PubMed · 10246911
The first of a two-part article dealing with an effective employee separation process and its maximization as a management tool through interview feedback.
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R E Yurk. Employee separation.. https://pubmed.ncbi.nlm.nih.gov/10246911/
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The importance of patient involvement in medical decision making is indisputable. Yet, decision making concerning medical treatment options is a difficult task for most patients. In order to study decision-making processes in health care, O'Connor developed the decisional conflict scale (DCS). The DCS assesses the level of 'decisional conflict' that patients experience while making health care decisions, and encompasses the following three subscales: (1) uncertainty about choosing among alternatives; (2) factors contributing to uncertainty; (3) perceived effectiveness of the decision. The aim of the present study is to investigate the reliability and validity of the Dutch version of the DCS. A written version of the DCS was administered in two samples of Dutch cancer patients. One sample consisted of cancer patients faced with the decision whether or not to undergo palliative chemotherapy (N=29). The other sample included women with early stage breast cancer who had to choose between mastectomy or lumpectomy followed by radiation therapy (N=141). The response rates were 76% and 91%, respectively. The reliability coefficients of the three subscales were 0.52, 0.80, 0.84, and 0.74, 0.83, 0.83 in the two samples, respectively. Construct validity was partly supported. Criterion validity was substantiated. In evaluating the factorial validity, it was found that the original three-factor model had to be rejected (chi(2)(87)=293, root mean square error of approximation (RMSEA)=0.137). A subsequent exploratory factor analysis suggested an alternative four-factor model. The psychometric properties of the DCS were partly confirmed in Dutch cancer patients. Improved 'wording' of certain items, e.g. to avoid double negatives, could further increase the factorial validity of the DCS. Then, this scale may be a valuable tool for studies that address the quality of medical decision making.
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