scholarly journals Mind the Gap: Stated versus Revealed Donations and the Differential Role of Behavioral Factors

2019 ◽  
Vol 95 (2) ◽  
pp. 225-245 ◽  
Author(s):  
J. A. Bouma ◽  
M. J. Koetse
Keyword(s):  
Behavioral Factors

scholarly journals Assessment of behavioral factors influencing cooperation in logistics

2020 ◽  
Vol 18 (3) ◽  
pp. 34-44 ◽  
Author(s):  
Tetiana Kolodizieva
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Methodological Approach ◽  
Behavioral Approach ◽  
Dual Relationships ◽  
Behavioral Factors ◽  
Factors Influencing ◽  
The Social

The article explores theoretical and methodical aspects of managing dual relationships that arise between participants in logistic cooperation in the process of formation and functioning of supply chains. The use of a behavioral approach to defining supply chains has allowed identifying and justifying the priority role of behavioral factors that influence modern logistics entities and determine the effectiveness and long-term satisfaction with logistics cooperation. Given the literature summary, the study has classified types of cooperation in logistic activity and proved that among the behavioral factors influencing the of logistical cooperation efficiency, the trust is of particular importance, which remains a limitation, a bottleneck in the process of formation and development of dual relationships in logistics chains. It is proposed to introduce a generic indicator, namely the level of confidence in the supply chain to assess the social, economic and strategic aspects of logistics interaction. A methodological approach to assessing the level of trust in logistic cooperation was adjusted based on determining the composition of criteria that directly affect this indicator and using the expert survey of supply chain participants. The study proposes to use the confidence indicator to form and improve networks and supply chains, taking into account its value when constructing a generalized outsourcing model.

scholarly journals The influence of cognitions, emotions and behavioral factors on treatment outcomes in musculoskeletal shoulder pain: a systematic review

2019 ◽  
Vol 33 (6) ◽  
pp. 980-991 ◽  
Author(s):  
Liesbet De Baets ◽  
Thomas Matheve ◽  
Mira Meeus ◽  
Filip Struyf ◽  
Annick Timmermans
Keyword(s):  
Surgical Treatment ◽  
Shoulder Pain ◽  
Self Efficacy ◽  
Pain Catastrophizing ◽  
Behavioral Factors ◽  
Fear Avoidance ◽  
Mediating Role ◽  
Predictive Role ◽  
Moderating Role

Objective: To examine the predictive, moderating and mediating role of cognitive, emotional and behavioral factors on pain and disability following shoulder treatment. Data sources: Electronic databases (PubMed, Web of Science, Embase and PsycINFO) were searched until 14 January 2019. Study selection: Studies including persons with musculoskeletal shoulder pain that describe the predictive, moderating or mediating role of baseline cognitive, emotional or behavioral factors on pain or disability following treatment were selected. Results: A total of 23 articles, describing 21 studies and involving 3769 participants, were included. Three studies had a high risk of bias. There was no predictive role of baseline depression, anxiety, coping, somatization or distress on pain or disability across types of shoulder treatment. No predictive role of fear-avoidance beliefs was identified in patients receiving physiotherapy, which contrasted to the results found when surgical treatment was applied. Baseline catastrophizing was also not predictive for pain or disability in patients receiving physiotherapy. After conservative medical treatments, results on the predictive role of catastrophizing were inconclusive. Treatment expectations and baseline self-efficacy predicted pain and disability in patients receiving physiotherapy, which was not the case in patients receiving conservative medical treatment. Finally, there was a moderating role for optimism in the relationship between pain catastrophizing and disability in patients receiving physiotherapy. Conclusion: There is evidence that expectations of recovery and self-efficacy have a predictive role and optimism a moderating role on pain and/or disability following physiotherapy for musculoskeletal shoulder pain. After surgical treatment, fear-avoidance is a predictor of pain and disability.

scholarly journals SOCIAL AND BEHAVIORAL FACTORS IN COGNITIVE AGING: APPLYING THE CAUSAL INFERENCE FRAMEWORK IN OBSERVATIONAL STUDIES

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S323-S323
Author(s):  
Anja K Leist
Keyword(s):  
Machine Learning ◽  
Cognitive Decline ◽  
Causal Inference ◽  
Cognitive Aging ◽  
Behavioral Interventions ◽  
Observational Studies ◽  
Intervention Research ◽  
Learning Approaches ◽  
Behavioral Factors

Abstract Rationale: There is an urgent need to better understand how to maintain cognitive functioning at older ages with social and behavioral interventions, given that there is currently no medical cure available to prevent, halt or reverse the progression of cognitive decline and dementia. However, in current models, it is still not well established which factors (e.g. education, BMI, physical activity, sleep, depression) matter most at which ages, and which behavioral profiles are most protective against cognitive decline. In the last years, advances in the fields of causal inference and machine learning have equipped epidemiology and social sciences with methods and models to approach causal questions in observational studies. Method: The presentation will give an overview of the causal inference framework and different machine learning approaches to investigate cognitive aging. First, we will present relevant research questions on the role of social and behavioral factors in cognitive aging in observational studies. Second, we will introduce the causal inference framework and recent methods to visualize and compute the strength of causal paths. Third, promising machine learning approaches to arrive at robust predictions are presented. The 13-year follow-up from the European SHARE survey that employs well-established cognitive performance tests is used to demonstrate the usefulness of the approach. Discussion: The causal inference framework, combined with recent machine learning approaches and applied in observational studies, provides a robust alternative to intervention research. Advantages for investigations under the new framework, e.g., fewer ethical considerations compared to intervention research, as well as limitations are discussed.

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