Students’ perception of healthcare services and factors affecting their utilization at a Nigerian University: a cross-sectional study

Study area

The study was conducted at ABUAD, located in Ekiti state, specifically in Ado Ekiti town, which serves as the capital of Ekiti state in southwestern Nigeria. ABUAD is a prominent institution in Ekiti, boasting an average student population of 8000²¹. ABUAD is a private university in Nigeria known for its modern teaching facilities, including advanced e-learning platforms and electronic boards. The university is organized into six colleges, namely, the College of Medicine and Health Sciences, the College of Pharmacy, the College of Law, the College of Engineering, the College of Sciences, and the College of Social and Management Sciences, which offer a diverse range of undergraduate studies.

Complementing these academic resources is the Afe Babalola University Multisystem Hospital (AMSH), which provides comprehensive healthcare services to the university community. AMSH is staffed by a diverse cadre of healthcare professionals, including doctors, nurses, and support staff, who are dedicated to delivering high-quality medical care. The hospital operates round-the-clock, ensuring that students have access to healthcare services at any time, whether for emergencies or routine medical needs….

Research design

This study utilized a cross-sectional design and employed a descriptive survey approach to gather information.

Study population and duration

The research was conducted among undergraduate students at ABUAD from April to May 2023.

Inclusion and exclusion criteria

The study included undergraduates from selected colleges who expressed a willingness to participate. Conversely, individuals who did not complete the questionnaire during the study period were excluded from the research.

Sample size determination

The sample size was determined using the Taro Yamane (1973) formula²².

where.

n = Minimum sample size.

N = accessible population.

e = Level of significance = 0.05.

The sample size was determined using a formula based on a study population of 8000 participants, a desired significance level of ± 5%, and a 10% adjustment for potential nonresponse. The calculated sample size was 423.

Sampling technique

A multi-stage sampling technique was employed to select participants for the study:

Stage 1:

Computer-generated codes were used for a simple random sampling technique to select four out of the six colleges at ABUAD. The decision not to include higher-level sampling, such as faculties, was based on the university’s organizational structure, which comprises colleges and departments.

Stage 2:

Two departments were selected from each college using a simple random sampling technique of computer-generated codes. This method ensured that each department had an equal and unbiased chance of being selected.. This approach was taken because each college at ABUAD typically includes a minimum of two departments except the College of Law which has one department. Proportionate allocation was then used to determine the number of students to be sampled from each department based on their relative sizes within the college (Table 1). Within each department, students were randomly selected to participate in the study. This was done by assigning numbers to all students in the department and using a random number generator to select the required number of participants. The link to the online questionnaire was shared with the selected students from each department.

To ensure the validity of responses, rigorous efforts were made to restrict the questionnaire’s access to eligible individuals and they include;

Access control:

The online questionnaire was distributed via a Google Forms link accessible only to students from the selected departments. Access was restricted to ensure that only eligible participants could respond.

Verification:

Participants were required to verify their student status before proceeding with the questionnaire, ensuring that only current ABUAD students were included in the study.

Response limits:

The Google Forms link was programmed to automatically stop accepting responses once the predetermined number of participants from each department was reached. This measure helped maintain sample integrity and data reliability.

Instrument for data collection

A 21-item semi-structured questionnaire was designed to address the study’s objectives. The survey comprised four sections: socio-demographics, utilization of healthcare services, students’ perceptions, and economic factors affecting healthcare utilization. The questionnaire included multiple-choice, Likert scale, and binary response questions.

The first section assessed the socio-demographics of the participants, gathering information on age, sex, marital status, and religion. Section B assessed the utilization of healthcare services among ABUAD students, using three questions that included yes/no and multiple-choice formats.Section C assessed the students’ perception towards the utilization of healthcare services. This section comprised 5 questions measured using a 4-point Likert scale, where “strongly agree” was the highest rank (assigned a score of 4) and “strongly disagree” was the lowest rank (assigned a score of 1). The students’ perceptions were quantified by summing their responses across five relevant questions. The possible total score for each student ranged from 5 (if a student selected “strongly disagree” for all questions) to 20 (if a student selected “strongly agree” for all questions). To categorize these perceptions into positive and negative, we compared the total score for each student against the midpoint of the possible score range, which is 12.5. Perceptions with a total score equal to or greater than 12.5 (more than 50% of the maximum possible score) were categorized as positive, while those with a total score less than 12.5 (less than 50% of the maximum possible score) were categorized as negative… The fourth section assessed the economic factors affecting the utilization of healthcare services among ABUAD students. A total of 3 questions were measured on a 4-point Likert scale. Strongly agree was the highest, and the strongly disagree was the lowest rank.

Validity and reliability

Content validity was ensured by academic staff in the Department of Public Health, Afe Babalola University. A pre-test involving 20 participants who were not part of the main sample was also conducted; the results yielded a Cronbach alpha reliability coefficient of 0.720, indicating good reliability.

Data collection and analysis

The self-administered online questionnaire was shared through selected departmental WhatsApp groups, and informed consent was obtained before participants accessed the survey. This ensured that only students from the selected departments could access the Google Forms link and participate in the study. Descriptive statistics were employed for categorical variables, and binary logistic regression analysis was used to assess the relationships between students’ perception and associated factors and between students’ perception and healthcare service utilization. Logistic regression was employed in this study to determine the influence of various social, perceptual, and economic factors on the utilization of healthcare services among students at Afe Babalola University. This statistical method is useful for modeling the relationship between a binary dependent variable (in this case, healthcare service utilization) and one or more independent variables (such as gender, family size, age, perceptions of healthcare services, and economic factors).

Steps in logistic regression analysis

Defining the dependent variable

The dependent variable in this analysis is the utilization of healthcare services, which is binary (0 = non-utilization, 1 = utilization).

The independent variables include:

Social factors

Gender, family size, and age.

Perception

Attitudes towards staff, distance of the facility, waiting time, and competence of healthcare staffs.

Economic barriers

Cost of services, ability to afford food, cost of drugs, family income, and monthly allowance.

Perception of healthcare services was defined through four key variables: attitudes towards staff, distance of the facility, waiting time, and competence of healthcare staff,. Each variable was measured using a Likert scale. Utilization of health services was defined as visiting the medical center at least once in the past six months. The individual variables were included in the logistic regression analysis to identify significant predictors of healthcare utilization.

In analyzing students’ perceptions of healthcare services, it was essential to focus on those who had actual experience with these services. Therefore, students who reported never utilizing the health services at the university medical center were excluded from the perception analysis. This exclusion ensures that the perception analysis accurately reflects the views of those with firsthand experience.

Perception factors considered students’ views on the attitude of healthcare staff, the distance of the facility from their hostel, waiting time, and staff competence. Economic barriers included students’ views on the affordability of services and food, the impact of high drug costs, family income across different brackets, and monthly allowances. Also, before the logistic regression analysis the responses of variables for perceptions and economic barriers were dichotomised into agree and disagree.

In our study, “economic barriers to utilization of health services” were assessed using three Likert scale questions. These questions asked participants to indicate their level of agreement (ranging from 1 = Strongly Disagree to 4 = Strongly Agree) with statements related to the financial aspects of accessing healthcare services.

For the purpose of the binary logistic regression analysis, we categorized the responses into two groups:

• “Agree” Category: This includes participants who selected “Agree” or “Strongly Agree.“.

• “Disagree” Category: This includes participants who selected “Disagree” or “Strongly Disagree.”

This binary categorization allowed us to create a dichotomous variable for each economic barrier question. In the regression model, we used “Agree” as the reference category. This means that the odds ratios generated from the regression analysis represent the likelihood of facing economic barriers (as defined by disagreement with the statements) compared to the reference group (those who agreed with the statements).

Statistical Product and Service Solutions (IBM SPSS) version 27 facilitated the data analysis, with the significance level set at 5%.

This study obtained ethical approval from the Afe Babalola University Health Research and Ethics Committee (ABUADHREC) before commencement, with the approval number ABUADHREC/19/05/2023/91. Informed consent was obtained from all subjects and/or their legal guardians, ensuring their voluntary participation. The study was conducted with a strict assurance of confidentiality for all information provided by the participants. Additionally, all methods were carried out in accordance with relevant guidelines and regulations, including the principles outlined in the Declaration of Helsinki.