A dynamic, computational model of job insecurity and job performance.

Despite decades of research, there is little empirical or theoretical consensus around how job insecurity shapes job performance. This article introduces an ecumenical, dynamic, and computational model of the job insecurity-job performance relationship. That is, rather than representing a single theoretical perspective on job insecurity effects, the model includes three key mechanisms through which job insecurity is theorized to impact performance-stress, social exchange, and job preservation motivation-and grounds these in a self-regulatory computational architecture. The model incorporates multiple, dynamic feedback loops that include job performance and job insecurity, as well as individual difference and contextual constructs to project the immediate, short-term, and long-term effects of changes to job security and other important variables. Simulations of the model demonstrate that a self-regulating representation of human information processing can produce effects consistent with the major propositions in the job insecurity literature. Moreover, interrupted time-series simulations of a new job insecurity threat reveal how, when, and why performance can stabilize above, near, or below baseline performance levels, sometimes for counterintuitive reasons. Additionally, the model shows how the frequently reported, cross-sectional, negative relationship between job insecurity and job performance can be explained by job performance's influence on job insecurity. The results imply important considerations and directions for future job insecurity research and demonstrate the value of a formal, dynamic systems approach to theorizing. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Changes in affect during the pursuit of performance goals.

The aim of this article is to examine how affect changes when people are pursuing performance goals. We do this using the circumplex model of affect, in which a person's current affective state is represented as a point on a plane defined by the latent dimensions of pleasure and activation. We test competing hypotheses regarding the direction of changes within this 2-dimensional space. The first set of hypotheses are derived from Carver and Scheier's (1998) theory of self-regulation, which predicts that changes in the prospects of goal attainment should produce changes along axes offset 45° from the pleasure and activation dimensions. The second set of hypotheses are derived from the concept of core affect (Russell, 2003), which predicts that changes in the prospects of goal attainment should produce changes in pleasure, while changes in task demands should produce changes in activation. Two studies are reported in which participants provided ratings of momentary affect during goal pursuit. We developed a latent change model to estimate the direction and magnitude of changes in affect attributable to changes in the prospects of goal attainment and task demand. The results are more consistent with the hypotheses derived from the core affect account than with the hypotheses derived from the Carver and Scheier account. Theoretical and practical implications are discussed, with a focus on prospects for the development of an integrative theory, which accounts for both the motivational and affective components of goal pursuit. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Interpreting moderated multiple regression: A comment on Van Iddekinge, Aguinis, Mackey, and DeOrtentiis (2018).

When data contradict theory, data usually win. Yet, the conclusion of Van Iddekinge, Aguinis, Mackey, and DeOrtentiis (2018) that performance is an additive rather than multiplicative function of ability and motivation may not be valid, despite applying a meta-analytic lens to the issue. We argue that the conclusion was likely reached because of a common error in the interpretation of moderated multiple-regression results. A Monte Carlo study is presented to illustrate the issue, which is that moderated multiple regression is useful for detecting the presence of moderation but typically cannot be used to determine whether or to what degree the constructs have independent or nonjoint (i.e., additive) effects beyond the joint (i.e., multiplicative) effect. Moreover, we argue that the practice of interpreting the incremental contribution of the interaction term when added to the first-order terms as an effect size is inappropriate, unless the interaction is perfectly symmetrical (i.e., X-shaped), because of the partialing procedure that moderated multiple regression uses. We discuss the importance of correctly specifying models of performance as well as methods that might facilitate drawing valid conclusions about theories with hypothesized multiplicative functions. We conclude with a recommendation to fit the entire moderated multiple-regression model in a single rather than separate steps to avoid the interpretation error highlighted in this article. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

A formal model of leadership goal striving: Development of core process mechanisms and extensions to action team context.

This research develops and tests a formal process-oriented theory of leader goal striving. Drawing on self-regulation theory, we developed a computational model that explicates the core process mechanisms involved in a leader-subordinate dyadic goal pursuit system. We then extended this core model to incorporate action team features (i.e., negative external disturbances, deadlines, and task interdependence) to account for leadership behavior in action team context. We simulated our proposed model to generate predictions about trajectories of a critical leadership function (i.e., leader engaging in team task-specific actions) under different conditions of disturbances, deadlines, task interdependence, and leader attributes. The predicted relationships were then tested in a laboratory experiment. As predicted by the model, time-related factors, including disturbances and deadlines, had significant effects on trajectories of leader actions. Over time within a given task, leaders were more likely to take actions when further than closer to the deadline. Leaders were also more likely to take actions when external disturbances set task states back. In addition, leaders' time allocation was less evenly distributed across subordinates when the deadline was short (vs. long). We discussed the implications of the model and how future research can extend our model to account for more complicated goal pursuit and team processes. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

On the pursuit of multiple goals with different deadlines.

This article presents a theory of how people prioritize their time when pursuing goals with different deadlines. Although progress has been made in understanding the dynamics of multiple-goal pursuit, theory in this area only addresses cases where the goals have the same deadline. We rectify this issue by integrating the multiple-goal pursuit model-a formal theory of multiple goal pursuit-with theories of intertemporal motivation and choice. We examine the ability of four computational models derived from this general theory to account for participants' choices across four experiments. The models make different assumptions about how people determine the valence of prioritizing a goal (i.e., by monitoring distance to goal or time pressure), and whether the goal is subject to temporal discounting. In each experiment, participants performed a task requiring them to pursue two goals. Experiments 1 and 2 manipulated deadline and distance; Experiment 3 manipulated deadline and time pressure; Experiment 4 manipulated all three factors. Counter to the predictions of existing theory, participants generally prioritized the goal with the shorter deadline. We also observed weak, but positive effects of distance on prioritization (Experiment 2) and nonlinear effects of time pressure (Experiment 3). The model that best explained participants' decisions assumed that valence is determined by time pressure and the expected utility of a goal is subject to temporal discounting. This new model broadens the range of phenomena that can be accounted for within a single theory of multiple-goal pursuit, and improves our understanding of the interface between motivation and decision making. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

A computational model of self-efficacy's various effects on performance: Moving the debate forward.

Self-efficacy, which is one's belief in one's capacity, has been found to both positively and negatively influence effort and performance. The reasons for these different effects have been a major topic of debate among social-cognitive and perceptual control theorists. In particular, the findings of various self-efficacy effects has been motivated by a perceptual control theory view of self-regulation that social-cognitive theorists' question. To provide more clarity to the theoretical arguments, a computational model of the multiple processes presumed to create the positive, negative, and null effects for self-efficacy is presented. Building on an existing computational model of goal choice that produces a positive effect for self-efficacy, the current article adds a symbolic processing structure used during goal striving that explains the negative self-efficacy effect observed in recent studies. Moreover, the multiple processes, operating together, allow the model to recreate the various effects found in a published study of feedback ambiguity's moderating role on the self-efficacy to performance relationship (Schmidt & DeShon, 2010). Discussion focuses on the implications of the model for the self-efficacy debate, alternative computational models, the overlap between control theory and social-cognitive theory explanations, the value of using computational models for resolving theoretical disputes, and future research and directions the model inspires. (PsycINFO Database Record

An integrative formal model of motivation and decision making: The MGPM*.

We develop and test an integrative formal model of motivation and decision making. The model, referred to as the extended multiple-goal pursuit model (MGPM*), is an integration of the multiple-goal pursuit model (Vancouver, Weinhardt, & Schmidt, 2010) and decision field theory (Busemeyer & Townsend, 1993). Simulations of the model generated predictions regarding the effects of goal type (approach vs. avoidance), risk, and time sensitivity on prioritization. We tested these predictions in an experiment in which participants pursued different combinations of approach and avoidance goals under different levels of risk. The empirical results were consistent with the predictions of the MGPM*. Specifically, participants pursuing 1 approach and 1 avoidance goal shifted priority from the approach to the avoidance goal over time. Among participants pursuing 2 approach goals, those with low time sensitivity prioritized the goal with the larger discrepancy, whereas those with high time sensitivity prioritized the goal with the smaller discrepancy. Participants pursuing 2 avoidance goals generally prioritized the goal with the smaller discrepancy. Finally, all of these effects became weaker as the level of risk increased. We used quantitative model comparison to show that the MGPM* explained the data better than the original multiple-goal pursuit model, and that the major extensions from the original model were justified. The MGPM* represents a step forward in the development of a general theory of decision making during multiple-goal pursuit. (PsycINFO Database Record

A formal, computational theory of multiple-goal pursuit: integrating goal-choice and goal-striving processes.

Understanding the processes involved when pursuing multiple goals over time is a central question for motivational theorists. A dynamic, computational model integrating theories of goal striving and goal choice is presented to account for data emerging from Schmidt and DeShon's (2007) multiple-goal-pursuit protocol. The simulated results match the results reported in their study, including the finding that relative discrepancy from the goals positively predicted resource allocation early on but negatively predicted it toward the end of the session. Variance in parameters in the model also accounted for individual differences found in the data. Discussion focuses on the theoretical contribution of formally integrating elements of self-regulation theories, further empirical work needed to test the model, and further theoretical work needed to continue the integration process exemplified here.

Self-efficacy and resource allocation: support for a nonmonotonic, discontinuous model.

Self-regulation theories are paving the way to integrating motivational theories of behavior. However, a review of the motivation literature reveals several possible relationships between self-efficacy and motivation. Past findings were reduced to 4 empirical models, which were compared within a single study using undergraduates playing a computer task. The effects of 2 manipulations of self-efficacy on resource allocation decisions were assessed. Consistent with a multiple goal process conceptualization, self-efficacy was found to relate positively to directing resources toward a goal but negatively to the magnitude of resources allocated for accepted goals. Differences in methods are used to reconcile current and past findings.

When self-efficacy negatively relates to motivation and performance in a learning context.

Recent reviews of the training literature have advocated directly manipulating self-efficacy in an attempt to improve the motivation of trainees. However, self-regulation theories conceive of motivation as a function of various goal processes, and assert that the effect of self-efficacy should depend on the process involved. Training contexts may evoke planning processes in which self-efficacy might negatively relate to motivation. Yet the typical between-persons studies in the current literature may obscure the effect. To examine this issue, 63 undergraduate students completed a series of questionnaires measuring self-efficacy and motivation before 5 class exams. Self-efficacy was negatively related to motivation and exam performance at the within-person level of analysis, despite a significant positive relation with performance at the between-persons level.

School-based mental health programming for children with inattentive and disruptive behavior problems: first-year treatment outcome.

This article examines the effectiveness of an evidence-based behavioral treatment package for children with inattentive and disruptive behavior problems when delivered in the context of a school-based mental health program. Child symptomatology and functioning are assessed in a treatment group (n = 30) and a waitlist control group (n = 12) across multiple time points (fall, winter, and spring). Treatment includes a daily report card procedure, year-long teacher consultation, and parenting sessions. According to the parent report, treated children show marked reductions in hyperactive and impulsive, oppositional or defiant and aggressive behavior, and marked improvement in peer relationships. Teachers observe treatment-related group differences in inattention, academic functioning, and the student-teacher relationship. Feasibility and acceptability data have implications for transporting evidence-based treatments to community settings and for integrating mental health services into the culture of the school community.

The depth of history and explanation as benefit and bane for psychological control theories.

A longstanding debate has recently re-erupted in the self-regulation literature around the concept of self-efficacy. This article presents an argument that the debate emerges from a lack of understanding of the history of control theories within both the social and physical sciences and the various levels of explanation to which phenomena can be subjected. This history, coupled with the issues of determinism, materialism, and empiricism evoked by the deeper level of explanation that some versions of control theory provide, has led some critics to mis-apply non-psychological properties to control theories and obscure their usefulness. Here, the usefulness of a deeper control theory level of explanation is illustrated using comparisons with explanations found in goal-setting theory and social cognitive theory.

The effect of feedback sign on task performance depends on self-concept discrepancies.

Control theories claim that information about performance is often used by multiple goal systems. A proposition tested here was that performance information can create discrepancies in self-concept goals, directing cognitive resources away from the task goal system. To manipulate performance information, 160 undergraduates were given false positive or false negative normative feedback while working on a task that did or did not require substantial cognitive resources. Half of the participants were then given an opportunity to reaffirm their self-concepts following feedback, whereas half were not. Feedback sign positively related to performance only for those working on the cognitively intense task and not given a chance to reaffirm. Otherwise, feedback sign was negatively related to performance, albeit weakly.

Two studies examining the negative effect of self-efficacy on performance.

Although hundreds of studies have found a positive relationship between self-efficacy and performance, several studies have found a negative relationship when the analysis is done across time (repeated measures) rather than across individuals. W. T. Powers (1991) predicted this negative relationship based on perceptual control theory. Here, 2 studies are presented to (a) confirm the causal role of self-efficacy and (b) substantiate the explanation. In Study 1, self-efficacy was manipulated for 43 of 87 undergraduates on an analytic game. The manipulation was negatively related to performance on the next trial. In Study 2, 104 undergraduates played the analytic game and reported self-efficacy between each game and confidence in the degree to which they had assessed previous feedback. As expected, self-efficacy led to overconfidence and hence increased the likelihood of committing logic errors during the game.