Predecisional information distortion in physicians’ diagnostic judgments: Strengthening a leading hypothesis or weakening its competitor?

© 2014.Decision makers have been found to bias their interpretation of incoming information to support an emerging judgment (predecisional information distortion). This is a robust finding in human judgment, and was recently also established and measured in physicians’ diagnostic judgments (Kostopoulou et al. 2012). The two studies reported here extend this work by addressing the constituent modes of distortion in physicians. Specifically, we studied whether and to what extent physicians distort information to strengthen their leading diagnosis and/or to weaken a competing diagnosis. We used the “stepwise evolution of preference” method with three clinical scenarios, and measured distortion on separate rating scales, one for each of the two competing diagnoses per scenario.In Study 1, distortion in an experimental group was measured against the responses of a separate control group. In Study 2, distortion in a new experimental group was measured against participants’ own, personal responses provided under control conditions, with the two response conditions separated by amonth. The two studies produced consistent results. On average, we found considerable distortion of information to weaken the trailing diagnosis but little distortion to strengthen the leading diagnosis. We also found individual differences in the tendency to engage in either mode of distortion. Given that two recent studies found both modes of distortion in lay preference (Blanchard, Carlson & Meloy, 2014; DeKay, Miller, Schley & Erford, 2014), we suggest that predecisional information distortion is affected by participant and task characteristics. Our findings contribute to the growing research on the different modes of predecisional distortion and their stability to methodological variation

How the UK public views the use of diagnostic decision aids by physicians: a vignette-based experiment

Objective: Physicians’ low adoption of diagnostic decision aids (DDAs) may be partially due to concerns about patient/public perceptions. We investigated how the UK public views DDA use and factors affecting perceptions. Materials and Methods: In this online experiment, 730 UK adults were asked to imagine attending a medical appointment where the doctor used a computerized DDA. The DDA recommended a test to rule out serious disease. We varied the test’s invasiveness, the doctor’s adherence to DDA advice, and the severity of the patient’s disease. Before disease severity was revealed, respondents indicated how worried they felt. Both before [t1] and after [t2] severity was revealed, we measured satisfaction with the consultation, likelihood of recommending the doctor, and suggested frequency of DDA use. Results: At both timepoints, satisfaction and likelihood of recommending the doctor increased when the doctor adhered to DDA advice (P ≤ .01), and when the DDA suggested an invasive versus noninvasive test (P ≤ .05). The effect of adherence to DDA advice was stronger when participants were worried (P ≤ .05), and the disease turned out to be serious (P ≤ .01). Most respondents felt that DDAs should be used by doctors “sparingly” (34%[t1]/29%[t2]), “frequently,” (43%[t1]/43%[t2]) or “always” (17%[t1]/21%[t2]). Discussion: People are more satisfied when doctors adhere to DDA advice, especially when worried, and when it helps to spot serious disease. Having to undergo an invasive test does not appear to dampen satisfaction. Conclusion: Positive attitudes regarding DDA use and satisfaction with doctors adhering to DDA advice could encourage greater use of DDAs in consultations

Online experiment comparing GPs’ antibiotic prescribing decisions to a clinical prediction rule

Background: The“STARWAVe” clinical prediction rule (CPR) uses seven factors to guide risk assessment and antibiotic prescribing in children with cough (Short illness duration, Temperature, Age, Recession, Wheeze, Asthma, Vomiting). Aim: To assess the influence of STARWAVe factors on General Practitioners’ (GPs) unaided risk assessments and prescribing decisions. We also explored two methods of obtaining risk assessments and tested the impact of parental concern. Design and setting: Experiment comprising clinical vignettes administered to 188 UK GPs online. Method: GPs were randomly assigned to view 32 (of 64) vignettes depicting children with cough. Vignettes varied the STARWAVe factors systematically. Per vignette, GPs assessed risk of deterioration in one of two ways (sliding scale vs. risk category selection) and indicated whether they would prescribe antibiotics. Finally, they saw an additional vignette, suggesting that the parent was concerned. Using mixed-effects regressions, we measured the influence of STARWAVe factors, risk elicitation method, and parental concern on GPs' assessments and decisions. Results: Six STARWAVe risk factors correctly increased GPs’ risk assessments (bssliding-scale0.66, ORscategory-selection1.61, ps0.001) while one incorrectly reduced them (short duration: bsliding-scale=-0.31, ORcategory-selection=0.75, ps0.039). Conversely, one STARWAVe factor increased prescribing odds (fever: OR=5.22, p<0.001) while the rest either reduced them (short duration, age, recession: ORs0.70, ps<0.001) or had no significant impact (wheeze, asthma, vomiting: ps0.065). Parental concern increased risk assessments (bsliding-scale=1.29, ORcategory-selection=2.82, ps0.003) but not prescribing (p=0.378). Conclusion: GPs use some, but not all, STARWAVe factors when making unaided risk assessments and prescribing decisions. Such discrepancies must be considered when introducing CPRs to clinical practice

The Role of Physicians’ First Impressions in the Diagnosis of Possible Cancers without Alarm Symptoms

Background. First impressions are thought to exert a disproportionate influence on subsequent judgments; however, their role in medical diagnosis has not been systematically studied. We aimed to elicit and measure the association between first impressions and subsequent diagnoses in common presentations with subtle indications of cancer. Methods. Ninety UK family physicians conducted interactive simulated consultations online, while on the phone with a researcher. They saw 6 patient cases, 3 of which could be cancers. Each cancer case included 2 consultations, whereby each patient consulted again with nonimproving and some new symptoms. After reading an introduction (patient description and presenting problem), physicians could request more information, which the researcher displayed online. In 2 of the possible cancers, physicians thought aloud. Two raters coded independently the physicians’ first utterances (after reading the introduction but before requesting more information) as either acknowledging the possibility of cancer or not. We measured the association of these first impressions with the final diagnoses and management decisions. Results. The raters coded 297 verbalizations with high interrater agreement (Kappa = 0.89). When the possibility of cancer was initially verbalized, the odds of subsequently diagnosing it were on average 5 times higher (odds ratio 4.90 [95% CI 2.72 to 8.84], P &lt; 0.001), while the odds of appropriate referral doubled (OR 1.98 [1.10 to 3.57], P = 0.002). The number of cancer-related questions physicians asked mediated the relationship between first impressions and subsequent diagnosis, explaining 29% of the total effect. Conclusion. We measured a strong association between family physicians’ first diagnostic impressions and subsequent diagnoses and decisions. We suggest that interventions to influence and support the diagnostic process should target its early stage of hypothesis generation. </jats:p

What You Find Depends on How You Measure It: Reactivity of Response Scales Measuring Predecisional Information Distortion in Medical Diagnosis

“Predecisional information distortion” occurs when decision makers evaluate new information in a way that is biased towards their leading option. The phenomenon is well established, as is the method typically used to measure it, termed “stepwise evolution of preference” (SEP). An inadequacy of this method has recently come to the fore: it measures distortion as the total advantage afforded a leading option over its competitor, and therefore it cannot differentiate between distortion to strengthen a leading option (“proleader” distortion) and distortion to weaken a trailing option (“antitrailer” distortion). To address this, recent research introduced new response scales to SEP. We explore whether and how these new response scales might influence the very proleader and antitrailer processes that they were designed to capture (“reactivity”). We used the SEP method with concurrent verbal reporting: fifty family physicians verbalized their thoughts as they evaluated patient symptoms and signs (“cues”) in relation to two competing diagnostic hypotheses. Twenty-five physicians evaluated each cue using the response scale traditional to SEP (a single response scale, returning a single measure of distortion); the other twenty-five did so using the response scales introduced in recent studies (two separate response scales, returning two separate measures of distortion: proleader and antitrailer). We measured proleader and antitrailer processes in verbalizations, and compared verbalizations in the single-scale and separate-scales groups. Response scales did not appear to affect proleader processes: the two groups of physicians were equally likely to bolster their leading diagnosis verbally. Response scales did, however, appear to affect antitrailer processes: the two groups denigrated their trailing diagnosis verbally to differing degrees. Our findings suggest that the response scales used to measure information distortion might influence its constituent processes, limiting their generalizability across and beyond experimental studies

Disentangling the relationship between physician and organizational performance: a signal detection approach

Background. In previous research, we employed a signal detection approach to measure the performance of general practitioners (GPs) when deciding about urgent referral for suspected lung cancer. We also explored associations between provider and organizational performance. We found that GPs from practices with higher referral positive predictive value (PPV; chance of referrals identifying cancer) were more reluctant to refer than those from practices with lower PPV. Here, we test the generalizability of our findings to a different cancer. Methods. A total of 252 GPs responded to 48 vignettes describing patients with possible colorectal cancer. For each vignette, respondents decided whether urgent referral to a specialist was needed. They then completed the 8-item Stress from Uncertainty scale. We measured GPs’ discrimination (d′) and response bias (criterion; c) and their associations with organizational performance and GP demographics. We also measured correlations of d′ and c between the 2 studies for the 165 GPs who participated in both. Results. As in the lung study, organizational PPV was associated with response bias: in practices with higher PPV, GPs had higher criterion (b = 0.05 [0.03 to 0.07]; P < 0.001), that is, they were less inclined to refer. As in the lung study, female GPs were more inclined to refer than males (b = −0.17 [−0.30 to −0.105]; P = 0.005). In a mediation model, stress from uncertainty did not explain the gender difference. Only response bias correlated between the 2 studies (r = 0.39, P < 0.001). Conclusions. This study confirms our previous findings regarding the relationship between provider and organizational performance and strengthens the finding of gender differences in referral decision making. It also provides evidence that response bias is a relatively stable feature of GP referral decision making

Risk assessment and antibiotic prescribing decisions in children presenting to UK primary care with cough: a vignette study

Objectives: The validated “STARWAVe” clinical prediction rule (CPR) uses seven variables to guide risk assessment and antimicrobial stewardship in children presenting with cough(Short illness duration, Temperature, Age, Recession, Wheeze, Asthma,Vomiting). We aimed to compare General Practitioners’ (GPs) risk assessments and prescribing decisions to those of STARWAVe, and assess the influence of the CPR’s clinical variables. Setting: Primary care. Participants: 252 GPs, currently practising in the UK. Design: GPs were randomly assigned to view four (of a possible eight) clinical vignettes online. Each vignette depicted a child presenting with cough, who was described in terms of the seven STARWAVe variables. Systematically, we manipulated patient age (20 months vs. 5 years), illness duration (3 vs. 6 days),vomiting (present vs. absent) and wheeze (present vs. absent), holding the remaining STARWAVe variables constant. Outcome measures:Per vignette, GPs assessed risk of hospitalisation and indicated whether they would prescribe antibiotics or not. Results: GPs overestimated risk of hospitalisationin 9% of vignette presentations (88/1008) and underestimated it in 46% (459/1008). Despite underestimating risk, they overprescribed: 78% of prescriptions were unnecessary relative to GPs’ own risk assessments (121/156), while 83% were unnecessary relativeto STARWAVe risk assessments (130/156). All four of the manipulated variables influenced risk assessments, but only three influenced prescribing decisions: a shorter illness duration reduced prescribing odds (OR 0.14, 95% CI 0.08-0.27, p<0.001), while vomiting and wheeze increased them (ORvomit2.17, 95% CI 1.32-3.57, p=0.002; ORwheeze8.98, 95% CI 4.99-16.15, p<0.001). Conclusions: Relative to STARWAVe, GPs underestimated riskof hospitalisation, overprescribed, and appeared to misinterpret illness duration (prescribing for longer rather than shorter illnesses). It is important to ascertain discrepancies between CPRs and current clinical practice. This has implications for the integration of CPRs into the electronic health record and the provision of intelligible explanations to decision maker

State of training and equipment of chainsaw operators employed for timber harvesting in Polish forests

One of the most important factors influencing work performance of chainsaw operators, considered as one of the most dangerous, is acquirement of knowledge in a training course enabling to obtain vocational qualifications as a logger and to gain experience in timber harvesting operations. Securing the safety of the chainsaw operator is realized on two levels. Firstly, by organizing appropriate training courses, and secondly, by providing employees with appropriate personal protective equipment. The research was carried out in 15 forest districts in different parts of Poland. The survey conducted on a group of over 200 loggers was aimed at identifying the most important factors affecting health and safety of work in forestry. According to the obtained results, a large group of chainsaw operators completed only a 2−3−day−long training courses, during which they could not get sufficient knowledge how to operate with the chainsaw. The lack of knowledge has a direct impact on the fact that 57% of the respondents use the chainsaw for its extreme wear, 41% of the loggers do not prepare the work place before tree felling and do not debark the stump. 40% of these workers do not set the chain brake, while starting the chainsaw engine. 41% of loggers do not work with an assistant in young stands. The consequences of such negligence are injuries. 76% of them are not reported as accidents at work

Influences of early diagnostic suggestions on clinical reasoning

Previous research has highlighted the importance of physicians’ early hypotheses for their subsequent diagnostic decisions. It has also been shown that diagnostic accuracy improves when physicians are presented with a list of diagnostic suggestions to consider at the start of the clinical encounter. The psychological mechanisms underlying this improvement in accuracy are hypothesised. It is possible that the provision of diagnostic suggestions disrupts physicians’ intuitive thinking and reduces their certainty in their initial diagnostic hypotheses. This may encourage them to seek more information before reaching a diagnostic conclusion, evaluate this information more objectively, and be more open to changing their initial hypotheses. Three online experiments explored the effects of early diagnostic suggestions, provided by a hypothetical decision aid, on different aspects of the diagnostic reasoning process. Family physicians assessed up to two patient scenarios with and without suggestions. We measured effects on certainty about the initial diagnosis, information search and evaluation, and frequency of diagnostic changes. We did not find a clear and consistent effect of suggestions and detected mainly non-significant trends, some in the expected direction. We also detected a potential biasing effect: when the most likely diagnosis was included in the list of suggestions (vs. not included), physicians who gave that diagnosis initially, tended to request less information, evaluate it as more supportive of their diagnosis, become more certain about it, and change it less frequently when encountering new but ambiguous information; in other words, they seemed to validate rather than question their initial hypothesis. We conclude that further research using different methodologies and more realistic experimental situations is required to uncover both the beneficial and biasing effects of early diagnostic suggestions