Persistence Decisions Research Articles

A Longitudinal Examination of Four Processual Mechanisms in Career Decision Making

The dual-process theory of career decision making (DTC) proposes four processual mechanisms that explain the career decision-making process and outcomes. Although research has examined the validity of the four processual mechanisms using a cross-sectional dataset in China, the roles of the four mechanisms in career decision making cannot be fully established without longitudinal and cross-cultural analyses. Using a sample of U.S. college students ( n = 206), the current study examined the validity of the four processual mechanisms in explaining the joint operation of five major decision-making difficulties with subsequent career decidedness as the criterion. The results supported not only the standalone mechanisms of managing state and persistent decision uncertainty but also the joint mechanisms from managing state (persistent) uncertainty to managing persistent (state) uncertainty. Therefore, the current study adds evidence to the DTC, particularly regarding the scientific and practical necessity of differentiating between state and persistent decision uncertainty and between reducing uncertainty and reducing the threat of uncertainty. Additionally, the current study offers interesting implications for the interplay of major decision difficulties across different sociocultural contexts of China and the U.S.

Statistical information about reward timing is insufficient for promoting optimal persistence decisions

When deciding how long to keep waiting for delayed rewards that will arrive at an uncertain time, different distributions of possible reward times dictate different optimal strategies for maximizing reward. When reward timing distributions are heavy-tailed (e.g., waiting on hold) there is a point at which waiting is no longer advantageous because the opportunity cost of waiting is too high. Alternatively, when reward timing distributions have more predictable timing (e.g., uniform), it is advantageous to wait as long as necessary for the reward. Although people learn to approximate optimal strategies, little is known about how this learning occurs. One possibility is that people learn a general cognitive representation of the probability distribution that governs reward timing and then infer a strategy from that model of the environment. Another possibility is that they learn an action policy in a way that depends more narrowly on direct task experience, such that general knowledge of the reward timing distribution is insufficient for expressing the optimal strategy. Here, in a series of studies in which participants decided how long to persist for delayed rewards before quitting, we provided participants with information about the reward timing distribution in several ways. Whether the information was provided through counterfactual feedback (Study 1), previous exposure (Studies 2a and 2b), or description (Studies 3a and 3b), it did not obviate the need for direct, feedback-driven learning in a decision context. Therefore, learning when to quit waiting for delayed rewards might depend on task-specific experience, not solely on probabilistic reasoning.

A Process Model of Career Decision-Making and Adaptation Under Uncertainty: Expanding the Dual-Process Theory of Career Decision-Making

The dual-process theory of career decision-making (DTC; Xu, 2021a ; 2021b ) resulted from a synthesized and critical reflection of career decision-making and related models in the contemporary psychosocial context of career development. The DTC features persistent decision uncertainty as a salient condition of contemporary career decision-making, and its theoretical framework and predictive model establish DTC’s conceptual and empirical foundation, respectively. However, the DTC and the career decision-making literature in general still lack a process-oriented prescriptive model that foregrounds decision uncertainty. Consequently, the extant literature fails to prescribe key decision-making components and procedures under decision uncertainty. Thus, drawing on the DTC, decision-making science, and existing models of career decision-making, we propose a four-stage process model, which involves four interlinked macro stages and micro steps within each stage. The model also involves five propositions to explain and predict the effects of important personal and environmental factors on the process and outcomes of each stage. We describe the DTC process model and use a case example to illustrate how the model can be applied in practice. Together, the DTC’s theoretical framework, predictive model, and process-oriented prescriptive model constitute a comprehensive theory regarding dynamic career decision-making and adaption in an uncertain world and offer diverse research and practical implications.

IoMT-Enabled Real-Time Blood Glucose Prediction With Deep Learning and Edge Computing

Blood glucose (BG) prediction is essential to the success of glycemic control in type 1 diabetes (T1D) management. Empowered by the recent development of the Internet of Medical Things (IoMT), continuous glucose monitoring (CGM) and deep learning technologies have been demonstrated to achieve the state of the art in BG prediction. However, it is challenging to implement such algorithms in actual clinical settings to provide persistent decision support due to the high demand for computational resources, while smartphone-based implementations are limited by short battery life and require users to carry the device. In this work, we propose a new deep learning model using an attention-based evidential recurrent neural network and design an IoMT-enabled wearable device to implement the embedded model, which comprises a low-cost and low-power system on a chip to perform Bluetooth connectivity and edge computing for real-time BG prediction and predictive hypoglycemia detection. In addition, we developed a smartphone app to visualize BG trajectories and predictions, and desktop and cloud platforms to backup data and fine-tune models. The embedded model was evaluated on three clinical data sets including 47 T1D subjects. The proposed model achieved superior performance of root mean square error (RMSE), mean absolute error, and glucose-specific RMSE, and obtained the best accuracy for hypoglycemia detection when compared with a group of machine learning baseline methods. Moreover, we performed hardware-in-the-loop in silico trials with ten virtual T1D adults to test the whole IoMT system with predictive low-glucose management, which significantly reduced hypoglycemia and improved BG control.

Career calculus: Assessing the psychological cost of pursuing an engineering career

AbstractBackgroundPersonal characteristics (e.g., race/ethnicity, gender, and precollege experiences) are known to shape students' pathways to engineering, as well as persistence decisions in college. However, the role of psychological cost in postgraduation intentions has received less scholarly attention.PurposeThe purpose of this study is to examine sociocognitive factors that shape students' postgraduation intentions in the early college years. Guided by Social Cognitive Career Theory and the concept of psychological cost, we examine the role of self‐efficacy beliefs, outcome expectations, and psychological cost, as well as key background characteristics, in students' postgraduation intentions.MethodWe analyzed survey responses from four cohorts of undergraduate engineering students at a large public university. Participants responded to items measuring self‐efficacy beliefs, outcome expectations, and psychological cost after their first and second years of college. We used structural equation modeling to examine the relationships between the sociocognitive variables and students' graduate school and career intentions.ResultsThe sociocognitive variables predicting postgraduation intentions after Year 1 differed from those predicting intentions after Year 2. After Year 1, we found no statistically significant sociocognitive variables predicting graduate school intentions or engineering career plans. After Year 2, both self‐efficacy and outcome expectations were significant predictors of postgraduation intentions. The psychological cost was significantly related to both self‐efficacy and outcome expectations. Finally, we found significant differences in racial/ethnic identity, sex, and first‐generation status.ConclusionExamining psychological cost provides additional insights into the factors informing students' postgraduation intentions over the course of their collegiate careers and suggests new directions for research on students' thinking about engineering careers.

The Role of Socioemotional Wealth in Entrepreneurial Persistence Decisions for Family Businesses

Many factors may influence entrepreneurial persistence in various contexts. For example, scholars find that family business entrepreneurs are more persistent than other entrepreneurs. However, the reasons why they are more persistent are not as well known. Utilizing a conjoint experiment with 64 entrepreneurs and 376 decisions, this paper examines the influence of socioemotional wealth (SEW) on persistence decisions in a family business context. The results of the Hierarchical Linear Modelling show that the expected financial returns, expected non-financial benefits, expected switching costs, and probability of expected outcomes influence entrepreneurial persistence decisions. Further, family business entrepreneurs with higher levels of SEW focus more on non-financial benefits when facing alternative opportunities. This study also provided empirical evidence for different dimensions of SEW. The results show that the emotional attachment of family members and the renewal of family bonds to the firm are effective indicators, which provide a direct measurement of SEW. The findings of this study increase scholarly understanding of both entrepreneurial persistence literature founded in threshold theory and SEW literature.

Persist or let it go: Do rational entrepreneurs make decisions rationally?

We theorize that both highly rational entrepreneurs and entrepreneurs with a high need for cognitive closure (NFCC) are likely to put more emphasis on retrospective factors (period and degree of underperformance, personal investments) and less on prospective factors (risk of going into default, potential for growth, personal options) when deciding whether to persist with an underperforming venture. Our findings from three discrete choice experiments with three independent samples of entrepreneurs (a sample of 176 Australian entrepreneurs; a narrow-replication with 128 Australian entrepreneurs; and a quasi-replication with 157 United Kingdom entrepreneurs) consistently show that entrepreneurs who perceive themselves as rational do not always demonstrate rational behavior and entrepreneurs with a high NFCC put more emphasis on retrospective factors in persistence decisions. Important theoretical and practical contributions flowing from our study are shared in the concluding section.

Do Rational Entrepreneurs Exit Rationally?

While theory suggests that highly rational entrepreneurs and with high need for cognitive closure (NFCC) are likely to put stronger emphasis on retrospective performance and personal factors when deciding whether to persist with an underperforming venture, our findings from a discrete choice experiment with 177 entrepreneurs show mixed evidence, thereby challenging existing research. Overall, we find that entrepreneurs who perceive themselves as rational do not always demonstrate rational behavior in persistence decisions and entrepreneurs with high NFCC pay significantly more attention to retrospective performance, but not to prospective performance and personal options.

The Roles of Personality and Regulatory Focus in Entrepreneurial Persistence Decisions

The decision for entrepreneurs of whether to persist with a new business or discontinue its operation when confronted with negative feedback from the market is one of the most challenging decisions...

Neural responses to negative events and subsequent persistence behavior differ in individuals recovering from opioid use disorder compared to controls

ABSTRACT Background: Negative emotion is associated with substance craving and use in individuals recovering from substance use disorders, including prescription opioid use disorder (POUD). Decisions to abandon or persist towards a goal after negative emotion-eliciting events, and neural responses that shape such decisions, may be important in maintaining recovery from POUD. Objectives: We examined differences in neural responses to negative events and subsequent persistence decisions in individuals recovering from POUD without a history of a substance use disorder. Methods: 20 individuals with POUD (POUD group: 4 females, abstinent 2–3 weeks after admission to an inpatient treatment facility post-detoxification, no other substance use disorder), and 20 individuals with no substance use history (control group: 6 females) completed a persistence-after-setbacks task during functional magnetic resonance imaging. Participants advanced along a path toward a reward; after encountering each negative event (i.e., progress-erasing setback), participants made decisions to persist or abandon the path. Persistence decision rates were compared between groups and blood-oxygen-level-dependent signal to negative events was analyzed within a striatum region of interest (ROI) as well as whole-brain. Results: The POUD group persisted less (t(38) = 2.293, p = .028, d = .725) and showed lower striatum (left ventral putamen) signal to negative events compared to the control group (p < .05, corrected for striatum ROI). Conclusions: In POUD, neural and behavioral responses to negative events differ from controls. These differences are a target for research to address whether POUD treatment increases persistence and striatum responses to negative events and improves recovery outcomes.

When owner, family, and community roles intertwine: Examining entrepreneurs’ persistence decisions and the gender effect

ABSTRACT Entrepreneurs play multiple roles in their daily lives, and these roles can influence their decisions. Yet we know little about how entrepreneurs respond to simultaneous influences from different domains. We examine how entrepreneurs’ persistence decisions are jointly influenced by owner role pressure, family role pressure, and community role pressure and whether female and male entrepreneurs make decisions differently. Results indicate that owner role pressure interacts with family role pressure to influence persistence decisions. Further, female entrepreneurs are influenced more by owner role pressure, but interestingly, male entrepreneurs are influenced more by community role pressure. Our research suggests that entrepreneurs should be aware of the role pressure driving their persistence with underperforming ventures. Educators and support organizations can direct entrepreneurs’ attention to the multiple roles they play in life and increase their awareness of how persistence decisions can be jointly influenced by those roles and the gender differences in the decisions.

Academic Stress and Persistence Decisions Among Din� Students Attending Din� College

Academic Stress and Persistence Decisions Among Din� Students Attending Din� College

Academic Stress and Persistence Decisions Among Diné Students Attending Diné College

Academic Stress and Persistence Decisions Among Diné Students Attending Diné College

Examining the Relationship Between Psychosocial and Academic Outcomes in Higher Education: A Descriptive Analysis

This article estimates the relationship between students’ psychosocial and academic outcomes during their first 3 years enrolled at public, 4-year institutions. Our sample comprises students from low-income backgrounds who applied for a competitive scholarship and enrolled at a 4-year public institution. We follow two cohorts of entering students throughout their first 3 years on campus. We observe their cumulative grade point average and persistence decisions each semester, and have annual measures of four psychosocial outcomes: mattering to campus, sense of belonging to campus, academic self-efficacy, and social self-efficacy. We find that psychosocial outcomes are moderately predictive of academic outcomes, with sense of belonging and academic self-efficacy emerging as most predictive of both cumulative grade point avaerage and persistence.

An evaluation of online students’ persistence intentions

PurposeThe high dropout rate among online learning students is a serious issue. Using the theory of planned behavior as a framework, this study investigates what effect attitude, opinion of others and perceived ease of online learning technologies leave on Pakistani online students' persistence intentions.Design/methodology/approachThe sample of this study comprises 320 students enrolled at a distance learning university in Pakistan. Online questionnaires are used to gather data for the study. Correlations and regression analysis are run to figure out the effect of independent variables on the dependent variable of the study.FindingsThe findings of the study show that 51% variance in online students’ persistence intentions can be explained by personal attitude, subjective norms and perceived behavioral control.Research limitations/implicationsThe use of a non-random sampling technique along with a cross-sectional design form the major limitations of the study.Practical implicationsThe outcome of the study may help online education providers as well as policymakers to design programs and initiatives to improve students’ retention in online study programs.Originality/valueThe study contributed to the extant literature by finding out Pakistani online students’ persistence behavior is affected by their attitude, subjective norms and perceived ease of online learning. The study also found that the opinion of people closely related to students influences their study persistence decisions.

The Influence of Stafford Load Debtload on Persistence Among Historically Underserved Populations at a Hispanic Serving Institution

This study presents a mixed methods explanatory analysis of the influence of Stafford loan debtload on persistence among underserved populations attending a Hispanic Serving Institution in the Southwest of the United States. Using data from cohort 2010, fall to fall persistence was examined to assess if debtload was related to persistence for all full-time, first-time undergraduate students based on demographic characteristics. Additionally, in-depth interviews were conducted on undergraduate students during fall 2017 to gain a better understanding of their experiences with debtload and if it played into their persistence decisions. Results of the study revealed statistically significant relationships between debtload and persistence for all first-time, full-time undergraduate students, White non-Hispanic students, Hispanic students, male students, female students, students from low and medium annual household incomes, as well as for first-generation and continuing generation students. Further, low debt was a predictor of non-persistence for each of these groups of students. The findings from the qualitative study showed how debtload influenced students’ persistence decisions. Overall, findings suggest that the threshold of debt is extremely low for these particular students attending a Hispanic Serving Institution.

Understanding Persistence Using a Phenomenological Variant of Ecological Systems Theory

Objective: Despite significant enrollment in community colleges, persistence and graduation rates are quite low. This study aims to better understand how students’ person–environment relationships and self-organization together contribute to the persistence decisions of community college students. Using Spencer et al.’s phenomenological variant on ecological systems theory (PVEST) framework, we aim to clarify the psychological functioning behind students’ persistence that is impacted by diverse systems, including the community college itself, family, and the broader community. Method: This study utilized qualitative interviews with 66 participants across two community colleges. Findings: We find that when participants’ experiences were analyzed through a PVEST frame, a majority of students described having phenomenological experiences around their student/learner identities. The feedback from these experiences prompted participants to negatively or positively reorganize their self-perceptions in regard to how they saw themselves as students and learners; this reorganization led to behaviors that influenced persistence plans. When participants’ microsystems (e.g., family, work, college) intersected, patterns emerged regarding how participants processed environmental feedback that resulted in a cyclical feedback loop, suggesting a more dynamic relationship with environments than previously presented. Contributions: Using PVEST as a framework allows for a more in-depth examination of the interface between students’ psychological foundations, processing of environmental feedback, and the resulting reorganization of self in regard to how role identities (e.g., student) provide greater insight into students’ persistence decisions. This study offers PVEST as an important framework for rethinking previous models of researching and supporting community college student persistence.

The Role of Perceived School Responsiveness within a Psychosociocultural Understanding of Latinx High School Students’ Academic Persistence Decisions

ABSTRACT Using the psychosociocultural approach, the mediating role of perceptions of high school responsiveness on perceived academic abilities, mentorship, and school environment with academic persistence decisions, respectively, was examined. For a sample of 104 Latinx high school students, results revealed a meaningful reduction in the relationships between academic abilities and mentorship with persistence decisions. High school responsiveness fully mediated the relationship between school environment and persistence decisions. The study highlights the unequivocal role that administrators, teachers, and other student service personnel have to create responsive and supportive learning contexts to enhance persistence decisions. Implications for research and practice are discussed.

A Real-Time Health 4.0 Framework with Novel Feature Extraction and Classification for Brain-Controlled IoT-Enabled Environments

In this letter, we propose two novel methods for four-class motor imagery (MI) classification using electroencephalography (EEG). Also, we developed a real-time health 4.0 (H4.0) architecture for brain-controlled internet of things (IoT) enabled environments (BCE), which uses the classified MI task to assist disabled persons in controlling IoT-enabled environments such as lighting and heating, ventilation, and air-conditioning (HVAC). The first method for classification involves a simple and low-complex classification framework using a combination of regularized Riemannian mean (RRM) and linear SVM. Although this method performs better compared to state-of-the-art techniques, it still suffers from a nonnegligible misclassification rate. Hence, to overcome this, the second method offers a persistent decision engine (PDE) for the MI classification, which improves classification accuracy (CA) significantly. The proposed methods are validated using an in-house recorded four-class MI data set (data set I, collected over 14 subjects), and a four-class MI data set 2a of BCI competition IV (data set II, collected over 9 subjects). The proposed RRM architecture obtained average CAs of 74.30% and 67.60% when validated using datasets I and II, respectively. When analyzed along with the proposed PDE classification framework, an average CA of 92.25% on 12 subjects of data set I and 82.54% on 7 subjects of data set II is obtained. The results show that the PDE algorithm is more reliable for the classification of four-class MI and is also feasible for BCE applications. The proposed low-complex BCE architecture is implemented in real time using Raspberry Pi 3 Model B+ along with the Virgo EEG data acquisition system. The hardware implementation results show that the proposed system architecture is well suited for body-wearable devices in the scenario of Health 4.0. We strongly feel that this study can aid in driving the future scope of BCE research.

Persistence Decisions: It’s Not Just About the Money

Drawing on threshold theory, we examine the effects of attributes of alternative opportunities on persistence decisions of family business entrepreneurs. The results of our conjoint experiment show that: (a) family business entrepreneurs are generally more persistent than other entrepreneurs and (b) family business entrepreneurs focus more on non-financial benefits than other entrepreneurs. Our study contributes to persistence literature within the family business context and provides a good basis for how family business literature can benefit from multi-level theoretical and empirical modelling.