Decision-Making for Risky Gains and Losses among College Students with Internet Gaming Disorder
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{"title"=>"Decision-making for risky gains and losses among college students with internet gaming disorder", "type"=>"journal", "authors"=>[{"first_name"=>"Yuan Wei", "last_name"=>"Yao", "scopus_author_id"=>"56254982800"}, {"first_name"=>"Pin Ru", "last_name"=>"Chen", "scopus_author_id"=>"56254723600"}, {"first_name"=>"Song", "last_name"=>"Li", "scopus_author_id"=>"56493885500"}, {"first_name"=>"Ling Jiao", "last_name"=>"Wang", "scopus_author_id"=>"56255774200"}, {"first_name"=>"Jin Tao", "last_name"=>"Zhang", "scopus_author_id"=>"55720355700"}, {"first_name"=>"Sarah W.", "last_name"=>"Yip", "scopus_author_id"=>"26041245200"}, {"first_name"=>"Gang", "last_name"=>"Chen", "scopus_author_id"=>"57198649489"}, {"first_name"=>"Lin Yuan", "last_name"=>"Deng", "scopus_author_id"=>"55261607600"}, {"first_name"=>"Qin Xue", "last_name"=>"Liu", "scopus_author_id"=>"55261416100"}, {"first_name"=>"Xiao Yi", "last_name"=>"Fang", "scopus_author_id"=>"7401433203"}], "year"=>2015, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84921738411", "doi"=>"10.1371/journal.pone.0116471", "issn"=>"19326203", "pui"=>"601683558", "isbn"=>"1932-6203", "pmid"=>"25615595", "scopus"=>"2-s2.0-84921738411"}, "id"=>"2bcf4130-6ffe-36e7-aced-1eaaf190856b", "abstract"=>"Individuals with Internet gaming disorder (IGD) tend to exhibit disadvantageous risky decision-making not only in their real life but also in laboratory tasks. Decision-making is a complex multifaceted function and different cognitive processes are involved in decision-making for gains and losses. However, the relationship between impaired decision-making and gain versus loss processing in the context of IGD is poorly understood. The main aim of the present study was to separately evaluate decision-making for risky gains and losses among college students with IGD using the Cups task. Additionally, we further examined the effects of outcome magnitude and probability level on decision-making related to risky gains and losses respectively. Sixty college students with IGD and 42 matched healthy controls (HCs) participated. Results indicated that IGD subjects exhibited generally greater risk taking tendencies than HCs. In comparison to HCs, IGD subjects made more disadvantageous risky choices in the loss domain (but not in the gain domain). Follow-up analyses indicated that the impairment was associated to insensitivity to changes in outcome magnitude and probability level for risky losses among IGD subjects. In addition, higher Internet addiction severity scores were associated with percentage of disadvantageous risky options in the loss domain. These findings emphasize the effect of insensitivity to losses on disadvantageous decisions under risk in the context of IGD, which has implications for future intervention studies.", "link"=>"http://www.mendeley.com/research/decisionmaking-risky-gains-losses-among-college-students-internet-gaming-disorder", "reader_count"=>48, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>1, "Librarian"=>1, "Researcher"=>5, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>12, "Student > Postgraduate"=>3, "Other"=>4, "Student > Master"=>5, "Student > Bachelor"=>9, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>1, "Librarian"=>1, "Researcher"=>5, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>12, "Student > Postgraduate"=>3, "Other"=>4, "Student > Master"=>5, "Student > Bachelor"=>9, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>3, "Nursing and Health Professions"=>2, "Biochemistry, Genetics and Molecular Biology"=>1, "Medicine and Dentistry"=>9, "Agricultural and Biological Sciences"=>1, "Arts and Humanities"=>1, "Neuroscience"=>2, "Business, Management and Accounting"=>1, "Psychology"=>21, "Social Sciences"=>4, "Computer Science"=>3}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>9}, "Neuroscience"=>{"Neuroscience"=>2}, "Social Sciences"=>{"Social Sciences"=>4}, "Psychology"=>{"Psychology"=>21}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>1}, "Computer Science"=>{"Computer Science"=>3}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>2}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Unspecified"=>{"Unspecified"=>3}, "Arts and Humanities"=>{"Arts and Humanities"=>1}}, "reader_count_by_country"=>{"Republic of Singapore"=>1, "Argentina"=>1, "United States"=>1, "Germany"=>1, "India"=>1, "Spain"=>1}, "group_count"=>4}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1871757"], "description"=>"<p>Mean percentage of risky choices made in (A) the gain and (B) the loss domain, as a function of EV level and group. Error bars reflect standard errors. IGD = Internet gaming disorder; HCs = healthy controls; EV = expected value; RA = risk advantageous; EQEV = equal expected value; RD = risk disadvantageous.</p>", "links"=>[], "tags"=>["future intervention studies", "hc", "probability level", "college students", "outcome magnitude", "IGD subjects", "Internet Gaming Disorder Individuals", "Internet Gaming Disorder", "gain", "loss domain", "Internet addiction severity scores"], "article_id"=>1294017, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Yuan-Wei Yao", "Pin-Ru Chen", "Song Li", "Ling-Jiao Wang", "Jin-Tao Zhang", "Sarah W. Yip", "Gang Chen", "Lin-Yuan Deng", "Qin-Xue Liu", "Xiao-Yi Fang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0116471.g001", "stats"=>{"downloads"=>6, "page_views"=>40, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Decision_making_performance_for_IGD_subjects_and_HCs_on_the_Cups_task_/1294017", "title"=>"Decision-making performance for IGD subjects and HCs on the Cups task.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-01-23 03:14:45"}
  • {"files"=>["https://ndownloader.figshare.com/files/1932341", "https://ndownloader.figshare.com/files/1932342"], "description"=>"<div><p>Individuals with Internet gaming disorder (IGD) tend to exhibit disadvantageous risky decision-making not only in their real life but also in laboratory tasks. Decision-making is a complex multifaceted function and different cognitive processes are involved in decision-making for gains and losses. However, the relationship between impaired decision-making and gain versus loss processing in the context of IGD is poorly understood. The main aim of the present study was to separately evaluate decision-making for risky gains and losses among college students with IGD using the Cups task. Additionally, we further examined the effects of outcome magnitude and probability level on decision-making related to risky gains and losses respectively. Sixty college students with IGD and 42 matched healthy controls (HCs) participated. Results indicated that IGD subjects exhibited generally greater risk taking tendencies than HCs. In comparison to HCs, IGD subjects made more disadvantageous risky choices in the loss domain (but not in the gain domain). Follow-up analyses indicated that the impairment was associated to insensitivity to changes in outcome magnitude and probability level for risky losses among IGD subjects. In addition, higher Internet addiction severity scores were associated with percentage of disadvantageous risky options in the loss domain. These findings emphasize the effect of insensitivity to losses on disadvantageous decisions under risk in the context of IGD, which has implications for future intervention studies.</p></div>", "links"=>[], "tags"=>["future intervention studies", "hc", "probability level", "college students", "outcome magnitude", "IGD subjects", "Internet Gaming Disorder Individuals", "Internet Gaming Disorder", "gain", "loss domain", "Internet addiction severity scores"], "article_id"=>1323514, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Yuan-Wei Yao", "Pin-Ru Chen", "Song Li", "Ling-Jiao Wang", "Jin-Tao Zhang", "Sarah W. Yip", "Gang Chen", "Lin-Yuan Deng", "Qin-Xue Liu", "Xiao-Yi Fang"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0116471.s001", "https://dx.doi.org/10.1371/journal.pone.0116471.s002"], "stats"=>{"downloads"=>2, "page_views"=>20, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Decision_Making_for_Risky_Gains_and_Losses_among_College_Students_with_Internet_Gaming_Disorder_/1323514", "title"=>"Decision-Making for Risky Gains and Losses among College Students with Internet Gaming Disorder", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2015-01-23 19:55:03"}
  • {"files"=>["https://ndownloader.figshare.com/files/1932340"], "description"=>"<p>* <i>P</i> < .05;</p><p>** <i>P</i> < .01;</p><p>*** <i>P</i> < .001.</p><p>S.E. = standard error.</p><p>Effect of probability level and outcome magnitude on risk taking as a function of domains and groups.</p>", "links"=>[], "tags"=>["future intervention studies", "hc", "probability level", "college students", "outcome magnitude", "IGD subjects", "Internet Gaming Disorder Individuals", "Internet Gaming Disorder", "gain", "loss domain", "Internet addiction severity scores"], "article_id"=>1323513, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Yuan-Wei Yao", "Pin-Ru Chen", "Song Li", "Ling-Jiao Wang", "Jin-Tao Zhang", "Sarah W. Yip", "Gang Chen", "Lin-Yuan Deng", "Qin-Xue Liu", "Xiao-Yi Fang"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0116471.t002", "stats"=>{"downloads"=>5, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Effect_of_probability_level_and_outcome_magnitude_on_risk_taking_as_a_function_of_domains_and_groups_/1323513", "title"=>"Effect of probability level and outcome magnitude on risk taking as a function of domains and groups.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-01-23 19:55:03"}

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Relative Metric

{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}
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