The decision evaluation scales
Introduction
An increasing number of studies evaluate the effects of involving patients in the medical decision making process [1]. Patients may be involved, for instance through the provision of information, through values clarification, or by helping patients to formulate their questions. A wide array of outcomes has been used in such evaluations including treatment choice and strength of treatment preference, quality of life outcomes, psychological outcomes such as anxiety, depression, and decisional conflict, satisfaction with care, cognitive outcomes relating to information needs, knowledge and risk perception, and outcomes such as use of care, and work absenteeism [2], [3].
This study focusses on how patients evaluate the treatment decision itself. In general, these decision related outcomes are meant to assess how patients evaluate the effects of interventions designed to increase patient involvement in decision making, and not to distinguish between patients.
In the study of treatment decisions in the context of decision support interventions, two approaches have been followed: (1) assess the patient's evaluation of the decision making processs [4]; and (2) assess the patient's evaluation of the decision. The first approach deals primarily with the quality of the information processing. Improving information processing is an important goal of decision support. For example, Hollen [5] developed a taxonomy of decision styles and decision quality inventories building on the framework developed by Janis and Mann [6]. Related approaches can be found in the coping literature, for instance coping with information [7], and Decision Styles Questionnaire [8]. It has been shown that these concepts can mediate the effectiveness of patient information material.
Our interest, however, is the second approach, i.e. the evaluation of the decision by patients. Such decision related evaluations have been found to be associated with treatment choices [9] or treatment choice intentions [10].
Several scales have been developed: the Decisional Conflict Scale [9], comprising the subscales Uncertainty, and Factors Contributing to Uncertainty; the Effective Decision Making scales; [9] the Satisfaction with Decision scale [11], the Decision Attitude Scale [4], the Satisfaction with decision making process questionnaire [12], the Satisfaction with Decision Made Questionnaire [12], the Decision Self Efficacy Scale [13] the Decision Emotional Control scale [13], and the Decision Regret scale [14]. In general, these scales have shown good internal reliability (Cronbach's α), and test–retest reliability. Evidence supporting construct validity has also been reported.
While a wide array of scales exist, it is unclear to what extent these scales assess different components of decision evaluation. For instance, Decision Uncertainty and Satisfaction with the Decision have generally been found to be strongly correlated [9], [11]; but whether both scales tap into the same construct is not known. Furthermore, some scales (e.g. the Decisional Conflict Scale) do not yield similar factor structures when translated into other languages [15].
Our goal is to uncover the factors underlying the evaluation by patients of treatment decisions. It was not our intention to translate existing scales completely or literally. Additional concepts were considered. These concepts emerged after reviewing the above literature [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], and the decision making, social psychological, health psychological, and coping literatures. The following concepts were identified: (1) affective evaluation including uncertainty and satisfaction with the decision; (2) informed choice; (3) effective decision making; (4) responsibility, blame, control; (5) perceived riskiness; (6) social support and social approval. The last three concepts are not covered by existing scales. Responsibility was added because it may affect treatment compliance. Responsibility may modify feelings of regret, which in turn affects decision making [16]. Avoiding blame for future accidents is also believed to affect decision making [17]. Sense of control is believed to affect health outcomes [18]. Perceived riskiness was included because risk is a major dimension in decision making [19]. Social support was included because of its importance in models for health behavior and stress.
Section snippets
Item construction
The decision items were developed in Dutch by one of us (PFMS). Some of the items were from existing scales, new items were developed for the additional concepts. We considered items from the studies discussed above and a questionnaire kindly provided by Broadstock and Michie [20]. Items were shortened or adapted to get brief unambiguous items. All items were presented to three investigators, of whom two investigated medical decision making from the patients perspective, the third was an expert
Number of participants
At study entrance (T1), 453 women were eligible and 390 (86%) gave informed consent [18]. By T2, 368 were still in the study [21]. Ninety-one women had a BRCA1/2 mutation and were therefore eligible for the second part of the study. Three woman withdrew after the positive genetic test result due to high emotional distress. The follow-up at T4 and T5 was complete in 88 and 87 women, respectively [2], [12].
Psychometric analyses
Of the 368 women at T2, 22 women were discarded as both their breasts were already removed,
Discussion and conclusion
We set out to uncover the dimensions involved in the evaluation of medical decisions from the patient perspective. We uncovered a new concept measured by the Decision Control scale. We confirmed previously uncovered dimensions such as Satisfaction–Uncertainty and Informed Choice.
We discuss first the Decision Control Scale. Control is a central concept in the health psychology literature [18], and thus, in retrospect, the emergence of this concept in the evaluation of medical decisions is not
Acknowledgements
This study was supported by a grant from the Dutch Cancer Society (NKB 98–1585), Amsterdam, the Netherlands. We thank our study participants, and the research assistants Monique Oude Elberink and Ineke Bakker. We thank Nelleke Koedoot, Sjaak Molenaar, and Paul Oosterveld from the department of Medical Psychology, Academic Medical Center, Amsterdam, for their cooperation during the item generation phase. We thank Loes Wiggers from the same department for suggesting the control label for the
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