{"id":"W4414715488","doi":"10.1016/j.addbeh.2025.108513","title":"The 10-item and 20-item gambling harms scale for affected others (GHS-10-AO, GHS-20-AO): benchmarked to health utility using propensity weighting and control for comorbidities","year":2025,"lang":"en","type":"article","venue":"Addictive Behaviors","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Department of Families, Housing, Community Services and Indigenous Affairs; Economic and Social Research Institute; Responsible Gambling Fund; Department of Social Services, Australian Government; Alberta Gambling Research Institute, University of Calgary; Leverhulme Trust; Australian Government; Government of South Australia; U.S. Department of Justice; Movember Foundation; Victorian Responsible Gambling Foundation","keywords":"Harm; Scale (ratio); Metric (unit); Harm avoidance; Reliability (semiconductor); Weighting; Perceived control; Control (management)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005437699,0.000503751,0.0005495758,0.002005941,0.0004998432,0.0007270842,0.0007408797,0.0004711858,0.002055477],"category_scores_gemma":[0.01842495,0.0002650978,0.001465298,0.001450896,0.0006513613,0.0008723829,0.002225004,0.001119789,0.0003621453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009069259,"about_ca_system_score_gemma":0.000856597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007686113,"about_ca_topic_score_gemma":0.01701427,"domain_scores_codex":[0.9973259,0.0009065866,0.000463957,0.0002340648,0.0009354201,0.0001341233],"domain_scores_gemma":[0.9942704,0.001227848,0.002634275,0.0005413753,0.0009510752,0.0003749882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003704189,0.0003833327,0.921679,0.0002371339,0.000588719,0.0001114245,0.001273317,0.001128614,0.0006026435,0.001207863,0.002835708,0.06958186],"study_design_scores_gemma":[0.00003868567,0.0003977049,0.9920595,0.0001083907,0.000100346,0.000253026,0.0003941259,0.002093279,0.0003305323,0.001252488,0.002943543,0.00002829974],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9800342,0.0004403515,0.009518099,0.0003083233,0.00005242803,0.001363354,0.002927819,0.00008696484,0.005268413],"genre_scores_gemma":[0.9790411,0.000334371,0.01329085,0.0002075531,0.00002221906,0.001461919,0.004106653,0.00002347655,0.001512005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007686113,"threshold_uncertainty_score":0.02875763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2636172486093018,"score_gpt":0.4346878625540119,"score_spread":0.1710706139447101,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}