A serious gaming framework for decision support on hydrological hazards

With increasing population and human intervention on the natural environment, hazards are a growing threat, coming in many forms, including floods, droughts, soil erosion, and water pollution. A key approach to mitigate hydrological disaster risk at the community level is informed planning with decision support systems. The literature shows emerging efforts on multi-hazard decision support systems for hydrological disasters and demonstrates the need for an engaging, accessible, and collaborative serious game environment facilitating the relationship between the environment and communities. In this study, a web-based decision support tool (DST) was developed for hydrological multi-hazard analysis while employing gamification techniques to introduce a competitive element. The serious gaming environment provides functionalities for intuitive management, visualization, and analysis of geospatial, hydrological, and economic data to help stakeholders in the decision-making process regarding hydrological hazard preparedness and response. Major contributions of the presented DST include involving the community in environmental decision making by reducing the technical complexity required for analysis, increasing community awareness for the environmental and socio-economic consequences of hydrological hazards, and allowing stakeholders to discover and discuss potential trade-offs to hazardous scenarios considering the limitations in budget, regulations, and technicality. The paper describes the software design approaches and system architecture applied for a modular, secure, and scalable software as well as the framework's intuitive web-based user interfaces for real-time and collaborative data analysis and damage assessment. Finally, a case study was conducted to demonstrate the usability of DST in a formal setting and to measure user satisfaction with surveys.

Web-Based Alcohol, Smoking, and Substance Involvement Screening Test Results for the General Spanish Population: Cross-Sectional Study

Background

Information technology in health sciences could be a screening tool of great potential and has been shown to be effective in identifying single-drug users at risk. Although there are many published tests for single-drug screening, there is a gap for concomitant drug use screening in general population. The ASSIST (Alcohol, Smoking and Substance Involvement Screening Test) website was launched on February 2015 in Madrid, Spain, as a tool to identify those at risk.

Objective

The aim of this study was to describe the use of a tool and to analyze profiles of drug users, their consumption patterns, and associated factors.

Methods

Government- and press-released launching of a Spanish-validated ASSIST test from the World Health Organization (WHO) was used for voluntary Web-based screening of people with drug-related problems. The tests completed in the first 6 months were analyzed .

Results

A total of 1657 visitors of the 15,867 visits (1657/15,867, 10.44%) completed the whole Web-based screening over a 6-month period. The users had an average age of 37.4 years, and 78.87% (1307/1657) screened positive for at least one of the 9 drugs tested. The drugs with higher prevalence were tobacco (840/1657, 50.69%), alcohol (437/1657, 26.37%), cannabis (361/1657, 21.79%), and sedatives or hypnotics (192/1657, 11.59%). Polyconsumption or concomitant drug use was stated by 31.80% (527/1657) of the users. Male respondents had a higher risk of having alcohol problems (odds ratio, OR 1.55, 95% CI 1.18-2.04; P=.002) and double the risk for cannabis problems (OR 2.07, 95% CI 1.46-2.92; P<.001). Growing age increased by 3 times the risk of developing alcohol problems for people aged between 45 and 65 years (OR 3.01, 95% CI 1.89-4.79; P<.001).

Conclusions

A Web-based screening test could be useful to detect people at risk. The drug-related problem rates detected by the study are consistent with the current literature. This tool could be useful for users, who use information technology on a daily basis, not seeking medical attention.

Hydra: A web-based system for cardiovascular analysis, diagnosis and treatment

BACKGROUND AND OBJECTIVE

Cardiovascular (CV) risk stratification is a highly complex process involving an extensive set of clinical trials to support the clinical decision-making process. There are many clinical conditions (e.g. diabetes, obesity, stress, etc.) that can lead to the early diagnosis or establishment of cardiovascular disease. In order to determine all these clinical conditions, a complete set of clinical patient analyses is typically performed, including a physical examination, blood analysis, electrocardiogram, blood pressure (BP) analysis, etc. This article presents a web-based system, called Hydra, which integrates a full and detailed set of services and functionalities for clinical decision support in order to help and improve the work of clinicians in cardiovascular patient diagnosis, risk assessment, treatment and monitoring over time.

METHODS

Hydra integrates a number of different services: a service for inputting all the information gathered by specialists (physical examination, habits, BP, blood analysis, electrocardiogram, etc.); a tool to automatically determine the CV risk stratification, including well-known standard risk stratification tables; and, finally, various tools to incorporate, analyze and graphically present the records of the ambulatory BP monitoring that provides BP analysis over a given period of time (24 or 48 hours). In addition, the platform presents a set of reports derived from all the information gathered from the patient in order to support physicians in their clinical decisions.

RESULTS

Hydra was tested and validated in a real domain. In particular, internal medicine specialists at the Hypertension Unit of the Santiago de Compostela University Hospital (CHUS) validated the platform and used it in different clinical studies to demonstrate its utility. It was observed that the platform increased productivity and accuracy in the assessment of patient data yielding a cost reduction in clinical practice.

CONCLUSIONS

This paper proposes a complete platform that includes different services for cardiovascular clinical decision support. It was also run as a web-based application to facilitate its use by clinicians, who can access the platform from any remote computer with Internet access. Hydra also includes different automated methods to facilitate the physicians' work and avoid potential errors in the analysis of patient data.

Confirmation bias in web-based search: a randomized online study on the effects of expert information and social tags on information search and evaluation

BACKGROUND

The public typically believes psychotherapy to be more effective than pharmacotherapy for depression treatments. This is not consistent with current scientific evidence, which shows that both types of treatment are about equally effective.

OBJECTIVE

The study investigates whether this bias towards psychotherapy guides online information search and whether the bias can be reduced by explicitly providing expert information (in a blog entry) and by providing tag clouds that implicitly reveal experts' evaluations.

METHODS

A total of 174 participants completed a fully automated Web-based study after we invited them via mailing lists. First, participants read two blog posts by experts that either challenged or supported the bias towards psychotherapy. Subsequently, participants searched for information about depression treatment in an online environment that provided more experts' blog posts about the effectiveness of treatments based on alleged research findings. These blogs were organized in a tag cloud; both psychotherapy tags and pharmacotherapy tags were popular. We measured tag and blog post selection, efficacy ratings of the presented treatments, and participants' treatment recommendation after information search.

RESULTS

Participants demonstrated a clear bias towards psychotherapy (mean 4.53, SD 1.99) compared to pharmacotherapy (mean 2.73, SD 2.41; t173=7.67, P<.001, d=0.81) when rating treatment efficacy prior to the experiment. Accordingly, participants exhibited biased information search and evaluation. This bias was significantly reduced, however, when participants were exposed to tag clouds with challenging popular tags. Participants facing popular tags challenging their bias (n=61) showed significantly less biased tag selection (F2,168=10.61, P<.001, partial eta squared=0.112), blog post selection (F2,168=6.55, P=.002, partial eta squared=0.072), and treatment efficacy ratings (F2,168=8.48, P<.001, partial eta squared=0.092), compared to bias-supporting tag clouds (n=56) and balanced tag clouds (n=57). Challenging (n=93) explicit expert information as presented in blog posts, compared to supporting expert information (n=81), decreased the bias in information search with regard to blog post selection (F1,168=4.32, P=.04, partial eta squared=0.025). No significant effects were found for treatment recommendation (Ps>.33).

CONCLUSIONS

We conclude that the psychotherapy bias is most effectively attenuated-and even eliminated-when popular tags implicitly point to blog posts that challenge the widespread view. Explicit expert information (in a blog entry) was less successful in reducing biased information search and evaluation. Since tag clouds have the potential to counter biased information processing, we recommend their insertion.