Influence of Psychosocial Distress Predictors on Quality of Life in Women With Breast Cancer in Nairobi County
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Date
2024-08Author
MURIITHI, ANASTASIA WANJIRU
Type
ThesisLanguage
enMetadata
Show full item recordAbstract
Breast cancer diagnosis and treatment affect a woman's physical, emotional, social, and sexual
wellbeing, making quality of life a crucial treatment outcome. The aim of this study was to
uncover some predictors of psychosocial distress and their influence on breast cancer patients’
quality of life. To achieve this purpose, the study focused on establishing the prevalence of
psychological distress, the influence of socio-demographic variables, treatment-related side
effects, body image, and the link between social support and quality of life in Kenyan women
with breast cancer. The Stress Process Model (SPM), the Social Cognitive Theory of Health
Promotion (SCTHP), and the Fundamental Cause Theory (FCT) served as the study's three
guiding theories. The study design was sequential exploratory mixed-methods. Data were
collected from two cancer hospitals in Nairobi County. With phenomenology explaining the
breast cancer patients lived experiences, qualitative data was gathered through interview
schedules with 20 patients, two 6-member focus group discussions, and 8 healthcare
practitioners. A questionnaire was used to gather quantitative data from 256 patients from two
hospitals, revealing a median age of 47 years. Thematic analysis found that breast cancer
patients experienced both losses and unexpected gains. Financial hardship hit hardest. The
effects of breast loss were enduring; the financial model had gaps; positive social support was
plentiful, but there was also negative social support. Descriptive statistics found that
psychosocial distress was prevalent and severe, with 63% of participants reporting severe
distress and 23% reporting clinically significant distress. Additionally, 91% of participants
reported financial distress, with 36% reporting clinical depression and 40% reporting anxiety.
Of the individuals, 75% had comorbid clinical-severe depression and anxiety. In order to
ascertain the factors that predicted psychosocial distress, a multinomial logistic regression
analysis was conducted. Factors affecting outcomes included income (p<0.05, OR 5.50), early
diagnosis (p<0.05, OR 0.31), severe treatment side effects (p<0.05, OR 2.89), poor body image
(p<0.05, OR 1.83), and decreased sexual function (p<0.05, OR 3.83). Social support moderated
psychosocial distress (p<0.05, OR 0.69). The results of the multivariate logistic regression
analysis, which investigated the influence of psychosocial distress predictors on quality of life,
indicated statistically significant relationships. The presence of some income (p<0.05, OR
1.08), early diagnosis (p<0.05, OR 2.03), mild treatment side effects (p<0.05, OR 1.88),
negative body image (p<0.05, OR 0.915), diminished sexual function (p<0.05, OR 0.288), and
adequate social support (p<0.05, OR 1.65). Social support moderated the influence of distress
on quality of life (p<0.05, OR 1.57). All hypothesised psychosocial distress predicators
correlated with quality of life. However, social support ameliorated the harmful effects of
distress on participants' quality of life. The main unattended issues in treatment were body
image and sexual function. Distress and emotional disorders such as anxiety and depression
were either disregarded or not addressed effectively. Financial distress stood out; this calls for
a reassessment of the SHIF cancer financing policy to close gaps. Furthermore, non-disease
factors have an influence on the quality of life for women with breast cancer. As a result, it is
critical to incorporate distress screening into cancer care and to adopt a multidisciplinary
approach to managing both the disease and the psychosocial challenges that breast cancer
patients face. The incorporation of psychotherapy and social interventions into breast cancer
care is necessary to achieve the fundamental treatment goal of enhancing quality of life
Publisher
KeMU