Déterminants de la procrastination académique : motivation autodéterminée, estime de soi et degré de maximation

Maximization delays decision-making in acute care nursing

The maximization personality trait refers to the tendency to face decision-making situations along a continuum from exhaustively analysing all the options (maximize) to choosing the one that exceeds a subjective threshold of acceptability (satisfy). Research has revealed the influence of maximizing on decision making, although little is known about its possible role in high risk and high uncertainty situations. A sample of 153 active Spanish nurses, with an average experience of 11 years, completed a maximization questionnaire and responded to written vignettes depicting time-demanding decision making in which three options were offered, representing delayed action, non-action, and immediate action. Two vignettes presented critical situations related to acute care during the COVID-19 pandemic, whilst two vignettes presented non-nursing scenarios. People high in maximization took longer to choose and were more likely to choose non-action. No relationship was found between maximization score and the subjective experience of the person making the choice. Maximization had no significant correlation with years of experience nor perceived expertise. Greater perceived expertise was associated with lower indecision and greater confidence. When participants answered nursing vignettes, they took longer to respond, but chose less delayed action and more immediate action. Our results suggest that maximization plays only a relative role in acute care decision-making in nursing, as compared to contextual variables and expertise. They also support a domain general approach to this personality trait. Findings are consistent with Nibbelink and Reed's Practice-Primed Decision Model for nursing.

The Effect of a 3-Minute Mindfulness Intervention, and the Mediating Role of Maximization, on Critical Incident Decision-Making

OBJECTIVE

In this study, we extend the impact of mindfulness to the concept of least-worst decision-making. Least-worst decisions involve high-uncertainty and require the individual to choose between a number of potentially negative courses of action. Research is increasingly exploring least-worst decisions, and real-world events (such as the COVID-19 pandemic) show the need for individuals to overcome uncertainty and commit to a least-worst course of action. From sports to business, researchers are increasingly showing that "being mindful" has a range of positive performance-related benefits. We hypothesized that mindfulness would improve least-worst decision-making because it would increase self-reflection and value identification. However, we also hypothesized that trait maximization (the tendency to attempt to choose the "best" course of action) would negatively interact with mindfulness.

METHODS

Three hundred and ninety-eight participants were recruited using Amazon MTurk and exposed to a brief mindfulness intervention or a control intervention (listening to an audiobook). After this intervention, participants completed the Least-Worst Uncertain Choice Inventory for Emergency Responders (LUCIFER).

RESULTS

As hypothesized, mindfulness increased decision-making speed and approach-tendencies. Conversely, for high-maximizers, increased mindfulness caused a slowing of the decision-making process and led to more avoidant choices.

CONCLUSIONS

This study shows the potential positive and negative consequences of mindfulness for least-worst decision-making, emphasizing the critical importance of individual differences when considering both the effect of mindfulness and interventions aimed at improving decision-making.

Police Perfection: Examining the Effect of Trait Maximization on Police Decision-Making

Police officers around the world must often select between equally unappealing, uncertain courses of action in an attempt to achieve the best outcome. Despite the immense importance of such decisions, there remains a lack of understanding in the study of individual differences in police decision-making. Here, using a sample of senior police officers recruited from decision-making training events across the United Kingdom (n = 96), we used the Least-worst Uncertain Choice Inventory For Emergency Responses (LUCIFER) to measure the effect of maximization on both domain-specific (police) and domain-general (military) decisions. In line with a wealth of research on traditional "consumer" decisions, we found that police officers who were "maximizers" found decisions more difficult. Gender and previous military experience also influenced the process of decision-making. Specifically, police officers with military experience took more time to assess the situation but were faster to choose a course of action and commit to it. Female police officers also were slower to assess the situation. As recent events show, the outcomes of police decisions have significant consequences for the public, the officers involved, the police force as a whole, and the wider population, yet psychological research has yet to fully explore the role of individual differences in how such decisions are made. While this study does not seek to identify factors associated with "good" or "better" decision-makers, it provides strong support for the need to factor in perspectives of the individual when creating theory, or applied tools, in support of police decision-making.

Self-efficacy for self-regulation and fear of failure as mediators between self-esteem and academic procrastination among undergraduates in health professions

Academic procrastination has been a widespread problem behavior among undergraduates. This study aimed to examine the prevalence of academic procrastination among undergraduates in health professions, and explore the mediation effects of self-efficacy for self-regulation and fear of failure in the relationship between self-esteem and academic procrastination. A cross-sectional design was used to study 1184 undergraduates in health professions from China. Participants completed measures of academic procrastination, self-esteem, self-efficacy for self-regulation and fear of failure. We used Pearson product-moment correlation to examine the bivariate correlations between study variables, and path analysis to examine mediation. Among the 1184 undergraduates, 877 (74.1%) procrastinated on at least one type of academic task. The total score for academic procrastination was negatively correlated with scores for self-esteem and self-efficacy for self-regulation, and positively correlated with the score for fear of failure. Moreover, the relationship between self-esteem and academic procrastination was fully mediated by self-efficacy for self-regulation (indirect effect: β = - .15, 95% bootstrap CI - .19 to - .11) and fear of failure (indirect effect: β = - .06, 95% bootstrap CI - .09 to - .04). These findings suggest that interventions targeting the enhancement of self-efficacy for self-regulation and the conquest of fear of failure may prevent or reduce academic procrastination among undergraduates in health professions, especially for those with lower self-esteem.

On the meaning and measurement of maximization

Building on Herbert Simon’s critique of rational choice theory, Schwartz et al. (2002) proposed that when making choices, some individuals — maximizers — search extensively through many alternatives with the goal of making the best choice, whereas others — satisficers — search only until they identify an option that meets their standards, which they then choose. They developed the Maximization Scale (MS) to measure individual differences in maximization, and a substantial amount of research has now examined maximization using the MS, painting a picture of maximizers that is generally negative. Recently, however, several researchers have criticized the MS, and almost a dozen new measures of maximization have now been published, resulting in a befuddling and contradictory literature. We seek to clarify the confusing literature on the measurement of maximization to help make sense of the existing findings and to facilitate future research. We begin by briefly summarizing the understanding of maximizers that has emerged through research using Schwartz et al.’s MS. We then review the literature on the measurement of maximization, attempting to identify the similarities and differences among the 11 published measures of maximization. Next, we propose a two-component model of maximization, outlining our view of how maximization should be conceptualized and measured. Our model posits that maximization is best understood as the pursuit of the maximization goal of choosing the best option through the maximization strategy of alternative search; other constructs such as decision difficulty and regret are best considered outcomes or causes — rather than components — of maximization. We discuss the implications of our review and model for research on maximization, highlighting what we see as pressing unanswered questions and important directions for future investigations.