Individual Decisions Research Articles

Suburbanization in Multi-ethnic Area – Conflicts and Local Strategies

The effects of suburbanization can be examined from several aspects, but beyond the individual decisions that initiated it, the real estate market aspects, or the transformation of land use, the effects on local communities and their reactions are rarely highlighted in professional circles. In our work within the agglomeration of Bratislava, the Slovak capital, we researched individual and collective opinions on suburbanization, as well as the questions and potential conflict situations arising among members of the “host community.” A striking element of the study area is that migration also means a change in the linguistic environment, as the newcomers often arrive from a predominantly Slovakspeaking city to an area mostly inhabited by the Hungarian minority. This adds additional dimensions to suburbanization and the responses it generates. Experiences show that the municipalities affected by the process use independent, yet in certain respects similar, strategies to manage it, and as part of these strategies, the ethnic factor also appears prominently in some topics.

Towards visual sentiment summary to understand customers’ satisfaction

Due to the COVID-19 pandemic, the shopping behavior of customers has been significantly affected and is being shifted towards online shopping. Understanding the customers’ opinions, attitudes, and emotions in feedback and comments plays an essential role in making decisions for organizations and individuals (e.g., companies and customers). In this study, we propose sentiment summaries from the customer knowledgebase (SSoCK) framework that analyses customer feedback and improve a mechanism for sentiment summarization by using text analysis including sentiment analysis. In the experiments, various domains from customer reviews (e.g., computer and Canon) are used to conduct. The results show that the proposed SSoCK framework has the high performance of sentiment classification in terms of its accuracy when compared to the other approaches. Moreover, the proposed framework generates various kinds of sentiment summaries that can support managers/potential customers understand trending/interesting aspects of the product with customer satisfaction and can be easily updated with new reviews within the same domain without storing any original data.

Orientation and mental representations in the decision-making process: a comparison between junior and senior professional

In the workplace, professionals have an orientation to individual or group decision-making based on ideal or real representation of the group situation. However, no previous studies investigated these dimensions in professionals of different ages. A total of 216 professionals were enrolled in this study based on their work experience and seniority. Specifically, senior professionals were from different Italian consulting companies, while juniors had not yet approached the world of work, but were completing their professional education. Participants were asked to read a realistic decision-making scenario and rate their individual or group decision-making orientation, thinking of an ideal and real group situation. A stronger group decision-making orientation was found in both groups of professionals, independent of age. However, professionals appear less group-oriented when they mentally self-represent their real compared to their ideal group. Additionally, in senior professionals, a positive correlation between individual and group orientation was found in the ideal group situation. Indeed, in junior professionals, a positive correlation between individual and group orientation was found in the real situation. Therefore, it might be that becoming older and increasing professionalism level correlate with awareness of the difference between real and ideal group representations.

Individual Analytics Mindset and Decision Quality: The Mediating Role of Effort and Persistence

Individual Analytics Mindset and Decision Quality: The Mediating Role of Effort and Persistence

Prognostic nomogram for proliferative verrucous leukoplakia

BackgroundProliferative verrucous leukoplakia (PVL) is a special type of leukoplakia characterized by high rate of malignant transformation into oral squamous cell carcinoma (OSCC). This study aimed to analyze the canceration risk and prognostic factors of PVL and establish effective diagnostic and prognostic predictive models. Materials and methodsA total of 467 patients were enrolled, including 170 cases of PVL. The independent risk and prognostic factors of PVL were analyzed by univariable and multivariable logistic regression. Nomogram models were constructed to predict the canceration risk and prognosis of PVL. The predictive power was evaluated by Hosmer–Lemeshow test, receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis. ResultsMultivariable logistic regression analyses identified that canceration risk factors of PVL included sex, lesion sites, clinical presentation, non-smoker and oral epithelial dysplasia (OED). The independent prognostic factors of PVL were sex, clinical presentation, local irritants and OED. Diagnosis and prognostic nomogram models were constructed. The areas under the ROC curve were 0.945 and 0.893, respectively. The calibration plots showed strong agreement between the prediction and observation. Decision curve analysis indicated that the models provided significant clinical benefits for patients. ConclusionOur study established and validated the diagnosis and prognostic predictive nomogram models, which were accurate to predict the canceration risk and prognostic factors of PVL, providing individualized clinical decisions for clinical work.

The survival outcomes of localized low-risk prostate cancer, a population-based study using NCDB.

The optimal treatment approach for low-risk prostate cancer (LRPC) remains controversial. While active surveillance is an increasingly popular option, definitive local treatments, including radical prostatectomy (RP), external beam radiotherapy (EBRT), and prostate seed implantation (PSI), are also commonly used. This study aimed to evaluate the survival outcomes of patients with LRPC using a large patient population from the National Cancer Database (NCDB). We analyzed data from 195,452 patients diagnosed with LRPC between 2004 and 2015 using the NCDB. Patients were classified based on their treatment modalities, including RP, EBRT, PSI, or no local treatment (NLT). Only patients with Charlson-Deyo comorbidity scores of 0 or 1 were included to ensure comparability. Propensity score analysis was used to balance the treatment groups, and the accelerated failure time model was used to analyze the survival rates of the treatment groups. After a median follow-up of 70.8 months, 24,545 deaths occurred, resulting in an all-cause mortality rate of 13%. RP demonstrated a survival benefit compared with NLT, particularly in patients younger than 74 years of age. In contrast, radiation treatments (EBRT and PSI) did not improve survival in the younger age groups, except for patients older than 70 years for EBRT and older than 65 years for PSI. Notably, EBRT in patients younger than 65 years was associated with inferior outcomes. This study highlights the differences in survival outcomes among LRPC treatment modalities. RP was associated with improved survival compared to NLT, especially in younger patients. In contrast, EBRT and PSI showed survival benefits primarily in the older age groups. NLT is a reasonable choice, particularly in younger patients when RP is not chosen. These findings emphasize the importance of individualized treatment decisions for LRPC management.

Using an interprofessional decision-making model to determine the level of collaborative decision-making in a virtual learning environment

Medicine and pharmacy students benefit from interprofessional education that supports the learning of collaboration skills for medicines management decision-making. However, if and how students undertake collaborative decision-making processes in interprofessional student teams has not been investigated. The aim of this study was to determine the level to which pharmacy and medical students collaborate to make medicines management decisions in a learning activity. Eight pharmacy and 13 medical students completed a 9-item survey to evaluate a interprofessional learning activity. A secondary analysis of survey data using a deductive approach, according to the Model of Interprofessional Decision-Making was undertaken. Different levels of collaboration were identified in the students’ responses ranging from the first and lowest level in the model, Individual Decision Making, to the fourth and highest level, Shared Decision. Most student responses were categorised as level three-Deliberation. Findings from this study indicate that pharmacy and medical students collaborate to different levels with each other to make patient care decisions. Further examination is required to see if this is usual variation or related to the design of the learning activity.

Using smartphones to study vaccination decisions in the wild.

One of the most important tools available to limit the spread and impact of infectious diseases is vaccination. It is therefore important to understand what factors determine people's vaccination decisions. To this end, previous behavioural research made use of, (i) controlled but often abstract or hypothetical studies (e.g., vignettes) or, (ii) realistic but typically less flexible studies that make it difficult to understand individual decision processes (e.g., clinical trials). Combining the best of these approaches, we propose integrating real-world Bluetooth contacts via smartphones in several rounds of a game scenario, as a novel methodology to study vaccination decisions and disease spread. In our 12-week proof-of-concept study conducted with N = 494 students, we found that participants strongly responded to some of the information provided to them during or after each decision round, particularly those related to their individual health outcomes. In contrast, information related to others' decisions and outcomes (e.g., the number of vaccinated or infected individuals) appeared to be less important. We discuss the potential of this novel method and point to fruitful areas for future research.

A novel prediction score determining individual clinical outcome 3 months after juvenile stroke (PREDICT-score)

BackgroundJuvenile strokes (< 55 years) account for about 15% of all ischemic strokes. Structured data on clinical outcome in those patients are sparse. Here, we aimed to fill this gap by systematically collecting relevant data and modeling a juvenile stroke prediction score for the 3-month functional outcome.MethodsWe retrospectively integrated and analyzed clinical and outcome data of juvenile stroke and TIA patients treated at the LMU University Hospital, LMU Munich, Munich. Good outcome was defined as a modified Rankin Scale of 0–2 or return to baseline of function. We analyzed candidate predictors and developed a predictive model. Predictive abilities were inspected using Area Under the ROC curve (AUROC) and visual representation of the calibration. The model was validated internally.Results346 patients were included in the analysis. We observed a good outcome in n = 293 patients (84.7%). The prediction model for an unfavourable outcome had an AUROC of 89.1% (95% CI 83.3–93.1%). The model includes age NIHSS, ASPECTS, blood glucose and type of vessel occlusion as predictors for the individual patient outcome.ConclusionsHere, we introduce the highly accurate PREDICT-score for the 3-month outcome after juvenile stroke derived from clinical routine data. The PREDICT-score might be helpful in guiding individual patient decisions and designing future studies but needs further prospective validation which is already planned.Trial registration The study has been registered at https://drks.de (DRKS00024407) on March 31, 2022.

The Finishing Space Value for Shooting Decision-Making in High-Performance Football.

Football players' decision-making behaviours near the scoring target (finishing situations) emerge from the evolving spatiotemporal information directly perceived in the game's landscape. In finishing situations, the ball carrier's decision-making about shooting or passing is not an individual decision-making process, but a collective decision that is guided by players' perceptions of match affordances. To sustain this idea, we collected spatiotemporal information and built a model to quantify the "Finishing Space Value" (FSV) that results from players' perceived affordances about two main questions: (a) is the opponent's target successfully reachable from a given pitch location?; and (b) from each given pitch location, the opposition context will allow enough space to shoot (low adversaries' interference)? The FSV was calculated with positional data from high-performance football matches, combining information extracted from Voronoi diagrams (VD) with distances and angles to the goal line. FSV was tested using as a reference the opinion of a "panel of expert" (PE), composed by football coaches, about a questionnaire presenting 50 finishing situations. Results showed a strong association between the subjective perception scale used by the PE to assess how probable a shot made by the ball carrier could result in a goal and FSV calculated for that same situation (R2=0.6706). Moreover, we demonstrate the accuracy of the FSV quantification model in predicting coaches' opinions about what should be the "best option" to finish the play. Overall, results indicated that the FSV is a promising model to capture the affordances of the shooting circumstances for the ball carrier's decision-making in high-performance football. FSV might be useful for more precise match analysis and informing coaches in the design of representative practice tasks.

From individual to household decision‐making: A practical perspective on the base of the pyramid consumer

AbstractThis paper proposes a new household decision‐making model for base of pyramid (BoP) consumers. Many decision‐making models focus on general consumer behaviour theory, with few focusing on the resource constraints experienced at the BoP. By focusing on the dynamics of household decisions, the data collected bring a unique perspective to BoP consumer behaviour and extend recent work in the BoP domain. The study comprised qualitative interviews with 61 household representatives (representing 233 household members) to explore decision‐making, loyalty, budgeting, shopping and category trade‐offs. The study proposes a household‐focused decision‐making framework, which is far more characteristic of BoP consumer behaviour (as opposed to isolated individual decisions). The proposed framework reveals the impact of situations and financial constraints on BoP household decision‐making and how most households operate in both the formal and informal economy. Family obligation was observed to be a key factor, as well as how functional illiteracy drives brand loyalty but also creates embarrassment. Word of mouth trumps all other sources of information and, due to household complexities, there is significant decision‐maker ambiguity, making it hard to define a target audience with a communication strategy. Brands are important, but fundamental value is still key and there is inexorable monthly variation in finances, making category trade‐offs commonplace.

Religiosity and Carbon Emissions: International Evidence

ABSTRACT Informal institutions can exert important effects on individual behavior, corporate decisions and social outcomes. Against the background in which global warming poses the critical menace to the world economy and human survival, this study draws on the role theory and adopts the OLS regression and IVREG model to examine the impact of religiosity (an informal institution) on carbon emissions at the country level. Our findings reveal that religiosity, proxied by the percentage of religious population within a country, is significantly negatively associated with carbon emissions, validating the important role of religious social norms in carbon emissions reduction. Moreover, the Kyoto Protocol attenuates the negative effect of religiosity on carbon emissions. Our study calls on policy makers and stakeholders to attach the importance to the impact of religiosity on environmental protection and the trade-off between economic development and carbon emissions reduction.

Innovative regression model-based decision support tool for optimizing radiotherapy techniques in thoracic esophageal cancer.

Modern radiotherapy exemplified by intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT), has transformed esophageal cancer treatment. Facing challenges in treating thoracic esophageal cancer near vital organs, this study introduces a regression model-based decision support tool for the optimal selection of radiotherapy techniques. We enrolled 106 patients diagnosed with locally advanced thoracic esophageal cancer in this study and designed individualized IMRT and VMAT radiotherapy plans for each patient. Detailed dosimetric analysis was performed to evaluate the differences in dose distribution between the two radiotherapy techniques across various thoracic regions. Single-factor and multifactorial logistic regression analyses were employed to establish predictive models (P1 and P2) and factors such as TLV/PTV ratio. These models were used to predict the compliance and potential advantages of IMRT and VMAT plans. External validation was performed in a validation group of 30 patients. Using predictive models, we developed a data-driven decision support tool. For upper thoracic cases, VMAT plans were recommended; for middle/lower thoracic cases, the tool guided VMAT/IMRT choices based on TLV/PTV ratio. Models P1 and P2 assessed IMRT and VMAT compliance. In validation, the tool showed high specificity (90.91%) and sensitivity (78.95%), differentiating IMRT and VMAT plans. Balanced performance in compliance assessment demonstrated tool reliability. In summary, our regression model-based decision support tool provides practical guidance for selecting optimal radiotherapy techniques for thoracic esophageal cancer patients. Despite a limited sample size, the tool demonstrates potential clinical benefits, alleviating manual planning burdens and ensuring precise, individualized treatment decisions for patients.

A Matter of Values: On the Link Between Economic Performance and Schwartz Human Values

Abstract The goal of the paper is to propose an abstract but formalised model of how Schwartz higher order values may influence individual decisions on sharing an individual effort among alternative economic activities. Subsequently, individual decisions are aggregated into the total (collective) economic output, taking into account interactions between the agents. In particular, we explore the relationship between individual higher order values: Self-Enhancement, Self-Transcendence, Openness to Change and Conservation – measured according to Schwartz’s universal human values theory – and individual and collective economic performance, by means of a theoretical agent based model. Furthermore, based on empirical observations, Openness to Change (measured by the population average in the case of collective output) is positively associated with individual and collective output. These relations are negative for Conservation. Self-Enhancement is positively associated with individual output but negatively with collective output. In case of Self-Transcendence, this effect is opposite. The model provides the potential explanations, in terms of individual and population differences in propensity for management, willingness to change and skills (measured by an educational level) for the empirically observed relations between Schwartz higher order values and individual and collective output. We directly calibrate the micro-level of the model using data from the ninth round of the European Social Survey (ESS9) and present the results of numerical simulations.

Linked Data for modelling and replicating the knowledge production process in data-driven humanities research

Abstract The steps from primary source to scholarly claim typically follow a ‘breadcrumb trail’ of wide-ranging decisions by one or more scholars. For replication studies, these decisions must be identified and made as explicit as possible so that the results can be faithfully reproduced. We use a replication study of premodern population estimates as a use case to gain more insight into the kinds of scholarly practices that need to be made explicit, and to think about possible solutions for modelling this process with future replicability in mind. We argue that Linked Data is the logical and flexible technique for modelling such a replication study. For our use case, it allows us to capture both the data itself and the individual decisions made to arrive at a scientifically derived population estimate based on, for example, geographical phenomena or source criticism. In this article, we set an agenda for the use of Linked Data in data-driven humanities research by exploring the benefits, opportunities, and challenges associated with using Linked Data to conduct a replication study in the humanities (and to promote the reproducibility of humanities research more generally). We identify three key aspects that can benefit from the flexibility offered by Linked Data: increasing the trustworthiness of quantitative studies; facilitating the reproducibility of future studies; and facilitating the interpretation of replication results.

Cognitive issues of mobile map design and use

ABSTRACT Internet-connected mobile devices have changed how people access information. Like other information sources, maps have benefited from and been re-envisioned for mobile devices, and they are used in new contexts. However, these new contexts often generate additional cognitive load. We explored in depth two strategies designers could use to mitigate high cognitive loads associated with mobile map use: offloading cognition and reducing cognitive load by improved design to support the allocation of attention between the map and the environment. In reviewing these strategies, we considered their relevance to several mobile map use cases (navigation, individual and collaborative spatial decision making, information enrichment, and entertainment). Next, we identified recent progress in our understanding of how to measure cognitive load and map use context. Finally, we explored the wider implications of mobile maps for human behaviour and cognition. We identified two important cross-cutting research questions: 1) How can mobile maps be designed to reduce cognitive load by providing what is really needed by users to facilitate their cognitive processes?; 2) How can the intrinsic additional cognitive load created by the characteristics of mobile maps be managed and minimised by supporting the distribution of the user's attention between the map and environment?

Repeated Exposure to COVID-19 Misinformation: A Longitudinal Analysis of Prevalence and Predictors in a Community Sample.

Belief in health misinformation can affect individual health decisions and actions. Repeated exposure to the same misinformation strengthens its impact, yet little is known about how commonly repeated exposure occurs. To estimate the prevalence, we tracked exposure to 5 inaccurate COVID-19 claims every week for up to 23 consecutive weeks in a racially diverse panel of adults (n=213). Repeated exposure was common: across the 5 claims, 10%-43% of respondents reported hearing the misinformation in≥3 different weeks. Frontline workers were more likely than other community members to experience repeated exposure, with adjusted incidence rate ratios (IRRs) ranging from 1.8 to 4.9 across the 4 items. Repeated exposure was most common among older adults. Adjusted IRR for those ages≥50 versus 18-29years ranged from 1.8 to 2.5 per misinformation claim. Public health planning efforts to counter health misinformation should anticipate multiple exposures to the same false claim, especially in certain subgroups.

Machine learning algorithms predict canine structural epilepsy with high accuracy.

Clinical reasoning in veterinary medicine is often based on clinicians' personal experience in combination with information derived from publications describing cohorts of patients. Studies on the use of scientific methods for patient individual decision making are largely lacking. This applies to the prediction of the individual underlying pathology in seizuring dogs as well. The aim of this study was to apply machine learning to the prediction of the risk of structural epilepsy in dogs with seizures. Dogs with a history of seizures were retrospectively as well as prospectively included. Data about clinical history, neurological examination, diagnostic tests performed as well as the final diagnosis were collected. For data analysis, the Bayesian Network and Random Forest algorithms were used. A total of 33 features for Random Forest and 17 for Bayesian Network were available for analysis. The following four feature selection methods were applied to select features for further analysis: Permutation Importance, Forward Selection, Random Selection and Expert Opinion. The two algorithms Bayesian Network and Random Forest were trained to predict structural epilepsy using the selected features. A total of 328 dogs of 119 different breeds were identified retrospectively between January 2017 and June 2021, of which 33.2% were diagnosed with structural epilepsy. An overall of 89,848 models were trained. The Bayesian Network in combination with the Random feature selection performed best. It was able to predict structural epilepsy with an accuracy of 0.969 (sensitivity: 0.857, specificity: 1.000) among all dogs with seizures using the following features: age at first seizure, cluster seizures, seizure in last 24 h, seizure in last 6 month, and seizure in last year. Machine learning algorithms such as Bayesian Networks and Random Forests identify dogs with structural epilepsy with a high sensitivity and specificity. This information could provide some guidance to clinicians and pet owners in their clinical decision-making process.

‘As if the soul returns to the body’: affect, stuckedness, and (in)voluntary return to Nicaragua from Spain

ABSTRACT This article attends to the emotional resonances of ‘stuckedness’ and (in)voluntary return as experienced by Nicaraguan migrants stranded in Spain during the COVID-19 pandemic. Feeling both figuratively and literally trapped in a context of cascading lockdowns, border closures, and travel restrictions, many viewed Spain’s Assisted Voluntary Return and Reintegration (AVRR) programme as offering a choice to ‘freely’ depart Spain – a way to simultaneously leave their distressing circumstances behind while returning to the comfort of ‘home’ and family. Building on recent literature that challenges the basis for participation in such programmes as founded on free, voluntary, and individual decisions, this article contends that, for some, the act of ‘choosing’ to return generates a profound and unexpected emotional response. In the case of a Nicaraguan migrant woman explored in detail here, the execution of said return activates feelings of relief, euphoria, and hope, as well as a renewed sense of self. Nevertheless, her response is temporally and geographically contingent, as returning to Nicaragua via AVRR does not necessarily diminish her desire to remigrate or render her less ‘stuck’. The empirical material that informs this paper was collected through digital ethnography and in-person encounters in both Spain and Nicaragua between 2020 and 2021.

JAK/STAT signaling promotes the emergence of unique cell states in ulcerative colitis

The intestinal epithelium ensures uptake of vital nutrients and acts as a barrier between luminal contents and the underlying immune system. In inflammatory bowel diseases, such as ulcerative colitis (UC), this barrier is compromised, and patients experience debilitating symptoms. Here, we perform single-cell RNA profiling of epithelial cells and outline patterns of cell fate decisions in healthy individuals and UC patients. We demonstrate that patterns of hierarchical behavior are altered in UC patients and identify unique cellular states associated with Janus kinase/signal transducer and activator of transcription (JAK/STAT) activation in ulcerated and non-ulcerated areas of the colonic epithelium. These transcriptional changes could be recapitulated in human colonic organoids, wherein cytokine-mediated activation of JAK/STAT led to the emergence of cell populations with augmented regenerative properties. Altogether, our findings indicate that intricate relationships between epithelial and cytokine signaling regulate cell fate during epithelial tissue regeneration in humans and have important implications for the understanding of UC biology.