Major recent interpretations of the conjunction fallacy postulate that people assess the probability of a conjunction according to (non-normative) averaging rules as applied to the constituents' probabilities or represent the conjunction fallacy as an effect of random error in the judgment process. In the present contribution, we contrast such accounts with a different reading of the phenomenon based on the notion of inductive confirmation as defined by contemporary Bayesian theorists. Averaging rule hypotheses along with the random error model and many other existing proposals are shown to all imply that conjunction fallacy rates would rise as the perceived probability of the added conjunct does. By contrast, our account predicts that the conjunction fallacy depends on the added conjunct being perceived as inductively confirmed. Four studies are reported in which the judged probability versus confirmation of the added conjunct have been systematically manipulated and dissociated. The results consistently favor a confirmation-theoretic account of the conjunction fallacy against competing views. Our proposal is also discussed in connection with related issues in the study of human inductive reasoning.

Background The use of mobile health (mHealth) apps in clinical settings is increasing widely. mHealth has been used to promote prevention, improve early detection, manage care, and support survivors and chronic patients. However, data on the efficacy and utility of mHealth apps are limited. Objective The main objective of this review was to provide an overview of the available research-tested interventions using mHealth apps and their impact on breast cancer care. Methods A systematic search of Medline, PsycINFO, Embase, and Scopus was performed to identify relevant studies. From the selected studies, the following information was extracted: authors, publication date, study objectives, study population, study design, interventions’ features, outcome measures, and results. Results We identified 29 empirical studies that described a health care intervention using an mHealth app in breast cancer care. Of these, 7 studies were about the use of an mHealth application in an intervention for breast cancer prevention and early detection, 12 targeted care management, and 10 focused on breast cancer survivors. Conclusions Our results indicate consistent and promising findings of interventions using mHealth apps that target care management in breast cancer. Among the categories of mHealth apps focusing on survivorship, mHealth-based interventions showed a positive effect by promoting weight loss, improving the quality of life, and decreasing stress. There is conflicting and less conclusive data on the effect of mHealth apps on psychological dimensions. We advocate further investigation to confirm and strengthen these findings. No consistent evidence for the impact of interventions using mHealth apps in breast cancer prevention and early detection was identified due to the limited number of studies identified by our search. Future research should continue to explore the impact of mHealth apps on breast cancer care to build on these initial recommendations.

Current widespread facemask usage profoundly impacts clinical practice and healthcare education where communicational dimensions are essential to the care and teaching processes. As part of a larger study, 208 medical and nursing students were randomly assigned to a masked vs unmasked version of the standardized facial emotion recognition task DANVA2. A significantly higher number of errors existed in the masked vs unmasked condition. Differences for happy, sad, and angry faces, but not for fearful faces, existed between conditions. Misinterpretation of facial emotions can severely affect doctorpatient and inter-professional communication in healthcare. Teaching communication in medical education must adapt to the current universal use of facemasks in professional settings.

Background: Research has been mainly focused on how to elicit patient preferences, with less attention on why patients form certain preferences. Objectives: To assess which psychological instruments are currently used and which psychological constructs are known to have an impact on patients' preferences and health-related decisions including the formation of preferences and preference heterogeneity. Methods: A systematic database search was undertaken to identify relevant studies. From the selected studies, the following information was extracted: study objectives, study population, design, psychological dimensions investigated, and instruments used to measure psychological variables. Results: Thirty-three studies were identified that described the association between a psychological construct, measured using a validated instrument, and patients' preferences or health-related decisions. We identified 33 psychological instruments and 18 constructs, and categorized the instruments into 5 groups, namely, motivational factors, cognitive factors, individual differences, emotion and mood, and health beliefs. Conclusions: This review provides an overview of the psychological factors and related instruments in the context of patients' preferences and decisions in healthcare settings. Our results indicate that measures of health literacy, numeracy, and locus of control have an impact on healthrelated preferences and decisions. Within the category of constructs that could explain preference and decision heterogeneity, health locus of control is a strong predictor of decisions in several healthcare contexts and is useful to consider when designing a patient preference study. Future research should continue to explore the association of psychological constructs with preference formation and heterogeneity to build on these initial recommendations.

Three experiments examined how people gather information on in-group and out-group members. Previous studies have revealed that category-based expectancies bias the hypothesis-testing process towards confirmation through the use of asymmetric-confirming questions (which are queries where the replies supporting the prior expectancies are more informative than those falsifying them). However, to date there is no empirical investigation of the use of such a question-asking strategy in an intergroup context. In the present studies, participants were asked to produce (Study 1) or to choose (Studies 2 and 3) questions in order to investigate the presence of various traits in an in-group or an out-group member. Traits were manipulated by valence and typicality. The results revealed that category-based expectancies do not always lead to asymmetric-confirming testing: whereas participants tended to ask questions that confirmed positive in-group and negative out-group stereotypical attributes, they used a more symmetric strategy when testing for the presence of negative in-group or positive out-group traits. Moreover, Study 3 also revealed a moderation effect of in-group identification. The findings point to the role played by motivational factors associated with preserving a positive social identity. Possible consequences of these hypothesis-testing processes in preserving a positive social identity for intergroup relations are discussed.

Objectives: Patient preference information (PPI) is gaining recognition among the pharmaceutical industry, regulatory authorities, and health technology assessment (HTA) bodies/payers for use in assessments and decision-making along the medical product lifecycle (MPLC). This study aimed to identify factors and situations that influence the value of patient preference studies (PPS) in decision-making along the MPLC according to different stakeholders. Methods: Semi-structured interviews (n = 143) were conducted with six different stakeholder groups (physicians, academics, industry representatives, regulators, HTA/payer representatives, and a combined group of patients, caregivers, and patient representatives) from seven European countries (the United Kingdom, Sweden, Italy, Romania, Germany, France, and the Netherlands) and the United States. Framework analysis was performed using NVivo 11 software. Results: Fifteen factors affecting the value of PPS in the MPLC were identified. These are related to: study organization (expertise, financial resources, study duration, ethics and good practices, patient centeredness), study design (examining patient and/or other preferences, ensuring representativeness, matching method to research question, matching method to MPLC stage, validity and reliability, cognitive burden, patient education, attribute development), and study conduct (patients’ ability/willingness to participate and preference heterogeneity). Three types of situations affecting the use of PPS results were identified (stakeholder acceptance, market situations, and clinical situations). Conclusion: The factors and situation types affecting the value of PPS, as identified in this study, need to be considered when designing and conducting PPS in order to promote the integration of PPI into decision-making along the MPLC.

These results might be used to develop tailored psycho-educational interventions. This might help healthcare professionals to develop personal skills to cope with the critical conditions that characterise their work and to enable them to recognise potential risk factors that favour burnout. This has pivotal implications for the maintenance of the patient-healthcare professional relationship and in reducing clinical errors.

In three studies, we investigated whether and to what extent the evaluation of two mutually exclusive hypotheses is affected by a feature-positive effect, wherein present clues are weighted more than absent clues. Participants (N = 126) were presented with abstract problems concerning the most likely provenance of a card that was drawn from one of two decks. We factored the correct response (the hypothesis favored by the consideration of all clues) and the ratio of present-to-absent features in each set of observations. Furthermore, across the studies, we manipulated the presentation format of the features' probabilities by providing the probability distributions of occurrences (Study 1), non-occurrences (Study 3) or both (Study 2). In all studies, both participant preference and accuracy were mostly determined by an over-reliance on present features. Moreover, across participants, both confidence in the responses and the informativeness of the present clues correlated positively with the number of responses given in line with an exclusive consideration of present features. These results were mostly independent of both the rarity of the absent clues and the presentation format. We concluded that the feature-positive effect influences hypothesis evaluation, and we discussed the implications for confirmation bias.