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Journal articles on the topic 'Decision-making effort'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Culbreth, Adam J., Erin K. Moran, and Deanna M. Barch. "Effort-based decision-making in schizophrenia." Current Opinion in Behavioral Sciences 22 (August 2018): 1–6. http://dx.doi.org/10.1016/j.cobeha.2017.12.003.

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2

Söllner, Anke, Arndt Bröder, and Benjamin E. Hilbig. "Deliberation versus automaticity in decision making: Which presentation format features facilitate automatic decision making?" Judgment and Decision Making 8, no. 3 (May 2013): 278–98. http://dx.doi.org/10.1017/s1930297500005982.

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AbstractThe idea of automatic decision making approximating normatively optimal decisions without necessitating much cognitive effort is intriguing. Whereas recent findings support the notion that such fast, automatic processes explain empirical data well, little is known about the conditions under which such processes are selected rather than more deliberate stepwise strategies. We investigate the role of the format of information presentation, focusing explicitly on the ease of information acquisition and its influence on information integration processes. In a probabilistic inference task, the standard matrix employed in prior research was contrasted with a newly created map presentation format and additional variations of both presentation formats. Across three experiments, a robust presentation format effect emerged: Automatic decision making was more prevalent in the matrix (with high information accessibility), whereas sequential decision strategies prevailed when the presentation format demanded more information acquisition effort. Further scrutiny of the effect showed that it is not driven by the presentation format as such, but rather by the extent of information search induced by a format. Thus, if information is accessible with minimal need for information search, information integration is likely to proceed in a perception-like, holistic manner. In turn, a moderate demand for information search decreases the likelihood of behavior consistent with the assumptions of automatic decision making.

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3

Rudge, B. A. "Decision-Making in Anaesthesia." Anaesthesia and Intensive Care 23, no. 5 (October 1995): 597–99. http://dx.doi.org/10.1177/0310057x9502300512.

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Anaesthetists work as part of a process and deal with complex situations in their daily work. Considerable effort is put into training anaesthetists, but little has been done either in research or improving awareness of the intangible components of the anaesthesia system that affect safety, such as decision-making. The purpose of this article is to apply the principles of decision-making to anaesthesia practice.

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4

Hauber, W., and S. Sommer. "Prefrontostriatal Circuitry Regulates Effort-Related Decision Making." Cerebral Cortex 19, no. 10 (January 8, 2009): 2240–47. http://dx.doi.org/10.1093/cercor/bhn241.

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5

Bayard, S., J. Cizeau, M. Georges, and Y. Dauvilliers. "Effort-based decision making in narcolepsy-cataplexy." Sleep Medicine 14 (December 2013): e71. http://dx.doi.org/10.1016/j.sleep.2013.11.141.

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6

Isnawati, Ida, and Ali Saukah. "TEACHERS’ GRADING DECISION MAKING." TEFLIN Journal - A publication on the teaching and learning of English 28, no. 2 (July 9, 2017): 155. http://dx.doi.org/10.15639/teflinjournal.v28i2/155-169.

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This study investigated teachers’ grading decision making, focusing on their beliefs underlying their grading decision making, their grading practices and assessment types, and factors they considered in grading decision making. Two teachers from two junior high schools applying different curriculum policies in grade reporting in Indonesian educational context were interviewed in depth to reveal their grading decision making. The results show that the teachers believe that assigning grades is not only for measuring the students’ ability, but also for making them active users of the language, giving them life skills and experience and motivating them. In addition, these teachers use various grading practices involving not only formal assessment but also informal one. Remedial tests, giving more tasks and grade adjustment are also done to reach the criteria of passing grade. The factors considered in grading decision making are achievement factors in the forms of scores from formal and informal assessment and non-achievement factors involving students’ effort and behavior, curriculum and school policy.

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Bardgett, Mark E., Melissa Depenbrock, Nathan Downs, Megan Points, and Leonard Green. "Dopamine modulates effort-based decision making in rats." Behavioral Neuroscience 123, no. 2 (2009): 242–51. http://dx.doi.org/10.1037/a0014625.

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8

Cos, Ignasi. "Perceived effort for motor control and decision-making." PLOS Biology 15, no. 8 (August 18, 2017): e2002885. http://dx.doi.org/10.1371/journal.pbio.2002885.

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9

Wickens, Christopher D. "Effort in Human Factors Performance and Decision Making." Human Factors: The Journal of the Human Factors and Ergonomics Society 56, no. 8 (October 30, 2014): 1329–36. http://dx.doi.org/10.1177/0018720814558419.

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10

Kleinmuntz, Don N. "Effort, Accuracy, and Rational Goal-Directed Decision Making." Contemporary Psychology: A Journal of Reviews 39, no. 9 (September 1994): 876–77. http://dx.doi.org/10.1037/034623.

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11

Addicott, Merideth A., Margaret C. Wardle, and James P. Selig. "Effort-based decision making varies by smoking status." Psychopharmacology 237, no. 4 (January 3, 2020): 1081–90. http://dx.doi.org/10.1007/s00213-019-05437-3.

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12

Arriaga, Patrícia, Ana Guinote, and Maria Vicente Rosa. "Organizational power predicts decision making quality." PSICOLOGIA 34, no. 2 (December 22, 2020): 27–38. http://dx.doi.org/10.17575/psicologia.v34i2.1381.

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The aim of this study was to analyze the link between power and the quality of decision. Participants were 50 employees from an organizational company, consisting of two groups (High-Power, N=24; Low-Power, N=26) based on the organization's hierarchical power position. To evaluate the quality of the decisions, all participants performed tasks involving choice among several alternatives in two separate moments of the same day: in the morning (at the beginning of the workday) and late afternoon (at the end of the workday). Additional subjective measures (fatigue, alertness, effort) and skin conductance were obtained. Results indicated that having high power in the organization was related to making better decisions, over and above the subjective levels of fatigue, alertness, effort, and physiological arousal. No effects of time-of-day were found on the decision making. Consistent with experimental research, having power facilitated decision-making performance in an organizational context.

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13

Frysak, Josef, Edward W. N. Bernroider, and Konradin Maier. "An Effort Feedback Perspective on Persuasive Decision Aids for Multi-Attribute Decision-Making." International Journal of Information Technology & Decision Making 16, no. 01 (January 2017): 161–81. http://dx.doi.org/10.1142/s0219622016500486.

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Decision strategies and the level of cognitive effort humans devote to decision-making are highly sensitive. This study investigates the role of feedback interventions in decision aids (DAs) to direct the user’s attention and consequently increase the level of effort spent on the thinking in multi-attribute selection problems. Guided by four research hypotheses, we conducted an experiment with two groups, one with feedback enabled, the other one with it disabled, and provide post hoc click data analysis. The self-developed persuasive DA used in the experiment featured a continuous feedback mechanism based on the users investment of time. This DA led the users through a smartphone decision scenario with altering levels of complexity. Results show that normative effort feedback increases the decision maker’s willingness to spend more effort. We provide new evidence supporting the view that DAs should pay more attention to soft persuasion by guiding the decision maker towards working harder rather than only confronting the user with final recommendations.

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Nakasato, Jean. "Data-Based Decision Making in Hawaii's Behavior Support Effort." Journal of Positive Behavior Interventions 2, no. 4 (October 2000): 247–51. http://dx.doi.org/10.1177/109830070000200413.

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15

Floresco, S. B., and S. Ghods-Sharifi. "Amygdala-Prefrontal Cortical Circuitry Regulates Effort-Based Decision Making." Cerebral Cortex 17, no. 2 (February 22, 2006): 251–60. http://dx.doi.org/10.1093/cercor/bhj143.

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16

Uban, Kristina A., Julia Rummel, Stan B. Floresco, and Liisa A. M. Galea. "Estradiol Modulates Effort-Based Decision Making in Female Rats." Neuropsychopharmacology 37, no. 2 (August 31, 2011): 390–401. http://dx.doi.org/10.1038/npp.2011.176.

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17

Chen, Xiuli, Sarah Voets, Ned Jenkinson, and Joseph M. Galea. "Dopamine-Dependent Loss Aversion during Effort-Based Decision-Making." Journal of Neuroscience 40, no. 3 (November 14, 2019): 661–70. http://dx.doi.org/10.1523/jneurosci.1760-19.2019.

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18

Cos, Ignasi. "Correction: Perceived Effort for Motor Control and Decision-Making." PLOS Biology 15, no. 11 (November 22, 2017): e1002617. http://dx.doi.org/10.1371/journal.pbio.1002617.

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19

Mosner, Maya G., Jessica L. Kinard, Sean McWeeny, Jasmine S. Shah, Nathan D. Markiewitz, Cara R. Damiano-Goodwin, Margaret R. Burchinal, et al. "Vicarious Effort-Based Decision-Making in Autism Spectrum Disorders." Journal of Autism and Developmental Disorders 47, no. 10 (July 11, 2017): 2992–3006. http://dx.doi.org/10.1007/s10803-017-3220-3.

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20

Todd, Peter, and Izak Benbasat. "An Experimental Investigation Of The Relationship Between Decision Makers, Decision Aids and Decision Making Effort." INFOR: Information Systems and Operational Research 31, no. 2 (May 1993): 80–100. http://dx.doi.org/10.1080/03155986.1993.11732217.

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21

Baar, Carl. "Using Process Theory to Explain Judicial Decision Making." Canadian journal of law and society 1 (1986): 57–79. http://dx.doi.org/10.1017/s0829320100001009.

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This article is part of an effort to place current research on the Canadian judicial process into a broader theoretical context. This effort developed first from a sense that the legal and behavioural frameworks that have dominated the explanation of judicial decision making in the United States Supreme Court obscure more than they illuminate about judicial decision making in Canada; and second from the realization that the most illuminating American studies — those that trace the process by which major cases are brought before the courts and decided — are seen as interesting but atheoretical, as journalism not science. Perhaps our theory is out of joint. And perhaps an effort to understand how American theories and research on judicial decision making can inform Canadian research may be instructive both to American judicial studies and to the work of those outside the United States who are continually tugged toward American approaches that promise liberation from traditional legal analysis.

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22

Taylor, Mackenzie B., and Francesca M. Filbey. "Residual Effects of Cannabis Use on Effort-Based Decision-Making." Journal of the International Neuropsychological Society 27, no. 6 (July 2021): 559–69. http://dx.doi.org/10.1017/s1355617721000473.

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AbstractObjective:Acute Δ9-tetrahydrocannabinol (THC) administration in humans (Lawn etal., 2016) and rats (Silveira, Adams, Morena, Hill, & Winstanley, 2016) has been associated with decreased effort allocation that may explain amotivation during acute cannabis intoxication. To date, however, whether residual effects of cannabis use on effort-based decision-making are present and observable in humans have not yet been determined. The goal of this study was to test whether prolonged cannabis use has residual effects on effort-based decision-making in 24-hr abstinent cannabis using adults.Method:We evaluated performance on the Effort Expenditure for Reward Task (EEfRT) in 41 adult cannabis users (mean age = 24.63 years, 21 males) and 45 nonusers (mean age = 23.90 years, 19 males). A mixed 2x3x3 ANOVA with age as a covariate was performed to examine the effect of group, probability of winning, and reward amount on EEfRT performance. EEfRT performance was operationalized as % of trials for which the hard (vs. easy) condition was chosen. Pearson’s correlations were conducted to test the relationship between EEfRT performance and measures of cannabis use, anhedonia and motivation.Results:We found that cannabis users selected hard trials significantly more than nonusers regardless of win probability or reward level. Frequency of cannabis use was positively correlated with amount of % hard trials chosen. There were no significant correlations between % hard trials chosen, self-reported anhedonia, or motivation.Conclusions:These results suggest that unlike acute effects, residual effects of cannabis following 24 hrs of abstinence are associated with greater effort allocation during effort-based decision-making.

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23

Barnett, B., A. Stokes, C. D. Wickens, T. Davis, R. Rosenblum, and F. Hyman. "A Componential Analysis of Pilot Decision-Making." Proceedings of the Human Factors Society Annual Meeting 31, no. 7 (September 1987): 842–46. http://dx.doi.org/10.1177/154193128703100735.

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In an effort to construct and validate an information-processing model of pilot decision-making, a microcomputer-based system, known as MIDIS, has been developed. A parallel effort resulted in the compilation of a cognitive test battery designed to assess individual differences in those cognitive attributes determined to be important in effective decision making. The processing model of pilot judgment is validated to the extent that pilots with strengths in particular cognitive attributes perform well on those decision scenarios determined to impose demands on those same abilities. Forty professional, instructor, and student pilots served as subjects in this validation study. The results reported here represent data from twenty of the highly-experienced instrument-rated pilots. The results indicated that the cognitive test of running memory span provided a valid predictor of the optimality of pilot's judgments. A test of risk assessment predicted pilot confidence and latency in the decision choices. Few of the other tests, including a test of declarative knowledge, provided significant correlations with the three attributes of decision performance for the pilots in the group studied to date.

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24

Yoon, Tehrim, Robert B. Geary, Alaa A. Ahmed, and Reza Shadmehr. "Control of movement vigor and decision making during foraging." Proceedings of the National Academy of Sciences 115, no. 44 (October 15, 2018): E10476—E10485. http://dx.doi.org/10.1073/pnas.1812979115.

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During foraging, animals decide how long to stay at a patch and harvest reward, and then, they move with certain vigor to another location. How does the brain decide when to leave, and how does it determine the speed of the ensuing movement? Here, we considered the possibility that both the decision-making and the motor control problems aimed to maximize a single normative utility: the sum of all rewards acquired minus all efforts expended divided by total time. This optimization could be achieved if the brain compared a local measure of utility with its history. To test the theory, we examined behavior of people as they gazed at images: they chose how long to look at the image (harvesting information) and then moved their eyes to another image, controlling saccade speed. We varied reward via image content and effort via image eccentricity, and then, we measured how these changes affected decision making (gaze duration) and motor control (saccade speed). After a history of low rewards, people increased gaze duration and decreased saccade speed. In anticipation of future effort, they lowered saccade speed and increased gaze duration. After a history of high effort, they elevated their saccade speed and increased gaze duration. Therefore, the theory presented a principled way with which the brain may control two aspects of behavior: movement speed and harvest duration. Our experiments confirmed many (but not all) of the predictions, suggesting that harvest duration and movement speed, fundamental aspects of behavior during foraging, may be governed by a shared principle of control.

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Barnett, Barbara J. "Perspectives on Decision Analysis for Decision Support System Design." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 37, no. 16 (October 1993): 1101. http://dx.doi.org/10.1177/154193129303701613.

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This symposium addresses the characterization of human decision making within a complex environment for the purpose of developing improved decision support systems. All of the work presented in this symposium was conducted under a Navy research program entitled “Tactical Decision Making Under Stress” (TADMUS). The overall objective of the TADMUS program is to improve tactical decision making of anti-air warfare (AAW) crew members within the Aegis cruiser's combat information center (CIC) under conditions of stress and uncertainty. The unique aspect of this effort is that each presentation addresses decision making behavior, within a single domain, from a different perspective. The goal of each effort is to characterize some aspect of expert decision making performance within the AAW task environment, and to make recommendations for the resulting decision support system design based upon these characterizations. The result is a multi-faceted, human-centered approach to information organization and interface display design for a decision support system.

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26

Nacar, Eyyup. "Investigation of Prospective Kickboxing Coaches’ Self-Esteem in Decision Making and Decision Making Styles." Journal of Education and Training Studies 7, no. 5 (April 2, 2019): 32. http://dx.doi.org/10.11114/jets.v7i5.4193.

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Decision refers to the act of choosing the most appropriate type of action possible according to present possibilities and conditions in order to achieve an aim. Decision making covers all cognitive and behavioral effort for choosing and preferring in the face of various situations and events. Starting from this point of view, in our study, it was aimed to investigate prospective kickboxing students’ self-esteem in decision making and decision making styles.The study included 62 voluntary prospective coaches, who participated in a kickboxing coaching in the city center of Elazığ in 2017. In order to obtain personal information from the participant prospective coaches in the study, a personal information form (age, gender, years of doing sports) was formed. In order to investigate the self-esteem in decision making and decision making styles of prospective kickboxing coaches, the Melbourne Decision Making Questionnaire, which was originally developed by Mann et al., (1998) and adapted into Turkish by Deniz (2004), was utilized. The obtained data were evaluated by using SPSS statistics package software and the level of significance was regarded as p<0.05.As a result of the study, according to participants’ variables of age, gender and years of doing sports, the comparison of prospective teachers’ decision making and decision making style mean scores did not constitute a statistically significant difference. The self-esteem levels of coaches in decision making were observed to be significantly high.

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Wardle, M. C., M. T. Treadway, L. M. Mayo, D. H. Zald, and H. de Wit. "Amping Up Effort: Effects of d-Amphetamine on Human Effort-Based Decision-Making." Journal of Neuroscience 31, no. 46 (November 16, 2011): 16597–602. http://dx.doi.org/10.1523/jneurosci.4387-11.2011.

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28

Kensinger Rose, Katherine, and James Elicker. "Parental Decision Making About Child Care." Journal of Family Issues 29, no. 9 (January 8, 2008): 1161–84. http://dx.doi.org/10.1177/0192513x07312103.

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In an effort to address how to best assess the importance of various characteristics of child care to parents, 355 employed mothers of children under 6 years of age completed a questionnaire exploring the importance of child care characteristics to their choice of arrangement, through ratings, rankings, and conjoint analysis. Results indicate that when rated, warmth of caregivers, educational level of caregivers, and utilization of a play-based curriculum emerge as the most important factors for mothers in this sample. When rank ordered, warmth, a play-based curriculum, and the educational level of caregivers emerge as the first-, second-, and third-most important factors. When examined using conjoint analysis of child care scenarios, warmth, flexibility of hours of operation, and education level of caregivers emerge as the most influential variables in the child care decision. Demographic differences in parental child care preferences and potential future uses for conjoint analysis are identified.

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Stuppy-Sullivan, Allison M., Joshua W. Buckholtz, and Arielle Baskin-Sommers. "Aberrant Cost–Benefit Integration During Effort-Based Decision Making Relates to Severity of Substance Use Disorders." Clinical Psychological Science 8, no. 1 (November 11, 2019): 155–68. http://dx.doi.org/10.1177/2167702619868155.

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Aberrant cost–benefit decision making is a key factor related to individual differences in the expression of substance use disorders (SUDs). Previous research highlights how delay-cost sensitivity affects variability in SUDs; however, other forms of cost–benefit decision making—effort-based choice—have received less attention. We administered the Effort Expenditure for Rewards Task (EEfRT) in an SUD-enriched community sample ( N = 80). Individuals with more severe SUDs were less likely to use information about expected value when deciding between high-effort, high-reward and low-effort, low-reward options. Furthermore, individuals whose severity of use was primarily related to avoiding aversive affective states and individuals with heightened sensitivity to delay costs during intertemporal decision making were the least sensitive to expected value signals when making decisions to engage in effortful behavior. Together, these findings suggest that individuals with more severe SUDs have difficulty integrating multiple decision variables to guide behavior during effort-based decision making.

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Colón-Semenza, Cristina, Daniel Fulford, and Terry Ellis. "Effort-Based Decision-Making for Exercise in People with Parkinson’s Disease." Journal of Parkinson's Disease 11, no. 2 (April 13, 2021): 725–35. http://dx.doi.org/10.3233/jpd-202353.

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Background: People with Parkinson’s disease (PwPD) are less active than their age-matched peers. Non-motor symptoms, specifically, deficient motivation, may influence decision-making for exercise due to the impaired mesolimbic dopaminergic pathway. Objective: The purpose of this study was to determine if effort-based decision-making for physical effort was different in PwPD compared to healthy controls. We sought to determine the relationship between effort-based decision making for exercise and a discrete motor task as well as the impact of components of motivation on decision-making for physical effort in PwPD. Methods: An effort-based decision-making paradigm using a discrete motor task (button pressing) and a continuous exercise task (cycling) was implemented in 32 PwPD and 23 healthy controls. Components of motivation were measured using the Apathy Scale and the Temporal Experience of Pleasure Scale- Anticipatory Pleasure scale. Results: The presence of Parkinson’s disease (PD) did not moderate decisions for either physical effort task. There was a moderate correlation between decisions for both tasks, within each group. The anticipation of pleasure and apathy were predictors of decisions for both physical effort tasks in PwPD, but not in healthy controls. Conclusion: PwPD responded similarly to effort and reward valuations compared to those without PD. Individuals were consistent in their decisions, regardless of the physical effort task. The anticipation of pleasure and apathy were significant predictors of decisions for exercise in PwPD only. Increased anticipation of pleasure, reduction of apathy, and the use of rewards may enhance engagement in high effort exercise among PwPD.

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Ganesan, Keertana, and Nikolaus Steinbeis. "Effort-related decision-making and its underlying processes during childhood." Developmental Psychology 57, no. 9 (September 2021): 1487–96. http://dx.doi.org/10.1037/dev0001228.

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32

Burk, Diana, James N. Ingram, David W. Franklin, Michael N. Shadlen, and Daniel M. Wolpert. "Motor Effort Alters Changes of Mind in Sensorimotor Decision Making." PLoS ONE 9, no. 3 (March 20, 2014): e92681. http://dx.doi.org/10.1371/journal.pone.0092681.

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33

Iodice, Pierpaolo, Cinzia Calluso, Laura Barca, Maurizio Bertollo, Patrizio Ripari, and Giovanni Pezzulo. "Fatigue increases the perception of future effort during decision making." Psychology of Sport and Exercise 33 (November 2017): 150–60. http://dx.doi.org/10.1016/j.psychsport.2017.08.013.

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34

McCollow, Meaghan M., and Holly H. Hoffman. "Evidence-Based Decision-Making: A Team Effort Toward Achieving Goals." Young Exceptional Children 23, no. 1 (September 28, 2018): 15–23. http://dx.doi.org/10.1177/1096250618801287.

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Assadi, Seyed M., Murat Yücel, and Christos Pantelis. "Dopamine modulates neural networks involved in effort-based decision-making." Neuroscience & Biobehavioral Reviews 33, no. 3 (March 2009): 383–93. http://dx.doi.org/10.1016/j.neubiorev.2008.10.010.

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Shadmehr, Reza, Helen J. Huang, and Alaa A. Ahmed. "A Representation of Effort in Decision-Making and Motor Control." Current Biology 26, no. 14 (July 2016): 1929–34. http://dx.doi.org/10.1016/j.cub.2016.05.065.

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Betsch, Tilmann, and Andreas Glöckner. "Intuition in Judgment and Decision Making: Extensive Thinking Without Effort." Psychological Inquiry 21, no. 4 (November 30, 2010): 279–94. http://dx.doi.org/10.1080/1047840x.2010.517737.

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38

Irvin, Renee A., and John Stansbury. "Citizen Participation in Decision Making: Is It Worth the Effort?" Public Administration Review 64, no. 1 (January 2004): 55–65. http://dx.doi.org/10.1111/j.1540-6210.2004.00346.x.

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39

KaurSehra, Sumeet, Yadwinder Singh Brar, and Navdeep Kaur. "Multi Criteria Decision Making Approach for Selecting Effort Estimation Model." International Journal of Computer Applications 39, no. 1 (February 29, 2012): 10–17. http://dx.doi.org/10.5120/4783-6989.

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40

Winter, Yael, Hilla Ben-Pazi, and Yehuda Pollak. "Effort Allocation in Children With ADHD: Abnormal Decision-Making or Poor Execution?" Journal of Attention Disorders 23, no. 11 (June 20, 2016): 1240–50. http://dx.doi.org/10.1177/1087054716654569.

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Objective: Effort allocation is a multi-faceted process driving both the decision to choose a high effort–high reward alternative over a low effort–low reward alternative, and the execution of this decision by recruiting sufficient effort. The objectives of our study were to examine whether children with ADHD would (a) show different reward–effort cost trade-off, and (b) have difficulty executing their decision. Method: 50 children, aged 9 to 15, with and without ADHD, had to choose between high effort–high reward and low effort–low reward alternatives using a handheld dynamometer and to execute their choice. Results: Children with ADHD and controls made similar number of high-effort choices ( p = .806). However, children with ADHD executed their high-effort choices less frequently compared with controls ( p = .029). Conclusion: These findings suggest that children with ADHD are not characterized by different effort–reward trade-off but rather by difficulties in recruiting effort for their preferences implementation.

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41

Zheng, Rui, Chun Su, and Yuqiao Zheng. "Two-stage flexible warranty decision-making considering downtime loss." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 234, no. 3 (November 29, 2019): 527–35. http://dx.doi.org/10.1177/1748006x19889261.

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Most existing warranty policies are rigid, and the downtime loss is also not taken into account. This study develops a two-stage decision framework to design flexible warranty policies, where the downtime loss is considered. In the first stage, by minimizing the warranty service cost, a fixed warranty policy is provided to determine the baseline of preventive maintenance’s times and effort. In the second stage, customers have three options to increase preventive maintenance times, preventive maintenance effort, or both of them, which results in three types of flexible warranty policies. The additional maintenance cost for the increased preventive maintenance times and/or preventive maintenance effort is paid by the customers. Besides, the flexible policies are optimized to minimize customer’s cost, which is the sum of the downtime loss and shared maintenance cost. A practical example is provided to illustrate the effectiveness of the proposed flexible warranty policies. The results indicate that compared with the fixed warranty policies, both the manufacturer and customers can benefit from the proposed flexible policies, especially when the downtime loss is substantial. Moreover, the proposed policy is more effective when the warranty period is longer.

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Gill, Simone V., Samuel J. Abplanalp, Laura Keegan, and Daniel Fulford. "Effort-Based Decision-Making and Gross Motor Performance: Are They Linked?" Brain Sciences 10, no. 6 (June 4, 2020): 347. http://dx.doi.org/10.3390/brainsci10060347.

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The purpose of this study was to investigate the relationship between effort-based decision making and gross motor performance. Effort-based decision making was measured using a modified version of the Effort Expenditure for Rewards Task (EEfRT), in which participants pressed a button on a keyboard to fill a bar on a screen for monetary reward. Participants received monetary rewards that were commensurate with the level of effort that they were willing to expend. Gross motor performance was measured with a walking task, in which participants matched their steps to the beat of an audio metronome; they walked to metronome beats that were slower and also faster than their normal walking pace. We hypothesized that increased effort during the effort-based decision making task would be paired with an increase in steps taken per minute during the gross motor task. However, the results of this study indicated a lack of a statistically significant relationship between the effort-based decision making task and the gross motor task. Planning rather than decision-making may have been the cognitive construct that governed our gross motor task. These findings can be beneficial when thinking about potential interventions for populations who experience deficits in motor performance and cognition as well as for understanding the relationship between both cognitive and motor performance in healthy adults.

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Nunez, Cecilia, Jennifer K. Hoots, Scott T. Schepers, Michael Bower, Harriet de Wit, and Margaret C. Wardle. "Pharmacological investigations of effort-based decision-making in humans: Naltrexone and nicotine." PLOS ONE 17, no. 10 (October 5, 2022): e0275027. http://dx.doi.org/10.1371/journal.pone.0275027.

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Many mental health disorders are characterized by an impaired ability, or willingness, to exert effort to obtain rewards. This impairment is modeled in effort-based decision tasks, and neuropharmacological studies implicate dopamine in this process. However, other transmitter systems such as opioidergic and cholinergic systems have received less attention. Here, in two separate studies we tested the acute effects of naltrexone and nicotine on effort-based decision-making in healthy adults. In Study 1, we compared naltrexone (50mg and 25mg) to placebo, and in Study 2, a pilot study, we compared nicotine (7mg) to placebo. In both studies, participants completed the Effort Expenditure for Rewards Task (EEfRT), which measured effort-based decision-making related to monetary rewards. Although subjects expended greater effort for larger reward magnitude and when there was a higher probability of receiving the reward, neither naltrexone nor nicotine affected willingness to exert effort for monetary rewards. Although the drugs produced significant and typical drug effects on measures of mood and behavior, they did not alter effort-based decision-making. This has implications both for the clinical use of these drugs, as well as for understanding the neuropharmacology of effort-related behavior.

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N C, Danushri. "Clinical Decision Making using Machine Learning." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (July 31, 2022): 3061–64. http://dx.doi.org/10.22214/ijraset.2022.45625.

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Abstract: Deaths due to cardiovascular diseases are increasing at an alarming rate. This led to nearly 2.1 million deaths in India in 2015. Heart disease is one of the deadliest causes of death worldwide and has a major impact on the lives of rural people. According to a recent study, cardiovascular disease mortality among rural Indians has surpassed urban Indians. Such numbers are alarming, especially when 68% of India's population lives in rural areas that have poor access to quality healthcare. This paper aims to provide a solution to this problem by introducing a new model*clinical*decision*support system*, abbreviated as CDSS, which*includes machine learning algorithms for the diagnosis of cardiovascular diseases. CDSS is intelligent enough to diagnose a patient's*disease* and help the doctor prescribe the*correct medication, reducing the cost and effort required to prescribe unnecessary treatment. *In this work, we applied correlation-based feature selection (CFS) and a multilayer perceptron classifier on a large heart disease dataset. The dataset used in this study is the "Cleveland Clinic Foundation Heart Disease Dataset" available at the UCI Machine Learning Repository. Our proposed model produced greater accuracy compared to other existing models used in this study. This system can be integrated into a public health care setting to help rural people get a correct, timely and cost-effective diagnosis.

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Hogan, Patrick S., Joseph K. Galaro, and Vikram S. Chib. "Roles of Ventromedial Prefrontal Cortex and Anterior Cingulate in Subjective Valuation of Prospective Effort." Cerebral Cortex 29, no. 10 (December 12, 2018): 4277–90. http://dx.doi.org/10.1093/cercor/bhy310.

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Abstract The perceived effort level of an action shapes everyday decisions. Despite the importance of these perceptions for decision-making, the behavioral and neural representations of the subjective cost of effort are not well understood. While a number of studies have implicated anterior cingulate cortex (ACC) in decisions about effort/reward trade-offs, none have experimentally isolated effort valuation from reward and choice difficulty, a function that is commonly ascribed to this region. We used functional magnetic resonance imaging to monitor brain activity while human participants engaged in uncertain choices for prospective physical effort. Our task was designed to examine effort-based decision-making in the absence of reward and separated from choice difficulty—allowing us to investigate the brain’s role in effort valuation, independent of these other factors. Participants exhibited subjectivity in their decision-making, displaying increased sensitivity to changes in subjective effort as objective effort levels increased. Analysis of blood-oxygenation-level dependent activity revealed that the ventromedial prefrontal cortex (vmPFC) encoded the subjective valuation of prospective effort, and ACC activity was best described by choice difficulty. These results provide insight into the processes responsible for decision-making regarding effort, partly dissociating the roles of vmPFC and ACC in prospective valuation of effort and choice difficulty.

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Tersago, Pieter, Miet Vanderhallen, Joëlle Rozie, and Sara-Jane McIntyre. "From Suspect Statement to Legal Decision Making." Zeitschrift für Psychologie 228, no. 3 (July 2020): 175–87. http://dx.doi.org/10.1027/2151-2604/a000412.

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Abstract. Notwithstanding that confessions are considered the “Queen of evidence,” how judges actually weigh suspects’ statements in reaching their decision remains relatively unknown. This study sought to examine how Belgian judges determine the evidential value of a suspect’s statement, specifically how they evaluate the statement’s: (a) admissibility and validity and (b) interaction with other pieces of evidence. To shed light on this legal decision-making process, 100 Belgian burglary case files were examined, and semi-structured interviews were undertaken with ten Belgian judges. The findings suggest that: the judge’s evaluation of a suspect’s statement differs depending on the outcome of the statement; how a statement is obtained does not appear to be an essential aspect of evidence evaluation; judges expend more effort to falsify denials than confessions; and only when they fail to falsify the denial is an acquittal granted.

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Chiu, LK, M. Ai, F. Makram, M. Quinci, J. Cooper, P. Loui, and M. Geddes. "P.001 The neural correlates of effort-reward decision-making in older adults." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 49, s1 (June 2022): S7—S8. http://dx.doi.org/10.1017/cjn.2022.106.

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Background: Effort mobilization is important in older adults to stay healthy, notably for decision-making. The process of decreasing subjective value of a reward as required effort increases is called effort discounting. By identifying underlying neural correlates related to effort discounting, we can better understand factors affecting normal cognitive aging. Methods: We acquired resting-state functional magnetic resonance images from 19 cognitively normal older adults (10 males; 66±6 years). Participants completed a computerized cognitive task—called Effort Expenditure for Rewards Task—capturing the willingness to expend effort for rewards through binary choices between high-reward-high-effort or low-reward-low-effort option to obtain varying monetary rewards. We modelled subjective value to assess the k parameter, effort discounting. A functional connectivity analysis examined the involvement of regions associated to the salience network. Results: The seed-to-voxel analysis revealed increased connectivity within the precuneus cortex and to clusters in the right temporal and posterior cingulate gyri, with increased k-value or decreased willingness to expend effort. There was also decreased connectivity between the anterior cingulate and right lateral occipital cortex, and between the left anterior insula to the cerebellum and precuneus cortex. Conclusions: The process of effort discounting is correlated to functional connectivity changes involving the precuneus, anterior cingulate, and left anterior insula in healthy older adults.

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Saleh, Youssuf, Campbell Le Heron, Pierre Petitet, Michele Veldsman, Daniel Drew, Olivia Plant, Ursula Schulz, et al. "Apathy in small vessel cerebrovascular disease is associated with deficits in effort-based decision making." Brain 144, no. 4 (March 18, 2021): 1247–62. http://dx.doi.org/10.1093/brain/awab013.

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Abstract Patients with small vessel cerebrovascular disease frequently suffer from apathy, a debilitating neuropsychiatric syndrome, the underlying mechanisms of which remain to be established. Here we investigated the hypothesis that apathy is associated with disrupted decision making in effort-based decision making, and that these alterations are associated with abnormalities in the white matter network connecting brain regions that underpin such decisions. Eighty-two patients with MRI evidence of small vessel disease were assessed using a behavioural paradigm as well as diffusion weighted MRI. The decision-making task involved accepting or rejecting monetary rewards in return for performing different levels of physical effort (hand grip force). Choice data and reaction times were integrated into a drift diffusion model that framed decisions to accept or reject offers as stochastic processes approaching a decision boundary with a particular drift rate. Tract-based spatial statistics were used to assess the relationship between white matter tract integrity and apathy, while accounting for depression. Overall, patients with apathy accepted significantly fewer offers on this decision-making task. Notably, while apathetic patients were less responsive to low rewards, they were also significantly averse to investing in high effort. Significant reductions in white matter integrity were observed to be specifically related to apathy, but not to depression. These included pathways connecting brain regions previously implicated in effort-based decision making in healthy people. The drift rate to decision parameter was significantly associated with both apathy and altered white matter tracts, suggesting that both brain and behavioural changes in apathy are associated with this single parameter. On the other hand, depression was associated with an increase in the decision boundary, consistent with an increase in the amount of evidence required prior to making a decision. These findings demonstrate altered effort-based decision making for reward in apathy, and also highlight dissociable mechanisms underlying apathy and depression in small vessel disease. They provide clear potential brain and behavioural targets for future therapeutic interventions, as well as modelling parameters that can be used to measure the effects of treatment at the behavioural level.

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Abhyankar, Aditi. "Behavioural Economics Towards Better Decision Making." Journal of Global Economy 16, no. 2 (June 14, 2022): 1–10. http://dx.doi.org/10.1956/jge.v16i2.648.

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Often, Individuals try to choose the best feasible option but sometimes, they don’t succeed in doing so. They make mistakes. Also, the market exchange makes psychological factors cease to matter but many psychological factors matter even for the markets. In contrast to the traditional assumption of neoclassical economics that individuals are rational Homooeconomici, that always seek to maximize their utility and follow their “true” preferences, research in behavioural economics has demonstrated that people’s judgments and decisions are often subject to systematic biases and heuristics, and are strongly dependent on the context of the decision. The insights from behavioural economics (BE) are now a well-established feature in consumer research and policy. Today, in fields from health behaviour to pension saving, from investment decisions to food choice, from sustainable consumption to the design of warning signs, the empirical and theoretical insights of BE have become a cornerstone of understanding consumer behaviour, helping inform policymakers on how to nudge people to make better, smarter, healthier and more sustainable choices (World Bank, 2014). BE is concerned with the question of how people actually behave in decision-making situations and how their choices can be improved so that consumers’ welfare is enhanced. For the market, it is always crucial to enhance sales every next quarter, using appropriate strategies. This paper makes a humble effort to briefly review the transition of the neoclassical (optimising) decision-making towards newer and better insights into behavioural economics and discuss how the latter has influenced and enhanced consumer behaviour and consumer policy on one hand and marketing strategy on the other.

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Floresco, Stan B., Maric T. L. Tse, and Sarvin Ghods-Sharifi. "Dopaminergic and Glutamatergic Regulation of Effort- and Delay-Based Decision Making." Neuropsychopharmacology 33, no. 8 (September 5, 2007): 1966–79. http://dx.doi.org/10.1038/sj.npp.1301565.

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