Does Confinement Affect Treatment Dropout Rates in Patients With Gambling Disorder? A Nine-Month Observational Study

Abstract

Background and Aims: COVID-19 pandemic and confinement have represented a challenge for patients with gambling disorder (GD). Regarding treatment outcome, dropout may have been influenced by these adverse circumstances. The aims of this study were: (a) to analyze treatment dropout rates in patients with GD throughout two periods: during and after the lockdown and (b) to assess clinical features that could represent vulnerability factors for treatment dropout. Methods: The sample consisted of n=86 adults, mostly men (n=79, 91.9%) and with a mean age of 45years old (SD=16.85). Patients were diagnosed with GD according to DSM-5 criteria and were undergoing therapy at a Behavioral Addiction Unit when confinement started. Clinical data were collected through a semi-structured interview and protocolized psychometric assessment. A brief telephone survey related to COVID-19 concerns was also administered at the beginning of the lockdown. Dropout data were evaluated at two moments throughout a nine-month observational period (T1: during the lockdown, and T2: after the lockdown). Results: The risk of dropout during the complete observational period was R=32/86=0.372 (37.2%), the Incidence Density Rate (IDR) ratio T2/T1 being equal to 0.052/0.033=1.60 (p=0.252). Shorter treatment duration (p=0.007), lower anxiety (p=0.025), depressive symptoms (p=0.045) and lower use of adaptive coping strategies (p=0.046) characterized patients who abandoned treatment during the lockdown. Briefer duration of treatment (p=0.001) and higher employment concerns (p=0.044) were highlighted in the individuals who dropped out after the lockdown. Treatment duration was a predictor of dropout in both periods (p=0.005 and p<0.001, respectively). Conclusion: The present results suggest an impact of the COVID-19 pandemic on treatment dropout among patients with GD during and after the lockdown, being treatment duration a predictor of dropout. Assessing vulnerability features in GD may help clinicians identify high-risk individuals and enhance prevention and treatment approaches in future similar situations.