Vol. 11/ Núm. 2 2024 pág. 3568

https://doi.org/10.69639/arandu.v11i2.522

Mental health assessment using Power BI: Development and

application of a dashboard for companies

Evaluación de salud mental mediante Power BI: Desarrollo y aplicación de un tablero

para empresas

Fernando Aguirre y Hernández

faguirre4093@gmail.com

https://orcid.org/0000-0002-7926-6789

Tecnológico Nacional de México / Instituto Tecnológico de Orizaba

Veracruz – México

Víctor Méndez García

vicmgarcia877@gmail.com

https://orcid.org/0009-0001-5619-7186

Tecnológico Nacional de México / Instituto Tecnológico de Orizaba

Veracruz – México

Edna Araceli Romero Flores

edna.rf@orizaba.tecnm.mx

https://orcid.org/0000-0001-9058-9346

Tecnológico Nacional de México / Instituto Tecnológico de Orizaba

Veracruz – México

Gabriela Cabrera Zepeda

gabriela.cz@orizaba.tecnm.mx

https://orcid.org/0000-0002-6302-6166

Tecnológico Nacional de México / Instituto Tecnológico de Orizaba

Veracruz – México

Guillermo Alfredo Arrioja Carrera

guillermo.ac@orizaba.tecnm.mx

https://orcid.org/0000-0003-3170-699X

Tecnológico Nacional de México / Instituto Tecnológico de Orizaba

Veracruz – México

Mauricio Romero Montoya

mauricio.rm@orizaba.tecnm.mx

https://orcid.org/0000-0002-4325-7717

Tecnológico Nacional de México / Instituto Tecnológico de Orizaba

Veracruz – México

Artículo recibido: 20 octubre 2024 - Aceptado para publicación: 26 noviembre 2024

Conflictos de intereses: Ninguno que declarar

ABSTRACT

This study focused on the creation and application of a mental health dashboard using Microsoft

Power BI and the DASS-21 scale to assess levels of stress, anxiety, and depression in two

companies: a productive one and a service one. The implemented methodology comprised three

main phases: the creation of Google Forms to collect data, the execution of the ETL process in

Vol. 11/ Núm. 2 2024 pág. 3569

Power BI, and the configuration of the dashboard. The results showed that the levels of stress,

anxiety, and depression in both organizations were mostly within normal parameters. However,

specific working areas and employees with critical levels of these disorders were identified,

providing each company with the information necessary to take appropriate measures. The

analysis by working areas revealed significant differences between departments, highlighting the

importance of adapting wellness strategies to the specific needs of each section. The use of the

Power BI dashboard proved to be an effective tool not only for general monitoring but also for

the precise identification of risk areas and the application of preventive and corrective measures.

Keywords: power bi, business intelligence, mental health, dashboard analysis

RESUMEN

Este estudio se centró en la creación y aplicación de un tablero de salud mental utilizando

Microsoft Power BI y la escala DASS-21 para evaluar los niveles de estrés, ansiedad y depresión

en dos empresas: una productiva y otra de servicios. La metodología implementada constó de tres

fases principales: la creación de Google Forms para la recolección de datos, la ejecución del

proceso ETL en Power BI y la configuración del tablero. Los resultados mostraron que los niveles

de estrés, ansiedad y depresión en ambas organizaciones se encontraban en su mayoría dentro de

los parámetros normales. Sin embargo, se identificaron áreas de trabajo específicas y empleados

con niveles críticos de estos trastornos, proporcionando a cada empresa la información necesaria

para tomar las medidas adecuadas. El análisis por áreas de trabajo reveló diferencias significativas

entre departamentos, destacando la importancia de adaptar las estrategias de bienestar a las

necesidades específicas de cada sección. El uso del tablero control de Power BI demostró ser una

herramienta eficaz no solo para el seguimiento general sino también para la identificación precisa

de áreas de riesgo y la aplicación de medidas preventivas y correctivas.

Palabras clave: power bi, inteligencia de negocios, salud mental, análisis tablero control

Todo el contenido de la Revista Científica Internacional Arandu UTIC publicado en este sitio está disponible bajo

licencia Creative Commons Atribution 4.0 International.

Vol. 11/ Núm. 2 2024 pág. 3570

INTRODUCTION

Society currently lives in a work environment that is deeply influenced by Industry 4.0

technologies, such as the Internet of Things (IoT), automated production and artificial Intelligence

(González Hernández et al., 2021). Furthermore, Joyanes Aguilar (2019) highlights the

importance of Business Intelligence=BI, which encompasses a set of tools capable of accessing

and analyzing data, offering summaries, maps and dashboards to provide detailed information for

timely, informed decisions, efficiency, and competitive advantage. This technological

environment imposes on employees the need to adopt an open mindset where it is essential that

they can adapt to the changing demands of their organizations and carry out their responsibilities

successfully. However, it is important to highlight that, on many occasions, a crucial aspect is

overlooked: the impact on the mental health of employees, a concern that is not always part of the

organizational culture of companies.

According to the Organización Mundial de la Salud (2022), approximately 60% of the

world's population is employed, and it is essential that all employees enjoy the right to work in a

safe and healthy work environment. It should be noted that poor work spaces often lead to

discrimination and inequality, as well as excessive working hours, lack of control at work and job

insecurity that result in a mental health risk. In 2019, 15% of working age adults were found to

experience a mental health disorder globally, and it is estimated that 12 billion days of work are

lost annually due to depression and anxiety, at a rate cost of $1 billion USD per year in terms of

productivity.

On the stress side, the consulting company Gall up Inc., found that the perceived work

stress by geographical area worldwide in workers is as follows: East Asia 55%, United States and

Canada 50%, Latin America and the Caribbean 50%, Australia and New Zealand 47%, Middle

East and North Africa 45%, Europe 39%, Sub-Saharan Africa 39%, South Asia 35%, Southeast

Asia 31%, and Commonwealth of Independent States 19 % (Inc, 2022). Mexico is the country

with the highest work stress with a value of 75%, followed by China 73% and the United States

59% (Organización Internacional del Trabajo, 2016).

In terms of health and safety, Mexico is regulated by the Federal Labor Law and Official

Mexican Standards. The NOM-035-STPS-2018 “Psychosocial risk factors at work-Identification,

analysis and prevention” contemplates those severe traumatic events as well as psychosocial risk

factors that can trigger the onset of a mental health disorder, in addition to 04 December 2023, an

update regarding the Table of Occupational Illnesses was already published in the Diario Oficial

de la Federación, which includes in group IV mental disorders such as: anxiety, non organic sleep-

wake cycle disorders, and disorders associated with stress and depression (Diario Oficial de la

Federación, 2023).

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As a result of the indicated statistics and in compliance with the regulatory framework for

safety and health at work, the timely detection of stress, depression and anxiety plays a crucial

role in the organizational field to mitigate the following problems: stress has a great potential for

impact work performance, as well as the ability to carry out activities, symptoms such as loss in

performance, physical and mental exhaustion (Delgado Espinoza et al., 2020; Velazquez Fuentes,

2022); Depression influences family dysfunction, job performance, premature abandonment or

withdrawal from the workplace, labor conflicts, decreased performance, increase in work

accidents, indecision, forgetfulness, concentration and effectiveness (Castellón Leal et al., 2016;

Mingote Adán et al., 2009; Yuan-Pang, 2017); and anxiety triggers irritability or frustration,

feeling overwhelmed when tackling tasks, missing deadlines, lack of concentration, excessive

worry that affects personal life, repetitive work-related thoughts, inappropriate responses to work

comments, and focusing on negative aspects (Vige, 2024)

Considering the problems arising from mental disorders, this study focused on the creation

and implementation of a mental health dashboard using Microsoft Power BI software and the

DASS-21 psychological scale (Depression, Anxiety, and Stress Scale) to evaluate the levels of

stress, anxiety, and depression among employees in organizations.

MATERIALS AND METHODS

Research design

The design of this study was non experimental, as the variables were not intentionally

manipulated but observed as they naturally occurred in their context. Additionally, a cross-

sectional approach was employed, as data was collected at a single point in time, allowing the

evaluation of stress, anxiety, and depression levels at a specific moment within the participating

organizations.

Instrument

Rating scales such as the Beck Inventory focus on somatic symptoms, but over time it was

recognized that non-somatic symptoms are equally relevant to depression, anxiety and stress, this

led to the development of the Depression Scales. Anxiety and Stress (DASS) by Lovibond and

Lovibond to measure these three negative emotional states, including non-somatic symptoms.

The DASS anxiety scale highlights symptoms related to fear, including situational anxiety and

generalized anxiety, while stress is differentiated from depression and anxiety, but may be related

to them due to the persistent response to stressors that it can give. This leads to maladaptive

behaviors that overlap with depression and anxiety (Medvedev, 2023).

The Depression, Anxiety and Stress Scale (DASS) was developed by Australian

psychologists Peter Lovibond and Stephen Lovibond, this scale has been widely used in the

assessment of depression, anxiety and stress levels in the general and clinical population. Initially,

the DASS scale consisted of 42 items (14 items for each subscale measuring depression and

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anxiety), however, the results of tests carried out between 1979 and 1990, together with a factor

analysis, revealed the existence of a third factor stress. It was suggested that this third factor could

be shared between anxiety and depression, but could still offer discriminative validity as an

individual subscale in the measure. Subsequently, an abbreviated version of the DASS-42 called

DASS-21 was created, which is an adaptation of the original 42-item version and is also used to

measure these three emotional states, including non-somatic symptoms. In addition to its use in

the clinical setting, the DASS-21 scale has been designed to be applied to any population of

interest; to date, it has been translated into more than 30 languages (J. Lee et al., 2019; Medvedev,

2023; Psychology Foundation of Australia, 2023).

The average Cronbach's alpha coefficient is 0.87, according to various sources for the

Depression, anxiety and stress scale DASS-21 (Abdulazis Alsaif, 2023; Al-Kalbani et al., 2022;

Bengwasan et al., 2022; Evans et al., 2021; Formiga et al., 2021; Hakim & Aristawati, 2023; Kaji

Thapa et al., 2022; Kakemam et al., 2022; Le et al., 2017; B. Lee & Kim, 2022; Makara-

Studzińska et al., 2022; Montenegro Bolaños, 2017; Moya et al., 2022; Pezirkianidis et al., 2018;

Ruiz et al., 2017; Simon & Bernardo, 2023; Teo et al., 2019; Thiyagarajan et al., 2022). This

high alpha coefficient guarantees that the items of the DASS-21 are highly consistent with each

other, making the scale a reliable instrument for measuring levels of depression, anxiety, and

stress in different contexts.

DASS-21 is made up of 7 items with a Likert-type response format with 4 alternatives

ranging from 0 to 3 points depending on the presence and intensity of each symptom in the last 7

days, 0=Did not apply to me at all, 1=Applied to me to some degree, or some of the time;

2=Applied to me a considerable degree or good part of time and 3=Applied to me very much, or

most of the time (Psychology Foundation of Australia, 2024). Table 1 shows the items associated

to each emotional state (stress, depression and anxiety) and Appendix A. includes the content of

the Scale DASS-21.

Table 1

Items associated to each emotional state for DASS-21 (Román et al., 2016)

Item

number

Emotional

State

Item

number

Emotional

State

Item

number

Emotional

State

3

Depression

2

Anxiety

1

Stress

5

Depression

4

Anxiety

6

Stress

10

Depression

7

Anxiety

8

Stress

13

Depression

9

Anxiety

11

Stress

16

Depression

15

Anxiety

12

Stress

17

Depression

19

Anxiety

14

Stress

21

Depression

20

Anxiety

18

Stress

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Regarding the rating of the scale, it is important to consider that the sum of each subscale must

be multiplied by 2 in order to identify the significance level for each emotional state, based on

Table 2:

Table 2

DASS severity ratings (Lovibond & Lovibond, 1995)

Significance level

Depression

Anxiety

Stress

Normal

0-9

0-7

0-14

Mild

10-13

8-9

15-18

Moderate

14-20

10-14

19-25

Severe

21-27

15-19

26-33

Extremely severe

28+

20+

34+

Procedure

The methodology we used for this study consisted of three phases. Figure 1 shows the

methodology.

Figure 1

Methodology used for the study

Phase 1:

o Google Forms creation: It consisted in a Google Forms named mental health

questionnaire that included a confidentiality notice, directions, sociodemographic

questionnaire (gender, age, education level and working area) and DASS-21 items.

o Linkage with a productive and service company: During the execution of the study, we

contacted service company “X” dedicated to the distribution of ice cream products and a

productive company “Y” dedicated to the manufacture of boxes. Appendix B shows the

steps we used for administering the mental health questionnaire in both organizations.

Phase 2

o Execution of the ETL process, Power BI: In the data extraction process, we used the

Mental Health questionnaire data which was stored in a Excel Google Sheets spreadsheet,

then, we obtained the link to this sheet and imported the data into Power BI; in the data

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transformation process, we used Power BI query editor to clean the data by removing

unwanted columns and rows, converting data types, and organizing it into tables according

to the analysis requirements and in the data loading process, the transformed data was

stored in the Power BI data model, enabling subsequent analysis and the creation of

effective visualizations.

o Dashboard configuration: To configure the dashboard, we created 5 pages, each serving

a specific analytical purpose: main menu; stress, depression, and anxiety severity in the

organization; stress, depression, and anxiety severity by working area; consolidated

severity of stress depression and anxiety and sociodemographic variables comparison.

o File generation and access: We created a Power BI .pbix file containing the mental health

status dashboard.

Phase 3:

o Delivery results: We shared via a download link for organizational leaders to access and

download the Mental Health Power BI dashboard to review the results.

RESULTS

Once we applied the mental health questionnaire in the service and productive company

the results visualized for the mental health dashboard are shown in Figure 2.

Figure 2

Mental health dashboard main menu

The stress, depression, and anxiety severity of the results obtained for the service and

productive companies through the dashboard are shown in Figure 3. This dashboard represents

the severity levels of stress, depression and anxiety across the entire companies, as well as the

employees who answered the mental health questionnaire, the progress percentage and the and

the number of employees pending to respond. The information provided in this dashboard is

organized into the following sections:

(1), (2) and (3) These sections specify the stress, depression and anxiety severity leves in

the company. The results are represented by a tachometer.

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(4) The section allows selecting the year and month when the mental health questionnaire

was answered, enabling dynamic visualization of the severity levels of stress, depression, and

anxiety within the organization. A slicer was used for this configuration.

(5), (6), and (7) These sections display the total number of employees who answered the

Google Forms mental health questionnaire, the progress percentage of respondents relative to the

total number of employees, and the number of employees pending to respond to the survey,

respectively. The Card visual object was used for all three sections.

Figure 3

Obtained results of stress, depression, and anxiety severity in the companies. From 1 to 7 the

circled numbers represent the visual sections of the dashboard (left image: service company, right

image: productive company)

The severity of stress, depression, and anxiety by working area for the results obtained from

service and productive companies is shown in Figure 4. This dashboard represents the number of

employees by working area with their respective severity levels of stress, depression, and anxiety

across the entire companies. It also includes the areas most impacted in terms of stress, depression,

and anxiety levels, as well as a summary table with employees and their respective severity levels

of these disorders. The information provided in this dashboard is organized into the following

sections:

(1) The section allows selecting the year and month when the mental health questionnaire

was answered.

(2) This section allows the identification of a specific person by their name.

(3) It allows filtering the work areas within the organization. A text filter was used for this

configuration.

(4), (5), and (6) These sections allow selecting the severity level for stress, depression, and

anxiety respectively.

(7), (8) and (9) These sections represent the working area that has the greatest impact on

the severity level of stress, depression, and anxiety, respectively. A 100% Stacked Bar Chart was

used for these configurations.

(10), (11) and (12) These visualizations show the number of employees by working area

and their respective severity levels for stress, depression, and anxiety disorders. A clustered

column chart was used for the configuration.

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(13) The table shows the names of the employees and the severity levels of stress,

depression, and anxiety for each one. To ensure the confidentiality of each person, the names

were coded for the service company as A1, A2, A3... An and for the productive company as B1,

B2, B3... Bn.

Figure 4

Obtained results of stress, depression, and anxiety severity by working area from 1 to 13 the

circled numbers represent the visual sections of the dashboard (left image: service company, right

image: productive company)

The consolidated severity levels of stress, depression, and anxiety by working area are

shown in Figure 5 This dashboard allows for a comparative analysis of disorder severity per

employee against the overall company levels of stress, depression, and anxiety. It enables the

comparison of severity levels in different working areas with those of individual employees and

the entire company. Additionally, it provides a table displaying each employee's respective

severity levels for the disorders, as well as identifying the working area that has the greatest

impact on stress, depression, and anxiety. The information provided in this dashboard is

organized into the following sections:

(1) The section allows selecting the year and month when the mental health questionnaire

was answered.

(2) This section allows the identification of a specific person by their name.

(3) It allows filtering the working area within the organization.

(4) The table shows the names of the employees and the severity levels of stress,

depression, and anxiety for each one.

(5), (6), and (7) These sections include the severity levels of disorders for each employee

selected with text box (2), working area selected with filter (3), and the entire organization

respectively.

(8), (9) and (10) These sections represent the working area that has the greatest impact on

the severity level of stress, depression, and anxiety, respectively.

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Figure 5

Consolidated severity of stress depression and anxiety by working area from 1 to 10 the circled

numbers represent the visual sections of the dashboard (left image: service company, right image:

productive company)

The next dashboard shown in Figure 6 includes a comprehensive breakdown of the severity levels

of stress, depression, and anxiety, categorized by sociodemographic variables such as gender,

education level, working area, and age. The information provided in this dashboard is organized

into the following sections:

(1), (2) and (3) These sections allow selecting the severity level for stress, depression, and

anxiety respectively.

(4) This entire section includes the comparison of stress against gender, education level,

working area, and age, showing the number of people with the severity conditions filtered through

(1).

(5) This entire section includes the comparison of depression against gender, education

level, working area, and age, showing the number of people with the severity conditions filtered

through (2).

(6) This entire section includes the comparison of anxiety against gender, education level,

working area, and age, showing the number of people with the severity conditions filtered through

(3).

Figure 6

Sociodemographic variables comparison, from 1 to 6 the circled numbers represent the visual

sections of the dashboard (left image: service company, right image: productive company)

DISCUSSION

The implementation of a mental health dashboard using Power BI in the two analyzed

companies allowed for dynamic and real time monitoring of stress, anxiety, and depression

severity levels among employees. This approach facilitated detailed comparisons by

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sociodemographic variables and specific working areas, providing managers with a broader

perspective to ensure relevant and effective intervention strategies for employees.

Regarding the service company, the following was identified: the severity levels for stress,

depression, and anxiety across the entire company remain within normal ranges, reflecting a

favorable environment within the organization. For the General Assistant working area, there is

a mild condition in depression and a moderate condition in anxiety; for the packer, a mild

condition in anxiety; and for human resources, a mild condition in anxiety. Appropriate support

measures should be taken for employee A18 due to the extremely severe condition in anxiety and

severe condition in depression, considering that NOM-035-STPS-2018 commands mandatory

intervention for disorders with extremely severe levels. Preventive measures should be taken for

employees A6, who has a moderate condition in depression and anxiety; A9, who has a severe

condition in anxiety; and A26, who has a moderate condition in anxiety.

Regarding the productive company, the following findings were identified: the severity

levels for stress, depression, and anxiety across the entire company remain within normal ranges.

In the cleaning working area, there are moderate levels of depression and anxiety. Employee B1

requires adequate support due to the extremely severe anxiety, along with severe stress and

depression. Similarly, employee B43 needs support for the extremely severe stress and anxiety,

coupled with severe depression. Preventive measures should be considered for individuals

presenting severe conditions: B7, who exhibits severe depression, moderate anxiety, and mild

stress; B17, who shows severe stress; and B23, who has mild stress, severe depression, and

moderate anxiety.

CONCLUSIONS

The results obtained through the Power BI dashboard provided a comprehensive view of

stress, anxiety, and depression levels in both the productive and service organizations, as well as

in specific working areas and at the individual level. Analyzing the data by working area revealed

significant differences in stress and anxiety levels between departments and among employees,

highlighting the importance of adapting wellness strategies to the specific needs of each section,

based on each company's organizational intervention programs. The individual analysis identified

employees with extremely severe levels of stress, anxiety, and depression, facilitating the

implementation of personalized and timely interventions. These results underscore the utility of

the Power BI dashboard not only for general monitoring but also for the precise identification of

risk areas and the application of preventive and corrective measures at different levels within the

organization. The integration of this type of tool ensures compliance with the regulatory

framework, such as NOM-035-STPS-2018, which requires the identification and prevention of

psychosocial risk factors at work. By providing a detailed and continuous assessment of

employees mental wellbeing, companies can not only improve the health and productivity of their

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workforce but also ensure adherence to current legal regulations, avoiding sanctions and

promoting a safer and healthier work environment.

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REFERENCES 
Abdulazis Alsaif, N. (2023). Workplace Related Stress Among Speech and Language Pathologists 
in Saudi Arabia [Master thesis].  
https://www.proquest.com/openview/2d8545919b366e08901bfe248b3e752d/1?pq-
origsite=gscholar&cbl=2026366&diss=y 
Al-Kalbani,  M.,  Al-Adawi,  S.,  &  Alshekaili,  W.  (2022).  Psychometric  properties  of  the 
depression, anxiety, stress scales-21 (DASS-21) in a sample of health care workers in 
Oman. Journal of Affective Disorders Reports, 10, 100451.  
https://doi.org/10.1016/j.jadr.2022.100451 
Bengwasan, P. D., Bernardo, A. B. I., & Maximo, S. I. (2022). Translation and Initial Validation 
of the Depression Anxiety and Stress Scale (DASS-21) in Ilokano. Psychological Studies, 
67(4), 594-604. https://doi.org/10.1007/s12646-022-00696-1 
Castellón Leal, E., Ibern Regàs, P., Gili Planas, M., Lahera Forteza, G., Sanz González, J., & Saiz 
Ruiz, J. (2016). El abordaje de la depresión en el ámbito del trabajo: Recomendaciones 
clave. Psiquiatría Biológica, 23(3), 112-117. https://doi.org/10.1016/j.psiq.2016.08.003 
Delgado Espinoza, S. K., Calvanapón Alva, F. A., & Cárdenas Rodríguez, K. (2020). El estrés y 
desempeño laboral de los colaboradores de una red de salud. Revista Eugenio Espejo, 14(2), 
11-18. https://doi.org/10.37135/ee.04.09.03 
Diario Oficial de la Federación. (2023). Decreto por el que se reforman y adicionan diversas 
disposiciones de la Ley Federal del Trabajo. 
https://www.dof.gob.mx/nota_detalle.php?codigo=5710347&fecha=04/12/2023#gsc.tab=
0 
Evans, L., Haeberlein, K., Chang, A., & Handal, P. (2021). Convergent Validity and Preliminary 
Cut-Off  Scores  for  the  Anxiety  and  Depression  Subscales  of  the  DASS-21  in  US 
Adolescents.  Child  Psychiatry  &  Human  Development,  52(4),  579-585. 
https://doi.org/10.1007/s10578-020-01050-0 
Formiga, N. S., Franco, J. B. M., Oliveira, H. C. C., Prochazka, G. L., Beserra, T. K. P., Valin, C. 
G. P., Grangeiro, S. R. A., & Nascimento, R. L. (2021). Invariância fatorial, sensibilidade 
e diferenças da medida de ansiedade, estresse e depressão (DASS-21) em trabalhadores 
brasileiros.  Research,  Society  and  Development,  10(7),  e26910715572-e26910715572. 
https://doi.org/10.33448/rsd-v10i7.15572 
González Hernández, I. J., Armas-Alvarez,  B.,  Coronel-Lazcano, M.,  Maldonado-López,  N., 
Vergara-Martínez,  O.,  &  Granillo  Macias,  R.  (2021).  El  desarrollo  tecnológico en  las 
revoluciones industriales. Ingenio y Conciencia Boletín Científico de la Escuela Superior 
Ciudad Sahagún, 8, 41-52. https://doi.org/10.29057/escs.v8i16.7118 

 Vol. 11/ Núm. 2 2024 pág. 3581 
Hakim,  M.  A.,  &  Aristawati,  N.  V.  (2023).  Mengukur  depresi,  kecemasan,  dan  stres  pada 
kelompok  dewasa  awal  di  Indonesia:  Uji  validitas  dan  reliabilitas konstruk  DASS-21. 
Jurnal Psikologi Ulayat, 10(2), 232-250. https://doi.org/10.24854/jpu553 
Inc, G. (2022). State of the Global Workplace: 2022 Report. https://lts-resource-page.s3.us-west-
2.amazonaws.com/2022-engagement.pdf 
Joyanes Aguilar, L. (2019). Inteligencia de negocios y analítica de datos (1.a ed.). Alfaomega. 
Kaji Thapa, D., Visentin, D., Kornhaber, R., & Cleary, M. (2022). Psychometric properties of the 
Nepali language version of the Depression Anxiety Stress Scales (DASS-21). Nursing 
Open, 9(6), 2608-2617. https://doi.org/10.1002/nop2.959 
Kakemam, E., Navvabi, E., Albelbeisi, A. H., Saeedikia, F., Rouhi, A., & Majidi, S. (2022). 
Psychometric properties of the  Persian  version of  Depression Anxiety  Stress Scale-21 
Items (DASS-21) in a sample of health professionals: A cross-sectional study. BMC Health 
Services Research, 22(1), 111. https://doi.org/10.1186/s12913-022-07514-4 
Le, M. T. H., Tran, T. D., Holton, S., Nguyen, H. T., Wolfe, R., & Fisher, J. (2017). Reliability, 
convergent  validity  and  factor  structure  of  the  DASS-21  in  a  sample  of  Vietnamese 
adolescents. PLOS ONE, 12(7), e0180557. https://doi.org/10.1371/journal.pone.0180557 
Lee, B., & Kim, Y. E. (2022). Validity of the depression, anxiety, and stress scale (DASS-21) in 
a  sample  of  Korean  university  students.  Current  Psychology,  41(6),  3937-3946. 
https://doi.org/10.1007/s12144-020-00914-x 
Lee, J., Lee, E.-H., & Moon, S. H. (2019). Systematic review of the measurement properties of 
the Depression Anxiety Stress Scales–21 by applying updated COSMIN methodology. 
Quality of Life Research, 28(9), 2325-2339. https://doi.org/10.1007/s11136-019-02177-x 
Lovibond, S. H., & Lovibond, P. F. (1995). Manual for the Depression Anxiety Stress Scales (2.a 
ed.). 
Makara-Studzińska, M., Tyburski, E., Załuski, M., Adamczyk, K., Mesterhazy, J., & Mesterhazy, 
A. (2022). Confirmatory Factor Analysis of Three Versions of the Depression Anxiety 
Stress  Scale  (DASS-42,  DASS-21,  and  DASS-12)  in  Polish  Adults.  Frontiers  in 
Psychiatry, 12. https://doi.org/10.3389/fpsyt.2021.770532 
Medvedev, O. N. (2023). Depression Anxiety Stress Scales (DASS-21) in International Contexts. 
En C. U. Krägeloh, M. Alyami, & O. N. Medvedev (Eds.), International Handbook of 
Behavioral  Health  Assessment  (pp.  1-15).  Springer  International  Publishing. 
https://doi.org/10.1007/978-3-030-89738-3_15-1 
Mingote Adán, J. C., Gálvez Herrer, M., Pino Cuadrado, P. del, & Gutiérrez García, M. a D. 
(2009). El paciente que padece un trastorno depresivo en el trabajo. Medicina y seguridad 
del trabajo, 55(214), 41-63. https://dialnet.unirioja.es/servlet/articulo?codigo=7502989 
Montenegro Bolaños, B. F. (2017). Aplicación de la escala dass-21 para valorar depresión, 
ansiedad y estrés en los profesionales de salud del Hospital de Especialidades Eugenio 

 Vol. 11/ Núm. 2 2024 pág. 3582 
Espejo  en  los  meses  de  julio-agosto  del  2016  [Tesis  de  Licenciatura,  PUCE]. 
http://bibliotecavirtualoducal.uc.cl/vufind/Record/oai:localhost:123456789-1436771 
Moya, E., Larson, L. M., Stewart, R. C., Fisher, J., Mwangi,  M.  N., &  Phiri, K. S. (2022). 
Reliability and  validity  of  depression anxiety  stress  scale  (DASS)-21  in  screening  for 
common mental disorders among postpartum women in Malawi. BMC Psychiatry, 22(1), 
352. https://doi.org/10.1186/s12888-022-03994-0 
Organización  Internacional  del  Trabajo.  (2016).  Estrés  en  el  trabajo. 
https://webapps.ilo.org/public/libdoc/ilo/2016/490658.pdf 
Organización  Mundial  de  la  Salud.  (2022).  La  salud  mental  en  el  trabajo. 
https://www.who.int/es/news-room/fact-sheets/detail/mental-health-at-work 
Pezirkianidis,  C.,  Karakasidou,  E.,  Lakioti,  A.,  Stalikas,  A.,  &  Galanakis,  M.  (2018). 
Psychometric Properties of  the  Depression,  Anxiety, Stress  Scales-21  (DASS-21)  in  a 
Greek Sample. Scientific Research Publishing, 9, 2933-2950.  
https://doi.org/10.4236/psych.2018.915170 
Psychology  Foundation  of  Australia.  (2023).  Depression  Anxiety  Stress  Scales—DASS. 
https://www2.psy.unsw.edu.au/dass/ 
Psychology Foundation of Australia. (2024). Download DASS forms.  
https://www2.psy.unsw.edu.au/dass/Download%20files/Dass21.pdf 
Román, F., Santibáñez, P., & Vinet, E. V. (2016). Uso de las Escalas de Depresión Ansiedad 
Estrés (DASS-21) como Instrumento de Tamizaje en Jóvenes con Problemas Clínicos. Acta 
de  Investigación  Psicológica,  6(1),  2325-2336.  https://doi.org/10.1016/S2007-
4719(16)30053-9 
Ruiz, F. J., Martín, M. B. G., Falcón, J. C. S., & González, P. O. (2017). The Hierarchical Factor 
Structure of the Spanish Version of Depression Anxiety and Stress Scale -21. International 
Journal of Psychology and Psychological Therapy, 17(1), 97-105. 
Simon,  P.,  &  Bernardo,  A.  (2023).  Longitudinal Measurement Invariance of  the  Depression 
Anxiety Stress Scale (DASS-21) in Filipino Adolescents. Transactions of the National 
Academy of Science and Technology, 44(2022), 1-7. 
https://doi.org/10.57043/transnastphl.2022.2557 
Teo, Y. C., Hj Yusuf, A., Alice Lim, W. P., Ghazali, N. B., Abd Rahman, H., Lin, N., & Koh, D. 
(2019). Validation of DASS-21 among nursing and midwifery students in Brunei. Journal 
of Public Health, 27(3), 387-391. https://doi.org/10.1007/s10389-018-0947-z 
Thiyagarajan, A., James, T. G., & Marzo, R. R. (2022). Psychometric properties of the 21-item 
Depression, Anxiety, and Stress Scale (DASS-21) among Malaysians during COVID-19: 
A  methodological  study.  Humanities  and  Social  Sciences  Communications,  9(1),  1-8. 
https://doi.org/10.1057/s41599-022-01229-x 

Vol. 11/ Núm. 2 2024 pág. 3583

Velazquez Fuentes, E. del C. (2022). El estrés laboral y su relación con el desempeño de los

promotores de servicio de las agencias del distrito de Magdalena del Mar, en una institución

financiera, 2019—2020. Ciencia Latina Revista Científica Multidisciplinar, 6(1), 155-180.

https://doi.org/10.37811/cl_rcm.v6i1.1492

Vige, W. (2024). ¿Qué es la ansiedad laboral? 10 consejos para combatir tus preocupaciones

laborales [2024] • Asana. https://asana.com/es/resources/work-anxiety

Yuan-Pang, W. (2017). A los hombres con depresión les insume más tiempo volver al trabajo.

Salud(i)Ciencia, 22(7), 672-675.

http://www.scielo.org.ar/scielo.php?script=sci_abstract&pid=S1667-

89902017000400014&lng=es&nrm=iso&tlng=es