When do drivers conform? When do they deviate?

Traditional and dominant social influence strategies based on group research aim to motivate people towards compliance with the group norm for behaviours in general and in traffic in particular. Yet, deviance and dissent have the potential to motivate people towards action against group norm, as well. The deviance regulation theory (DRT) proposes that an individual might choose to deviate from the group norm to express his/her uniqueness. In addition, according to the normative conflict model, an individual might deviate because the target behaviour may serve for the group benefit. However, up to date no study has compared behaviours of different nature in terms of conformity and deviance motivations in traffic. The current study explores these motivations in the context of persuasive messages that aim to facilitate picking up hitchhikers, obeying speed limits on campus, and seat belt use, in three different samples. In the first study, we investigated the effectiveness of positive and negative message frames. These messages emphasized the attributes of people on uniqueness or group benefit who pick up or do not pick up hitchhikers with regard to the perceived group norms in a 2 (norm: picking up or not picking up a hitchhiker) by 4 (message frame: positive uniqueness, negative uniqueness, positive group benefit, negative group benefit) design among 249 participants. The results revealed that positive uniqueness frame is effective when the norm is picking up a hitchhiker, but not when the norm is not picking up a hitchhiker. In the second and third studies, we applied a 2 (norm) × 2 (uniqueness message frame: positive and negative) design for speeding on campus and seat belt use with 79 and 144 participants, respectively. The speeding study supports the DRT, as the negative frame in obeying the speed limit norm condition had a stronger effect on reducing speeding than the other conditions. Using seat belt emerged as impervious to norms and evaluation of group members, since none of the conditions differed from each other.The Scientific and Technological Research Council of Turkey (TÜBİTAK) Turkish Academy of Sciences TÜBA-GEBIP suppor

A data-driven decision support system with smart packaging in grocery store supply chains during outbreaks

The unexpected emergence of the COVID-19 pandemic has changed how grocery shopping is done. The grocery retail stores need to ensure hygiene, quality, and safety concerns in-store shopping by providing “no-touch” smart packaging solutions for agri-food products. The benefit of smart packaging is to inform consumers about the freshness level of a packaged product without having direct contact. This paper proposes a data-driven decision support system that uses smart packaging as a smart product-service system to manage the sustainable grocery store supply chain during outbreaks to prevent food waste. The proposed model dynamically updates the price of a packaged perishable product depending on freshness level while reducing food waste and the number of rejected customers and maximising profit by increasing the inventory turnover rate of grocery stores. The model was tested on a hypothetical but realistic case study of a single product. The results of this study showed that stock capacities, freshness discount rate, freshness period, and quantity discounts significantly affect the performance of a grocery store supply chain during outbreaks

Data-driven optimal dynamic pricing strategy for reducing perishable food waste at retailers

Approximately forty per cent of fresh products are wasted in low and middle-income countries before reaching consumers. Perishable foods have only a certain shelf-life and they need to be sold for consumption before a specific date. When a product is priced incorrectly, it is often disposed of directly or redistributed. Redistribution of surplus food also has an economic impact on food prices. Therefore, setting an optimal pricing strategy is crucial to reduce inventory and surplus food in an environment with volatile demands. In this context, big data analytics can help managers forecast customer behaviour and determine pricing strategies throughout the retail industry. This study focuses on food waste at the retailer stage of food supply chain (FSC). We present a dynamic pricing model that uses real-time Internet of Things (IoT) sensor data as a novel contribution to decide pricing at different stages of a sales season for retailers. The food waste problem at the retail stage of a FSC is investigated in a pilot project for bulk apple sales to address the research question. This study proposes a four-stage data-driven optimal dynamic pricing strategy for bulk produce to reduce food waste for retailers in low and middle-income countries. A multi-stage dynamic programming method is used to decide on a pricing strategy for bulk produce, with real-time IoT sensor data being retrieved to analyse and determine the length of freshness scores. The effect of the sale price, replenishment amount, discount rate, and freshness score on profit and food waste are evaluated. All these analyses assist managers in taking the best possible actions and remedies. Appropriate interventions boost sales, increase profits by reducing waste and determining competitive sales price, while improving customer loyalty and satisfaction by striking the right balance between food quality and price. Our results show the huge potential of using hyperspectral imaging sensors in the FSC of a retailer. The model is demonstrated empirically to test its practicability

Neurological features and outcomes of Wilson's disease: a single-center experience

Wilson's disease (WD) is an autosomal recessive genetic disorder of copper metabolism, and WD patients can present with neurologic symptoms. We aimed to report the general characteristics and prognosis of a Turkish series of WD patients with neurological manifestations. A total of 12,352 patients were screened from the patient database, and 53 WD patients were included. Patients were classified based on the predominant neurological syndrome type including tremor, dystonia, parkinsonism, or discrete neurological signs and were classified as having "good outcome," "stable," and "poor outcome" according to their treatment response. There were 32 male and 21 female patients, aged 20-66 years. The mean follow-up was 11.3 +/- 4.56 years. Sixty-two percent of patients presented predominantly with neurological symptoms. Neurological WD diagnosis was established after a mean time delay of 2.3 years from the WD diagnosis. The most common neurological manifestation was dystonia, followed by tremor and parkinsonism. Fifteen patients had a family history of WD. Consanguinity was present in 20 patients. Patients were treated with D-penicillamine, trientine, zinc salts, or their combinations. Besides the main treatments, 41 patients were on symptomatic treatment for neurologic symptoms. Thirty-six patients had a "good outcome," five patients were stable, and six patients had "poor outcome." Post-chelation neurological worsening was observed in 11 patients. WD should be considered in differential diagnosis in any patient with unexplained neurologic symptoms. Early diagnosis is important, and appropriate treatment should be promptly initiated to prevent progressive and irreversible damage, with good prognosis and stable disease in the majority of the patients with treatment compliance

Anticholinergic Burden, Polypharmacy, and Cognition in Parkinson's Disease Patients with Mild Cognitive Impairment: A Cross-Sectional Observational Study

Introduction: Anticholinergic burden may be an important risk factor for the cognitive impairment. Especially in polypharmacy, even drugs with low anticholinergic effects may contribute to a significant anticholinergic burden. The drugs with anticholinergic effects are used in treatment of motor and nonmotor symptoms of Parkinson's disease (PD). Therefore, it is important to screen for polypharmacy and anticholinergic burden in PD patients with mild cognitive impairment (MCI). Methods: This cross-sectional study was conducted with 58 patients with PD. PD-MCI was diagnosed according to MDS Level 2 Comprehensive Assessment. Cognitive performance (attention - working memory, executive functions, language, memory, and visuospatial functions) of patients was evaluated. The anticholinergic burden was scored by Anticholinergic Cognitive Burden (ACB) Scale, Anticholinergic Risk Scale (ARS), and Anticholinergic Drug Scale (ADS). Results: There was no significant difference in anticholinergic burden between PD-MCI and PD-normal cognition. A significant concordance was observed between ACB, ARS, and ADS scores (p < 0.001; Kendall's W = 0.653). While the variable predicting anticholinergic burden was the total number of drugs for ACB and ADS scales, it was the number of antiparkinson drugs for ARS scale. Conclusion: Patients with PD are at high risk for polypharmacy and anticholinergic burden. Anticholinergic burden should be considered in the selection of drugs, especially for comorbidities in patients with PD. No significant correlation was found between the cognition and anticholinergic burden in patients with PD-MCI. Although the risk scores of antiparkinson and other drugs were different among the 3 scales, significant concordance was observed between scales

THE APPLICABILITY OF A PREMATURE EJACULATION PROFILE QUESTIONNAIRE FORMS IN OUR COUNTRY

WOS: 000282109300168

THE DEMOGRAPHY AND PARTNER'S RELATIONSHIP OF PREMATURE EJACULATION IN TURKEY: MULTICENTER STUDY

WOS: 000282109300169

Medication management and treatment adherence in Parkinson's disease patients with mild cognitive impairment

Introduction The key feature that distinguishes mild cognitive impairment (MCI) from dementia is the absence of significant functional decline because of cognitive impairment. In Parkinson's disease patients (PD) with MCI (PD-MCI), the effect of cognitive impairment on complex instrumental daily activities, such as medication management, is not well established. Method 26 patients with PD-MCI (diagnosed to Level 2 Movement Disorders Society diagnostic criteria) and 32 idiopathic PD patients without cognitive impairment participated in the study. A detailed neuropsychological testing battery (including tests for attention and working memory, executive functions, language, visuospatial functions, episodic memory) and various prospective memory tasks were applied to the patients. Medication taking behaviors were evaluated using two different methods based on the performance (medication management ability assessment) and self-reporting (adherence scale). Results The PD-MCI group obtained significantly lower scores in medication management assessment and made more mistakes on following prescription instructions (e.g., they took more or less tablets and did not use medications as instructed with regard to meal times). Cognitive areas predicting success in medication management performance were language, event-based prospective memory and visuospatial functions. There was no significant difference between the two groups' self-reporting of adherence. Conclusion Mild cognitive impairment in patients with PD adversely affects medication management. Diagnosing MCI in PD is important to ensure that the appropriate measures can be taken to provide support and improve the medication management process. Adherence assessments based on self-reporting may not provide reliable and sensitive information in patients with PD-MCI

Impact of Earthquake on Multiple Sclerosis Attacks

Objective: The association between stressful life events and subsequent multiple sclerosis (MS) attacks has been frequently reported with conflicting results. In this study, we investigated the impact of a common stressor on MS attacks. Methods: We prospectively evaluated the attack and disability status of 48 consecutive relapsing remitting (RRMS) or secondary progressive MS (SPMS) patients (Group 1) exposed to 1999 Izmit earthquake in comparison to 34 consecutive MS patients (Group 2) with similar demographic and clinical features and living outside the earthquake zone