The decision evaluation scales

https://doi.org/10.1016/j.pec.2004.07.010Get rights and content

Abstract

There are several instruments to assess how patients evaluate their medical treatment choice. These are used to evaluate decision aids. Our objective is to investigate which psychological factors play a role when patients evaluate their medical treatment choices. A pool of 36 items was constructed, covering concepts such as uncertainty about and satisfaction with the decision, informed choice, effective decision making, responsibility for the decision, perceived riskiness of the choice, and social support regarding the decision. This pool was presented to patients at high risk for breast and ovarian cancer, awaiting a genetic test result, and facing the choice between prophylactic surgery or screening. Additional measures were assessed for validation purposes. Factor and Rasch analyses were used for factor and item selection. Construct validity of emerging scales was assessed by relating them with the additional measures. Three factors summarised the psychological factors concerning decision evaluation: Satisfaction–Uncertainty, Informed Choice, and Decision Control. Reliabilities (Cronbach's α) of the three scales were 0.79, 0.85, and 0.75, respectively. Construct validity hypotheses were confirmed. The first two scales were similar to previously developed scales. Of these three scales, the Decision Control scale correlated most strongly with the well-being measures, was associated with partner's agreement and physician's preferences as perceived by patients, and with a negative emotional reaction to the information material. In conclusion, the Decision Control scale is a new scale to evaluate decision aids, and it appears to be rooted in health psychological theories.

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

References (30)

  • N. Koedoot et al.

    The decisional conflict scale: further validation in two samples of Dutch oncology patients

    Patient Educ. Couns.

    (2001)
  • C.C. Kan et al.

    Latent trait standardization of the benzodiazepine dependence self–report questionnaire using the Rasch Scaling Model

    Compr. Psychiatry

    (2001)
  • A.M. O’Connor et al.

    Decision aids for people facing health treatment or screening decisions (Cochrane Review)

    The Cochrane Library, Issue 4

    (2003)
  • A.M. O’Connor et al.

    Decision aids for patients facing health treatment or screening decisions: systematic review

    Br. Med. J.

    (1999)
  • S. Molenaar et al.

    Feasibility and effects of decision aids

    Med. Decis. Making

    (2000)
  • F. Sainfort et al.

    Measuring post-decision satisfaction

    Med. Decis. Making

    (2000)
  • P.J. Hollen

    Psychometric properties of 2 instruments to measure quality decision–making

    Res. Nurs. Health

    (1994)
  • I.L. Janis et al.

    Decision making: a psychological analysis of conflict, choice and commitment

    (1977)
  • S.M. Miller et al.

    Interacting effects of information and coping style in adapting to gynecologic stress: should the doctor tell all

    J. Personal. Social Psychol.

    (1983)
  • P.F. Pierce

    Deciding on breast cancer treatment: a description of decision behavior

    Nurs. Res.

    (1993)
  • A.M. O’Connor

    Validation of decision conflict scale

    Med. Decis. Making

    (1995)
  • I. Unic et al.

    Prophylactic mastectomy or screening in women suspected to have the BRCA1/2-mutation: a prospective pilot study of women's treatment choices and medical and decision-analytic recommendations

    Med. Decis. Making

    (2000)
  • M. Holmes-Rovner et al.

    Patient satisfaction with health care decisions: the Satisfaction with Decision scale

    Med. Decis. Making

    (1996)
  • M.J. Barry et al.

    A randomized trial of a multimedia shared decision-making program for men facing a treatment decision for benign prostatic hyperplasia

    Disease Manage. Clin. Outcomes

    (1997)
  • H. Bunn et al.

    Validation of client decision-making instruments in the context of psychiatry

    Can. J. Nurs. Res.

    (1996)
  • Cited by (47)

    • A novel patient decision aid for aftercare in breast cancer patients: A promising tool to reduce costs by individualizing aftercare

      2018, Breast
      Citation Excerpt :

      Therefore, we developed a PtDA for breast cancer patients to support them in making decisions about their personal aftercare trajectory, combining both analytical and intuitive preference identification exercises. The aim of the current study was to test the PtDA's effect on patient-perceived SDM, patient decision evaluation (choice satisfaction-uncertainty, choice information and choice control) [19], aftercare choice and hospital costs in a pilot test with a control group. Based on previous research [6–9], it was expected that using the PtDA during a consultation would increase consultation time but lower hospital care costs, due to a proportion of patients opting for less intensive aftercare.

    • Patients’ perception of their involvement in shared treatment decision making: Key factors in the treatment of inflammatory bowel disease

      2018, Patient Education and Counseling
      Citation Excerpt :

      iv) The patients’ anxiety level was measured using one item pertaining to the level of anxiety at the end of the appointment to discuss test results and treatment selection with the IBD specialist. This item was also consistent with current literature on this subject [30,39]. Likert scales were used in which respondents indicated their agreement or disagreement with a given statement [40].

    View all citing articles on Scopus
    View full text