Survival Analysis of Recovery from Drug Addiction Using the Cox Proportional Hazards Model
| dc.contributor.author | Victor Kiptoo Rotich | |
| dc.contributor.author | Benard Cheruiyot Tonui | |
| dc.contributor.author | Joseph Kipyegon Cheruiyot | |
| dc.contributor.author | Reuben Cheruiyot Lang’at | |
| dc.date.accessioned | 2026-05-12T09:01:14Z | |
| dc.date.issued | 2026 | |
| dc.description.abstract | Drug addiction remains a critical public health challenge, particularly in developing countries like Kenya, where access to effective rehabilitation services is limited. Understanding the factors that influence recovery time is essential for improving treatment outcomes and informing evidence-based interventions. This study aimed to model recovery time among drug-addicted individuals using survival analysis techniques and to identify key determinants influencing the rate of recovery. This study focuses on applying the Cox PH model to estimate recovery hazard rates and identify significant predictors among individuals receiving treatment. A retrospective cohort design was employed using secondary data obtained from a rehabilitation facility in Kericho County, Kenya, covering the period 2021 to 2025. The key findings indicate that education level (HR 1.18, p=0.049) and Substance Type (Multiple Drugs vs. Alcohol, HR 0.67, p=0.027) are significant predictors of recovery from drug addiction. Specifically, higher education levels are associated with a higher hazard of recovery, likely due to enhanced health literacy. At the same time, individuals using multiple substances face a lower hazard of recovery compared to those using alcohol only, reflecting the clinical complexity of polysubstance use. The Cox PH model satisfied the proportional hazards assumption (Global p=0.24), confirming its adequacy for the data. These results highlight the importance of socio-demographic and substance-related factors in recovery from drug addiction. In practice, treatment facilities/rehabilitation centers should integrate health literacy enhancement programs specifically for individuals with lower education levels to improve treatment adherence and accelerate recovery. Besides, more intensive and prolonged interventions, such as enhanced counseling, specialized therapy, and closer monitoring, are recommended for polysubstance users to address their greater clinical needs. For policy, the study’s results underscore the need to develop substance-specific treatment guidelines, increase resource allocation for polysubstance addiction programs, and implement standardized drug-user data recording systems in rehabilitation facilities across Kenya. These strategies will improve recovery outcomes, optimize service delivery, and strengthen national efforts for reducing the burden of drug addiction. | |
| dc.identifier.issn | 2326-9006 | |
| dc.identifier.uri | https://ir-library.kabianga.ac.ke/handle/123456789/1179 | |
| dc.publisher | American Journal of Theoretical and Applied Statistics | |
| dc.subject | Cox PH Model | |
| dc.subject | Survival Analysis | |
| dc.subject | Drug Addiction | |
| dc.subject | Recovery Rates | |
| dc.subject | Hazard Rates | |
| dc.subject | Proportional Hazards | |
| dc.title | Survival Analysis of Recovery from Drug Addiction Using the Cox Proportional Hazards Model | |
| dc.type | Article |
