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Difficulties with diagnosis and aggressive, long-term treatment may result in lower quality of life (QOL), including high levels of anxiety, depression, and uncertainty, greater symptom distress, and lower overall QOL among women with avarian cancer. The purpose of this study was to describe demographic, clinical, and other risk factors associated with compromised QOL among women who have undergone surgery for avarian malignancies.
Subjects were recruited to participate in a clinical trial that tested a specialized nursing intervention addressing psychological and physical care among women post-surgical for avarian cancer. QOL was measured using five standardized self-report measures: the State-Trait Anxiety Scale (SAS), the Center for Epidemiological Studies Depression Scale (CES-D), the Mishel Uncertainty in Illness Scale (MUIS), the Symptom Distress Scale (SDS), and the Short-Form Health Survey (SF-12). Baseline data were collected while women were hospitalized following surgery.
The sample (n=145) included women with avarian cancer (58%) and other cancers metastasized to the avaries and abdomen (42%). Mean scores on the measures were consistent with or higher than previously reported means for similar populations. Women reporting the lowest QOL were more likely to be younger, more educated, and have early stage disease.
Significance of results:
Women who have undergone surgery for ovarian malignancies have psychological needs that are often considered secondary to physical needs. Interventions should include routine screening for distress and referral to appropriate psychological and social services, thereby facilitating quality cancer care.
The actual Content Analysis of Verbatim Explanations (CAVE) technique has two steps: identifying and extracting causal explanations in verbatim material; and then rating these explanations along 7-point scales according to their internality, stability, and globality. We will describe these steps in order.
IDENTIFYING AND EXTRACTING CAUSAL EXPLANATIONS
Four or more events with explanations are ideally required to generate a valid style. Multiple events are the only way that a researcher can estimate a cross-situational style. Also, multiple events allow explanatory style to be more reliably measured. Peterson, Villanova, and Raps (1985) compared studies that disconfirm the reformulated learned helplessness model with those that support it, finding that the supporting studies had more attributions per subject than the disconfirming studies. Multiple events apparently minimize the effects of the reality of the situation, allowing the individual's habitual style to emerge.
In our research, we usually find bad events with explanations to be more abundant in verbatim material than good events with explanations. What this means is that researchers specifically interested in how people explain good events will have to search more diligently for suitable material for content analysis. When individuals describe events, good or bad, they often end up explaining them, if allowed or encouraged to elaborate their descriptions.
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