Introduction
Healthcare workers often experience a high degree of occupational stress, running the risk of developing unhealthy behaviors, poor physical and mental health, emotional exhaustion, and job loss due to the negative consequences of occupational stress (Han et al. Reference Han, Trinkoff and Gurses2015). Long-term stress can lead to burnout syndrome, which is characterized by extreme exhaustion, detachment, and inability to feel a sense of accomplishment at work (Lacy and Chan Reference Lacy and Chan2018). In Paraguay, the frequency of burnout syndrome in healthcare workers ranges between 24.1 (Chávez et al. Reference Chávez, Marcet and Ramirez2021) and 72.6% (Delgado Maidana et al. Reference Delgado Maidana, Vega and Sanabria2011) and has even been reported in medical students (Chávez et al. Reference Chávez, Marcet and Ramirez2021; Delgado Maidana et al. Reference Delgado Maidana, Vega and Sanabria2011; Rojas-Melgarejo et al. Reference Rojas-Melgarejo, Mereles-Oviedo and Barrios2017).
Burnout syndrome has been associated with numerous adverse outcomes in the medical profession including: increased absenteeism and turnover and a considerable increase in the risk of making medical errors (Clough et al. Reference Clough, March, Chan, Casey, Phillips and Ireland2017; Ireland et al. Reference Ireland, Clough, Gill, Langan, O'Connor and Spencer2017).
The rate of help-seeking in order to cope with occupational and emotional stress still remains low among medical professionals, with some studies reporting that only one of four depressed physicians seek professional help (Canadian Medical Association 2003).
Therefore, health professionals should know when and how to ask for help, and we should be able to identify barriers for accessing help. These barriers may include the stigma of occupational stress at an individual or social level. Scambler defines stigma as “any attribute, trait, or disorder that marks an individual as being unacceptably different from the ‘normal’ people with whom he or she interacts, and elicits some form of community sanction’’ (Scambler Reference Scambler1998). Four types of stigma associated with mental health help-seeking behaviors have been described: (a) public stigma; (b) personal stigma; (c) self-stigma; and (d) structural stigma (Clough et al., Reference Clough, Ireland and March2019).
Clough, Ireland, and March developed the Stigma of Occupational Stress Scale for Doctors (SOSS-D) with the aim of measuring stigma related to occupational stress and burnout among physicians; it is a comprehensive and useful instrument reporting excellent psychometric properties (Clough et al., Reference Clough, Ireland and March2019). Considering that there is no validated Spanish version of this scale, we aimed to investigate the psychometric properties of the translated Spanish version of the SOSS-D and the factors associated with Physicians’ Burnout in Paraguay. This purpose is increasingly relevant following evidence of occupational stress among physicians in Paraguay and around the world during the COVID-19 pandemic (Torales et al., Reference Torales, O’Higgins, Castaldelli-Maia and Ventriglio2020).
Methods
Study design and participants
This was an observational, cross-sectional study, based on an online survey launched from 30th July to 30th November 2021. Participants were 747 Paraguayan healthcare workers, aged 24–77 years old, of both sexes, who voluntarily completed the survey, spread through messaging apps (“WhatsApp” or “Telegram”) and email. All participants received complete information about the aim of the study, privacy, and data-processing.
The participants were selected through an intentional, non-probabilistic, sampling from the staffing records of the National Union of Physicians of Paraguay. The total number of professionals accessed through staffing records was 900.
The Internet-based approach has been particularly useful, especially in times of social distancing due to the current COVID-19 pandemic and it is of note that this approach is based on the evidence that responses to online surveys may provide similar findings to those reported through “in person” samples (Gosling et al. Reference Gosling, Vazire, Srivastava and John2004).
Measures
Demographic and occupational data
Participants were asked to provide information on their sex, age, highest degree of medical education attained, years of professional practice, number of hours per week worked, and place where they provide most of their services as a physician (public, private, both).
Health status regarding COVID-19
Participants responded about their front line COVID-19 status and whether they had been diagnosed with COVID-19, or had been in contact with people with a COVID-19 diagnosis, whether they had lost a family member or close friend to COVID-19 (yes, no), and whether they had been vaccinated against COVID-19 (yes both doses, yes one dose, no).
Mental health status and substance use
Participants responded whether they had been previously diagnosed with a mental disorder (yes, no), whether they consulted a therapist, whether they regularly consumed any psychotropic medication (yes, no), which prescribed psychotropic medication they consumed (multiple responses), which was the greatest source of stress in their life (work, money, family, others), whether they used non-prescribed, over-the-counter or off-label substances to improve their mood (yes, no), which substance they used (multiple responses), whether they were smokers, whether they had used any illegal substances (cannabis, ecstasy, others), whether anyone had been concerned about their substance use (yes, no), and whether they had been concerned about their own substance use (yes, no).
The SOSS-D
Originally developed by Clough, Ireland, and March (Clough et al., Reference Clough, Ireland and March2019), the SOSS-D is a psychometrically valid self-administered scale aimed to measure stigma toward occupational stress and burnout among medical doctors. The SOSS-D has a three-factor model (“perceived structural” stigma, “personal stigma,” and “perceived other” stigma). It has 11 items rated on a seven-point Likert scale from one (completely disagree) to seven (completely agree). Higher scores on the scale show higher levels of stigma. In the English version, the internal consistency of the three factors were α = 0.78 for factor one, α = 0.71 for factor two, and α = 0.84 for factor three. Cronbach’s alpha values for the current sample is described in the results section of the present study.
Stigma subscale of the Perceived barriers to treatment scale (PBPT)
Like the authors of the original version of the SOSS-D (Clough et al., Reference Clough, Ireland and March2019), we used the stigma subscale of the PBPT (Mohr et al. Reference Mohr, Ho, Duffecy, Barron, Lehman, Jin and Reifler2010) to measure general stigma (as a barrier to help-seeking for difficulties with stress or burnout). This subscale includes seven items, rated on a five-point Likert scale. Scores range from 7 to 35, with higher scores indicating higher stigma. In our study, “psychiatrist/psychologist/therapist” was used instead of “counselor/therapist” for better adaptation to the local context. Internal consistency of the measure in a previous study was α = 0.89. Cronbach’s alpha values for the current sample is described in the results section of the study.
The Oldenburg Burnout Inventory
The Oldenburg Burnout Inventory (OLBI) (Demerouti and Bakker Reference Demerouti, Bakker and Halbesleben2008) includes two subscales: exhaustion and disengagement from work, with 8 items each. Exhaustion is defined as a consequence of intensive physical, affective, and cognitive strain, as a long-term consequence of prolonged exposure to certain job demands, while disengagement refers to distancing oneself from work in general, work object, and work content (Demerouti et al. Reference Demerouti, Mostert and Bakker2010). All items are rated on a four-point Likert scale from one (completely agree) to four (completely disagree). The total OLBI score is obtained by adding the two subtotals. The higher the score, the higher the level of burnout. Suggested cut-off scores are ≥2.25 for exhaustion and ≥2.1 for disengagement (Peterson et al. Reference Peterson, Demerouti, Bergström, Samuelsson, Åsberg and Nygren2008).
In this paper, we used a Spanish version previously validated in Paraguay (Torales et al. Reference Torales, Kadhum, Zárate, Barrios, González, Farrell, Ventriglio and Arce2019). Cronbach’s alpha values for the current sample is described in the results section of the study.
The CAGE questionnaire
The CAGE questionnaire is a four-item scale validated as a lifetime alcohol use screening instrument (Ewing Reference Ewing1984). This screening instrument consists of four dichotomous response items, with a score of zero for “no” and one for “yes” responses. A total score of two or higher value is considered clinically significant. The normal cut-off for the CAGE is two positive (“yes”) answers (Ewing Reference Ewing1984).
In this paper we used a Spanish version previously validated in Paraguay (Torales et al. Reference Torales, Kadhum, Zárate, Barrios, González, Farrell, Ventriglio and Arce2019). Cronbach’s alpha values for the current sample is described in the results section of the study.
Translation process and validation
The translation of the SOSS-D from English to Spanish was performed following the procedures suggested for cross-cultural adaptation of self-report measures, using the back-translation method (Beaton et al. Reference Beaton, Bombardier, Guillemin and Ferraz2000):
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1. The original English version was translated into Spanish.
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2. A bilingual expert back-translated the Spanish version into English.
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3. A native English speaker compared, sentence by sentence, the back translation with the original English version, to verify if they were equivalent in meaning.
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4. Minor changes were made after the comparison and the Spanish version was administered to 20 individuals, as a pilot test, to verify if the questionnaire was comprehensible.
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5. After the pilot test, the final Spanish version was approved (Available upon request to the corresponding author).
Statistical analysis
To test the construct validity, the pertinence of performing an exploratory factor analysis was preliminary assessed using the Kaiser – Meyer – Olkin (KMO; SPSS software - version 23) test for sample adequacy and the Bartlett’s test of sphericity. The sample was randomly divided into two subsamples, in which exploratory factor analysis was performed with the afore-mentioned software and confirmatory factor analysis (CFA) was performed with JASP statistical software (version 0.10.2.0). Exploratory factor analysis aimed to obtain the factor structure, to be confirmed with confirmatory analysis. Exploratory factor analysis was made using principal axis factoring with promax rotation, with a kappa value of 4, taking into consideration the correlation between the items and that the assumption of normality was not met. CFA was performed using Jeffrey’s Amazing Statistics Program (Love et al. Reference Love, Selker, Marsman, Jamil, Dropmann and Verhagen2019). Diagonally weighted least squares estimation procedure was used for CFA, taking into consideration the sample size. Model fit was tested through chi-square (χ2), the comparative fit index (CFI), the normed fit index (NFI), the Tucker – Lewis index (TLI), the root mean square error of approximation (RMSEA), and the standardized root mean square residual (SRMSR). These indices detect if the fit model is good (RMSEA and SRMSR <0.05 and CFI and TLI >0.95) or acceptable (RMSEA and SRMSR between 0.05 and 0.08, and CFI and TLI between 0.90 and 0.95) (Schermelleh-Engel et al. Reference Schermelleh-Engel, Moosbrugger and Müller2003).
Reliability was measured with McDonald’s Omega coefficient (ω) and Cronbach’s alpha (α). Convergent validity was measured via the correlations of the SOSS-D with the PBPT using Pearson correlations in SPSS. These correlations are defined as strong (r ≥ 0.50), moderate (r values between 0.30 and 0.49), and weak (r values between 0.10 and 0.29) (Cohen Reference Cohen2013).
Lastly, bivariate analyses were conducted to assess differences between participants’ characteristics (demographics, occupational data, health status regarding COVID-19, mental health status and substance use, OLBI scores, and CAGE scores) on the SOSS-D scores.
Results
Demographic and occupational data
Of 747 surveyed physicians (response rate = 83%), 66.7% were women. Their age ranged from 24 to 77 years old, with a mean of 38.8 ± 8.8 and a median of 37 years. Regarding medical education attained, the most frequent was a postgraduate degree in a medical specialty. Of participants, 82.3 % provided most of their services as physicians in the public or state sector. More details are shown in Table 1.
Table 1. Demographic and occupational characteristics of surveyed physicians (n = 747)
For years of professional practice, the range was between 1 and 50 years, with a mean of 12.7 ± 8.5 and a median of 11 years. The average number of hours per week worked by the physicians was 53.6 ± 18.5 hours, with a median of 50 hours (range between 4 and 100 per week).
Health status regarding COVID-19
Of participants, 67.5% have been on the front line of care for patients with COVID-19, 44.7% have been sick with COVID-19, and 74.8% have lost a family member, close friend, or partner because of COVID-19 infection. Of the surveyed physicians, 93% have been vaccinated with two doses of COVID-19, 5.5% with one dose and 1.5% have not been vaccinated.
Mental health status and substance use
Of the surveyed physicians, 18.5% have been previously diagnosed with a mental health condition, 12.9% currently see a mental health professional, and 13.4% regularly use prescribed psychotropic medication. Work, income, and family/intimate relationships were the main sources of stress for Paraguayan physicians (Table 2).
Table 2. Mental health status and main stressors (n = 747)
Regarding the use of non-prescribed, over-the-counter or off-label substances to improve mood, 8.7% of physicians stated that they did so. The most used substances were benzodiazepines (60%), followed by antidepressants (13.2%) (Fig. 1). Smoking was reported in 9.8% of surveyed participants. In addition, 17.5% of them reported having consumed some type of illegal substances. Of the participants, 32.8% mentioned that someone had been concerned about their substance use. Likewise, 25.9% of the surveyed physicians mentioned having been personally concerned about their substance use. Fig. 2 shows the type of illegal substances used by the participants.
Fig. 1. Lifetime use of non-prescribed, over-the-counter or off-label substances (n = 65 have used non-prescribed, over-the-counter or off-label substances).
Fig. 2. Lifetime use of illegal substances (n = 131 have used illegal substances).
Alcohol use
Of the 747 participants, 57.6% reported alcoholic beverage consumption. 19.3% of these scored ≥2 on the CAGE questionnaire to detect problematic alcohol consumption (Ewing Reference Ewing1984). Cronbach’s alpha for the CAGE questionnaire was 0.676.
Burnout and perceived barriers to treatment
The mean OLBI score was 2.7 ± 0.41, with a mean disengagement score of 2.5 ± 0.42 and a mean exhaustion score of 2.9 ± 0.51. These results indicate clinically significant disengagement in 85.9% and clinically significant exhaustion in 91.57% of participants. In addition, 88.1% reported clinically significant scores (≥2.25 for exhaustion and ≥2.1 for disengagement) on both subscales. Cronbach’s alpha for OLBI was 0.84, which indicates robust reliability.
The mean score of the stigma subscale of the PBPT was 13.73 ± 6.8, and its reliability was α = 0.914.
Factor analysis
The mean score on the SOSS-D was 42.82 ± 10.32. The mean scores for each factor were:
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Perceived Structural Stigma (PSS) = 4.14 ± 1.35.
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Personal Stigma (PS) = 3.31 ± 1.35.
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Perceived Other Stigma (POS) = 4.05 ± 1.2.
KMO test was adequate (KMO = 0.763) and sphericity tested significantly (p < 0.0001). These results confirmed that the sample was adequate for a factor analysis. Secondly, the sample was randomly divided into two subsamples (subsample 1, n = 448; subsample 2, n = 299), in order to perform exploratory and CFA.
Three factors had a raw eigenvalue greater than the parallel random values, thus three factors were retained. After extraction, these factors explained 61.7% of total variance.
The original three-dimensional model, as found in the exploratory factor analysis performed on subsample 1, was assessed with CFA in subsample 2. The model adjustment was good, according to all fit indices (S-B χ 2 = 184.7 df = 41, p > 0,001; RMSEA = 0.063; SRMSR = 0.061; CFI = 0.914, NFI = 0.902, TLI = 0.909). This confirms that the model of the Spanish version of the SOSS-D may reproduce the same three-factor model of the original version. The factor loadings are showed on Table 3.
Table 3. Factor loadings for 11 items of the SOSS-D based on confirmatory factor analysis (CFA)
Internal consistency and convergent validity
The total SOSS-D Cronbach’s alpha showed an internal consistency of α = 0.684. Cronbach’s alphas for each factor were PSS = 0.73, PS = 0.521, and POS = 0.496. Omega coefficient was 0.71 for the total SOSS-D. Omega coefficients for each factor were PSS = 0.72, PS = 0.42, and POS = 0.28. Inter-correlations among the SOSS-D factors were statistically significant (p < 0.01) (Table 4).
Table 4. Inter-correlations among the SOSS-D factors
Convergent validity of the SOSS-D was assessed by evaluating the correlations of the SOSS-D with a convergent scale (stigma subscale of the PBPT). The correlation between SOSS-D and the stigma subscale of PBPT was statistically significant (r = 0.245, p < 0.001). Significantly correlations were found between the factors PSS (r = 0.211, p < 0.001), PS (r = 0.194, p < 0.001), and POS (r = 0.111, p < 0.05) and the stigma subscale of the PBPT.
SOSS-D and factors associated with physicians’ burnout
POS factor scores were inversely correlated with years of practice (r = −0.1, p = 0.006) and age (r = −0.103, p = 0.05). OLBI scores were directly correlated with PSS (r = 0.277, p < 0.001) and POS (r = 0.099, p = 0.007). The score obtained in the CAGE questionnaire was also directly correlated with the PSS factor (r = 0.126, p = 0.009) and the PS factor (r = 0.103, p = 0.033). Lower scores in the PSS factor were associated with front line status against COVID-19 (t = 2.31, df = 745, p = 0.021).
A previous diagnosis of a mental disorder was associated with PSS and PS factors, as those with a previous history of a mental disorder reported higher (t = −3.25, df = 745, p = 0.001) and lower scores (t = 3.2, df = 745, p = 0.001), respectively. Those who regularly used prescribed psychotropic medications reported higher scores in Personal Structural Stigma (PSS) (t = −2.14, df = 745, p = 0.033). Likewise, those who consumed alcoholic beverages have shown higher Personal Structural Stigma (PSS) scores (t = −2.1, df = 745, p = 0.038). Those who consumed non-prescribed, over-the-counter or off-label substances have shown higher PSS (t = −2.4, df = 745, p = 0.016) and POS (t = −2.42, df = 745, p = 0.016) scores.
The relationship between OLBI scores and PBPT scores was significant and direct (r = 0.238, p = 0.001); the relationship with age was significant and inverse (r = −0.279, p = 0.001) as well as the relationship with working hours was significant and direct, but weak (r = 0.108, p = 0.003). Those participants with a history of any mental disorder reported higher OLBI scores (t = −6.344, df = 745, p = 0.001), those with prescribed medication consumption have shown higher scores on OLBI (t = −3.571, df = 745, p=0.001), whereas those with an off-label consumption of medication reported higher OLBI scores (t = −3.508, df = 745, p = 0.001). Physicians who consumed illegal substances have shown higher scores at the OLBI (t = −3.568, df = 745, p = 0.001). In addition, those who consumed alcoholic beverages presented lower scores at the OLBI (t = 2.077, df = 745, p = 0.038).
Discussion
The Spanish version of the SOSS-D reported good fit indices in the CFA, as well as high factor loadings in all the items, which confirms that this version reproduces the three factors of the original English version. Likewise, the internal consistency measured with Cronbach’s alpha and McDonald’s Omega coefficients was acceptable both for the complete scale and for the different factors. In terms of construct validity, convergence with the stigma subscale of the PBPT resulted in a direct and statistically significant correlation.
The mean scores for both the total SOSS-D and the three factors were similar to the mean scores found in the original version (Clough, Ireland, et al., Reference Clough, Ireland and March2019). One of the limitations of this scale is the lack of a precise cut-off point confirming whether the stigma is clinically significant. The interpretation of the scale is quantitative: the higher the score, the greater the stigma.
The POS factor was found to be inversely related to years of medical practice, which might mean that those physicians with fewer years of practice reported a higher perception of stigma. The same relationship was found with age, which might suggest that younger physicians have shown higher stigma in seeking professional help (Clough, March, et al., Reference Clough, March, Leane and Ireland2019).
Physicians working on the front line of care for patients with COVID-19 reported significantly lower scores on the PSS factor of the SOSS-D, which might mean that they have experienced less stigma when seeking psychological help. This might be due to the fact that Paraguay offers established strong policies and plans for mental health care of health personnel in the context of the COVID-19 pandemic (Villalba-Arias et al. Reference Villalba-Arias, Estigarribia, Bogado, Méndez, Toledo, González, Castaldelli-Maia, Ventriglio and Torales2020, Reference Villalba-Arias, Estigarribia, Bogado, Méndez, Toledo, Barrios, Castaldelli-Maia, Ventriglio and Torales2021).
The scores obtained in the CAGE questionnaire were also associated with the PSS and PS factors of the SOSS-D, both directly. This could represent that problematic alcohol consumption generated greater stigma in physicians, making it difficult for them to seek professional care. The same was true for those physicians who used nonprescription medications and/or illegal substances: research has reported that substance abuse is one of the barriers making it difficult for physicians to seek psychological help (Vayr et al. Reference Vayr, Herin, Jullian, Soulat and Franchitto2019).
In Paraguay, a recent study (Villalba-Arias et al. Reference Villalba-Arias, Estigarribia, Bogado, Méndez, Toledo, Barrios, Castaldelli-Maia, Ventriglio and Torales2021) found a prevalence of 41.90% and 48.15% of depressive and anxiety symptoms, respectively, in healthcare workers. This percentage is higher than 18.5% self-reported history of mental disorders found in this investigation. Other research has reported 29% of depression and 24% of anxiety in the medical population (Ruitenburg et al. Reference Ruitenburg, Frings-Dresen and Sluiter2012). These differences might be explained by the evidence that our study only included physicians and it relied exclusively on self-reporting and not on clinical interviews. Our research, moreover, found that 13.4% of the surveyed physicians regularly consumed psychotropic medication, mainly antidepressants and anxiolytics, consistent with the most prevalent disorders.
Of surveyed physicians, 17.5% reported a current use of illegal substances; of these, 25.9% reported having a personal concern about their substance use. Some authors have reported a prevalence of substance addiction among physicians of 10 – 12% (Goldenberg et al. Reference Goldenberg, Miotto, Skipper and Sanford2020). In our research, cannabis was the most used illegal substance among physicians, in almost 60% of cases. Notably, research has shown that physicians who use nonprescription medications and/or illegal substances may face higher stigma and should overcome more barriers to seeking psychological help (Vayr et al. Reference Vayr, Herin, Jullian, Soulat and Franchitto2019).
Almost nine out of 10 of the surveyed physicians presented a burnout syndrome, according to the suggested OLBI cut-off scores of ≥2.25 for exhaustion and ≥2.1 for disengagement (Peterson et al. Reference Peterson, Demerouti, Bergström, Samuelsson, Åsberg and Nygren2008). This syndrome is frequently detected with above 50% of incidence in physicians and physicians-in-training (Dyrbye and Shanafelt Reference Dyrbye and Shanafelt2016; Shanafelt et al. Reference Shanafelt, Hasan, Dyrbye, Sinsky, Satele, Sloan and West2015). Higher percentages found in our research might be due to the current demanding context of the COVID-19 pandemic. It is known that during any pandemic, healthcare workers face a number of intense work stressors: work overload, longer working hours, strict security measures in hospital units, constant vigilance, shortage of protective equipment, and reduced social contact (Brooks et al. Reference Brooks, Webster, Smith, Woodland, Wessely, Greenberg and Rubin2020). Physician burnout is a phenomenon that needs to be studied and effectively addressed, as it is associated with negative patient’s care outcomes (Shanafelt et al. Reference Shanafelt, Balch, Bechamps, Russell, Dyrbye, Satele, Collicott, Novotny, Sloan and Freischlag2010) and also physician safety (West et al. Reference West, Tan and Shanafelt2012).
A significant relationship was found between burnout and self-perceived stigma. This is consistent with similar research concluding that physicians with burnout are more likely to perceive significant stigma around seeking help for their distress (Weiss et al. Reference Weiss, Quinn, Danley, Wiens and Mehta2021). The relationship with age was inverse. This is in line with literature suggesting that burnout symptoms vary greatly with age and that young adults are particularly susceptible (Marchand et al. Reference Marchand, Blanc and Beauregard2018). Also, a history of a mental disorder was a factor associated with higher rate of burnout symptoms, as suggested by previous research (Stelnicki et al. Reference Stelnicki, Jamshidi, Angehrn, Hadjistavropoulos and Carleton2021).
Physicians with burnout may use substances as a coping behavior (Oglesby et al. Reference Oglesby, Gallucci, Wynveen, Ylitalo and Benson2020), so substance use, especially illicit substances, should be monitored and studied. Alcohol consumption is also related to higher scores on the burnout scale; however, in our study an inverse relationship was found, implying that those who consumed alcoholic beverages had fewer burnout symptoms. It should be considered that alcohol consumption may serve physicians as a coping strategy (Colville et al. Reference Colville, Smith, Brierley, Citron, Nguru, Shaunak, Tam and Perkins-Porras2017).
A strength of this research is that it is the first attempt to determine the psychometric properties of the Spanish version of the SOSS-D. This measure might become a valuable assessment tool for Spanish-speaking physicians affected by burnout syndrome and with difficulties in accessing mental health services.
Limitations of this research may include the overrepresentation of some sociodemographic factors that might have influenced the results. For example, the overrepresentation of women in the sample could have affected burnout rates, considering that there are gender differences in physician burnout, with higher rates in the female physician population compared to the male population (Rotenstein et al. Reference Rotenstein, Harry, Wickner, Gupte, Neville, Lipsitz, Cullen, Rozenblum, Sequist and Dudley2021). In addition, the overrepresentation of physicians who spend most of their working hours in the public/state sector might also have affected the results. In Paraguay, the public/state healthcare system is deficient and might represent an additional stress factor increasing exhaustion and disengagement from work rates in healthcare workers (Aboaja et al. Reference Aboaja, Wahab, Cao, O'Higgins and Torales2022). The low Omega and Alpha coefficients of the POS subscale could be due to the lack of homogeneity of its questions, suggesting the need for further validation studies in larger samples. Also, we relied entirely on self-report measures. Finally, test-retest reliability was not calculated, and a second assessment of the recruited subjects was not performed.
Conclusion
In conclusion, our study has shown that the Spanish version of the scale reported good psychometric properties and reproduced the three-factor model of the original English version. Likewise, we have reported a high frequency of burnout syndrome in Paraguayan physicians, as well as detecting many factors associated with burnout. Our findings might suggest programs for the prevention and care of mental health among physicians and other health professionals who may have a vulnerability to burnout (Torales, O’Higgins, et al., Reference Torales, O’Higgins, Castaldelli-Maia and Ventriglio2020; Torales, Ríos-González, et al., Reference Torales, Ríos-González, Barrios, O'Higgins, González, García, Castaldelli-Maia and Ventriglio2020).
Supplementary material
Available upon request to the corresponding author.
Financial support
This research received no specific grant from any funding agency, commercial, or not-for-profit sectors.
Conflict of interest
The authors have no conflicts of interest to disclose.
Ethical standards
This study was approved by the Department of Medical Psychology of the National University of Asunción, Paraguay (Reference number: 012/2021). Data were treated with confidentiality, equality, and justice, respecting the Helsinki principles. Participants gave consent for their data to be used in this research. Participants who required feedback from the survey were invited to write down their email address and received information or specific helpful suggestions.
