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Journal articles on the topic 'Decisional models'
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T., S. Aimé Metchebon, Valérie Brison, and Marc Pirlot. "Two models for comparing decisional maps." International Journal of Multicriteria Decision Making 3, no. 2/3 (2013): 129. http://dx.doi.org/10.1504/ijmcdm.2013.053730.
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Ferrarese, Moreno. "Decisional processing on parking behavior in entropic settings." Archives of Transport 41, no. 1 (March 13, 2017): 17–29. http://dx.doi.org/10.5604/01.3001.0009.7377.
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This paper surveys the most recent advances in the context of decisional processing with focusing on the parking behavior in entropic settings, including the measures and the necessary mechanisms for the interaction of the actors-players, and their connection to decisional processing theory. The aim of this article is to provide a critical review of the most fashionable models and methods in parking lot financial design: the first class of methods covers the approach of analysis with the random entropic model; the second class of methods is the decisional processing through rational choice models as rational individual evaluations. Both techniques are described in detail in sections; we illustrate them using the well-known and easy multimodal problem approach and then we present the advanced applications. Thus, it is possible to identify all strong and weak points of the models and to compare them for a best feasible solution for parking lot economic and financial design. Taking into account a close equivalence between the aggregate methods of entropy maximization and disaggregated microeconomic method of discrete choice models, based on random utility theory, we try to provide a critical approach of it through the rational choice models and to underline the possible benefit of it for the problem decision.
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Dewald, Samantha Rose, Loki Natarajan, and Irene Su. "Fertility preservation and decisional regret in young breast cancer survivors: A longitudinal analysis." Journal of Clinical Oncology 35, no. 5_suppl (February 10, 2017): 106. http://dx.doi.org/10.1200/jco.2017.35.5_suppl.106.
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106 Background: Fertility is important to many young breast cancer survivors (YBCS), who face difficult decisions on whether to undergo fertility preservation prior to treatment. Because few longitudinal data assessing decisional regret are available, the objectives of this study were to assess longitudinal changes in decisional regret on fertility preservation following breast cancer diagnosis; determine if fertility preservation treatment decisions are related to decreased decisional regret. Methods: From 3 academic breast cancer programs, 169 YBCS younger than age 45 were recruited at diagnosis between 2009 and 2012 and followed prospectively for ovarian function. Participants completed questionnaires on fertility preservation choices and the Decisional Regret Scale (DRS) during study visits every 6 months for up to 5 years. DRS is scored 0 (no regret) to 100 (highest regret). DRS was dichotomized as none versus any decisional regret. Generalized linear models estimated the change in DRS over time and the association between patient characteristics and DRS. Results: Mean age at diagnosis was 38.7 (SD 4.8). Median total follow-up was 176 days (IQR 84 to 1415 days). Enrollment DRS was available for 89 women; 48% reported decisional regret about fertility preservation (median DRS=20). Participants worried about future fertility were more likely to report decisional regret (p=0.009). 31% underwent fertility preservation, but this was not associated with decisional regret (p=0.65). In repeated measures analysis for the entire cohort, no significant change in DRS occurred over this time period (OR 0.8, 95% CI 0.4-1.7). Worry about future fertility remained significantly associated with DRS over time (OR 55.1, 95% CI 7.7-395.1). Conclusions: In a cohort of YBCS, experiencing decisional regret about fertility preservation persists for years after diagnosis. Those worried about future fertility are more likely to experience decisional regret regarding fertility preservation.
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Neufeld, Richard W. J. "“Locus of Control, Sensation Seeking, and Mathematical Models of Stress and Decisional Control: Comment on De Brabander and Hellemans”." Psychological Reports 81, no. 3_suppl (December 1997): 1289–90. http://dx.doi.org/10.2466/pr0.1997.81.3f.1289.
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In a recent study, De Brabander and Hellemans (1996) reported that stress (somatic complaints) was inversely related to scores on personality scales of “thrill-and-adventure sensation seeking” and “internal locus of control.” These observations, useful in their own right, are of further value when examined in the light of mathematical models of stress and decisional control. It is suggested that diminished stress associated with higher scores on these scales may result from increased engagement and reduced aversiveness of cognitive demands mediating reduction of threat under conditions of decisional control.
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Marcus, Bess H., Bernardine M. Pinto, Laurey R. Simkin, Janet E. Audrain, and Elaine R. Taylor. "Application of Theoretical Models to Exercise Behavior among Employed Women." American Journal of Health Promotion 9, no. 1 (September 1994): 49–55. http://dx.doi.org/10.4278/0890-1171-9.1.49.
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Purpose. This study examines the utility of three theoretical models—the stages of change model, self-efficacy theory, and the decisional balance model—in understanding exercise behavior among employed women. Design. Data for this cross-sectional study were collected as part of a routine follow-up of a worksite-based smoking and health risk appraisal study. Setting. The study was conducted in three Rhode Island worksites, including one manufacturing company, one medical center, and one retail outlet. Subjects. Of a sample of 431 women who completed exercise questionnaires, 293 reported participation in a physical activity over the previous week. The average age of the sample was 41.1 years, and mean years of education was 12.8. Measures. Previously validated measures to determine stage of exercise behavior, exercise self-efficacy, exercise decisional balance, and physical activity participation were administered. Additional demographic information was also obtained. Results. Frequency counts revealed that 39% of the population was sedentary, 34% were participating in irregular activity, and 27% were active. MANOVAs followed by one way ANOVAs revealed that women in Precontemplation scored the lowest and those in Maintenance scored the highest on the self-efficacy, pro, and decisional-balance indices, with the trend reversed on the con scale. A chi-square test revealed that women with one or more young children in the home were more likely to be in a lower stage of exercise adoption. Conclusions. Most of the women in this cross-sectional study did not engage in regular activity. Presence of young children in the home was significantly related to decreased activity. The results are limited by the nonrandomized, and cross-sectional nature of the study design. Data suggest that, with multiple roles and responsibilities, women may be better served by stage-matched interventions to increase physical activity.
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Tricou, Colombe, Sriram Yennu, Murielle Ruer, Eduardo Bruera, and Marilène Filbet. "Decisional control preferences of patients with advanced cancer receiving palliative care." Palliative and Supportive Care 16, no. 5 (November 2, 2017): 544–51. http://dx.doi.org/10.1017/s1478951517000803.
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ABSTRACTObjective:Understanding patients' decisional control preferences (DCPs) is important to improving the quality of care and the satisfaction of patients who have advanced cancer with their care. In addition to passive decisional control (i.e., the patient prefers his/her doctor or family caregiver to make a decision on their behalf) and active decisional control (i.e., the patient decides alone), shared decisional control, where patients and caregivers decide together, could be more appropriate. The primary aim of our study was to describe the decision-making process and the DCPs of patients with advanced cancer receiving palliative care in France.Method:We conducted a prospective survey with advanced cancer patients referred to a palliative care team in an outpatient setting. We collected information about patients' demographic and clinical characteristics using the Decision Control Preference Scale, the Satisfaction with the Decisions and Care questionnaire, and the Understanding of Illness questionnaire.Results:A total of 200 patients were evaluable. The median age was 63.5 years and 53.5% female. The cancers most commonly represented were gastrointestinal and breast. A total of 72 patients (36.2%) preferred active decisional control, 52 (26.1%) preferred shared decisional control, and 75 (37.7%) preferred passive decisional control. Younger age (p = 0.003), higher education (p < 0.001), and employment status (p = 0.046) were found to be associated with active or shared DCPs. Some 82% of patients were satisfied with the decision-making process, 35% of whom expressed wishes that did not match the actual decision-making process. Only 23% of patients thought they could be cured of their illness, and 47% thought that their treatment would “get rid of ” their disease.Significance of Results:The decision-making processes are shared in the three models of DCPs in our cohort of French patients with advanced cancer. Further prospective studies are needed.
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Grangel, Reyes, Michel Bigand, and Jean-Pierre Bourey. "Transformation of decisional models into UML: application to GRAI grids." International Journal of Computer Integrated Manufacturing 23, no. 7 (July 2010): 655–72. http://dx.doi.org/10.1080/09511921003767563.
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Anguzu, R., R. Cusatis, N. Fergestrom, A. Cooper, K. D. Schoyer, J. B. Davis, J. Sandlow, and K. E. Flynn. "Decisional conflict among couples seeking specialty treatment for infertility in the USA: a longitudinal exploratory study." Human Reproduction 35, no. 3 (March 2020): 573–82. http://dx.doi.org/10.1093/humrep/dez292.
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Abstract STUDY QUESTION What are couples’ decisional conflicts around family-building approaches before and after seeking a specialty consultation for infertility? SUMMARY ANSWER Decisional conflict is high among couples before an initial specialty consultation for infertility; on average, women resolved decisional conflict more quickly than men. WHAT IS KNOWN ALREADY Couples have multiple options for addressing infertility, and decisional conflict may arise due to lack of information, uncertainty about options and potential risks or challenges to personal values. STUDY DESIGN, SIZE, DURATION We conducted a total of 385 interviews and 405 surveys for this longitudinal, mixed-methods cohort study of 34 opposite-sex couples who sought a new reproductive specialty consultation (n = 68), who enrolled before the initial consultation and were followed over 12 months. PARTICIPANTS/MATERIALS, SETTING, METHODS The in-depth, semi-structured interviews included questions about information gathering, deliberation and decision-making, and self-administered surveys included the Decisional Conflict Scale (DCS), at six time points over 12 months. A DCS total score of 25 is associated with implementing a decision, and higher scores indicate more decisional conflict. A systematic content analysis of interview transcripts identified major themes. Paired t tests identified differences in DCS between women and men within couples. Linear mixed models predicted changes in DCS over time, adjusting for sociodemographic and fertility-related factors. MAIN RESULTS AND THE ROLE OF CHANCE The major qualitative themes were communication with partners, feeling supported and/or pressured in decision (s), changing decisions over time and ability to execute a desired decision. Average DCS scores were highest before the initial consultation. Within couples, men had significantly higher decisional conflict than women pre-consultation (48.9 versus 40.2, P = 0.037) and at 2 months (28.9 versus 22.1, P = 0.015), but differences at other time points were not significant. In adjusted models, predicted DCS scores declined over time, with women, on average, reaching the DCS threshold for implementing a decision at 2 months while for men it was not until 4 months. LIMITATIONS, REASONS FOR CAUTION This is a convenience sample from a single center, and generalizability may be limited. WIDER IMPLICATIONS OF THE FINDINGS Understanding how couples discuss and make decisions regarding family-building could improve the delivery of patient-centered infertility care. Our findings are the first to prospectively explore decisional conflict at multiple time points in both men and women; the observed gender differences underlie the importance of supporting both partners in clinical decision-making for infertility. STUDY FUNDING/COMPETING INTEREST(S) This work was supported by the National Institute of Child Health and Human Development under Grant [R21HD071332], the Research and Education Program Fund, of the Advancing a Healthier Wisconsin endowment at Medical College of Wisconsin, the National Research Service Award under Grant [T32 HP10030] and the use of REDCap for data collection from the National Center for Advancing Translational Sciences, National Institutes of Health under Grant through [8UL1TR000055]. The authors have no competing interests.
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Witteman, Holly O., Anne-Sophie Julien, Ruth Ndjaboue, Nicole L. Exe, Valerie C. Kahn, Angela (Angie) Fagerlin, and Brian J. Zikmund-Fisher. "What Helps People Make Values-Congruent Medical Decisions? Eleven Strategies Tested across 6 Studies." Medical Decision Making 40, no. 3 (April 2020): 266–78. http://dx.doi.org/10.1177/0272989x20904955.
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Background. High-quality health decisions are often defined as those that are both evidence informed and values congruent. A values-congruent decision aligns with what matters to those most affected by the decision. Values clarification methods are intended to support values-congruent decisions, but their effects on values congruence are rarely evaluated. Methods. We tested 11 strategies, including the 3 most commonly used values clarification methods, across 6 between-subjects online randomized experiments in demographically diverse US populations ( n1 = 1346, n2 = 456, n3 = 840, n4 = 1178, n5 = 841, n6 = 2033) in the same hypothetical decision. Our primary outcome was values congruence. Decisional conflict was a secondary outcome in studies 3 to 6. Results. Two commonly used values clarification methods (pros and cons, rating scales) reduced decisional conflict but did not encourage values-congruent decisions. Strategies using mathematical models to show participants which option aligned with what mattered to them encouraged values-congruent decisions and reduced decisional conflict when assessed. Limitations. A hypothetical decision was necessary for ethical reasons, as we believed some strategies may harm decision quality. Later studies used more outcomes and covariates. Results may not generalize outside US-based adults with online access. We assumed validity and stability of values during the brief experiments. Conclusions. Failing to explicitly support the process of aligning options with values leads to increased proportions of values-incongruent decisions. Methods representing more than half of values clarification methods commonly in use failed to encourage values-congruent decisions. Methods that use models to explicitly show people how options align with their values offer more promise for helping people make decisions aligned with what matters to them. Decisional conflict, while arguably an important outcome in and of itself, is not an appropriate proxy for values congruence.
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Plesca, Cezar, Vincent Charvillat, and Romulus Grigoras. "Adapting Content Delivery to Limited Resources and Inferred User Interest." International Journal of Digital Multimedia Broadcasting 2008 (2008): 1–13. http://dx.doi.org/10.1155/2008/171385.
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This paper discusses adaptation policies for information systems that are subject to dynamic and stochastic contexts such as mobile access to multimedia web sites. In our approach, adaptation agents apply sequential decisional policies under uncertainty. We focus on the modeling of such decisional processes depending on whether the context is fully or partially observable. Our case study is a movie browsing service in a mobile environment that we model by using Markov decision processes (MDPs) and partially observable MDP (POMDP). We derive adaptation policies for this service, that take into account the limited resources such as the network bandwidth. We further refine these policies according to the partially observable users' interest level estimated from implicit feedback. Our theoretical models are validated through numerous simulations.
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Grangel, Reyes, Michel Bigand, and Jean-Pierre Bourey. "UML Profiles for Transforming GRAI Decisional Models into UML Use Cases." IFAC Proceedings Volumes 42, no. 4 (2009): 900–905. http://dx.doi.org/10.3182/20090603-3-ru-2001.0213.
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Genga, Laura, Luca Allodi, and Nicola Zannone. "Association Rule Mining Meets Regression Analysis: An Automated Approach to Unveil Systematic Biases in Decision-Making Processes." Journal of Cybersecurity and Privacy 2, no. 1 (March 21, 2022): 191–219. http://dx.doi.org/10.3390/jcp2010011.
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Decisional processes are at the basis of most businesses in several application domains. However, they are often not fully transparent and can be affected by human or algorithmic biases that may lead to systematically incorrect or unfair outcomes. In this work, we propose an approach for unveiling biases in decisional processes, which leverages association rule mining for systematic hypothesis generation and regression analysis for model selection and recommendation extraction. In particular, we use rule mining to elicit candidate hypotheses of bias from the observational data of the process. From these hypotheses, we build regression models to determine the impact of variables on the process outcome. We show how the coefficient of the (selected) model can be used to extract recommendation, upon which the decision maker can operate. We evaluated our approach using both synthetic and real-life datasets in the context of discrimination discovery. The results show that our approach provides more reliable evidence compared to the one obtained using rule mining alone, and how the obtained recommendations can be used to guide analysts in the investigation of biases affecting the decisional process at hand.
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Casula, Mattia. "Who governs in (local) governance? Theoretical considerations and empirical evidence." Revista de Administração Pública 51, no. 6 (December 2017): 1121–38. http://dx.doi.org/10.1590/0034-7612161618.
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Abstract This article aims to discuss the possible actors that can determine public policies, and the influence of new decisional arenas on politics. This theoretical work presents the evolution of different models of producing public policies, to the transformations taking place with the adoption of the governance model. Using empirical evidence from the Italian case, the study of new decisional arenas for the determination of public policies shows that there are still several problems to be addressed. Such problems are connected, above all, with the uncertain democratic nature of these arenas, as well as with the impossibility to clearly attribute political responsibility to the choices adopted in these spaces. These are issues and future research questions to be resolved, limiting the analysis to specific case studies, preferably related to the local sphere.
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Costa, Luís, Miguel F. Gago, Darya Yelshyna, Jaime Ferreira, Hélder David Silva, Luís Rocha, Nuno Sousa, and Estela Bicho. "Application of Machine Learning in Postural Control Kinematics for the Diagnosis of Alzheimer’s Disease." Computational Intelligence and Neuroscience 2016 (2016): 1–15. http://dx.doi.org/10.1155/2016/3891253.
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The use of wearable devices to study gait and postural control is a growing field on neurodegenerative disorders such as Alzheimer’s disease (AD). In this paper, we investigate if machine-learning classifiers offer the discriminative power for the diagnosis of AD based on postural control kinematics. We compared Support Vector Machines (SVMs), Multiple Layer Perceptrons (MLPs), Radial Basis Function Neural Networks (RBNs), and Deep Belief Networks (DBNs) on 72 participants (36 AD patients and 36 healthy subjects) exposed to seven increasingly difficult postural tasks. The decisional space was composed of 18 kinematic variables (adjusted for age, education, height, and weight), with or without neuropsychological evaluation (Montreal cognitive assessment (MoCA) score), top ranked in an error incremental analysis. Classification results were based on threefold cross validation of 50 independent and randomized runs sets: training (50%), test (40%), and validation (10%). Having a decisional space relying solely on postural kinematics, accuracy of AD diagnosis ranged from 71.7 to 86.1%. Adding the MoCA variable, the accuracy ranged between 91 and 96.6%. MLP classifier achieved top performance in both decisional spaces. Having comprehended the interdynamic interaction between postural stability and cognitive performance, our results endorse machine-learning models as a useful tool for computer-aided diagnosis of AD based on postural control kinematics.
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Pendharkar, Parag C., and Marvin D. Troutt. "DEA based data preprocessing for maximum decisional efficiency linear case valuation models." Expert Systems with Applications 39, no. 10 (August 2012): 9435–42. http://dx.doi.org/10.1016/j.eswa.2012.02.118.
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Fiorucci, P., F. Gaetani, R. Minciardi, and E. Trasforini. "Natural risk assessment and decision planning for disaster mitigation." Advances in Geosciences 2 (May 13, 2005): 161–65. http://dx.doi.org/10.5194/adgeo-2-161-2005.
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Abstract. In this paper, decisional models are introduced aiming at defining a general framework for natural disaster mitigation. More specifically, an integrated approach based on system modelling and optimal resource assignment is presented in order to support the decision makers in pre-operational and real-time management of forest fire emergencies. Some strategies for pre-operative and real time risk management will be described and formalized as optimal resource assignment problems. To this end, some models capable to describe the resources dynamics will be introduced, both in pre-operative phase and in real-time phase.
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Morano, Rosato, Tajani, Manganelli, and Liddo. "Contextualized Property Market Models vs. Generalized Mass Appraisals: An Innovative Approach." Sustainability 11, no. 18 (September 6, 2019): 4896. http://dx.doi.org/10.3390/su11184896.
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The present research takes into account the current and widespread need for rational valuation methodologies, able to correctly interpret the available market data. An innovative automated valuation model has been simultaneously implemented to three Italian study samples, each one constituted by two-hundred residential units sold in the years 2016–2017. The ability to generate a “unique” functional form for the three different territorial contexts considered, in which the relationships between the influencing factors and the selling prices are specified by different multiplicative coefficients that appropriately represent the market phenomena of each case study analyzed, is the main contribution of the proposed methodology. The method can provide support for private operators in the assessment of the territorial investment conveniences and for the public entities in the decisional phases regarding future tax and urban planning policies.
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Rotaru, Ionela Magdalena, and Sorin Borza. "Conception And Fabrication In Automotive Industry Using Knowledge Management Principles." Balkan Region Conference on Engineering and Business Education 1, no. 1 (August 15, 2014): 359–64. http://dx.doi.org/10.2478/cplbu-2014-0054.
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AbstractKnowledge management is a reality nowadays, a powerful resource and one of the premises that provides efficiency and decisional support to any approach no matter of the specific domain were we apply the knowledge management principles. Knowledge models, the specific instruments of the knowledge management represent the start point of this paper, in which we present some aspects regarding the conception and fabrication using knowledge models in the automotive industry field. The approach starts with a short presentation of some knowledge models from the technical area and in the final part of the paper we present the guiding lines for a proposed knowledge model.
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Wenzel, Lari B., Dana B. Mukamel, Kathryn Osann, Lisa Sparks, Laura Jean Havrilesky, Alexi A. Wright, Joan L. Walker, et al. "Shared decision-making in ovarian cancer." Journal of Clinical Oncology 35, no. 15_suppl (May 20, 2017): 5549. http://dx.doi.org/10.1200/jco.2017.35.15_suppl.5549.
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5549 Background: The value of shared decision-making in ovarian cancer is relatively unexplored. The goal of this study was to test a new decision aid, Patient Centered Outcome Aid (PCOA), that facilitates shared decision-making and helps ovarian cancer patients assimilate information and identify quality of life (QOL), toxicity and survival trade-offs between IP/IV therapy and IV therapy alone, based on their preferences and personal clinical characteristics. Methods: Participants were randomized to either PCOA (N=64) or usual care (N=59). Patient characteristics, QOL and shared decision-making data were collected at baseline and treatment initiation. Primary outcomes included satisfaction with treatment decision and decisional regret. Comparisons were made using t-tests and multivariate methods, adjusting for patient covariates. Multivariate linear models were used to investigate predictors of the primary outcomes. Results: Although satisfaction and decisional regret did not differ significantly by arm at any time point, the majority of PCOA patients indicated that the aid helped them understand treatment options and side effects. Notably, low shared decision-making and low QOL, were significant predictors of low satisfaction at treatment initiation (multiple r=0.76), six months (multiple r=0.48) and nine months (r=0.58). They were also significant predictors of decisional regret (multiple r=0.48 and 0.36 at 6 and 9 months). Patient covariates including age, stage, treatment and neoadjuvant status were not associated with differences in satisfaction or decisional regret. Conclusions: There were no clinically meaningful differences in satisfaction with the treatment decision, or decisional regret between the study arms. The absence of a difference may reflect the high degree of shared decision-making in both arms and greater disease severity in PCOA patients, who were more likely to report low baseline QOL and declining QOL over time. Both shared decision-making and quality of life were robust, independent predictors of satisfaction with the treatment decision over time. This implies that women who perceive themselves as less engaged in the decision process, and report poor QOL may benefit from a decision aid, in addition to physician counseling. Clinical trial information: NCT02259699.
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Thomson, Jessica L., Lisa M. Tussing-Humphreys, Jamie M. Zoellner, and Melissa H. Goodman. "Psychosocial constructs were not mediators of intervention effects for dietary and physical activity outcomes in a church-based lifestyle intervention: Delta Body and Soul III." Public Health Nutrition 19, no. 11 (January 22, 2016): 2060–69. http://dx.doi.org/10.1017/s1368980015003602.
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AbstractObjectiveEvaluating an intervention’s theoretical basis can inform design modifications to produce more effective interventions. Hence the present study’s purpose was to determine if effects from a multicomponent lifestyle intervention were mediated by changes in the psychosocial constructs decisional balance, self-efficacy and social support.DesignDelta Body and Soul III, conducted from August 2011 to May 2012, was a 6-month, church-based, lifestyle intervention designed to improve diet quality and increase physical activity. Primary outcomes, diet quality and aerobic and strength/flexibility physical activity, as well as psychosocial constructs, were assessed via self-report, interviewer-administered surveys at baseline and post intervention. Mediation analyses were conducted using ordinary least squares (continuous outcomes) and maximum likelihood logistic (dichotomous outcomes) regression path analysis.SettingChurches (five intervention and three control) were recruited from four counties in the Lower Mississippi Delta region of the USA.SubjectsRural, Southern, primarily African-American adults (n 321).ResultsBased upon results from the multiple mediation models, there was no evidence that treatment (intervention v. control) indirectly influenced changes in diet quality or physical activity through its effects on decisional balance, self-efficacy and social support. However, there was evidence for direct effects of social support for exercise on physical activity and of self-efficacy for sugar-sweetened beverages on diet quality.ConclusionsResults do not support the hypothesis that the psychosocial constructs decisional balance, self-efficacy and social support were the theoretical mechanisms by which the Delta Body and Soul III intervention influenced changes in diet quality and physical activity.
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Perales, D. David Pérez, Francisco-Cruz Lario Esteban, Ma Mar Eva Alemany Díaz, and Jorge E. Hernández. "Framework for Modelling the Decision." International Journal of Decision Support System Technology 4, no. 2 (April 2012): 59–77. http://dx.doi.org/10.4018/jdsst.2012040104.
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In the supply chains operations planning context, and from a research viewpoint, it has been mainly assumed that different supply chain members make decisions in a centralised manner (one decision centre). However, reality shows that this is not the most usual situation, rather distributed supply chain decision making is. This paper proposes a framework to support modelling the decisional view of collaborative planning from a decision-making process perspective for both centralised and distributed situations. Along these lines, the framework assumes that the supply chain may be composed of one or several decision centres which aim to support every supply chain planning operation. Therefore, the main framework contributions are: consideration of decisions jointly with physical, organisation and information views; the spatial and temporal integration among the different supply chain decision centres; the definition of the macro level for “conceptually” modelling the collaborative planning process and the micro level for developing analytical models in all the decisional activities identified in the supply chains operations planning process. Finally, a brief overview of a real case application is also described.
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Scaltritti, Michele, Remo Job, F. Xavier Alario, and Simone Sulpizio. "On the Boundaries between Decision and Action: Effector-selective Lateralization of Beta-frequency Power Is Modulated by the Lexical Frequency of Printed Words." Journal of Cognitive Neuroscience 32, no. 11 (November 2020): 2131–44. http://dx.doi.org/10.1162/jocn_a_01606.
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Current computational and neuroscientific models of decision-making posit a discrete, serial processing distinction between upstream decisional stages and downstream processes of motor-response implementation. We investigated this framework in the context of two-alternative forced-choice tasks on linguistic stimuli, words and pseudowords. In two experiments, we assessed the impact of lexical frequency and action semantics on two effector-selective EEG indexes of motor-response activation: the lateralized readiness potential and the lateralization of beta-frequency power. This allowed us to track potentially continuous streams of processing progressively mapping the evaluation of linguistic stimuli onto corresponding response channels. Whereas action semantics showed no influence on EEG indexes of motor-response activation, lexical frequency affected the lateralization of response-locked beta-frequency power. We argue that these observations point toward a continuity between linguistic processing of word input stimuli and implementation of corresponding choice in terms of motor behavior. This interpretation challenges the commonly held assumption of a discrete processing distinction between decisional and motor-response processes in the context of decisions based on symbolic stimuli.
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Mollá, Nuria, Alejandro Rabasa, Jesús J. Rodríguez-Sala, Joaquín Sánchez-Soriano, and Antonio Ferrándiz. "Incremental Decision Rules Algorithm: A Probabilistic and Dynamic Approach to Decisional Data Stream Problems." Mathematics 10, no. 1 (December 21, 2021): 16. http://dx.doi.org/10.3390/math10010016.
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Data science is currently one of the most promising fields used to support the decision-making process. Particularly, data streams can give these supportive systems an updated base of knowledge that allows experts to make decisions with updated models. Incremental Decision Rules Algorithm (IDRA) proposes a new incremental decision-rule method based on the classical ID3 approach to generating and updating a rule set. This algorithm is a novel approach designed to fit a Decision Support System (DSS) whose motivation is to give accurate responses in an affordable time for a decision situation. This work includes several experiments that compare IDRA with the classical static but optimized ID3 (CREA) and the adaptive method VFDR. A battery of scenarios with different error types and rates are proposed to compare these three algorithms. IDRA improves the accuracies of VFDR and CREA in most common cases for the simulated data streams used in this work. In particular, the proposed technique has proven to perform better in those scenarios with no error, low noise, or high-impact concept drifts.
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Klann, Elyssa M., and Y. Joel Wong. "A Pregnancy Decision-Making Model: Psychological, Relational, and Cultural Factors Affecting Unintended Pregnancy." Psychology of Women Quarterly 44, no. 2 (June 2020): 170–86. http://dx.doi.org/10.1177/0361684320904321.
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Empirical data from the past 50 years have illuminated some of the factors that influence pregnancy decision-making. Yet, formal models of pregnancy decision-making are uncommon and rarely incorporate cultural perspectives. In order to address this gap in the literature, we propose the Pregnancy Decision-Making Model (PDMM), a comprehensive model of the factors that are likely to affect pregnancy decisions in the context of unintended pregnancy, with special attention to relational and intersectional components of pregnancy decisions. The PDMM begins with three primary Evaluation factors: Evaluation of Capital, Evaluation of Values, and Evaluation of Narratives. Barriers to Access are proposed to be a key factor in limiting agency and autonomy and determining pregnancy outcomes. Social Influences are also hypothesized to influence Evaluation factors and their relationship with outcome variables, which include the Pregnancy Outcome, Decisional Certainty, and Decisional Satisfaction. As the PDMM is designed to be flexible in its prediction of a variety of outcomes, we consider a number of possible permutations of the model. Finally, we discuss the utility of the PDMM for inspiring future research, as well as the practical implications of the model.
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Toivonen, Kirsti, Tamara Williamson, Linda Carlson, Lauren Walker, and Tavis Campbell. "Potentially Modifiable Factors Associated with Adherence to Adjuvant Endocrine Therapy among Breast Cancer Survivors: A Systematic Review." Cancers 13, no. 1 (December 31, 2020): 107. http://dx.doi.org/10.3390/cancers13010107.
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Adjuvant endocrine therapy (AET) reduces risk of breast cancer recurrence. However, suboptimal adherence and persistence to AET remain important clinical issues. Understanding factors associated with adherence may help inform efforts to improve use of AET as prescribed. The present systematic review examined potentially modifiable factors associated with adherence to AET in accordance with PRISMA guidelines (PROSPERO registration ID: CRD42019124200). All studies were included, whether factors were significantly associated with adherence or results were null. This review also accounted for the frequency with which a potentially modifiable factor was examined and whether univariate or multivariate models were used. This review also examined whether methodological or sample characteristics were associated with the likelihood of a factor being associated with AET adherence. A total of 68 articles were included. Potentially modifiable factors were grouped into six categories: side effects, attitudes toward AET, psychological factors, healthcare provider-related factors, sociocultural factors, and general/quality of life factors. Side effects were less likely to be associated with adherence in studies with retrospective or cross-sectional than prospective designs. Self-efficacy (psychological factor) and positive decisional balance (attitude toward AET) were the only potentially modifiable factors examined ≥10 times and associated with adherence or persistence ≥75% of the time in both univariate and multivariate models. Self-efficacy and decisional balance (i.e., weight of pros vs. cons) were the potentially modifiable factors most consistently associated with adherence, and hence may be worth focusing on as targets for interventions to improve AET adherence among breast cancer survivors.
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Blanc-Sylvestre, Nicolas, Philippe Bouchard, Catherine Chaussain, and Claire Bardet. "Pre-Clinical Models in Implant Dentistry: Past, Present, Future." Biomedicines 9, no. 11 (October 26, 2021): 1538. http://dx.doi.org/10.3390/biomedicines9111538.
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Biomedical research seeks to generate experimental results for translation to clinical settings. In order to improve the transition from bench to bedside, researchers must draw justifiable conclusions based on data from an appropriate model. Animal testing, as a prerequisite to human clinical exposure, is performed in a range of species, from laboratory mice to larger animals (such as dogs or non-human primates). Minipigs appear to be the animal of choice for studying bone surgery around intraoral dental implants. Dog models, well-known in the field of dental implant research, tend now to be used for studies conducted under compromised oral conditions (biofilm). Regarding small animal models, research studies mostly use rodents, with interest in rabbit models declining. Mouse models remain a reference for genetic studies. On the other hand, over the last decade, scientific advances and government guidelines have led to the replacement, reduction, and refinement of the use of all animal models in dental implant research. In new development strategies, some in vivo experiments are being progressively replaced by in vitro or biomaterial approaches. In this review, we summarize the key information on the animal models currently available for dental implant research and highlight (i) the pros and cons of each type, (ii) new levels of decisional procedures regarding study objectives, and (iii) the outlook for animal research, discussing possible non-animal options.
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Wright, Megan S. "Dementia, Healthcare Decision Making, and Disability Law." Journal of Law, Medicine & Ethics 47, S4 (2019): 25–33. http://dx.doi.org/10.1177/1073110519898040.
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Persons with dementia often prefer to participate in decisions about their health care, but may be prevented from doing so because healthcare decision-making law facilitates use of advance directives or surrogate decision makers for persons with decisional impairments such as dementia. Federal and state disability law provide alternative decision-making models that do not prevent persons with mild to moderate dementia from making their own healthcare decisions at the time the decision needs to be made. In order to better promote autonomy and wellbeing, persons with dementia should be accommodated and supported so they can make their own healthcare decisions.
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VENTRE, Viviana. "Behavioral issues in decision problems: the role of information." Journal of Mathematical Economics and Finance 4, no. 2 (December 31, 2018): 27. http://dx.doi.org/10.14505/jmef.v4.2(7).02.
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Operational research (OR) might exhibit a partial perspective in modelling decisional processes as rational processes, because individual choices are strictly influenced by cognitive and motivational biases which can be different among people and for each person in dierent situation. We point out that the level of information of each problem solver play an important role in causing inconsistent preferences, and we demonstrate that only about strict conditions decision models coincide with real choices, because only in particular cases the optimum and rational decision matches with the real one. Moreover, cognitive and motivational biases influence also the modeler in the process of modelling. Behavioral Operational Research (BOR) studies the influence of behavioral issues in the modelling process, to avoid such kinds of biases and create eficient models to define choices in similar decision processes.
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Copeland, A. M., and M. J. Wenger. "Investigating perceptual and decisional mechanisms for the dynamics of perceptual learning: Theory, models, and data." Journal of Vision 3, no. 9 (March 18, 2010): 676. http://dx.doi.org/10.1167/3.9.676.
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Wong, Yu-Ning, Mark D. Schluchter, Terrance L. Albrecht, Al Bowen Benson, Joanne Buzaglo, Michael Collins, Anne Lederman Flamm, et al. "Financial Concerns About Participation in Clinical Trials Among Patients With Cancer." Journal of Clinical Oncology 34, no. 5 (February 10, 2016): 479–87. http://dx.doi.org/10.1200/jco.2015.63.2463.
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Purpose The decision to enroll in a clinical trial is complex given the uncertain risks and benefits of new approaches. Many patients also have financial concerns. We sought to characterize the association between financial concerns and the quality of decision making about clinical trials. Methods We conducted a secondary data analysis of a randomized trial of a Web-based educational tool (Preparatory Education About Clinical Trials) designed to improve the preparation of patients with cancer for making decisions about clinical trial enrollment. Patients completed a baseline questionnaire that included three questions related to financial concerns (five-point Likert scales): “How much of a burden on you is the cost of your medical care?,” “I'm afraid that my health insurance won't pay for a clinical trial,” and “I’m worried that I wouldn’t be able to afford the costs of treatment on a clinical trial.” Results were summed, with higher scores indicating greater concerns. We used multiple linear regressions to measure the association between concerns and self-reported measures of self-efficacy, preparation for decision making, distress, and decisional conflict in separate models, controlling for sociodemographic characteristics. Results One thousand two hundred eleven patients completed at least one financial concern question. Of these, 27% were 65 years or older, 58% were female, and 24% had a high school education or less. Greater financial concern was associated with lower self-efficacy and preparation for decision making, as well as with greater decisional conflict and distress, even after adjustment for age, race, sex, education, employment, and hospital location (P < .001 for all models). Conclusion Financial concerns are associated with several psychological constructs that may negatively influence decision quality regarding clinical trials. Greater attention to patients’ financial needs and concerns may reduce distress and improve patient decision making.
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Minniti, Maria, and William Bygrave. "A Dynamic Model of Entrepreneurial Learning." Entrepreneurship Theory and Practice 25, no. 3 (April 2001): 5–16. http://dx.doi.org/10.1177/104225870102500301.
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We model entrepreneurial learning as a calibrated algorithm of an iterated choice problem in which entrepreneurs learn by updating a subjective stock of knowledge accumulated on the basis of past experiences. Specifically, we argue that entrepreneurs repeat only those choices that appear most promising and discard the ones that resulted in failure. The contribution of the paper is twofold. First, we provide a structural model of entrepreneurial learning in which failure is as informative—though clearly not as desirable—as success. Second, to complement standard economic models in which agents are rational, we allow our entrepreneurs to have myopic foresight. Our entrepreneurs process information, make mistakes, update their decisional algorithms and, possibly, through this struggle, improve their performance.
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George, Tracey E., and Lee Epstein. "On the Nature of Supreme Court Decision Making." American Political Science Review 86, no. 2 (June 1992): 323–37. http://dx.doi.org/10.2307/1964223.
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How does the U.S. Supreme Court reach decisions? Since the 1940s, scholars have focused on two distinct explanations. The legal model suggests that the rule of law (stare decisis) is the key determinant. The extralegal model posits that an array of sociological, psychological, and political factors produce judicial outcomes. To determine which model better accounted for judicial decisions, we used Supreme Court cases involving the imposition of the death penalty since 1972 and estimated and evaluated the models' success in accounting for decisional outcomes. Although both models performed quite satisfactorily, they possessed disturbing weaknesses. The legal perspective overpredicted liberal outcomes, the extralegal model conservative ones. Given these results, we tested another proposition, namely that extralegal and legal frameworks present codependent, not mutually exclusive, explanations of decision making. Based on these results, we offer an integrated model of Supreme Court decision making that contemplates a range of political and environmental forces and doctrinal constraints.
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Piazza, Gianni. "Come decidono gli attivisti all'interno dei Centri Sociali? Uno studio comparato delle occupazioni in una cittŕ italiana." PARTECIPAZIONE E CONFLITTO, no. 1 (May 2012): 118–40. http://dx.doi.org/10.3280/paco2012-001006.
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The Social Centres in Italy are autonomous groups set up by left-wing radical activists, who occupy and/or self-manage unused buildings, where they organize political campaigns, social and countercultural activities. In this article, a typology of decision-making and internal democracy models, based on decisional method and preferences' treatment adopted (Consensual vs. Majoritarian), is here proposed and tested through the binary comparison of two Social Centres, as empirical cases, in the same city (Catania in Sicily), with the most dissimilar characteristics (campaigns/activities, political ideological orientations, national networks, legal position, attitude towards institutions). The research, methodologically founded on participant observation, the analysis of self-produced documents and a set of semi-structured interviews, provided unexpected findings, entailing an explanation through the procedure of re-identification and/or cultural recollocation of Pizzorno. As a consequence, the diverse models of decisionmaking and internal democracy adopted by activists of the two Social Centres seem to be depended on their different ends, collective identities and political-ideological orientations
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Granata, Giuseppe, and Giancarlo Scozzese. "The Influence of Virtual Communities in Marketing Decision." International Business Research 10, no. 12 (November 16, 2017): 191. http://dx.doi.org/10.5539/ibr.v10n12p191.
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Purpose – The introduction and growth of the Internet and modern technology has had a strong impact on the structures of companies and led to a change in the decisional processes. In the new economic scenarios, with the growth of social networks and Web 3.0, technologies go through developments and transformations that are of vital importance to ensure the competitiveness of companies.Methodology – The study analyzes the possibility of applying social networks to the new business models, underlining their importance not only with regard to managers but also, and especially, to crowdsourcing processes.Implications – The objective of the study is to focus on the impact that web 3.0 and social networks have on management and marketing decisions, underlining certain processes in order to improve the competitive advantages of companies.
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Carrozza, Chiara. "Italian water services reform from 1994 to 2008: decisional rounds and local modes of governance." Water Policy 13, no. 6 (April 26, 2011): 751–68. http://dx.doi.org/10.2166/wp.2011.030.
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Italian water services reform, started in 1994, has been surrounded by a lively debate on water management models; however, the story of the reform is difficult to understand if only those models chosen by local public agencies are considered. This paper provides a general picture of the reform, analyzes the decision-making process and presents a map of local outcomes. The decision-making analysis considers the course of action taken by the actors involved in reform from 1994 to 2008, and summarizes the events into three rounds. The map of the local modes of governance is focused on the relationship between local authorities and utilities, and has been realized through a collection of data from the 91 areas in which the national system has been reorganized, which has allowed the definition of four ideal types of outcome. The analysis shows that the range of solutions is wider (and the boundaries between them more ambiguous) than commonly assumed by the mainstream national debate which appears to overestimate the role of tools and of formal instruments, and, conversely, to underestimate the real and differentiated abilities and power of the actors in the water sector.
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Smith, Philip L., and Simon D. Lilburn. "Vision for the blind: visual psychophysics and blinded inference for decision models." Psychonomic Bulletin & Review 27, no. 5 (June 8, 2020): 882–910. http://dx.doi.org/10.3758/s13423-020-01742-7.
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Abstract Evidence accumulation models like the diffusion model are increasingly used by researchers to identify the contributions of sensory and decisional factors to the speed and accuracy of decision-making. Drift rates, decision criteria, and nondecision times estimated from such models provide meaningful estimates of the quality of evidence in the stimulus, the bias and caution in the decision process, and the duration of nondecision processes. Recently, Dutilh et al. (Psychonomic Bulletin & Review 26, 1051–1069, 2019) carried out a large-scale, blinded validation study of decision models using the random dot motion (RDM) task. They found that the parameters of the diffusion model were generally well recovered, but there was a pervasive failure of selective influence, such that manipulations of evidence quality, decision bias, and caution also affected estimated nondecision times. This failure casts doubt on the psychometric validity of such estimates. Here we argue that the RDM task has unusual perceptual characteristics that may be better described by a model in which drift and diffusion rates increase over time rather than turn on abruptly. We reanalyze the Dutilh et al. data using models with abrupt and continuous-onset drift and diffusion rates and find that the continuous-onset model provides a better overall fit and more meaningful parameter estimates, which accord with the known psychophysical properties of the RDM task. We argue that further selective influence studies that fail to take into account the visual properties of the evidence entering the decision process are likely to be unproductive.
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Chen, Shi-Yu, Hui-Chun Hsu, Ruey-Hsia Wang, Yau-Jiunn Lee, and Chang-Hsun Hsieh. "Glycemic Control in Insulin-Treated Patients With Type 2 Diabetes: Empowerment Perceptions and Diabetes Distress as Important Determinants." Biological Research For Nursing 21, no. 2 (December 25, 2018): 182–89. http://dx.doi.org/10.1177/1099800418820170.
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The purpose of this cross-sectional study was to explore the determinants of hemoglobin A1c (HbA1c) levels in insulin-treated patients with Type 2 diabetes mellitus (T2DM) based on demographic and disease characteristics, self-reported regimen adherence factors (adherence in insulin regimen and self-monitoring of blood glucose), and psychosocial factors (decisional balance for insulin injection, health literacy, self-efficacy for insulin injection, diabetes distress, and empowerment perceptions). Via convenience sampling, 255 insulin-treated patients with T2DM were recruited from two endocrinology clinics in Taiwan. A self-report questionnaire was used to collect demographic and disease characteristics, regimen adherence factors, and psychosocial factors. The first HbA1c level measured after completion of the questionnaire was the dependent variable. The last HbA1c level measured before patients started insulin therapy as well as body mass index (BMI) was collected from medical records. Results indicated that adherence in insulin regimen was relatively good. Regimen adherence factors did not significantly correlate with HbA1c levels, but empowerment perception, decisional balance for insulin injection, health literacy, and diabetes distress did. The hierarchical multiple regression models indicated that BMI, the last HbA1c levels before starting insulin therapy, empowerment perception, and diabetes distress were important determinants of HbA1c levels. Nurses could periodically assess the diabetes distress of insulin-treated patients with T2DM and refer to mental health professionals when needed. Furthermore, applying empowerment approaches such as enhancing self-awareness of improved glycemic control and sharing more decision-making power with insulin-treated patients with T2DM might have benefits for their glycemic control.
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Krieger, Janice L., Jessica L. Krok-Schoen, Phokeng M. Dailey, Angela L. Palmer-Wackerly, Nancy Schoenberg, Electra D. Paskett, and Mark Dignan. "Distributed Cognition in Cancer Treatment Decision Making: An Application of the DECIDE Decision-Making Styles Typology." Qualitative Health Research 27, no. 8 (May 12, 2016): 1146–59. http://dx.doi.org/10.1177/1049732316645321.
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Distributed cognition occurs when cognitive and affective schemas are shared between two or more people during interpersonal discussion. Although extant research focuses on distributed cognition in decision making between health care providers and patients, studies show that caregivers are also highly influential in the treatment decisions of patients. However, there are little empirical data describing how and when families exert influence. The current article addresses this gap by examining decisional support in the context of cancer randomized clinical trial (RCT) decision making. Data are drawn from in-depth interviews with rural, Appalachian cancer patients ( N = 46). Analysis of transcript data yielded empirical support for four distinct models of health decision making. The implications of these findings for developing interventions to improve the quality of treatment decision making and overall well-being are discussed.
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Obiri, Isaac Amankona, Qi Xia, Hu Xia, Kwame Opuni-Boachie Obour Agyekum, Kwame Omono Asamoah, Emmanuel Boateng Sifah, Xiaosong Zhang, and Jianbin Gao. "A Fully Secure KP-ABE Scheme on Prime-Order Bilinear Groups through Selective Techniques." Security and Communication Networks 2020 (November 29, 2020): 1–18. http://dx.doi.org/10.1155/2020/8869057.
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Key-policy attribute-based encryption (KP-ABE) is the cryptographic primitive which enables fine grained access control while still providing end-to-end encryption. Although traditional encryption schemes can provide end-to-end encryption, users have to either share the same decryption keys or the data have to be stored in multiple instances which are encrypted with different keys. Both of these options are undesirable. However, KP-ABE can provide less key overhead compared to the traditional encryption schemes. While there are a lot of KP-ABE schemes, none of them simultaneously supports multiuse of attributes, adaptive security, monotone span programs, and static security assumption. Hence, we propose a fully secure KP-ABE scheme for monotone span programs in prime-order group. This scheme uses selective security proof techniques to obtain the requisite ingredients for full security proof. This strengthens the correlation between selective and full security models and enables the transition of the best qualities in selective security models to fully secure systems. The security proof is based on decisional linear assumption and three-party Diffie–Hellman assumption.
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Collignon, Bertrand, Axel Séguret, and José Halloy. "A stochastic vision-based model inspired by zebrafish collective behaviour in heterogeneous environments." Royal Society Open Science 3, no. 1 (January 2016): 150473. http://dx.doi.org/10.1098/rsos.150473.
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Collective motion is one of the most ubiquitous behaviours displayed by social organisms and has led to the development of numerous models. Recent advances in the understanding of sensory system and information processing by animals impels one to revise classical assumptions made in decisional algorithms. In this context, we present a model describing the three-dimensional visual sensory system of fish that adjust their trajectory according to their perception field. Furthermore, we introduce a stochastic process based on a probability distribution function to move in targeted directions rather than on a summation of influential vectors as is classically assumed by most models. In parallel, we present experimental results of zebrafish (alone or in group of 10) swimming in both homogeneous and heterogeneous environments. We use these experimental data to set the parameter values of our model and show that this perception-based approach can simulate the collective motion of species showing cohesive behaviour in heterogeneous environments. Finally, we discuss the advances of this multilayer model and its possible outcomes in biological, physical and robotic sciences.
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Skeem, Jennifer L., Edward P. Mulvey, and Charles W. Lidz. "Building mental health professionals' decisional models into tests of predictive validity: The accuracy of contextualized predictions of violence." Law and Human Behavior 24, no. 6 (December 2000): 607–28. http://dx.doi.org/10.1023/a:1005513818748.
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Rounsevell, Mark D. A., and Almut Arneth. "Representing human behaviour and decisional processes in land system models as an integral component of the earth system." Global Environmental Change 21, no. 3 (August 2011): 840–43. http://dx.doi.org/10.1016/j.gloenvcha.2011.04.010.
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SALTINI, A., M. A. MAZZI, L. DEL PICCOLO, and C. ZIMMERMANN. "Decisional strategies for the attribution of emotional distress in primary care." Psychological Medicine 34, no. 4 (April 21, 2004): 729–39. http://dx.doi.org/10.1017/s0033291703001260.
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Background. In primary care the General Health Questionnaire (GHQ) is used to provide an independent assessment of probable caseness of psychological disorder against which to test the ability of the general practitioner (GP) to recognize patients with current emotional problems.Method. The aim of the present study was to identify those clinical and psychosocial data on patients that increase the likelihood of GPs' attribution of emotional distress (GP model) and those that predict patients' emotional distress as defined by the GHQ-12 (GHQ model). The associations were explored using a classification tree technique (CHAID) and compared using bivariate logistic regression. Six GPs and 444 primary care patients took part.Results. The accuracy indices of the hierarchical GP and GHQ models were 72% and 69% respectively. The availability of information on patients' psychopharmacological and psychiatric/psychological treatment in the last year was the most important predictor of attribution. Occupational, financial and housing problems and life events of loss were the most important predictors of the GHQ-12 case definition. The overall accuracy of the bivariate model was 73%. Compared with the GHQ-12, GPs gave significantly more importance to psychiatric treatment, psychopharmacological drug use and chronic illness.Conclusions. The findings suggest that to improve the detection of current emotional distress in primary care patients GPs should pay foremost and systematic attention to social problems and recent life events of loss. These problems are important clues for the possible presence of emotional distress, whereas critical patient data, in particular psychiatric history and psychopharmacological treatment, increase the probability of attribution errors.
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Marini, Marco, Alessandro Ansani, and Fabio Paglieri. "Attraction comes from many sources: Attentional and comparative processes in decoy effects." Judgment and Decision Making 15, no. 5 (September 2020): 704–26. http://dx.doi.org/10.1017/s1930297500007889.
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AbstractThe attraction effect emerges when adding a seemingly irrelevant option (decoy) to a binary choice shifts preference towards a target option. This suggests that choice behaviour is dynamic, i.e., choice values are developed during deliberation, rather than manifesting some pre-existing preference set. Whereas several models of multialternative and multiattribute decision making consider dynamic choice processes as crucial to explain the attraction effect, empirically investigating the exact nature of such processes requires complementing choice output with other data. In this study, we focused on asymmetrically dominated decoys (i.e., decoys that are clearly dominated only by the target option) to examine the attentional and comparative processes responsible for the attraction effect. Through an eye-tracker paradigm, we showed that the decoy option can affect subjects’ preferences in two different and not mutually exclusive ways: by focusing the attention on the salient option and the dominance attribute, and by increasing comparisons with the choice dominant pattern. Although conceptually and procedurally distinct, both pathways for decoy effects produce an increase in preferences for the target option, in line with attentional and dynamic models of decision making. Eye-tracking data provide further details to the verification of such models, by highlighting the context-dependent nature of attention and the development of similarity-driven competitive decisional processes.
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Yu, Catherine, Dorothy Choi, Brigida A. Bruno, Kevin E. Thorpe, Sharon E. Straus, Paul Cantarutti, Karen Chu, et al. "Impact of MyDiabetesPlan, a Web-Based Patient Decision Aid on Decisional Conflict, Diabetes Distress, Quality of Life, and Chronic Illness Care in Patients With Diabetes: Cluster Randomized Controlled Trial." Journal of Medical Internet Research 22, no. 9 (September 30, 2020): e16984. http://dx.doi.org/10.2196/16984.
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Background Person-centered care is critical for delivering high-quality diabetes care. Shared decision making (SDM) is central to person-centered care, and in diabetes care, it can improve decision quality, patient knowledge, and patient risk perception. Delivery of person-centered care can be facilitated with the use of patient decision aids (PtDAs). We developed MyDiabetesPlan, an interactive SDM and goal-setting PtDA designed to help individualize care priorities and support an interprofessional approach to SDM. Objective This study aims to assess the impact of MyDiabetesPlan on decisional conflict, diabetes distress, health-related quality of life, and patient assessment of chronic illness care at the individual patient level. Methods A two-step, parallel, 10-site cluster randomized controlled trial (first step: provider-directed implementation only; second step: both provider- and patient-directed implementation 6 months later) was conducted. Participants were adults 18 years and older with diabetes and 2 other comorbidities at 10 family health teams (FHTs) in Southwestern Ontario. FHTs were randomly assigned to MyDiabetesPlan (n=5) or control (n=5) through a computer-generated algorithm. MyDiabetesPlan was integrated into intervention practices, and clinicians (first step) followed by patients (second step) were trained on its use. Control participants received static generic Diabetes Canada resources. Patients were not blinded. Participants completed validated questionnaires at baseline, 6 months, and 12 months. The primary outcome at the individual patient level was decisional conflict; secondary outcomes were diabetes distress, health-related quality of life, chronic illness care, and clinician intention to practice interprofessional SDM. Multilevel hierarchical regression models were used. Results At the end of the study, the intervention group (5 clusters, n=111) had a modest reduction in total decisional conflicts compared with the control group (5 clusters, n=102; −3.5, 95% CI −7.4 to 0.42). Although there was no difference in diabetes distress or health-related quality of life, there was an increase in patient assessment of chronic illness care (0.7, 95% CI 0.4 to 1.0). Conclusions Use of goal-setting decision aids modestly improved decision quality and chronic illness care but not quality of life. Our findings may be due to a gap between goal setting and attainment, suggesting a role for optimizing patient engagement and behavioral support. The next steps include clarifying the mechanisms by which decision aids impact outcomes and revising MyDiabetesPlan and its delivery. Trial Registration ClinicalTrials.gov NCT02379078; https://clinicaltrials.gov/ct2/show/NCT02379078
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Bao, Hai Yong, Man De Xie, Zhen Fu Cao, and Shan Shan Hong. "Signature-Encryption Scheme: A Novel Solution to Mobile Computation." Advanced Materials Research 546-547 (July 2012): 1415–20. http://dx.doi.org/10.4028/www.scientific.net/amr.546-547.1415.
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Mobile communication technologies have been widely utilized in daily lives, many low-computing-power and weakly-structured-storage devices have emerged, such as PDA, cell phones and smart cards, etc. How to solve the security problems in such devices has become a key problem in secure mobile communication. In this paper, we would like to propose an efficient signature-encryption scheme. The security of the signature part is not loosely related to Discrete Logarithm Problem (DLP) assumption as most of the traditional schemes but tightly related to the Decisional Diffie-Hellman Problem (DDHP) assumption in the Random Oracle Models. Different from the existing solutions, our scheme introduces a trusted agent of the receiver who can filter the “rubbish” messages beforehand. Thus, with high efficiency in computation and storage, it is particularly suitable for the above mobile devices with severely constrained resources and can satisfy the security requirements of mobile computations.
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Lucke, Kathleen T., Hernando Martinez, Thomas B. Mendez, and Lyda C. Arévalo-Flechas. "Resolving to Go Forward." Qualitative Health Research 23, no. 2 (December 20, 2012): 218–30. http://dx.doi.org/10.1177/1049732312468062.
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Little is known about the experiences and needs of family caregivers of Latino/Hispanic individuals with spinal cord injury (SCI) during the early years of recovery. The purpose of this grounded theory study was to describe the experiences and identify the informational, decisional, interpersonal, and resource support needs of family caregivers of newly injured Latino/Hispanic individuals with SCI during the first 2 years after undergoing rehabilitation. “Resolving to go forward” was the core category that emerged from two simultaneous processes of “learning to care for” and “getting through” during the initial years as the primary informal caregiver. Most caregivers felt alone and abandoned after the injured person returned home, and experienced barriers to services and resources primarily because of language issues and economic status. We recommend that researchers develop and evaluate culturally appropriate, informal caregiving models to improve outcomes for both Latino individuals with SCI and their family caregivers.
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Peluso, Lorenzo, Thomas Boisdenghien, Laila Attanasio, Filippo Annoni, Lili Mateus Sanabria, Paolo Severgnini, Benjamin Legros, et al. "Multimodal Approach to Predict Neurological Outcome after Cardiac Arrest: A Single-Center Experience." Brain Sciences 11, no. 7 (July 1, 2021): 888. http://dx.doi.org/10.3390/brainsci11070888.
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Introduction: The aims of this study were to assess the concordance of different tools and to describe the accuracy of a multimodal approach to predict unfavorable neurological outcome (UO) in cardiac arrest patients. Methods: Retrospective study of adult (>18 years) cardiac arrest patients who underwent multimodal monitoring; UO was defined as cerebral performance category 3–5 at 3 months. Predictors of UO were neurological pupillary index (NPi) ≤2 at 24 h; highly malignant patterns on EEG (HMp) within 48 h; bilateral absence of N20 waves on somato-sensory evoked potentials; and neuron-specific enolase (NSE) >75 μg/L. Time-dependent decisional tree (i.e., NPi on day 1; HMp on day 1–2; absent N20 on day 2–3; highest NSE) and classification and regression tree (CART) analysis were used to assess the prediction of UO. Results: Of 137 patients, 104 (73%) had UO. Abnormal NPi, HMp on day 1 or 2, the bilateral absence of N20 or NSE>75 mcg/L had a specificity of 100% to predict UO. The presence of abnormal NPi was highly concordant with HMp and high NSE, and absence of N20 or high NSE with HMp. However, HMp had weak to moderate concordance with other predictors. The time-dependent decisional tree approach identified 73/103 patients (70%) with UO, showing a sensitivity of 71% and a specificity of 100%. Using the CART approach, HMp on EEG was the only variable significantly associated with UO. Conclusions: This study suggests that patients with UO had often at least two predictors of UO, except for HMp. A multimodal time-dependent approach may be helpful in the prediction of UO after CA. EEG should be included in all multimodal prognostic models.
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Lipschitz, Jessica M., Andrea L. Paiva, Colleen A. Redding, Deborah Levesque, Joseph S. Rossi, Risa B. Weisberg, and James O. Prochaska. "Development and Preliminary Psychometric Evaluation of Decisional Balance and Self-Efficacy Measures for Managing Anxiety in a National Sample of Clinically Anxious Adults." American Journal of Health Promotion 32, no. 1 (September 26, 2016): 215–23. http://dx.doi.org/10.1177/0890117116669493.
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Purpose: Anxiety is the most common and costly mental illness in the United States. Reducing avoidance is a core element of evidence-based treatments. Past research shows readiness to address avoidance affects outcomes. Investigating avoidance from a transtheoretical model (TTM) perspective could facilitate tailored approaches for individuals with low readiness. This study developed and examined psychometric properties of TTM measures for addressing anxiety-based avoidance. Design: Cross-sectional survey. Setting: Community centers, online survey. Participants: Five hundred ninety-four individuals aged 18 to 70 with clinically significant anxiety. Measures: Overall Anxiety Severity Questionnaire, stages of change, decisional balance, and self-efficacy. Analysis: The sample was randomly split into halves for principal component analyses (PCAs) and confirmatory factor analyses (CFAs) to test measurement models. Further analyses examined relationships between constructs. Results: For decisional balance, PCA indicated two 5-item factors (pros and cons). Confirmatory factor analysis supported a 2-factor correlated model, Satorra-Bentler scaled chi-square [Formula: see text], comparative fit index (CFI = 0.94), root mean square error of approximation (RMSEA = 0.07), pros: α = 0.87, ρ = 0.87, cons: α = 0.75, and ρ = 0.75. For self-efficacy, PCA indicated one 6-item factor supported by CFA, [Formula: see text], P < .01, CFI = 0.98, RMSEA = 0.09, α = 0.90, ρ = 0.87. As hypothesized, significant cross-stage differences were observed for pros and self-efficacy, and significant relationships between anxiety severity and pros, cons, and self-efficacy were found. Conclusion: Findings show strong psychometric properties and support the application of a readiness-based model to anxiety. In contrast to findings of other behaviors, cons remain high in action and maintenance. These measures provide a solid empirical foundation to develop TTM-tailored interventions to enhance engagement in treatment.
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Brodeur, Normand, Gilles Rondeau, Serge Brochu, Jocelyn Lindsay, and Jason Phelps. "Does the Transtheoretical Model Predict Attrition in Domestic Violence Treatment Programs?" Violence and Victims 23, no. 4 (August 2008): 493–507. http://dx.doi.org/10.1891/0886-6708.23.4.493.
Full textAbstract:
Attrition in intervention programs for domestically violent men is considered to be a serious and enduring problem. Researchers have found a number of sociodemographic variables that partially explain this phenomenon; however, models based on these variables have a limited predictive power. Scott (2004) argues that a firm theoretical base is needed in future investigations of the problem and suggests the use of the transtheoretical model of behavior change (TTM), which was found to predict dropout with accuracy in other areas of behavioral change. This study investigated the relationship between four TTM constructs (Stages of Change, Decisional Balance, Self-Efficacy, and Processes of Change) and premature termination with a sample of Canadian French-speaking men (N = 302) in five domestic violence treatment programs. Contrary to the initial hypotheses, the TTM constructs did not predict dropout. Discussion investigates how social desirability bias affects results being obtained by current TTM measures and whether more motivation to change at intake necessarily relates to involvement in treatment for longer periods of time.