, denial coping, breast cancer survivors, treatment-related symptoms
- MeSH terms
- Adult, Aged, Aged, 80 and over, Anxiety, Breast Neoplasms, Fear, Female, Forecasting, Health Status, Humans, Longitudinal Studies, Middle Aged, Prognosis, Regression Analysis
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