Advanced technology is a primary solution for the shortage of care professionals and increasing demand for care, and thus acceptance of such technology is paramount. This study investigates factors that increase use of advanced technology during elderly care, focusing on current use of advanced technology, factors that influence its use, and care professionals’ experiences with the use. This study uses a mixed-method design. Logfiles were used (longitudinal design) to determine current use of advanced technology, questionnaires assessed which factors increase such use, and in-depth interviews were administered to retrieve care professionals’ experiences. Findings suggest that 73% of care professionals use advanced technology, such as camera monitoring, and consult clients’ records electronically. Six of nine hypotheses tested in this study were supported, with correlations strongest between performance expectancy and attitudes toward use, attitudes toward use and satisfaction, and effort expectancy and performance expectancy. Suggested improvements for advanced technology include expanding client information, adding report functionality, solving log-in problems, and increasing speed. Moreover, the quickest way to increase acceptance is by improving performance expectancy. Care professionals scored performance expectancy of advanced technology lowest, though it had the strongest effect on attitudes toward the technology.
DOCUMENT
PurposeThis study aims to identify variability in aviation operators in order to gain greater understanding of the changes in aviation professional groups. Research has commonly addressed human factors and automation in broad categories according to a group’s function (e.g., pilots, air traffic controllers [ATCOs], engineers). Accordingly, pilots and Air Traffic Controls (ATCOs) have been treated as homogeneous groups with a set of characteristics. Currently, critical themes of human performance in light of systems’ developments place the emphasis on quality training for improved situational awareness (SA), decision-making and cognitive load.Design/methodology/approachAs key solutions centre on the increased understanding and preparedness of operators through quality training, the authors deploy an iterative mixed methodology to reveal generational changes of pilots and ATCOs. In total, 46 participants were included in the qualitative instrument and 70 in the quantitative one. Preceding their triangulation, the qualitative data were analysed using NVivo and the quantitative analysis was aided through descriptive statistics.FindingsThe results show that there is a generational gap between old and new generations of operators. Although positive views on advanced systems are being expressed, concerns about cognitive capabilities in the new systems, training and skills gaps, workload and role implications are presented.Practical implicationsThe practical implications of this study extend to different profiles of operators that collaborate either directly or indirectly and that are critical to aviation safety. Specific implications are targeted on automation complacency, bias and managing information load, and training aspects where quality training can be aided by better understanding the occupational transitions under advanced systems.Originality/valueIn this paper, the authors aimed to understand the changing nature of the operators’ profession within the advanced technological context, and the perceptions and performance-shaping factors of pilots and ATCOs to define the generational changes.
DOCUMENT
Citizens regularly search the Web to make informed decisions on daily life questions, like online purchases, but how they reason with the results is unknown. This reasoning involves engaging with data in ways that require statistical literacy, which is crucial for navigating contemporary data. However, many adults struggle to critically evaluate and interpret such data and make data-informed decisions. Existing literature provides limited insight into how citizens engage with web-sourced information. We investigated: How do adults reason statistically with web-search results to answer daily life questions? In this case study, we observed and interviewed three vocationally educated adults searching for products or mortgages. Unlike data producers, consumers handle pre-existing, often ambiguous data with unclear populations and no single dataset. Participants encountered unstructured (web links) and structured data (prices). We analysed their reasoning and the process of preparing data, which is part of data-ing. Key data-ing actions included judging relevance and trustworthiness of the data and using proxy variables when relevant data were missing (e.g., price for product quality). Participants’ statistical reasoning was mainly informal. For example, they reasoned about association but did not calculate a measure of it, nor assess underlying distributions. This study theoretically contributes to understanding data-ing and why contemporary data may necessitate updating the investigative cycle. As current education focuses mainly on producers’ tasks, we advocate including consumers’ tasks by using authentic contexts (e.g., music, environment, deferred payment) to promote data exploration, informal statistical reasoning, and critical web-search skills—including selecting and filtering information, identifying bias, and evaluating sources.
LINK
Background: Decline in physical activity and functioning is commonly observed in the older population and might be associated with biomarkers such as Advanced Glycation End-products (AGEs). AGEs contribute to age-related decline in the function of cells and tissues in normal aging and have been found to be associated with motor function decline. The aim of this study is to investigate the association between the levels of AGEs, as assessed by skin autofluorescence, and the amount of physical activity and loss of physical functioning in older participants.Methods: Cross-sectional data of 5,624 participants aged 65 years and older from the Lifelines cohort study was used. Linear regression analyses were utilized to study associations between skin autofluorescence/AGE-levels (AGE reader), the number of physically active days (SQUASH), and physical functioning (RAND-36), respectively. A logistic regression analysis was used to study associations between AGE-levels and the compliance with the Dutch physical activity guidelines (SQUASH).Results: A statistical significant association between AGE levels and the number of physically active days (β = -0.21, 95% CI: -0.35 to -0.07, P = .004), physical functioning (β = -1.60, 95% CI: -2.64 to -0.54, P = .003), and compliance with the Dutch physical activity guidelines (OR = 0.76, 95% CI: 0.62 to 0.94, P = .010) was revealed.Conclusions: This study indicates that high AGE levels may be a contributing factor as well as a biomarker for lower levels of physical activity and functioning in the older population.
DOCUMENT
This research paper looks at a selection of science-fiction films and its connection with the progression of the use of television, telephone and print media. It also analyzes statistical data obtained from a questionnaire conducted by the research group regarding the use of communication media.
DOCUMENT
![Does Science-Fiction predict [or change] the future?](https://publinova-harvester-content-prod.s3.amazonaws.com/thumbnails/files/previews/pdf/20250506145555255024.adbf7edd-9619-4d0e-9a17-e0e7096adc7f-thumbnail-400x300.png)
High consumption of carbohydrates is linked to metabolic syndrome, possibly via the endogenous formation of advanced glycated end-products. Many Dutch elementary school children have a carbohydrate intake of >130g/day, the estimated minimum requirement. In this observational study, 126 Dutch elementary school children (5-12y of age) from two schools differing in frequency of gym lessons (2 or 5 times a week) were included. In all participants, height, weight, waist circumference, autofluorescence of skin glycated end-products (AGE-score), sports activity and carbohydrate consumption were recorded once. Sports activities in leisure time differentiated participants in ‘sportsmen’ and ‘non-sportsmen’. Carbohydrate intake and AGE score were positively associated in non-sportsmen (p<0.003), but negatively in sportsmen (p<0.002). In sportsmen, but not in non-sportsmen (p>0.50), a positive association was found (p<0.002) between carbohydrate intake and subject age. The intake of total carbohydrate and carbohydrates from juices and soft drinks was lower (p<0.001) at the Wassenberg School relative to the Alexander School. Based on waist to height ratio, >95% of the children had normal fat mass. No correlations were found between waist to height ratio or BMI and carbohydrate intake. Waist to height ratio was positively associated with BMI (p<0.001)) and subject age (p<0.001). Of all principal parameters, AGE score is most affected by being sportsmen or not (p<0.001). This study indicates that an increased intake of carbohydrates can be counteracted by sufficient physical activity (>2.5 hours per week). This implies that skin autofluorescence is a fast and non-invasive method to screen children for life style.
DOCUMENT
ObjectivesDecision-making for patients with a locally advanced laryngeal carcinoma (T3 and T4) is challenging due to the treatment choice between organ preservation and laryngectomy, both with different and high impact on function and quality of life (QoL). The complexity of these treatment decisions and their possible consequences might lead to decisional conflict (DC). This study aimed to explore the level of DC in locally advanced laryngeal carcinoma patients facing curative decision-making, and to identify possible associated factors.MethodsIn this multicenter prospective cohort study, participants completed questionnaires on DC, level of shared decision-making (SDM), and a knowledge test directly after counseling and 6 months after treatment. Descriptive statistics and Spearman correlation tests were used to analyze the data.ResultsDirectly after counseling, almost all participants (44/45; 98%) experienced Clinically Significant DC score (CSDC >25, scale 0–100). On average, patients scored 47% (SD 20%) correct on the knowledge test. Questions related to radiotherapy were answered best (69%, SD 29%), whilst only 35% (SD 29%) of the questions related to laryngectomy were answered correctly. Patients' perceived level of SDM (scale 0–100) was 70 (mean, SD 16.2), and for physicians this was 70 (SD 1.7).ConclusionMost patients with advanced larynx cancer experience high levels of DC. Low knowledge levels regarding treatment aspects indicate a need for better patient counseling.Level of Evidence4 Laryngoscope, 134:3604–3610, 2024
MULTIFILE
Marketing Analytics provides guidelines in the application of statistics using IBM SPSS Statistics Software (SPSS) for students and professionals using quantitative methods in marketing and consumer behavior. With simple language and a practical, screenshot-led approach, the book presents 11 multivariate techniques and the steps required to perform analysis. Each chapter contains a brief description of the technique, followed by the possible marketing research applications. One of these applications is then used in detail to illustrate its applicability in a research context, including the needed SPSS commands and illustrations. Each chapter also includes practical exercises that require the readers to perform the technique and interpret the results, equipping students with the necessary skills to apply statistics by means of SPSS in marketing and consumer research. Finally, there is a list of articles employing the technique that can be used for further reading.This textbook provides introductory material for advanced undergraduate and postgraduate students studying marketing and consumer analytics, teaching methods along with practical software-applied training using SPSS. Support material includes two real data sets to illustrate the techniques’ applications and PowerPoint slides providing a step-by-step guide to the analysis and commented outcomes. Professionals are invited to use the book to select and use the appropriate analytics for their specific context.
DOCUMENT
Background: Advanced statistical modeling techniques may help predict health outcomes. However, it is not the case that these modeling techniques always outperform traditional techniques such as regression techniques. In this study, external validation was carried out for five modeling strategies for the prediction of the disability of community-dwelling older people in the Netherlands. Methods: We analyzed data from five studies consisting of community-dwelling older people in the Netherlands. For the prediction of the total disability score as measured with the Groningen Activity Restriction Scale (GARS), we used fourteen predictors as measured with the Tilburg Frailty Indicator (TFI). Both the TFI and the GARS are self-report questionnaires. For the modeling, five statistical modeling techniques were evaluated: general linear model (GLM), support vector machine (SVM), neural net (NN), recursive partitioning (RP), and random forest (RF). Each model was developed on one of the five data sets and then applied to each of the four remaining data sets. We assessed the performance of the models with calibration characteristics, the correlation coefficient, and the root of the mean squared error. Results: The models GLM, SVM, RP, and RF showed satisfactory performance characteristics when validated on the validation data sets. All models showed poor performance characteristics for the deviating data set both for development and validation due to the deviating baseline characteristics compared to those of the other data sets. Conclusion: The performance of four models (GLM, SVM, RP, RF) on the development data sets was satisfactory. This was also the case for the validation data sets, except when these models were developed on the deviating data set. The NN models showed a much worse performance on the validation data sets than on the development data sets.
DOCUMENT
The inefficiency of maintaining static and long-lasting safety zones in environments where actual risks are limited is likely to increase in the coming decades, as autonomous systems become more common and human workers fewer in numbers. Nevertheless, an uncompromising approach to safety remains paramount, requiring the introduction of novel methods that are simultaneously more flexible and capable of delivering the same level of protection against potentially hazardous situations. We present such a method to create dynamic safety zones, the boundaries of which can be redrawn in real-time, taking into account explicit positioning data when available and using conservative extrapolation from last known location when information is missing or unreliable. Simulation and statistical methods were used to investigate performance gains compared to static safety zones. The use of a more advanced probabilistic framework to further improve flexibility is also discussed, although its implementation would not offer the same level of protection and is currently not recommended.
MULTIFILE
