Psychometric properties of the Patient Health Questionnaire (PHQ-9) in the Dominican Republic

Psychometric properties of the Patient Health Questionnaire (PHQ-9) in the Dominican Republic | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Psychometric properties of the Patient Health Questionnaire (PHQ-9) in the Dominican Republic Zoilo Emilio Garcia-Batista, Kiero Guerra-Peña, Adriana Maria Alvarez-Hernandez, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4586950/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 16 You are reading this latest preprint version Abstract The PHQ-9 is a globally recognized and widely used tool for screening depression. Its importance lies in its ability to assess the DSM criteria for depressive disorders, allowing both diagnosis and assessment of the severity of the condition. However, despite its prevalence internationally, no comprehensive studies on its psychometric properties have been carried out in the Dominican Republic. This lack of reliable and valid psychometric instruments to assess depression entails several significant challenges. On the one hand, it limits diagnostic accuracy, which may result in incorrect or incomplete detection of depressive symptoms. In addition, it hinders proper assessment of the symptomatology and severity of the disorder, which could lead to inappropriate treatments. It also restricts the possibilities for research on depression in the specific context of the Dominican Republic, which hinders a complete understanding of the disease in terms of its cultural and social characteristics. To address this gap in the literature, this study set out to examine the psychometric properties of the PHQ-9 in the Dominican population. For this purpose, we relied on the participation of 1437 Dominicans. The results obtained provide favorable evidence on validity and reliability. In terms of internal structure, a unidimensional model was found to explain a significant proportion of the variability in the responses. In addition, confirmatory analyses showed an excellent fit of the proposed model. In terms of reliability, both McDonald's Omega coefficient and Cronbach's Alpha coefficient yielded values above the accepted threshold of 0.70, indicating adequate internal consistency. Likewise, a strong association was verified between the PHQ-9 and GAD-7 scores, providing additional evidence of criterion validity. These results support previous findings and suggest that the PHQ-9 is a reliable and valid tool to assess depression in the Dominican population. PHQ-9 Depression Psychometric Validation Dominican Republic Mental Health Figures Figure 1 Figure 2 Introduction Depression is a debilitating mental disorder characterized by a persistent sense of sadness, hopelessness, loss of energy, and loss of interest (American Psychiatric Association [APA], 2013). According to the World Health Organization (WHO, 2020) it constituted one of the most prevalent disorders and affects more than 264 million people worldwide (WHO, 2017). It is widely recognized that depression constitutes one of the most disabling mental disorders due to its significant impact on the quality of life and daily functioning of people who suffer from it. In addition, the various symptoms that characterize depression can lead to the development of physical and mental comorbidities (Gold et al., 2020 , Steffen et al., 2020 ). In this context, psychometric research has emerged as an essential component in the study and treatment of depression. Accurate assessment of this disorder is not only essential for proper clinical diagnosis, but also provides a solid basis for scientific research and the implementation of effective therapeutic interventions. Psychometric measurement of depression has become a central pillar in clinical research and clinical practice, allowing for a deeper understanding and more accurate assessment of the nature and severity of this disorder (Fried et al., 2022 ; Garcia-Batista et al., 2018). Screening tests to assess depression have become a highly relevant tool, as they allow early detection and avoid problems of underdiagnosis. Indeed, the longer the time without treatment, the worse the course and outcome of depression. Despite the importance of early detection, it is estimated that more than 50% of potential cases of depression remain undetected (Fekadu et al., 2022 ). Having valid and reliable instruments that allow adequate detection and measurement of this disorder is the first step for adequate treatment (Cassiani-Miranda, Pérez-Aníbal, Vargas-Hernández, Herazo-Bustos, & Cabarcas-Tovar, 2018 ; Sun et al., 2020 ). One of the most widely used screening tests worldwide is the 9-item version of the Patient Health Questionnaire-9 (PHQ-9). Each of the items corresponds to the diagnostic criteria of the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders. They are assessed on a scale of 0 to 3 (0 = never; 3 = almost every day). The PHQ-9 has the advantage of being a short, self-administered, easy-to-fill questionnaire that, in addition to serving for the diagnosis of depression, also allows the severity of the disorder to be assessed (Molebatsi, Motlhatlhedi, & Wambua, 2020 ; Sun et al., 2020 ). According to Kroenke ( 2021 ) the PHQ-9 is the most widely used depression screening scale in the world. Its international popularity is due to multiple factors. First, the nine items of this scale encompass the DSM criteria for depressive disorders, which allows it to be a diagnostic tool and a measure of the severity of the disorder. On the other hand, the total score is obtained by simply adding the item scores, and the cut-off points are easily memorized: 5, 10, 15 and 20, which represent thresholds for mild, moderate, moderately severe and severe depressive symptoms, respectively. Finally, it should be noted that unlike some depression scales, the PHQ-9 is available as public domain and is free to use. The PHQ-9 has been translated and validated in multiple languages and contexts: Spanish, French, Chinese, Korean, Thai, Greek, Arabic, Somali and Sinhalese, for example. Similarly, its specificity (0.71–0.84), sensitivity (0.90–0.97) (Wittkampf, Naeije, Schene, Huyser, & van Weert, 2007 ), reliability and validity have been evaluated and verified in many countries, both in clinical and non-clinical contexts (Baader et al., 2012 ; Cassiani-Miranda et al., 2018 ; Dajpratham et al., 2020 ; Hanwella, Ekanayake, & de Silva, 2014 ; Martin, Rief, Klaiberg, & Braehler, 2006 ; Molebatsi et al., 2020 ; Sun et al., 2020 ). Recently Bianchi et al. ( 2022 ) performed an analysis of the PHQ-9 by integrating data from 29 samples from seven different countries (e.g., Germany, USA) and five different languages (e.g., German, English). The integration of these samples resulted in a total of 58,272 participants (63% female; Mage = 43, SDage = 13), the largest sample size study to date. The psychometric results indicate that the satisfactory psychometric properties are maintained in the different samples, with no differences according to sex, age and language. Thus, the unidimensionality of the PHQ-9 was verified both in the pooled sample and in the subsamples (factor loadings between 0.72 and 0.89). In the same way, the internal consistency of the PHQ-9 was verified by obtaining Omega values above ,90. Taken together, these results provide solid evidence of the PHQ-9 for its use at the professional level and for research purposes. Despite the empirical support of the PHQ-9 and its wide international use, no specific studies have been found in the Dominican Republic that have evaluated its validity and reliability. Indeed, it is required to verify whether the psychometric properties are adequate in this context, or whether adjustments in its content or structure are required (Cassiani-Miranda et al., 2018 ). Taking this into consideration, the following objectives are proposed in the present study: a) to examine the internal structure of the PHQ-9 in the Dominican population; b) to verify internal consistency; c) to obtain evidence of criterion validity. In case of verifying that the scores obtained by means of the PHQ-9 have adequate psychometric properties in the context of the Dominican Republic, it will provide a screening tool for the early detection of this disorder in a better clinical and non-clinical context. Methodology Participants The study included the participation of 1437 individuals, 72.1% of whom were women and 27.9% were men, representing a diverse sample of the native population of the Dominican Republic. Participants ranged in age from 18 to 72 years, reflecting a wide variety of experiences and perspectives. The mean age of participants was 33.69 years, with a standard deviation of 11.18, indicating some variability in the distribution of ages within the sample. For the selection of participants, accidental non-probability sampling was used, which allowed the inclusion of individuals from diverse sociodemographic and geographic contexts in the Dominican Republic. This sampling strategy was chosen to guarantee the representativeness of the sample and to capture the heterogeneity of the Dominican population in terms of age, gender and other relevant factors. Data collection was conducted online, using accessible and secure digital platforms. Before participating in the study, all individuals provided informed consent, thus ensuring their full understanding and willingness to participate in the research. Instruments Patient Health Questionnaire (PHQ-9) : evaluates depressive symptomatology during the last two weeks by means of 9 items, using a four-alternative Likert-type response scale ranging from 0 (no days) to 3 (almost every day). The PHQ-9 scale scores assess 5 categories of depressive disorder: none (0–4 points), mild (5–9 points), moderate (10–14 points), moderately severe (15–19 points) and severe (20–27 points). For this study, the Spanish version of the PHQ-9 (Diez-Quevedo, Rangil, Sanchez-Planell, Kroenke, & Spitzer, 2001) was used, which has been shown to possess satisfactory sensitivity (0.84) and excellent specificity (0.92) compared to the Structured Clinical Interview, considered the gold standard at the time of assessment (Huarcaya-Victoria et al., 2020 ; Muñoz Navarro et al., 2017). Generalized Anxiety Disorder-7 Scale (GAD-7) is an instrument that has been designed to identify probable cases of generalized anxiety (Spitzer et al., 2006). It is composed of 7 items with a Likert-type response mode, which includes options from 0 (no day) to 3 (almost every day). For its correction, a direct score is obtained from the sum of the scores of all the items, which can fluctuate between 0 and 21. The original version has a good level of reliability, as well as criterion, construct, factorial and procedural validity. A cut-off point greater than or equal to 10 was identified, which optimized sensitivity (89%) and specificity (82%) (Spitzer et al., 2006). On the other hand, there are no established cut-off points for the Spanish version. Considering the 10-point cut-off, sensitivity values of 86.8% and specificity of 93.4% were found. Regarding internal consistency, an adequate homogeneity was verified (Cronbach's alpha = 0.93). Likewise, the scale correlated significantly with the following instruments: Hamilton Anxiety Rating Scale (HAM-A) (.852, p < .001), the Hospital Anxiety and Depression Scale (HADS) (anxiety domain, .903, p < .001) and the World Health Organization Disability Assessment Questionnaire (WHO-DAS II) (.696, p < .001) (García-Campayo et al., 2010). Statistical analysis Dimensionality assessment. An analysis of the underlying structure of the Patient Health Questionnaire Scale (PHQ-9) was conducted employing parallel analysis, a technique suggested in academic studies for the exploration of dimensions (Cho et al., 2009; Garrido et al., 2013 ; Horn, 1965 ). Factor modeling specifications and fit criteria. Construct validity was examined using confirmatory factor analysis (CFA). For this purpose, the DWLS (Diagonally Weighted Least Square) method was selected as the estimation technique, highlighting its suitability for working with ordinal variables (Forero et al., 2009 ; Nye & Drasgow, 2011 ). The adequacy of the AFC-derived model was determined using various fit indices: the comparative fit index (CFI), the root mean square error of approximation (RMSEA), the root mean square standardized residual (SRMR) and the Tucker-Lewis Index (TLI) (Kline, 2023 ; Hu & Bentler, 1999 ). For the CFI and TLI, values of .90 and .95, respectively, are interpreted as acceptable and excellent. For the RMSEA, values below .08 are considered adequate and those below .05 excellent (Schermelleh-Engel et al., 2003 ). Regarding the SRMR, values of .05 or less are understood as indicative of a good fit, and values between .05 and .08 as acceptable fit (Kline, 2023 ; Hu and Bentler, 1999 ). Reliability analysis. Reliability was assessed by internal consistency, using McDonald's Omega (Ꞷ) and Cronbach's Alpha (α) coefficients, with values above .70 being considered appropriate for both coefficients (Förster and Rojas, 2008 ; Ventura and Caycho, 2017 ). Treatment of missing data. The percentage of omitted responses on the PHQ-9 items was marginal (0.16%). In contexts where this proportion is less than 5%, as noted by Little et al. (2014), it is generally acceptable to use a simple imputation procedure. Attending to this recommendation, it was decided to implement imputation with the median to make up for missing values (Longford, 2005 ). Software for the analysis. Data management was carried out using IBM SPSS Statistics (Version 25). For the calculation of descriptive statistics, Spearman's correlation, reliability analyses and confirmatory factor analysis (CFA), JASP software (version 0.17.1) was used. The polychoric correlations were calculated with the Mplus software (version 7.4). Results The mean values of the PHQ-9 items showed variation, with item 9 presenting the lowest mean (M = 1.18) and item 3 the highest (M = 2.16), reflecting trends toward responses in the moderate to high range within the scale. Standard deviations indicated consistent variability across items, with the smallest dispersion in item 9 (SD = 0.568) and the largest in item 5 (SD = 1.10), suggesting a homogeneous distribution of responses across items. Skewness ranged from a slight skewness in item 3 (Skewness = 0.53) to a noticeable skewness in item 9 (Skewness = 3.65), pointing to a skew in responses toward one of the extremes of the scale, particularly in item 9. Table 1 Descriptive statistics and polychoric correlations of the Patient Health Questionnaire (PHQ-9) items. Item/Statistics Scale of the Patient Health Questionnaire (PHQ-9) 1 2 3 4 5 6 7 8 9 1 - 2 .80** - 3 .58** .61** - 4 .64** .68** .61** - 5 .56** .56** .59** .62** - 6 .57** .66** .52** .54** .54** - 7 .56** .64** .58** .61** .52** .63** - 8 .51** .60** .51** .53** .56** .56** .65** - 9 .55** .67** .47** .48** .50** .74** .54** .59** - Mean 1.91 1.85 2.16 2.14 2.12 1.52 1.84 1.46 1.18 SD 0.90 0.90 1.06 0.97 1.10 0.88 0.96 0.77 0.57 Asymmetry 0.84 0.91 0.53 0.59 0.55 1.69 0.97 1.83 3.65 Sex Differences in Anxiety: Results of the PHQ-9 Given the non-normal distribution of the data by group, the Mann-Whitney U test was applied to determine the differences in PHQ-9 scores between the male (n = 246) and female (n = 668) groups. One case that selected the "Other" option was omitted from the analysis (n = 1). The findings indicated a significant difference in median PHQ-9 scores for males (median = 13, interquartile range = 7) and females (median = 16, interquartile range = 8), with a U value = 101752.5, p < .001. This suggests that the levels of depressive symptomatology reported by women were significantly higher compared to those of men. The effect size, calculated as, rrb = .24, indicates a small effect size. Scale dimensionality To investigate the underlying structure of the Patient Health Questionnaire (PHQ-9), a parallel analysis was performed which indicated that only one factor should be retained. Specifically, the eigenvalue of the first factor obtained from the real data was 5.69, notably higher than the eigenvalue of 1.15 obtained from the first factor in the simulated data. In contrast, the second factor of the real data showed an eigenvalue of 0.74, which was lower than the eigenvalue of 1.10 found in the simulated data, indicating that this second factor lacked relevance and should not be retained. The principal axis factorization technique with a Promax rotation was used for this analysis. This factor was able to explain 59% of the total variance, indicating that a significant proportion of the variance is explained by a single factor, thus reflecting a strong and consistent unidimensional structure in the data set examined. Confirmatory factor analysis Following the theoretical model and the analysis of the dimensional structure performed, an evaluation of the model fit was carried out through a confirmatory factor analysis. The evaluated model demonstrated an excellent fit, as observed by the chi-square indices χ² (14) = 38.56 (p < .001), Comparative Fit Index (CFI) = 0.99 and Tucker-Lewis Index (TLI) = 0.99, and a reasonably good fit with a Root Mean Square Error of Approximation (RMSEA) = .064 (90% CI = .054, .076) and Standard RMSR = 0.051. The factor loadings for each scale item were found to be significant and exhibited high values (≥ .72), indicating a strong and significant association with the proposed factor. Reliability This section analyzes the consistency of the participants' responses through McDonald's Omega and Cronbach's Alpha coefficients. The importance of this consistency analysis lies in its ability to verify whether the items of the instrument reliably measure the construct they intend to assess, as highlighted by Förster and Rojas ( 2008 ) and Ventura and Caycho ( 2017 ). The results obtained for McDonald's Omega (Ꞷ= .891) and for Cronbach's alpha (α = .886) demonstrate a high internal consistency of the scale. Table 2 details the item-level statistics, showing that each item contributes to the reliability of the scale, evidenced by both the McDonald omega coefficient and Cronbach's alpha. The item-total correlation indices exceed the value of .40, indicating that each item possesses exceptional discrimination, in agreement with Hingorjo and Jaleel ( 2012 ). Table 2 Reliability statistics of individual items If item is deleted Item McDonald's ω Cronbach's α Item-to-rest correlation 1 .876 .869 .682 2 .870 .863 .755 3 .880 .874 .636 4 .874 .868 .689 5 .882 .875 .627 6 .880 .873 .635 7 .876 .870 .671 8 .883 .877 .586 9 .887 .885 .481 Criterion validity Given the absence of bivariate normality in the scores obtained from the GAD-7 and the PHQ-9 (Shapiro-Wilk = 0.974, p < .001), it was decided to use Spearman's correlation method instead of Pearson's correlation method. Such analysis indicated a positive, strong and significant correlation between both scales (ρ = .73, p < .001), which implies that high levels of depressive symptomatology, measured through the PHQ-9, are related to high levels of anxiety symptoms, assessed through the GAD-7. The strong correlation observed between these two instruments points to a significant relationship between anxiety and depressive symptoms, supporting claims found in previous studies (Sawaya et al., 2016 ; Pranckeviciene et al., 2022 ). Discussion The PHQ-9 is the most widely used depression screening scale in the world. By contemplating the DSM criteria for depressive disorders, it is a useful tool both for diagnostic purposes and for assessing the severity of the disorder. Despite its wide international use, there are no studies that have examined its psychometric properties in the Dominican Republic. Not having valid and reliable psychometric instruments to assess depression entails a number of problems. First, there is less capacity to make accurate diagnoses, resulting in incorrect or incomplete detection of depressive symptoms (Calderón et al., 2012 ; Molebatsi et al., 2020 ). In addition, not having tools to assess the presence of symptoms and severity of the disorder can lead to misdiagnosis and, consequently, inadequate treatment. In addition to the practical limitations, not having this type of tool limits the possibilities for research on depression, making it difficult to achieve a deeper understanding that is adjusted to the cultural and social characteristics of the Dominican Republic. Given this gap in the literature, the present study aimed to examine the psychometric properties of the PHQ-9. In general terms, satisfactory evidence was found regarding the validity and reliability of the PHQ-9 in the Dominican population. When examining the internal structure, the satisfactory fit of a unidimensional model was verified. Indeed, the results of the parallel analysis indicated the existence of a single underlying factor that explains 59% of the variability. On the other hand, the fit indices of the confirmatory factor analysis were satisfactory and the factor loadings of each item in the scale were significant and showed high values. These results indicate a solid unidimensional structure consistent with the results obtained in previous research (Bianchi et al., 2022 ). Regarding reliability, a thorough evaluation of internal consistency was carried out using both McDonald's Omega coefficient (Ꞷ) and Cronbach's Alpha coefficient (α). The results obtained revealed satisfactory values for both coefficients, exceeding the established threshold of 0.70 recommended by the specialized literature (Förster and Rojas, 2008 ; Ventura and Caycho, 2017 ). These findings are similar to those reported in previous research (Bianchi et al., 2022 ; Muñoz Navarro et al., 2017), and suggest that the scale items consistently measure the construct. Finally, examining the relationship with external variables corroborates a significant association between PHQ-9 and GAD-7 scores. The obtained results provide evidence of criterion validity by verifying a strong relationship between anxiety and depression symptoms as reported in previous research (Sawaya et al., 2016 ; Pranckeviciene et al., 2022 ). As a whole, the results obtained support the use of PHQ-9 as a reliable and valid tool for the assessment of depression, providing a solid basis for the interpretation of the scores obtained and for making clinical or research decisions based on them. Based on the present work, mental health professionals in the Dominican Republic will have a low-cost screening tool for the early detection of depression. It should be noted that the PHQ-9 also allows an assessment of severity, thus providing useful information for the design of interventions adapted to the level of severity of depression manifested by the patient (Kroenke, 2021 ). Having this tool will improve the treatment of depression and increase the volume of research on this disorder in the Dominican context. It is important to note that despite the efforts made, the present study has a number of limitations to consider. First, the study sample was selected through a non-probabilistic sample and with participants from the general population. It would be beneficial for future research to consider clinical samples. On the other hand, it should be noted that no analyses were performed to analyze the sensitivity and specificity of the PHQ-9. Although previous literature indicates that the PHQ-9 has adequate diagnostic accuracy (Diez-Quevedo et al., 2001; Huarcaya-Victoria et al., 2020 ; Muñoz Navarro et al., 2017), future research would be desirable to provide additional evidence in the Dominican context. Despite all limitations, we note that this is the first study to demonstrate the construct validity and reliability of the PHQ-9 in Dominican population. Mental health in the Dominican Republic emerges as a major concern, especially in light of alarming data provided by the World Health Organization (WHO). According to WHO reports, approximately 4.7% of the Dominican population suffers from depressive disorders, and 5.7% suffers from anxiety disorders (WHO, 2017). Unfortunately, a growth in these figures is projected if the situation of mental health services in the country is not improved, and technical tools are not developed to improve the quality of the treatments provided (Ministry of Public Health, 2020). We hope that this study will help to change this situation and contribute to improving the capacity to detect and evaluate depression in the Dominican Republic. Declarations Acknowledgments This research was financed by the Fondo Nacional de Innovación y Desarrollo Científico y Tecnológico (FONDOCYT) of the Dominican Republic, (Project Code: 2022-3A1-241), for which we thank them. Ethics Approval and Consent to Participate Respect for all bioethical principles and codes has been an essential pillar in each of the phases of the PsicAP project in the Dominican Republic. Due to this, all the methodology in this study follows the relevant guidelines and regulations to guarantee ethical prowess, following the Declaration of Helsinki. From the onset, participants were aware of the potential benefits and risks associated with the study, only included in the project after signing the informed consent voluntarily. Through this, they learned they could withdraw from the study during any of its phases if necessary. Likewise, respect for the confidentiality and anonymity of all participants was ensured, in part, by storing the data in secure and encrypted systems. To ensure respect and ethical monitoring throughout the study, the project has been submitted to institutional bioethics committees (Faculty of Health Sciences Bioethics Committee [COBEFACS] at the Mother and Teacher Pontifical Catholic University [PUCMM], Dominican Republic) and received approval on July 14, 2020 (registry code: COBE-FACS-EXT-00-1-2022-2023). Additionally, the study received approval from the national committee (National Health Bioethics Committee [CONABIOS], Dominican Republic) on September 8, 2020 (registry code: 021-2023). Declaration of Data Availability Data sharing for this manuscript is not applicable given that no datasets were generated during this specific study. However, this study is part of a larger study which will contain datasets. Information regarding the data of this project is available upon request from the corresponding author Z.E.G.B. Declaration of Competing Interests No, I declare that the authors have no competing interests, or other interests that might be perceived to influence the results and/or discussion reported in this paper. References Asociación Americana de Psiquiatría (2013). Guía de consulta de los criterios diagnósticos del DSM 5. Arlington, VA: Asociación Americana de Psiquiatría. Baader, T., Molina, J. L., Venezian, S., Rojas, C., Farías R., Fierro-Freixeneta, C., Backenstrass, M., & Mundt, C. (2012). Validación y utilidad de la encuesta PHQ-9 (Patient Health Questionnaire) en el diagnóstico de depresión en pacientes usuarios de atención primaria en Chile. Revista chilena de neuro-psiquiatría, 50 (1), 10-22. https://dx.doi.org/10.4067/S0717-92272012000100002 Bianchi, R., Verkuilen, J., Toker, S., Schonfeld, I. S., Gerber, M., Brähler, E., & Kroenke, K. (2022). Is the PHQ-9 a unidimensional measure of depression? A 58,272-participant study. Psychological Assessment, 34 (6), 595-603. https://doi.org/10.1037/pas0001124 Calderón, M., Gálvez-Buccollini, J. A., Cueva, G., Ordoñez, C., Bromley, C., & Fiestas, F. (2012). Validación de la versión peruana del PHQ-9 para el diagnóstico de depresión. Revista Peruana de Medicina Experimental y Salud Publica, 29 (4), 578-585. Cassiani-Miranda, C.A., Pérez-Aníbal, E., Vargas-Hernández, M.C., Herazo-Bustos, M., & Cabarcas-Tovar, A. (2018). Validez de apariencia y adaptación de la escala PHQ-9 para la detección de sintomatología depresiva en universitarios de ciencias de la salud de Cartagena (Colombia). Salud Uninorte, 34 (1), 75-87. Dajpratham, P., Pukrittayakamee, P., Atsariyasing, W., Wannarit, K., Boonhong, J., & Pongpirul, K. (2020). The validity and reliability of the PHQ-9 in screening for post-stroke depression. BMC Psychiatry, 20 (291). https://doi.org/10.1186/s12888-020-02699-6 Fekadu, A., Demissie, M., Birhane, R., Medhin, G., Bitew, T., Hailemariam, M.& Prince, M. (2022). Under detection of depression in primary care settings in low and middle-income countries: a systematic review and meta-analysis. Systematic Reviews , 11(1), 21. Forero, C. G., Maydeu-Olivares, A., y Gallardo-Pujol, D. (2009). Factor analysis with ordinal indicators: A Monte Carlo study comparing DWLS and ULS estimation. Structural Equation Modeling: A Multidisciplinary Journal , 16 (4), 625–641. Förster, C., & Rojas, C. (2008). Evaluación al interior del aula: una mirada desde a validez, confiabilidad y objetividad. Revista Pensamiento Educativo, 43 (2), 285-305. Fried, E. I., Flake, J. K., & Robinaugh, D. J. (2022). Revisiting the theoretical and methodological foundations of depression measurement. Nature Reviews Psychology, 1(6), 358-368. García-Batista ZE, Guerra-Peña K, Cano-Vindel A, Herrera-Martínez SX & Medrano LA. (2018). Validity and reliability of the Beck Depression Inventory (BDI-II) in general and hospital population of Dominican Republic. PLoS One . 29;13(6):e0199750. doi: 10.1371/journal.pone.0199750. PMID: 29958268; PMCID: PMC6025862. Garrido, L. E., Abad, F. J., & Ponsoda, V. (2013). A new look at Horn’s parallel analysis with ordinal variables. Psychological Methods, 18(4), 454–474. https://doi.org/10.1037/a0030005 Gold, S. M., Köhler-Forsberg, O., Moss-Morris, R., Mehnert, A., Miranda, J. J., Bullinger, M., & Otte, C. (2020). Comorbid depression in medical diseases. Nature Reviews Disease Primers, 6 (1), 69. Hanwella, R., Ekanayake, S., & de Silva, V.A. (2014). The validity and reliability of the Sinhala translation of the Patient Health Questionnaire (PHQ-9) and PHQ-2 screener. Depression Research and Treatment, 2014 . http://dx.doi.org/10.1155/2014/768978 Hingorjo, M., & Jaleel, F. (2012). Analysis of One-Best MCQs: The Difficulty Index, Discrimination Index and Distractor Efficiency . Journal of the Pakistan Medical Association, 62 (2), 142-147. Hogan, T. (2015). Pruebas psicológicas: Una introducción práctica. http://cort.as/-PVTd Horn, J. L. (1965). A rationale and test for the number of factors in factor analysis. Psychometrika , 30 , 179-185. https://doi.org/10.1007/BF02289447 http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S0026-17422013000400009 Hu, L.-T., y Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal , 6 (1), 1–55. Huarcaya-Victoria, J., De-Lama-Morán, R., Quiros, M., Bazán, J., López, K. and Lora, D., 2020. Propiedades psicométricas del Patient Health Questionnaire (PHQ-9) en estudiantes de medicina en Lima, Perú. Revista de Neuro-Psiquiatria , 83(2), pp.72-78. Kline, R. B. (2023). Principles and practice of structural equation modeling . Guilford publications. Kroenke K. (2021) PHQ-9: global uptake of a depression scale. World Psychiatry . 2021 Feb;20(1):135-136. doi: 10.1002/wps.20821. PMID: 33432739; PMCID: PMC7801833. Longford, N. T. (2005). Missing data and small-area estimation: Modern analytical equipment for the survey statistician . Springer Science & Business Media. Löwe, B., Gräfe, K., Zipfel, S., Spitzer, R. L., Herrmann-Lingen, C., Witte, S., & Herzog, W. (2003). Detecting panic disorder in medical and psychosomatic outpatients: comparative validation of the Hospital Anxiety and Depression Scale, the Patient Health Questionnaire, a screening question, and physicians' diagnosis. Journal of psychosomatic research , 55 (6), 515–519. https://doi.org/10.1016/s0022-3999(03)00072-2 Martin, A., Rief, W., Klaiberg, A., & Braehler, E. (2006). Validity of the Brief Patient Health Questionnaire Mood Scale (PHQ-9) in the general population. General Hospital Psychiatry, 28 (1), 71– 77. http://dx.doi.org/10.1016/j.genhosppsych.2005.07.003 Ministerio de Salud Pública. (2020). MSP: La depresión es la principal causa de suicidios en la República Dominicana. https://www.msp.gob.do/web/?p=8481 Molebatsi, K., Motlhatlhedi, K., & Wambua, G.N. (2020). The validity and reliability of the Patient Health Questionnaire-9 for screening depression in primary health care patients in Botswana. BMC Psychiatry, 20 (295). https://doi.org/10.1186/s12888-020-02719-5 Montero, I. & León, O. G. (2007). A guide for naming research studies in Psychology. International Journal of Clinical and Health Psychology, 7 (3), 847-862. Muñoz-Navarro, R., Cano-Vindel, A., Wood, C. M., Ruíz-Rodríguez, P., Medrano, L. A., & Limonero, J. T., et al. (2016). The PHQ-PD as a Screening Tool for Panic Disorder in the Primary Care Setting in Spain. PLoS ONE, 11 (8), e0161145. https://doi.org/10.1371/journal.pone.0161145 Nye, C. D., & Drasgow, F. (2011). Assessing goodness of fit: Simple rules of thumb simply do not work. Organizational Research Methods , 14 (3), 548-570. Organización Mundial de la Salud. (2017). Depression and Other Common Mental Disorders: Global Health Estimates. Ginebra: Organización Mundial de la Salud. Organización Mundial de la Salud. (2020). Depression. https://www.who.int/news-room/fact-sheets/detail/depression Pranckeviciene A, Saudargiene A, Gecaite-Stonciene J, Liaugaudaite V, Griskova-Bulanova I, Simkute D, Naginiene R, Dainauskas LL, Ceidaite G, Burkauskas J. Validation of the patient health questionnaire-9 and the generalized anxiety disorder-7 in Lithuanian student sample. PLoS One. 2022 Jan 27;17(1):e0263027. doi: 10.1371/journal.pone.0263027. PMID: 35085349; PMCID: PMC8794093. Sawaya, H., Atoui, M., Hamadeh, A., Zeinoun, P., & Nahas, Z. (2016). Adaptation and initial validation of the Patient Health Questionnaire–9 (PHQ-9) and the Generalized Anxiety Disorder–7 Questionnaire (GAD-7) in an Arabic speaking Lebanese psychiatric outpatient sample. Psychiatry research , 239 , 245-252. Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of psychological research online , 8(2), 23-74. Spitzer, R. L., Kroenke, K., & Williams, J. B. (1999). Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. Primary Care Evaluation of Mental Disorders. Patient Health Questionnaire. JAMA , 282 (18), 1737–1744. https://doi.org/10.1001/jama.282.18.1737 Steffen, A., Nübel, J., Jacobi, F. et al. Mental and somatic comorbidity of depression: a comprehensive cross-sectional analysis of 202 diagnosis groups using German nationwide ambulatory claims data. BMC Psychiatry , 20, 142 (2020). https://doi.org/10.1186/s12888-020-02546-8 Sun, Y., Fu, Z., Bo, Q., Mao, Z., Ma, X., & Wang, C. (2020). The reliability and validity of PHQ-9 in patients with major depressive disorder in psychiatric hospital. BMC Psychiatry, 20 (474). https://doi.org/10.1186/s12888-020-02885-6 Ventura, J., & Caycho, T. (2017). El coeficiente Omega: un método alternativo para la estimación de la confiabilidad. Revista Latinoamericana de Ciencias Sociales, Niñez y Juventud, 15 (1), 625-627. Wittkampf, K. A., Naeije, L., Schene, A. H., Huyser, J., & van Weert, H. C. (2007). Diagnostic accuracy of the mood module of the Patient Health Questionnaire: A systematic review. General Hospital Psychiatry, 29 (5), 388–395. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 12 Dec, 2025 Reviews received at journal 21 Nov, 2025 Reviews received at journal 17 Nov, 2025 Reviews received at journal 14 Nov, 2025 Reviewers agreed at journal 05 Nov, 2025 Reviewers agreed at journal 02 Nov, 2025 Reviewers agreed at journal 02 Nov, 2025 Reviewers agreed at journal 01 Nov, 2025 Reviewers agreed at journal 31 Oct, 2025 Reviews received at journal 23 Jul, 2024 Reviewers agreed at journal 13 Jul, 2024 Reviewers invited by journal 21 Jun, 2024 Editor invited by journal 20 Jun, 2024 Editor assigned by journal 20 Jun, 2024 Submission checks completed at journal 19 Jun, 2024 First submitted to journal 15 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4586950","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":320652649,"identity":"1b5e11a4-9573-4910-9f38-07a7f0719bf4","order_by":0,"name":"Zoilo Emilio Garcia-Batista","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8klEQVRIiWNgGAWjYFACxsYDUEYDwwcgxcZOWEsDXAvjDJAWZiLsOQBjMPOASQLK5dubGw58qKiVN28/3PjZ5tc2eT5mBsYPH3PwOKvnYMPBGWeOG845k9gsndt327CNmYFZcuY23FqYJRIbDvO2HWOcIcHYIJ3bc5sRqIWNmRePFjawln/H7IFamn9b9ty2J6iFB6yloSYRqKVNmuHH7USCWiR4QH45diB5Bk9im2Vvw+3kNmbGZrx+kW9vf/jgQ02d7Qz2449v/Phz23Z+e/PBDx/xaIGCwxCKsQ1MNhBUDwR1UPoPMYpHwSgYBaNgpAEAvsRUlMQnpSIAAAAASUVORK5CYII=","orcid":"","institution":"Pontificia Universidad Católica Madre y Maestra","correspondingAuthor":true,"prefix":"","firstName":"Zoilo","middleName":"Emilio","lastName":"Garcia-Batista","suffix":""},{"id":320652650,"identity":"d8975386-bd3f-4175-9e6b-ef0b523c4c9f","order_by":1,"name":"Kiero Guerra-Peña","email":"","orcid":"","institution":"Pontificia Universidad Católica Madre y Maestra","correspondingAuthor":false,"prefix":"","firstName":"Kiero","middleName":"","lastName":"Guerra-Peña","suffix":""},{"id":320652651,"identity":"32f53277-68a1-4780-ab3c-6acd6136434f","order_by":2,"name":"Adriana Maria Alvarez-Hernandez","email":"","orcid":"","institution":"Pontificia Universidad Católica Madre y Maestra","correspondingAuthor":false,"prefix":"","firstName":"Adriana","middleName":"Maria","lastName":"Alvarez-Hernandez","suffix":""},{"id":320652652,"identity":"d42d8a70-bd27-4333-8f22-d6d78b52abd0","order_by":3,"name":"ANTONIO CANO-VINDEL","email":"","orcid":"","institution":"Complutense University of Madrid","correspondingAuthor":false,"prefix":"","firstName":"ANTONIO","middleName":"","lastName":"CANO-VINDEL","suffix":""},{"id":320652653,"identity":"aab94ba6-73ef-4f6f-87f9-e28b83dc442e","order_by":4,"name":"Roger Muñoz-Navarro","email":"","orcid":"","institution":"University of Valencia","correspondingAuthor":false,"prefix":"","firstName":"Roger","middleName":"","lastName":"Muñoz-Navarro","suffix":""},{"id":320652654,"identity":"ad6c4ef9-fd97-4f1c-beb7-6d5a6b9a9cb6","order_by":5,"name":"Luciana Sofia Moretti","email":"","orcid":"","institution":"Universidad Empresarial Siglo 21","correspondingAuthor":false,"prefix":"","firstName":"Luciana","middleName":"Sofia","lastName":"Moretti","suffix":""},{"id":320652655,"identity":"e3102c47-8ac7-4797-8b68-9ae90ffef9e6","order_by":6,"name":"Jairo Espinal-Martinez","email":"","orcid":"","institution":"Pontificia Universidad Católica Madre y Maestra","correspondingAuthor":false,"prefix":"","firstName":"Jairo","middleName":"","lastName":"Espinal-Martinez","suffix":""},{"id":320652656,"identity":"d14f84cb-8d5d-4b25-b87e-acbadf0a8f98","order_by":7,"name":"Leonardo Medrano","email":"","orcid":"","institution":"Pontificia Universidad Católica Madre y Maestra","correspondingAuthor":false,"prefix":"","firstName":"Leonardo","middleName":"","lastName":"Medrano","suffix":""}],"badges":[],"createdAt":"2024-06-15 14:38:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4586950/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4586950/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":60432126,"identity":"9cfb7fe5-7b23-42a8-9e83-6b20ac1c2a60","added_by":"auto","created_at":"2024-07-16 16:47:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":15280,"visible":true,"origin":"","legend":"\u003cp\u003eParallel analysis for the PHQ-9 Scale\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4586950/v1/c98b8248124e9ef0eec7ad0d.png"},{"id":60432127,"identity":"7ae56a96-3f11-4743-8590-3f7ded9df71d","added_by":"auto","created_at":"2024-07-16 16:47:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":46180,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eOne-factor model for the PHQ-9\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4586950/v1/a8f46e2dd9c60ddcd314c478.png"},{"id":60432128,"identity":"888a7396-ae70-4bdf-8df2-44f7fe7069fa","added_by":"auto","created_at":"2024-07-16 16:47:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":587850,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4586950/v1/c89b3bb7-3f79-4cc5-956c-2536f062f204.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Psychometric properties of the Patient Health Questionnaire (PHQ-9) in the Dominican Republic","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDepression is a debilitating mental disorder characterized by a persistent sense of sadness, hopelessness, loss of energy, and loss of interest (American Psychiatric Association [APA], 2013). According to the World Health Organization (WHO, 2020) it constituted one of the most prevalent disorders and affects more than 264\u0026nbsp;million people worldwide (WHO, 2017). It is widely recognized that depression constitutes one of the most disabling mental disorders due to its significant impact on the quality of life and daily functioning of people who suffer from it. In addition, the various symptoms that characterize depression can lead to the development of physical and mental comorbidities (Gold et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Steffen et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this context, psychometric research has emerged as an essential component in the study and treatment of depression. Accurate assessment of this disorder is not only essential for proper clinical diagnosis, but also provides a solid basis for scientific research and the implementation of effective therapeutic interventions. Psychometric measurement of depression has become a central pillar in clinical research and clinical practice, allowing for a deeper understanding and more accurate assessment of the nature and severity of this disorder (Fried et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Garcia-Batista et al., 2018).\u003c/p\u003e \u003cp\u003eScreening tests to assess depression have become a highly relevant tool, as they allow early detection and avoid problems of underdiagnosis. Indeed, the longer the time without treatment, the worse the course and outcome of depression. Despite the importance of early detection, it is estimated that more than 50% of potential cases of depression remain undetected (Fekadu et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Having valid and reliable instruments that allow adequate detection and measurement of this disorder is the first step for adequate treatment (Cassiani-Miranda, P\u0026eacute;rez-An\u0026iacute;bal, Vargas-Hern\u0026aacute;ndez, Herazo-Bustos, \u0026amp; Cabarcas-Tovar, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sun et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOne of the most widely used screening tests worldwide is the 9-item version of the Patient Health Questionnaire-9 (PHQ-9). Each of the items corresponds to the diagnostic criteria of the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders. They are assessed on a scale of 0 to 3 (0\u0026thinsp;=\u0026thinsp;never; 3\u0026thinsp;=\u0026thinsp;almost every day). The PHQ-9 has the advantage of being a short, self-administered, easy-to-fill questionnaire that, in addition to serving for the diagnosis of depression, also allows the severity of the disorder to be assessed (Molebatsi, Motlhatlhedi, \u0026amp; Wambua, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sun et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAccording to Kroenke (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) the PHQ-9 is the most widely used depression screening scale in the world. Its international popularity is due to multiple factors. First, the nine items of this scale encompass the DSM criteria for depressive disorders, which allows it to be a diagnostic tool and a measure of the severity of the disorder. On the other hand, the total score is obtained by simply adding the item scores, and the cut-off points are easily memorized: 5, 10, 15 and 20, which represent thresholds for mild, moderate, moderately severe and severe depressive symptoms, respectively. Finally, it should be noted that unlike some depression scales, the PHQ-9 is available as public domain and is free to use.\u003c/p\u003e \u003cp\u003eThe PHQ-9 has been translated and validated in multiple languages and contexts: Spanish, French, Chinese, Korean, Thai, Greek, Arabic, Somali and Sinhalese, for example. Similarly, its specificity (0.71\u0026ndash;0.84), sensitivity (0.90\u0026ndash;0.97) (Wittkampf, Naeije, Schene, Huyser, \u0026amp; van Weert, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), reliability and validity have been evaluated and verified in many countries, both in clinical and non-clinical contexts (Baader et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Cassiani-Miranda et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Dajpratham et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Hanwella, Ekanayake, \u0026amp; de Silva, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Martin, Rief, Klaiberg, \u0026amp; Braehler, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Molebatsi et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sun et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRecently Bianchi et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) performed an analysis of the PHQ-9 by integrating data from 29 samples from seven different countries (e.g., Germany, USA) and five different languages (e.g., German, English). The integration of these samples resulted in a total of 58,272 participants (63% female; Mage\u0026thinsp;=\u0026thinsp;43, SDage\u0026thinsp;=\u0026thinsp;13), the largest sample size study to date. The psychometric results indicate that the satisfactory psychometric properties are maintained in the different samples, with no differences according to sex, age and language. Thus, the unidimensionality of the PHQ-9 was verified both in the pooled sample and in the subsamples (factor loadings between 0.72 and 0.89). In the same way, the internal consistency of the PHQ-9 was verified by obtaining Omega values above ,90. Taken together, these results provide solid evidence of the PHQ-9 for its use at the professional level and for research purposes.\u003c/p\u003e \u003cp\u003eDespite the empirical support of the PHQ-9 and its wide international use, no specific studies have been found in the Dominican Republic that have evaluated its validity and reliability. Indeed, it is required to verify whether the psychometric properties are adequate in this context, or whether adjustments in its content or structure are required (Cassiani-Miranda et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Taking this into consideration, the following objectives are proposed in the present study: a) to examine the internal structure of the PHQ-9 in the Dominican population; b) to verify internal consistency; c) to obtain evidence of criterion validity. In case of verifying that the scores obtained by means of the PHQ-9 have adequate psychometric properties in the context of the Dominican Republic, it will provide a screening tool for the early detection of this disorder in a better clinical and non-clinical context.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eThe study included the participation of 1437 individuals, 72.1% of whom were women and 27.9% were men, representing a diverse sample of the native population of the Dominican Republic. Participants ranged in age from 18 to 72 years, reflecting a wide variety of experiences and perspectives. The mean age of participants was 33.69 years, with a standard deviation of 11.18, indicating some variability in the distribution of ages within the sample.\u003c/p\u003e \u003cp\u003eFor the selection of participants, accidental non-probability sampling was used, which allowed the inclusion of individuals from diverse sociodemographic and geographic contexts in the Dominican Republic. This sampling strategy was chosen to guarantee the representativeness of the sample and to capture the heterogeneity of the Dominican population in terms of age, gender and other relevant factors.\u003c/p\u003e \u003cp\u003eData collection was conducted online, using accessible and secure digital platforms. Before participating in the study, all individuals provided informed consent, thus ensuring their full understanding and willingness to participate in the research.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eInstruments\u003c/h2\u003e \u003cp\u003e \u003cem\u003ePatient Health Questionnaire (PHQ-9)\u003c/em\u003e: evaluates depressive symptomatology during the last two weeks by means of 9 items, using a four-alternative Likert-type response scale ranging from 0 (no days) to 3 (almost every day). The PHQ-9 scale scores assess 5 categories of depressive disorder: none (0\u0026ndash;4 points), mild (5\u0026ndash;9 points), moderate (10\u0026ndash;14 points), moderately severe (15\u0026ndash;19 points) and severe (20\u0026ndash;27 points). For this study, the Spanish version of the PHQ-9 (Diez-Quevedo, Rangil, Sanchez-Planell, Kroenke, \u0026amp; Spitzer, 2001) was used, which has been shown to possess satisfactory sensitivity (0.84) and excellent specificity (0.92) compared to the Structured Clinical Interview, considered the gold standard at the time of assessment (Huarcaya-Victoria et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mu\u0026ntilde;oz Navarro et al., 2017).\u003c/p\u003e \u003cp\u003e \u003cem\u003eGeneralized Anxiety Disorder-7 Scale\u003c/em\u003e (GAD-7) is an instrument that has been designed to identify probable cases of generalized anxiety (Spitzer et al., 2006). It is composed of 7 items with a Likert-type response mode, which includes options from 0 (no day) to 3 (almost every day). For its correction, a direct score is obtained from the sum of the scores of all the items, which can fluctuate between 0 and 21. The original version has a good level of reliability, as well as criterion, construct, factorial and procedural validity. A cut-off point greater than or equal to 10 was identified, which optimized sensitivity (89%) and specificity (82%) (Spitzer et al., 2006). On the other hand, there are no established cut-off points for the Spanish version. Considering the 10-point cut-off, sensitivity values of 86.8% and specificity of 93.4% were found. Regarding internal consistency, an adequate homogeneity was verified (Cronbach's alpha\u0026thinsp;=\u0026thinsp;0.93). Likewise, the scale correlated significantly with the following instruments: Hamilton Anxiety Rating Scale (HAM-A) (.852, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), the Hospital Anxiety and Depression Scale (HADS) (anxiety domain, .903, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and the World Health Organization Disability Assessment Questionnaire (WHO-DAS II) (.696, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) (Garc\u0026iacute;a-Campayo et al., 2010).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003e \u003cem\u003eDimensionality assessment.\u003c/em\u003e An analysis of the underlying structure of the Patient Health Questionnaire Scale (PHQ-9) was conducted employing parallel analysis, a technique suggested in academic studies for the exploration of dimensions (Cho et al., 2009; Garrido et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Horn, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1965\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eFactor modeling specifications and fit criteria.\u003c/em\u003e Construct validity was examined using confirmatory factor analysis (CFA). For this purpose, the DWLS (Diagonally Weighted Least Square) method was selected as the estimation technique, highlighting its suitability for working with ordinal variables (Forero et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Nye \u0026amp; Drasgow, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The adequacy of the AFC-derived model was determined using various fit indices: the comparative fit index (CFI), the root mean square error of approximation (RMSEA), the root mean square standardized residual (SRMR) and the Tucker-Lewis Index (TLI) (Kline, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Hu \u0026amp; Bentler, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). For the CFI and TLI, values of .90 and .95, respectively, are interpreted as acceptable and excellent. For the RMSEA, values below .08 are considered adequate and those below .05 excellent (Schermelleh-Engel et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Regarding the SRMR, values of .05 or less are understood as indicative of a good fit, and values between .05 and .08 as acceptable fit (Kline, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Hu and Bentler, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1999\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eReliability analysis.\u003c/em\u003e Reliability was assessed by internal consistency, using McDonald's Omega (Ꞷ) and Cronbach's Alpha (α) coefficients, with values above .70 being considered appropriate for both coefficients (F\u0026ouml;rster and Rojas, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Ventura and Caycho, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTreatment of missing data. The percentage of omitted responses on the PHQ-9 items was marginal (0.16%). In contexts where this proportion is less than 5%, as noted by Little et al. (2014), it is generally acceptable to use a simple imputation procedure. Attending to this recommendation, it was decided to implement imputation with the median to make up for missing values (Longford, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eSoftware for the analysis.\u003c/em\u003e Data management was carried out using IBM SPSS Statistics (Version 25). For the calculation of descriptive statistics, Spearman's correlation, reliability analyses and confirmatory factor analysis (CFA), JASP software (version 0.17.1) was used. The polychoric correlations were calculated with the Mplus software (version 7.4).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe mean values of the PHQ-9 items showed variation, with item 9 presenting the lowest mean (M\u0026thinsp;=\u0026thinsp;1.18) and item 3 the highest (M\u0026thinsp;=\u0026thinsp;2.16), reflecting trends toward responses in the moderate to high range within the scale. Standard deviations indicated consistent variability across items, with the smallest dispersion in item 9 (SD\u0026thinsp;=\u0026thinsp;0.568) and the largest in item 5 (SD\u0026thinsp;=\u0026thinsp;1.10), suggesting a homogeneous distribution of responses across items. Skewness ranged from a slight skewness in item 3 (Skewness\u0026thinsp;=\u0026thinsp;0.53) to a noticeable skewness in item 9 (Skewness\u0026thinsp;=\u0026thinsp;3.65), pointing to a skew in responses toward one of the extremes of the scale, particularly in item 9.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eDescriptive statistics and polychoric correlations of the Patient Health Questionnaire (PHQ-9) items.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eItem/Statistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e \u003cp\u003eScale of the Patient Health Questionnaire (PHQ-9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e8\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.80**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.58**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.61**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.64**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.68**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.61**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.56**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.56**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.59**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.62**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.57**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.66**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.52**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.54**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.54**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.56**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.64**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.58**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.61**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.52**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.63**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.51**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.60**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.51**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.53**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.56**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.56**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.65**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.55**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.67**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.47**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.48**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.50**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.74**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e.54**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.59**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsymmetry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSex Differences in Anxiety: Results of the PHQ-9\u003c/h2\u003e \u003cp\u003eGiven the non-normal distribution of the data by group, the Mann-Whitney U test was applied to determine the differences in PHQ-9 scores between the male (n\u0026thinsp;=\u0026thinsp;246) and female (n\u0026thinsp;=\u0026thinsp;668) groups. One case that selected the \"Other\" option was omitted from the analysis (n\u0026thinsp;=\u0026thinsp;1). The findings indicated a significant difference in median PHQ-9 scores for males (median\u0026thinsp;=\u0026thinsp;13, interquartile range\u0026thinsp;=\u0026thinsp;7) and females (median\u0026thinsp;=\u0026thinsp;16, interquartile range\u0026thinsp;=\u0026thinsp;8), with a U value\u0026thinsp;=\u0026thinsp;101752.5, p\u0026thinsp;\u0026lt;\u0026thinsp;.001. This suggests that the levels of depressive symptomatology reported by women were significantly higher compared to those of men. The effect size, calculated as, rrb\u0026thinsp;=\u0026thinsp;.24, indicates a small effect size.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eScale dimensionality\u003c/h2\u003e \u003cp\u003eTo investigate the underlying structure of the Patient Health Questionnaire (PHQ-9), a parallel analysis was performed which indicated that only one factor should be retained. Specifically, the eigenvalue of the first factor obtained from the real data was 5.69, notably higher than the eigenvalue of 1.15 obtained from the first factor in the simulated data. In contrast, the second factor of the real data showed an eigenvalue of 0.74, which was lower than the eigenvalue of 1.10 found in the simulated data, indicating that this second factor lacked relevance and should not be retained. The principal axis factorization technique with a Promax rotation was used for this analysis. This factor was able to explain 59% of the total variance, indicating that a significant proportion of the variance is explained by a single factor, thus reflecting a strong and consistent unidimensional structure in the data set examined.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eConfirmatory factor analysis\u003c/h2\u003e \u003cp\u003eFollowing the theoretical model and the analysis of the dimensional structure performed, an evaluation of the model fit was carried out through a confirmatory factor analysis. The evaluated model demonstrated an excellent fit, as observed by the chi-square indices χ\u0026sup2; (14)\u0026thinsp;=\u0026thinsp;38.56 (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), Comparative Fit Index (CFI)\u0026thinsp;=\u0026thinsp;0.99 and Tucker-Lewis Index (TLI)\u0026thinsp;=\u0026thinsp;0.99, and a reasonably good fit with a Root Mean Square Error of Approximation (RMSEA)\u0026thinsp;=\u0026thinsp;.064 (90% CI\u0026thinsp;=\u0026thinsp;.054, .076) and Standard RMSR\u0026thinsp;=\u0026thinsp;0.051. The factor loadings for each scale item were found to be significant and exhibited high values (\u0026ge;\u0026thinsp;.72), indicating a strong and significant association with the proposed factor.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eReliability\u003c/h2\u003e \u003cp\u003eThis section analyzes the consistency of the participants' responses through McDonald's Omega and Cronbach's Alpha coefficients. The importance of this consistency analysis lies in its ability to verify whether the items of the instrument reliably measure the construct they intend to assess, as highlighted by F\u0026ouml;rster and Rojas (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) and Ventura and Caycho (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The results obtained for McDonald's Omega (Ꞷ= .891) and for Cronbach's alpha (α\u0026thinsp;=\u0026thinsp;.886) demonstrate a high internal consistency of the scale. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e details the item-level statistics, showing that each item contributes to the reliability of the scale, evidenced by both the McDonald omega coefficient and Cronbach's alpha. The item-total correlation indices exceed the value of .40, indicating that each item possesses exceptional discrimination, in agreement with Hingorjo and Jaleel (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eReliability statistics of individual items\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eIf item is deleted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eMcDonald's ω\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eCronbach's α\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eItem-to-rest correlation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.682\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.870\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.755\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.874\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.874\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.868\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.873\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.870\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.671\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.877\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.586\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.885\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCriterion validity\u003c/h2\u003e \u003cp\u003eGiven the absence of bivariate normality in the scores obtained from the GAD-7 and the PHQ-9 (Shapiro-Wilk\u0026thinsp;=\u0026thinsp;0.974, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), it was decided to use Spearman's correlation method instead of Pearson's correlation method. Such analysis indicated a positive, strong and significant correlation between both scales (ρ\u0026thinsp;=\u0026thinsp;.73, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), which implies that high levels of depressive symptomatology, measured through the PHQ-9, are related to high levels of anxiety symptoms, assessed through the GAD-7. The strong correlation observed between these two instruments points to a significant relationship between anxiety and depressive symptoms, supporting claims found in previous studies (Sawaya et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Pranckeviciene et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe PHQ-9 is the most widely used depression screening scale in the world. By contemplating the DSM criteria for depressive disorders, it is a useful tool both for diagnostic purposes and for assessing the severity of the disorder. Despite its wide international use, there are no studies that have examined its psychometric properties in the Dominican Republic. Not having valid and reliable psychometric instruments to assess depression entails a number of problems. First, there is less capacity to make accurate diagnoses, resulting in incorrect or incomplete detection of depressive symptoms (Calder\u0026oacute;n et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Molebatsi et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In addition, not having tools to assess the presence of symptoms and severity of the disorder can lead to misdiagnosis and, consequently, inadequate treatment. In addition to the practical limitations, not having this type of tool limits the possibilities for research on depression, making it difficult to achieve a deeper understanding that is adjusted to the cultural and social characteristics of the Dominican Republic.\u003c/p\u003e \u003cp\u003eGiven this gap in the literature, the present study aimed to examine the psychometric properties of the PHQ-9. In general terms, satisfactory evidence was found regarding the validity and reliability of the PHQ-9 in the Dominican population. When examining the internal structure, the satisfactory fit of a unidimensional model was verified. Indeed, the results of the parallel analysis indicated the existence of a single underlying factor that explains 59% of the variability. On the other hand, the fit indices of the confirmatory factor analysis were satisfactory and the factor loadings of each item in the scale were significant and showed high values. These results indicate a solid unidimensional structure consistent with the results obtained in previous research (Bianchi et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRegarding reliability, a thorough evaluation of internal consistency was carried out using both McDonald's Omega coefficient (Ꞷ) and Cronbach's Alpha coefficient (α). The results obtained revealed satisfactory values for both coefficients, exceeding the established threshold of 0.70 recommended by the specialized literature (F\u0026ouml;rster and Rojas, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Ventura and Caycho, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). These findings are similar to those reported in previous research (Bianchi et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Mu\u0026ntilde;oz Navarro et al., 2017), and suggest that the scale items consistently measure the construct.\u003c/p\u003e \u003cp\u003eFinally, examining the relationship with external variables corroborates a significant association between PHQ-9 and GAD-7 scores. The obtained results provide evidence of criterion validity by verifying a strong relationship between anxiety and depression symptoms as reported in previous research (Sawaya et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Pranckeviciene et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs a whole, the results obtained support the use of PHQ-9 as a reliable and valid tool for the assessment of depression, providing a solid basis for the interpretation of the scores obtained and for making clinical or research decisions based on them.\u003c/p\u003e \u003cp\u003eBased on the present work, mental health professionals in the Dominican Republic will have a low-cost screening tool for the early detection of depression. It should be noted that the PHQ-9 also allows an assessment of severity, thus providing useful information for the design of interventions adapted to the level of severity of depression manifested by the patient (Kroenke, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Having this tool will improve the treatment of depression and increase the volume of research on this disorder in the Dominican context.\u003c/p\u003e \u003cp\u003eIt is important to note that despite the efforts made, the present study has a number of limitations to consider. First, the study sample was selected through a non-probabilistic sample and with participants from the general population. It would be beneficial for future research to consider clinical samples. On the other hand, it should be noted that no analyses were performed to analyze the sensitivity and specificity of the PHQ-9. Although previous literature indicates that the PHQ-9 has adequate diagnostic accuracy (Diez-Quevedo et al., 2001; Huarcaya-Victoria et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mu\u0026ntilde;oz Navarro et al., 2017), future research would be desirable to provide additional evidence in the Dominican context.\u003c/p\u003e \u003cp\u003eDespite all limitations, we note that this is the first study to demonstrate the construct validity and reliability of the PHQ-9 in Dominican population. Mental health in the Dominican Republic emerges as a major concern, especially in light of alarming data provided by the World Health Organization (WHO). According to WHO reports, approximately 4.7% of the Dominican population suffers from depressive disorders, and 5.7% suffers from anxiety disorders (WHO, 2017). Unfortunately, a growth in these figures is projected if the situation of mental health services in the country is not improved, and technical tools are not developed to improve the quality of the treatments provided (Ministry of Public Health, 2020). We hope that this study will help to change this situation and contribute to improving the capacity to detect and evaluate depression in the Dominican Republic.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was financed by the Fondo Nacional de Innovaci\u0026oacute;n y Desarrollo Cient\u0026iacute;fico y Tecnol\u0026oacute;gico (FONDOCYT) of the Dominican Republic, (Project Code: 2022-3A1-241), for which we thank them.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics Approval and Consent to Participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRespect for all bioethical principles and codes has been an essential pillar in each of the phases of the PsicAP project in the Dominican Republic. Due to this, all the methodology in this study follows the relevant guidelines and regulations to guarantee ethical prowess, following the Declaration of Helsinki. From the onset, participants were aware of the potential benefits and risks associated with the study, only included in the project after signing the informed consent voluntarily. Through this, they learned they could withdraw from the study during any of its phases if necessary. Likewise, respect for the confidentiality and anonymity of all participants was ensured, in part, by storing the data in secure and encrypted systems.\u003c/p\u003e\n\u003cp\u003eTo ensure respect and ethical monitoring throughout the study, the project has been submitted to institutional bioethics committees (Faculty of Health Sciences Bioethics Committee [COBEFACS] at the Mother and Teacher Pontifical Catholic University [PUCMM], Dominican Republic) and received approval on July 14, 2020 (registry code: COBE-FACS-EXT-00-1-2022-2023). Additionally, the study received approval from the national committee (National Health Bioethics Committee [CONABIOS], Dominican Republic) on September 8, 2020 (registry code: 021-2023).\u003cstrong\u003e\u003cem\u003e\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eDeclaration of Data Availability\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData sharing for this manuscript is not applicable given that no datasets were generated during this specific study. However, this study is part of a larger study which will contain datasets. Information regarding the data of this project is available upon request from the corresponding author Z.E.G.B.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eDeclaration of Competing Interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo, I declare that the authors have no competing interests, or other interests that might be perceived to influence the results and/or discussion reported in this paper.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAsociaci\u0026oacute;n Americana de Psiquiatr\u0026iacute;a (2013). \u003cem\u003eGu\u0026iacute;a de consulta de los criterios diagn\u0026oacute;sticos del DSM 5. \u003c/em\u003eArlington, VA: Asociaci\u0026oacute;n Americana de Psiquiatr\u0026iacute;a.\u003c/li\u003e\n\u003cli\u003eBaader, T., Molina, J. L., Venezian, S., Rojas, C., Far\u0026iacute;as R., Fierro-Freixeneta, C., Backenstrass, M., \u0026amp; Mundt, C. (2012). Validaci\u0026oacute;n y utilidad de la encuesta PHQ-9 (Patient Health Questionnaire) en el diagn\u0026oacute;stico de depresi\u0026oacute;n en pacientes usuarios de atenci\u0026oacute;n primaria en Chile. \u003cem\u003eRevista chilena de neuro-psiquiatr\u0026iacute;a, 50\u003c/em\u003e(1), 10-22. https://dx.doi.org/10.4067/S0717-92272012000100002\u003c/li\u003e\n\u003cli\u003eBianchi, R., Verkuilen, J., Toker, S., Schonfeld, I. S., Gerber, M., Br\u0026auml;hler, E., \u0026amp; Kroenke, K. (2022). Is the PHQ-9 a unidimensional measure of depression? A 58,272-participant study. \u003cem\u003ePsychological Assessment, 34\u003c/em\u003e(6), 595-603. https://doi.org/10.1037/pas0001124\u003c/li\u003e\n\u003cli\u003eCalder\u0026oacute;n, M., G\u0026aacute;lvez-Buccollini, J. A., Cueva, G., Ordo\u0026ntilde;ez, C., Bromley, C., \u0026amp; Fiestas, F. (2012). Validaci\u0026oacute;n de la versi\u0026oacute;n peruana del PHQ-9 para el diagn\u0026oacute;stico de depresi\u0026oacute;n. \u003cem\u003eRevista Peruana de Medicina Experimental y Salud Publica, 29\u003c/em\u003e(4), 578-585. \u003c/li\u003e\n\u003cli\u003eCassiani-Miranda, C.A., P\u0026eacute;rez-An\u0026iacute;bal, E., Vargas-Hern\u0026aacute;ndez, M.C., Herazo-Bustos, M., \u0026amp; Cabarcas-Tovar, A. (2018). Validez de apariencia y adaptaci\u0026oacute;n de la escala PHQ-9 para la detecci\u0026oacute;n de sintomatolog\u0026iacute;a depresiva en universitarios de ciencias de la salud de Cartagena (Colombia). \u003cem\u003eSalud Uninorte, 34\u003c/em\u003e(1), 75-87.\u003c/li\u003e\n\u003cli\u003eDajpratham, P., Pukrittayakamee, P., Atsariyasing, W., Wannarit, K., Boonhong, J., \u0026amp; Pongpirul, K. (2020). The validity and reliability of the PHQ-9 in screening for post-stroke depression. \u003cem\u003eBMC Psychiatry, 20\u003c/em\u003e(291). https://doi.org/10.1186/s12888-020-02699-6\u003c/li\u003e\n\u003cli\u003eFekadu, A., Demissie, M., Birhane, R., Medhin, G., Bitew, T., Hailemariam, M.\u0026amp; Prince, M. (2022). Under detection of depression in primary care settings in low and middle-income countries: a systematic review and meta-analysis. \u003cem\u003eSystematic Reviews\u003c/em\u003e, 11(1), 21.\u003c/li\u003e\n\u003cli\u003eForero, C. G., Maydeu-Olivares, A., y Gallardo-Pujol, D. (2009). Factor analysis with ordinal indicators: A Monte Carlo study comparing DWLS and ULS estimation. \u003cem\u003eStructural Equation Modeling: A Multidisciplinary Journal\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e(4), 625\u0026ndash;641.\u003c/li\u003e\n\u003cli\u003eF\u0026ouml;rster, C., \u0026amp; Rojas, C. (2008). Evaluaci\u0026oacute;n al interior del aula: una mirada desde a validez, confiabilidad y objetividad. \u003cem\u003eRevista Pensamiento Educativo, 43\u003c/em\u003e(2), 285-305.\u003c/li\u003e\n\u003cli\u003eFried, E. I., Flake, J. K., \u0026amp; Robinaugh, D. J. (2022). Revisiting the theoretical and methodological foundations of depression measurement. \u003cem\u003eNature Reviews Psychology, \u003c/em\u003e1(6), 358-368.\u003c/li\u003e\n\u003cli\u003eGarc\u0026iacute;a-Batista ZE, Guerra-Pe\u0026ntilde;a K, Cano-Vindel A, Herrera-Mart\u0026iacute;nez SX \u0026amp; Medrano LA. (2018). Validity and reliability of the Beck Depression Inventory (BDI-II) in general and hospital population of Dominican Republic. \u003cem\u003ePLoS One\u003c/em\u003e. 29;13(6):e0199750. doi: 10.1371/journal.pone.0199750. PMID: 29958268; PMCID: PMC6025862.\u003c/li\u003e\n\u003cli\u003eGarrido, L. E., Abad, F. J., \u0026amp; Ponsoda, V. (2013). A new look at Horn\u0026rsquo;s parallel analysis with ordinal variables. Psychological Methods, 18(4), 454\u0026ndash;474. https://doi.org/10.1037/a0030005\u003c/li\u003e\n\u003cli\u003eGold, S. M., K\u0026ouml;hler-Forsberg, O., Moss-Morris, R., Mehnert, A., Miranda, J. J., Bullinger, M., \u0026amp; Otte, C. (2020). Comorbid depression in medical diseases. \u003cem\u003eNature Reviews Disease Primers, 6\u003c/em\u003e(1), 69.\u003c/li\u003e\n\u003cli\u003eHanwella, R., Ekanayake, S., \u0026amp; de Silva, V.A. (2014). The validity and reliability of the Sinhala translation of the Patient Health Questionnaire (PHQ-9) and PHQ-2 screener. \u003cem\u003eDepression Research and Treatment, 2014\u003c/em\u003e. http://dx.doi.org/10.1155/2014/768978\u003c/li\u003e\n\u003cli\u003eHingorjo, M., \u0026amp; Jaleel, F. (2012). Analysis of One-Best MCQs: The Difficulty Index, Discrimination Index and Distractor Efficiency . \u003cem\u003eJournal of the Pakistan Medical Association, 62\u003c/em\u003e(2), 142-147.\u003c/li\u003e\n\u003cli\u003eHogan, T. (2015). \u003cem\u003ePruebas psicol\u0026oacute;gicas: Una introducci\u0026oacute;n pr\u0026aacute;ctica.\u003c/em\u003e http://cort.as/-PVTd\u003c/li\u003e\n\u003cli\u003eHorn, J. L. (1965). A rationale and test for the number of factors in factor analysis. \u003cem\u003ePsychometrika\u003c/em\u003e, \u003cem\u003e30\u003c/em\u003e, 179-185. https://doi.org/10.1007/BF02289447\u003c/li\u003e\n\u003cli\u003ehttp://www.scielo.org.mx/scielo.php?script=sci_arttext\u0026amp;pid=S0026-17422013000400009\u003c/li\u003e\n\u003cli\u003eHu, L.-T., y Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. \u003cem\u003eStructural equation modeling: a multidisciplinary journal\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e(1), 1\u0026ndash;55.\u003c/li\u003e\n\u003cli\u003eHuarcaya-Victoria, J., De-Lama-Mor\u0026aacute;n, R., Quiros, M., Baz\u0026aacute;n, J., L\u0026oacute;pez, K. and Lora, D., 2020. Propiedades psicom\u0026eacute;tricas del Patient Health Questionnaire (PHQ-9) en estudiantes de medicina en Lima, Per\u0026uacute;. \u003cem\u003eRevista de Neuro-Psiquiatria\u003c/em\u003e, 83(2), pp.72-78.\u003c/li\u003e\n\u003cli\u003eKline, R. B. (2023). \u003cem\u003ePrinciples and practice of structural equation modeling\u003c/em\u003e. Guilford publications.\u003c/li\u003e\n\u003cli\u003eKroenke K. (2021) PHQ-9: global uptake of a depression scale. \u003cem\u003eWorld Psychiatry\u003c/em\u003e. 2021 Feb;20(1):135-136. doi: 10.1002/wps.20821. PMID: 33432739; PMCID: PMC7801833.\u003c/li\u003e\n\u003cli\u003eLongford, N. T. (2005). \u003cem\u003eMissing data and small-area estimation: Modern analytical equipment for the survey statistician\u003c/em\u003e. Springer Science \u0026amp; Business Media.\u003c/li\u003e\n\u003cli\u003eL\u0026ouml;we, B., Gr\u0026auml;fe, K., Zipfel, S., Spitzer, R. L., Herrmann-Lingen, C., Witte, S., \u0026amp; Herzog, W. (2003). Detecting panic disorder in medical and psychosomatic outpatients: comparative validation of the Hospital Anxiety and Depression Scale, the Patient Health Questionnaire, a screening question, and physicians\u0026apos; diagnosis. \u003cem\u003eJournal of psychosomatic research\u003c/em\u003e, \u003cem\u003e55\u003c/em\u003e(6), 515\u0026ndash;519. https://doi.org/10.1016/s0022-3999(03)00072-2\u003c/li\u003e\n\u003cli\u003eMartin, A., Rief, W., Klaiberg, A., \u0026amp; Braehler, E. (2006). Validity of the Brief Patient Health Questionnaire Mood Scale (PHQ-9) in the general population. \u003cem\u003eGeneral Hospital Psychiatry, 28\u003c/em\u003e(1), 71\u0026ndash; 77. http://dx.doi.org/10.1016/j.genhosppsych.2005.07.003\u003c/li\u003e\n\u003cli\u003eMinisterio de Salud P\u0026uacute;blica. (2020). \u003cem\u003eMSP: La depresi\u0026oacute;n es la principal causa de suicidios en la Rep\u0026uacute;blica Dominicana.\u003c/em\u003e https://www.msp.gob.do/web/?p=8481\u003c/li\u003e\n\u003cli\u003eMolebatsi, K., Motlhatlhedi, K., \u0026amp; Wambua, G.N. (2020). The validity and reliability of the Patient Health Questionnaire-9 for screening depression in primary health care patients in Botswana. \u003cem\u003eBMC Psychiatry, 20\u003c/em\u003e(295). https://doi.org/10.1186/s12888-020-02719-5\u003c/li\u003e\n\u003cli\u003eMontero, I. \u0026amp; Le\u0026oacute;n, O. G. (2007). A guide for naming research studies in Psychology. \u003cem\u003eInternational Journal of Clinical and Health Psychology, 7\u003c/em\u003e (3), 847-862.\u003c/li\u003e\n\u003cli\u003eMu\u0026ntilde;oz-Navarro, R., Cano-Vindel, A., Wood, C. M., Ru\u0026iacute;z-Rodr\u0026iacute;guez, P., Medrano, L. A., \u0026amp; Limonero, J. T., et al. (2016). The PHQ-PD as a Screening Tool for Panic Disorder in the Primary Care Setting in Spain. \u003cem\u003ePLoS ONE, 11\u003c/em\u003e(8), e0161145. https://doi.org/10.1371/journal.pone.0161145\u003c/li\u003e\n\u003cli\u003eNye, C. D., \u0026amp; Drasgow, F. (2011). Assessing goodness of fit: Simple rules of thumb simply do not work. \u003cem\u003eOrganizational Research Methods\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(3), 548-570.\u003c/li\u003e\n\u003cli\u003eOrganizaci\u0026oacute;n Mundial de la Salud. (2017). Depression and Other Common Mental Disorders: Global Health Estimates. Ginebra: Organizaci\u0026oacute;n Mundial de la Salud. \u003c/li\u003e\n\u003cli\u003eOrganizaci\u0026oacute;n Mundial de la Salud. (2020).\u003cem\u003e Depression. \u003c/em\u003ehttps://www.who.int/news-room/fact-sheets/detail/depression\u003c/li\u003e\n\u003cli\u003ePranckeviciene A, Saudargiene A, Gecaite-Stonciene J, Liaugaudaite V, Griskova-Bulanova I, Simkute D, Naginiene R, Dainauskas LL, Ceidaite G, Burkauskas J. Validation of the patient health questionnaire-9 and the generalized anxiety disorder-7 in Lithuanian student sample. PLoS One. 2022 Jan 27;17(1):e0263027. doi: 10.1371/journal.pone.0263027. PMID: 35085349; PMCID: PMC8794093.\u003c/li\u003e\n\u003cli\u003eSawaya, H., Atoui, M., Hamadeh, A., Zeinoun, P., \u0026amp; Nahas, Z. (2016). Adaptation and initial validation of the Patient Health Questionnaire\u0026ndash;9 (PHQ-9) and the Generalized Anxiety Disorder\u0026ndash;7 Questionnaire (GAD-7) in an Arabic speaking Lebanese psychiatric outpatient sample. \u003cem\u003ePsychiatry research\u003c/em\u003e, \u003cem\u003e239\u003c/em\u003e, 245-252.\u003c/li\u003e\n\u003cli\u003eSchermelleh-Engel, K., Moosbrugger, H., \u0026amp; M\u0026uuml;ller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. \u003cem\u003eMethods of psychological research online\u003c/em\u003e, 8(2), 23-74.\u003c/li\u003e\n\u003cli\u003eSpitzer, R. L., Kroenke, K., \u0026amp; Williams, J. B. (1999). Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. Primary Care Evaluation of Mental Disorders. Patient Health Questionnaire. \u003cem\u003eJAMA\u003c/em\u003e, \u003cem\u003e282\u003c/em\u003e(18), 1737\u0026ndash;1744. https://doi.org/10.1001/jama.282.18.1737\u003c/li\u003e\n\u003cli\u003eSteffen, A., N\u0026uuml;bel, J., Jacobi, F. et al. Mental and somatic comorbidity of depression: a comprehensive cross-sectional analysis of 202 diagnosis groups using German nationwide ambulatory claims data. \u003cem\u003eBMC Psychiatry\u003c/em\u003e, 20, 142 (2020). https://doi.org/10.1186/s12888-020-02546-8\u003c/li\u003e\n\u003cli\u003eSun, Y., Fu, Z., Bo, Q., Mao, Z., Ma, X., \u0026amp; Wang, C. (2020). The reliability and validity of PHQ-9 in patients with major depressive disorder in psychiatric hospital. \u003cem\u003eBMC Psychiatry, 20\u003c/em\u003e(474). https://doi.org/10.1186/s12888-020-02885-6\u003c/li\u003e\n\u003cli\u003eVentura, J., \u0026amp; Caycho, T. (2017). El coeficiente Omega: un m\u0026eacute;todo alternativo para la estimaci\u0026oacute;n de la confiabilidad. \u003cem\u003eRevista Latinoamericana de Ciencias Sociales, Ni\u0026ntilde;ez y Juventud, 15\u003c/em\u003e(1), 625-627.\u003c/li\u003e\n\u003cli\u003eWittkampf, K. A., Naeije, L., Schene, A. H., Huyser, J., \u0026amp; van Weert, H. C. (2007). Diagnostic accuracy of the mood module of the Patient Health Questionnaire: A systematic review. \u003cem\u003eGeneral Hospital Psychiatry, 29\u003c/em\u003e(5), 388\u0026ndash;395. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"PHQ-9, Depression, Psychometric Validation, Dominican Republic, Mental Health","lastPublishedDoi":"10.21203/rs.3.rs-4586950/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4586950/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe PHQ-9 is a globally recognized and widely used tool for screening depression. Its importance lies in its ability to assess the DSM criteria for depressive disorders, allowing both diagnosis and assessment of the severity of the condition. However, despite its prevalence internationally, no comprehensive studies on its psychometric properties have been carried out in the Dominican Republic. This lack of reliable and valid psychometric instruments to assess depression entails several significant challenges. On the one hand, it limits diagnostic accuracy, which may result in incorrect or incomplete detection of depressive symptoms. In addition, it hinders proper assessment of the symptomatology and severity of the disorder, which could lead to inappropriate treatments. It also restricts the possibilities for research on depression in the specific context of the Dominican Republic, which hinders a complete understanding of the disease in terms of its cultural and social characteristics.\u003c/p\u003e \u003cp\u003eTo address this gap in the literature, this study set out to examine the psychometric properties of the PHQ-9 in the Dominican population. For this purpose, we relied on the participation of 1437 Dominicans. The results obtained provide favorable evidence on validity and reliability. In terms of internal structure, a unidimensional model was found to explain a significant proportion of the variability in the responses. In addition, confirmatory analyses showed an excellent fit of the proposed model. In terms of reliability, both McDonald's Omega coefficient and Cronbach's Alpha coefficient yielded values above the accepted threshold of 0.70, indicating adequate internal consistency. Likewise, a strong association was verified between the PHQ-9 and GAD-7 scores, providing additional evidence of criterion validity. These results support previous findings and suggest that the PHQ-9 is a reliable and valid tool to assess depression in the Dominican population.\u003c/p\u003e","manuscriptTitle":"Psychometric properties of the Patient Health Questionnaire (PHQ-9) in the Dominican Republic","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-16 16:47:42","doi":"10.21203/rs.3.rs-4586950/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-12T14:04:05+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-21T11:20:58+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-18T02:50:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-14T12:54:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"44810132079382332455142035902728348948","date":"2025-11-05T11:00:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"18268259879961975540802378694701752721","date":"2025-11-03T01:28:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"110437240593752588734470885603508860105","date":"2025-11-02T15:37:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"172413483506403142215731385728936766330","date":"2025-11-01T17:19:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"69092741812135542927385170497941614985","date":"2025-10-31T18:24:28+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-23T22:54:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"184954013179360192718312390125740758090","date":"2024-07-13T18:37:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-21T09:41:48+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-06-20T18:39:49+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-20T18:31:18+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-19T04:36:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychology","date":"2024-06-15T14:33:51+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"744fdc3a-88a3-4b0a-b1c9-1ee2f6469876","owner":[],"postedDate":"July 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-11T09:56:37+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-16 16:47:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4586950","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4586950","identity":"rs-4586950","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}