Perceived effects of accreditation on education quality and health-related job outcomes: scales validation and correlates in Lebanon

Deema Rahme; Daniele Saade; Hala Sacre; Chadia Haddad; Samah Tawil; Samar Merhi; Randa Aoun; Aline Hajj; Fouad Sakr; Jihan Safwan; Marwan Akel; Rony M Zeenny; Pascale Salameh

doi:10.1186/s12909-025-07448-5

. 2025 Jul 1;25:886. doi: 10.1186/s12909-025-07448-5

Perceived effects of accreditation on education quality and health-related job outcomes: scales validation and correlates in Lebanon

Deema Rahme ^1,^2,^✉,^#, Daniele Saade ^2,^#, Hala Sacre ², Chadia Haddad ^2,^3,⁴, Samah Tawil ^2,³, Samar Merhi ⁵, Randa Aoun ², Aline Hajj ^2,^6,⁷, Fouad Sakr ^2,⁸, Jihan Safwan ^2,⁸, Marwan Akel ², Rony M Zeenny ^2,⁹, Pascale Salameh ^2,^3,^10,¹¹

PMCID: PMC12211563 PMID: 40597986

Abstract

Background

This study examines the impact of program accreditation on education quality and career outcomes among students and graduates of health-related disciplines in Lebanon. In the absence of a national accrediting body, many universities seek international accreditation. Additionally, the study validates four scales measuring factors influencing university choice and perceptions of accreditation.

Methods

A cross-sectional study was conducted between September and December 2023, enrolling 642 participants, including students and graduates from Lebanese health-related programs. Four validated scales included: Reasons for Choosing University Program (RCUP, 14 items), Perception of University Program Accreditation (PUPA, 12 items), Perceived Impact on Education Quality (PI-AQE, 27 items), and Perceived Impact on Career Outcomes (PI-ACO, 9 items). Principal component analysis with Promax rotation assessed construct validity. Bivariate analyses (t-tests and ANOVA) examined relationships between scales and participant characteristics. Multivariate analysis of covariance (MANCOVA) adjusted for sociodemographic and university-related factors, while multiple regression explored predictors of time to employment for graduates.

Results

Students from three universities reported significantly lower RCUP scores, indicating weaker motivations for their program choice. Clear communication of accreditation status correlated positively with RCUP (β = 1.097, p = 0.004). Pharmacy students scored higher on RCUP (β = 2.412, p = 0.002). Higher income levels (β = 1.829, p = 0.020) and awareness of accreditation (β = 2.348, p = 0.004) were linked to more favorable PUPA scores. Females (β = 4.981, p = 0.002) and high-income individuals (β = 3.777, p = 0.040) anticipated a stronger impact on PI-AQE. Graduates, particularly those with a PhD (β = 4.755, p = 0.042) or a Bachelor’s degree (β = 2.557, p = 0.003), expressed more positive PI-ACO perceptions. Conversely, uncertainty about accreditation was associated with lower PI-ACO scores (β = -3.019, p = 0.004). Notably, university accreditation status (β = -0.355, p = 0.011) and longer professional experience (β = -0.274, p = 0.010) were significantly linked to a shorter time to employment.

Conclusion

This study validates tools for assessing accreditation’s impact on Lebanese health education. Findings emphasize that accreditation status, program choice, and demographics significantly shape perceptions of education quality and career prospects. Effective communication about accreditation may enhance career readiness and suggest potential benefits for employment prospects. These findings emphasize the importance of accreditation as a strategic tool for advancing health education quality and optimizing career prospects in the healthcare sector.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12909-025-07448-5.

Keywords: Quality education, Health profession, University accreditation, University choice, Career outcome, Scale validation, Accreditation perception

Introduction

Ensuring high-quality education in health professions is paramount, as graduates play a vital role in delivering optimal patient care [1, 2]. Accredited programs provide a comprehensive and up-to-date curriculum, equipping students with the necessary knowledge and skills to excel in the healthcare sector [3–5]. Accreditation signifies a program's commitment to continuous improvement, transparency, and meeting professional standards [6, 7]. This, in turn, fosters student success by opening doors to scholarships, facilitating credit transfer between institutions, and ensuring graduates possess the qualifications sought by employers [7–11]. Accreditation plays a role in maintaining the quality and relevance of the curriculum by assessing and updating it according to professional practice standards and the evolving needs of the healthcare industry [12–14]. It also supports the growth and professional development of faculty and staff members [12, 13]. Further, accredited institutions offer research prospects where students can benefit from research facilities, experienced faculty members, and collaborative projects that expand their knowledge and drive innovation [15–17]. The accreditation of health-related academic programs demonstrates significant regional variations in frameworks, standards, and implementation approaches. The Americas have developed a comprehensive and well-established system through interstate collaboration, emphasizing quality assurance and educational standards through established bodies [18, 19], while Europe's journey toward accreditation has been more gradual, marked by a 65-year lag behind the U.S., influenced by market liberalization and inter-state cooperation [18]. Africa has shown progress through initiatives like the tropEd network, which focuses on establishing common standards and quality assurance mechanisms across diverse institutions [20].

In Lebanon, despite universities obtaining initial permission from the Ministry of Education and Higher Education (MEHE) to operate, a national quality agency for program accreditation is lacking [21]. This gap has prompted Lebanese health-related academic programs to actively seek accreditation from recognized international bodies, as a means to ensure quality standards and global recognition.

Similarly, Arab nations have made significant strides in implementing accreditation processes to standardize healthcare education [22–24]. Regional and national accreditation bodies evaluate various aspects of programs, guaranteeing adherence to set benchmarks [25–29]. Many universities in the Middle East, including Lebanon, Qatar, Jordan, and Oman, actively seek international accreditation to ensure global competitiveness of their graduates and their ability to contribute to advancements in healthcare [30–37].

When choosing a university, students consider various factors, with program accreditation playing a pivotal role. It signifies adherence to quality standards and aligns with other considerations such as university rankings, faculty expertise, and research opportunities [38–41]. University ranking systems like QS and Times Higher Education provide valuable information to students seeking informed decisions about their education [42, 43].

Despite the importance of program accreditation in Lebanon, there is currently a lack of research on student and graduate awareness and perceptions regarding accreditation and its impact on their education and career outcomes in health professions such as medicine, pharmacy, nursing, dentistry, and nutrition [44–46]. This knowledge gap highlights the need for further investigation to understand the true effects of program accreditation on educational quality and job prospects for health professionals in Lebanon. This study aimed to validate four measurement scales that assess university choice factors, accreditation perception, and the perceived impact of accreditation on educational quality and career outcomes among Lebanese health domain students and graduates, while also examining the correlations between these perceptions and employment outcomes.

Methods

Study design and participant recruitment

A cross-sectional study design was employed to further validate the developed scales and assess the perspectives of students and graduates. Data collection occurred between September and December 2023. The target population consisted of two main categories: first, university students who are currently enrolled as undergraduates in health-related disciplines at various Lebanese universities; second, healthcare professionals who graduated from Lebanese universities within the past 10 years.

Snowball sampling was the primary recruitment strategy in this study, specifically chosen to overcome the limitations of traditional methods, such as random sampling from university records or contacting healthcare institutions, in reaching health profession students and graduates [47]. The process began with carefully selected"seed"participants who met the eligibility criteria and played a key role in referring other qualified participants from their professional networks [48].

This approach leveraged existing relationships within the healthcare field, facilitating access to participants who might have been difficult to reach through conventional methods while fostering trust through peer referrals [47, 48]. The questionnaire was administered as an online survey created using Google Forms, ensuring easy access and completion. The introductory page outlined the study’s purpose, eligibility requirements, and included a mechanism for participants to share the survey link with others.

Participants were encouraged to distribute the link to classmates, colleagues, and relevant social media groups or professional associations. As new participants completed the survey, they too were encouraged to share the link within their own networks. This referral process created a snowball effect, gradually expanding the participant pool from the initial"seeds"to a more diverse sample across various health disciplines.

Participation in the study was entirely voluntary and involved no incentives. To ensure privacy and confidentiality, all collected data were anonymized and de-identified.

Scale development and content validity

The study employed the Delphi technique, a structured communication method developed by the RAND Corporation in the 1950 s [49], which is widely used in healthcare research to achieve consensus through systematic, interactive rounds of expert consultation [50, 51]. A modified Delphi approach was used in this study to develop a consensus-based list of items evaluating the impact of program accreditation in health professions education [52]. The process involved a multidisciplinary panel of thirteen academics with extensive experience (minimum of 10 years) in teaching, research, quality assurance, and accreditation within health professions, including pharmacy, medicine, nutrition, nursing, and physical therapy. This diverse panel ensured a comprehensive perspective on the subject.

Delphi Process was as follows:

Round 1 – Initial Item Generation and Focus Group Discussion

The first phase began with a comprehensive literature review to identify key items related to the impact of accreditation in health professions education. These items formed the basis for a structured discussion among the expert panel in a focus group setting. Panelists were encouraged to critically evaluate the proposed items, suggest modifications, and propose additional items based on their expertise and experiences.

2.
Round 2 – Online Assessment and Item Refinement

Following the focus group discussion, a refined list of items was compiled and distributed to the expert panel via an online survey. Panelists were asked to rate the importance and relevance of each item using a Likert scale. Statistical analysis was performed to assess consensus, with a predetermined agreement threshold of 90% for item retention.

3.
Consensus and Finalization

Items that did not reach the 90% consensus threshold were reconsidered, revised, or eliminated based on expert feedback. The final set of items represented the collective agreement of the panel on key factors influencing accreditation outcomes in health professions education.

This rigorous process resulted in four distinct scales: Reasons for Choosing a given University/Program (RCUP – 14 items), Perception of University/Program Accreditation (PUPA – 12 items), Perceived Impact of University/Program accreditation on the quality of education (PI-AQE – 27 items), and Perceived Impact of University/Program Accreditation on Career Outcomes (PI-ACO – 9 items). Each scale utilized a 5-point Likert format (1 = strongly disagree to 5 = strongly agree) to assess respondents'attitudes and perceptions.

Ethics approval

The Research Ethics Committee at INSPECT-LB (Institut National de Santé Publique, d'Épidémiologie Clinique et de Toxicologie-Liban) approved the study protocol under the reference number (2023REC-013-INSPECT-10–09).

Sample size

The minimum sample size for the study was 384 participants, calculated using Epi Info 7 for a population-based survey. Alpha was set at 5% and beta at 20% [53]. The calculation was performed with a 5% confidence limit to yield a 95% confidence interval, with the design effect set to 1, given that no cluster sampling was used [53].

Questionnaire

The study questionnaire was developed in English and designed to be completed in approximately 10 min. This self-administered questionnaire served to assess the perspectives of both university students and graduates from health professions programs in Lebanon regarding program accreditation. The questionnaire was divided into four key sections.

The first section focused on gathering basic demographic information about the participants. This included standard details like age, gender, and university affiliation. For students, their major field of study was captured, while graduates provided information on their professional status and work experience. Additionally, the researchers employed the household crowding index [54] as a measure of socioeconomic status. This index calculates the number of people residing in the participant's household divided by the number of rooms (excluding kitchens and bathrooms).

Moving beyond demographics, Section 2 delved into the various factors that influenced participants'decisions when choosing a university and specific program. The questionnaire likely explored a range of potential influences, such as the reputation and ranking of the university, whether the program was accredited, the specific curriculum content and course offerings, the qualifications and expertise of the faculty, the availability of research opportunities for students, the support services offered by the university (e.g., financial aid), the quality of campus facilities, and finally, the career prospects associated with the chosen program.

Section 3 shifted the focus to program accreditation itself. Here, the questionnaire aimed to assess participants'level of awareness and understanding of program accreditation. The specific questions likely explored their knowledge of accreditation bodies operating in the region, the importance they placed on program accreditation when making their university and program choices, and their perceived benefits of program accreditation for both students and graduates.

Finally, Section 4 addressed the perceived impact of program accreditation on educational quality and career outcomes. This section likely explored how participants believed accreditation influenced the quality of education they received or will receive. It likely also investigated their perceptions of how accreditation might impact their job opportunities and career advancement prospects after graduation.

Statistical analysis

The data were analyzed using SPSS software version 25(IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp; 2017). Descriptive analysis used counts and percentages for categorical variables and mean and standard deviation for continuous measures.

A Principal component analysis technique (PCA) using the Promax rotation was conducted to assess the construct validity of the suggested scales. The Kaiser–Meyer–Olkin (KMO) and Bartlett’s test of sphericity were calculated to ensure the model’s adequacy. Additionally, Cronbach’s alpha values were calculated for every scale to assess their internal consistency (reliability). These scales were deemed normally distributed, as verified by the visual inspection of the histogram, while the skewness and kurtosis were below |1.96|.

The bivariate analysis was conducted by taking the four scales as the dependent variables. The independent-sample t-test was used to compare the means of scales between two groups, whereas the ANOVA test was used to compare three or more means. The Pearson correlation test was used to correlate continuous variables. Bonferroni correction was applied for multiple testing; the corrected alpha was obtained by dividing 0.05 by the number of comparisons to be tested, yielding a significance level below 0.002 in the bivariate analysis [55]. After that, a multivariate analysis of covariance (MANCOVA) was carried out to compare the four scales between the type of profession (student vs. graduate) adjusted for age, gender, major of the study, monthly income, name of university, years to find a job, highest degree, accreditation status, being aware of accrediting agency, communication or promotion about accreditation by the university. In addition, a multiple regression was conducted to assess the correlates of the time between graduation and employment after ensuring the absence of co-linearity, homoscedasticity, normality of the residues, and the linear relationship. A p-value less than 0.05 was considered significant.

Results

Sociodemographic characteristics

A total of 642 health students and graduates participated in the study; their mean age was 23.3 years (± 5.167). The majority were not married (90.7%), females (81%), undergraduate students (75.4%), specializing in pharmacy (60.3%), and residing in Beirut (34.9%) and Mount Lebanon (33.5%). Income was well distributed across categories and Lebanese regions. Appendix Table 1 presents the detailed sociodemographic data characteristics.

Employment characteristics

Regarding work experience, most respondents were students not working (56.4%), followed by working students (21.3%). Among those who were employed, the majority had less than two years of work experience (14.3%) and were working in the same field of their study major (32.7%). Furthermore, the majority (20.9%) of healthcare professionals took less than one year to find a job and were practicing in Lebanon (36.1%) (Appendix Table 2).

Sociodemographic and professional characteristics

In the bivariate analysis, most undergraduate respondents were pharmacists (75%), while nutritionists were the most represented among graduates (27.8%). A similar percentage of graduates had either a Bachelor’s or a Master’s degree as the highest level of education (P < 0.001). Most graduates were from the Lebanese University (34.9%) and were currently working full-time in their main field of study (61.4%). The majority lived in Lebanon and secured a job within one year of graduation (34.8%). Almost the same number of graduates had less than two years of work experience. All other differences between students and graduates are listed in Table 1.

Table 1.

Differences in sociodemographic and professional characteristics between students and graduates

Variable	Undergraduates (%) N = 484	Graduates (%) N = 158	p-value
Gender
Male	92 (19.0%)	30 (19.0%)	1.000
Female	392 (81.0%)	128 (81.0%)	1.000
Marital status
Single/Widowed/Divorced/Separated	471 (97.3%)	116 (73.4%)	< 0.001
Married	13 (2.7%)	42 (26.6%)	< 0.001
Major of study
Pharmacy	363 (75.0%)	24 (15.2%)	< 0.001
Medicine	29 (6.0%)	2 (1.3%)
Nursing	15 (3.1%)	31 (19.6%)
Dentistry	50 (10.3%)	0 (0.0%)
Physical Therapy	4 (0.8%)	9 (5.7%)
Nutrition	2 (0.4%)	44 (27.8%)
Medical Laboratory	14 (2.9%)	23 (14.6%)
Midwifery	5 (1.0%)	18 (11.4%)
Other	2 (0.4%)	7 (4.4%)
Highest degree earned
Undergraduate	431 (89.0%)	4 (2.5%)	< 0.001
Bachelor	44 (9.1%)	71 (44.9%)
PharmD/Medical Doctor	6 (1.2%)	5 (3.2%)
Masters	3 (0.6%)	70 (44.3%)
PhD	0 (0.0%)	8 (5.1%)
Other
Name of university graduated from/will graduate from
Lebanese University (UL)	43 (8.9%)	53 (34.9%)	< 0.001
Saint Joseph University (USJ)	67 (13.8%)	22 (14.5%)
Beirut Arab University (BAU)	64 (13.2%)	13 (8.6%)
Lebanese American University (LAU)	1 (0.2%)	5 (3.3%)
Lebanese International University (LIU)	286 (59.1%)	14 (9.2%)
Notre Dame University-Louaize (NDU)	18 (3.7%)	25 (16.4%)
Other	5 (1.1%)	26 (13.1%)
Income (USD)
< 500	119 (24.6%)	33 (20.9%)	0.522
500 −1000	130 (26.9%)	51 (32.3%)
1001–2000	109 (22.5%)	35 (22.2%)
2001–3000	51 (10.5%)	12 (7.6%)
3001–4000	28 (5.8%)	13 (8.2%)
> 4000	47 (9.7%)	14 (8.9%)
Region of living
Beirut	193 (39.9%)	31 (19.6%)	< 0.001
Mount Lebanon	134 (27.7%)	81 (51.3%)
North Lebanon	71 (14.7%)	13 (8.2%)
South Lebanon	71 (14.7%)	8 (5.1%)
Beqaa	15 (3.1%)	6 (3.8%)
Abroad	0 (0.0%)	19 (12.0%)
Professional Status
Student (working)	135 (27.9%)	0 (0.0%)	< 0.001
Student (not working)	349 (72.1%)	0 (0.0%)
Graduate/Postgraduate working full-time	0 (0.0%)	97 (61.4%)
Graduate/Postgraduate working part-time	0 (0.0%)	25 (15.8%)
Graduate/Postgraduate not working	0 (0.0%)	36 (22.8%)
Current field of work
Same as my university degree as a health professional	101 (20.9%)	109 (69.0%)	< 0.001
Different from my university degree as a health professional	56 (11.6%)	18 (11.4%)
Does not apply since I do not work (student or graduate not working)	327 (67.6%)	31 (19.6%)
Place of Employment
I don’t work	348 (71.9%)	32 (20.3%)	< 0.001
Lebanon	122 (25.2%)	110 (69.6%)
Abroad	3 (0.6%)	14 (8.9%)
Remote job	11 (2.3%)	2 (1.3%)
How many years did it take to find a job after graduation?
Not applicable	427 (88.2%)	27 (17.1%)	< 0.001
< 1	37 (7.6%)	55 (34.8%)
1–2	11(2.3%)	29 (18.4%)
2–3	4 (0.8%)	8 (5.1%)
> 3	5 (1.0%)	39 (24.7%)
Years of work experience
Not applicable	427 (88.2%)	27 (17.1%)	< 0.001
0–2	37 (7.6%)	55 (34.8%)
2–5	11 (2.3%)	29 (18.4%)
5–7	11 (2.3%)	29 (18.4%)
> 7	0 (0%)	18 (11.3%)
	Mean ± SD	Mean ± SD
Age	21.55 ± 2.16	28.61 ± 7.52	< 0.001
Household crowding index	1.13 ± 0.55	1.06 ± 1.72	0.43

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Scale validation and description

Construct validity and factor analysis

A factor analysis was run to assess the construct validity of all concepts. Items related to every scale could be extracted with Promax rotation. All items loaded appropriately on their respective factors (domains), and no variable showed low factor loading (< 0.3), low communality (< 0.3), or over-correlation with each other (r > 0.9). The KMO measures of sampling adequacy were satisfactory for all models, ranging from 0.500 to 0.956, with a significant Bartlett’s test of sphericity (P < 0.001). The percentage of explained variance ranged from 53.65% to 87.7%. Table 2 presents the Promax rotated matrix of factor analysis of the four scales used in this study. The final validated scales related to the Choice of University/Program and Perception of Accreditation comprised three domains each. Regarding the Impact of University/Program accreditation on the quality of education, it included two domains, while all the items in the Impact of University/Program accreditation on career outcomes formed one component.

Table 2.

Factor analysis (Promax rotated component matrix) and internal consistency of the four scales

Domain	Behaviors	Loading	Cronbach alpha
Reasons for Choosing a University/Program (RCUP)			0.839
Kaiser–Meyer–Olkin (KMO) = 0.857; Bartlett’s test of sphericity P < 0.001; cumulative percentage of variance explained 53.67%
Domain I: Educational aspects	1. Quality and reputation of academic programs	0.782	0.661
	2. Accreditation of the University/Program of interest	0.683	0.661
	3. Availability of the study major	0.680
	4. University ranking	0.538
Domain II: Learning experience aspects	5. Cost of tuition and availability of financial aid	0.699	0.637
	6.Geographical location of the university campus	0.690
	7.Extracurricular activities (sports, clubs, etc.)	0.487
	8.Campus facilities (libraries, labs, etc.)	0.474
Domain III: Deontology and career aspects	12. Personal values and alignment with university culture	0.812	0.795
	11. Diversity and inclusiveness of the student body	0.785
	13. Recommendations from teachers, counselors, or peers	0.740
	10. Size of the university (small, medium, large)	0.610
	14. Career opportunities	0.558
	9. Opportunities for internships and experimental training	0.407
Perception of University/Program Accreditation (PUPA)			0.899
Kaiser–Meyer–Olkin (KMO) = 0.88; Bartlett’s test of sphericity P < 0.001; cumulative percentage of variance explained 69.72%
Domain I: Importance of accreditation	1. Accreditation agencies are credible and effective in evaluating the University/Program	0.907	0.848
	2. Accreditation is essential for a University/Program	0.839
	3. An accredited University/Program influences my decision to enroll in a particular program	0.815
	5. It is essential for a University/Program to maintain accreditation	0.653
Domain II: Communication about accreditation	7. Regularly sharing information with students through official e-mails or newsletters improves communication and awareness of accreditation status	0.906	0.893
	8. Organizing informational sessions or workshops for students improves communication and awareness of accreditation status	0.901
	9. Creating a dedicated webpage or online portal with accreditation details improves communication and awareness of accreditation status	0.846
	10. Displaying accreditation certificates or logos in visible areas improves communication and awareness of accreditation status	0.764
Domain III: Students awareness about accreditation	6. I think there is enough awareness among students about the accreditation status of my University/Program	0.848	0.781
	11. Joining a non-accredited University/Program has potentially negative consequences on educational outcomes	0.764
	12. Joining a non-accredited University/Program has potentially negative consequences on career outcomes	0.753
	4. I am aware of the criteria and standards a University/Program should meet to become accredited	0.641
Perception of the Impact of University/Program Accreditation on the Quality of Education (PI-AQE)			0.981
Kaiser–Meyer–Olkin (KMO) = 0.97; Bartlett’s test of sphericity P < 0.001; cumulative percentage of variance explained 72.09%
Domain I: Impact of accreditation on educational quality	1. Accreditation is essential for ensuring quality education	0.666	0.969
	2. Accreditation enhances the reputation of the institution	0.893
	3. Accreditation improves the credibility of the degrees offered	0.858
	4. Accreditation enables students to transfer credits to other institutions effortlessly	0.615
	5. Accreditation helps institutions identify areas for improvement	0.735
	6. Accreditation ensures that the curriculum is up-to-date and relevant	0.889
	7. Accreditation promotes high standards of teaching and learning	0.963
	8. Accreditation ensures that faculty members are qualified and experienced	0.777
	9. Accreditation ensures that students have access to the necessary resources and facilities	0.752
	10. Accreditation encourages institutions to continuously improve the quality of education	0.859
	11. Accreditation fosters a culture of innovation and research in the institution	0.684
	12. Accreditation provides students with a strong foundation of knowledge and skills	0.623
	13. Accreditation instills confidence in the quality of education received by students	0.734
	14. Accreditation enhances the quality of the experiential learning programs (professional training)	0.520
	22. Accreditation enhances the reputation and credibility of the degree for postgraduate studies internationally	0.522
Domain II: Impact of accreditation on postgraduation outcomes	25. Accreditation improves the chances of passing licensure exams	0.967	0.967
	15. Accreditation prepares students for success in their chosen careers	0.900
	17. Accreditation promotes active engagement and participation of students in their education	0.864
	19. Accreditation ensures fair assessment practices and provides constructive feedback to students	0.846
	20. Accreditation supports the development of students'skills necessary for their future careers	0.834
	16. Accreditation ensures that the education provided is relevant to the needs of students, society, and the current demands of the job market	0.812
	24. Accreditation is essential for obtaining professional licensure in the field of study	0.803
	27. Accreditation provides students with the necessary knowledge and skills for international licensure	0.719
	26. Accreditation enables students to meet the professional standards required for international licensure	0.717
	18. Accreditation encourages the use of effective teaching methods	0.708
	21. Accreditation provides students with the necessary skills and items for postgraduate studies	0.678
	23. Accreditation supports students in successfully competing for postgraduate opportunities in a global academic community	0.579
Perception of the Impact of University/Program Accreditation on Career Outcomes (PI-ACO)			0.951
Kaiser–Meyer–Olkin (KMO) = 0.929; Bartlett’s test of sphericity P < 0.001; cumulative percentage of variance explained 72.003%
Domain I	1. Accreditation increases the recognition of degrees in the national job market	0.829
	2. Accreditation enhances the reputation and credibility of degrees internationally	0.828
	3. Accreditation enhances the employability of graduates in the national job market	0.820
	4. Accreditation enhances the employability of graduates in the international job market	0.863
	5. Accreditation opens doors to job opportunities both nationally and internationally	0.868
	6. Accreditation provides graduates with the desired skills and items for the national job market	0.839
	7. Accreditation provides graduates with the desired skills and items for the international job market	0.857
	8. Accreditation helps employers recognize the quality of education received by graduates	0.860
	9. Accreditation supports graduates in successfully competing for jobs in a global workforce	0.872

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Reliability measures

The internal consistency of all items and domains was confirmed by measuring Cronbach’s alpha. The overall values of the complete scales were very good (0.839) to excellent (0.981). Further examination within each domain showed values ranging from 0.661 to 0.795 in the RCUP scale and 0.781 to 0.893 in the PUPA scale. The excellent values of 0.967 and 0.969 were recorded for each domain in the PI-AQE and the PI-ACO (Table 2).

Structural validity

All items were significantly correlated with their respective domains, with all P-values < 0.001. All domains were significantly correlated with each other and with the total scales (P < 0.001). Table 3 presents the Pearson correlation analysis. Finally, the mean scores of the four included scales were 38.21 ± 4.26 (RCUP), 50.54 ± 6.96 (PUPA), 117.04 ± 16.06 (PI-AQE), and 38.62 ± 5.75 (PI-ACO).

Table 3.

Pearson correlation analysis between the scales used in the study

	RCUP	PUPA	PI-AQE	PI-ACO
RCUP	-	0.307	0.217	0.165
p-value		< 0.001	< 0.001	< 0.001
PUPA		-	0.695	0.595
p-value		-	< 0.001	< 0.001
PI-AQE			-	0.738
p-value			-	< 0.001
PI-ACO				-
RCUP domains
Domain I: Educational aspects	0.602
p-value	< 0.001
Domain II: Learning experience aspects	0.847
p-value	< 0.001
Domain III: Deontology and career aspects	0.919
p-value	< 0.001
PUPA domains
Domain I: Importance of accreditation		0.835
p-value		< 0.001
Domain II: Communication about accreditation		0.841
p-value		< 0.001
Domain III: Students awareness about accreditation		0.859
p-value		< 0.001
PI-AQE domains
Domain I: Impact on educational quality			0.970
p-value			< 0.001
Domain II: Impact on postgraduation outcomes			0.959
p-value			< 0.001

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RCUP Reasons for Choosing a University/Program, PUPA Perception of University/Program Accreditation, PI-AQE Perception of the Impact of University/Program Accreditation on the Quality of Education, PI-ACO Perception of the Impact of University/Program Accreditation on Career Outcomes

Difference of scores according to participants’ characteristics: Bivariate analysis

In the bivariate analysis, higher means of RCUP scores were notably linked to the profession of being a pharmacist (P < 0.001), having a higher income, and engaging in a field related to one’s university degree (P = 0.038). Additionally, increased scores on the same scale were associated with higher levels of education (P = 0.003), awareness of accreditation, and regular exposure to communication or promotion related to the university (P < 0.001).

Higher means were also detected for PUPA in females (P = 0.06) and were similar between those who affirmed that their university/program was accredited and those who denied it (51.8 ± 6.53 vs.. 51.5 ± 6.76; P < 0.001). The same was also observed in the mean scores of PUPA, where higher scores were associated with awareness of accreditation and regular exposure to communication or promotion related to the university (P < 0.001).

Regarding the influence of PI-AQE score, elevated mean scores were observed among females (P = 0.004), individuals with a higher level of education (P = 0.043), and those in fields of study other than pharmacy (P = 0.01). Additionally, higher mean scores were linked to the affirmation of accreditation and regular exposure to university-related communication or promotion (P < 0.05). Similar trends were noted in the variation of mean scores for the PI-ACO, with the only distinction being a higher score among those who denied accreditation for their university/program. Further details of the bivariate analysis for various scales are presented in Table 4.

Table 4.

Differences in mean scores based on sociodemographic and professional characteristics

Variable	RCUP (mean ± SD)	p-value	PUPA (mean ± SD)	p-value	PI-AQE (mean ± SD)	p-value	PI-ACO (mean ± SD)	p-value
Gender
Male	38.38 ± 4.36	0.03	49.5 ± 7.37	0.002	113.32 ± 17.34	0.0001*	37.5 ± 6.43	0.0009
Female	38.18 ± 4.24	0.03	50.8 ± 6.85	0.002	117.91 ± 15.63	0.0001*	38.9 ± 5.55	0.0009
Marital status
Single/Widowed/Divorced/Separated	38.24 ± 4.22	0.03	50.5 ± 6.95	0.026	116.7 ± 38.57	0.003	38.57 ± 5.78	0.022
Married	37.96 ± 4.73	0.03	51.07 ± 7.1	0.026	120.81 ± 14.41	0.003	39.16 ± 5.38	0.022
Major of study
Pharmacy	38.95 ± 4.12	< 0.001*	50.88 ± 7.14	0.006	115.69 ± 16.4	0.0005*	38.29 ± 5.76	0.003
Others	37.11 ± 4.24	< 0.001*	50.03 ± 6.67	0.006	119.09 ± 15.31	0.0005*	39.13 ± 5.71	0.003
Name of university graduated from/will graduate from
Lebanese University (UL)	35.52 ± 4.83	< 0.001*	49.15 ± 5.46	0.0009*	116.01 ± 15.38	0.0005*	38.55 ± 5.21	0.013
Saint Joseph University (USJ)	38.16 ± 3.39		50.10 ± 6.83		118.87 ± 15.93		39.30 ± 5.41
Lebanese American University (LAU)	38.69 ± 4.34		50.55 ± 7.11		115.25 ± 16.65		38.21 ± 5.76
Beirut Arab University (BAU)	39.18 ± 3.58		51.83 ± 7.99		118.24 ± 16.01		38.54 ± 6.28
Others	38.82 ± 3.36		51.45 ± 6.94		121.81 ± 13.73		39.58 ± 6.1
Income (USD)
< 500	37.39 ± 4.48	0.0009*	49.36 ± 7.06	0.0003*	114.78 ± 17.78	0.004	37.8 ± 6.14	0.002
500 −2000	38.38 ± 4.24		50.46 ± 7.01		117.23 ± 15.74		38.64 ± 5.63
> 2000	38.64 ± 4.02		51.78 ± 6.61		118.75 ± 14.83		39.34 ± 5.53
Current field of work
Same as my university degree as a health professional	38.4 ± 4.16	0.001*	50.51 ± 6.43	0.036	117.79 ± 15.01	0.028	38.33 ± 5.47	0.023
Different from my university degree as a health professional	37.02 ± 4.57		50.02 ± 7.16		117.66 ± 15.92		39.24 ± 5.58
Does not apply since I do not work (student or graduate not working)	38.36 ± 4.23		50.66 ± 7.23		116.48 ± 16.7		38.67 ± 5.94
Place of Employment
I don’t work	38.56 ± 4.13	0.0004*	50.88 ± 7.22	0.010	116.76 ± 16.75	0.010	38.69 ± 5.88	0.010
Lebanon	37.66 ± 4.44		49.86 ± 6.69		116.72 ± 15.21		38.28 ± 5.59
Abroad	39.58 ± 3.51		52.52 ± 5.26		122.94 ± 11.81		39.88 ± 4.56
Remote job	36.15 ± 4.39		50.15 ± 4.99		123.15 ± 13.53		41.07 ± 5.63
How many years did it take to find a job after graduation?
Not applicable	38.39 ± 4.13	0.017	50.70 ± 7.21	0.005	116.81 ± 16.49	0.028	38.75 ± 5.79	0.033
< 1	37.67 ± 4.64		50.40 ± 6.03		118.09 ± 14.09		38.49 ± 5.5
1–3	38.00 ± 4.6		48.52 ± 6.85		115.42 ± 17.3		37.72 ± 5.55
> 3	38.80 ± 2.16		55.6 ± 4.03		123.4 ± 17.11		37.6 ± 9.98
Highest degree earned
Undergraduate	38.55 ± 4.18	0.0001*	50.63 ± 7.33	0.011	116.30 ± 16.87	0.003	38.41 ± 5.87	0.005
Bachelor	37.74 ± 4.26		50.05 ± 6.4		118.49 ± 14.21		39.64 ± 5.29
PharmD/Medical Doctor	38.63 ± 5.31		50.45 ± 5.27		108.36 ± 12.95		37.27 ± 5.93
Masters	36.68 ± 4.31		50.21 ± 5.66		119.39 ± 13.68		38.16 ± 5.64
PhD	40.37 ± 3.85		55.87 ± 5.98		127.12 ± 12.1		41.75 ± 4.09
Years of work experience after graduation
Not applicable	38.37 ± 4.16	0.005	50.74 ± 7.1	0.018	116.81 ± 16.56	0.026	38.76 ± 5.75	0.014
0–2	37.34 ± 4.24		49.57 ± 7.01		116.22 ± 16.04		37.88 ± 6.29
2–5	38.65 ± 4.46		49.57 ± 6.77		118.2 ± 14.01		39.87 ± 4.7
5–7	39.83 ± 2.28		52.66 ± 4.16		124.0 ± 10.23		38.25 ± 5.37
> 7	37.61 ± 5.27		50.84 ± 6.16		118.20 ± 13.75		37.70 ± 5.41
Is your University/Program accredited or attempting to receive accreditation?
No, it is not accredited/attempting to receive accreditation	38.75 ± 3.88	0.001*	51.8 ± 6.53	< 0.001*	117.48 ± 16.84	< 0.001*	39.66 ± 5.3	0.0006
I am not sure whether it is accredited/attempting or not	37.30 ± 4.66		47.44 ± 7.28		111.60 ± 16.21		37.25 ± 5.73
Yes, it is accredited/attempting to receive accreditation	38.38 ± 4.18		51.15 ± 6.76		118.27 ± 15.72		38.84 ± 5.75
Are you aware of the accrediting agency of your University/Program?
No, I am not aware of the accreditation agency	37.01 ± 4.51	< 0.001*	48.76 ± 7.07	< 0.001*	116.14 ± 15.59	0.008	38.17 ± 6.01	0.007
Yes, I am fully aware of the accreditation agency	39.01 ± 4.00		52.25 ± 6.77		118.73 ± 16.07		39.29 ± 5.81
Yes, but I am not entirely sure about the details	38.31 ± 4.19		50.01 ± 6.74		115.71 ± 16.56		38.31 ± 5.47
My University/Program is not accredited/attempting to receive accreditation	38.78 ± 3.23		51.92 ± 5.86		119.71 ± 12.24		37.57 ± 4.51
Have you ever seen or heard any communication or promotion about your university?
No, never	37.046 ± 4.71	< 0.001*	49.05 ± 7.43	< 0.001*	115.83 ± 16.71	0.0007*	38.31 ± 5.69	0.001*
Yes, occasionally	38.58 ± 4.02		50.77 ± 6.51		116.44 ± 15.29		38.35 ± 5.56
Yes, frequently	39.43 ± 4.77		52.71 ± 6.66		120.90 ± 16.39		39.93 ± 6.19

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* Indicates significant p-values based on the Bonferroni corrections p ≤ 0.002

Multivariable analysis

Difference of scores between students and graduates

The means of the scales, compared between students and graduates, were adjusted over age, gender, study major, monthly income, university name, years to find a job, highest degree, accreditation status, awareness of the accrediting agency, and communication or promotion of accreditation. The adjusted means are shown in Fig. 1. No significant difference was found among student or graduate groups for RCUP or PI-AQE. For PUPA, a borderline higher mean was found for students, while for IP-ACO, a significantly higher mean score was found for students compared to graduates (39.26 vs. 36.66, p = 0.015).

Fig. 1 — Adjusted means of accreditation perception scales among students and graduates

Additionally, as shown in Table 5, the MANCOVA models were reported, taking the four scales as the dependent variables and the professional status as the independent variables, adjusted over age, gender, study major, monthly income, university name, years to find a job, highest degree, accreditation status, awareness of the accrediting agency, and communication or promotion of accreditation.

Table 5.

Multivariable analysis of covariance (MANCOVA)

	Beta	P-value		Confidence interval
	Beta	P-value		Lower	Upper
RCUP score correlates
Major of the study (Pharmacy vs. others^a)	2.412		.002	.921	3.904
Income (500–2000$ vs. < 500$^a)	.673		.098	-.125	1.472
Income (> 2000 $ vs. < 500$^a)	.668		.162	-.269	1.605
University (LU vs. others^a)	−3.052		<.001	−4.313	−1.791
University (USJ vs. others^a)	−1.156		.092	−2.502	.189
University (LIU vs. others^a)	−2.773		.002	−4.509	−1.038
University (BAU vs. others^a)	−2.454		.011	−4.337	-.572
Years find a job (< 1 year vs. not applicable^a)	.273		.635	-.856	1.402
Years find a job (1–3 years vs. not applicable^a)	.062		.933	−1.377	1.501
Years find a job (> 3 years vs. not applicable^a)	.969		.610	−2.760	4.698
Highest degree (Bachelor vs. undergraduate^a)	-.249		.684	−1.447	.949
Highest degree (PharmD vs. undergraduate^a)	-.031		.983	−2.800	2.738
Highest degree (Masters vs. undergraduate^a)	-.731		.397	−2.424	.962
Highest degree (PhD vs. undergraduate^a)	1.447		.389	−1.849	4.743
Accreditation status (not sure whether it is accredited/attempting or not vs. No, it is not accredited^a)	-.768		.314	−2.266	.729
Accreditation status (Yes, it is accredited vs. No, it is not accredited^a)	−1.161		.108	−2.575	.254
Aware of the accrediting agency (Yes, I am fully aware vs. no^a)	1.031		.035	.070	1.991
Aware of the accrediting agency (Yes, but I am not entirely sure about the details vs. no^a)	.820		.080	-.099	1.740
Aware of the accrediting agency (University/Program is not accredited vs. no^a)	1.670		.158	-.650	3.991
heard any communication or promotion about your University/Program accreditation status (Yes vs. No^a)	1.097		.004	.359	1.835
Gender (female vs. male^a)	-.090		.831	-.918	.737
Age	-.031		.456	-.112	.050
Professional (Graduate vs. student^a)	.303		.695	−1.818	1.213
PUPA score correlates
Major of the study (Pharmacy vs. others^a)	.275		.827	−2.187	2.736
Income (500–2000$ vs. < 500$^a)	.773		.250	-.545	2.091
Income (> 2000 $ vs. < 500$^a)	1.829		.020	.283	3.375
University (LU vs. others^a)	−1.200		.258	−3.281	.882
University (USJ vs. others^a)	−1.833		.106	−4.054	.388
University (LIU vs. others^a)	−2.389		.102	−5.254	.475
University (BAU vs. others^a)	−1.620		.306	−4.727	1.487
Years find a job (< 1 year vs. not applicable^a)	.172		.856	−1.691	2.035
Years find a job (1–3 years vs. not applicable^a)	−1.013		.403	−3.388	1.363
Years find a job (> 3 years vs. not applicable^a)	5.635		.073	-.520	11.790
Highest degree (Bachelor vs. undergraduate^a)	1.057		.294	-.921	3.034
Highest degree (PharmD vs. undergraduate^a)	.524		.822	−4.047	5.095
Highest degree (Masters vs. undergraduate^a)	1.838		.197	-.956	4.632
Highest degree (PhD vs. undergraduate^a)	6.530		.019	1.090	11.970
Accreditation status (not sure whether it is accredited/attempting or not vs. No, it is not accredited^a)	−4.051		.001	−6.523	−1.579
Accreditation status (Yes, it is accredited vs. No, it is not accredited^a)	−1.824		.126	−4.158	.511
aware of the accrediting agency (Yes, I am fully aware vs. no^a)	2.348		.004	.764	3.933
aware of the accrediting agency (Yes, but I am not entirely sure about the details vs. no^a)	.416		.590	−1.101	1.934
aware of the accrediting agency (University/Program is not accredited vs. no^a)	1.438		.461	−2.392	5.269
heard any communication or promotion about your University/Program accreditation status (Yes vs. No^a)	1.359		.029	.141	2.578
Gender (female vs. male^a)	1.811		.009	.445	3.177
Age	-.007		.920	-.141	.127
Professional (Graduate vs. student^a)	−2.470		.053	-.032	4.972
PI-AQE score correlates
Major of the study (Pharmacy vs. others^a)	−3.922		.181	−9.670	1.825
Income (500–2000$ vs. < 500$^a)	2.304		.142	-.774	5.381
Income (> 2000 $ vs. < 500$^a)	3.777		.040	.167	7.387
University (LU vs. others^a)	−3.344		.177	−8.204	1.517
University (USJ vs. others^a)	−1.944		.462	−7.129	3.241
University (LIU vs. others^a)	−4.295		.208	−10.983	2.394
University (BAU vs. others^a)	−2.129		.565	−9.383	5.126
Years find a job (< 1 year vs. not applicable^a)	-.189		.932	−4.539	4.161
Years find a job (1–3 years vs. not applicable^a)	-.388		.891	−5.934	5.159
Years find a job (> 3 years vs. not applicable^a)	6.446		.379	−7.925	20.817
Highest degree (Bachelor vs. undergraduate^a)	2.796		.235	−1.821	7.412
Highest degree (PharmD vs. undergraduate^a)	−7.168		.188	−17.841	3.504
Highest degree (Masters vs. undergraduate^a)	3.353		.313	−3.170	9.877
Highest degree (PhD vs. undergraduate^a)	11.046		.088	−1.656	23.749
Accreditation status (not sure whether it is accredited/attempting or not vs. No, it is not accredited^a)	−5.532		.060	−11.304	.240
Accreditation status (Yes, it is accredited vs. No, it is not accredited^a)	1.721		.535	−3.730	7.172
aware of the accrediting agency (Yes, I am fully aware vs. no^a)	1.120		.552	−2.580	4.820
aware of the accrediting agency (Yes, but I am not entirely sure about the details vs. no^a)	−2.320		.199	−5.862	1.222
aware of the accrediting agency (University/Program is not accredited vs. no^a)	.181		.968	−8.764	9.125
heard any communication or promotion about your University/Program accreditation status (Yes vs. No^a)	1.004		.489	−1.841	3.849
Gender (female vs. male^a)	4.981		.002	1.791	8.171
Age	.047		.769	-.266	.359
Professional (Graduate vs. student^a)	−4.486		.132	−1.355	10.327
PI-ACO score correlates
Major of the study (Pharmacy vs. others^a)	-.838		.426	−2.907	1.230
Income (500–2000$ vs. < 500$^a)	.869		.124	-.238	1.977
Income (> 2000 $ vs. < 500$^a)	1.406		.034	.107	2.705
University (LU vs. others^a)	-.131		.884	−1.880	1.619
University (USJ vs. others^a)	-.525		.581	−2.391	1.341
University (LIU vs. others^a)	−1.641		.181	−4.048	.767
University (BAU vs. others^a)	−1.477		.267	−4.088	1.133
Years find a job (< 1 year vs. not applicable^a)	-.893		.263	−2.458	.673
Years find a job (1–3 years vs. not applicable^a)	-.807		.428	−2.803	1.189
Years find a job (> 3 years vs. not applicable^a)	−1.148		.663	−6.319	4.024
Highest degree (Bachelor vs. undergraduate^a)	2.557		.003	.896	4.218
Highest degree (PharmD vs. undergraduate^a)	-.693		.723	−4.534	3.148
Highest degree (Masters vs. undergraduate^a)	1.255		.294	−1.093	3.603
Highest degree (PhD vs. undergraduate^a)	4.755		.042	.183	9.326
Accreditation status (not sure whether it is accredited/attempting or not vs. No, it is not accredited^a)	−3.019		.004	−5.096	-.942
Accreditation status (Yes, it is accredited vs. No, it is not accredited^a)	−1.439		.150	−3.401	.523
aware of the accrediting agency (Yes, I am fully aware vs. no^a)	1.285		.059	-.047	2.616
aware of the accrediting agency (Yes, but I am not entirely sure about the details vs. no^a)	-.095		.884	−1.370	1.180
aware of the accrediting agency (University/Program is not accredited vs. no^a)	−2.687		.102	−5.906	.532
heard any communication or promotion about your University/Program accreditation status (Yes vs. No^a)	.235		.652	-.789	1.259
Gender (female vs. male^a)	1.558		.008	.410	2.706
Age	.035		.539	-.077	.148
Professional (Graduate vs. student^a)	−2.608		.015	.506	4.710

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In the global model, the independent variable is the professional status. Covariates are: age, gender, major of the study, monthly income, name of university, years to find a job, highest degree, accreditation status, aware of accrediting agency, communication or promotion about accreditation

^aReference group

Considering the RCUP scale as the dependent variable, the results showed that being a pharmacist (Beta = 2.41), being fully aware of the accrediting agency (Beta = 1.03), hearing any communication or promotion about university/program accreditation status (Beta = 1.09) were significantly associated with higher quality education scores. However, being in UL (Beta = −3.05), LIU (Beta = −2.77), and BAU (Beta = −2.45) was significantly associated with lower RCUP scores.

Taking the PUPA as the dependent variable, the results showed that a higher income (Beta = 1.82), having postgraduate degrees (Beta = 6.53), being aware of the accrediting agency (Beta = 2.34), having heard any communication or promotion of university/program accreditation status (Beta = 1.35), and being a female (Beta = 1.81) were significantly associated with higher perception scores. However, not being sure whether or not the university is accredited/trying to get accredited (Beta = −4.05) was significantly associated with lower PUPA scores.

Considering the impact of PI-AQE as the dependent variable, the results showed that having a high income (Beta = 3.77) and being a female (Beta = 4.98) were significantly associated with higher scores. Regarding PI-ACO, being a graduate (Beta = 2.60), being a female (Beta = 1.55), having a higher income (Beta = 1.40), and holding a bachelor’s (Beta = 2.55) or a Ph.D. (Beta = 4.75) degree as the highest attainment were significantly associated with higher scores. However, being unsure whether or not the university is accredited/attempting to get accredited (Beta = −3.01) was significantly associated with lower scores.

Multivariable analysis of time between graduation and employment (for graduates)

Having graduated from the Lebanese University (Beta = −0.30) or an accredited university (Beta = −0.56), being unsure whether or not the university is accredited/attempting to get accredited (Beta = −0.47), and having more years of experience (Beta = −0.15) were significantly associated with a lower time between graduation and employment (Table 6).

Table 6.

Multivariable linear regression of time between graduation and employment

	Unstandardized Beta	Standardized Beta	p-value	Confidence interval
	Unstandardized Beta	Standardized Beta	p-value	Lower Bound	Upper Bound
RCUP score	.004	.025	.757	-.022	.030
PUPA score	.001	.012	.902	-.021	.024
PI-AQE	.006	.117	.311	-.005	.017
PI-ACO	-.013	-.100	.307	-.038	.012
University (LU vs. others^a)	-.306	-.188	.042	-.602	-.011
University (USJ vs. others^a)	.098	.042	.601	-.273	.469
University (LIU vs. others^a)	.203	.118	.204	-.111	.517
University (BAU vs. others^a)	.113	.044	.584	-.294	.520
Age in years	.016	.165	.130	-.005	.037
Accreditation status of university (not sure vs. Not accredited^a)	-.478	-.277	.045	-.945	-.010
Accreditation status of university (Accredited vs. Not accredited^a)	-.566	-.355	.011	−1.002	-.131
Years of experience	-.150	-.274	.010	-.264	-.036
Monthly household family income	-.067	-.133	.068	-.140	.005

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^aReference group

Discussion

In this study, the content and structure of four scales related to university/program choice, perception of accreditation, and the perceived impact of accreditation on educational quality and career outcomes were appropriately validated. The findings demonstrated robust factorial structures and strong reliability, establishing these scales as effective tools for assessing key factors influencing participants’ choices and career paths within the Lebanese context. The results highlighted the complex interplay among perceptions of accreditation, university characteristics, and individual backgrounds.

Accreditation: a double-edged sword

While a generally positive perception of accreditation (PUPA) and its impact on education quality (PI-AQE) and career outcomes (PI-ACO) was observed amongst participants, the reasons guiding their university choice (RCUP) were surprisingly limited. This limitation may signify that students are choosing universities based on a narrow set of factors, such as geographical proximity, reputation, financial aspects, or influence, rather than a comprehensive evaluation of available programs, specialties, or educational experiences which was reported in similar studies conducted in Italy and Indonesia [56, 57]. This reflects a potential shortcoming in Lebanese universities'ability to differentiate themselves and effectively market their programs.

The analysis revealed that the LU (public university), LIU, and BAU scored lower on the RCUP compared with other private universities. Interestingly, universities that effectively communicated their accredited status seemed to perform better on this novel scale, suggesting a crucial link between transparent communication, institutional reputation, and student choice [37]. Students prefer accredited universities because they anticipate higher satisfaction and better career outcomes, such as rapid integration into the labor market and higher entry-level annual salaries, which was also reported in previous studies in Britain, Colombia, U.S.A., and Cyprus [58–63].

Nuances in pharmacy student decisions

The study uncovered a distinct pattern among pharmacy students. Those who hailed from universities with more varied program options (as indicated by higher RCUP scores) displayed a more nuanced decision-making process when selecting their chosen path. This highlights the effectiveness of the employed scales in capturing the subtle variations within student decision-making, revealing the influence of program diversity beyond the mere presence of accreditation. Understanding these dynamics is crucial for institutions and policymakers seeking to enhance the effectiveness and communication of accreditation processes within the educational landscape.

Demographics and educational background shape perceptions

Significant correlations emerged between demographic and educational factors and their influence on perceptions of accreditation. Participants with higher income levels, those holding Ph.D. or Bachelor's degrees (compared to lower levels of education), and female respondents exhibited more favorable views of accreditation, suggesting that greater exposure to higher education and an understanding of accreditation processes contribute to more positive perceptions. Similarly, studies in Saudi Arabia [64] and Qatar [6] have shown that administrators, faculty members, and students value accreditation, particularly when linked to recognized national or international standards, despite concerns such as increased workload. In this study, participants uncertain about their institution’s accreditation status had lower perceptions of its impact on career outcomes, likely due to a lack of awareness about its importance [61–63]. In Lebanon, private universities with high tuition fees often emphasize their accreditation, which may explain the positive perceptions among higher-income participants. Additionally, the higher proportion of female participants with favorable views on accreditation could reflect broader gender-based differences in valuing quality education, as noted in similar studies, such as one conducted in China [65].

Job search duration: a complex picture

The study's findings on job search duration highlighted several important trends. Graduates from accredited universities, those with substantial work experience, and students from Lebanese University (UL) secured employment more quickly, reflecting the perceived value of accreditation, practical experience, and institutional reputation. Employers often favor these individuals due to their perceived competence and reduced need for extensive training, facilitating their faster integration into the workforce [66].

Notably, UL students, often from lower socioeconomic backgrounds due to the absence of tuition fees, also experienced shorter job search times, possibly due to their willingness to accept lower-paying positions to secure employment quickly. This mirrors trends in other low-wage labor markets in the U.S, where financial necessity drives individuals to accept less favorable job conditions [67]. However, the specifics of the jobs obtained by participants were not explored in this study, underscoring the need for further research into the impact of socioeconomic background on job search strategies and employment outcomes.

Additionally, the generally prolonged job search duration observed in recent years may indicate market saturation or a reduced capacity of healthcare establishments to absorb new graduates. This highlights the need for universities to produce practice-ready, specialized professionals with diverse skill sets to meet evolving market demands, as previously suggested in the literature [44].

Finally, this study is the first one in Lebanon to offer valuable insights into the complex network of factors that shape student decisions and career paths in various health sectors. It emphasizes the significance of program diversity in conjunction with accreditation, the influence of demographics and educational background on perceptions, and the intricate relationships among accreditation, experience, and socioeconomic status in job search outcomes. Furthermore, the study findings were based on the high reliability and validity of the scales employed to evaluate student and graduate perspectives on program accreditation.

Despite the findings of the study, several limitations must be acknowledged. First, the cross-sectional design of the study limits causal interpretations, restricting the ability to infer temporal relationships between accreditation status and perceived educational or career outcomes. Longitudinal studies are warranted to assess how these perceptions evolve over time and their long-term impact on career trajectories.

Second, the use of snowball sampling, although effective in reaching participants across various health-related disciplines, may introduce selection bias. This method relies on initial participants to recruit others, potentially resulting in a sample that is not fully representative of the broader student and graduate population in Lebanon. As such, the findings should be interpreted with caution, particularly when generalizing to students from unrepresented regions or disciplines. Future studies employing probability-based sampling techniques could mitigate this limitation and provide more representative insights.

Third, the reliance on self-reported measures for perceptions of accreditation and educational outcomes may be susceptible to social desirability bias or recall bias. Participants may have provided responses that reflect perceived expectations rather than their true experiences. The incorporation of objective measures, such as academic performance metrics or employment records, in future research would enhance the reliability of the findings.

Lastly, the study's focus on Lebanese universities. Hence, variations in accreditation processes and educational standards across countries may yield different perceptions and outcomes. Future studies across multiple regions would be instrumental in validating the scales and exploring the broader applicability of the findings.

Conclusion

This study aims to enhance the understanding health education quality by developing and validating four comprehensive measurement scales to assess university and program choice, perceptions of accreditation, and its impact on educational quality and career outcomes. The findings revealed that Lebanese students and graduates perceive accreditation as a driver for quicker employment and enhanced career prospects, particularly among those from accredited programs. Socioeconomic factors such as higher income and advanced education were associated with more positive views of accreditation, highlighting its perceived importance in health education. Effective communication about accreditation status was also linked to better-informed university choices, emphasizing the role of transparency in influencing student decisions. These validated scales offer tools for evaluating accreditation's impact and provide insights for institutions and policymakers to enhance communication strategies and support mechanisms. Future research can extend the application of these instruments to diverse contexts, strengthening the understanding of accreditation's role in health professions education.

Supplementary Information

Supplementary Material 1.^{(19.2KB, docx)}

Acknowledgements

Not applicable.

Abbreviations

RCUP: Reasons for Choosing University/ Program
PUPA: Perception of University /Program Accreditation
PI-AQE: Perception of the Impact of University/ Program Accreditation on the Quality of Education
PI-ACO: Perception of the Impact of University/ Program Accreditation on Career Outcomes
MEHE: Ministry of Education and Higher Education
UL: Lebanese University
LIU: Lebanese International University
BAU: Beirut Arab University
USJ: Saint Joseph University
LAU: Lebanese American University
NDU: Notre Dame University-Louaize
MANCOVA: Multivariate Analysis of Covariance
PCA: Principal Component Analysis
KMO: Kaiser–Meyer–Olkin
SD: Standard Deviation
SPSS: Statistical Package for the Social Sciences
INSPECT-LB: Institut National de Santé Publique, d'Épidémiologie Clinique et de Toxicologie-Liban
SDGs: Sustainable Development Goals
QS: Quacquarelli Symonds (University Rankings)

Authors’ contributions

All authors approved the submitted version and have agreed both to be personally accountable for their own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which they were not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature. -DR and DS had role in designing the survey, data acquisition, and writing the manuscript. CH, ST, and SM had role in data analysis, results interpretation, and writing the manuscript. HS was involved in survey validation, writing and editing the manuscript as well as reviewing relevant literature to discuss implications for future research. RA, AH, FS, JS, MA, and RZ were involved in survey validation, data collection, revising the final manuscript. PS made substantial contributions to the conception of the work, interpretation of data, approving and revising the final draft.

Funding

The study did not receive funds or grants from any source.

Data availability

Data is provided within the manuscript or supplementary information files.

Declarations

Ethics approval and consent to participate

Consent for publication

Not applicable.

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.

Deema Rahme and Daniele Saade contributed equally to this work.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1.^{(19.2KB, docx)}

Data Availability Statement

Data is provided within the manuscript or supplementary information files.

[CR1] 1.UNESCO. SDG Resources for Educators - Quality Education. 2023 [Available from: https://en.unesco.org/themes/education/sdgs/material/04.

[CR2] 2.Insights GGI. How to Achieve Quality Education: Strategies for Success. 2023. Available from: https://www.graygroupintl.com/blog/how-to-achieve-quality-education.

[CR3] 3.Abubakar IR. Sustainable University Accreditation and Certification. Springer International Publishing; 2019. p. 1–10.

[CR4] 4.Katoue MG, Somerville SG, Barake R, Scott M. The perceptions of healthcare professionals about accreditation and its impact on quality of healthcare in Kuwait: a qualitative study. J Eval Clin Pract. 2021;27(6):1310–20. [DOI] [PubMed] [Google Scholar]

[CR5] 5.Hussein M, Pavlova M, Ghalwash M, Groot W. The impact of hospital accreditation on the quality of healthcare: a systematic literature review. BMC Health Serv Res. 2021. 10.1186/s12913-021-07097-6. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR6] 6.Wilby KJ, Alamri M, Monfared S. Student and graduate perceptions regarding Canadian-based accreditation of a pharmacy program in Qatar. Am J Pharm Educ. 2019;83(6):6805. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR7] 7.Ibrahim H, Abdel-Razig S, Nair SC. Medical students’ perceptions of international accreditation. Int J Med Educ. 2015;6:121. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR8] 8.Oglesby WH, Hall AG, Valenta AL, Harwood KJ, McCaughey D, Feldman S, et al. Accrediting graduate programs in healthcare quality and safety. Am J Med Qual. 2021;36(6):441–8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR9] 9.Kruk ME, Gage AD, Arsenault C, Jordan K, Leslie HH, Roder-Dewan S, et al. High-quality health systems in the sustainable development goals era: time for a revolution. Lancet Glob Health. 2018;6(11):e1196–252. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR10] 10.Accreditation in the United States. U.S Department of Education; 2023.

[CR11] 11.Hegji A. Institutional Eligibility for Participation in Title IV Student Financial Aid Programs. Congressional Research Service; 2023.

[CR12] 12.Almurayh A, Saeed S, Aldhafferi N, Alqahtani A, Saqib M. Sustainable education quality improvement using academic accreditation: findings from a University in Saudi Arabia. Sustainability. 2022;14(24):16968. [Google Scholar]

[CR13] 13.Iqbal S, Taib CAB, Razalli MR. The effect of accreditation on higher education performance through quality culture mediation: the perceptions of administrative and quality managers. The TQM Journal. 2023;ahead-of-print(ahead-of-print).

[CR14] 14.Frank JR, Taber S, Van Zanten M, Scheele F, Blouin D. The role of accreditation in 21st century health professions education: report of an international consensus group. BMC Med Educ. 2020. 10.1186/s12909-020-02121-5. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR15] 15.Lim KY. A proposal for the future of medical education accreditation in Korea. J Educ Eval Health Prof. 2020;17:32. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR16] 16.Makhoul SA. Higher education accreditation, quality assurance and their impact to teaching and learning enhancement. J Econ Administr Sci. 2019;35(4):235–50. [Google Scholar]

[CR17] 17.Mazzucco W, Silenzi A, Gray M, Vettor R. The accreditation system of Italian medical residency programs: fostering quality and sustainability of the National Health Service. Acta Biomed. 2019;90(9-s):15–20. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR18] 18.Goodman JD. The history of European public health education accreditation in perspective. Southeastern European Journal of Public Health. 2015;3.

[CR19] 19.McLean RA, Blackwell JL, Stoskopf CH. Accreditation across cultures: a case study. J Allied Health. 2006;35(2):121–3. [PubMed] [Google Scholar]

[CR20] 20.Hoffmann A. Joint efforts towards capacity building in international and global health. Public Health Rev. 2022;43:1604688. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR21] 21.Kaissi B, Abou Chahine S, Jammal A, editors. Towards a new higher education quality assurance system for Lebanon. 9th biennial INQAAHE Conference; 2009.

[CR22] 22.Ahmed H, Ahmed M, Siddiek AG. Application of quality assurance & accreditation in the institutes of higher education in the Arab world (descriptive & analytical survey). Am Int J Contemp Res. 2013;3:4. [Google Scholar]

[CR23] 23.Rawabdeh AAA. The Internationalization and globalization of institutional and program accreditation in higher education: quality assurance building pillars: an open manuscript for Jordan. Int J Business Insights Transform. 2017;10:2. [Google Scholar]

[CR24] 24.Ashour S. One or multiple paths to quality assurance of higher education institutions in the United Arab Emirates. Qual High Educ. 2017;23(3):183–200. [Google Scholar]

[CR25] 25.Al-Shehri AM, Al-Alwan I. Accreditation and culture of quality in medical schools in Saudi Arabia. Med Teach. 2013;35(sup1):S8–14. [DOI] [PubMed] [Google Scholar]

[CR26] 26.Mattar MY. Combating academic corruption and enhancing academic integrity through international accreditation standards: the model of Qatar University. J Acad Ethics. 2022;20(2):119–46. [Google Scholar]

[CR27] 27.Addas AN. Challenges in implementing academic accreditation in higher education in Saudi Arabia. J King Abdulaziz Univ. 2018;12:101–16. [Google Scholar]

[CR28] 28.Salam S, Shersad F. the role of accreditation standards in delivering a quality assured program-experience in the UAE. The Online Journal of Quality in Higher Education–October. 2015;2(4).

[CR29] 29.Shaaban I, Khalifa A, Ibrahim D, Al-Shatoury H, El-Gizawy A, Eltalawy H, et al., editors. Quality assurance processes in Egyptian higher education institutions at both institutional and national level: their development and sustainability. 2011. https://www.aneca es/eng/ANECA/Background/Relevant-events/2011/INQAAHE-2011-Conference-in-Madrid.

[CR30] 30.Jaber MA, Al Batsh MW. Jordanian experience in accreditation and quality assurance in HEIs. US-China Foreign Language. 2016;14(4):312–27. [Google Scholar]

[CR31] 31.Albarwani S, Al-Saadoon M, Al-Rawas O, Al-Yaarubi S, Al-Abri R, Al-Lamki L, et al. Accrediting the MD programme in Sultan Qaboos University: process, earned benefits, and lessons learned. Health Professions Educ. 2015;1(1):50–7. [Google Scholar]

[CR32] 32.Saidi MF. Benbouziane PM. Achieving International Competitiveness Through Academic Accreditation: The Case of Qatar University. Revue les cahiers du POIDEX N; 2012. p. 10. [Google Scholar]

[CR33] 33.Alonazi WB. the influence of international education accreditation on a graduate health and hospital program. Int Bus Res. 2018;11(2):170. [Google Scholar]

[CR34] 34.Blouin D, Tekian A, Kamin C, Harris IB. The impact of accreditation on medical schools’ processes. Med Educ. 2018;52(2):182–91. [DOI] [PubMed] [Google Scholar]

[CR35] 35.Pradeep Kumar BS, Don Passey. ImpactofAccreditationonQualityandExcellenceofHEIs.pdf. Revista Investigacion Operacional. 2020;41(2):151–67.

[CR36] 36.Hajj A, Zeenny RM, Akel M, Sacre H, Salameh P. The Lebanese experience for early career development: Bridging the gap to reach the International Pharmaceutical Federation (FIP) Global Competency Framework. Pharm Educ. 2022;22(1):211–20. [Google Scholar]

[CR37] 37.Al-Eyadhy A, Alenezi S. The impact of external academic accreditation of undergraduate medical program on students’ satisfaction. BMC Med Educ. 2021. 10.1186/s12909-021-03003-0. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR38] 38.Nuseir MT, El Refae GA. Factors influencing the choice of studying at UAE universities: an empirical research on the adoption of educational marketing strategies. J Mark High Educ. 2022;32(2):215–37. [Google Scholar]

[CR39] 39.Echchabi A, Al-Hajri S, Tanas IN. Factors influencing Omani students’ selection of higher education institutions: an emphasis on undergraduate and postgraduate students. Int J Educ Econ Dev. 2019;10(4):356–70. [Google Scholar]

[CR40] 40.Hailat KQ, Alsmadi S, Nassar M, Chung SB. An investigation of the push–pull factors influencing student selection of higher education: the case of Arabian Gulf students in the UK. J Public Aff. 2022;22(4):e2657. [Google Scholar]

[CR41] 41.Gameraddin M, Al-Sultan K, Salih S, Gareeballah A, Hasaneen M, Alomaim W, et al. Factors influencing undergraduate students’ preference of health sciences specialties. Adv Med Educ Pract. 2022. 10.2147/AMEP.S377344. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR42] 42.Rauhvargers A. Global university rankings and their impact: Report II: European University Association Brussels; 2013.

[CR43] 43.Galleli B, Teles NEB, Santos JARd, Freitas-Martins MS, Hourneaux Junior F. Sustainability university rankings: a comparative analysis of UI green metric and the times higher education world university rankings. Int J Sustain High Educ. 2022;23(2):404–25. [Google Scholar]

[CR44] 44.Hajj A, Zeenny RM, Sacre H, Akel M, Haddad C, Salameh P. Pharmacy education and workforce: strategic recommendations based on expert consensus in Lebanon. J Pharm Policy Pract. 2023. 10.1186/s40545-022-00510-3. [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR45] 45.Al-Khourry P, Kotob M, El Kader FA, Eido M, Ghandour M. Lebanese students’ awareness regarding accreditation in higher education institutions. Business Educ Accredit. 2014;6(1):23–32. [Google Scholar]

[CR46] 46.Natafgi N, Saliba M, Daya R, El-Jardali F. Integrating quality and patient safety concepts in medical curricula. Baseline assessment in Lebanon. Le J Med libanais Lebanese Med J. 2012;60(2):77–87. [PubMed] [Google Scholar]

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PERMALINK

Perceived effects of accreditation on education quality and health-related job outcomes: scales validation and correlates in Lebanon

Deema Rahme

Daniele Saade

Hala Sacre

Chadia Haddad

Samah Tawil

Samar Merhi

Randa Aoun

Aline Hajj

Fouad Sakr

Jihan Safwan

Marwan Akel

Rony M Zeenny

Pascale Salameh

Abstract

Background

Methods

Results

Conclusion

Supplementary Information

Introduction

Methods

Study design and participant recruitment

Scale development and content validity

Ethics approval

Sample size

Questionnaire

Statistical analysis

Results

Sociodemographic characteristics

Employment characteristics

Sociodemographic and professional characteristics

Table 1.

Scale validation and description

Construct validity and factor analysis

Table 2.

Reliability measures

Structural validity

Table 3.

Difference of scores according to participants’ characteristics: Bivariate analysis

Table 4.

Multivariable analysis

Difference of scores between students and graduates

Fig. 1.

Table 5.

Multivariable analysis of time between graduation and employment (for graduates)

Table 6.

Discussion

Accreditation: a double-edged sword

Nuances in pharmacy student decisions

Demographics and educational background shape perceptions

Job search duration: a complex picture

Conclusion

Supplementary Information

Acknowledgements

Abbreviations

Authors’ contributions

Funding

Data availability

Declarations

Ethics approval and consent to participate

Consent for publication

Competing interests

Footnotes

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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