Department of Psychiatry, University of Oxford, Oxford, United Kingdom.
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
PLoS One. 2022 May 17;17(5):e0267941. doi: 10.1371/journal.pone.0267941. eCollection 2022.
To examine differences in recidivism rates between different prisons using two designs-between-individual and within-individual-to account for confounding factors.
We examined recidivism rates among 37,891 individuals released from 44 Swedish prisons in three security levels, and who were followed from 2006 to 2013. We used longitudinal data from nationwide registers, including all convictions from district courts. First, we applied a between-individual design (Cox proportional hazards regression), comparing reconviction rates between individuals released from prisons within the same security level, while adjusting for a range of individual-level covariates. Second, we applied a within-individual design (stratified Cox proportional hazards regression), comparing rates of reconviction within the same individuals, i.e., we compared rates after release from one prison to the rates in the same individual after release from another prison, thus adjusting for all time-invariant confounders within each individual (e.g. genetics and early environment). We also adjusted for a range of time-varying individual-level covariates.
Results showed differences in the hazard of recidivism between different prisons in between-individual analyses, with hazards ranging from 1.22 (1.05-1.43) to 4.99 (2.44-10.21). Results from within-individual analyses, which further adjusted for all time-invariant confounders, showed minimal differences between prisons, with hazards ranging from 0.95 (0.87-1.05) to 1.05 (0.95-1.16). Only small differences were found when violent and non-violent crimes were analyzed separately.
The study highlights the importance of research designs that more fully adjust for individual-level confounding factors to avoid over-interpretation of the variability in comparisons across prisons.
采用个体间和个体内设计来检验不同监狱累犯率的差异,以考虑混杂因素。
我们对 37891 名从瑞典 44 个不同安全级别监狱释放的个体进行累犯率的研究,随访时间从 2006 年到 2013 年。我们使用了全国性登记册的纵向数据,包括地区法院的所有定罪记录。首先,我们采用个体间设计(Cox 比例风险回归),比较同一安全级别监狱释放的个体间的再定罪率,同时调整了一系列个体水平的协变量。其次,我们采用个体内设计(分层 Cox 比例风险回归),比较同一个体内的再定罪率,即我们比较从一个监狱释放后的再定罪率与从另一个监狱释放后的再定罪率,从而调整了每个个体内所有时间不变的混杂因素(例如,遗传和早期环境)。我们还调整了一系列时间变化的个体水平协变量。
个体间分析结果显示,不同监狱之间的累犯风险存在差异,风险比范围为 1.22(1.05-1.43)至 4.99(2.44-10.21)。个体内分析结果进一步调整了所有时间不变的混杂因素,结果显示监狱之间的差异很小,风险比范围为 0.95(0.87-1.05)至 1.05(0.95-1.16)。当分别分析暴力犯罪和非暴力犯罪时,差异较小。
本研究强调了采用更充分调整个体水平混杂因素的研究设计的重要性,以避免过度解释监狱间比较的变异性。