Determinants of HIV self-testing utilization among health sciences undergraduate students in Kenya

Abstract

Background

HIV self-testing (HIVST) was endorsed by WHO in 2016 to expand access to HIV diagnosis, especially for young people. Kenyan youths, including university students, remain vulnerable to HIV, yet uptake of free HIVST kits is inconsistent. This study assessed determinants of HIVST utilization among health sciences undergraduates at the University of Nairobi.

Methods

We conducted a cross-sectional analytical study at the Chiromo and Faculty of Health Sciences campuses. Multi-stage cluster sampling yielded 412 students from Medicine, Pharmacy, Nursing, Dentistry and Medical Laboratory Science. Data on socio-demographics, sexual behaviour, stigma, and institutional access were collected via self-administered questionnaires and analysed in R. Associations were examined using χ²/Fisher’s exact tests and Wilcoxon tests; variables with p < .05 entered a multivariable mixed-effects logistic regression model to account for clustering by course and year of study.

Results

Overall, 30.5% reported prior HIVST use. Uptake was higher among older students and those in advanced years. Being in a relationship and consistently using condoms were associated with lower HIVST uptake. Recency of the last HIV test strongly predicted use, with students tested within the preceding 3–6 months more likely to self-test. Residence and gender were not independent predictors after adjustment.

Conclusions

HIVST uptake among Kenyan health sciences undergraduates is moderate but uneven. Age, academic seniority and recent HIV testing history increase uptake, whereas perceived low risk (e.g. condom use) reduces it. Universities and the Ministry of Health should pair easy kit access with messaging that encourages routine testing regardless of perceived risk to accelerate progress toward UNAIDS 95-95-95 targets.

Keywords

HIV HIVST health sciences undergraduate students

Introduction

The World Health Organization (WHO) provided guidance on HIV self-testing (HIVST) to improve HIV diagnosis, especially among youth, who are disproportionately affected by higher risk sexual behaviors.¹ However, testing and care linkage remain low among this population.^2,3 In Kenya, HIV prevalence is high among women and young adults, including undergraduate students.⁴ HIVST is seen as a key tool in achieving the global HIV agenda for 2030 due to its affordability and privacy.⁵ Despite the availability of free self-test kits, their utilization in Kenya, particularly among university students, is limited.⁶ The Kenya HIV Impact Assessment (KENPHIA) estimated an HIV prevalence of 4.9% and 36,000 annual infections.⁴ Higher statistics were observed among women and those aged 20–34 years, including many undergraduate university students.⁷ To address the rising HIV/AIDS prevalence among youths, HIV prevention programs, including HIV Testing and Counselling (HTC), have been implemented in nearly all tertiary institutions in Kenya.⁸ HIV self-testing allows individuals to privately obtain a specimen, carry out the test, and interpret the results.¹ It is widely accepted for its affordability, accessibility, and privacy, increasing access to HIV testing services in high-risk populations.⁹

The “Chukua Selfie” program in Kenya aims to improve HIV awareness and sensitization among youths.¹⁰ Approved test kits like ORAQUICK® and INSTI® are available free of cost in government facilities.⁷ Globally, an estimated 11.8 million youths aged 15–24 years live with HIV/AIDS, with only a minority knowing their status.¹¹ Young people in this age group contribute 13% of the total number of HIV infections in Kenya.¹² Undergraduate students in Kenyan institutions of higher learning are particularly susceptible to HIV due to high levels of sexual activity and specific behaviours such as unprotected intercourse, multiple/concurrent partnerships, and cross-generational sexual relationships among female students.¹³

Efforts to raise HIV/AIDS awareness in institutions of higher learning are limited, and additional efforts are needed to address structural factors that increase vulnerability.¹⁴ Despite the availability of free HIV self-testing kits, HIV self-testing remains underutilized in Kenya.¹⁵ HIVST can be a low-cost, high-impact intervention to reach untested groups and increase the number of people living with HIV being diagnosed and starting treatment. It also provides an opportunity to link those who test negative with HIV prevention services.¹⁶

Logistic regression has been used in numerous studies to enhance understanding of HIV/AIDS among college students.¹⁷ These studies provide statistics on HIV among college students and insights into factors affecting HIV testing uptake.¹⁸ The present study aimed to assess determinants affecting the utility of HIV self-testing kits among faculty of health sciences undergraduate students and applied a multilevel model approach to understand differences in HIVST based on course type and level of study and also aimed to account for the clustered nature of the data by using a mixed-effects logistic regression model as previous studies had mostly identified factors influencing HIVST utility among youths.

The study was conducted at the University of Nairobi (UoN) KNH and Chiromo campuses, which has a significant population of youthful health sciences students and aimed to uncover determinants associated with HIVST among youths and encourage active testing among UoN undergraduate students. It also sought to support HIV prevention campaigns targeted at students and youths in Kenya, with the support of the University of Nairobi administration, the Ministry of Health, and affiliated partners.

Methods

Study design

A cross-sectional analytical study was conducted to estimate HIVST frequency and its determinants among health sciences undergraduates at UoN.

Scope and study population

The research took place at UoN’s Chiromo (for basic sciences) and the Faculty of Health Sciences campuses. Participants were undergraduates from the Faculty of Health Sciences, enrolled in various health-related courses (Medicine, Pharmacy, Nursing, Dentistry and Medical Laboratory Science). The University’s diverse student population provided a sample representative of all undergraduate programmes and years within the UoN Faculty of Health Sciences.

Sample size and sampling procedure

Using Slovin’s formula, the sample size was determined to be 412, adjusted for clustering with a design effect of 1.2. Multi-stage cluster sampling targeted different medical courses and year groups, using simple random sampling from student registration numbers.

Eligibility criteria

Included were Health Sciences undergraduates aged 18–24 years at Chiromo and KNH campuses, excluding those aware of their positive HIV status or engaged in end-of-semester exams.

Data collection

Self-administered questionnaires were distributed online using SurveyMonkey. The data collected was securely exported in CSV format, encrypted, and stored securely. Invitations were emailed via class representatives using lists of student registration numbers and emails; each selected student received a unique SurveyMonkey link. No monetary or material incentives were offered; participants were only assured of strict confidentiality.

The questionnaires, were designed to capture various determinants influencing HIVST. The dependent variable was HIVST utilization. The independent variables included socio-demographic factors (age, sex, marital status, religion, residence), individual factors (HIV knowledge, sexual behavior, stigma, media exposure, kit affordability), and institutional factors (healthcare accessibility, HIVST availability). The questionnaire was piloted among 25 law undergraduates at University of Nairobi Parklands Campus; feedback informed wording and flow, establishing face and content validity prior to deployment.

Ethical considerations

Ethical approval was obtained from the KNH-UoN Ethical Review Committee (P346/04/2023) and permission granted by National Commission for Science, Technology and Innovation-Kenya (610,114). Data confidentiality was ensured by anonymizing participant information using unique identifiers. Questionnaires were disseminated after obtaining verbal consent through class representatives.

Data analysis

Analysis used R Studio software. Data collected from Survey Monkey was cleaned and prepared by addressing incomplete or inconsistent responses. The cleaned data was imported into R Studio version 4.4, and a verification process was conducted to ensure accurate and reliable data transfer for analysis.

Descriptive statistics and chi-square tests were used to identify variables associated with HIVST. Variables with a p-value <.05 at the bivariate level were included in the multilevel logistic regression model. This model accounted for the hierarchical data structure, considering both fixed and random effects across courses and study years. Model validation included checking for multicollinearity and influential values, with the variance inflation factor (VIF) guiding variable inclusion.

Results

Socio-demographic characteristics

We invited 420 students; 412 completed the survey (response rate 98.1%). The Department of Medicine had the highest number of respondents (n = 238, 57.8%), and the Department of Medical Laboratory had the lowest (n = 27, 6.6%). Ages ranged from 18 to 25 years, with 22-year-olds (17.2%) and 23-year-olds (16.5%) being the most common. Males comprised 50.5% (n = 208) of respondents, with females being more prevalent in all faculties except Medicine (43.9% male) and Pharmacy (50% male). Most respondents were single (96.8%), with a few in relationships (1.7%) or married (1.5%). Religious affiliation was predominantly Christian (90.5%), followed by Muslim (6.3%), Atheist (1.9%), Hindu (0.7%), and Sikh (0.5%). The majority were full-time students across all faculties.

Frequency of use of HIVST

Out of the respondents who answered the question on HIV self-testing kit usage (n = 271), 40.5% (n = 110) reported using the kits, with a 95% confidence interval ranging from 35.2% to 46.4%. Only 271/412 (65.8%) responded to the HIVST-use item; 141 exited before reaching this question. Complete-case analysis was applied for the primary outcome. The utilization of HIVST varied significantly across different courses. Nursing students exhibited the highest usage at 62.2%, while Medical Laboratory students had the lowest at 22.2%. Dental students reported a 28.6% utilization rate, whereas students in the MBCHB program showed a 40.5% usage rate. Pharmacy students had a utilization rate of 40%.

Variations in HIVST utilization across course-type and year-of-study

HIVST users were slightly older than non-users (median 23 vs 22 years; Wilcoxon p = .03). Uptake differed by year of study (Fisher’s exact p = .0013), being lowest in Year 1 (1.2%) and Year 3 (11.0%) and highest in Year 6 (11.0%). Marital status showed an association (p = .04), although very few students were married/partnered. Recency of the last HIV test was strongly related to HIVST use (p < .0001): students tested within the past 3–6 months were more likely to use HIVST, while those untested for >12 months were least likely. Differences across departments/courses were not statistically significant (all p > .05). See Table 1 for full results. Differences were tested using chi-square or Fisher’s exact tests at α = 0.05. The detailed variable performance, including chi-squared, Fisher’s exact tests, and Mann-Whitney tests, are summarized in Table 1.

Table 1.

Relationship between demographic characteristics & use of HIVST kits.

Characteristic	HIVST-ve, n = 188	HIVST + ve, n = 82	Statistical significance
Age	22.0 (IQR: 20.0–23.0)	23.0(IQR:21.5–24.0)	Wilcoxon sum-rank test p = .03
Gender
Male	96 (51%)	40 (49%)	X² (1) < 0.001
Female	92 (49%)	42 (51%)	p > .9
Marital status
Single	182 (97%)	77 (94%)	X² (1) = 0.002
Relationship	5 (2.7%)	1 (1.2%)	p = .968
Married	1 (0.5%)	4 (4.9%)
Religion
Atheist	2 (1.1%)	4 (4.9%)
Christian	178 (95%)	74 (90%)	Fisher’s exact test
Sikh	0 (0%)	1 (1.2%)	p = .1355
Muslim	7 (3.7%)	3 (3.7%)
Hindu	1 (0.5%)	0 (0%)
Mode of study
Full time	186 (99%)	82 (100%)	Fisher’s exact test
Part time	2 (1.1%)	0 (0%)	p > .9
Department
Dentistry	17 (9.0%)	5 (6.1%)
Medicine	130 (69%)	51 (62%)	X² (1) = 3.427
Nursing	19 (10%)	13 (16%)	p = .33
Pharmacy	22 (12%)	13 (16%)
Course
Dental	17 (9.0%)	5 (6.1%)
MBCHB	115 (61%)	48 (59%)	X² (1) = 4.763
Medical Laboratory	15 (8.0%)	3 (3.7%)	p = .313
Nursing	19 (10%)	13 (16%)
Pharmacy	22 (12%)	13 (16%)
Year of study
1	23 (12%)	1 (1.2%)
2	39 (21%)	15 (18%)	Fisher’s exact test
3	41 (22%)	9 (11%)	p = .0013
4	40 (21%)	25 (30%)
5	39 (21%)	23 (28%)
6	6 (3.2%)	9 (11%)
Residency
In school	121 (64%)	50 (61%)	X² (1) = 0.294
Out of school	67 (36%)	32 (39%)	p = .69

The bold indicates all significant p-values that are less than 0.05 (p < 0.05).

Individual factors associated with HIVST use

Consistent condom use and having gone >1 year without an HIV test were both associated with lower HIVST uptake, while sexual activity showed an association in unadjusted analysis that disappeared after adjustment. Other measured behaviours (multiple partners, perceived seriousness, shame, saliva contact) were not independently related to HIVST use. See Table 2 for full estimates.

Table 2.

Individual factors associated with HIVST use.

Characteristic	Unadjusted			Adjusted
Characteristic	OR¹	95% CI¹	p-value	OR¹	95% CI¹	p-value
Sexually active_No	1	-	1	-	-	-
Yes	1.71	1.01, 2.88	0.046	1.8	0.54, 3.07	0.6
Protection_No	-	-	-	-	-	-
Yes	0.44	0.24, 0.83	0.011	0.36	0.17, 0.73	0.005
Multiple sex partner_No	-	-	-	-	-	-
Yes	1.01	0.43, 2.39	>0.9	0.64	0.24, 1.73	0.4
Sex_No	-	-	-	-	-	-
Yes	1.89	1.06, 3.36	0.031	2.92	0.29,29.0	0.4
Last test_Last 3 months	-	-	-	-	-	-
Last 6 months	0.6	0.29, 1.25	0.2	0.81	0.26, 2.55	0.7
More than 1 year ago	0.17	0.09, 0.33	<0.001	0.20	0.07, 0.55	0.002
Seriousness_No	1	-	-	1	-	-
Yes	0.22	0.02, 2.45	0.2	0.74	0.05,11.5	0.8
Contact with saliva No	1	-	-	1	-	-
Yes	1.02	0.61,1.72	>0.9	0.53	0.23,1.23	0.14
Shame 0				1
2	1.14	0.59,2.21	0.7	1.07	0.4,2.82	0.9
3	1.28	0.47,3.52	0.6	1.61	0.4,6.44	0.5
4	1.93	0.4,9.24	0.4	2.13	0.19,23.8	0.5

The bold indicates all significant p-values that are less than 0.05 (p < 0.05).

Institutional factors associated with HIVST use

HIVST uptake increased with advancing year of study (Years 2–6 vs Year 1) and was higher among Nursing students compared with Dentistry. “Department” was dropped from the multivariable model because of multicollinearity with course. Place of residence (hostel vs outside) showed no association with HIVST use. See Table 3 for the full adjusted and unadjusted estimates.

Table 3.

Instituional factors associated with HIVST use.

Characteristic	Unadjusted			Adjusted
Characteristic	OR¹	95% CI¹	p-value	OR¹	95% CI¹	p-value
Course_Dentistry	1	-	-	1	-	-
Medicine	1.31	0.46, 3.75	0.6	1.27	0.43, 3.71	0.7
Nursing	2.64	0.78, 8.93	0.12	4.67	1.29, 16.9	0.019
Pharmacy	2.27	0.68, 7.56	0.2	2.15	0.62, 7.48	0.2
Year of study_1	1	-	-	1	-	-
2	9.12	1.11, 74.8	0.039	12.6	1.50, 105	0.02
3	4.95	0.58, 42.0	0.14	6.86	0.78, 60.5	0.083
4	15.8	1.97, 126	0.009	20.1	2.41, 167	0.006
5	16.2	1.98, 133	0.009	22.2	2.60, 189	0.005
6	42.5	4.25, 426	0.001	55	5.46, 554	<0.001
Reside in university hostels	1	-	-	1	-	-
Reside outside university hostels	1.15	0.68, 1.95	0.6	1.3	0.72, 2.33	0.4

The bold indicates all significant p-values that are less than 0.05 (p < 0.05).

Predictors of HIVST use in the combined model

Older age was associated with higher HIVST uptake, while consistent condom use and not testing for >1 year were associated with lower uptake. After adjustment, year of study and sexual activity were not independently related to HIVST use. See Table 4 for complete estimates.

Table 4.

Predictors of HIVST use.

Characteristic	Unadjusted			Adjusted
Characteristic	OR¹	95% CI¹	p-value	OR¹	95% CI¹	p-value
Gender
Male	1	-	-	1	-	-
Female	1.02	0.61, 1.71	>0.9	1.72	0.67, 4.43	0.3
Age	1.33	1.14, 1.54	<0.001	1.53	1.03, 2.27	0.034
Relationship status
Single	1	-	-	1	-	-
Relationship	0.65	0.05, 4.03	0.5	0.12	0.06, 0.31	0.041
Married	6.95	0.71, 67.8	0.10	2.47	0.17, 35.7	0.5
Year_of_study	1.48	1.20, 1.84	<0.001	0.97	0.60, 1.57	0.9
Sexually active
Not sexually active	1	-	-	1	-	-
Sexually active	1.71	1.01, 2.88	0.046	0.97	0.34, 2.74	>0.9
Used protection
No	1	-	-	-	-	-
Yes	0.44	0.24, 0.83	0.011	0.36	0.14, 0.95	0.039
Have multiple sex partners
No	1	-	-	1	-	-
Yes	1.01	0.43, 2.39	>0.9	0.44	0.10, 1.94	0.3

The bold indicates all significant p-values that are less than 0.05 (p < 0.05).

Model assumptions

The combined model, incorporating variables such as course, year of study, and residence, successfully met all the necessary statistical assumptions. All model assumptions were met when the combined model was fitted with course, year of study and residence variables. Multicollinearity analysis revealed all variables had low to moderate levels, with the highest variances in Age (2.339) and Year of Study (2.282), both below the cut-off threshold of 5, indicating no multicollinearity violation as shown in Table 5. The plot of model residuals versus predicted values displayed a consistent spread along the vertical axis, indicating no violation of linearity and homoscedasticity assumptions. This consistency is crucial for the validity of the model’s findings. Figure 1 illustrates this homoscedasticity, further confirming the model’s robustness

Table 5.

Multicollinearity of the combined model.

Variable	Variance inflation factor	Degree of freedom	Corrected VIF VIF^(1/(2*Df))
Gender	1.170	1	1.082
Age	2.339	1	1.529
Marital status	1.077	1	1.038
Year of study	2.282	1	1.511
Residence	1.147	1	1.071
Sexually activeness	1.252	1	1.119
Used protection	1.132	1	1.064
Have multiple sex partners	1.210	1	1.099
Ever had sex	1.130	2	1.063
Last time HIV test done	1.363	1	1.080
Is HIV a serious disease?	1.075	1	1.037

Figure 1.

Homoscedasticity of the combined model.

Discussion

HIV self-testing (HIVST) is a crucial tool for HIV prevention and management, empowering individuals and reducing stigma.¹⁹ In this study, roughly one-third of students reported using HIVST kits—higher than the 9.0% reported in Nigeria,²⁰ and comparable to the 37.9% found at the University of KwaZulu-Natal, South Africa.²¹

The relatively high uptake among health sciences students is important given their elevated exposure to HIV risk. UNAIDS notes that young people aged 15–24 account for a substantial share of new global infections.¹⁶ In Kenya, KENPHIA and national HIV dashboards similarly highlight persistent vulnerability in this age band.^22,23 University life—marked by new partnerships and peer influence—can amplify these risks; hence, promoting HIVST supports early diagnosis, timely linkage to care, and reduced transmission within this population.

As reported in the Results, department or course was not independently associated with HIVST use, although usage varied within the Faculty of Health Sciences: Nursing showed the highest uptake (43.8%) and Dentistry the lowest (21.7%). This pattern contrasts with findings from Zimbabwe, where nursing students had among the lowest uptake.²⁴ Differences by academic year were also evident, with higher use among senior students—likely reflecting greater maturity, clinical exposure, and health literacy. Similar trends have been documented elsewhere.^20,25

Age emerged as a key determinant: older students were more likely to self-test, echoing prior studies.²⁶ In contrast, gender did not differentiate uptake here, unlike another report that found gender effects.²⁷ Marital status appeared to shape testing behaviour (with married students testing more), and consistent condom use was associated with lower HIVST uptake—an observation that warrants further exploration to understand perceptions of personal risk and motivations for testing.

Overall, the combined model underscored a complex interplay of age, sexual practices, and perceived risk in shaping HIVST behaviour. Public health strategies should therefore pair HIVST promotion with comprehensive sexual health education, encouraging routine testing regardless of condom use or recent sexual activity.

Conclusion

The study revealed that 30.5% of health sciences undergraduates at the University of Nairobi have utilized HIV Self-Testing (HIVST), a rate higher than some regional studies. This underscores the variable health-seeking behaviors in different academic and cultural contexts and highlights the importance of HIVST in empowering students with knowledge of their HIV status. Such uptake is crucial for achieving the UNAIDS 95-95-95 targets.

Key determinants of HIVST utilization were academic progression and age, with older and more advanced students more inclined to self-test, likely due to increased awareness and a mature approach towards HIV prevention. Students practicing safe sex were less inclined to use HIVST, possibly perceiving themselves at lower risk. Interestingly, feelings of stigma did not deter HIVST usage; in fact, they were associated with higher usage rates, indicating complex dynamics surrounding self-testing. Additionally, marital status played a significant role, with married students more likely to engage in HIVST, reflecting the influence of relationship dynamics on health decisions.

Recommendations

(1) We recommend increasing awareness and education on the benefits of regular HIV testing, including HIVST, regardless of perceived risk levels among undergraduate students.

(2) Universities should facilitate easier access to HIVST kits and incorporate HIV awareness programs into the curriculum to encourage early and regular testing.

(3) Ministry of Health Kenya should formulate policies that support widespread availability and affordability of HIVST kits, especially targeting youths in tertiary institutions

Recommendation for further research

Future research should explore the underlying reasons for low HIVST uptake among certain student groups and investigate the long-term impact of HIVST on HIV prevention and management. Future research should also consider longitudinal designs and include multiple institutions to provide a broader understanding of HIVST utilization among university students.

Limitations

This study’s limitations include its cross-sectional design, which does not establish causality. Additionally, the self-reported nature of the data may introduce bias. The study was also conducted at a single university, which may limit the generalizability of the findings to other settings. Non-response (overall and item-level) may have introduced selection bias; respondents could differ in HIV testing behaviour from non-respondents.

Footnotes

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Nicholas Kyalo Muendo

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