Stage 1 Registered Report: http://dx.doi.org/10.23668/psycharchives.14372. The rapid expansion of online sports betting has raised concerns about its potential impact on individual health and public health. In order to further develop etiological models for gambling disorder (GD) in sports betting, it is essential to unravel the underlying causal processes. Recent studies have identified risky online gambling behavior as an early indicator of GD. This study focuses on impulsivity as a well-documented risk factor for GD and investigated whether increased impulsivity leads to risky online gambling behavior and subsequently contributes to GD. Impulsivity, risky gambling behavior, and GD symptoms were assessed three times at three-month intervals using a longitudinal cross-lagged panel design. We recruited a final sample of n = 427 regular sports bettors from the online gambling provider Tipico. Impulsivity and GD were assessed using a combination of online experimental tasks and questionnaires. As a measure of risky gambling behavior, Tipico provided player tracking data for all participants. Random intercept cross‐lagged panel models were used to test the evidence for our hypotheses. Results showed partial support for the role of impulsivity in the development of GD, particularly through facets such as impulsive choice and certain impulsive personality traits. However, the findings suggest that impulsivity does not directly predict risky betting behavior, nor does such behavior mediate the relationship between impulsivity and GD severity. These results emphasize the complexity of pathways to GD, highlighting the need to explore multifactorial models incorporating emotional, cognitive, and environmental mediators.

Stage 1 Registered Report: http://dx.doi.org/10.23668/psycharchives.14372. Die rasche Ausbreitung von Online-Sportwetten hat Bedenken hinsichtlich ihrer potenziellen Auswirkungen auf die Gesundheit des Einzelnen sowie die öffentliche Gesundheit aufkommen lassen. Um ätiologische Modelle für Glücksspielsucht (GSS) bei Sportwetten weiterzuentwickeln, müssen die zugrunde liegenden kausalen Prozesse entschlüsselt werden. Jüngste Studien haben risikoreiches Online-Glücksspielverhalten als Frühindikator für Spielsucht identifiziert. Diese Studie konzentriert sich auf Impulsivität als gut dokumentierten Risikofaktor für Spielsucht und untersucht, ob erhöhte Impulsivität zu riskantem Online-Glücksspielverhalten führt und anschließend zu Spielsucht beiträgt. Impulsivität, riskantes Glücksspielverhalten und GSS-Symptome wurden dreimal in dreimonatigen Abständen in einem längsschnittlichen, verzögerten Paneldesign untersucht. Wir rekrutierten eine endgültige Stichprobe von n = 427 regelmäßigen Sportwettern des Online-Glücksspielanbieters Tipico. Impulsivität und GSS wurden mit einer Kombination aus experimentellen Online-Aufgaben und Fragebögen untersucht. Als Maß für riskantes Spielverhalten stellte Tipico für alle Teilnehmer Spieler-Tracking-Daten zur Verfügung. Um die Evidenz für unsere Hypothesen zu testen, wurden kreuzverzögerte Panelmodelle mit zufälligem Intercept verwendet. Die Ergebnisse zeigten, dass die Rolle der Impulsivität bei der Entwicklung von GSS teilweise unterstützt wird, insbesondere durch Facetten wie impulsive Entscheidungen und bestimmte impulsive Persönlichkeitseigenschaften. Die Ergebnisse deuten jedoch darauf hin, dass Impulsivität weder direkt riskantes Wettverhalten vorhersagt, noch die Beziehung zwischen Impulsivität und dem Schweregrad von GSS vermittelt. Diese Ergebnisse unterstreichen die Komplexität der Entstehungswege von GSS und verdeutlichen die Notwendigkeit, multifaktorielle Modelle zu erforschen, die emotionale, kognitive und umweltbedingte Mediatoren einbeziehen.

readme ispo.txt: readme file for data flow of the ISPO study; jbac24pr29_readme.txt: Description of the files; 2024-11-07_ispo_long.do: Stata script file for creating the merged longitudinal dataset; 2025-05-06_ispo_stata2mplus.do: Stata script file for creating the data file for testing the hypotheses in MPlus; 2024-11-07_raw_transaction_data_tipico.do: Stata script file for converting the raw transaction data file into a Stata data file; 2024-11-07_t1 transaction data outcomes.do: Stata script file for analysing the transaction data at measurement point 1; 2024-11-07_t2_transaction data outcomes.do: Stata script file for analysing the transaction data at measurement point 2; 2024-11-07_t3_transaction data outcomes.do: Stata script file for analysing the transaction data at measurement point 3; all_data_22042024.dta: Original Stata dataset for the primary data set jbac24pr29_pd3.csv ; all_data_24012024.dta: Original Stata dataset for the primary data set jbac24pr29_pd2.csv; all_data_24112023.dta: Original Stata dataset for the primary data set jbac24pr29_pd1.csv; drop_out_22042024.do: Stata script file for dropout analysis for measurement point 3; drop_out_24012024.do: Stata script file for dropout analysis for measurement point 2; drop_out_24112023.do: Stata script file for dropout analysis for measurement point 1; dsm_analysis_22042024.do: Stata script file for analysing the DSM for measurement point 3; dsm_analysis_24012024.do: Stata script file for analysing the DSM for measurement point 2; dsm_analysis_24112023.do: Stata script file for analysing the DSM for measurement point 1; dsm_analysis_24112023.do: Stata script file for analysing the DSM for measurement point 1; extract_gonogo_22042024.do: Stata script file for preparing the Go/NoGo task analysis for measurement point 3; extract_gonogo_24012024.do: Stata script file for preparing the Go/NoGo task analysis for measurement point 2; extract_gonogo_24112023.do: Stata script file for preparing the Go/NoGo task analysis for measurement point 1; extract_mcq_22042024.do: Stata script file for the extraction of MCQ data for measurement point 3; extract_mcq_24012024.do: Stata script file for the extraction of MCQ data for measurement point 2; extract_mcq_24112023.do: Stata script file for the extraction of MCQ data for measurement point 1; extract_quest_22042024.do: Stata script file for extracting questionnaire data for later analysis for measurement point 3; extract_quest_24012024.do: Stata script file for extracting questionnaire data for later analysis for measurement point 2; extract_quest_24112023.do: Stata script file for extracting questionnaire data for later analysis for measurement point 1; gonogo_analysis_22042024.do: Stata script file for analysing the GoNoGo task for measurement point 3; gonogo_analysis_24012024.do: Stata script file for analysing the GoNoGo task for measurement point 2; gonogo_analysis_24112023.do: Stata script file for analysing the GoNoGo task for measurement point 1; k-value_18122023.do: Stata script file for determining the k-value of the MCQ-27 for measurement point 1; k-value_19062024.do: Stata script file for determining the k-value of the MCQ-27 for measurement point 3; k-value_24012024.do: Stata script file for determining the k-value of the MCQ-27 for measurement point 2; sessions_22042024.do: Stata script file for merging the individual sessions at measurement point 3; sessions_24012024.do: Stata script file for merging the individual sessions at measurement point 2; sessions_24112023.do: Stata script file for merging the individual sessions at measurement point 1; soziodem_22042024.do: Stata script file for processing the socio-demographic data for measurement point 3; soziodem_24012024.do: Stata script file for processing the socio-demographic data for measurement point 2; soziodem_24112023.do: Stata script file for processing the socio-demographic data for measurement point 1; suppsp_analysis_22042024.do: Stata script file for creating the subscales of the SUPPS-P for measurement point 3; suppsp_analysis_24012024.do: Stata script file for creating the subscales of the SUPPS-P for measurement point 2; suppsp_analysis_24112023.do: Stata script file for creating the subscales of the SUPPS-P for measurement point 1; trials_22042024.do: Stata script file for merging the trials at measurement point 3; trials_24012024.do: Stata script file for merging the trials at measurement point 2; trials_24112023.do: Stata script file for merging the trials at measurement point 1; stata2mplus.ado: Stata program that prepares data for analysis in Mplus; import factor scores.do: Stata script file for importing the factor scores; ispo_long_toMplus.do: Stata script file for preparing the longitudinal data set for analysis with Mplus; efa_t1.inp: Mplus input file for the exploratory analysis of the tracking data at measurement point 1; efa_t2.inp: Mplus input file for the exploratory analysis of the tracking data at measurement point 2; efa_t3.inp: Mplus input file for the exploratory analysis of the tracking data at measurement point 3; t1_esem_factor scores.inp: Mplus input file for the exploratory analysis of the tracking data in the form of an exploratory structural equation model at measurement point 1; t2_esem_factor scores.inp: Mplus input file for the exploratory analysis of the tracking data in the form of an exploratory structural equation model at measurement point 2; t3_esem_factor scores.inp: Mplus input file for the exploratory analysis of the tracking data in the form of an exploratory structural equation model at measurement point 3; hypothesis 1a.inp: Mplus input file for testing hypothesis 1a; hypothesis 1a_without56.inp: Mplus input file for testing hypothesis 1a without participants who are older than or equal to 56; hypothesis 1b.inp: Mplus input file for testing hypothesis 1b; hypothesis 1b_without56.inp: Mplus input file for testing hypothesis 1b without participants who are older than or equal to 56; hypothesis 1c_loc.inp: Mplus input file for testing hypothesis 1c_loc; hypothesis 1c_loc_without56.inp: Mplus input file for testing hypothesis 1c_loc without participants who are older than or equal to 56; hypothesis 1c_ss.inp: Mplus input file for testing hypothesis 1c_ss; hypothesis 1c_ss_without56.inp: Mplus input file for testing hypothesis 1c_ss without participants who are older than or equal to 56; hypothesis 1c_urg.inp: Mplus input file for testing hypothesis 1c_urg; hypothesis 1c_urg_without56.inp: Mplus input file for testing hypothesis 1c_urg without participants who are older than or equal to 56; hypothesis_2a_1.inp: Mplus input file for testing hypothesis 2a_1; hypothesis_2a_2.inp: Mplus input file for testing hypothesis 2a_2; hypothesis_2a_3.inp: Mplus input file for testing hypothesis 2a_3; hypothesis_2b_1.inp: Mplus input file for testing hypothesis 2b_1; hypothesis_2b_2.inp: Mplus input file for testing hypothesis 2b_2; hypothesis_2b_3.inp: Mplus input file for testing hypothesis 2b_3; hypothesis_2c_1.inp: Mplus input file for testing hypothesis 2c_1; hypothesis_2c_2.inp: Mplus input file for testing hypothesis 2c_2; hypothesis_2c_3.inp: Mplus input file for testing hypothesis 2c_3; hypothesis_2d_1.inp: Mplus input file for testing hypothesis 2d_1; hypothesis_2d_2.inp: Mplus input file for testing hypothesis 2d_2; hypothesis_2d_3.inp: Mplus input file for testing hypothesis 2d_3; hypothesis_2e_1.inp: Mplus input file for testing hypothesis 2e_1; hypothesis_2e_2.inp: Mplus input file for testing hypothesis 2e_2; hypothesis_2e_3.inp: Mplus input file for testing hypothesis 2e_3; hypothesis_3a_1.inp: Mplus input file for testing hypothesis 3a_1; hypothesis_3a_1_med.inp: Mplus input file for testing hypothesis 3a_1_med; hypothesis_3a_2.inp: Mplus input file for testing hypothesis 3a_2; hypothesis_3a_2_med.inp: Mplus input file for testing hypothesis 3a_2_med; hypothesis_3a_3.inp: Mplus input file for testing hypothesis 3a_3; hypothesis_3a_3_med.inp: Mplus input file for testing hypothesis 3a_3_med; hypothesis_3b_1.inp: Mplus input file for testing hypothesis 3b_1; hypothesis_3b_1_med.inp: Mplus input file for testing hypothesis 3b_1_med; hypothesis_3b_2.inp: Mplus input file for testing hypothesis 3b_2; hypothesis_3b_2_med.inp: Mplus input file for testing hypothesis 3b_2_med; hypothesis_3b_3.inp: Mplus input file for testing hypothesis 3b_3; hypothesis_3b_3_med.inp: Mplus input file for testing hypothesis 3b_3_med; hypothesis_3c_1.inp: Mplus input file for testing hypothesis 3c_1; hypothesis_3c_1_med.inp: Mplus input file for testing hypothesis 3c_1_med; hypothesis_3c_2.inp: Mplus input file for testing hypothesis 3c_1; hypothesis_3c_2_med.inp: Mplus input file for testing hypothesis 3c_2_med; hypothesis_3c_3.inp: Mplus input file for testing hypothesis 3c_3; hypothesis_3c_3_med.inp: Mplus input file for testing hypothesis 3c_3_med; hypothesis_3d_1.inp: Mplus input file for testing the hypothesis 3d_1; hypothesis_3d_1_med.inp: Mplus input file for testing the hypothesis 3d_1_med; hypothesis_3d_2.inp: Mplus input file for testing the hypothesis 3d_2; hypothesis_3d_2_med.inp: Mplus input file for testing the hypothesis 3d_2_med; hypothesis_3d_3.inp: Mplus input file for testing the hypothesis 3d_3; hypothesis_3d_3_med.inp: Mplus input file for testing the hypothesis 3d_3_med; hypothesis_3e_1.inp: Mplus input file for testing hypothesis 3e_1; hypothesis_3e_1_med.inp: Mplus input file for testing hypothesis 3e_1_med; hypothesis_3e_2.inp: Mplus input file for testing hypothesis 3e_2; hypothesis_3e_2_med.inp: Mplus input file for testing hypothesis 3e_2_med; hypothesis_3e_3.inp: Mplus input file for testing hypothesis 3e_3; hypothesis_3e_3_med.inp: Mplus input file for testing hypothesis 3e_3_med; 2025-05-06_Flowchart data analysis ISPO study.jpg: Flowchart to illustrate the data analysis in the ISPO study; jbac24pr29_pd1.csv: Primary data set for measurement point 1; jbac24pr29_pd2.csv: Primary data set for measurement point 2; jbac24pr29_pd3.csv: Primary data set for measurement point 3; jbac24pr29_pd4.csv: Primary data set for the tracking data; jbac24pr29_kb1.txt: Codebook for primary data set for measurement point 1 (jbac24pr29_pd1.csv); jbac24pr29_kb2.txt: Codebook for primary data set for measurement point 2 (jbac24pr29_pd2.csv); jbac24pr29_kb3.txt: Codebook for primary data set for measurement point 3 (jbac24pr29_pd3.csv); jbac24pr29_kb4.txt: Codebook for primary data set for the tracking data (jbac24pr29_pd4.csv); jbac24pr29_ad1.csv: Data set with derived variables for measurement point 1; jbac24pr29_ad2.csv: Data set with derived variables for measurement point 2; jbac24pr29_ad3.csv: Data set with derived variables for measurement point 3; jbac24pr29_ad4.csv: Longitudinal data set merged over all three measurement points with derived variables; jbac24pr29_aa1.txt: Codebook for the data set with derived variables for measurement point 1 (jbac24pr29_ad1.csv); jbac24pr29_aa2.txt: Codebook for the data set with derived variables for measurement point 2 (jbac24pr29_ad2.csv); jbac24pr29_aa3.txt: Codebook for the data set with derived variables for measurement point 3 (jbac24pr29_ad3.csv); jbac24pr29_aa4.txt: Codebook for the longitudinal data set merged over all three measurement points with derived variables (jbac24pr29_ad4.csv)