Psychometric assessment of the persian version of the study anxiety questionnaire in medical sciences students

Abstract

Background

This study aimed to evaluate the psychometric properties of the Persian version of the Study Anxiety Questionnaire (SAQ).

Methods

This methodological study was conducted in 2024 among 380 medical sciences students at Shahroud University of Medical Sciences, Iran. The face and content validity of the questionnaire were assessed using both quantitative and qualitative approaches following a forward-backward translation process. After confirming the adequacy of the sample, explanatory and confirmatory factor analysis was performed. Convergent and discriminant validity were evaluated using the average variance extracted (AVE), maximum shared squared variance (MSV), composite reliability (CR) values and Heterotrait-Monotrait (HTMT) ratio. To determine reliability, internal consistency was assessed using Cronbach’s alpha and Macdonald’s omega coefficients, while stability was measured using the intraclass correlation coefficient.

Results

No items were removed during the content validity phase. The Maximum Likelihood Exploratory Factor Analysis (MLEFA) identified four components of the SAQ (Motivational, Academic anxiety, Cognitive, and Test anxiety) comprising 19 items in total, which collectively accounted for 51.42% of the total variance. The confirmatory factor analysis results indicated a good fit for the 19-item model of the questionnaire. The AVE, CR, and HTMT values indicate acceptable levels of convergent and discriminant validity. The Cronbach’s alpha, Macdonald’s omega, and intraclass correlation coefficients were all within acceptable ranges, indicating strong internal consistency and stability for the Persian version of the SAQ.

Conclusion

The findings of this study suggest that the Persian version of the SAQ possesses sufficient validity and reliability for assessing study anxiety among Iranian medical sciences students.

Background

Anxiety is a psychophysiological issue characterized by feelings of fear and uncertainty, often triggered when an individual perceives an event as a threat to their self or self-esteem [1]. Although some believe that certain levels of anxiety can enhance performance [2], excessive anxiety (manifesting as worry, fear, or restlessness) can lead to negative responses and thought patterns in some individuals [3], which may, in turn, lower their quality of life and overall satisfaction with their circumstances [4]. Students, in particular, encounter new challenges and various levels of anxiety due to individual differences, academic difficulties, and adjusting to an unfamiliar, competitive environment [5]. Studies indicate that nearly half of all students experience anxiety symptoms, with rates increasing in recent years, particularly since the COVID-19 pandemic [6]. Academic anxiety can arise from various sources, such as test anxiety, math anxiety, language anxiety, social anxiety, family-related anxiety, and library anxiety [7], each of which can significantly affect students’ academic and psychosocial motivation and performance [8].

A specific form of anxiety experienced by students is study anxiety [9]. Khuda et al. (2023) categorize study anxiety into two types: social or performance anxiety and test anxiety. Test anxiety occurs temporarily during exams, whereas social or performance anxiety is a persistent concern that may escalate to a phobia and even cause trauma in some students [10]. Study anxiety is not solely caused by low motivation or inadequate study skills but can also stem from topic misunderstandings and negative experiences in previous classes [9]. This anxiety intensifies when students must present assignments in front of others [11], affecting academic performance, hindering academic progress [12], and limiting their ability to plan effectively [13]. Anxious students often struggle with concentration and memory, which are critical for academic success [14], potentially leading to decreased self-confidence [15] and impairing problem-solving and reasoning abilities [16]. Approximately 30% of students exhibit symptoms of anxiety (such as restlessness, negative thinking, and concentration difficulties) especially before exams [17]. Besides psychological symptoms, anxious students experience physiological responses, including increased heart rate, elevated body temperature, sweating [18], rapid, shallow breathing, and nausea [19].

Given the impact of study anxiety, effectively addressing and assessing its levels in students requires a suitable and reliable tool. Several instruments exist, such as the Test Anxiety (TA) scale, which assesses worry over possible negative outcomes or failure in exams but does not account for all aspects of study anxiety [20]; the Study Anxiety Scale for School Students, which is limited to school-aged students [21]; and the Study Anxiety Sources Inventory, which identifies anxiety sources but does not measure anxiety levels [7]. One newer, comprehensive tool is the Study Anxiety Questionnaire (SAQ), which encompasses both academic and emotional dimensions, making it a valuable instrument for evaluating study-related anxiety and related student behaviors. The SAQ can assist students seeking psychological support by highlighting areas of strength and weakness, enabling targeted self-improvement [22]. However, except for the original version, the SAQ has not been psychometrically validated in other countries. Due to the absence of a validated measure for study anxiety in Iran, there is a clear need for a psychometric evaluation of this scale. This study was therefore conducted to determine the validity of the Persian version of the Study Anxiety Questionnaire (SAQ) among medical sciences students.

Methods

Study design and participants

This study is a descriptive cross-sectional and methodological investigation aimed at validating the Persian version of the SAQ among medical sciences students. Data collection took place between June 9th and July 21st, 2024. To meet the objectives of this study and conduct factor analysis, it was determined, based on numerous studies, that 5–10 students should be considered for each item [23]. The adequacy of the sample size in factor analysis depends on factors such as item communality, the number of factors, and factor loadings. Consequently, the required sample size in factor analysis can vary, typically ranging from 3 to 10 per item or 100 to 200 samples [24]. In this study, 380 students from Shahroud University of Medical Sciences were selected through convenience sampling. The inclusion criteria required students to have completed at least one academic semester and to have no history of mental disorders or neuroleptic drug use (as self-reported and diagnosed by a psychiatrist or university psychologist). The exclusion criteria included the occurrence of a stressful event, such as the death of a first-degree family member within the last three months, or the student’s dismissal or transfer to another educational institution, making them inaccessible for the study. Based on these participation criteria, nine students were excluded from the data analysis. Therefore, out of the initial 390 students who entered the study, data from 380 participants were included in the final statistical analysis.

Scale

The SAQ, designed by Casali in 2022, consists of 19 items that assess two key areas: the adequacy of study methods—through an inventory of study skills and behaviors—and the frequency of anxiety symptoms, whether related to exams or daily worries. Items 1–5 address the cognitive aspect, 6–8 focus on the behavioral aspect, 9–11 examine the motivational aspect, and 12–19 pertain to the anxiety aspect. The questionnaire is scored on a 5-point Likert scale, ranging from 1 (“never”) to 5 (“always”), with higher scores indicating greater levels of study anxiety [22]. Before conducting the study, an email was sent to Casali on January 3, 2023, requesting permission to translate and validate the instrument in Persian; this permission was granted on January 23, 2023.

Translation

The tool was translated into Persian using the forward-backward translation technique recommended by the World Health Organization [25]. First, the original version of the SAQ was translated into Persian by two independent translators—one with expertise in psychology and the other a specialist in English language and translation. The translations from both translators were then reviewed by a panel of five experts. After integrating their feedback and combining the two translations, a single Persian version was produced. In the next step, this Persian version was back-translated into English by two independent translators who were unaware of the original text and the purpose of the research. The resulting English versions were reviewed and merged by another panel of experts, creating a single version that was compared to the original instrument. No significant differences were found in the translation of any items. If any discrepancies or ambiguities had arisen at this stage, the translations would have been sent to the original author for clarification to ensure the accuracy of the content. However, there was no intent to delete any items, as doing so might compromise the content validity of the instrument.

Face validity

To assess face validity, 10 medical sciences students were interviewed in person. They were asked to evaluate the tool and its items based on several criteria: appropriateness of appearance, level of difficulty (identifying items that were hard to understand), relevancy (the extent to which the items were appropriate and aligned with the tool’s main purpose), and ambiguity (the potential for misunderstandings or insufficient clarity of the wording). The students were also asked to provide suggestions for improvement.

Additionally, the tool’s suitable was quantitatively evaluated using an impact score based on the students’ responses to a five-point Likert scale (very Suitable = 5, Suitable = 4, somewhat Suitable = 3, slightly Suitable = 2, and not Suitable = 1). The impact score was calculated using the formula: Impact score = Frequency (%) × Suitable. Items that scored higher than 1.5 at this stage were considered relevant and retained. However, items with lower scores were not immediately removed but were subjected to further review [26].

Content validity

The content validity of the questionnaire was assessed using both qualitative and quantitative methods. For the qualitative assessment, 12 experts in psychometrics, medical education, and psychology reviewed the Study Anxiety Questionnaire. They provided suggestions for improvement regarding adherence to writing principles, appropriateness of items, and the correct placement of items. These suggestions were reviewed and discussed by the research team, leading to the necessary modifications to the questionnaire. For the quantitative assessment, the content validity ratio (CVR) and content validity index (CVI) were calculated for each item. The CVR was determined using the formula (CVR = (ne - [N / 2]) / (N / 2)), where N represents the total number of experts, and ne represents the number of experts who deemed the item essential. According to Lawshe’s table, the minimum acceptable CVR value for a panel of 12 experts is 0.56 [27].

The Content Validity Index (CVI) was also assessed based on the experts’ evaluations. Each expert rated all the questions on a scale ranging from “relevant = 1,” “slightly relevant = 2,” “relevant, but needs revision = 3,” to “completely relevant = 4.” The CVI for each item was calculated by dividing the number of experts who gave a rating of 3 or 4 by the total number of experts. Items with a CVI score above 0.79 were considered sufficient. Those with scores between 0.70 and 0.79 were reviewed, while items scoring below 0.70 were deemed unacceptable and removed. The researchers also calculated the Scale-Level Content Validity Index (S-CVI) and the Scale-Level Content Validity Ratio (S-CVR) by averaging the CVI and CVR results. An S-CVI threshold greater than 0.9 was deemed acceptable [28]. Additionally, a modified kappa statistic was calculated for each item to account for chance agreement among the experts, with items scoring 0.70 or higher considered appropriate. The validity index of the entire questionnaire was determined using two methods: Scale-CVI-Average and Scale-CVI/Universal, with 0.9 being regarded as an excellent criterion and 0.8 as the lower acceptable limit for S-CVI [29].

Construct validity

The construct validity of the SAQ was examined using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). To conduct each factor analysis (EFA and CFA), two separate samples of 190 participants each (totaling 380 students) were used. The sample size requirement was determined based on Cattell’s general rule [30]. Construct validity was first assessed with Maximum Likelihood Exploratory Factor Analysis (MLEFA) using Promax rotation on data from one sample of 190 participants. Kaiser-Meyer-Olkin (KMO) and Bartlett tests were employed to assess sampling adequacy. KMO values between 0.7 and 0.8 and 0.8–0.9 were regarded as good and excellent, respectively [31, 32]. Items with factor loadings of approximately 0.33 or greater were deemed to belong to a latent factor, as estimated by the formula: CV = 5.152÷ √ (n – 2), where CV represents the number of extractable factors and n denotes the sample size [33]. Subsequently, items with factor loadings below 0.33 were eliminated from the EFA analysis [34]. Eigenvalues (λ) are the sum of squared factor loadings (SSL) across all items (k) for each factor. This represents the amount of variance in each item that can be explained by the analysis. To calculate the percentage of total variance explained by the factor, the Eigenvalue is divided by the total number of items [35].

In the present study, we conducted a confirmatory factor analysis (CFA) to assess the validity of our measurement model. Following the initial model evaluation, we identified areas for potential improvement based on modification indices. Consequently, we made targeted modification to the model by allowing certain error terms to covary, which enhanced the model fit and provided a more accurate representation of the underlying constructs. The model fit indices were considered acceptable with a root mean square error of approximation (RMSEA) of less than 0.08, a Standardized Root Mean Square Residual (SRMR) below 0.08, a comparative fit index (CFI) greater than 0.9, a parsimonious comparative fit index (PCFI) greater than 0.5, a parsimonious normed fit index (PNFI) below 0.5, an incremental fit index (IFI) greater than 0.9, and a chi-square/degrees of freedom ratio (CMIN/DF) less than 3 [36].

Convergent and discriminant validity

This type of validity was assessed using Average Variance Extracted (AVE), Maximum Shared Squared Variance (MSV), and Composite Reliability (CR). Convergent validity was considered acceptable if the AVE value exceeded 0.5 or if the CR value was greater than 0.7. Additionally, if the AVE was higher than the MSV, the discriminant validity of the tool was confirmed [37]. The mentioned values can be evaluated through the results of the confirmatory factor analysis. Also the study used the Heterotrait-Monotrait Ratio (HTMT) correlation criterion to determine discriminant validity. According to this criterion, the HTMT ratio between all constructs should be less than 0.85 [38].

Reliability

CR was assessed for each factor, with CR values above 0.7 indicating good reliability. To measure the internal consistency of the factors, both Cronbach’s alpha and McDonald’s omega coefficients were calculated, with a threshold of 0.7 considered acceptable. The stability of the SAQ was evaluated using intra-class correlation coefficients (ICC), with a minimum acceptable level set at 0.75 [39]. For this purpose, a sample of 30 students completed the questionnaire twice, with a two-week interval between administrations.

Normality, outliers and missing data

Univariate and multivariate outliers were assessed using distribution charts and Mahalanobis distance (with Mahalanobis distance p < 0.001). Univariate normality was evaluated based on skewness (values within ± 3) and kurtosis (values within ± 7), while multivariate normality was assessed using the Mardia coefficient (values < 8) [40]. For CFA, listwise deletion was employed to handle missing data, as it was preferred over imputation due to the nature of the non-responses, which were primarily linked to incomplete questionnaires. In the present study, a total of 380 responses were analyzed. As the data were collected through online forms, no missing data were encountered. Statistical analyses were conducted using SPSS and AMOS version 26.0.

Results

Among the 380 participants, 244 (64.2%) were female, with most (96.3%) being single. The average age of the students was 21.76 (SD = 1.95) years. About one-third (117 participants) lived with their families, and 78 (20.5%) were nursing students. A detailed summary of participant characteristics is presented in Table 1.

Table 1.

Demographic characteristics of students

Variable		n (%)
Gender	Male	136 (35.8)
	Female	244 (64.2)
Marital status	Single	366 (96.3)
	Married	11 (2.9)
	Divorced	3 (0.8)
Residence status	Dormitory	243 (63.9)
	Rented house	20 (5.3)
	With family	117 (30.8)
		Mean (SD)
Age (per year)		21.76 (1.95)
Interest in field (up to 10)		7.53 (2.21)

n: frequency; %:percent; SD: Standard deviation

Face and content validity

The face validity results indicated that all questionnaire items were deemed appropriate, clear, and important. Additionally, the impact score for each item was above 1.5. In terms of qualitative content validity, revisions were made to some items based on feedback from 12 experts. For quantitative content validity, the CVR and CVI were calculated for each item. With the cut point set at 0.56, no items were excluded. Furthermore, both the Scale-Level Content Validity Index (S-CVI) and Scale-Level Content Validity Ratio (S-CVR) values exceeded 0.9.

Construct validity

The EFA was performed using the maximum likelihood extraction method, yielding a KMO value of 0.867 and a significant Bartlett’s test of sphericity (Chi-square = 2143.403, P < 0.001) (Table 2). Promax rotation identified four factors with eigenvalues greater than one, which together accounted for 51.42% of the total variance (Fig. 1). No items were eliminated from the questionnaire at this stage. There were moderate to strong positive relationships between factor 1 and Factors 2 (0.365) and 3 (0.641), indicating some shared variance and potential interdependencies. However, Factor 1 had a weak positive relationship with factor 4 (0.225), suggesting they are more distinct from each other.

Table 2.

Exploratory Factors analysis of the SAQ (N = 190)

Factors	Qn. Item	Factor Loading	h2	λ	%Variance
Motivational	11. Motivation	0.899	0.764	3.13	16.47
	9. Desire to study	0.794	0.594
	10. Interest	0.770	0.652
	8. Reviewing	0.659	0.441
	7. Organization	0.607	0.427
	6. Schemes	0.554	0.369
Academic anxiety	12. When I’m studying, I think that I might look bad.	0.963	0.776	2.30	12.11
	15. I worry that others will criticize and/or judge me.	0.803	0.712
	16. It is important for me not to disappoint others.	0.578	0.471
	13. I am sure that no matter how much I study, the exam will not go as I want.	0.508	0.436
	14. I tend to feel less prepared than my classmates.	0.369	0.236
Cognitive	2. Reasoning	0.936	0.877	2.58	13.58
	1. Comprehension	0.844	0.720
	3. Elaboration	0.667	0.689
	5. Flexibility	0.434	0.460
	4. Memory	0.394	0.535
Test anxiety	19. In the days leading up to the exam, I feel sad and depressed.	0.803	0.597	1.76	9.24
	18. While studying, I think about what would happen if the exam result is bad.	0.788	0.805
	17. As the exam time approaches, I feel more tense and worried.	0.704	0.614

Abbreviations: h²: Item Communalities, λ: Eigenvalue

Fig. 1.

Scree plot for factors through exploratory factor analysis of SAQ

Confirmatory factor analysis

The CFA findings indicated that all goodness-of-fit indices supported the final model (χ² = 319.348, DF = 145, P < 0.001, CMIN/DF = 2.202, PCFI = 0.769, PNFI = 0.716, RMSEA = 0.080 (90% CI: 0.068 to 0.092), SRMR = 0.07, IFI = 0.908, CFI = 0.907, NFI = 0.844, TLI = 0.890) (Fig. 2).

Fig. 2.

The final model of the SAQ based on CFA (N = 190)

Convergent and discriminant validity

To evaluate convergent validity, the CR values for all factors were above 0.7, and the AVE values for all factors (except Academic Anxiety) exceeded 0.5. The AVE value for academic anxiety factor was slightly below this benchmark, at 0.461 (Table 3). AVE is a robust indicator of convergent validity. Additionally, in behavioral studies, a CR above 0.7 alone can substantiate convergent validity. Based on CR and MaxR results, convergent validity was confirmed for all four factors. Furthermore, since AVE was higher than the MSV across all factors (except academic anxiety), discriminant validity was established for the motivational, cognitive, and test anxiety factors. In terms of discriminant validity, the results of the HTMT ratio were below 0.85, showing good discriminant validity for all factors (Table 4).

Table 3.

Convergent and discriminant validity, and reliability of the Persian version of the SAQ

	CR	AVE	MSV	MaxR (H)	α	Ω	ICC
Motivational	0.857	0.511	0.361	0.916	0.868	0.859	0.835
Academic anxiety	0.803	0.461	0.614	0.849	0.800	0.804	0.788
Cognitive	0.847	0.533	0.361	0.878	0.862	0.866	0.859
Test anxiety	0.854	0.661	0.614	0.855	0.850	0.850	0.895

SAQ: Study Anxiety Questionnaire; CR: Composite Reliability; AVE: Average Variance Extracted; MSV: Maximum Shared Squared Variance; α: Cronbach’s alpha; Ω: McDonald’s omega; ICC: Intraclass Correlation Coefficients

Table 4.

Discriminant validity assessment using the HTMT criterion

	Motivational	Academic anxiety	Cognitive	Test anxiety
Motivational
Academic anxiety	0.465
Cognitive	0.715	0.587
Test anxiety	0.405	0.816	0.529

Reliability

The four factors extracted from the SAQ showed acceptable reliability, as indicated by Cronbach’s alpha, McDonald’s omega, and the ICC (Table 3). The overall ICC and Cronbach’s alpha coefficients for the questionnaire were 0.813 (95% CI: 0.591to 0.914) and 0.732, respectively. Furthermore, a CR value above 0.7 confirmed the structure’s reliability.

Discussion

Based on the results of the present study, MLEFA findings showed that SAQ consists of four factors: motivational, academic anxiety, cognitive, and test anxiety. In general, 19 items of this questionnaire predict 51.42% of the total variance. This questionnaire was designed by Casali in 2022 to measure anxiety symptoms related to studying in students. The original version of SAQ contains 19 items, which is a questionnaire tool consisting of four factors: cognitive, behavioral, motivational and anxiety. This questionnaire has not been psychometrically evaluated in other cultures [22].

The first factor extracted in the Persian version of the SAQ was the motivational factor, consisting of six items primarily reflecting a student’s motivation, desire, and interest in studying, as well as their planning and prioritization of courses. This factor explained the highest percentage of anxiety and highlighted its importance in evaluating anxiety symptoms related to studying. It is generally associated with measuring willingness, interest, and motivation to study, aligning with the corresponding factor in the original version [22]. Motivation reflects how much a student is willing to invest in studying and their approach to overcoming challenges. Assessing the motivational component includes examining how anxiety influences a student’s reasons for studying and their persistence when facing academic challenges [41]. According to previous research, students’ cognitive and behavioral strategies, along with their motivation to learn, are associated with academic success [42]. Casali et al. (2022) identified Motivational as one of the factors in the original SAQ, consistent with the findings of this study [22]. Experiencing certain levels of anxiety may be connected to a student’s motivation to perform well, especially in demanding fields like medical sciences. This dynamic may contribute to a concept known as “motivational anxiety,” where anxiety experienced by students is not purely detrimental but may instead encourage engagement and focus, particularly when students feel pressure to meet expectations or demonstrate competence. This factor suggests that while students may feel anxious, this anxiety could partly stem from their strong desire to succeed academically [43, 44].

The second factor identified in the current version was the academic anxiety factor, comprising five items. These items primarily capture students’ concerns about being criticized, appearing inadequate to others, and perceptions of others—such as classmates and surrounding people—based on their academic performance. In the original version of the questionnaire, all items related to this factor were grouped under the broader label of “Anxiety” [22]. Academic anxiety encompasses feelings of worry, tension, or fear associated with academic contexts or tasks, such as exams, assignments, and social pressures from parents or peers [45]. Research indicates that academic anxiety can negatively impact academic achievement [46].

The third well-established factor is the cognitive factor, consisting of five items that primarily assess reasoning skills, flexibility, comprehension, and a detailed description of the student’s memory status. This factor corresponds directly to the cognitive factor in the original version of the questionnaire [22]. Additionally, dimensions related to cognition are frequently used in similar instruments to assess anxiety [21, 47, 48]. Cognitive status is therefore an important component in predicting symptoms associated with study anxiety. Cognitive performance plays a critical role in the assessment of study anxiety in students, as it directly influences how they perceive, process, and respond to academic stress. Cognitive functions—including attention, memory, reasoning, and problem-solving abilities—are integral to academic performance [49]. Within the context of study anxiety, cognitive functioning determines how students interpret academic challenges, such as exams or assignments. Students experiencing higher levels of anxiety may encounter cognitive distortions, such as overestimating task difficulty or underestimating their ability to succeed. Such distorted thinking can disrupt cognitive functions, leading to difficulties in concentration, memory recall, and decision-making, which in turn can intensify anxiety [50].

The final factor is test anxiety. The items in this factor primarily assess symptoms of anxiety that students experience before an exam, along with concerns about potential negative outcomes. Symptoms of test anxiety range from mild worry to intense, debilitating anxiety. While a low level of test anxiety can motivate students to study and prepare, severe test anxiety can disrupt physiological and psychological functioning, or both [51]. In medical sciences, assessing and managing test anxiety is especially important. Due to the nature and objectives of medical sciences, students are evaluated not only in cognitive and emotional domains but also in psychomotor skills through various methods, such as the Objective Structured Clinical Exam (OSCE) [52].

Based on the results of the present study, all fit indices in the confirmatory factor analysis for the four factors—Motivational, Academic Anxiety, Cognitive, and Test Anxiety—were within the acceptable range, indicating that the proposed model for the questionnaire had a good fit with the data. Consistent with these findings, Casali et al. (2022) found that the four-factor model comprising Cognitive, Behavioral, Motivational, and Anxiety factors in the original version of the SAQ also showed a good fit [22]. To date, no other studies have psychometrically evaluated this questionnaire; however, other instruments measuring study-related anxiety are available. For example, Lowe (2018) reported that the construct validity of the Test Anxiety Measure for College Students (TAM-C) was confirmed through confirmatory factor analysis, aligning with the present results [53]. Additionally, the short version of TAM-C, which includes a six-factor structure (covering social concerns, cognitive interference, worry, physiological hyperarousal, task-irrelevant behaviors, and facilitating anxiety), also demonstrated a good fit [47]. Similarly, Mowbray et al. (2015) found that the proposed model of the 17-item German Test Anxiety Inventory (TAI-G) had an acceptable goodness of fit in CFA [54]. Another tool developed in 2011 by Vitasari et al., designed to identify sources of study anxiety, also showed favorable confirmatory factor analysis results [7]. In Pakistan, a similar tool called the “Study Anxiety Scale” was developed; however, this scale did not use confirmatory factor analysis during its validation stages [21].

The results of the present study indicate that the SAQ items demonstrate good discriminant validity (except academic anxiety factor) and convergent validity for all factors. The original SAQ version was also evaluated for these validity aspects. Convergent validity results revealed a significant moderate correlation between the three subscales related to study methods—cognitive and behavioral aspects and motivation—and the measure of self-regulation strategies. Additionally, the “anxiety” subscale of the SAQ exhibited a strong significant correlation with the Cognitive Behavioral Assessment-Outcome Evaluation (CBA-OE) anxiety measure. The negative correlation between the cognitive component and the anxiety measure supports the discriminant validity of the SAQ [22]. In similar studies, convergent validity has been confirmed using measures of trait anxiety, test anxiety, and academic performance [20]. Furthermore, Mowbray et al. (2015) confirmed the convergent validity of the German Test Anxiety Inventory (TAI-G), demonstrating a significant correlation between TAI-G scores and self-esteem, self-efficacy, and general anxiety scores [54]. Other similar instruments have also confirmed both convergent and discriminant validity [47, 53]. While the current study’s results align with those of previous studies, it is notable that none of the previous studies utilized Fornell and Larcker’s approach to assess the psychometrics of the Persian version of the SAQ. This approach represents a strength of the present study.

In the present study, Cronbach’s alpha and Macdonald’s omega coefficients were found to be at acceptable levels, indicating favorable internal consistency for the Persian version of the SAQ. CFA also evaluated the scale’s CR, and since CR was above 0.7 for all factors, it confirmed the structural reliability of the instrument. An advantage of measuring CR is that it is not influenced by the number of scale items or sample size [55]. Consistent with these findings, the original version of the SAQ demonstrated acceptable reliability, with Cronbach’s alpha coefficients for its subscales ranging from 0.74 to 0.87 [22]. Similar instruments have shown comparable internal consistency. For instance, Vitasari et al. (2011) reported an acceptable internal consistency for their study anxiety sources instrument, with a Cronbach’s alpha coefficient of 0.897 [7]. Other studies have also confirmed the acceptable internal consistency of similar instruments [20, 48, 56]. Notably, the current study also utilized McDonald’s omega coefficient and composite reliability, which were not employed in previous studies.

The stability of the SAQ was assessed using test/retest analysis, which revealed a significant correlation between the first and second evaluations. This result confirms the good reproducibility of the SAQ and indicates that the Persian version has acceptable stability, as reflected by the ICCs. Specifically, all subscales demonstrated ICC values ranging from 0.788 to 0.895, suggesting acceptable stability. While measurement consistency for the original SAQ was not reported [22], previous studies have shown stability in similar measurement tools [21, 48, 56].

The Persian version of the SAQ retains all 19 items from the original version, as no items were removed. Consequently, the total score ranges from 19 to 95, with higher scores indicating greater levels of anxiety symptoms among students. The Persian SAQ includes four factors: test anxiety (three items), cognitive (five items), and academic anxiety (five items), and motivational (six items).

The study has limitations, including potential bias due to self-reported data. A substantial number of participants resided in student dormitories, which may also influence the findings. Additionally, the findings are specific to Iranian culture and society. Therefore, to apply this questionnaire in other cultural contexts, further psychometric evaluation would be necessary.

The Persian version of the SAQ is a flexible tool that can be utilized in both educational and clinical settings to assess study anxiety, helping identify study anxiety symptoms and enabling targeted interventions for medical sciences students. Its comprehensive four-factor structure provides valuable insights into both the debilitating and motivational aspects of study anxiety. Additionally, the SAQ is suitable for large-scale use due to its brevity, ease of administration, and simple scoring system, making it an ideal choice for researchers, educators, and counselors. However, although the questionnaire has been psychometrically validated within the Iranian context, further validation in diverse cultural and educational settings is recommended to ensure its broader applicability.

Conclusions

According to the findings of the current study, the SAQ for medical sciences students consists of 19 items and four factors. This scale demonstrates acceptable validity, reliability, and stability for assessing study anxiety among the Iranian medical sciences students.

Abbreviations

CVR

Content validity ratio

CVI

Content validity index

EFA

Exploratory factor analysis

CFA

Confirmatory factor analysis

MLEFA

Maximum likelihood exploratory factor analysis

KMO

Kaiser-meyer-olkin

RMSEA

Root mean square of error of approximation

CFI

Comparative fit index

TLI

Tucker lewis index

PNFI

Parsimonious normed fit index

IFI

Incremental fit index

ICC

Intra-class correlation coefficient

PCFI

Parsimony comparative fit index

AVE

Average extracted variance

MSV

Maximum shared squared variance

CR

Composite reliability

SRMR

Standardized root mean square residual

HTMT

Heterotrait-monotrait

NFI

Normed fit index

COPE

Committee on publication ethics

S-CVI

Scale content validity index

S-CVR

Scale content validity ratio

SAQ

Study anxiety questionnaire

OSCE

Objective structured clinical exam

TEAM

Test and examination anxiety measure

TAI-G

German test anxiety inventory

TAM-C

Test anxiety measure for college students: cba-oe: cognitive behavioral assessment-outcome evaluation

Author contributions

Study design: S. M., M. K., H. E.; Data collection: S. M., F. A., H. R., G. F., Data analysis: S. M., H.S., Study supervision: S. M., M. K.; Manuscript writing: All authors (S. M., F. A., H. R., H.S., G. F., M. K., H. E.). All authors have read and approved the final manuscript.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Data availability

The dataset(s) supporting the conclusions of this article is(are) included within the article (and its additional file(s)).

Declarations

Ethics approval and consent to participate

This study was carried out in compliance with the principles of the Declaration of Helsinki and was approved by the Ethics Council for Biomedical Research at Shahroud University of Medical Sciences (Approval Number: IR.SHMU.REC.1402.033). Prior to the study’s commencement, participants were thoroughly informed about its objectives and the terms of their involvement. Written informed consent was obtained from each participant. The authors adhered to the guidelines of the Committee on Publication Ethics (COPE) in disseminating their findings.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.