Abstract
Background
Clinical practice is essential for developing competence, yet students in resource-limited settings often face multiple barriers. This study assessed the level of clinical learning challenges and associated factors among undergraduate nursing students at Wachemo University, Ethiopia.
Methods
An institution-based cross-sectional study was conducted from 18 February to 22 March, 2026. A census approach was used; all eligible regular undergraduate nursing students with clinical attachment were invited to participate. Data were collected via structured, self-administered questionnaires deployed through Kobo Toolbox. The tool incorporated a 9-item clinical learning challenge scale (5-point Likert), the Generalized Anxiety Disorder-2 (GAD-2) scale, the Patient Health Questionnaire-2 (PHQ-2) scale, and dedicated skill laboratory preparedness. High clinical learning challenge was defined as a total score
percentile (
. Data were analyzed using descriptive statistics and logistic regression analysis. Variables with p-value < 0.25 in Bivariable analysis were considered for multivariable logistic regression. Statistical significance was declared at p-value < 0.05.
Results
A total of 280 nursing students participated (response rate 93.3% of 300 invited). The most prevalent challenges were overcrowding in the clinical ward (74.3%), inadequate clinical materials and equipment (69.9%), and a high student-to-patient ratio limiting hands-on practice (67.5%). Overall, 137 (48.9%) students experienced high clinical learning challenges. In multivariable analysis, third-year academic standing (AOR = 2.48, 95% CI: 1.36–4.52), moderate-to-severe anxiety (AOR = 2.58, 95% CI: 1.49–4.46), moderate-to-severe depression (AOR = 1.95, 95% CI: 1.14–3.33), and inadequate skill laboratory preparation (AOR = 2.18, 95% CI: 1.32–3.60) were independently associated with high clinical learning challenges.
Conclusion and recommendation
Nearly half of nursing students experienced clinical learning challenges during clinical attachment. Poor skill laboratory preparation, psychological distress, and advanced academic year were key determinants. Strengthening skill laboratory training, improving clinical supervision, and providing psychological support services were recommended.
Keywords: Clinical learning challenges, Nursing students, Clinical practice, Undergraduate nursing education, Ethiopia
Introduction
Clinical learning is one of the most important components of nursing education, enabling students to apply theoretical knowledge in real-world healthcare settings [1]. Effective clinical practice enhances psychomotor skills, communication abilities, critical thinking, and professional competence among nursing students [2]. The clinical learning environment encompasses all physical, psychological, and educational factors that influence students’ acquisition of clinical competencies, including supervision quality, resource availability, and interpersonal relationships with staff and patients [3, 4].
Globally, approximately 40% to 80% of nursing students face several challenges during clinical attachment [5]. Studies from India (65%) [6], Bangladesh (68%) [7], and Kenya (75.8%) [8] highlight the magnitude of the problem. In Ethiopia, previous studies have reported prevalence rates as high as 79.2% [9], indicating that clinical learning challenges are particularly pronounced in resource-constrained settings.
The problem is more pronounced due to limited healthcare resources, including a shortage of clinical instructors, inadequate supervision, overcrowded clinical sites, lack of learning materials, fear of making mistakes, poor communication with staff, and limited opportunities for hands-on practice [10]. Additional barriers include high patient loads, insufficient teaching hospitals, and a shortage of qualified clinical instructors [1, 11, 12]. The quality of supervision has been identified as a critical factor, with students who receive structured guidance demonstrating greater confidence and clinical competence [11, 13].
These challenges may contribute to stress, anxiety, emotional exhaustion, and poor academic performance [5, 14, 15]. Clinical learning challenges may negatively influence students’ confidence, competency, and professional development [16, 17]. Moreover, unresolved stress during clinical attachment may contribute to burnout, reduced motivation, poor patient care, and increased intention to leave the profession [18–20]. The relationship between psychological distress and clinical performance is bidirectional; anxious or depressed students may have impaired cognitive function, reduced motivation, and difficulty concentrating during clinical procedures, while challenging clinical experiences may exacerbate existing psychological symptoms [5, 16, 21].
Skill laboratory preparedness is another crucial factor influencing clinical learning outcomes. Students who receive adequate simulation-based training before clinical placement demonstrate greater confidence and competence during patient care activities [7, 22, 23]. In Ethiopian universities, skill laboratories often suffer from insufficient manikins, outdated task trainers, high student-instructor ratios, and limited open practice hours [5, 15, 24], creating a gap between theoretical preparation and clinical reality.
Despite the importance of clinical learning in nursing education, there is limited evidence regarding the prevalence and determinants of clinical learning challenges among undergraduate nursing students in Ethiopia’s southern region. While studies have been conducted at other Ethiopian institutions [3, 4, 17, 25, 26], none have specifically examined Wachemo University, which serves a unique population with distinct healthcare infrastructure and educational resources. Understanding the specific challenges at this institution is essential for developing targeted interventions. Therefore, this study aimed to assess the prevalence of clinical learning challenges and associated factors among undergraduate nursing students at Wachemo University.
Methods
Setting
The study was conducted among undergraduate nursing students at Wachemo University, Ethiopia. Wachemo University is located in Hosanna Town, the administrative capital of Hadiya Zone, central Ethiopia. The university offers diverse undergraduate, postgraduate, and professional programs. It is College of Health Sciences and Medicine, which includes the Nursing Department, is vital in training healthcare professionals for the region. Wachemo University emphasizes community-based education and practical training. Nursing students complete clinical placements at affiliated health facilities, including Wachemo University Teaching and Referral Hospital, one of the largest hospitals in the area.
Study design and period
An institution-based cross-sectional study from 18 February to 22 March 2026.
Population and sample
The source population included all regular undergraduate nursing students who had completed at least one year of clinical practice. A census approach was adopted. All 300 eligible students were invited; 280 completed the questionnaire (response rate 93.3%). Sample size was adequate for logistic regression (events-per-variable ratio > 10) [27].
Inclusion and exclusion criteria
Inclusion criteria
Study participants were all regular undergraduate nursing students who had attended clinical practice during the study period.
Exclusion criteria
Students who were seriously ill or absent during data collection were excluded.
Data collection tool and procedure
Data were collected using a structured self-administered questionnaire adapted from previous validity studies [17, 25]. The tool had five sections: socio-demographic characteristics, clinical learning challenges (nine items, 5‑point Likert: 1 = never a problem to 5 = always a problem; total score 9–45), psychological distress (Generalized Anxiety Disorder-2 for anxiety and Patient Health Questionnaire-2 for depression) [18], skill laboratory preparation (two items), and coping strategies. High clinical learning challenges were defined as a total score at or above the 75th percentile (≥ 33), consistent with previous Ethiopian nursing studies [25]. Moderate-to-severe anxiety and depression were defined as GAD-2 and PHQ-2 scores ≥ 3, respectively (cutoff for validated screening for resource-limited settings) [17].
The 9-item clinical learning challenge scale demonstrated acceptable internal consistency in this study, with a Cronbach’s alpha coefficient of 0.81, indicating good reliability for assessing perceived clinical learning barriers. The skill laboratory preparation variable was measured using two items: “Skill lab sessions prepared me well for clinical practice” and “I practiced enough procedures before clinical attachment.” Responses were recorded on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree). For analysis, responses were dichotomized into “Agree” (strongly agree/agree) versus “Disagree/Neutral” (neutral/disagree/strongly disagree), consistent with previous Ethiopian studies [17, 25].
The questionnaire was translated into Amharic and back-translated for consistency. Data collectors received one day of training, and data were collected using Kobo Toolbox with daily supervision and completeness checks.
Variables
Dependent variable
Clinical learning challenge/stress(high vs. low).
Independent variables:
Age, sex, academic year, marital status, skill laboratory preparation (agree vs. neutral/disagree), anxiety (normal vs. moderate-severe), depression (normal vs. moderate-severe), coping strategies.
Operational definition
Clinical Learning Challenge: A student was categorized as having high clinical learning challenges if their total score on the 9-item clinical learning challenge scale was at or above the 75th percentile (≥ 33 out of 45). This threshold represents the top quartile of challenge severity and has been used in similar Ethiopian nursing education research [25].
Data quality management
The questionnaire was initially prepared in English and then translated to Amharic for data collection. Back-translation to English was performed to ensure consistency. The tool was adapted from similar studies conducted in Ethiopia. A one-day training was provided to data collectors and supervisors before data collection. The training covered study objectives, interview techniques, ethical considerations, and proper use of Kobo Toolbox. During data collection, supervisors conducted daily spot checks and provided feedback to data collectors. Completed questionnaires were reviewed for completeness and consistency on a daily basis. Incomplete questionnaires were rejected and re-collected. After data collection, double data entry was performed on 10% of the sample to check for entry errors.
Data processing and analysis
Data collected via Kobo Toolbox were exported to Microsoft Excel for initial cleaning. The data were then imported into SPSS version 27 for analysis. Descriptive statistics (frequency distributions, percentages, mean, median, standard deviation) were computed. For inferential analysis, Binary logistic regression was used. Multicollinearity was assessed using the variance inflation factor (VIF); all VIF values were < 2.5, indicating no significant collinearity. Multivariable logistic regression using the enter method was performed. Model fit was assessed using the Hosmer-Lemeshow test (p = 0.342) and Nagelkerke R² (0.224). Adjusted odds ratios with 95% confidence intervals were reported. Statistical significance was declared at p < 0.05.
Results
Socio-demographic and academic characteristics of participants
From 300 participants, 280 returned complete questionnaires (response rate 93.3%). The mean age (
) of participants was 22.8
and half of participants 140(50%) were 22–24 years age group. Among participants, 179 (63.9%) were female. Regarding academic year, the majority of students, 144(51.4%), were fourth-year nursing students (Table 1).
Table 1.
Socio-demographic and academic characteristics of participants
| Variables | Category | Frequency | Percentage (%) |
|---|---|---|---|
| Age (in years) | 19–21 | 98 | 35 |
| 22–24 | 140 | 50 | |
| 25–27 | 42 | 15 | |
| Sex | Male | 101 | 36.1 |
| Female | 179 | 63.9 | |
| Academic year | 2nd | 46 | 16.4 |
| 3rd | 90 | 32.1 | |
| 4th | 144 | 51.43 | |
| Marital status | Single | 247 | 88.2 |
| Married | 33 | 11.8 |
Prevalence of clinical learning challenges
Overcrowding in clinical areas/wards was the most reported challenge 74.3%, followed by inadequate clinical materials and equipment 69.9% and high student‑to‑patient ratio limits hands‑on practice 67.5%. Lack of clinical instructors to provide guidance was reported at 56.8%, and feeling nervous, anxious, or on edge 44.6%. Overall, 137 (48.9%,95% CI: 43.1% – 54.8%) students had high clinical learning challenges (Table 2).
Table 2.
Prevalence of clinical learning challenges
| Challenge items | Mean(SD) | % moderate to severe challenge |
|---|---|---|
| Overcrowding in clinical areas/wards | 3.9(1) | 74.3 |
| Inadequate clinical materials and equipment | 3.8 (1.1) | 69.9 |
| High student‑to‑patient ratio limits hands‑on practice | 3.7 (1.1) | 67.5 |
| Limited accessibility to clinical placements | 3.5 (1.2) | 60.7 |
| Lack of clinical instructors to provide guidance | 3.3 (1.3) | 56.8 |
| Feeling nervous, anxious, or on edge | 3.1 (1.4) | 44.6 |
| Trouble relaxing before/during clinical rotations | 2.9 (1.3) | 41.1 |
| Becoming easily annoyed or irritable | 2.7 (1.3) | 37.5 |
| Feeling afraid as if something awful might happen | 2.6 (1.2) | 34.3 |
Psychological distress, skill lab preparedness, and coping
Moderate‑to‑severe anxiety (GAD‑2 ≥ 3) was reported among 92 students (32.9%). Moderate‑to‑severe depression (PHQ‑2 ≥ 3) was found in 78 students (27.9%). Only 64 students (22.9%) agreed that skill lab sessions prepared them well for clinical practice, and just 56 (20.0%) felt they had practiced enough procedures before clinical attachment (Table 3).
Table 3.
Psychological distress, skill lab preparedness
| Variables | Category | Frequency | Percentage (%) |
|---|---|---|---|
| Anxiety (GAD‑2 score) | Normal (0–2) | 188 | 67.1 |
| Moderate‑severe (≥ 3) | 92 | 32.9 | |
| Depression (PHQ‑2 score) | Normal (0–2) | 202 | 72.1 |
| Moderate‑severe (≥ 3) | 78 | 27.9 | |
| Skill lab sessions prepared me well for clinical practice | Agree | 64 | 22.9 |
| Neutral / Disagree | 216 | 77.1 | |
| Practiced enough procedures before clinical attachment | Agree | 56 | 20.0 |
| Neutral / Disagree | 224 | 80.0 |
Coping strategies
The most common approaches were prayer/spiritual coping 200 (71.4%) and seeking support from friends 163 (58.2%). Ignoring stress was used by 98 (35.0%). Only 52 (18.6%) talked to instructors about their challenges. Substance use (khat, alcohol, or cigarettes) was reported by 45 students (16.1%); among them, khat chewing was most frequent (28, 10.0%) (Table 4).
Table 4.
Coping strategies
| Coping strategy | Frequency | % of students |
|---|---|---|
| Prayer / spiritual coping | 200 | 71.4 |
| Seeking support from friends | 163 | 58.2 |
| Ignoring the stress | 98 | 35.0 |
| Talking to instructors about challenges | 52 | 18.6 |
| Substance use (any) | 45 | 16.1 |
| Khat chewing | 28 | 10.0 |
| Alcohol use | 12 | 4.3 |
| Cigarette smoking | 5 | 1.8 |
Factors associated with clinical learning challenges
In Bivariate logistic regression analysis, sex, marital status, academic year, level of anxiety, depression, and Skill lab preparation were candidates. On multivariable analysis, third academic standing, level of anxiety, depression, and inadequate skill laboratory preparation were significantly associated with clinical learning.
Students in their third year had odds 2.48 times higher of experiencing high clinical learning challenges compared to second-year students (AOR = 2.48, 95% CI: 1.36–4.52, p = 0.003). Students with moderate‑to‑severe anxiety symptoms (GAD‑2 score ≥ 3) were 2.58 times more likely to experience high clinical learning challenges compared to those with normal anxiety levels (AOR = 2.58, 95% CI: 1.49–4.46, p = 0.001). Similarly, moderate‑to‑severe depression (PHQ‑2 score ≥ 3) independently increased the odds of high challenges by nearly twofold (AOR = 1.95, 95% CI: 1.14–3.33, p = 0.015). Students who disagreed or were neutral that skill lab sessions prepared them well for clinical practice had 2.18 times higher odds of high clinical challenges compared to those who agreed (AOR = 2.18, 95% CI: 1.32–3.60, p = 0.002) (Table 5).
Table 5.
Factors associated with clinical learning challenges
| Variables | Category | Clinical learning challenge | COR | AOR | P-value | |
|---|---|---|---|---|---|---|
| Absent N (%) | Present N (%) | |||||
| Sex | Female | 93 (52.0) | 86 (48.0) | 1.00 | 1.00 | |
| Male | 50 (49.5) | 51 (50.5) | 1.10 (0.69–1.77) | 1.15 (0.68–1.95) | 0.602 | |
| Marital status | Single | 127 (51.4) | 120 (48.6) | 1.00 | 1.00 | |
| Married | 16 (48.5) | 17 (51.5) | 1.13 (0.60–2.11) | 1.21 (0.59–2.48) | 0.608 | |
| Academic year | 2nd | 27 (58.7) | 19 (41.3) | 1.00 | 1.00 | |
| 3rd | 37 (41.1) | 53 (58.9) | 2.04 (0.99–4.19) | 2.48 (1.36–4.52) | 0.003 | |
| 4th | 80 (55.6) | 64 (44.4) | 1.14 (0.66–1.95) | 1.18 (0.65–2.14) | 0.586 | |
| Anxiety (GAD‑2 score) | Normal | 114 (60.6) | 74 (39.4) | 1.00 | 1.00 | |
| Moderate‑severe | 29 (31.5) | 63 (68.5) | 3.35 (1.97–5.68) | 2.58 (1.49–4.46) | 0.001 | |
| Depression (PHQ‑2 score) | Normal | 117 (57.9) | 85 (42.1) | 1.00 | 1.00 | |
| Moderate‑severe | 26 (33.3) | 52 (66.7) | 2.75 (1.68–4.74) | 1.95 (1.14–3.33) | 0.015 | |
| Skill lab prepared well | Agree | 43 (67.2) | 21 (32.8) | 1.00 | 1.00 | |
| Disagree/neutral | 100 (46.3) | 116 (53.7) | 2.38(1.32–4.27) | 2.18 (1.32–3.60) | 0.002 | |
Model fit: Hosmer-Lemeshow χ²=8.93, df = 8, p = 0.342; Nagelkerke R²=0.224; Classification accuracy = 68.2%
Discussion
This study assessed the prevalence of clinical learning challenges and associated factors among undergraduate nursing students at Wachemo University. This study revealed that nearly half (48.9% 95% CI: 43.1% – 54.8%) of students experience high-level clinical learning challenges. The finding is consistent with studies conducted in Ethiopia at Gondor (52%) [4] and Jimma (47%) [3], However, this prevalence is lower than some earlier Ethiopian studies reporting rates up to 79% [17, 25, 26]. This variation may reflect differences in measurement tools and cutoff points, as well as potential improvements in clinical education infrastructure in recent years.
The dominant challenges were overcrowding, inadequate equipment, and high student-to-patient ratio being the most frequently cited institutional barriers. This finding is consistent with studies conducted in other Ethiopian universities where shortage of resources and overcrowded teaching hospitals negatively affected clinical learning experiences [17, 26]. Similar patterns have been reported in other African settings, including Kenya [28] and Nigeria [10], suggesting that resource constraints are a widespread challenge in nursing education across the continent. The consistency of these findings across multiple institutions underscores the need for systemic improvements in clinical education infrastructure, including increased investment in teaching hospitals and clinical learning resources.
Those in third year had an odds ratio of 2.48 more likely to have clinical learning change than second year (AOR = 2.48, 95% CI: 1.36–4.52, p = 0.003). This pattern can be explained by the nature of clinical rotations; second-year students typically perform basic, low complexity skills (e.g., vital signs, hygiene) under close supervision. By third year, they are expected to manage more complex procedures (wound care, medication administration, and catheterization) in the medical-surgical ward, yet they have not acquired the coping strategy, ward familiarity, or professional confidence [19]. This transition to independent practice, when poorly scaffolded, can be particularly stressful [8]. Notably, fourth-year students did not have significantly higher odds than second-year students (AOR = 1.18, p = 0.586), suggesting that students adapt over time or that senior students develop more effective coping mechanisms. This trajectory has been reported in Ethiopian nursing programs and is consistent with theories of professional development in nursing education [17].
Students with moderate‑to‑severe anxiety symptoms (GAD‑2 score ≥ 3) were 2.58 times more likely to experience high clinical learning challenges compared to those with normal anxiety levels (AOR = 2.58, 95% CI: 1.49–4.46, p = 0.001). Similarly, moderate‑to‑severe depression (PHQ‑2 score ≥ 3) independently increased the odds of high challenges by nearly twofold (AOR = 1.95, 95% CI: 1.14–3.33, p = 0.015). More critically, both conditions independently predicted high clinical challenge. This indicates that anxious or depressed students do not simply perceive challenge as worse; their psychological state may actually impair their ability to engage in the clinical environment [6, 7, 23]. Anxious student my avoid asking questions, fear making mistakes, and hyperfocus on potential threats [7]. Depressed students often lack motivation and concentration that are essential for active participation in the ward [13, 14, 29]. These findings are consistent with international studies from India [14], Bangladesh [2], and Iran [9], which have documented strong associations between psychological distress and poor clinical learning outcomes. The relationship is likely bidirectional; challenging clinical experiences may exacerbate psychological symptoms, while psychological distress impairs clinical performance, creating a cycle that reinforces both conditions.
Students who disagreed or were neutral that skill lab sessions prepared them well for clinical practice had 2.18 times higher odds of high clinical challenges compared to those who agreed (AOR = 2.18, 95% CI: 1.32–3.60, p = 0.002). Students who practiced procedures before clinical attachment and received adequate instructor support were more confident and less stressed during patient care activities. This highlights the importance of simulation-based learning and well-equipped skill laboratories in nursing education. In Ethiopian universities, skill labs suffer from insufficient manikins, outdated task trainers, high student-instructor ratio, and limited open-hour practice [8, 13, 17, 25]. International studies from the United States [14] and Europe [1] have similarly demonstrated that simulation‑based learning significantly improves clinical competence and reduces anxiety during clinical placement. Investing in skill laboratory infrastructure and increasing opportunities for supervised practice before clinical placement could substantially reduce clinical learning challenges.
Strengths and limitations of the study
Strengths
The study achieved a high response rate (93.3%), used standardized screening tools (GAD‑2 and PHQ‑2) with established validity in resource‑limited settings, and provided a comprehensive assessment of environmental, psychological, and educational factors influencing clinical learning.
Limitations
The cross‑sectional design precludes causal inference; while associations were identified, the direction of causality cannot be determined. Self‑reported data may be subject to social desirability bias, and the 9‑item clinical challenge scale measures perceived severity rather than objective external evaluation of the clinical environment. The single‑institution setting limits generalisability to other contexts. The screening tools (GAD‑2 and PHQ‑2) do not establish clinical diagnoses, only screen for symptoms. The cutoff used for defining high clinical learning challenges (75th percentile) may affect prevalence estimates and should be interpreted cautiously when comparing with studies using different thresholds.
Conclusion
Clinical learning challenges are highly prevalent among nursing students at Wachemo University, affecting nearly one in two students. Overcrowded wards, inadequate equipment, and high student‑to‑patient ratios are the most common institutional barriers. Independent determinants identified include third‑year academic status, anxiety, depression, and poor skill laboratory preparation as independent predictors of clinical learning challenge.
Recommendations
For Wachemo University
✓ Significantly strengthen skill laboratory facilities and increase simulation-based teaching.
Establish student counselling and psychological support services, including routine screening for anxiety and depression and referral pathways for students experiencing psychological distress.
Counselling
For Clinical Training Sites
Develop structured orientation and supportive supervision.
For Future Researchers
Conduct longitudinal and multicenter studies.
Explore qualitative experiences of nursing students during clinical attachment.
Acknowledgements
The authors would like to thank Wachemo University, data collectors, supervisors, and all nursing students who participated in this study.
Author contributions
Conceptualization: Sentayehu Admasu Saliya Data curation: Sentayehu Admasu Saliya Formal analysis: Sentayehu Admasu Saliya Funding acquisition: Sentayehu Admasu Saliya Investigation: Sentayehu Admasu Saliya Methodology: Sentayehu Admasu Saliya Validation: Sentayehu Admasu Saliya Visualization Sentayehu Admasu Saliya Writing – original draft: Sentayehu Admasu Saliya Writing – review & editing: Sentayehu Admasu Saliya.
Funding
No specific funding was received for this study.
Data availability
No datasets were generated or analysed during the current study.
Declarations
Ethical approval
was obtained from Wachemo University’s Institutional Review Board (Ref: WU/IRB/112/2026). Written informed consent was obtained from each participant. Participation was voluntary, and confidentiality was maintained by using codes. The study was conducted in accordance with the Declaration of Helsinki.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
No datasets were generated or analysed during the current study.