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IEEE Transactions on Visualization and... Apr 2022In the era of 'information overload', effective information provision is essential for enabling rapid response and critical decision making. In making sense of diverse...
In the era of 'information overload', effective information provision is essential for enabling rapid response and critical decision making. In making sense of diverse information sources, dashboards have become an indispensable tool, providing fast, effective, adaptable, and personalized access to information for professionals and the general public alike. However, these objectives place heavy requirements on dashboards as information systems in usability and effective design. Understanding these issues is challenging given the absence of consistent and comprehensive approaches to dashboard evaluation. In this article we systematically review literature on dashboard implementation in healthcare, where dashboards have been employed widely, and where there is widespread interest for improving the current state of the art, and subsequently analyse approaches taken towards evaluation. We draw upon consolidated dashboard literature and our own observations to introduce a general definition of dashboards which is more relevant to current trends, together with seven evaluation scenarios - task performance, behaviour change, interaction workflow, perceived engagement, potential utility, algorithm performance and system implementation. These scenarios distinguish different evaluation purposes which we illustrate through measurements, example studies, and common challenges in evaluation study design. We provide a breakdown of each evaluation scenario, and highlight some of the more subtle questions. We demonstrate the use of the proposed framework by a design study guided by this framework. We conclude by comparing this framework with existing literature, outlining a number of active discussion points and a set of dashboard evaluation best practices for the academic, clinical and software development communities alike.
Topics: Computer Graphics; Delivery of Health Care; Research Design; Software
PubMed: 35213306
DOI: 10.1109/TVCG.2022.3147154 -
Trauma, Violence & Abuse Jul 2023Youth sexual violence and abuse (SVA) are leading public health and human rights issues around the world. Prevention is key to reducing SVA rates and minimising... (Review)
Review
Youth sexual violence and abuse (SVA) are leading public health and human rights issues around the world. Prevention is key to reducing SVA rates and minimising resultant harms. Despite advocacy for more collaborative approaches, knowledge of how to effectively engage young people and key stakeholders in the design, implementation, and evaluation of SVA prevention programs is limited. This mixed-methods systematic review aimed to synthesise available evidence on participatory design (PD) application in primary and secondary SVA prevention targeting young people. A systematic search was executed across seven electronic databases. Eligible studies were peer-reviewed, published in English, reported primary or secondary SVA prevention, described application of PD or a related approach, and targeted young people aged 12-25 years. Quality was assessed using the Mixed Methods Appraisal Tool. Overall, 20 articles reporting 15 studies were included. Most (55%; = 11) employed a qualitative design. Descriptions, methods, and scope of PD application varied across included studies. A lack of empirical evaluations prevented conclusions regarding the utility of PD application in terms of measured outcomes. The methodology, agent of change, training, and engagement (MATE) taxonomy was subsequently developed to describe and classify PD application. As illustrated in the MATE taxonomy, PD methods promoting agency, encouraging input, and facilitating empowerment are likely to facilitate more meaningful engagement of participants. Integration of participant and expert views, community consultation, and appropriate socio-cultural adaption appear to be critical determinants of program acceptability and feasibility. Empirical evaluations are needed to assess the relative utility of PD methods in line with SVA prevention objectives.
Topics: Adolescent; Humans; Sex Offenses; Sexual Behavior; Violence
PubMed: 35293245
DOI: 10.1177/15248380221078891 -
Journal of Environmental Health Science... Dec 2022Climate change is among the most renowned concerns of the current century, endangering the lives of millions of people worldwide. To comply with the United Nations... (Review)
Review
INTRODUCTION
Climate change is among the most renowned concerns of the current century, endangering the lives of millions of people worldwide. To comply with the United Nations Climate Change Conference (COP21), hospitals should be on track to reduce greenhouse gas emissions. Although hospitals contribute to climate change by emitting greenhouse gases, they are also affected by the health consequences of climate change. Despite all the guidance provided, hospitals need more radical measures to confront climate change. The current study was carried out to examine the components of hospitals' adaptation to climate change and to review measures to confront climate change in hospitals.
METHOD
This systematic review was designed and carried out in 2020. The required information was collected from international electronic databases including Scopus, PubMed, Web of Science, EMBASE, and Google Scholar. Moreover, Iranian datasets such as Scientific Database (SID), Irandoc, Magiran, and IranMedex were reviewed. No restriction was considered in the methodology of the study. For the relevant thesis, the ProQuest database was also explored. The related sources were examined and the Snowball method was applied to find additional related studies. The research team also reviewed other accessible electronic resources, such as international guidelines and academic websites. The checklist of the Joanna Briggs Institute (JBI, 2017) was employed in order to evaluate the quality of the included papers. The studies published until June1, 2020, were included in the study.
RESULTS
Of 11,680 published documents in the initial search, the full-texts of 140 were read after evaluating the titles and abstracts, of which 114 were excluded due to lack of sufficient information related to countermeasures in hospitals. Finally, the full-texts of 26 studies were reviewed to extract the required components. Two strategies were found, including climate change mitigation and climate change adaptation, with 13 components including water, wastewater, energy, waste, green buildings, food, transportation, green purchasing policy, medicines, chemicals and toxins, technology, sustainable care models, and leadership in hospitals were identified as affecting these measures and strategies.
CONCLUSION
Considering the significance of climate change and strategies to confront it as one of the current challenges and priorities in the world, it is necessary to develop a framework and model to reduce the effects of climate change and adapt to climate changes in hospitals and other health centers. The identification and classification of the measures and components, influencing hospital adaptability and solutions for reducing the climate change impacts could be the first stage in developing this strategy. This is because it is impossible to create this framework without identifying these factors and their mutual impacts at the first. In the present study, through a systematic review using a comprehensive approach, the related components were explored and divided into two categories, including measures to reduce the effects and measures to adapt to climate change. The results of this study can be useful in developing a comprehensive action model to reduce greenhouse gas emissions and adapt hospitals to climate change.
PubMed: 36406601
DOI: 10.1007/s40201-022-00810-5 -
Frontiers in Medicine 2022The efficiencies that master protocol designs can bring to modern drug development have seen their increased utilization in oncology. Growing interest has also resulted...
BACKGROUND
The efficiencies that master protocol designs can bring to modern drug development have seen their increased utilization in oncology. Growing interest has also resulted in their consideration in non-oncology settings. Umbrella trials are one class of master protocol design that evaluates multiple targeted therapies in a single disease setting. Despite the existence of several reviews of master protocols, the statistical considerations of umbrella trials have received more limited attention.
METHODS
We conduct a systematic review of the literature on umbrella trials, examining both the statistical methods that are available for their design and analysis, and also their use in practice. We pay particular attention to considerations for umbrella designs applied outside of oncology.
FINDINGS
We identified 38 umbrella trials. To date, most umbrella trials have been conducted in early phase settings (73.7%, 28/38) and in oncology (92.1%, 35/38). The quality of statistical information available about conducted umbrella trials to date is poor; for example, it was impossible to ascertain how sample size was determined in the majority of trials (55.3%, 21/38). The literature on statistical methods for umbrella trials is currently sparse.
CONCLUSIONS
Umbrella trials have potentially great utility to expedite drug development, including outside of oncology. However, to enable lessons to be effectively learned from early use of such designs, there is a need for higher-quality reporting of umbrella trials. Furthermore, if the potential of umbrella trials is to be realized, further methodological research is required.
PubMed: 36313987
DOI: 10.3389/fmed.2022.1037439 -
Clinical Psychology Review Apr 2023Intolerance of uncertainty, a transdiagnostic factor manifested across emotional disorders, has been associated with difficulties in regulating emotions. This... (Meta-Analysis)
Meta-Analysis
Intolerance of uncertainty, a transdiagnostic factor manifested across emotional disorders, has been associated with difficulties in regulating emotions. This meta-analysis addresses the lack of synthesis of this relationship. PsycInfo, PubMed, Scopus, and ProQuest were systematically searched for relevant articles published up to and during November 2022. We combined 161 effect sizes from 91 studies (N = 30,239), separating the analysis into maladaptive and adaptive emotion regulation strategies and their association with intolerance of uncertainty. We found a moderate positive relationship between maladaptive, and a moderate inverse relationship between adaptive emotion regulation and intolerance of uncertainty. Analysing the magnitude of relationships revealed that cognitive avoidance and mindfulness were the maladaptive and adaptive strategies respectively which had the largest effect sizes and thus strongest relationships with intolerance of uncertainty. Combining all strategies, cognitive avoidance remained the largest effect size, while expressive suppression had the smallest effect size and was non-significant in its relationship. Further analyses testing study sample, design, and age as moderators found no significant moderator for the relationships between intolerance of uncertainty and emotion regulation strategies. These findings have implications for future intolerance of uncertainty interventions, with emotion regulation as a potential target of change.
Topics: Humans; Emotional Regulation; Emotions; Mood Disorders; Uncertainty
PubMed: 36965452
DOI: 10.1016/j.cpr.2023.102270 -
Journal of Medical Internet Research Jan 2024A conversational agent powered by artificial intelligence, commonly known as a chatbot, is one of the most recent innovations used to provide information and services... (Review)
Review
BACKGROUND
A conversational agent powered by artificial intelligence, commonly known as a chatbot, is one of the most recent innovations used to provide information and services during the COVID-19 pandemic. However, the multitude of conversational agents explicitly designed during the COVID-19 pandemic calls for characterization and analysis using rigorous technological frameworks and extensive systematic reviews.
OBJECTIVE
This study aims to describe the general characteristics of COVID-19 chatbots and examine their system designs using a modified adapted design taxonomy framework.
METHODS
We conducted a systematic review of the general characteristics and design taxonomy of COVID-19 chatbots, with 56 studies included in the final analysis. This review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to select papers published between March 2020 and April 2022 from various databases and search engines.
RESULTS
Results showed that most studies on COVID-19 chatbot design and development worldwide are implemented in Asia and Europe. Most chatbots are also accessible on websites, internet messaging apps, and Android devices. The COVID-19 chatbots are further classified according to their temporal profiles, appearance, intelligence, interaction, and context for system design trends. From the temporal profile perspective, almost half of the COVID-19 chatbots interact with users for several weeks for >1 time and can remember information from previous user interactions. From the appearance perspective, most COVID-19 chatbots assume the expert role, are task oriented, and have no visual or avatar representation. From the intelligence perspective, almost half of the COVID-19 chatbots are artificially intelligent and can respond to textual inputs and a set of rules. In addition, more than half of these chatbots operate on a structured flow and do not portray any socioemotional behavior. Most chatbots can also process external data and broadcast resources. Regarding their interaction with users, most COVID-19 chatbots are adaptive, can communicate through text, can react to user input, are not gamified, and do not require additional human support. From the context perspective, all COVID-19 chatbots are goal oriented, although most fall under the health care application domain and are designed to provide information to the user.
CONCLUSIONS
The conceptualization, development, implementation, and use of COVID-19 chatbots emerged to mitigate the effects of a global pandemic in societies worldwide. This study summarized the current system design trends of COVID-19 chatbots based on 5 design perspectives, which may help developers conveniently choose a future-proof chatbot archetype that will meet the needs of the public in the face of growing demand for a better pandemic response.
Topics: Humans; Artificial Intelligence; COVID-19; Pandemics; Avatar; Communication
PubMed: 38064638
DOI: 10.2196/43112 -
EXCLI Journal 2023Classic decision theory requires that rational agents show description invariance: which description is chosen should not matter for judgments, preferences, or choices... (Review)
Review
Classic decision theory requires that rational agents show description invariance: which description is chosen should not matter for judgments, preferences, or choices given the descriptions are co-extensive. Framing research has amply demonstrated a failure of description invariance by showing that the choice of the description has a systematic effect on judgments, preferences, and choices. Specifically, framing research has shown that linguistically different descriptions of seemingly equivalent options frequently lead to preference reversals. I summarize the research on framing in situations entailing risk. This includes the characterization of different research designs used, the size and robustness of the framing effects reported for those designs, and the theoretical accounts put forward to explain framing effects. The theoretical accounts are evaluated with respect to their merits, empirically and theoretically. I end by providing the implications of framing research. My central point is that the existence of framing effects points to the adaptiveness of the processes underlying human judgment and choice rather than simply showing human irrationality.
PubMed: 37927347
DOI: 10.17179/excli2023-6169 -
Frontiers in Endocrinology 2022Obesity-related data derived from multiple complex systems spanning media, social, economic, food activity, health records, and infrastructure (sensors, smartphones,... (Review)
Review
Obesity-related data derived from multiple complex systems spanning media, social, economic, food activity, health records, and infrastructure (sensors, smartphones, etc.) can assist us in understanding the relationship between obesity drivers for more efficient prevention and treatment. Reviewed literature shows a growing adaptation of the machine-learning model in recent years dealing with mechanisms and interventions in social influence, nutritional diet, eating behavior, physical activity, built environment, obesity prevalence prediction, distribution, and healthcare cost-related outcomes of obesity. Most models are designed to reflect through time and space at the individual level in a population, which indicates the need for a macro-level generalized population model. The model should consider all interconnected multi-system drivers to address obesity prevalence and intervention. This paper reviews existing computational models and datasets used to compute obesity outcomes to design a conceptual framework for establishing a macro-level generalized obesity model.
Topics: Humans; Obesity; Diet; Exercise; Machine Learning
PubMed: 36313777
DOI: 10.3389/fendo.2022.1027147 -
Journal of Affective Disorders Mar 2024Understanding predictors of suicidal ideation (SI) is crucial for preventing suicides. Given Europe's high suicide rates and the complex nature of SI, it is essential to... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Understanding predictors of suicidal ideation (SI) is crucial for preventing suicides. Given Europe's high suicide rates and the complex nature of SI, it is essential to also examine social determinants like education as potential risk factors for SI in this region. This systematic review and meta-analysis investigates the association between formal/vocational education and SI in Europe.
METHODS
Electronic databases (PubMed, Web of Science, PsycINFO, PSYNDEX) were searched until November 2022. Included studies involved European populations examining associations between education and SI. Pooled Odds Ratios (OR) with 95 % confidence intervals (CI) were calculated using random-effects models. Heterogeneity was assessed with the heterogeneity variance τ and I statistic; subgroup analyses were performed based on study characteristics. Risk of bias was assessed using an adaption of the Newcastle-Ottawa Scale.
RESULTS
From 20,564 initial studies, 41 were included in the meta-analysis (outlier-adjusted, 96,809 study participants). A negative, insignificant association (OR = 0.86, 95 % CI: 0.75; 1.00) was observed between education and SI, with significant heterogeneity (τ = 0.09, I = 73 %). Subgroup analyses indicated that population type, age group, categorization of education, timeframe of SI assessment, and study quality significantly moderated the effect size.
LIMITATIONS
Heterogeneity across studies limits generalizability. The cross-sectional design precludes establishing causal relationships, and social desirability bias may have underestimated the association between education and SI.
CONCLUSIONS
This systematic review and meta-analysis suggests a trend towards a protective effect of education on the emergence of SI in Europe. Future research, preferably with longitudinal study design examining various covariates, should systematically consider educational inequalities in SI.
Topics: Humans; Suicidal Ideation; Suicide; Longitudinal Studies; Cross-Sectional Studies; Europe
PubMed: 38199415
DOI: 10.1016/j.jad.2024.01.040 -
Trials Mar 2021In recent years, the popularity of multi-arm multi-stage, seamless adaptive, and platform trials has increased. However, many design-related questions and questions... (Review)
Review
BACKGROUND
In recent years, the popularity of multi-arm multi-stage, seamless adaptive, and platform trials has increased. However, many design-related questions and questions regarding which operating characteristics should be evaluated to determine the potential performance of a specific trial design remain and are often further complicated by the complexity of such trial designs.
METHODS
A systematic search was conducted to review existing software for the design of platform trials, whereby multi-arm multi-stage trials were also included. The results of this search are reported both on the literature level and the software level, highlighting the software judged to be particularly useful.
RESULTS
In recent years, many highly specialized software packages targeting single design elements on platform studies have been released. Only a few of the developed software packages provide extensive design flexibility, at the cost of limited access due to being commercial or not being usable as out-of-the-box solutions.
CONCLUSIONS
We believe that both an open-source modular software similar to OCTOPUS and a collaborative effort will be necessary to create software that takes advantage of and investigates the impact of all the flexibility that platform trials potentially provide.
Topics: Clinical Trials as Topic; Research Design; Software
PubMed: 33663579
DOI: 10.1186/s13063-021-05130-x