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

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

The tight coupling between category and causal learning

The main goal of the present research was to demonstrate the interaction between category and causal induction in causal model learning. We used a two-phase learning procedure in which learners were presented with learning input referring to two interconnected causal relations forming a causal chain (Experiment 1) or a common-cause model (Experiments 2a, b). One of the three events (i.e., the intermediate event of the chain, or the common cause) was presented as a set of uncategorized exemplars. Although participants were not provided with any feedback about category labels, they tended to induce categories in the first phase that maximized the predictability of their causes or effects. In the second causal learning phase, participants had the choice between transferring the newly learned categories from the first phase at the cost of suboptimal predictions, or they could induce a new set of optimally predictive categories for the second causal relation, but at the cost of proliferating different category schemes for the same set of events. It turned out that in all three experiments learners tended to transfer the categories entailed by the first causal relation to the second causal relation

Reference Values of the QOLIBRI from General Population Samples in the United Kingdom and The Netherlands

The Quality of Life after Traumatic Brain Injury (QOLIBRI) instrument is an internationally validated patient-reported outcome measure for assessing disease-specific health-related quality of life (HRQoL) in individuals after traumatic brain injury (TBI). However, no reference values for general populations are available yet for use in clinical practice and research in the field of TBI. The aim of the present study was, therefore, to establish these reference values for the United Kingdom (UK) and the Netherlands (NL). For this purpose, an online survey with a reworded version of the QOLIBRI for general populations was used to collect data on 4403 individuals in the UK and 3399 in the NL. This QOLIBRI version was validated by inspecting descriptive statistics, psychometric criteria, and comparability of the translations to the original version. In particular, measurement invariance (MI) was tested to examine whether the items of the instrument were understood in the same way by different individuals in the general population samples and in the TBI sample across the two countries, which is necessary in order to establish reference values. In the general population samples, the reworded QOLIBRI displayed good psychometric properties, including MI across countries and in the non-TBI and TBI samples. Therefore, differences in the QOLIBRI scores can be attributed to real differences in HRQoL. Individuals with and without a chronic health condition did differ significantly, with the latter reporting lower HRQoL. In conclusion, we provided reference values for healthy individuals and individuals with at least one chronic condition from general population samples in the UK and the NL. These can be used in the interpretation of disease-specific HRQoL assessments after TBI applying the QOLIBRI on the individual level in clinical as well as research contexts

The attitudes and beliefs of Pakistani medical practitioners about depression: a cross-sectional study in Lahore using the Revised Depression Attitude Questionnaire (R-DAQ)

BACKGROUND: Mental disorders such as depression are common and rank as major contributors to the global burden of disease. Condition recognition and subsequent management of depression is variable and influenced by the attitudes and beliefs of clinicians as well as those of patients. Most studies examining health professionals' attitudes have been conducted in Western nations; this study explores beliefs and attitudes about depression among doctors working in Lahore, Pakistan. METHODS: A cross-sectional survey conducted in 2015 used a questionnaire concerning demographics, education in psychiatry, beliefs about depression causes, and attitudes about depression using the Revised Depression Attitude Questionnaire (R-DAQ). A convenience sample of 700 non-psychiatrist medical practitioners based in six hospitals in Lahore was approached to participate in the survey. RESULTS: Six hundred and one (86 %) of the doctors approached consented to participate; almost all respondents (99 %) endorsed one of various biopsychosocial causes of depression (38 to 79 % for particular causes), and 37 % (between 13 and 19 % for particular causes) noted that supernatural forces could be responsible. Supernatural causes were more commonly held by female doctors, those working in rural settings, and those with greater psychiatry specialist education. Attitudes to depression were mostly less confident or optimistic and less inclined to a generalist perspective than those of clinicians in the UK or European nations, and deterministic perspectives that depression is a natural part of aging or due to personal failings were particularly common. However, there was substantial confidence in the efficacy of antidepressants and psychological therapy. More confident and therapeutically optimistic views and a more generalist perspective about depression management were associated with a rejection of supernatural explanations of the origin of depression. CONCLUSIONS: Non-psychiatrist medical practitioners in Pakistan hold a range of views about the causes of depression, with supernatural explanations held by more than a third. Depression attitudes appear less positive than among UK and European clinicians, with the notions that depression is due to a lack of stamina and will-power and a natural part of growing old being especially commonly held; more positive attitudes appear to be associated with a rejection of supernatural explanatory models of depression

Cue interaction and judgments of causality: Contributions of causal and associative processes

In four experiments, the predictions made by causal model theory and the Rescorla-Wagner model were tested by using a cue interaction paradigm that measures the relative response to a given event based on the influence or salience of an alternative event. Experiments 1 and 2 uncorrelated two variables that have typically been confounded in the literature (causal order and the number of cues and outcomes) and demonstrated that overall contingency judgments are influenced by the causal structure of the events. Experiment 3 showed that trial-by-trial prediction responses, a second measure of causal assessment, were not influenced by the causal structure of the described events. Experiment 4 revealed that participants became less sensitive to the influence of the causal structure in both their ratings and their predictions as trials progressed. Thus, two experiments provided evidence for high-level (causal reasoning) processes, and two experiments provided evidence for low-level (associative) processes. We argue that both factors influence causal assessment, depending on what is being asked about the events and participants' experience with those events

A probabilistic constraint satisfaction model of information distortion in diagnostic reasoning.

Information distortion is a cognitive bias in sequential diagnostic reasoning. It means that assumptions about the diagnostic validity of later evidence are distorted in favor of the leading hypothesis. Therefore the bias contributes to a primacy effect. Current parallel constraint satisfaction models account for order effects and coherence shifts, but do not explain information distortion. As an alternative a new, probabilistic constraint satisfaction model is proposed, which considers uncertainty about diagnostic validity by defining probability distributions over coherence relations. Simulations based on the new model show that by shifting distributions in favor of the leading hypothesis an increase in coherence can be achieved. Thus the model is able to explain information distortion by assuming a need for coherence. It also accounts for a number of other recent findings on clinical diagnostic reasoning. Alternative models and necessary future research are discussed