Influence of Demographic Variables on Relapse Risk Among Substance Use Addicts in Langata Sub County, Nairobi Kenya

Authors

Susan Ndinda Kivuva

Tangaza University, Nairobi (Kenya)

Wambua Pius Muasa Ph.D

Tangaza University, Nairobi (Kenya)

Article Information

DOI: 10.47772/IJRISS.2026.100600224

Subject Category: Public Health

Volume/Issue: 10/6 | Page No: 3065-3073

Publication Timeline

Submitted: 2026-05-20

Accepted: 2026-05-25

Published: 2026-06-20

Abstract

Globally studies have linked the demographic variables and relapse risk among substance use addicts. The study aimed to establish the influence of demographic characteristics of age, gender, marital status, admission criteria on relapse risk among substance use addicts in Langata sub-county, Nairobi, Kenya. The study employed cross-sectional research design. Using census method, the study utilized a sample size of 144 participants. The data was collected with demographic details of the participants and the Stimulant Relapse Risk Scale (SRRS). The data was analyzed using descriptive statistics (percentages, frequencies) and inferential statistics and particularly t-test and One Way ANOVA. The results showed significant difference between demographic characteristics and relapse risk. There was a significant difference in the scores for relapse risk between Male (M = 98.11, SD = 28.24) and Female participants (M = 113.00, SD = 32.47) at conditions, t (123) =. -2.21, p = .03. The results showed that there was significance difference between age and relapse risky (r = .434). Also, the results showed there was a significance difference between marital status and relapse risk (r = .013). The descriptive statistics emerging from the results suggested that there was a significant difference in the scores for relapse risk between Voluntary (M = 98.22, SD = 26.49) and Involuntary participants (M = 103.36, SD = 32.44) at conditions t (123) =.052, p = .033.

Keywords

Age, gender, marital status, admission criteria, relapse risk, substance use addicts, Nairobi

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References

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