Daily Decisions Research Articles

Leveraging technology to communicate sustainability-related product information: Evidence from the field

The information gap between businesses and consumers concerning the sustainability impacts of products and services is considered a key obstacle impeding sustainable consumption. To that end, mobile technologies, such as QR codes, have been identified as a useful tool that can bridge this information gap by providing consumers with sustainability-related product information at the point of purchase. However, the literature offers scarce insights into the factors that influence consumers' intention to use QR codes for sustainability-related product information in daily consumption decisions. This paper investigates this relationship in two studies of consumer acceptance of QR codes. Study 1 utilises the Technology Acceptance Model to study the factors that may affect consumers' intention to scan QR codes with sustainability information. The results show that the perceived ease of use and the perceived usefulness of the QR codes are significant predictors of consumers’ attitudes towards and intentions to scan QR codes. Further analysis shows that QR codes visuals and written appeals may also affect scan intention. The extant literature lacks evidence from investigations of real-life behaviour. Study 2 contributes to this gap in the literature by investigating the usage of QR codes in a field experiment. The results show an overall scan rate of 4.22% for the QR codes, with consumers scoring high on perceived usefulness of QR codes, perceived sustainability quality of the product and preference for using QR codes in the future. Importantly, QR codes with a suggestive appeal were scanned at higher rates than that of QR codes without such appeal. The paper thus responds to calls for research on how companies can leverage marketing innovations using technology to communicate sustainability-related product information to consumers and stimulate sustainable consumption. • Marketing innovations in the form of QR codes can facilitate sustainable consumption. • In collaboration with a large firm, I conduct two studies: a nationally representative survey and a field experiment. • Findings reveal that several behavioural factors are likely to influence consumers' intention to scan the QR codes. • Consumers also state preferences for the QR codes with regards to visual cues, message appeals and placement. • Overall, the two studies reveal the QR codes as a useful avenue to communicate sustainability-related product information.

Research priorities in pernicious anaemia: James Lind Alliance Priority Setting Partnership

ObjectivesTo form a James Lind Alliance (JLA) Priority Setting Partnership (PSP) to determine research priorities related to the cause, diagnosis, treatment and management of pernicious anaemia (PA) from the perspectives...

Health beliefs of emerging adults: How colleges may enhance student health literacy and co-produce healthy outcomes

Objective: Health literacy is important while attending a residential college where daily decisions can impact one’s physical and mental health and knowing who or what to trust for information is of the utmost importance in claiming more decision-making autonomy. Participants: A total of 189 students at a University in the Northeastern United States participated in this study. Methods: A cross-sectional survey assessment of shared beliefs around health behaviors was conducted. Results: Areas of high consensus center around knowledge of positive health behaviors. Consensus lessens as participants are faced with statements that require more independent thinking, more information, and more subjectivity. Gender differences are also prevalent. Conclusions: Exercising agency is needed when making a commitment to one health choice vs. another. Agency in emerging adulthood has been found to be positively correlated with commitment and deliberate decision-making both of which are needed as college students face independent health choices.

THE OPINIONS OF EDUCATION STAKEHOLDERS IN THE TABORA REGION ON STRATEGIES FOR IMPROVING DECISION-MAKING IN TANZANIA'S COMMUNITY-BASED SECONDARY SCHOOLS

<p><strong>Background:</strong> Heads of schools make decisions on a daily basis that determine the extent to which curriculum is implemented. Those daily decisions, in a big extent, determine a school's success or failure in the curriculum implementation process. <strong>Objectives:</strong> The focus of this research was to find out what education stakeholders in the Tabora region thought about strategies for improving decision-making in Tanzania's community-based secondary schools. <strong>Methodology: </strong>Quantitative approach and survey research designs were used in the study. The information was gathered from 140 people using a questionnaire research tool. Heads of secondary schools, teachers, parents, Quality Assurers (QA) and District Education Officers (DEO) are among the respondents. <strong>Findings:</strong> The study findings found participatory decision-making procedures, adherence to the country’s education and training policy and having an effective mentorship and pedagogical leadership programmes in schools as the main strategies to follow in order to improve decision-making in schools. The collected findings confirm the claim of the study's informant, a decision-making theory, making the important proclamation that for decision-making procedures to be effective, they must proceed step-by-step and involve a range of essential stakeholders from the outset to the conclusion. <strong>Recommendations:</strong> The study recommended that heads of schools should adopt a participatory decision-making process, adhere to Tanzania's education and training policy standards, and establish effective mentorship and pedagogical leadership programmes in schools.</p><p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0952/a.php" alt="Hit counter" /></p>

Feeling the Future? Mixed Empirical Evidence for a Link Between Processing Fluency and Judgments About Future Probability

Many daily decisions require estimates of the inherently indeterminate probability of future events. We propose that people rely on heuristics instead of formal reasoning to come up with such estimates and that processing fluency may serve as a heuristic cue. Across seven experimental online studies that use random samples of MTurk workers as participants, statistical mediation analyses provide support for the notion that manipulating the fluency of utopic city pictures (presentation duration: 300 vs. 900 ms), statements about future societal developments (prior exposure: no vs. yes), and election promises made on Twitter during the 2020 U.S. presidential race (presentation size: small vs. large) has an indirect effect via subjective fluency on estimated probabilities of future occurrences. However, the total effects of the experimental manipulations on probability judgments show no consistent pattern, being negative in one study, positive in two studies, and not different from zero in the remaining four studies.

Predicting COVID-19 county-level case number trend by combining demographic characteristics and social distancing policies.

ObjectivePredicting daily trends in the Coronavirus Disease 2019 (COVID-19) case number is important to support individual decisions in taking preventative measures. This study aims to use COVID-19 case number history, demographic characteristics, and social distancing policies both independently/interdependently to predict the daily trend in the rise or fall of county-level cases.Materials and MethodsWe extracted 2093 features (5 from the US COVID-19 case number history, 1824 from the demographic characteristics independently/interdependently, and 264 from the social distancing policies independently/interdependently) for 3142 US counties. Using the top selected 200 features, we built 4 machine learning models: Logistic Regression, Naïve Bayes, Multi-Layer Perceptron, and Random Forest, along with 4 Ensemble methods: Average, Product, Minimum, and Maximum, and compared their performances.ResultsThe Ensemble Average method had the highest area-under the receiver operator characteristic curve (AUC) of 0.692. The top ranked features were all interdependent features.ConclusionThe findings of this study suggest the predictive power of diverse features, especially when combined, in predicting county-level trends of COVID-19 cases and can be helpful to individuals in making their daily decisions. Our results may guide future studies to consider more features interdependently from conventionally distinct data sources in county-level predictive models. Our code is available at: https://doi.org/10.5281/zenodo.6332944.

Dominance or Integration? Influence of Sexual Dimorphism and Clothing Color on Judgments of Male and Female Targets' Attractiveness, Warmth, and Competence.

The face is an important source of information in social interactions. Prior studies exploring the mechanism of face perception were consistent with either dominance or integration theory. Studies have shown that both sexually dimorphic features and background cues play essential roles in the formation of impressions and the perception of facial attractiveness. In this study, we conducted two experiments to examine 539 participants’ appraisal of attractiveness, warmth, and competence of the target faces of masculine and feminine men and women dressed in red, blue, or white. The results showed that: (1) feminized male/female faces were considered to have a higher degree of attractiveness, warmth, and competence, (2) people rated feminine faces wearing red higher in terms of attractiveness perception, while there was no significant effect of red on attractiveness perception of masculine faces, (3) when evaluating the warmth of targets, the promotion effect of red was found for feminine faces but not for masculine faces. This study, conducted in a pathogen disgust environment, provides direct evidence to support the integration theory over the dominance theory. Feminized red preference found in this study matches Chinese collectivism and the red cultural heritage, which has an important value for people's daily impression management and consumption decisions.

Health claim effects on consumer acceptability, emotional responses, and purchase intent of protein bars

Consumers are seeking product's claims to make their daily food purchase decisions more informed. In this context, health claims can communicate to consumers about nutrient-specific health benefits. The objective of this research was to study the effect of health claims, in textual form, on consumers' acceptability, emotional responses, and purchase decisions regarding protein bars. For this study, four protein bars were selected by a focus group ( N = 6) based on acceptability. A total of N = 80 participants evaluated the pre-selected protein bars in two different tasting sessions [(1) Blind, where no information was provided, and (2) Informed, where health-related information of protein bars was provided]. Participants rated their liking for different sensory attributes (appearance, aroma, taste, texture, sweetness, bitterness, and aftertaste) and overall liking using a 9-point hedonic scale. Check-all-that-apply (CATA) was used to study emotions and 22 terms related to sensory attributes of the protein bar. There was a non-significant increase in the purchase intent for three out of four samples in session 2 but it was found to be high for the sample associated with positive emotions. Overall, this study showed that taste overpowered the health claims (expressed in textual form) on the acceptability. There were, however, slight effects of the health claims on the elicited emotions of consumers towards the protein bars. • Health claims, expressed in textual form, do not affect the sensory liking of protein bars. • Taste and flavour were the main differentiating factors in the protein bars when considering their sensory acceptability. • Protein bars associated with positive emotions had higher purchase intent.

Computational Technologies for Pakistani Consumers’ Understanding of the Country-of-Origin Label for Fruit and Vegetable Products in Social Networks

Whether or not consumers consider information about origin in their routine food purchase decisions is a contentious issue. Usage of social networks has redefined lifestyle and culture, and firms are finding it difficult to understand their customers. This study aims to investigate the effect of social networks (digital marketing) on Pakistani consumers’ understanding of the CoO (country-of-origin) label for F&V (fruit and vegetable) products and its relative importance in daily purchase decisions of fruit and vegetable products. In a random survey of 797 consumers in two Pakistani cities, we found that the relationship between the CoO information and the daily F&V product choices of Pakistani consumers was less important than other factors. Consumers are mistaken about the CoO label, with only one-third of respondents correctly understanding the difference between labels of “made in...” and “product of....” Therefore, mandatory CoO label policies may increase costs and reinforce consumers’ misinterpretation of the meaning of these labels; obtaining a “user-friendly” CoO label serves only those consumers who properly understand the information. This study contributes to understanding of the extent to which consumers are competent in their knowledge and understanding of these informational labels.

Contamination classification for pellet quality inspection using deep learning

For many applications it is critical to deliver a contamination free polyethylene product. Therefore, continuous inspection of polymer production is vital. Most systems inspect a pellet stream in an at-line fashion and provide feature information about any present contaminant such as color and size. However, in certain scenarios it is also of interest to determine whether the contamination is free flowing in the pellet stream (loose) or incorporated into the polymer pellet (embedded). Typical analytical equipment does not provide this information and the classification is thus a manual and subjective task.To automate this classification, a multi-class classifier was built with a convolutional neural network (CNN), including InceptionV3, VGG16, and ResNet50, were tested with and without image augmentation and the trained model was able to achieve an accuracy greater than 95% for all classes on the test set. This is a successful application of deep learning techniques to directly improve manufacturing efficiency, and the model is currently in use for daily decision making.

An interpretable decision-support systems for daily cryptocurrency trading

Cryptocurrencies, especially Bitcoin (BTC), have become an important commodity for both individual and corporate investors within the last decade. The limited supply, high volatility, and random price fluctuations have increased investors' interest in BTC, especially in daily trading. Although BTC has been yielding a high rate of returns, price fluctuations and constant speculations make the investors wary of unexpected price movements. Predictive modeling suffers from the complexity of the datasets (i.e., the high number of features employed to forecast BTC movements) as well as the black-box nature of most machine learning algorithms (which is especially problematic for corporate investors since they are obligated to disclose their investment decisions to their clients). Therefore, the main goal of the current study is to assist individual and corporate investors in making transparent and interpretable daily BTC trading decisions by developing a predictive analytics framework. To address the complexities posed by the datasets, a comprehensive tri-level feature selection approach is proposed. The selected features are then, fed into the Classification & Regression Tree (C&RT) to build a highly parsimonious, transparent, and interpretable prediction model. The resultant model was not only evaluated on the test (holdout) sample but was also tested on challenging time periods, including the first half of 2020 (the start of the pandemic era) to exhibit the viability and reliability of the proposed framework. Finally, a decision support tool is developed for the practical implementation of the model. The tool can be used by short-term investors not only due to its highly simplistic, transparent, and interpretable structure, but also its higher accuracy, sensitivity, and specificity results when compared to the extant literature.

Factors that determine paratransit drivers’ willingness to participate in formal bus services in an African city

Small and medium-sized buses that operate in an unscheduled manner, called paratransit, have become the primary means of public transportation in African cities. Despite the stress and unfair labour conditions that paratransit drivers endure, it is unclear why some drivers are willing to join formal bus services such as bus rapid transit while others resist. Whereas paratransit drivers have the autonomy to make daily decisions, formal drivers follow strict schedules. We surveyed paratransit drivers in Accra to examine how they respond to losing control of daily decisions to identify the factors that influence their participation in formal transportation under different financial incentives. The results show that although increasing financial incentives attract most drivers, the desire to control their own decisions and unpleasant past experiences with formal services influence participation. Our models show that age, ownership of vehicles, and preference for regular or irregular income are important factors influencing their participation. Policymakers and bus reform implementation agencies should consider that some paratransit drivers are not interested in the benefits of formal services but prefer the autonomy associated with their daily decisions.

Ventilatory weaning strategies for predicting extubation success in children following cardiac surgery for congenital heart disease: a protocol for a systematic review and meta-analysis

IntroductionCongenital heart disease (CHD) comprises the anatomic malformations that jeopardise the structure and function of the heart. It can be extremely complex and serious, corresponding to 30% of all deaths...

Lessons Learned From Dear Pandemic, a Social Media-Based Science Communication Project Targeting the COVID-19 Infodemic.

The World Health Organization has identified excessive COVID-19 pandemic–related information as a public health crisis, calling it an “infodemic.” Social media allows misinformation to spread quickly and outcompete scientifically grounded information delivered via other methods. Dear Pandemic is an innovative, multidisciplinary, social media–based science communication project whose mission is to educate and empower individuals to successfully navigate the overwhelming amount of information circulating during the pandemic. This mission has 2 primary objectives: (1) to disseminate trustworthy, comprehensive, and timely scientific content about the pandemic to lay audiences via social media and (2) to promote media literacy and information-hygiene practices, equipping readers to better manage the COVID-19 infodemic within their own networks. The volunteer team of scientists publishes 8-16 posts per week on pandemic-relevant topics. Nearly 2 years after it launched in March 2020, the project has a combined monthly reach of more than 4 million unique views across 4 social media channels, an email newsletter, and a website. We describe the project’s guiding principles, lessons learned, challenges, and opportunities. Dear Pandemic has emerged as an example of a promising new paradigm for public health communication and intervention. The contributors deliver content in ways that are personal, practical, actionable, responsive, and native to social media platforms. The project’s guiding principles are a model for public health communication targeting future infodemics and can bridge the chasm between the scientific community and the practical daily decision-making needs of the general public.

Optimization of Customer-Side Battery Storage for Multiple Service Provision: Arbitrage, Peak Shaving, and Regulation

Battery storage management that involves multiple revenue streams would affect customers’ monthly electricity costs. In this article, a three-level model of battery storage management is proposed for achieving various functionalities, including energy arbitrage, peak shaving, and frequency regulation. The original joint optimization problem with the horizon of one month is decomposed into three subproblems according to time scales, covering the daily battery power baseline decision, hourly regulation capacity submission, and real-time regulation response in seconds. A dynamic programming framework is adopted to integrate three submodels, featuring reduced solving complexity and the overall optimality of the proposed model. Also, the unexpected regulation capacity of customers and the uncertainty of exogenous information are considered to accurately depict the characteristics of practical scenarios. Extensive case studies for two types of customers, i.e., the pure consumer and the prosumer, are conducted to validate the effectiveness of the proposed model, which achieves at least 6% (consumer) and 19% (prosumer) benefit improvement as compared with other strategies.

Peer feedback decreases impulsive choice in adolescents with and without attention-deficit/hyperactivity disorder.

Impulsivity is a core feature of attention-deficit/hyperactivity disorder (ADHD). Previous work using the delay discounting task to assess impulsivity reveals that adolescents with ADHD tend to prefer a smaller-immediate reward over a larger-delayed reward, and this relates to problematic choices in daily life. To gain a better understanding of daily decision-making in adolescence, it is important to examine the social context, as peers have a major influence on decisions. Peer influence often has a negative connotation, but also provides an opportunity to promote positive outcomes. To date, it is unclear if peers affect impulsive decision-making in adolescents with ADHD, for better or for worse. The aim of this preregistered study was to examine the effect of peer feedback on impulsive choice in male adolescents with and without ADHD (ages 13-23; N=113). We utilized an adapted delay discounting task that was administered alone, in a social condition, and alone again. In the social condition, adolescents received either (between-subjects) manipulated impulsive or non-impulsive peer feedback. Impulsive peer feedback consisted of likes for choosing the smaller immediate reward, whereas non-impulsive peers endorsed choosing the larger delayed reward. Preregistered analyses showed that non-impulsive peer feedback resulted in decreased impulsive choice, whereas impulsive peer feedback did not alter decision-making in adolescents with and without ADHD. Explorative analyses of inattention and hyperactivity-impulsivity symptoms in the total sample, irrespective of diagnosis, showed that lower hyperactivity-impulsivity and more inattention symptoms were associated with increased susceptibility to non-impulsive peer feedback. Together, these findings indicate that peers may provide an opportunity to decrease impulsivity and emphasize individual differences in susceptibility to non-impulsive peer feedback related to inattention and hyperactivity-impulsivity. Therefore, peer feedback may be a promising component in behavioral peer-supported interventions in adolescents with ADHD.

A goal programming model for the optimization of log logistics considering sorting decisions and social objective

Log logistics include sorting, processing, and transporting of logs from their place of harvest to demand locations. These activities account for a significant portion of the total log procurement costs; therefore, attempts were made in previous studies to optimize some aspects of log logistics. However, operational details, such as sorting decisions, truck compatibility requirements, and social objectives, are often disregarded in the optimization literature. Incorporating these details into the model makes the results more realistic and applicable. To address these gaps, a bi-objective mixed-integer programming model is developed in this paper to optimize log logistics. The first objective is to minimize total logistics costs, and the second objective is to provide a balanced workload for trucking contractors. The bi-objective model is solved using the goal programming approach. The model is applied to log logistics of a large Canadian forest company, where trucking contractors use heterogeneous fleet of trucks to carry various log sorts from cutblocks to sort yards for sorting. The planning horizon is 4 weeks with daily decisions. The goal programming model generates balanced workloads for the contractors with less than 0.4% increase in total costs compared to the single objective model where only the total cost is minimized.

Role of Brachytherapy in the Postoperative Management of Endometrial Cancer: Decision-Making Analysis among Experienced European Radiation Oncologists.

Simple SummaryThere are various society-specific guidelines addressing adjuvant brachytherapy (BT) after surgery for endometrial cancer (EC). However, these recommendations are not uniform. Against this background, clinicians need to make decisions despite gaps between best scientific evidence and clinical practice. We analysed decision criteria influencing the selection for adjuvant radiotherapy among European radiation oncology experts. For this, GEC-ESTRO provided 19 European radiation oncology experts on gynaecological brachytherapy for decision-making analyses. The manuscript presents patterns in decision-making among these experts and demonstrates areas of consensus/discrepancies. We also analysed dose prescription and techniques of brachytherapy. This analysis is of special value as the objective approach enabled us to obtain an unbiased description of decision-making among the specialists (the study was not aimed to create or enforce a consensus). The manuscript provides valuable insight into clinical decision-making with a high impact on treatment selection, as expected differences between experts were observed. With this manuscript we are able to visualize and quantify these. This information is relevant for interdisciplinary discussions.Background: There are various society-specific guidelines addressing adjuvant brachytherapy (BT) after surgery for endometrial cancer (EC). However, these recommendations are not uniform. Against this background, clinicians need to make decisions despite gaps between best scientific evidence and clinical practice. We explored factors influencing decision-making for adjuvant BT in clinical routine among experienced European radiation oncologists in the field of gynaecological radiotherapy (RT). We also investigated the dose and technique of BT. Methods: Nineteen European experts for gynaecological BT selected by the Groupe Européen de Curiethérapie and the European Society for Radiotherapy & Oncology provided their decision criteria and technique for postoperative RT in EC. The decision criteria were captured and converted into decision trees, and consensus and dissent were evaluated based on the objective consensus methodology. Results: The decision criteria used by the experts were tumour extension, grading, nodal status, lymphovascular invasion, and cervical stroma/vaginal invasion (yes/no). No expert recommended adjuvant BT for pT1a G1-2 EC without substantial LVSI. Eighty-four percent of experts recommended BT for pT1a G3 EC without substantial LVSI. Up to 74% of experts used adjuvant BT for pT1b LVSI-negative and pT2 G1–2 LVSI-negative disease. For 74–84% of experts, EBRT + BT was the treatment of choice for nodal-positive pT2 disease and for pT3 EC with cervical/vaginal invasion. For all other tumour stages, there was no clear consensus for adjuvant treatment. Four experts already used molecular markers for decision-making. Sixty-five percent of experts recommended fractionation regimens of 3 × 7 Gy or 4 × 5 Gy for BT as monotherapy and 2 × 5 Gy for combination with EBRT. The most commonly used applicator for BT was a vaginal cylinder; 82% recommended image-guided BT. Conclusions: There was a clear trend towards adjuvant BT for stage IA G3, stage IB, and stage II G1–2 LVSI-negative EC. Likewise, there was a non-uniform pattern for BT dose prescription but a clear trend towards 3D image-based BT. Finally, molecular characteristics were already used in daily decision-making by some experts under the pretext that upcoming trials will bring more clarity to this topic.

Dupilumab for atopic dermatitis: a real-world Portuguese multicenter retrospective study

Introduction Atopic dermatitis (AD) is a difficult-to-treat inflammatory skin disease with a high impact on patients’ quality of life. Dupilumab, an IL-4 and IL-13 inhibitor, was the first monoclonal antibody approved for the treatment of moderate-to-severe AD and is currently approved in patients aged 6 or older. Methods This is a nationwide, multicenter, retrospective, 48-week study designed by the Portuguese Group of AD to assess real-world efficacy and safety of dupilumab for the treatment of AD. Results A total of 169 patients were enrolled, with a mean disease duration of 22.75 (±11.98) years. The percentage of patients achieving an improvement of at least 75% in Eczema Area and Severity Index (EASI) compared to baseline (EASI75 response) at weeks 12 and 48 was 67.6% and 74.1%, respectively. In the same timepoints, 25.0% and 44.1% achieved an EASI90 response. Patient-reported outcome measures also improved throughout the study period. Regarding safety, 32.0% of the patients developed adverse events, with conjunctivitis (26.6%), persistent facial erythema (4.7%), and arthritis/arthralgia (3.6%) as the more frequently reported. Conclusion Data from real-world populations are crucial to guide clinicians in their daily decisions. This study provides data demonstrating that dupilumab is an effective and safe therapeutic option for AD.

Danish cattle veterinarians' perspectives on antimicrobial use: Contextual and individual influencing factors

The global risk for antimicrobial resistance (AMR) can be reduced by reducing antimicrobial use (AMU). Veterinarians are one of the key actors in relation to AMU in livestock, and understanding the dynamics of veterinary treatment and prescription is central to achieving AMU reduction. Veterinary AMU decisions are influenced by a complex pattern of both individual and contextual factors. In this study, we conducted semi-structured interviews with 16 Danish cattle veterinarians to investigate their perspectives on AMU and current practices in a national context with low use and extensive legal control. We found that personal experiences and emotions, rather than scientific evidence, guided some veterinarians when making AMU choices. Furthermore, less-experienced veterinarians felt pressure to prescribe according to colleagues' and farmers' preferences for certain antimicrobials. We found that changes in Danish legislation seemed to have introduced hesitancy and a lack of motivation within the veterinary profession, and that AMR was perceived as an abstract threat not applicable to the veterinarians' daily professional decision making. We concluded that the lack of field-generated research of local relevance nourished a culture in which AMU choices are built on personal experience rather than scientific evidence, which also diminished newly educated veterinarians' self-confidence in relation to their AMU choices. Future research should focus on developing locally relevant research on optimal AMU choices and AMR, and the implications of extensive legal control of AMU in livestock farming should be further investigated to find a balance on the path to reducing AMU.