The Spheres & Shield Maze Task: A virtual reality serious game for the assessment of risk taking in decision making

[EN] Risk taking (RT) is an essential component in decision-making process that depicts the propensity to make risky decisions. RT assessment has traditionally focused on self-report questionnaires. These classical tools have shown clear distance from real-life responses. Behavioral tasks assess human behavior with more fidelity, but still show some limitations related to transferability. A way to overcome these constraints is to take advantage from virtual reality (VR), to recreate real-simulated situations that might arise from performance-based assessments, supporting RT research. This article presents results of a pilot study in which 41 individuals explored a gamified VR environment: the Spheres & Shield Maze Task (SSMT). By eliciting implicit behavioral measures, we found relationships between scores obtained in the SSMT and self-reported risk-related constructs, as engagement in risky behaviors and marijuana consumption. We conclude that decontextualized Virtual Reality Serious Games are appropriate to assess RT, since they could be used as a cross-disciplinary tool to assess individuals' capabilities under the stealth assessment paradigm.This work was supported by the Spanish Ministry of Economy, Industry and Competitiveness funded projects "Advanced Therapeutic Tools for Mental Health'' (DPI2016-77396-R), and "Assessment and Training on Decision Making in Risk Environments'' (RTC-2017-6523-6) (MINECO/AEI/FEDER,UE) and by the Generalitat Valenciana funded project "Rebrand'' (PROMETEU/2019/105).Juan-Ripoll, CD.; Soler-Domínguez, JL.; Chicchi-Giglioli, IA.; Contero, M.; Alcañiz Raya, ML. (2020). The Spheres & Shield Maze Task: A virtual reality serious game for the assessment of risk taking in decision making. Cyberpsychology Behavior and Social Networking. 23(11):773-781. https://doi.org/10.1089/cyber.2019.0761S7737812311Bechara, A., Damasio, H., Tranel, D., & Damasio, A. R. (2005). The Iowa Gambling Task and the somatic marker hypothesis: some questions and answers. Trends in Cognitive Sciences, 9(4), 159-162. doi:10.1016/j.tics.2005.02.002Krain, A. L., Wilson, A. M., Arbuckle, R., Castellanos, F. X., & Milham, M. P. (2006). Distinct neural mechanisms of risk and ambiguity: A meta-analysis of decision-making. NeuroImage, 32(1), 477-484. doi:10.1016/j.neuroimage.2006.02.047Einhorn, H. J. (1970). The use of nonlinear, noncompensatory models in decision making. Psychological Bulletin, 73(3), 221-230. doi:10.1037/h0028695Figner, B., & Weber, E. U. (2011). Who Takes Risks When and Why? Current Directions in Psychological Science, 20(4), 211-216. doi:10.1177/0963721411415790Endsley, M. R., & Garland, D. J. (Eds.). (2000). Situation Awareness Analysis and Measurement. doi:10.1201/b12461Lauriola, M., & Levin, I. P. (2001). Personality traits and risky decision-making in a controlled experimental task: an exploratory study. Personality and Individual Differences, 31(2), 215-226. doi:10.1016/s0191-8869(00)00130-6Rundmo, T. (1996). Associations between risk perception and safety. Safety Science, 24(3), 197-209. doi:10.1016/s0925-7535(97)00038-6Zuckerman, M., & Kuhlman, D. M. (2000). Personality and Risk‐Taking: Common Bisocial Factors. Journal of Personality, 68(6), 999-1029. doi:10.1111/1467-6494.00124Dahlen, E. R., Martin, R. C., Ragan, K., & Kuhlman, M. M. (2005). Driving anger, sensation seeking, impulsiveness, and boredom proneness in the prediction of unsafe driving. Accident Analysis & Prevention, 37(2), 341-348. doi:10.1016/j.aap.2004.10.006Donohew, L., Zimmerman, R., Cupp, P. S., Novak, S., Colon, S., & Abell, R. (2000). Sensation seeking, impulsive decision-making, and risky sex: implications for risk-taking and design of interventions. Personality and Individual Differences, 28(6), 1079-1091. doi:10.1016/s0191-8869(99)00158-0Moreno, M., Estevez, A. F., Zaldivar, F., Montes, J. M. G., Gutiérrez-Ferre, V. E., Esteban, L., … Flores, P. (2012). Impulsivity differences in recreational cannabis users and binge drinkers in a university population. Drug and Alcohol Dependence, 124(3), 355-362. doi:10.1016/j.drugalcdep.2012.02.011Dvorak, R. D., & Day, A. M. (2014). Marijuana and self-regulation: Examining likelihood and intensity of use and problems. Addictive Behaviors, 39(3), 709-712. doi:10.1016/j.addbeh.2013.11.001Trocki, K. F., Drabble, L. A., & Midanik, L. T. (2009). Tobacco, marijuana, and sensation seeking: Comparisons across gay, lesbian, bisexual, and heterosexual groups. Psychology of Addictive Behaviors, 23(4), 620-631. doi:10.1037/a0017334Ames, S. L., Zogg, J. B., & Stacy, A. W. (2002). Implicit cognition, sensation seeking, marijuana use and driving behavior among drug offenders. Personality and Individual Differences, 33(7), 1055-1072. doi:10.1016/s0191-8869(01)00212-4Highhouse, S., Nye, C. D., Zhang, D. C., & Rada, T. B. (2016). Structure of the Dospert: Is There Evidence for a General Risk Factor? Journal of Behavioral Decision Making, 30(2), 400-406. doi:10.1002/bdm.1953Jackson, D. N., Hourany, L., & Vidmar, N. J. (1972). A four-dimensional interpretation of risk taking1. Journal of Personality, 40(3), 483-501. doi:10.1111/j.1467-6494.1972.tb00075.xSkeel, R. L., Neudecker, J., Pilarski, C., & Pytlak, K. (2007). The utility of personality variables and behaviorally-based measures in the prediction of risk-taking behavior. Personality and Individual Differences, 43(1), 203-214. doi:10.1016/j.paid.2006.11.025Horvath, P., & Zuckerman, M. (1993). Sensation seeking, risk appraisal, and risky behavior. Personality and Individual Differences, 14(1), 41-52. doi:10.1016/0191-8869(93)90173-zLejuez, C. W., Aklin, W. M., Zvolensky, M. J., & Pedulla, C. M. (2003). Evaluation of the Balloon Analogue Risk Task (BART) as a predictor of adolescent real-world risk-taking behaviours. Journal of Adolescence, 26(4), 475-479. doi:10.1016/s0140-1971(03)00036-8Verhulst, N., De Keyser, A., Gustafsson, A., Shams, P., & Van Vaerenbergh, Y. (2019). Neuroscience in service research: an overview and discussion of its possibilities. Journal of Service Management, 30(5), 621-649. doi:10.1108/josm-05-2019-0135de-Juan-Ripoll, C., Soler-Domínguez, J. L., Guixeres, J., Contero, M., Álvarez Gutiérrez, N., & Alcañiz, M. (2018). Virtual Reality as a New Approach for Risk Taking Assessment. Frontiers in Psychology, 9. doi:10.3389/fpsyg.2018.02532Bechara, A., Damasio, A. R., Damasio, H., & Anderson, S. W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50(1-3), 7-15. doi:10.1016/0010-0277(94)90018-3Bottari, C., Dassa, C., Rainville, C., & Dutil, É. (2009). The factorial validity and internal consistency of the Instrumental Activities of Daily Living Profile in individuals with a traumatic brain injury. Neuropsychological Rehabilitation, 19(2), 177-207. doi:10.1080/09602010802188435Verschoor, A., D’Exelle, B., & Perez-Viana, B. (2016). Lab and life: Does risky choice behaviour observed in experiments reflect that in the real world? Journal of Economic Behavior & Organization, 128, 134-148. doi:10.1016/j.jebo.2016.05.009Tarr, M. J., & Warren, W. H. (2002). Virtual reality in behavioral neuroscience and beyond. Nature Neuroscience, 5(S11), 1089-1092. doi:10.1038/nn948Alcañiz, M., Rey, B., Tembl, J., & Parkhutik, V. (2009). A Neuroscience Approach to Virtual Reality Experience Using Transcranial Doppler Monitoring. Presence: Teleoperators and Virtual Environments, 18(2), 97-111. doi:10.1162/pres.18.2.97Chittaro, L., & Ranon, R. (2009). Serious Games for Training Occupants of a Building in Personal Fire Safety Skills. 2009 Conference in Games and Virtual Worlds for Serious Applications. doi:10.1109/vs-games.2009.8Lovreglio, R., Gonzalez, V., Amor, R., Spearpoint, M., Thomas, J., Trotter, M., & Sacks, R. (2017). The Need for Enhancing Earthquake Evacuee Safety by Using Virtual Reality Serious Games. Lean and Computing in Construction Congress - Volume 1: Proceedings of the Joint Conference on Computing in Construction. doi:10.24928/jc3-2017/0058Rizzo, A. A., Bowerly, T., Buckwalter, J. G., Klimchuk, D., Mitura, R., & Parsons, T. D. (2009). A Virtual Reality Scenario for All Seasons:The Virtual Classroom. CNS Spectrums, 11(1), 35-44. doi:10.1017/s1092852900024196Chicchi Giglioli, I. A., de Juan Ripoll, C., Parra, E., & Alcañiz Raya, M. (2019). Are 3D virtual environments better than 2D interfaces in serious games performance? An explorative study for the assessment of executive functions. Applied Neuropsychology: Adult, 28(2), 148-157. doi:10.1080/23279095.2019.1607735Huang, H.-M., Rauch, U., & Liaw, S.-S. (2010). Investigating learners’ attitudes toward virtual reality learning environments: Based on a constructivist approach. Computers & Education, 55(3), 1171-1182. doi:10.1016/j.compedu.2010.05.014Dalgarno, B., & Lee, M. J. W. (2009). What are the learning affordances of 3-D virtual environments? British Journal of Educational Technology, 41(1), 10-32. doi:10.1111/j.1467-8535.2009.01038.xFowler, C. (2014). Virtual reality and learning: Where is the pedagogy? British Journal of Educational Technology, 46(2), 412-422. doi:10.1111/bjet.12135Zuckerman, M., Kolin, E. A., Price, L., & Zoob, I. (1964). Development of a sensation-seeking scale. Journal of Consulting Psychology, 28(6), 477-482. doi:10.1037/h0040995Patton, J. H., Stanford, M. S., & Barratt, E. S. (1995). Factor structure of the barratt impulsiveness scale. Journal of Clinical Psychology, 51(6), 768-774. doi:10.1002/1097-4679(199511)51:63.0.co;2-1So, R. H. Y., Lo, W. T., & Ho, A. T. K. (2001). Effects of Navigation Speed on Motion Sickness Caused by an Immersive Virtual Environment. Human Factors: The Journal of the Human Factors and Ergonomics Society, 43(3), 452-461. doi:10.1518/001872001775898223Zuckerman, M. (2008). Sensation Seeking. The International Encyclopedia of Communication. doi:10.1002/9781405186407.wbiecs029Orlebeke, J. F., Van Der Molen, M. W., Dolan, C., & Stoffels, E. J. (1990). The additive factor logic applied to the personality trait disinhibition. Personality and Individual Differences, 11(6), 553-558. doi:10.1016/0191-8869(90)90037-rPopham, L. E., Kennison, S. M., & Bradley, K. I. (2011). Ageism, Sensation-Seeking, and Risk-Taking Behavior in Young Adults. Current Psychology, 30(2), 184-193. doi:10.1007/s12144-011-9107-0Roberti, J. W. (2004). A review of behavioral and biological correlates of sensation seeking. Journal of Research in Personality, 38(3), 256-279. doi:10.1016/s0092-6566(03)00067-9Zuckerman, M., Eysenck, S. B., & Eysenck, H. J. (1978). Sensation seeking in England and America: Cross-cultural, age, and sex comparisons. Journal of Consulting and Clinical Psychology, 46(1), 139-149. doi:10.1037/0022-006x.46.1.139Television campaigns and adolescent marijuana use: tests of sensation seeking targeting. (2001). American Journal of Public Health, 91(2), 292-296. doi:10.2105/ajph.91.2.292Barry, D., & Petry, N. M. (2008). Predictors of decision-making on the Iowa Gambling Task: Independent effects of lifetime history of substance use disorders and performance on the Trail Making Test. Brain and Cognition, 66(3), 243-252. doi:10.1016/j.bandc.2007.09.00

Disclosure, Apology, and Offer Programs: Stakeholders’ Views of Barriers to and Strategies for Broad Implementation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94445/1/j.1468-0009.2012.00679.x.pd

Ethnicity and the association between anthropometric indices of obesity and cardiovascular risk in women: a cross-sectional study

Objectives: The objectives of this study were to determine whether the cross-sectional associations between anthropometric obesity measures, body mass index (BMI), waist circumference (WC) and waist-to hip ratio (WHR), and calculated 10-year cardiovascular disease (CVD) risk using the Framingham and general CVD risk score models, are the same for women of Australian, UK and Ireland, North European, South European and Asian descent. This study would investigate which anthropometric obesity measure is most predictive at identifying women at increased CVD risk in each ethnic group. Design: Cross-sectional data from the National Heart Foundation Risk Factor Prevalence Study. Setting: Population-based survey in Australia. Participants: 4354 women aged 20–69 years with no history of heart disease, diabetes or stroke. Most participants were of Australian, UK and Ireland, North European, South European or Asian descent (97%).Outcome measures: Anthropometric obesity measures that demonstrated stronger predictive ability of identifying women at increased CVD risk and likelihood of being above the promulgated treatment thresholds of various risk score models. Results: Central obesity measures, WC and WHR, were better predictors of cardiovascular risk. WHR reported a stronger predictive ability than WC and BMI in Caucasian women. In Northern European women, BMI was a better indicator of risk using the general CVD (10% threshold) and Framingham (20% threshold) risk score models. WC was the most predictive of cardiovascular risk among Asian women. Conclusions: Ethnicity should be incorporated into CVD assessment. The same anthropometric obesity measure cannot be used across all ethnic groups. Ethnic-specific CVD prevention and treatment strategies need to be further developed

A transatlantic perspective on 20 emerging issues in biological engineering

Advances in biological engineering are likely to have substantial impacts on global society. To explore these potential impacts we ran a horizon scanning exercise to capture a range of perspectives on the opportunities and risks presented by biological engineering. We first identified 70 potential issues, and then used an iterative process to prioritise 20 issues that we considered to be emerging, to have potential global impact, and to be relatively unknown outside the field of biological engineering. The issues identified may be of interest to researchers, businesses and policy makers in sectors such as health, energy, agriculture and the environment

Do social networks affect the use of residential aged care among older Australians?

Background: Older people's social networks with family and friends can affect residential aged care use. It remains unclear if there are differences in the effects of specific (with children, other relatives, friends and confidants) and total social networks upon use of low-level residential care and nursing homes. Methods: Data were drawn from the Australian Longitudinal Study of Ageing. Six waves of data from 1477 people aged ≥ 70 collected over nine years of follow-up were used. Multinomial logistic regressions of the effects of specific and total social networks on residential care use were carried out. Propensity scores were used in the analyses to adjust for differences in participant's health, demographic and lifestyle characteristics with respect to social networks. Results Higher scores for confidant networks were protective against nursing home use (odds ratio [OR] upper versus lower tertile of confidant networks = 0.50; 95%CI 0.33–0.75). Similarly, a significant effect of upper versus lower total network tertile on nursing home use was observed (OR = 0.62; 95%CI 0.43–0.90). Evidence of an effect of children networks on nursing home use was equivocal. Nursing home use was not predicted by other relatives or friends social networks. Use of lower-level residential care was unrelated to social networks of any type. Social networks of any type did not have a significant effect upon low-level residential care use. Discussion: Better confidant and total social networks predict nursing home use in a large cohort of older Australians. Policy needs to reflect the importance of these particular relationships in considering where older people want to live in the later years of life.Lynne C Giles, Gary FV Glonek, Mary A Luszcz and Gary R Andrew

Assessing the impact and cost-effectiveness of needle and syringe provision and opioid substitution therapy on hepatitis C transmission among people who inject drugs in the UK: an analysis of pooled data sets and economic modelling

Background There is limited evidence of the impact of needle and syringe programmes (NSPs) and opioid substitution therapy (OST) on hepatitis C virus (HCV) incidence among people who inject drugs (PWID), nor have there been any economic evaluations. Objective(s) To measure (1) the impact of NSP and OST, (2) changes in the extent of provision of both interventions, and (3) costs and cost-effectiveness of NSPs on HCV infection transmission. Design We conducted (1) a systematic review; (2) an analysis of existing data sets, including collating costs of NSPs; and (3) a dynamic deterministic model to estimate the impact of differing OST/NSP intervention coverage levels for reducing HCV infection prevalence, incidence and disease burden, and incremental cost-effectiveness ratios to measure the cost-effectiveness of current NSP provision versus no provision. Setting Cost-effectiveness analysis and impact modelling in three UK sites. The pooled analysis drew on data from the UK and Australia. The review was international. Participants PWID. Interventions NSP coverage (proportion of injections covered by clean needles) and OST. Outcome New cases of HCV infection. Results The review suggested that OST reduced the risk of HCV infection acquisition by 50% [rate ratio (RR) 0.50, 95% confidence interval (CI) 0.40 to 0.63]. Weaker evidence was found in areas of high (≥ 100%) NSP coverage (RR 0.77, 95% CI 0.38 to 1.54) internationally. There was moderate evidence for combined high coverage of NSPs and OST (RR 0.29, 95% CI 0.13 to 0.65). The pooled analysis showed that combined high coverage of NSPs and OST reduced the risk of HCV infection acquisition by 29–71% compared with those on minimal harm reduction (no OST, ≤ 100% NSP coverage). NSPs are likely to be cost-effective and are cost-saving in some settings. The impact modelling suggest that removing OST (current coverage 81%) and NSPs (coverage 54%) in one site would increase HCV infection incidence by 329% [95% credible interval (CrI) 110% to 953%] in 2031 and at least double (132% increase; 95% CrI 51% to 306%) the number of new infections over 15 years. Increasing NSP coverage to 80% has the largest impact in the site with the lowest current NSP coverage (35%), resulting in a 27% (95% CrI 7% to 43%) decrease in new infections and 41% (95% CrI 11% to 72%) decrease in incidence by 2031 compared with 2016. Addressing homelessness and reducing the harm associated with the injection of crack cocaine could avert approximately 60% of HCV infections over the next 15 years. Limitations Findings are limited by the misclassification of NSP coverage and the simplified intervention definition that fails to capture the integrated services that address other social and health needs as part of this. Conclusions There is moderate evidence of the effectiveness of OST and NSPs, especially in combination, on HCV infection acquisition risk. Policies to ensure that NSPs can be accessed alongside OST are needed. NSPs are cost-saving in some sites and cost-effective in others. NSPs and OST are likely to prevent considerable rates of HCV infection in the UK. Increasing NSP coverage will have most impact in settings with low coverage. Scaling up other interventions such as HCV infection treatment are needed to decrease epidemics to low levels in higher prevalence settings. Future work To understand the mechanisms through which NSPs and OST achieve their effect and the optimum contexts to support implementation. Funding The National Institute for Health Research Public Health Research programme. </jats:sec

Hypoglycemia Revisited in the Acute Care Setting

Hypoglycemia is a common finding in both daily clinical practice and acute care settings. The causes of severe hypoglycemia (SH) are multi-factorial and the major etiologies are iatrogenic, infectious diseases with sepsis and tumor or autoimmune diseases. With the advent of aggressive lowering of HbA1c values to achieve optimal glycemic control, patients are at increased risk of hypoglycemic episodes. Iatrogenic hypoglycemia can cause recurrent morbidity, sometime irreversible neurologic complications and even death, and further preclude maintenance of euglycemia over a lifetime of diabetes. Recent studies have shown that hypoglycemia is associated with adverse outcomes in many acute illnesses. In addition, hypoglycemia is associated with increased mortality among elderly and non-diabetic hospitalized patients. Clinicians should have high clinical suspicion of subtle symptoms of hypoglycemia and provide prompt treatment. Clinicians should know that hypoglycemia is associated with considerable adverse outcomes in many acute critical illnesses. In order to reduce hypoglycemia-associated morbidity and mortality, timely health education programs and close monitoring should be applied to those diabetic patients presenting to the Emergency Department with SH. ED disposition strategies should be further validated and justified to achieve balance between the benefits of euglycemia and the risks of SH. We discuss relevant issues regarding hypoglycemia in emergency and critical care settings

Cross-Sector Review of Drivers and Available 3Rs Approaches for Acute Systemic Toxicity Testing

Acute systemic toxicity studies are carried out in many sectors in which synthetic chemicals are manufactured or used and are among the most criticized of all toxicology tests on both scientific and ethical grounds. A review of the drivers for acute toxicity testing within the pharmaceutical industry led to a paradigm shift whereby in vivo acute toxicity data are no longer routinely required in advance of human clinical trials. Based on this experience, the following review was undertaken to identify (1) regulatory and scientific drivers for acute toxicity testing in other industrial sectors, (2) activities aimed at replacing, reducing, or refining the use of animals, and (3) recommendations for future work in this area