Background: Patients with schizophrenia and their families have suffered greatly from stigmatizing effects. Although many efforts have been made to eradicate both prejudice and stigma, they still prevail even among medical professionals, and little is known about how contact with schizophrenia patients affects their attitudes towards schizophrenia.Methods: We assessed the impact of the renaming of the Japanese term for schizophrenia on clinical residents and also evaluated the influence of contact with schizophrenia patients on attitudes toward schizophrenia by comparing the attitudes toward schizophrenia before and after a one-month clinical training period in psychiatry. Fifty-one clinical residents participated. Their attitudes toward schizophrenia were assessed twice, before and one month after clinical training in psychiatry using the Implicit Association Test (IAT) as well as Link’s devaluation-discrimination scale.Results: The old term for schizophrenia, “Seishin-Bunretsu-Byo”, was more congruent with criminal than the new term for schizophrenia, “Togo-Shitcho-Sho”, before clinical training. However, quite opposite to our expectation, after clinical training the new term had become even more congruent with criminal than the old term. There was no significant correlation between Link's scale and IAT effect.Conclusions: Renaming the Japanese term for schizophrenia still reduced the negative images of schizophrenia among clinical residents. However, contact with schizophrenia patients unexpectedly changed clinical residents’ attitudes towards schizophrenia negatively. Our results might contribute to an understanding of the formation of negative attitudes about schizophrenia and assist in developing appropriate clinical training in psychiatry that could reduce prejudice and stigma concerning schizophrenia.

Many practical decisions are more realistic concerning preventing bad decisions than seeking better ones. However, there has been no behavioral decision theory research on avoiding the worst decisions. This study is the first behavioral decision research on decision strategies from the perspective of avoiding the worst decisions. We conducted a computer simulation with the Mersenne Twister method and a psychological experiment using the monitoring information acquisition method for two-stage decision strategies of all combinations for different decision strategies: lexicographic, lexicographic semi-order, elimination by aspect, conjunctive, disjunctive, weighted additive, equally weighted additive, additive difference, and a majority of confirming dimensions. The rate of choosing the least expected utility value among the alternatives was computed as the rate of choosing the worst alternative in each condition. The results suggest that attention-based decision rules such as disjunctive strategy lead to a worse decision, and that striving to make the best choice can conversely often lead to the worst outcome. From the simulation and the experiment, we concluded that simple decision strategies such as considering what is most important can lead to avoiding the worst decisions. The findings of this study provide practical implications for decision support in emergency situations.

Previous studies on decision strategies in multi-attribute decision-making (MADM) have primarily relied on computational simulations to assess strategy performance under varying conditions, with particular emphasis on comparisons to the weighted additive rule (WAD) and on evaluations of the cognitive effort required. In contrast, considerably less attention has been devoted to examining the consistency of decision outcomes across different strategies or to developing a systematic classification of strategies based on outcome similarity. To address this gap, the present study investigates the characteristics of decision strategies by analyzing the concordance rates of choices made under identical conditions, along with measures of decision accuracy and information-processing effort. We conducted a hierarchical cluster analysis and applied multi-dimensional scaling (MDS) to a choice concordance matrix derived from simulations using the Mersenne Twister method. In addition, linear multiple regression analyses were performed using the MDS coordinates as predictors of both decision accuracy and cognitive effort. The cluster analysis revealed a primary bifurcation between two major groups: one centered around the Disjunctive (DIS) rule, and another encompassing compensatory strategies such as WAD. Notably, although the Lexicographic (LEX) rule is traditionally considered non-compensatory, it exhibited high similarity in choice patterns to compensatory strategies when assessed via concordance rates. In contrast, DIS-based strategies produced markedly distinct choice patterns.

Information tables are often used for decision making. This study considers multi-attribute table designs from a diagrammatic perspective. We used two experiments to show how the decision-making strategies and performance are changed based on table design changes, using the eye-tracking method. We employed a multi-attribute catalog table with alternatives presented along the horizontal axis and attributes along the vertical axis in Experiment 1 and the opposite layout in Experiment 2. In each experiment, we used four different types of representations of the attribute values, and these values were restricted to two levels for comparison with previous works. The four types used were: (i) numerical representations, (ii) textual representations, (iii) black-and-white representations with black representing better values, and (iv) black-and-while representations with white representing better values. Our results suggest, among others, that (1) placing the alternatives along the vertical axis makes the table easier to decide in comparison to the opposite layout, and that (2) the two-stage decision strategy is taken with numerical representations and textual representations, while a single stage strategy is taken with the black-and-white representations. We also showed how the graphic black-and-white representations made decision-making easier, and how the order changes of alternatives and of attributes of a table influenced decision makers’ decision.

Highlighting is widely used in tables and visualizations to guide users’ attention, yet its role in multi-attribute decision making remains unclear. We conducted an eye-tracking experiment using five-alternative × five-attribute tables representing digital audio players. The experiment compared three table conditions: (a) tables highlighting the better value for each attribute, (b) tables highlighting the largest value for each attribute, and (c) tables without highlighting. In half of the tables, trade-offs existed only between two alternatives (Dominance tables). Eye-movement analyses revealed that participants showed different information-search patterns between the first and second halves of the trials across all conditions, suggesting the use of a two-stage decision-making strategy. In Dominance tables, decisions were made fastest in condition (a), and the number of participants who made irrational choices was also smallest in this condition. These findings indicate that highlighting can facilitate the identification of dominance relations among alternatives and thereby support faster and more accurate decision-making in multi-attribute tables.