Individuals with disabilities are highly susceptible to how others perceive them. This is particularly true in the context of qualified medical professionals, who are critical in delivering healthcare to individuals with disabilities (Frank, 2016). To navigate the many challenges in their daily lives, people with disabilities often depend on medical professionals. For this reason, they are vulnerable to the attitudes and reactions of healthcare providers (Bania et al., 2020). To alleviate the psychological stress experienced by people with disabilities, healthcare workers must offer comfort and reassurance (Bania et al., 2020).
According to Bania et al. (2020), a healthcare professional’s negative attitude toward patients with disabilities can significantly harm them. Such attitudes may lead to serious consequences, including impaired access to necessary therapeutic or preventive services (Subramaniam & Villeneuve, 2020), diminished self-worth (Frank, 2016), reduced quality of life, and loss of self-reliance (Bania et al., 2020; Frank, 2016). For example, some individuals with disabilities may begin a course of treatment but discontinue it prematurely, believing it will yield little or no benefit (Bania et al., 2020; Frank, 2016). Until recently, most instruments used to assess the perspectives of medical professionals and students concerning disabilities were adapted from scales initially designed to measure public attitudes (Karam et al., 2024). Furthermore, several psychometric tools in this context have demonstrated poor internal consistency and a lack of test-retest reliability (Gething & Wheeler, 1992; Wallymahmed et al., 2007). Indeed, the Mental Retardation Misconceptions Scale (Antonak, 1982; Antonak & Livneh, 1988) and the Scale of Attitudes Toward Disabled Persons (Antonak, 1982) were found to exhibit weak internal consistency and limited stability over time (Wallymahmed et al., 2007).
In response to these limitations, several more promising instruments have been developed. Among the most widely used is the Interaction with Disabled Persons (IDP) Scale, developed in Australia (Gething, 1991; Gething & Wheeler, 1992; Wallymahmed et al., 2007). This scale addressed prior methodological shortcomings, including using unidimensional constructs to measure complex, multidimensional phenomena and outdated or inappropriate terminology (e.g., failure to adopt person-first language). These deficiencies, particularly the reliance on unidimensional models, are inconsistent with contemporary research emphasizing the multidimensional nature of attitudes toward disabilities (Antonak & Livneh, 1988; Iacono et al., 2009).
Gething (1992) also reported considerable missing data in responses to items on the Attitude Toward Disabled Persons Scale, citing respondent refusals and, in some cases, aggressive responses to specific items. In contrast, the IDP has demonstrated solid psychometric properties. During the IDP standardization project, 6,000 cases representing a cross-section of the Australian population were collected between 1988 and 1990 (Gething, 1994). Across fifteen administrations, Cronbach’s alpha values—a measure of internal consistency—ranged from 0.74 to 0.86.
Gething (1991) employed exploratory factor analyses, including varimax rotation and principal component analysis, which yielded five- and six-factor models with eigenvalues equal to or greater than 1.00 (Gething, 1994; Wallymahmed et al., 2007). These studies provided strong evidence of construct, factorial, and content validity in both the original Australian-English version and international adaptations (Bania et al., 2019; Bania et al., 2020; Gething & Wheeler, 1992; Iacono et al., 2009; Thomas, 2003; Wallymahmed et al., 2007). The internal consistency of the IDP typically ranges from 0.74 to 0.86 (Gething, 1991; Iacono et al., 2009).
Gething (1992) and Gething and Wheeler (1992) identified five to six factors in the IDP using exploratory and principal components analyses supported by varimax rotation. These factors accounted for 53% to 79% of the variance across 12 separate samples. Subsequent analyses using maximum likelihood estimation and oblique rotation confirmed the presence of six components, which were considered robust due to the replication of results across multiple datasets. Several researchers—including Bania et al. (2020), Forlin et al. (1999), and Iacono et al. (2009)—have successfully replicated this sixfactor structure.
Table 1 Comparison of the IDP factor solution derived in this study with 12 other studies Although the above studies report various factors, there remains a clear need for additional research—both in native English-speaking countries and internationally—concerning the uni dimensionality issue of the IDP scale. For example, Bania et al. (2019) note that only four studies (Bania et al., 2019; Bania et al., 2020) have examined participants from six European countries, including Greece. Substantial work remains to be done to evaluate the most widely used instruments designed to measure the attitudes of healthcare professionals toward individuals with disabilities. Moreover, comprehensive information regarding the psychometric properties of international adaptations of these scales is lacking.
| Study | # of Factors | Factor One Items | Factor Two Items | Factor Three Items | Factor Four Items | Factor Five Items | Factor Six Items |
|---|---|---|---|---|---|---|---|
| Gething (1994) | 6 | 9,11,12,16,17,18 | 1,2,3,13 | 3,6,9,10,12 | 7,20 | 1,4,15 | 4,5 |
| MacLean & Gannon (1995) | 2 | 9,11,12,17,18 | 1,2,3,5,13 | ||||
| Forlin et al. (1999) | 6 | 11,16,17,18 | 1,2,3,13 | 3,6,9,12 | 7,20 | 1,4,15 | 4,5 |
| Tait & Purdie (2000) – First findings | 2 | 9,11,12,17,18 | 1,2,3,5,13 | ||||
| Tait & Purdie (2000) – Second findings | 4 | 6,8,9,12 | 1,2,10,13,15 | 16,17,18 | 4,5,7,20 | ||
| Yoshida et al. (2003) | 5 | 9,11,12,16,17,18 | 1,2,3 | 6,10 | 4,5 | 14,15 | |
| Thomas et al. (2003) | 3 | 9,12,16,17,18 | 1,2,3,13,15 | 5,7,14,20 | |||
| Wallymahmed et al. (2007) | 5 | 9,11,16,17,18 | 2,3,4,6 | 7,13,20 | 1,4,15,16,19 | 10,14,15 | 7,20 |
| Locono et al. (2009) – Two rounds | 6 | 9,11,12,16,17,18 | 1,2,8,13,15 | 1,4,15,16,19 | 16,9 | 2,3,4,5,7,20 | 2,14 |
| Bania et al. (2019) | 4 | 6,9,11,12,16,17,18 | 2,4,5,7 | 10,14,15 | 1,13,16,9 | ||
| Bania et al. (2020) | 6 | 9,11,16,17,18 | 1,4,15 | 7,20 | 1,6,10 | 2,3 | 4,5,13 |
| Robert Loo (2001) | 6,2 | Findings do not support a six-factor or a two-factor solution | |||||
| Lobato et al. (2021) | 2 | 9,11,12,17 | 1,2,4,13 | ||||
Notably, no previous study has evaluated the psychometric properties of Arabic versions of these instruments among healthcare professionals. Few investigations have explored how Arab medical and healthcare students perceive individuals with disabilities. These include a survey by Alabdulwahab and Al-Gain (2003) conducted with 130 Saudi Arabian healthcare professionals and a more recent study by Jelleli et al. (2022) examining attitudes toward intellectual disability. However, although both studies assess attitudes, neither evaluates the psychometric soundness of the scales employed within the Arabic language and cultural context.
Therefore, it is essential to assess the construct validity and reliability of the IDP—a widely used instrument—using a diverse sample of qualified healthcare professionals and preclinical medical students soon to enter their careers’ professional phase. Investigating the Arabic version of the IDP scale addresses a significant gap in the literature, as no prior study has examined how Arabic-speaking healthcare professionals view individuals with disabilities.
The present study has two primary objectives: (1) to translate the IDP scale into Arabic and adapt it to Arab cultural norms, and (2) to evaluate its psychometric properties among a sample of Arab physicians and medical students, considering previously reported structural concerns. These issues underscore the need for continued research into the IDP’s dimensional structure to determine the number of underlying factors and the composition of its subscales.
2. Method
2.1. Instrument translation
The IDP scale was initially translated from English into Arabic, followed by a back-translation into English. Two multilingual translators, fluent in both languages, performed the translation and back-translation conceptually rather than literally. They reviewed and compared the original and back-translated versions, reaching a consensus on each sentence to ensure consistency across items. Subsequently, a panel of multilingual professors—highly proficient in English and of Arab origin—examined the translation to verify its linguistic and cultural appropriateness. The Arabic version of the IDP was then administered to 172 respondents, comprising medical doctors and healthcare students.
2.2. Participants and procedures
After obtaining ethical approval No, (…………) from the Standing Committee for Bioethics Research (SCBR) at (…………) to conduct the study, data were electronically gathered via an online survey using a convenience sampling technique. The doctors and preclinical students who participated in this study are Arabic-speaking individuals situated in the northern (…………) metropolitan area. As part of the validation procedure, medical professionals who worked with people with disabilities were given the Arabic version of the IDP scale. To be eligible for the study, medical professionals had to be native Arabic speakers who could understand and complete the IDP scale. They were also required to have at least three months of experience working with individuals with disabilities.
Furthermore, the medical student participants had to be enrolled in medical school at the time of the survey. All participants were asked at the beginning of the study whether they had any prior experience working with or interacting with individuals with disabilities. On the survey’s home webpage, each participant was asked to give informed consent to participate in the study voluntarily. The data obtained from the Arabic IDP scale in this study were gathered from the University of (…………) and four public and university hospitals in the (…………) region, located in the northern part of (…………) in (…………).
2.3. Measures
The Community Disability and Ageing Programme developed a validated Australian tool known as the IDP (Gething, 1992). The IDP is used to evaluate personal attitudes and perceptions toward individuals with disabilities, highlighting those that are considered harmful, and it is also used to examine how people respond to previous interactions with individuals with disabilities (Gething, 1992; Gething & Wheeler, 1992). In theory, the basis of the IDP is the idea that negative attitudes are indicative of distance and unfamiliarity, which in turn cause anxiety and uncertainty. Feelings of ignorance and uncertainty regarding how to treat and interact with individuals with disabilities have been linked to this unfamiliarity or uneasiness.
The psychometric properties of the original English-Australian version of the IDP scale are good. The instrument comprises 20 items, to which responses are made on a six-point scale, with options ranging from ‘very much disagree’ to ‘very much agree.’ According to Gething (1992), Gething and Wheeler (1992), and Thomas et al. (2003), an unfavorable attitude towards individuals with disabilities is indicated by a high IDP score, while low scores indicate a positive attitude. However, Gething (1994) removed items 8 and 19 from the original IDP scale due to the frequently mentioned issues associated with these items. A 5-point scale, with ‘not sure’ as the middle point, was used instead of the 6-point response scale. The responses on the 5-point scale range from ‘strongly agree’ to ‘strongly disagree.’ This later adaptation was incorporated into this study.
2.4. Statistical analysis
2.4.1. Factorial validity
Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were performed to examine the construct validity of the IDP scale and, specifically, the model fit. The Statistical Package for Social Sciences version 25 and the Analysis of Moment Structures version 25 were used for the EFA and CFA, respectively. First, the underlying factors or constructs of the set of 20 attitude questions in the IDP were identified using exploratory factor analysis (EFA), allowing us to validate the factor structure of the IDP. A set of items with similar response patterns is a factor when developing a construct. The structure of the emerging factor should support our presumptions about the connections between the elements in each of our proposed constructs.
Two techniques are used to assess construct validity in EFA: the first technique involves determining the number of factors that underpin a set of variables (e.g., questions in a questionnaire), and the second consists of verifying whether the factors are uncorrelated (DiStefano & Morgan, 2021, as cited in Abd ElHafeez et al., 2022).
Before performing the EFA, we used Bartlett’s test of sphericity and the Kaiser–Meyer–Olkin (KMO) test to evaluate factorability. The KMO index is a statistical measure used to assess sample adequacy, with high levels of factor analysis adequacy indicated by values close to 1 (KMO ≥ 0.6: low sample adequacy, KMO ≥ 0.7: medium sample adequacy, KMO ≥ 0.8: high sample adequacy, and KMO ≥ 0.9: extremely high sample adequacy). Bartlett’s test of sphericity was used to determine whether variables in an identity matrix are correlated (Bartlett, 1954). A significant p-value (e.g., p < 0.05) indicates appropriate factorial analysis.
For the EFA, the factor loadings for each question item were calculated using the maximum likelihood extraction approach and direct noblemen rotation (Coughlin, 2013). The number of factors to retain (i.e., the number of factors that account for most of the variation of the original observed variables) was then determined by using three different approaches: a scree plot graph, parallel analysis, and the eigenvalue > 1 criterion. Each factor’s total squared factor loadings were divided by the number of variables to determine the eigenvalue. The eigenvalue indicates the extent to which the entire sample’s variation is explained by each factor. Eigenvalues greater than 1 indicate that a factor is significant. The number of elements to retain is indicated by the data point in the scree plot graph, located above the point of inflection, where the eigenvalues are plotted against the factors (Coughlin, 2013).
Abd ElHafeez et al. (2022) stating that a unique factor is associated with items that have significant factor loadings (a cut-off value of 0.40). Because items with factor loadings below 0.40 account for less than 10% of the variation in the latent construct under examination, they are deemed insufficient. Consequently, items with factor loadings of 0.40 or above are often recommended for retention. Additionally, items should not load onto multiple components.
Finally, fewer questionnaire questions for a construct is achieved by excising items that appear to load non-uniquely on just one factor or that cross-load.
CFA was used to evaluate the model’s fit yielded by the EFA. The factor structure of the IDP, as determined by exploratory factor analysis (EFA), was verified using confirmatory factor analysis (CFA). The factor analysis results were then compared to previous studies to determine the optimal number of factors to retain. To examine the model’s goodness of fit, the following metrics were measured as part of the analysis: chi-square or standard deviation (χ2/SD), standardized root mean square residual (SRMR), Tucker–Lewis index (TLI), the goodness of fit index (GFI), root mean square error of approximation (RMSEA), and adjusted goodness of fit index. Lastly, Cronbach’s alpha test was used to assess the internal consistency reliability of the IDP scale (Hooper et al., 2008).
The standardized estimates, residual moments, and modification indices were considered for evaluating the model fit. The average convergent validity was also assessed using the average variance extracted (AVE). According to Fornell and Larcker (1981), a rule of thumb for adequate convergent validity is that the AVE value must be greater than 0.5. Furthermore, Pearson’s correlation coefficient analysis was run to calculate the level of agreement between two or more factors. Pearson’s correlation coefficients were used to ascertain whether the factors were linked.
3. Results
As Table 2 shows, one hundred and seventy-two individuals were recruited from the University of (…………) and four public university hospitals in (…………) region to participate in this study. The mean and standard deviation for the Arabic IDP were found to be as follows: M = 3.106 and SD = 0.587. The approximation rate to the maximum scores was relatively high, at 62%, indicating that the participants generally demonstrated a positive interaction. One hundred eleven participants were male (64.5%), while 61 were female (35.5%). The participants comprised 57.6% of medical doctors and 42.4% of medical students.
| Variable | Level | N | % | Total |
|---|---|---|---|---|
| Entire Sample | Men | 111 | 64.5% | 172 |
| Women | 61 | 35.5% | ||
| Doctor’s Gender | Men | 63 | 61.6% | 99 |
| Women | 36 | 37.4% | ||
| Age (Doctors) | Under 30 years | 11 | 11.1% | 99 |
| 30–40 years | 23 | 23.2% | ||
| Over 40 years | 65 | 65.7% | ||
| Years of Experience | 5 years or less | 10 | 10.1% | 99 |
| More than 5 years | 89 | 89.9% | ||
| Students’ Gender | Men | 48 | 65.7% | 73 |
| Women | 25 | 34.2% | ||
| Age (Students) | Under 20 years | 14 | 19.2% | 73 |
| 20–30 years | 59 | 80.8% | ||
| 30–40 years | 0 | 0% | ||
| Over 41 years | 0 | 0% | ||
| Total Number of Participants | 172 | |||
3.1. Internal consistency
Table 3 presents the mean values, standard deviations, score range, and Cronbach’s alpha values for the sympathy and discomfort factors.
| Scale / Factor | Items | Mean (x̄) | Standard Deviation (σ) | Cronbach’s α | α if Item Deleted |
|---|---|---|---|---|---|
| IDP (Total) | — | 3.106 | 0.587 | 0.785 | 0.745 |
| Discomfort Factor | 9, 11, 12, 16, 17, 18 | 2.349 | 0.856 | 0.858 | 0.802 |
| Sympathy Factor | 2, 3, 5, 6, 7, 13 | 3.860 | 0.576 | 0.644 | 0.502 |
With a Cronbach’s alpha value of 0.785, the IDP scale total achieves a relatively high internal consistency reliability score. Cronbach’s alpha coefficients for the IDP factors were as follows: the discomfort factor had a high coefficient of 0.858, and the sympathy factor coefficient had a borderline value of 0.644. A Cronbach’s alpha of 0.6 indicates moderate reliability. Generally, a reliability level of 0.8 or higher is considered extremely good, and an α of 0.6–0.7 is acceptable (Hulin et al., 2001). This is discussed in greater detail in the discussion section.
3.2. Construct validity
The data were examined to determine whether the presumptions required to perform an EFA were met. The suitability of the data for factor analysis was assessed using the KMO, which indicated commendable sampling adequacy with an overall KMO index of 0.760. The p-value for Bartlett’s test was less than 0.001, indicating its appropriateness for the exploratory factor analysis (EFA). The first EFA run revealed many items’ cross-loading issues and low coefficients. However, when the loading pattern was set to less than 0.40, items 1, 4, 8, 10, 14, and 15 did not load. Therefore, only two factors (i.e., components) had eigenvalues greater than 1.0. Two components with eigenvalues exceeding the breakpoint account for 64.935% of the shared variation, as indicated by the results of the EFA analysis. The first component, discomfort, comprises six items related to feeling physically or emotionally uncomfortable, with an eigenvalue of 10.035, accounting for 59.024% of the variance. Items loaded with the discomfort factor were 2, 3, 5, 6, 7, and 13, with the second factor having an eigenvalue of 1.005. Together with six additional items related to feelings of sympathy and sorrow for the misfortunes of others, this second factor, labeled sympathy, explains 5.911% of the variation. The sympathy factor items were 9, 11, 12, 16, 17, and 18. However, as previously mentioned, six items failed to load on any factor, with a loading pattern of less than 0.40. Furthermore, two items that had cross-loads were eliminated: items 8 and 19. Overall, however, the loadings for the two-factor solution obtained in this study demonstrate good discriminability.
3.2.1. Confirmatory factor analysis
A selection of fit indices was used to evaluate the model fit of twelve items produced by the EFA. A CFA was first conducted with the same factor loadings as those obtained from the EFA. However, the model fit was poor, as both the Tucker–Lewis index (TLI) and the comparative fit index (CFI) were below the recommended cut-off point of 0.95 (Byrne, 2016), with the following values: TLI = 0.752 and CFI = 0.801—indicating a poor match between the proposed model and the collected data. This result indicates a poor model fit because the RMSEA value (RMSEA = 0.104) was higher than the recommended point of 0.05 (MacCallum et al., 1996). As indicated by the modification indices, item 6 was then deleted, and other residual covariance matrices were checked for any potential addition of residual covariances between the items as a parameter to improve the model fit. The model then underwent considerable improvement, with CFI TLI values indicating a good fit (CFI = 0.950, TLI = 0.923) and an RMSEA value of 0.058.
Overall, as Table 4 shows the CFA findings reveal a strong model fit and appropriate factor loading, supporting the proposed two-factor structure of the Arabic IDP scale.
| Model Step | χ² | df | χ²/df | LI | CFI | RMSEA (90% CI) | FI | FI IC | RMR | CVI |
|---|---|---|---|---|---|---|---|---|---|---|
| First run with EFA items | 151.328 | 53 | 2.85 | .75 | .80 | .10 (.085, .123) | .99 | .73 | 5832.924 | .10 |
| Second and final run | 74.183 | 47 | 1.57 | .92 | .95 | .05 (.031, .082) | .99 | .86 | 5767.780 | .931 |
3.2.2. Reliability of the 11-item scale produced using confirmatory factor analysi
Cronbach’s alpha was computed again for the 11-item scale yielded by our CFA. This was done after deleting item 6, which was loaded with the rest of the items in the EFA analysis. The total Cronbach’s alpha coefficient was 0.753. The value of α for the discomfort factor was 0.83 for the final set of items, which included items 9, 11, 12, 16, 17, and 18. The value of α for the sympathy factor was 0.705, and its final set included items 2, 3, 5, 7, and 13.
3.2.3. Convergent validity
For the sympathy factor, the AVE values were ≥0.5, establishing the convergent validity. However, this was not the same for the discomfort factor, as the AVE values did not exceed the threshold level. For Pearson’s correlation coefficient analysis, the correlation values between the subscales were greater than .30, establishing the convergent validity of both factors.
4. Discussion
The findings of this study provide sufficient evidence of the validity and reliability of the Arabic IDP scale for evaluating the interactions of Arab medical doctors and college-level healthcare students with individuals with disabilities. The IDP scores of the study participants were relatively high, indicating that they generally reported positive interactions with individuals with disabilities. The two-factor orthogonal solution yielded the most fitting model of the Arabic IDP scale’s structure, aligning with the results of two previous studies (MacLean & Gannon, 1995; Tait & Purdie, 2000).
Following analysis using residual covariance, modification indices, and the deletion procedure, the confirmatory factor analysis (CFA) results demonstrated a strong model fit. The model fit was assessed using several fit indices, and the 11-item scale yielded by the CFA was deemed adequate. The scores for the two-factor solution were consistently high, as were the Cronbach’s alpha coefficients calculated during the exploratory factor analysis (EFA). When Cronbach’s alpha was recalculated for the 11-item scale yielded by the CFA, the overall reliability remained high.
The final two factors of the 11-item scale comprised a discomfort factor, which included items 9, 11, 12, 16, 17, and 18, and a sympathy factor, which included items 2, 3, 5, 7, and 13. Convergent validity was assessed using average variance extracted (AVE) and Pearson’s correlation.
For the number of factor replications, the present study’s findings differ from those of the original research by Gething and Wheeler (1992). The Cronbach’s alpha of 0.83 for the discomfort factor corresponds with the findings of Gething (1994), who reported the same value for items 9, 11, 12, 16, 17, and 18. The current results are consistent with those of nearly all reviewed studies, as this factor (discomfort) consistently includes items 9, 12, 16, 17, and 18 and has demonstrated outstanding internal consistency.
The results concerning the sympathy factor align closely with a few studies, including the original research of MacLean and Gannon (1995) and the initial findings of Tait and Purdie (2000). This factor was initially labeled “sympathy”; however, in the present study, item 7 (“I am grateful that I do not have such a burden”) was added to the set (items 2, 3, 5, and 13). Given the language of item 7, its loading within the sympathy factor may be attributed to the notion that gratitude can foster sympathy or even empathy. It is widely acknowledged that gratitude and sympathy often promote prosocial behaviors that benefit others at a personal cost. Moreover, individuals with high dispositional gratitude may develop improved emotional regulation and form meaningful connections with others. This may explain why confident respondents resonated with this item and scored differently from others.
The findings are consistent with those of researchers who employed the maximum likelihood extraction approach and the direct oblimin rotation method. They also align with studies that did not replicate the original IDP factor structure proposed by Gething and Wheeler (1992), who reported a six-factor solution. However, regarding common variance and Cronbach’s alpha, the current findings parallel those of MacLean and Gannon (1995), who derived a five-factor solution and reported similar percentages of explained variance. In this study, factor 1 accounted for 59% of the variance, while MacLean and Gannon (1995) reported that factor 1 accounted for 55%. In both studies, the two factors were reliably measured, comprising nearly identical items, with a Cronbach’s alpha of >0.80 for factor 1 (discomfort) and >0.68 for factor 2 (sympathy).
The two-factor solution demonstrated strong reliability and validity, corroborating findings by Tait and Purdie (2000), who reported similar results using CFA. The two-factor model also supports earlier concerns raised by Thomas et al. (2003), as cited in Iacono et al. (2009), who contended that Gething (1991) and Gething and Wheeler (1992) over-factored the instrument. They argued that the Kaiser–Guttman criterion, which accepts factors with eigenvalues greater than one, is overly permissive, especially for a 20-item instrument. Thomas et al. (2003) employed the maximum likelihood method and direct oblimin rotation to analyze data from 358 college students. Using a stringent criterion for identifying component loadings above 0.4, they extracted only three factors, thereby warranting further investigation of this issue.
Other challenges noted in the literature pertain to sampling methods and the varied cultural backgrounds of participants. The current study included a diverse sample comprising medical doctors and college students. For instance, Forlin et al. (1999) administered the IDP scale to 2,375 education students in Australia and 475 similar students in South Africa. Loo (2001) conducted a psychometric revision of the IDP using data from 231 Canadian undergraduates studying volunteer management. Notably, the two-factor and six-factor solutions were not supported by the findings in these studies. For many scales, the internal consistency reliability was low to moderate. Thomas et al. (2003) administered the 1994 version of the IDP scale to 358 U.S. students. In contrast, Yoshida et al. (2003) administered an Urdu adaptation of the IDP to 591 Pakistani respondents and extracted five components, yielding different results.
This study has several strengths. First, it employs a diverse sample comprising medical doctors and preclinical medical students, with a relatively adequate sample size. Second, the data were collected from the northern region of (...............), (...............), which is home to a substantial Arabic-speaking population. Participants were drawn from the University of (...............) and four public and university hospitals in the (...............) Region, including students enrolled in healthcare programs.
However, several limitations should be noted. Since no gold standard measures have been validated in an Arab context, criterionrelated validity could not be examined. Additionally, to assess convergent and discriminant validity more robustly, future research should employ supplementary measures to determine the degree of positive and negative correlations between the IDP scale and similar instruments.
Funding
The authors have no funding to disclose.
Compliance with Ethical Standards
Compliance with Ethical Standards: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee at (...............) and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
Conflicts of Interest
The authors declare they have no conflict of interest.
Informed Consent
Informed consent was obtained from all individual adult participants included in the study.
Data Availability
All data are available upon request from the authors.
Acknowledgments
We thank everyone who provided the information and support to complete this work.