Pellerin, Marc-André MSc; Elwyn, Glyn MB BCh, MSc, PhD; Rousseau, Michel PhD; Stacey, Dawn RN, PhD; Robitaille, Hubert PhD; Légaré, France MD, PhD
Patient-centered care has grown to occupy a central role in health care and now forms the basis for medical education curricula around the world.1 At the crux of patient-centered care is shared decision making (SDM), a process by which health decisions are made jointly by the health professional and the patient, based on the best available evidence and the patient's values and characteristics, yet without discounting the values and convictions of the clinician.2–4 SDM challenges clinicians to find common ground with their patients concerning their health care3 and is particularly relevant in gray-zone situations5 where treatment options have both risks and benefits or where scientific evidence is lacking.5,6
Involving patients in decision making is thought to influence patients' health for the better.7 In addition, a Cochrane systematic review that combined the results of 55 randomized clinical trials of patient decision aids, also known as SDM programs, concluded that SDM increases patients' involvement in decision making, improves their knowledge of the benefits and risks of various treatment options, encourages realistic expectations, and reduces decisional conflict.8 Other studies have found that good communication, enabled by the SDM process, makes patients more satisfied with the care received, motivates patients to adhere to their treatment9 (possibly reducing medication-related hospital admissions in the United States by 33% to 69%10,11), increases patients' confidence in the physician and the health system, fosters a feeling of self-efficacy, facilitates patients' agreement with their doctor, and inspires mutual understanding of the issue at hand.9 Studies have also shown that SDM helps to reduce the number of individuals who choose options that are devoid of benefits12 and increases the number of those who choose options that are beneficial.13 This phenomenon has been associated with a reduction of unjustified variations in medical practices,14 which in turn may foster the sustainability of the health system.15 Finally, SDM benefits care providers in particular ways—for example, by giving them the opportunity to strengthen the therapeutic alliance with their patients and by helping to protect them from possible litigation.16,17
Despite these benefits, physicians seem to apply SDM poorly in consultations. We analyzed the results of 10 studies that had used the Observing Patient Involvement in Decision Making (OPTION) scale—a validated scale that assesses physicians' skill in SDM18—wherein the closer the score for 12 items is to 100%, the better the SDM practices of the physician. We found that the final OPTION scores recorded by these studies ranged from 3% ± 2% to 43% ± 13%,6,18–25 with only one study recording mean scores over 60% (mean 63%, range 42%–78%). This study measured scores after physicians had completed six months of SDM skills training26 and was the only one of the 10 studies to have conducted physician training. These low scores do not align with the fact that a vast majority of patients want to be involved in the decision-making process.7 Meanwhile, no studies have yet used a third-observer instrument to evaluate whether residents in family medicine apply SDM behaviors with regard to primary-care-related decisions.
Despite the benefits associated with patients' involvement in clinical encounters, to the best of our knowledge, family medicine residents are not generally trained in SDM. Residency programs in family medicine across Canada are explicit about training residents in a patient-centered care approach but not necessarily about training them specifically in SDM. In November 2009, the CanMEDS FMU Framework on Undergraduate Competencies From a Family Medicine Perspective included a statement encouraging patients to take as active a role as they are comfortable with in collaborating with the physician and health care team in deciding on a management plan.27 The purpose of our study was therefore to use the OPTION scale to assess family medicine residents' SDM skills in the context of primary care. A secondary purpose was to determine whether the demographic characteristics of participating residents were correlated with their scores. By identifying residents' strengths and weaknesses regarding SDM, we hope to recommend ways to improve family medicine training or develop new interventions to improve professional practices in this regard.
Study design and instrument
Conducted between January 2009 and April 2010, this descriptive study explored the manner in which family medicine residents applied behaviors associated with SDM in their clinical encounters. To evaluate these behaviors, we used the revised OPTION scale.18 This unidimensional scale assesses the magnitude of SDM use during the physician–patient consultation by identifying 12 SDM-specific behaviors that clinicians can adopt to promote patients' active participation in decision making.18 These items are
* drawing attention to an identified problem as one that requires a decision-making process;
* stating that there is more than one way to deal with the identified problem (equipoise);
* assessing the patient's preferred approach to receiving information to assist decision making (e.g., discussion, reading printed material, assessing graphical data, using videotape or other media);
* listing options, which can include the choice of “no action”;
* explaining the pros and cons of options to the patient (taking “no action” is an option);
* exploring the patient's expectations (or ideas) about how the problem(s) is to be managed;
* exploring the patient's concerns (fears) about how the problem(s) is to be managed;
* checking that the patient has understood the information;
* offering the patient explicit opportunities to ask questions during the decision-making process;
* eliciting the patient's preferred level of involvement in decision making;
* indicating the need for a decision-making (or deferring) stage; and
* indicating the need to review the decision (or deferment).
The items are coded on a five-point scale, where “0” indicates the nonperformance of a behavior and “4” indicates the performance of a behavior at high competency.18 We obtained an overall score by adding the scores of each item and standardizing the sum to obtain a value between 0% and 100%, with a high score indicating that the clinician practices numerous behaviors associated with SDM.28 The OPTION scale has been validated in many languages, including English and French.18,29 In English, it showed satisfactory psychometric qualities, with the original study producing a Cronbach alpha of 0.68 for a sample of 21 general practitioners and 186 patients.18 In French, a recent study produced a Cronbach alpha of 0.73 with 41 general practitioners and 128 patients.6 The higher the score, the more reliable the scale, but Nunnaly30 has indicated 0.7 to be an acceptable reliability coefficient, even if lower thresholds (≥0.6) are also sometimes used.31–33
Participants and recruitment procedure
The standard deviation (SD) of OPTION scores recorded in a previous study6 indicates that our large sample of 152 dyads is associated with a precision of ±3% given a 95% confidence interval (CI). In other words, if a similar study were performed 100 times, for 95 of those times the mean OPTION score would fall in the range of –3% to +3% of the mean OPTION score obtained in our study. To recruit residents, we worked with two Canadian academic health centers. The first was an anglophone center based in London, Ontario; the second was a francophone center located in Quebec City, Quebec. To qualify for recruitment, professionals had to be family medicine residents in a community-based clinic or a family medicine teaching unit associated with one of the two centers. The eligibility criteria for patients were age 18 years or older and the ability to give informed consent. We excluded patients who were already part of a dyad, who were closely related to one of the researchers, or who suffered from an acute medical condition requiring immediate care. Neither residents nor patients received financial compensation for their participation.
This study was part of the “EXACKTE2: Exploiting the clinical consultation as a knowledge transfer and exchange environment” research project,34 for which the study protocol was approved by the ethics committees associated with the two academic health centers. The EXACKTE2 study intends to validate a conceptual framework for how patients and physicians influence each other in consultations while practicing SDM. For our current study, we focused only on family medicine residents, using data from the third-observer instrument.
We began our study by introducing family medicine residents to the EXACKTE2 project. After the residents agreed to the terms of the study and signed a consent form, we determined a convenient time to recruit one of their patients. Because our project was interested in unique dyads, we recruited only one patient per resident. We then approached the patients prior to the consultations, presented the project, and secured their consent to participate. Both residents and patients were informed that the confidentiality of the information they provided would be protected. They were told that they could refuse to participate or could withdraw from the study at any time, merely by verbally informing the research team. They were not obliged to give their reasons for withdrawing and would not be subject to any penalty. We then audiotaped the encounters and transcribed them verbatim in preparation for analysis with the OPTION scale. We collected demographic data about participating residents using a sociodemographic questionnaire at the time of the consent.
After reading the coding instructions for the revised OPTION scale,28 the two main coders (H.R., M.A.P.) worked with a coder who had used the tool previously but who was not involved in this study.6 These three coders began by scoring 10 encounters individually. The intraclass correlation (ICC) for their scores was 0.62 (95% CI = 0.26–0.87). The three coders then met to reach a common understanding for the 12 items, especially those items that had earned a lower ICC score, and to add coding cues. The coder who had used the tool previously but who was not involved in this study6 was not involved in further steps. The two main coders then trained two assistant coders. After the training, the two main coders and the two assistant coders individually scored two sets of 20 randomly selected encounters, 10 in English and 10 in French. The ICC scores produced were, respectively, 0.83 (95% CI = 0.71–0.92) and 0.64 (95% CI = 0.44–0.82) for each set of 20 encounters (10 English and 10 French). During this process, the principal investigator of the EXACKTE2 research project (F.L.) helped to establish consensus. We then distributed the remaining verbatim transcriptions randomly among the four coders, who proceeded to rate them all. At the end of this process, no significant differences in scoring between raters were observed (P = .08). Finally, the four coders rescored the second set of dyadic encounters to assess intrarater stability: The ICC scores varied between 0.68 (95% CI = 0.36–0.86) and 0.95 (95% CI = 0.89–0.98). ICC scores above 0.40, 0.60, and 0.80 can be interpreted as indicating fair, moderate, and substantial agreement, respectively.18,35
We calculated descriptive statistics to assess the extent to which residents involved their patients in SDM. We determined means, SDs, minimums, and maximums for each item and for the total OPTION scores. Additionally, we conducted inferential statistical analysis using the data from the sociodemographic questionnaire to explore associations between the application of SDM and selected criteria: age, gender, language, year of residency, degree(s) obtained prior to medical training, and participation in a committee, a work group, or a continuing medical education activity during the prior year. We used the Pearson correlation coefficient to explore the association of OPTION scores with residents' age and the duration of the consultation, and the Student t test to compare mean OPTION scores in light of the sociodemographic variables. Finally, we performed an ANOVA to compare the raters' scores and an ANCOVA to compare scores after adjusting for time. We used the SAS statistical package (SAS OnlineDoc 9.2; SAS Institute Inc., Cary, North Carolina, 2010).
Of the 245 family medicine residents we identified as potential study participants, 212 were considered eligible and 159 agreed to participate, yielding a 75% participation rate among eligible residents. In the end, we successfully formed, recorded, transcribed, and analyzed 152 unique resident–patient dyads (Figure 1). Among the 152 residents who formed part of a dyad, 67 (44%) were in their first year of residency, 60 (40%) were in their second year, and 25 (16%) were in their third year. All third-year residents were from Ontario (Quebec's residency program only lasts two years). A summary of the sociodemographic characteristics of residents and patients is presented in Tables 1 and 2.
On the OPTION scale, family medicine residents earned an overall mean score of 24% ± 8% out of 100, with scores ranging from 8% to 43%. The scores' distribution is presented in Figure 2. Mean scores were calculated for each item and ranged between 1.46/4 (37%) and 0.15/4 (4%). The three highest-scoring items were “The clinician lists options, which can include the choice of ‘no action,’” “The clinician draws attention to an identified problem as one that requires a decision making process,” and “The clinician explains the pros and cons of options to the patient (taking ‘no action’ is an option).” The five lowest-scoring items were “The clinician explores the patient's concerns (fears) about how the problem(s) are to be managed,” “The clinician indicates the need for a decision making (or deferring) stage,” “The clinician elicits the patient's preferred level of involvement in decision making,” “The clinician states that there is more than one way to deal with the identified problem (equipoise),” and “The clinician assesses the patient's preferred approach to receiving information to assist decision making (e.g., discussion, reading printed material, assessing graphical data, using videotape or other media).” Table 3 lists the scores for these and all other items.
Analysis showed significant differences in OPTION scores between French and English consultations (French OPTION mean = 25% ± 8%; English OPTION mean = 22% ± 7%; t = 2.79, P = .006). It also showed significant differences between consultations with male and female practitioners (female OPTION mean = 25% ± 8%; male OPTION mean = 22% ± 7%; t = 2.08, P = .04). We observed a positive correlation between the OPTION score and the duration of consultation (r = 0.24, P = .003). The mean duration of a consultation (only including time with the patient, not time with a supervisor) was 0:28:41, SD ± 0:13:43. The minimum and maximum consultation times were 0:04:45 and 1:13:47, respectively. Considering that French consultations lasted significantly longer than English consultations (average duration of a consultation: French = 36 ± 13 minutes, English = 20 ± 9 minutes; t = 9.44, P < .0001) and that female residents' consultations lasted significantly longer than male residents' consultations (average duration of a consultation: female resident = 31 ± 14 minutes; male resident = 24 ± 12 minutes; t = 2.69, P = .008), we adjusted for time. After this adjustment, we observed no difference in OPTION scores according to the language of the consultation (P = .21) or the gender of the resident (P = .13). This indicates that the duration of the consultation can influence scores.
Family medicine residents who had obtained an academic degree prior to their medical education obtained lower OPTION scores than those who had not obtained such a degree (mean for those having a prior degree = 22% ± 7%; n = 62; 95% CI = 19.9%–23.2%; mean for those without a prior degree = 25% ± 8%; n = 88; 95% CI = 23.4%–26.8%; t = 2.87; P = .005). Because a higher proportion of English-speaking residents had prior degrees, we adjusted the scores according to both language and the duration of the consultation. Even after adjustment, we continued to observe a significant difference in the OPTION scores of residents with a prior degree and residents without one (P < .05). We found no association between residents' age and the OPTION score (r = −0.16, P > .05) or between the score and the resident's participation in a committee or a work group (t = −0.13, P = .89) or participation in a continuing medical education activity over the prior year (t = −1.13, P = .26). Furthermore, there was no statistically significant difference between the resident's year of training and the OPTION score. The mean scores (±SD) were 24% (±7), 24% (±8), and 21% (±7) for first-, second-, and third-year residents, respectively (P = .26 after adjusting for the duration of the consultation). Finally, the analyses revealed no association between the preference of the patient about his or her role in decision making (see Table 2) and the OPTION score of the corresponding resident (r = −0.09, P = .29).
Our findings show that SDM behaviors are not widely or well integrated in the practice of family medicine residents in the context of this study. Although there is no consensus on optimal OPTION scores, a mean score of 24% suggests that further skill building is needed for family medicine residents to be better able to involve their patients in decision making. These scores are similar to those of other published studies that used the revised OPTION scale to assess the practice of SDM behaviors by fully licensed physicians working in diverse medical settings. We cannot associate these weak OPTION scores with patients' lack of motivation to be involved in decision making, because most patients desire to take part in the decision-making process.7
What do these scores teach us?
Our findings support the theory that the duration of the consultation is an important factor in residents' capacity to apply SDM behaviors. Nonetheless, the evidence suggests that professionals who have had SDM training can incorporate SDM behaviors without lengthening the consultation.36 It therefore seems likely that the low scores obtained in our study result from the participation of residents—that is, physicians who are not fully licensed—who had not been trained in SDM. This observation points to the merit of offering appropriate training and giving residents enough time at the beginning of their residency to learn to integrate SDM in their consultations. Giving residents specific tools such as patient decision aids, which are known to provide information that enables patients to more actively participate in treatment decisions,37 could also help residents practice SDM within the time normally allocated for a consultation.
Our analysis also allows us to determine which SDM behaviors measured by the OPTION scale residents most applied and which they least applied in their clinical practice. Of these behaviors, the three highest-ranked and the five lowest-ranked items are of particular interest. Although the OPTION scale is unidimensional, the three highest-ranked items are highly related in that they evaluate the resident's ability to deliver information appropriately by “drawing attention to an identified problem requiring a decision making process” (Item 1), “listing the options which can include the choice of ‘no action’” (Item 4), and “explaining the pros and cons of options” (Item 5). All three items target problems and treatments and focus on curing the patient and delivering information.38 Although curing must remain a main purpose of any consultation, the SDM philosophy emphasizes patient participation. Therefore, to promote patients' involvement in health decisions, efforts to encourage caring for the patient—as opposed to merely curing him or her—are needed.38 For example, the residency curricula could include seminars and simulated cases for residents to learn and practice these specific SDM behaviors.
The five lowest-ranked items obtained scores under 25%, which, according to OPTION classification, falls below “a minimal attempt is made to exhibit the behavior.” Caring is a key element in consultations, particularly insofar as it improves the resident's ability to “explore the patient's concerns (fears)” (Item 7). This item figured among the five lowest-ranking behaviors. The behavior “indicating the need for a decision making (or deferring) stage” (Item 11) also earned a low score. Although residents put a lot of energy into informing their patients, they rarely indicated to patients the need to make a decision. This omission helps explain patients' limited involvement in the final decision and may reflect residents' willingness to be transparent in their clinical approach but their reluctance to negotiate or deal with decisions taken by their patients. Also, our findings suggest that residents have difficulty “eliciting the patient's preferred level of involvement” (Item 10). Although some clinicians argue that they can identify their patients' preferred level of involvement without asking, research has emphasized that they cannot, in general, do so.39–44 Moreover, several studies have shown that patients' satisfaction and commitment to treatment are higher when the patient and the practitioner agree on the patient's role in the decision-making process, on the meaning of the diagnosis and the prognosis, and on the treatment plan.41,42,45,46
Another rarely observed SDM behavior was “stating that there is more than one way to deal with the problem” (Item 2). Making explicit the existence of more than one valid option helps the patient to understand that there is no absolute answer to his or her health problem and that each option needs to be considered. Stating that there is more than one way to deal with the problem can also encourage residents to balance the pros and the cons of each option. The least observed behavior was “assessing preferred approach to receiving information” (Item 3). The low score obtained for this element may be explained by the context. Considering the variety of medical conditions seen in primary care,47,48 residents might not have different formats of information—leaflets, videos, reviews—for every condition. If residents feel that they cannot offer patients a choice of format, they might consider it futile to assess the patient's preference of ways to receive information. This reality highlights the notion that primary care physicians are not well equipped to transfer knowledge to their patients—and, by extension, are not well equipped to facilitate SDM. Developing interventions like patient decision aids, whose effectiveness has been proven, could be a way to overcome this shortcoming.8
Overall, the low scores recorded in this study suggest the necessity of improving residents' ability to practice SDM in their encounters. The lack of patient-centered behaviors that we have documented here should be targeted by medical education programs to improve family medicine residents' ability to exhibit SDM behaviors and involve their patients in clinical encounters. The fact that SDM is not taught throughout the medical curriculum may explain these low scores, as may the fact that residents do not see SDM modeled in clinical practice. Better integration of SDM throughout the curriculum, combined with appropriate role models, would be beneficial. The medical formation could include specific training sessions on SDM such as large-group learning, directed independent learning, seminars/workshops, small-group sessions, simulation, patient care experiences, and longitudinal patient care experiences. Also, medical educators would need to be trained and tooled on risk communication. This study, like the Association of American Medical Colleges' “Recommendations for Preclerkship Clinical Skills Education For Undergraduate Medical Education,”49 offers a basis for developing SDM interventions throughout the medical curriculum.
Strengths and limitations
To the best of our knowledge, our study is the first to provide a basis for interventions that target the promotion of specific SDM behaviors among residents working in teaching units in primary care, an area known for its decisional diversity. Our study based its assessments on the OPTION scale, a validated scale assessing 12 SDM-specific behaviors, and benefitted from a substantial sample of 152 participating dyads recruited in two different parts of Canada (French- and English speaking). As such, it offers a broad perspective of Canadian medical residents' practice of SDM in primary care.
The study also has limitations. First, measuring a phenomenon as complex and subjective as the medical decision-making process can be influenced by a number of factors. Among them is a particularity of the scale. The OPTION scale is designed to measure clinicians' ability to involve patients in decision making; it does not take patients' participation into account. A patient could approach many of the elements contained in the OPTION grid proactively, thereby initiating the SDM process, but unless the clinician expressed 1 of the 12 behaviors measured—which, if the client were proactive enough, the clinician might not be called on to do—the scale would measure the clinician's exhibition of SDM behavior as nil. It is therefore possible that OPTION scores underestimate not only the resident's practice of SDM but also his or her potential or willingness to practice SDM. In this way, OPTION fails to reflect SDM's nature as a dynamic process that is influenced by the evolution of the interaction between the clinician and the patient.50
Second, because a previous study did not find an association between decisional conflict scores and the nature of the health care decision made,51 we assumed that any encounter could lead to SDM. For this reason, we did not code and stratify patients' reasons for consulting. However, Elwyn and colleagues28 have suggested that the type of consultation may influence patients' involvement and that in some cases, like follow-up encounters, SDM-specific behaviors may already have taken place. This could serve to underestimate a given resident's overall OPTION score and reduces our ability to draw associations between the type of consultation and the OPTION score.
Third, it remains possible that videotaping the consultations might have allowed the coders to identify additional behaviors. Our decision to not videotape may therefore also have underestimated the scores. At the same time, agreeing to participate in an SDM study and knowing the encounter to be audiotaped could lead residents to display more SDM behaviors than they otherwise would. This could mean that even the low scores observed in our studies were inflated. Moreover, we acknowledge that a unique dyad—in other words, a single encounter—do not accurately represent each resident's ability or indeed tendency to translate SDM in clinical practice, because some encounters may be less favorable to SDM than others.
Lastly, as mentioned earlier, this study only recruited family medicine residents in Canada. For that reason, its results cannot be judged as representative of family medicine residents in other countries. For all of these reasons, our findings must be interpreted with caution.
This descriptive study used a third-observer instrument to assess family medicine residents' adoption of SDM-specific behaviors in primary-care-related decisions. The findings should inform health service researchers and educators working to develop interventions targeting behaviors essential for SDM, particularly in the context of family medicine residencies. Special attention should be paid to the allocation of the time necessary for residents to perform SDM, on focusing on caring as well as on curing, on reinforcing the importance of engaging patients' participation in consultations, and on developing communication tools to be used by both the residents and their patients.
The authors greatly appreciate the contributions of the patients and physicians who participated in this study; of the recruitment team in London under the leadership of Moira Stewart (Christina Bodea and Sherry Benko); of the recruitment team in Quebec City (Anthony Calabrino, Marie-Laure Dioh, Hubert Robitaille, Marc-André Pellerin, Lilianne Bordeleau, Annie LeBlanc); and of the coders who rated the consultations with the OPTION scale (Véronique Couture, Sébastien Courchesne-O'Neill, Hubert Robitaille, Marc-André Pellerin). The authors thank Merlin Njoya for helping with statistical analyses and Jennifer Petrela for her role in editing the text. France Légaré holds a Tier 2 Canada Research Chair in the Implementation of Shared Decision Making in Primary Care.
This study is part of EXACKTE2: “Exploiting the clinical consultation as a knowledge transfer and exchange environment,” a project funded by the Canadian Institutes of Health Research (CIHR 2008–2011; grant #185649-KTE). The EXACKTE2 team is composed of France Légaré, Moira Stewart, Glyn Elwyn, Michel Rousseau, Michel Labrecque, Dawn Stacey, Dominick Frosch, Jeremy Grimshaw, Mathieu Ouimet, and Trudy van der Weijden.
Ethical approval for this study was granted by the research ethics board of the Centre de Santé et de Services Sociaux de la Vieille Capitale in Quebec City, Quebec, Canada (final approval 2008/11/25; ethics number #2008-2009-23) and the Office of the Research Ethics of the University of Western Ontario (final approval 2009/02/03; ethics number #15712E).
The authors presented a poster based on this research at the 32nd Annual Meeting of the Society for Medical Decision Making in Toronto, Ontario, Canada, October 23 to 27, 2010.
1Stewart M, Brown JB, Weston WW, McWhinney IT, McWilliam CL, Freeman TT. Patient-Centered Medicine: Transforming the Clinical Method. 2nd ed. Milton Keynes, UK: Radcliffe Medical Press; 2003.
2Towle A, Godolphin W. Framework for teaching and learning informed shared decision making. BMJ. 1999;319:766–771.
3Weston WW. Informed and shared decision-making: The crux of patient-centered care. CMAJ. 2001;165:438–439.
4Elwyn G, Edwards A, Kinnersley P. Shared decision-making in primary care: The neglected second half of the consultation. Br J Gen Pract. 1999;49:477–482.
5Lomas J, Lavis J. Guidelines in the Mist. Hamilton, Ontario, Canada: Centre for Health Economics and Policy Analysis; 1996.
6Gagnon S, Labrecque M, Njoya M, Rousseau F, St-Jacques S, Légaré F. How much do family physicians involve pregnant women in decisions about prenatal screening for Down syndrome? Prenat Diagn. 2009;30:115–121.
7Kiesler DJ, Auerbach SM. Optimal matches of patient preferences for information, decision-making and interpersonal behavior: Evidence, models and interventions. Patient Educ Couns. 2006;61:319–341.
8O'Connor AM, Bennett CL, Stacey D, et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev. July 8, 2009;CD001431.
9Street RL, Makoul G, Arora NK, Epstein RM. How does communication heal? Pathways linking clinician–patient communication to health outcomes. Patient Educ Couns. 2009;74:295–301.
10McDonnell P, Jacobs M. Hospital admissions resulting from preventable adverse drug reactions. Ann Pharmacother. 2002;36:1331–1336.
11Senst B, Achusim L, Genest R, et al. Practical approach to determining costs and frequency of adverse drug events in a health care network. Am J Health Syst Pharm. 2001;58:1126–1132.
12Evans R, Edwards A, Brett J, et al. Reduction in uptake of PSA tests following decision aids: Systematic review of current aids and their evaluations. Patient Educ Couns. 2005;58:13–26.
13O'Connor AM, Bennett C, Stacey D, et al. Do patient decision aids meet effectiveness criteria of the international patient decision aid standards collaboration? A systematic review and meta-analysis. Med Decis Making. 2007;27:554–574.
14Wennberg JE, Fisher ES, Skinner JS. Geography and the debate over Medicare reform. Health Aff (Millwood). 2002;suppl Web exclusives:W96–W114.
15Coulter A. Engaging Patients in Their Healthcare. How Is the UK Doing Relative to Other Countries? Oxford, UK: Picker Institute Europe; 2006.
16King JS, Moulton BW. Rethinking informed consent: The case for shared medical decision-making. Am J Law Med. 2006;32:429–501.
18Elwyn G, Hutchings H, Edwards A, et al. The OPTION scale: Measuring the extent that clinicians involve patients in decision-making tasks. Health Expect. 2005;8:34–42. http://www.optioninstrument.com/publications.php
. Accessed May 11, 2011.
19Siriwardena AN, Edwards AG, Campion P, Freeman A, Elwyn G. Involve the patient and pass the MRCGP: Investigating shared decision making in a consulting skills examination using a validated instrument. Br J Gen Pract. 2006;56:857–862.
20Loh A, Simon D, Hennig K, Hennig B, Harter M, Elwyn G. The assessment of depressive patients' involvement in decision making in audio-taped primary care consultations. Patient Educ Couns. 2006;63:314–318.
21Goss C, Fontanesi S, Mazzi MA, et al. Shared decision making: The reliability of the OPTION scale in Italy. Patient Educ Couns. 2007;66:296–302.
22Goossensen A, Zijlstra P, Koopmanschap M. Measuring shared decision making processes in psychiatry: Skills versus patient satisfaction. Patient Educ Couns. 2007;67:50–56.
23Weiss MC, Peters TJ. Measuring shared decision making in the consultation: A comparison of the OPTION and Informed Decision Making instruments. Patient Educ Couns. 2008;70:79–86.
24Young HN, Bell RA, Epstein RM, Feldman MD, Kravitz RL. Physicians' shared decision-making behaviors in depression care. Arch Intern Med. 2008;168:1404–1408.
25Butow P, Juraskova I, Chang S, Lopez A-L, Brown R, Bernhard J. Shared decision making coding systems: How do they compare in the oncology context? Patient Educ Couns. 2010;78:261–268.
26Edwards A, Elwyn G. Inside the black box of shared decision making: Distinguishing between the process of involvement and who makes the decision. Health Expect. 2006;9:307–320.
28Elwyn G, Edwards A, Wensing M, Grol R. Shared Decision Making: Measurement Using the OPTION Instrument. Cardiff, UK: Cardiff University; 2005.
29Légaré F, Cauchon M, Labrecque M. French version OPTION: Observer l'implication du patient. In: Elwin G, Edwards A, Wensing M, Grol R, eds. Shared Decision Making: Measurement Using the OPTION Instrument. Cardiff, UK: Cardiff University, 2005.
30Nunnaly J. Psychometric Theory. New York, NY: McGraw-Hill; 1978.
31Galvin JE, Scharff DP, Glasheen C, Fu Q. Development of a population-based questionnaire to explore psychosocial determinants of screening for memory loss and Alzheimer disease. Alzheimer Dis Assoc Disord. 2006;20:182–191.
32Godwin M, Streight S, Dyachuk E, et al. Testing the Simple Lifestyle Indicator Questionnaire: Initial psychometric study. Can Fam Physician. 2008;54:76–77.
33Damen GW, Langereis MC, Snik AF, Chute PM, Mylanus EA. Classroom performance and language development of CI students placed in mainstream elementary school. Otol Neurotol. 2007;28:463–472.
34Légaré F, Stewart M, Frosch D, et al. EXACKTE2
: Exploiting the clinical consultation as a knowledge transfer and exchange environment: A study protocol. Implement Sci. 2009;4:14.
35Landis WJ, Hauschka BT, Rogerson CA, Glimcher MJ. Electron microscopic observations of bone tissue prepared by ultracryomicrotomy. J Ultrastruct Res. 1977;59:185–206.
36Stacey D, O'Connor A, Graham I, Pomey M. Randomized controlled trial of the effectiveness of an intervention to implement evidence-based patient decision support in a nursing call centre. J Telemed Telecare. 2006;12:410–415.
37Charles C, Gafni A, Whelan T. Shared decision-making in the medical encounter: What does it mean? (or it takes at least two to tango). Soc Sci Med. 1997;44:681–692.
38Webb C. Caring, curing, coping: Towards an integrated model. J Adv Nurs. 1996;23:960–968.
39Irvine EJ. Review article: Patients' fears and unmet needs in inflammatory bowel disease. Aliment Pharmacol Ther. 2004;20(suppl 4):54–59.
40Bruera E, Sweeney C, Calder K, Palmer L, Benisch-Tolley S. Patient preferences versus physician perceptions of treatment decisions in cancer care. J Clin Oncol. 2001;19:2883–2885.
41Street RL, Richardson MN, Cox V, Suarez-Almazor ME. (Mis)understanding in patient–health care provider communication about total knee replacement. Arthritis Rheum. 2009;61:100–107.
42Bruera E, Willey JS, Palmer JL, Rosales M. Treatment decisions for breast carcinoma: Patient preferences and physician perceptions. Cancer. 2002;94:2076–2080.
43Chu D-T, Kim S-W, Kuo H-P, et al. Patient attitudes towards chemotherapy as assessed by patient versus physician: A prospective observational study in advanced non-small cell lung cancer. Lung Cancer. 2007;56:433–443.
44Marinsek M, Kovacic D, Versnik D, Parasuh M, Golez S, Podbregar M. Analgesic treatment and predictors of satisfaction with analgesia in patients with acute undifferentiated abdominal pain. Eur J Pain. 2007;11:773–778.
45Staiger TO, Jarvik JG, Deyo RA, Martin B, Braddock CH 3rd. Brief report: Patient–physician agreement as a predictor of outcomes in patients with back pain. J Gen Intern Med. 2005;20:935–937.
46Jackson JL. Communication about symptoms in primary care: Impact on patient outcomes. J Altern Complement Med. 2005;11(suppl 1):S51–S56.
47Braddock CH 3rd, Edwards KA, Hasenberg NM, Laidley TL, Levinson W. Informed decision making in outpatient practice: Time to get back to basics. JAMA. 1999;282:2313–2320.
48Bindman AB, Forrest CB, Britt H, Crampton P, Majeed A. Diagnostic scope of and exposure to primary care physicians in Australia, New Zealand, and the United States: Cross sectional analysis of results from three national surveys. BMJ. 2007;334:1261.
50Charles C, Gafni A, Whelan T. Decision-making in the physician–patient encounter: Revisiting the shared treatment decision-making model. Soc Sci Med. 1999;49:651–661.
51Légaré F, O'Connor AM, Graham ID, Wells GA, Tremblay S. Impact of the Ottawa Decision Support Framework on the agreement and the difference between patients' and physicians' decisional conflict. Med Decis Making. 2006;26:373–390.