ArticleInternational journal of environmental research and public health2022
Serious Games as a Validation Tool for PREDIS: A Decision Support System for Disaster Management.
Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper, we validate PREDIS, a decision support system for disaster management using serious games to collect experts' judgments on its performance. PREDIS is a model for DISaster response supplier selection (PREDIS). It has a PREDictive component (PRED) for predicting the disaster human impact and an estimation component to Estimate the DISaster (EDIS) needs to optimise supplier-based resource allocation. A quasi-experiment design embedded in a participatory simulation game is conducted to compare the opinions of equal samples of 22 experts and non-experts. The following questions are put forward. First, "Does PREDIS model assists the decision makers to make the same decisions faster?" Second, "Does the PREDIS model assist the non-experts as simulated decision makers to decide like an expert?" Using AHP weights of decision makers' preferences as well as Borda counts, the decisions are compared. The result shows that PREDIS helps to reduce the decision-making time by experts and non-experts to 6 h after the disaster strike, instead of the usual 72 h. It also assists 71% of the non-experts to make decisions similar to those made by experts. In summary, the PREDIS model has two major capabilities. It enables the experts and non-experts to predict the disaster results immediately using widely available data. It also enables the non-experts to decide almost the same as the experts; either in predicting the human impact of a disaster and estimating the needs or in selecting suitable suppliers.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.