Walkercollier3812

Previous research has described physicians' reluctance to use computerized diagnostic aids (CDAs) but has never experimentally examined the effects of not consulting an aid that was readily available. Experiment 1. Participants read about a diagnosis made either by a physician or an auto mechanic (to control for perceived expertise). Half read that a CDA was available but never actually consulted; no mention of a CDA was made for the remaining half. For the physician, failure to consult the CDA had no significant effect on competence ratings for either the positive or negative outcome. For the auto mechanic, failure to consult the CDA actually increased competence ratings following a negative but not a positive outcome. Negligence judgments were greater for the mechanic than for the physician overall. Experiment 2. MSA-2 agonist Using only a negative outcome, we included 2 different reasons for not consulting the aid and provided accuracy information highlighting the superiority of the CDA over the physician. In neither condition was the physician rated lower than when no aid was mentioned. Ratings were lower when the physician did not trust the CDA and, surprisingly, higher when the physician believed he or she already knew what the CDA would say. Finally, consistent with our previous research, ratings were also high when the physician consulted and then followed the advice of a CDA and low when the CDA was consulted but ignored. Individual differences in numeracy did not qualify these results. Implications for the literature on algorithm aversion and clinical practice are discussed.Calibration of a microsimulation model (MSM) is a challenging but crucial step for the development of a valid model. Numerous calibration methods for MSMs have been suggested in the literature, most of which are usually adjusted to the specific needs of the model and based on subjective criteria for the selection of optimal parameter values. This article compares 2 general approaches for calibrating MSMs used in medical decision making, a Bayesian and an empirical approach. We use as a tool the MIcrosimulation Lung Cancer (MILC) model, a streamlined, continuous-time, dynamic MSM that describes the natural history of lung cancer and predicts individual trajectories accounting for age, sex, and smoking habits. We apply both methods to calibrate MILC to observed lung cancer incidence rates from the Surveillance, Epidemiology and End Results (SEER) database. We compare the results from the 2 methods in terms of the resulting parameter distributions, model predictions, and efficiency. Although the empirical method proves more practical, producing similar results with smaller computational effort, the Bayesian method resulted in a calibrated model that produced more accurate outputs for rare events and is based on a well-defined theoretical framework for the evaluation and interpretation of the calibration outcomes. A combination of the 2 approaches is an alternative worth considering for calibrating complex predictive models, such as microsimulation models.Turning an object upside-down disrupts our ability to perceive it accurately, and this inversion effect is disproportionately larger for faces and whole bodies than most other objects. This disproportionate inversion effect is taken as an indicator of holistic processing for these stimuli. Large inversion effects are also found when viewing motion-only information from faces and bodies; however, these have not been compared to other moving objects in an identity task so it is unclear whether inversion effects remain disproportionately larger for faces and bodies when they are engaged in motion. The current study investigated the effect of inversion on static and moving unfamiliar faces, human bodies, and German Shepherd dogs in an old-new recognition memory task. Sensitivity and baseline corrected reaction time (RT) results revealed that inversion effects for faces and whole-bodies remained disproportionately larger than those for German Shepherd dogs, regardless of presentation type, suggesting that both static and moving faces and bodies are processed holistically.

Shared decision making integrates health care provider expertise with patient values and preferences. The MAPPIN'SDM is a recently developed measurement instrument that incorporates physician, patient, and observer perspectives during medical consultations. This review sought to critically appraise the development, sensibility, reliability, and validity of the MAPPIN'SDM and to determine in which settings it has been used.

This critical appraisal was performed through a targeted review of the literature. Articles outlining the development or measurement property assessment of the MAPPIN'SDM or that used the instrument for predictor or outcome purposes were identified.

Thirteen studies were included. The MAPPIN'SDM was developed by both adapting and building on previous shared decision making measurement instruments, as well as through creation of novel items. Content validity, face validity, and item quality of the MAPPIN'SDM are adequate. Internal consistency ranged from 0.91 to 0.94 and agreement statistics from 0.41 to 0.92. The MAPPIN'SDM has been evaluated in several populations and settings, ranging from chronic disease to acute oncological settings. Limitations include high reading levels required for self-administered patient questionnaires and the small number of studies that have employed the instrument to date.

The MAPPIN'SDM generally shows adequate development, sensibility, reliability, and validity in preliminary testing and holds promise for shared decision making research integrating multiple perspectives. Further research is needed to develop its use in other patient populations and to assess patient understanding of complex item wording.

The MAPPIN'SDM generally shows adequate development, sensibility, reliability, and validity in preliminary testing and holds promise for shared decision making research integrating multiple perspectives. Further research is needed to develop its use in other patient populations and to assess patient understanding of complex item wording.