Two Specialists, Two Recommendations: Discordance Between Urologists' & Radiation Oncologists' Prostate Cancer Treatment Recommendations.

OBJECTIVE: To examine the treatment recommendation patterns among urologists and radiation oncologists, the level of concordance or discordance between physician recommendations, and the association between physician recommendations and the treatment that patients received. METHOD: The study was a secondary analysis of data from a randomized clinical trial conducted November 2010 to April 2014 (NCT02053389). Eligible participants were patients from the trial who saw both specialists. The primary outcome was physician recommendations that were scored using an adapted version of the validated PhyReCS coding system. Secondary outcomes included concordance between physician recommendations and the treatment patients received. RESULTS: Participants were 108 patients (Mean age 61.9 years; range 43-82; 87% non-Hispanic White). Urologists were more likely to recommend surgery (79% of recommendations) and radiation oncologists were more likely to recommend radiation (68% of recommendations). Recommendations from the urologists and radiation oncologists were concordant for only 33 patients (30.6%). Most patients received a treatment that both physicians recommended (59%); however, 35% received a treatment that only one of their physicians recommended. When discordant, urologists more often recommended surgery and radiation oncologists recommended radiation and surgery as equally appropriate options. CONCLUSION: Urologists and radiation oncologists are more likely to differ than agree in their treatment recommendations for the same patients with clinically localized prostate cancer and more likely to favor treatment aligned with their specialty. Additional studies are needed to better understand how patients make decisions after meeting with two different specialists to inform the development of best practices within oncology clinics.

Association of quantitative information and patient knowledge about prostate cancer outcomes.

OBJECTIVE: When the volume or complexity of health information exceeds the capacity to process it, patients may misinterpret or ignore critical information. Numerical information is especially challenging to process for many patients, yet no empirical data shows whether numerical information influences how well they could process and recall it. METHOD: Using natural language processing tools, we estimated the amount of numerical and probability-related (quantitative) information that was provided in 112 paired urology-radiology clinical consultations with patients who had been recently diagnosed with prostate cancer. The primary outcome measured was patient knowledge about their prostate cancer outcomes assessed before and after the consultations. RESULTS: Patients with prostate cancer, Gleason score 6 or 7, and stage Time 1 or Time 2 participated in the study. Paired consultations included on average 11,086 words spoken. The relationship between quantitative information provided in consultations and patient knowledge about their cancer outcomes followed an inverted U-shape. There was a positive association between quantitative information and patient knowledge about their cancer outcomes. However, after the amount of quantitative information exceeded 4% (422 quantitative words) in paired consultations, the relationships between knowledge and the number of quantitative words became negative. Individual differences in education were not associated with observed relationships. CONCLUSION: Despite concerns about patients' capacity to process quantitative information, we found that patients' knowledge about cancer risks is positively associated with a certain amount of quantitative information. In the consultations, patients need to receive quantitative information that is well balanced with qualitative explanations. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Preparing Patients with Early Stage Prostate Cancer to Participate in Clinical Appointments Using a Shared Decision Making Training Video.

BACKGROUND: Rates of shared decision making (SDM) are relatively low in early stage prostate cancer decisions, as patients' values are not well integrated into a preference-sensitive treatment decision. The study objectives were to develop a SDM training video, measure usability and satisfaction, and determine the effect of the intervention on preparing patients to participate in clinical appointments. METHODS: A randomized controlled trial was conducted to compare a plain-language decision aid (DA) to the DA plus a patient SDM training video. Patients with early stage prostate cancer completed survey measures at baseline and after reviewing the intervention materials. Survey items assessed patients' knowledge, beliefs related to SDM, and perceived readiness/intention to participate in their upcoming clinical appointment. RESULTS: Of those randomized to the DA + SDM video group, most participants (91%) watched the video and 93% would recommend the video to others. Participants in the DA + SDM video group, compared to the DA-only group, reported an increased desire to participate in the decision (mean = 3.65 v. 3.39, P < 0.001), less decision urgency (mean = 2.82 v. 3.39, P < 0.001), and improved self-efficacy for communicating with physicians (mean = 4.69 v. 4.50, P = 0.05). These participants also reported increased intentions to seek a referral from a radiation oncologist (73% v. 51%, P = 0.004), to take notes (mean = 3.23 v. 2.86, P = 0.004), and to record their upcoming appointments (mean = 1.79 v. 1.43, P = 0.008). CONCLUSIONS: A novel SDM training video was accepted by patients and changed several measures associated with SDM. This may be a scalable, cost-effective way to prepare patients with early stage prostate cancer to participate in their clinical appointments.[Box: see text].

Head to head randomized trial of two decision aids for prostate cancer.

BACKGROUND: While many studies have tested the impact of a decision aid (DA) compared to not receiving any DA, far fewer have tested how different types of DAs affect key outcomes such as treatment choice, patient-provider communication, or decision process/satisfaction. This study tested the impact of a complex medical oriented DA compared to a more simplistic decision aid designed to encourage shared decision making in men with clinically localized prostate cancer. METHODS: 1028 men at 4 VA hospitals were recruited after a scheduled prostate biopsy. Participants completed baseline measures and were randomized to receive either a simple or complex DA. Participants were men with clinically localized cancer (N = 285) by biopsy and who completed a baseline survey. Survey measures: baseline (biopsy); immediately prior to seeing the physician for biopsy results (pre- encounter); one week following the physician visit (post-encounter). Outcome measures included treatment preference and treatment received, knowledge, preference for shared decision making, decision making process, and patients' use and satisfaction with the DA. RESULTS: Participants who received the simple DA had greater interest in shared decision making after reading the DA (p = 0.03), found the DA more helpful (p's < 0.01) and were more likely to be considering watchful waiting (p = 0.03) compared to those receiving the complex DA at Time 2. While these differences were present before patients saw their urologists, there was no difference between groups in the treatment patients received. CONCLUSIONS: The simple DA led to increased desire for shared decision making and for less aggressive treatment. However, these differences disappeared following the physician visit, which appeared to change patients' treatment preferences. Trial registration This trial was pre-registered prior to recruitment of participants.

What Helps People Make Values-Congruent Medical Decisions? Eleven Strategies Tested across 6 Studies.

Background. High-quality health decisions are often defined as those that are both evidence informed and values congruent. A values-congruent decision aligns with what matters to those most affected by the decision. Values clarification methods are intended to support values-congruent decisions, but their effects on values congruence are rarely evaluated. Methods. We tested 11 strategies, including the 3 most commonly used values clarification methods, across 6 between-subjects online randomized experiments in demographically diverse US populations (n1 = 1346, n2 = 456, n3 = 840, n4 = 1178, n5 = 841, n6 = 2033) in the same hypothetical decision. Our primary outcome was values congruence. Decisional conflict was a secondary outcome in studies 3 to 6. Results. Two commonly used values clarification methods (pros and cons, rating scales) reduced decisional conflict but did not encourage values-congruent decisions. Strategies using mathematical models to show participants which option aligned with what mattered to them encouraged values-congruent decisions and reduced decisional conflict when assessed. Limitations. A hypothetical decision was necessary for ethical reasons, as we believed some strategies may harm decision quality. Later studies used more outcomes and covariates. Results may not generalize outside US-based adults with online access. We assumed validity and stability of values during the brief experiments. Conclusions. Failing to explicitly support the process of aligning options with values leads to increased proportions of values-incongruent decisions. Methods representing more than half of values clarification methods commonly in use failed to encourage values-congruent decisions. Methods that use models to explicitly show people how options align with their values offer more promise for helping people make decisions aligned with what matters to them. Decisional conflict, while arguably an important outcome in and of itself, is not an appropriate proxy for values congruence.

Physician Recommendations Trump Patient Preferences in Prostate Cancer Treatment Decisions.

OBJECTIVE: To assess the influence of patient preferences and urologist recommendations in treatment decisions for clinically localized prostate cancer. METHODS: We enrolled 257 men with clinically localized prostate cancer (prostate-specific antigen <20; Gleason score 6 or 7) seen by urologists (primarily residents and fellows) in 4 Veterans Affairs medical centers. We measured patients' baseline preferences prior to their urology appointments, including initial treatment preference, cancer-related anxiety, and interest in sex. In longitudinal follow-up, we determined which treatment patients received. We used hierarchical logistic regression to determine the factors that predicted treatment received (active treatment v. active surveillance) and urologist recommendations. We also conducted a directed content analysis of recorded clinical encounters to determine if urologists discussed patients' interest in sex. RESULTS: Patients' initial treatment preferences did not predict receipt of active treatment versus surveillance, Δχ2(4) = 3.67, P = 0.45. Instead, receipt of active treatment was predicted primarily by urologists' recommendations, Δχ2(2) = 32.81, P < 0.001. Urologists' recommendations, in turn, were influenced heavily by medical factors (age and Gleason score) but were unrelated to patient preferences, Δχ2(6) = 0, P = 1. Urologists rarely discussed patients' interest in sex (<15% of appointments). CONCLUSIONS: Patients' treatment decisions were based largely on urologists' recommendations, which, in turn, were based on medical factors (age and Gleason score) and not on patients' personal views of the relative pros and cons of treatment alternatives.

Effects of Design Features of Explicit Values Clarification Methods: A Systematic Review.

BACKGROUND: Diverse values clarification methods exist. It is important to understand which, if any, of their design features help people clarify values relevant to a health decision. PURPOSE: To explore the effects of design features of explicit values clarification methods on outcomes including decisional conflict, values congruence, and decisional regret. DATA SOURCES: MEDLINE, all EBM Reviews, CINAHL, EMBASE, Google Scholar, manual search of reference lists, and expert contacts. STUDY SELECTION: Articles were included if they described the evaluation of 1 or more explicit values clarification methods. DATA EXTRACTION: We extracted details about the evaluation, whether it was conducted in the context of actual or hypothetical decisions, and the results of the evaluation. We combined these data with data from a previous review about each values clarification method's design features. DATA SYNTHESIS: We identified 20 evaluations of values clarification methods within 19 articles. Reported outcomes were heterogeneous. Few studies reported values congruence or postdecision outcomes. The most promising design feature identified was explicitly showing people the implications of their values, for example, by displaying the extent to which each of their decision options aligns with what matters to them. LIMITATIONS: Because of the heterogeneity of outcomes, we were unable to perform a meta-analysis. Results should be interpreted with caution. CONCLUSIONS: Few values clarification methods have been evaluated experimentally. More research is needed to determine effects of different design features of values clarification methods and to establish best practices in values clarification. When feasible, evaluations should assess values congruence and postdecision measures of longer-term outcomes.

Design Features of Explicit Values Clarification Methods: A Systematic Review.

BACKGROUND: Values clarification is a recommended element of patient decision aids. Many different values clarification methods exist, but there is little evidence synthesis available to guide design decisions. PURPOSE: To describe practices in the field of explicit values clarification methods according to a taxonomy of design features. DATA SOURCES: MEDLINE, all EBM Reviews, CINAHL, EMBASE, Google Scholar, manual search of reference lists, and expert contacts. STUDY SELECTION: Articles were included if they described 1 or more explicit values clarification methods. DATA EXTRACTION: We extracted data about decisions addressed; use of theories, frameworks, and guidelines; and 12 design features. DATA SYNTHESIS: We identified 110 articles describing 98 explicit values clarification methods. Most of these addressed decisions in cancer or reproductive health, and half addressed a decision between just 2 options. Most used neither theory nor guidelines to structure their design. "Pros and cons" was the most common type of values clarification method. Most methods did not allow users to add their own concerns. Few methods explicitly presented tradeoffs inherent in the decision, supported an iterative process of values exploration, or showed how different options aligned with users' values. LIMITATIONS: Study selection criteria and choice of elements for the taxonomy may have excluded values clarification methods or design features. CONCLUSIONS: Explicit values clarification methods have diverse designs but can be systematically cataloged within the structure of a taxonomy. Developers of values clarification methods should carefully consider each of the design features in this taxonomy and publish adequate descriptions of their designs. More research is needed to study the effects of different design features.

Informed Decision Making: Assessment of the Quality of Physician Communication about Prostate Cancer Diagnosis and Treatment.

INTRODUCTION: Little is known about how physicians present diagnosis and treatment planning in routine practice in preference-sensitive treatment decisions. We evaluated completeness and quality of informed decision making in localized prostate cancer post biopsy encounters. METHODS: We analyzed audio-recorded office visits of 252 men with presumed localized prostate cancer (Gleason 6 and Gleason 7 scores) who were seeing 45 physicians at 4 Veterans Affairs Medical Centers. Data were collected between September 2008 and May 2012 in a trial of 2 decision aids (DAs). Braddock's previously validated Informed Decision Making (IDM) system was used to measure quality. Latent variable models for ordinal data examined the relationship of IDM score to treatment received. RESULTS: Mean IDM score showed modest quality (7.61±2.45 out of 18) and high variability. Treatment choice and risks and benefits were discussed in approximately 95% of encounters. However, in more than one-third of encounters, physicians provided a partial set of treatment options and omitted surveillance as a choice. Informing quality was greater in patients treated with surveillance (ß = 1.1, p = .04). Gleason score (7 vs 6) and lower age were often cited as reasons to exclude surveillance. Patient preferences were elicited in the majority of cases, but not used to guide treatment planning. Encounter time was modestly correlated with IDM score (r = 0.237, p = .01). DA type was not associated with IDM score. DISCUSSION: Physicians informed patients of options and risks and benefits, but infrequently engaged patients in core shared decision-making processes. Despite patients having received DAs, physicians rarely provided an opportunity for preference-driven decision making. More attention to the underused patient decision-making and engagement elements could result in improved shared decision making.

Patient-physician communication about early stage prostate cancer: analysis of overall visit structure.

BACKGROUND: We know little about patient-physician communication during visits to discuss diagnosis and treatment of prostate cancer. OBJECTIVE: To examine the overall visit structure and how patients and physicians transition between communication activities during visits in which patients received new prostate cancer diagnoses. PARTICIPANTS: Forty veterans and 18 urologists at one VA medical centre. METHODS: We coded 40 transcripts to identify major communication activities during visits and used empiric discourse analysis to analyse transitions between activities. RESULTS: We identified five communication activities that occurred in the following typical sequence: 'diagnosis delivery', 'risk classification', 'options talk', 'decision talk' and 'next steps'. The first two activities were typically brief and involved minimal patient participation. Options talk was typically the longest activity; physicians explicitly announced the beginning of options talk and framed it as their professional responsibility. Some patients were unsure of the purpose of visit and/or who should make treatment decisions. CONCLUSION: Visits to deliver the diagnosis of early stage prostate cancer follow a regular sequence of communication activities. Physicians focus on discussing treatment options and devote comparatively little time and attention to discussing the new cancer diagnosis. Towards the goal of promoting patient-centred communication, physicians should consider eliciting patient reactions after diagnosis delivery and explaining the decision-making process before describing treatment options.

Animated randomness, avatars, movement, and personalization in risk graphics.

BACKGROUND: Risk communication involves conveying two inherently difficult concepts about the nature of risk: the underlying random distribution of outcomes and how a population-based proportion applies to an individual. OBJECTIVE: The objective of this study was to test whether 4 design factors in icon arrays-animated random dispersal of risk events, avatars to represent an individual, personalization (operationalized as choosing the avatar's color), and a moving avatar-might help convey randomness and how a given risk applies to an individual, thereby better aligning risk perceptions with risk estimates. METHODS: A diverse sample of 3630 adults with no previous heart disease or stroke completed an online nested factorial experiment in which they entered personal health data into a risk calculator that estimated 10-year risk of cardiovascular disease based on a robust and validated model. We randomly assigned them to view their results in 1 of 10 risk graphics that used different combinations of the 4 design factors. We measured participants' risk perceptions as our primary outcome, as well as behavioral intentions and recall of the risk estimate. We also assessed subjective numeracy, whether or not participants knew anyone who had died of cardiovascular causes, and whether or not they knew their blood pressure and cholesterol as potential moderators. RESULTS: Animated randomness was associated with better alignment between risk estimates and risk perceptions (F1,3576=6.12, P=.01); however, it also led to lower scores on healthy lifestyle intentions (F1,3572=11.1, P<.001). Using an avatar increased risk perceptions overall (F1,3576=4.61, P=.03) and most significantly increased risk perceptions among those who did not know a particular person who had experienced the grave outcomes of cardiovascular disease (F1,3576=5.88, P=.02). Using an avatar also better aligned actual risk estimates with intentions to see a doctor (F1,3556=6.38, P=.01). No design factors had main effects on recall, but animated randomness was associated with better recall for those at lower risk and worse recall for those at higher risk (F1,3544=7.06, P=.01). CONCLUSIONS: Animated randomness may help people better understand the random nature of risk. However, in the context of cardiovascular risk, such understanding may result in lower healthy lifestyle intentions. Therefore, whether or not to display randomness may depend on whether one's goal is to persuade or to inform. Avatars show promise for helping people grasp how population-based statistics map to an individual case.

Blocks, ovals, or people? Icon type affects risk perceptions and recall of pictographs.

BACKGROUND: Research has demonstrated that icon arrays (also called "pictographs") are an effective method of communicating risk statistics and appear particularly useful to less numerate and less graphically literate people. Yet research is very limited regarding whether icon type affects how people interpret and remember these graphs. METHODS: 1502 people age 35-75 from a demographically diverse online panel completed a cardiovascular risk calculator based on Framingham data using their actual age, weight, and other health data. Participants received their risk estimate in an icon array graphic that used 1 of 6 types of icons: rectangular blocks, filled ovals, smile/frown faces, an outline of a person's head and shoulders, male/female "restroom" person icons (gender matched), or actual head-and-shoulder photographs of people of varied races (gender matched). In each icon array, blue icons represented cardiovascular events and gray icons represented those who would not experience an event. We measured perceived risk magnitude, approximate recall, and opinions about the icon arrays, as well as subjective numeracy and an abbreviated measure of graphical literacy. RESULTS: Risk recall was significantly higher with more anthropomorphic icons (restroom icons, head outlines, and photos) than with other icon types, and participants rated restroom icons as most preferred. However, while restroom icons resulted in the highest correlations between perceived and actual risk among more numerate/graphically literate participants, they performed no better than other icon types among less numerate/graphically literate participants. CONCLUSIONS: Icon type influences both risk perceptions and risk recall, with restroom icons in particular resulting in improved outcomes. However, optimal icon types may depend on numeracy and/or graphical literacy skills.

Animated graphics for comparing two risks: a cautionary tale.

BACKGROUND: The increasing use of computer-administered risk communications affords the potential to replace static risk graphics with animations that use motion cues to reinforce key risk messages. Research on the use of animated graphics, however, has yielded mixed findings, and little research exists to identify the specific animations that might improve risk knowledge and patients' decision making. OBJECTIVE: To test whether viewing animated forms of standard pictograph (icon array) risk graphics displaying risks of side effects would improve people's ability to select the treatment with the lowest risk profile, as compared with viewing static images of the same risks. METHODS: A total of 4198 members of a demographically diverse Internet panel read a scenario about two hypothetical treatments for thyroid cancer. Each treatment was described as equally effective but varied in side effects (with one option slightly better than the other). Participants were randomly assigned to receive all risk information in 1 of 10 pictograph formats in a quasi-factorial design. We compared a control condition of static grouped icons with a static scattered icon display and with 8 Flash-based animated versions that incorporated different combinations of (1) building the risk 1 icon at a time, (2) having scattered risk icons settle into a group, or (3) having scattered risk icons shuffle themselves (either automatically or by user control). We assessed participants' ability to choose the better treatment (choice accuracy), their gist knowledge of side effects (knowledge accuracy), and their graph evaluation ratings, controlling for subjective numeracy and need for cognition. RESULTS: When compared against static grouped-icon arrays, no animations significantly improved any outcomes, and most showed significant performance degradations. However, participants who received animations of grouped icons in which at-risk icons appeared 1 at a time performed as well on all outcomes as the static grouped-icon control group. Displays with scattered icons (static or animated) performed particularly poorly unless they included the settle animation that allowed users to view event icons grouped. CONCLUSIONS: Many combinations of animation, especially those with scattered icons that shuffle randomly, appear to inhibit knowledge accuracy in this context. Static pictographs that group risk icons, however, perform very well on measures of knowledge and choice accuracy. These findings parallel recent evidence in other data communication contexts that less can be more-that is, that simpler, more focused information presentation can result in improved understanding. Decision aid designers and health educators should proceed with caution when considering the use of animated risk graphics to compare two risks, given that evidence-based, static risk graphics appear optimal.