Gambling for long periods of time with fewer breaks (i.e. playing continuously) is understood to be an indicator of harmful gambling. Yet, empirical research using account-based tracking data to establish this relationship remains scarce. In the current study, we addressed this gap by exploring the associations between session length, break length, and risk of gambling-related harm using carded electronic gaming machine (EGM) session data from a land-based casino operator. In line with prior literature, we hypothesized problem gambling severity to be associated with longer gaming sessions, shorter break time, and therefore more continuous play. The dataset for the secondary analyses consisted of 1,332 regular players who gambled on EGMs using their loyalty card from March 2021 to February 2022 and completed the Problem Gambling Severity Index in March 2022. Contrary to our hypotheses, results demonstrated no meaningful associations between problem gambling severity and session length, break length, or the extent to which sessions were continuous. We replicated the analyses with an additional operator dataset of 898 regular EGM customers and corroborated our initial findings. Furthermore, exploratory decision tree classification models revealed no optimal threshold in which machine session length could accurately predict high-risk and problem gambling. These findings contradict the prevailing assumption that problem gambling severity is associated with long, continuous play sessions, bringing into question the utility of solely relying on session length as an indicator of harmful gambling. Rather, harm reduction practices may look to other risky behaviors that occur within these long sessions to more effectively identify and interrupt risky play.
Salmon et al. (Fri,) studied this question.
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