3.1. Study Design and Setting
This study used a convergent cross-sectional mixed-methods design, in which quantitative survey data and qualitative open-ended responses were collected simultaneously and analyzed independently before integration during interpretation. The cross-sectional design involved collecting data at a single point in time to assess associations between logbook characteristics and student satisfaction outcomes. Quantitative data were collected using a structured questionnaire, whereas qualitative insights were obtained from open-ended responses. This approach enabled a comprehensive assessment of logbook use, student satisfaction, and perceived educational value. The study followed a convergent mixed-methods framework, in which quantitative and qualitative strands were analyzed independently and integrated during interpretation to provide comprehensive insight into the research question.
The research was conducted across seven medical universities in the Kurdistan Region: Koya University, Hawler Medical University, University of Sulaimani, University of Duhok, University of Zakho, University of Garmian, and University of Kurdistan Hewler. Participants were recruited from clinical teaching hospitals and medical campuses affiliated with these universities.
Data collection took place during the 2024 - 2025 academic year, from November 15, 2024, to March 1, 2025, spanning approximately 3.5 months.
3.2. Study Population and Sampling
The target population comprised medical students in the clinical years (stages 2 - 6 and final-year graduates) with prior experience using either paper or electronic logbooks. Students in preclinical years or those without logbook experience were excluded.
Convenience sampling was used because of accessibility and feasibility, resulting in the participation of 210 students. Participants were invited through institutional communication channels and student groups, and those who voluntarily responded to the online questionnaire were included. Although this approach enabled efficient data collection across multiple institutions, it may limit the generalizability of the findings.
The sample size was determined based on feasibility and the availability of eligible participants during the data collection period. No formal sample size calculation was performed.
3.3. Variables
The primary outcome variable was student satisfaction with logbook use, measured as a categorical variable (satisfied vs. not satisfied/recommendation vs. non-recommendation). For ordinal logistic regression, satisfaction was initially measured using five response categories, from very dissatisfied to very satisfied. For binary logistic regression, categories were collapsed into satisfied (satisfied/very satisfied) versus not satisfied (neutral/dissatisfied/very dissatisfied).
Key exposure and predictor variables included frequency of logbook use (regular vs. irregular), type of logbook (paper vs. electronic), template clarity (clear vs. unclear), and perceived challenges, such as time constraints, unclear guidelines, and difficulty recalling clinical details.
Potential confounders considered in the regression analyses included gender, university affiliation, and academic level.
3.4. Data Collection Tool
Data were collected using a structured, self-administered questionnaire distributed via Google Forms. The tool was adapted from a previously validated instrument (
11) and refined for the study context. Minor wording modifications were made to ensure contextual relevance. Content validity was assessed through consultation with two faculty members in medical education, and minor adjustments were made accordingly.
The questionnaire comprised four sections: 1) demographics, including age, gender, university, and level of study; 2) logbook characteristics, including type, frequency of use, and activities recorded; 3) perceived benefits, including self-confidence, learning, communication, and progress tracking; and 4) challenges and satisfaction, including difficulties faced, overall satisfaction, and suggestions for improvement.
Closed-ended questions used categorical response options, whereas satisfaction was assessed using ordinal response categories that were later grouped for regression analysis.
3.5. Ethical Considerations
Ethical clearance was obtained from the ethics committee of the Faculty of Medicine, Koya University. Participation was voluntary, and electronic informed consent was obtained from all participating medical students before completion of the questionnaire. Participants were provided with detailed information about the study purpose, procedures, confidentiality, and their right to withdraw at any stage without penalty. Submission of the completed questionnaire was considered an indication of informed consent. Data were collected anonymously, with no personally identifiable information recorded.
3.6. Bias
To minimize selection bias, the questionnaire link was distributed across multiple universities to capture a diverse sample of medical students. Information bias was reduced by using a standardized, structured questionnaire. However, recall bias may have occurred because the measures were self-reported. The cross-sectional design also limits causal inference. Residual confounding may persist despite adjustment in multivariable regression models.
3.7. Data Analysis
Quantitative data collected through Google Forms were exported to Microsoft Excel for cleaning and subsequently analyzed using IBM SPSS Statistics version 27.
Descriptive statistics, including frequencies and percentages, were used to summarize demographic characteristics and categorical study variables.
Student satisfaction with logbook experience was treated as an ordinal outcome variable using five response categories, from very dissatisfied to very satisfied. Ordinal logistic regression analysis was performed to identify factors associated with higher levels of satisfaction. Variables with a P value < 0.20 in univariate analysis were entered into a multivariable ordinal logistic regression model to adjust for potential confounding. Regression coefficients (β), 95% confidence intervals (CIs), and P values were reported.
For the analysis of logbook recommendation, the outcome variable was dichotomized as recommend versus not recommend/unsure. Binary logistic regression was used to examine predictors of recommendation, and results were presented as odds ratios (ORs) with corresponding 95% CIs and P values.
Independent variables included logbook use frequency, template clarity, perceived challenges, academic stage, university affiliation, gender, and age group. Multicollinearity was assessed before regression modeling to ensure model stability. A P value ≤ 0.05 was considered statistically significant.
Qualitative data obtained from open-ended responses were analyzed using a descriptive thematic analysis approach, following the framework of Braun and Clarke (
12). Of the 210 participants included in the quantitative analysis, 162 (77.1%) provided responses to at least one open-ended question and were included in the qualitative strand of the study. Responses were exported verbatim from Google Forms, anonymized, and checked for completeness before analysis.
Two researchers independently reviewed the responses multiple times for familiarization and generated initial inductive codes. Discrepancies between coders were discussed and resolved through consensus to enhance analytical rigor. Codes were subsequently organized into broader themes reflecting perceived benefits, challenges, rewarding clinical stages, and suggested improvements. Themes were reviewed and refined to ensure coherence and internal consistency.
Recurrent patterns across responses indicated adequate descriptive depth for interpretation. Quantitative and qualitative findings were integrated during the interpretation phase, consistent with a convergent mixed-methods design, to provide a comprehensive understanding of logbook effectiveness.