Subjective wellbeing and mental health during the COVID-19 pandemic: Data from three population groups in Colombia

Abstract

This paper presents three data sets about the consequences of COVID-19 pandemic on mental health and subjective wellbeing in Colombia for three population subgroups: adults (+18 years old), college students, and informal workers. The data was gathered using three different online surveys in Colombia, South America. Each online survey had a different collection process. For adults and informal workers, we use a snowballing sampling strategy. For college students, we use social networks and students associations’ platforms. In total 2253 individuals participated in the data collection. The surveys aims at informing policymakers and academics about the consequences of COVID-19 in the wellbeing of three population groups. The datasets available in this report includes sociodemographic variables, standardized measures of subjective wellbeing, questions concerning to the pandemic and the quarantine, and emotional closeness with friends and keen. Information of informal workers includes a wide range of information about economic outcomes, like job stability, alternative income, financial inclusion, government welfare, and consumption patterns. This paper presents descriptive and correlation analysis of the variables included in the surveys. The information of this report aims at contributing to a broader discussion, beyond the epidemiological side, of the consequences of the pandemic on the population health. This data in brief is valuable by contributing records from a country in the global South, a region where information for policymaking and academic research is usually scarce. Before the pandemic unfolded, there were reports of high subjective wellbeing in Latin America, by studying subjective wellbeing in the middle of a crisis, is possible to examine how a crisis of this dimension affects the population wellbeing and resilience.

Specifications Table

Subject area	Social Science
More specific subject area	Policy health
Type of data	Text, dummy, and metric variables
How data were acquired	Online surveys Survey adults´ wellbeing: DOI: http://dx.doi.org/10.17632/3z6k2r3rmd.2#file-31e19dec-e4d7-4103-b4a5-76874b11eeb1 Survey informal workers´ wellbeing: DOI: http://dx.doi.org/10.17632/nwyg8gnwz3.1#file-607cc1e7-7d1f-44d5-a12d-5d4bf74fe6d4 Survey college students´ wellbeing: DOI: http://dx.doi.org/10.17632/w9brygpwg7.2#file-5679a493-2a9b-42b0-a9ed-8a5c2ccadd2d
Data format	Raw
Parameters for data collection	Data set adults´ wellbeing: Adults (+18 years old) living in Colombia. Open online survey available through social networks. Data set informal workers´ wellbeing: Informal workers (not formally employed with a company). Adults living in Colombia. Data set college students´ wellbeing: College students from a private university in Cali, Colombia. Any student could participate in the survey.
Description of data collection	Data set adults´ wellbeing: Online survey collected using a snowballing sampling strategy. Over 10 researchers were involved in the survey distribution. Survey was released in April 2020 during the quarantine in Colombia. A short video and web platform were created for the study: https://www.icesi.edu.co/polis/investigaciones/salud/salud-mental-covid-19.php?fbclid=IwAR3rwyVXM-jQDi6EYWlgAV2ApmvQW_00tPnnJCh70YVnuvhUVRU-tHeeI4w Data set informal workers´ wellbeing: Online survey collected using a snowballing sampling strategy. Over 20 researchers were involved in the survey distribution. Survey was available for two weeks in May 2020 during the quarantine in Colombia. Data set college students´ wellbeing: Online survey available to students through the university social networks and students´ associations. Survey was active for two weeks in April, after one month and half of school closing due to the pandemic.
Data source location	Institution: POLIS – Observatorio de políticas públicas – Universidad Icesi City/Town/Region: Cali - Valle del Cauca Country: Colombia Contact email: polisicesi@icesi.edu.co
Data accessibility	Data set adults´ wellbeing: Available at Mendeley Data DOI: 10.17632/3z6k2r3rmd.2 https://data.mendeley.com/datasets/3z6k2r3rmd/2 Data set informal workers´ wellbeing: Available at Mendeley Data DOI: 10.17632/nwyg8gnwz3.1 https://data.mendeley.com/datasets/nwyg8gnwz3/1 Data set college students´ wellbeing: Available at Mendeley Data DOI: 10.17632/w9brygpwg7.1 https://data.mendeley.com/datasets/w9brygpwg7/2 Further details about data: https://www.icesi.edu.co/polis/

Value of the Data

• •The data sets presented in this paper are relevant because allow examining the consequences of COVID-19 crisis on the population mental health and wellbeing in three different populations: adults, informal workers, and college students. Before the pandemic of COVID-19, in Latin America there were reports of high subjective well-being, life satisfaction and happiness, factors associated with a good physical and mental health. The pandemic of COVID-19 affects the mental health and wellbeing of the global population. The pervasiveness of fear, uncertainty, and loss has direct and negative impacts on mental health. Information and variables available in this report can help to examine the extent of the current crisis on wellbeing.
• •These data have the purpose to contribute the study of the association of the pandemic and subjective wellbeing. This information is useful for academic researchers and policy makers to expand the knowledge of the consequences of COVID-19 beyond the epidemiological research.
• •The data in this article is useful to inform changes in self-reported levels of subjective wellbeing in the population. The surveys presented in this paper, collect data about demographic characteristics, standardized measures of subjective wellbeing, and queries regarding concerns and direct affections of COVID-19.
• •With this information is possible to explore differences on how diverse population groups experience this pandemic. The effects of COVID-19 may have differentiated consequences in the population. Women, minority, less educated and poorer population may have less access to opportunities and resources to cope with the magnitude of the pandemic.
• •The data of this analysis provides an insight into the economic consequences of COVID-19 amongst informal workers. Information is valuable for researchers conducting policy recommendations. Researchers and policymakers can benefit from the use of this dataset. The data containing this report provides information about job stability, income generation, access to banking services, income generation during COVID-19, and home composition. Taking as a whole, the data set provides insights into the economic consequences of COVID-19 in a population that depends heavily on people's circulation and personal interactions.
• •The other population group for which this report makes data available is college students. The data set associated with this article allows analysis of the mental health and wellbeing of college students during COVID-19. College students face unique challenges during this pandemic. Their academic trajectories, job perspectives, and professional training are held while the public health and economic crisis unfold. Before the pandemic, reports about the increasing rates of anxiety and depression amongst college students were concerning, with soaring prevalence worldwide. The pandemic may aggravate this problem. This data set collects information about the impacts of COVID-19 on the mental health and subjective wellbeing of college students in Cali, Colombia. The measures used in this study are comparable with information about the most common manifestations of mental health (worry and depression) and measures of subjective wellbeing (happiness and life satisfaction) collected worldwide, allowing valid international comparisons.

1. Data

1.1. Data set adults wellbeing

The data for this population groups was collected through and online survey. The design of the web questionnaire is based on a population survey – called CaliBRANDO- collected annually by POLIS, the Observatory of Public Policies of Universidad Icesi. CaliBRANDO survey runs annually (from 2014 to 2019) and the primary focus is to measure life satisfaction and subjective wellbeing in Cali, the third largest city in Colombia [1], [2], [3]. CaliBRANDO survey provides panel data to measure life satisfaction and wellbeing before the current pandemic unfolded.

As a response of the current pandemic and aiming at comparing population life satisfaction and subjective wellbeing before and during the pandemic, researchers at POLIS released a web survey after one-month of strict lockdown was in place in Colombia. The questionnaire includes four sections: (i) demographic data; (ii) measures for life satisfaction and wellbeing; and (iii) concerns and direct affections of COVID-19; and (iv) emotional closeness with family members, friends and partner. Sociodemographic data includes age, gender, educational attainment and social stratification. The measure of social stratification is a national scale (1– 6) to classify households and individuals based on their access to public services and human capital accumulation. In this scale, 1 represent the most deprived households and individuals, whereas 6 correspond to the affluent population [4]. This strata classification is widely known in the country by citizens since is the mechanism government uses to provide direct subsidizes to the population through utilities (running water and electricity) and individuals choose households based on the household strata. Household strata is displayed in all utilities bills, and for the most part, Colombians are aware of the strata in which they live.

For measuring wellbeing, life satisfaction, and the prevalence of the most common negative emotions affecting a good mental health (worry and depression), we use the standardized and validated scale of core measures of wellbeing [5]. All questions were in a scale of 0-10, were 0 represents the lowest value and 10 the highest. Table 1 presents the descriptive statistics of this dataset.

Table 1.

Descriptive statistics – adults´ wellbeing.

Demographic data
Average age (years)	36
Female (%)	63
Education level (%)
Primary school	1
Secondary school	8
Technician	11
Professional	51
Specialization	11
Master/
Doctorate	18
Economic activity (%)
Employee	44
Studying	24
Work holidays	4
Looking for a Job	7
Retired	4
Working as independent	16
Income reduced due to quarantine (%)	50
Socio-economic strata (%)
1	3
2	13
3	25
4	26
5	21
6	12
Race/Ethnicity (%)
Minority	6
Non-minority	83
Subjective well-being
Life satisfaction (average- scale 0–10)	8
Happy (average- scale 0–10)	7
Worried (average- scale 0–10)	5
Depressed (average- scale 0–10)	3
COVID-19 and well-being (average- scale 0–10)
I am concerned about my health.	6
I am concerned about the health of my loved ones.	8
With government measures, I feel isolated.	6
I consider that the quarantine is an individual responsibility and not of the government.	6
I enjoy having time to spend with my family	8
I feel more productive working at home or independently.	5
I keep informed and read the news about the COVID-19.	7
I am concerned about the financial consequences of the COVID-19.	9
I feel that in last days my anxiety and stress levels have increased.	6
How emotionally close do you feel to your loved ones: (average- scale 0–10)
Family	8
Friends	7
Couple	6

1.2. Data set informal workers wellbeing

Data about informal workers comes from an online survey collected after a month and half of the quarantine in Colombia. The survey had in total 53 questions divided into seven sections:

Demographic information: Data in this section refers to variables as gender, educational attainment, race/ethnicity, and family composition. Socioeconomic strata, a widely used variable in Colombia to stratify households by economic and social characteristics, are included in the data set. This variable ranges from 1 to 6. Individuals in the lowest categories are the poorest (1 y 2); the most affluent population is categorized in 5 and 6 in this variable [4]. The questionnaire did not explain this variable to respondents since is a widely known scale in the country displayed in all utilities bills. For the most part, Colombians are aware of the socioeconomic classification of their households. Table 2 presents the descriptive statistics for this section.

Table 2.

Demographic data informal workers.

Average age (years)	38
Socio-economic strata (%)
1	10
2	27
3	34
4	15
5	10
6	3
Female (%)	51
Race/Ethnicity (%)
Minority	11
Non-minority	81
Civil status (%)
Married	25
Cohabitation	25
Separated/Divorced	6
Single	42
Widow	2
Have children (%)	57
Education Attainment (%)
Primary school	6
Secondary school	30
Technician	28
Professional	30
Specialization	5
Master/
Doctorate	1
None	0
Household (%)
Own – paying mortgage	10
Own – paid	21
Rented	42
Family	26
Other	1
Have health insurance scheme (%)	78
Contribute to health and pension programs (%)	31
Contribute to health and pension programs after COVID-19 (%)	50

Economic stability at home: Variables of this component refers to household composition, economic providers, and job loss within the family circle. Table 3 provides descriptive statistics for this component.

Table 3.

Economic stability at home.

Household position (%)
Head of household	48
Dependent	26
Stay home mom or dad	13
Other	13
Average people at home	3
Average people at home employed	2
Respondent is the main economic provider at home (%)	50
Anyone in the household lost their job due to COVID-19 (%)	44

Consequences of COVID-19 in economic activity: Questions in this section inquire about the economic activity before the quarantine and how the COVID-19 crisis affects respondents' jobs. This section includes questions about the positive and negative aspects of working in the informal sector. Likewise, questions about how informal workers adapt to new economic activities are included. Table 4 reports descriptive statistics.

Table 4.

Consequences of covid-19 in economic activity.

Fear about consequences from the COVID-19 (%)
Death of relatives, friends or acquaintances	66
Getting sick	43
Economic crisis at home	51
Unemployment	37
Global economic crisis	33
Family issues	9
Another	4
Economic activity (%)
Professional independent	23
Non-professional independent	27
Business owner	17
Catalog merchant (Yanbal, Avon, Natura)	2
Driver (Uber, Cabify, informal transport)	6
Housework	3
Working at hairdressing salon	4
Delivery services (Rappi, Uber eats)	6
Informal employee in a business	5
Manual work (gardener, carpenter, builder)	1
Any work activity	2
Other	4
Economic activity main source of income (%)	91
Main advantage of informal work (%)
Not having a boss	21
Not having a schedule	14
Your income depends on you	40
It is a supplement income	16
Ease of entering at labor market	6
Other	3
Main disadvantage of informal work (%)
Lack of job stability	24
No wage premium or additional income payment	13
Lack of salary compensation for dismissal	3
Risks inherent in your occupation (accidents)	11
Income instability	37
Lack of social benefits	9
Other	4
Work activity paused while quarantine ends (%)	70
Average worked hours	36
Labor conditions during quarantine (%)
Working using a digital platform	63
Working using personal network	27
Working using a family network	3
Working using resources/networks	7
Has special permission to carry out the work	56
Taking protective measures to carry out the work	96
Employer has reduced hours of work	55
Consider it will be easy to return to work after quarantine	51

Financial stability: This segment of the survey inquires about income before quarantine, savings, and income reduction due to the strict lock-down. The survey includes questions about alternative economic activities to compensate for income reduction and welfare program participation. Table 5 presents the variables in this section and the general tabulation.

Table 5.

Financial stability.

Monthly income before quarantine (%)
Less than 1 mmw (<300 USD)	31
Between 1 mmw and less than 2 mmw (300–650 USD)	37
Between 2 mmw and less than 4 mmw(650–1300 USD)	17
Between 4 mmw and less than 8 mmw (1300–2600 USD)	4
More than 8 mmw (>2600 USD)	3
Income enough to cover basic needs and save before quarantine (%)	66
Enough savings to face the current economic circumstances (%)	21
Income reduced due to quarantine (%)	91
How compensate income reduction? (%)
Performing another economic activity	21
Using savings	37
Asking for help to family and/or friends	27
Acquiring debts	12
Receiving financial support from the State (subsidies)	2
No means to compensate for the economic crisis	15
Other	5
Other economic activity to offset income reduction due to quarantine (%)
Working online	16
Working on digital platforms	10
None	65
Other	9
Expect to generate the same levels of income after quarantine is lifted (%)	31
Role of the government
Agree with the quarantine measure (%)	87
Feel support by the government during the pandemic (%)	6
Beneficiary of any government subsidy (%)	7

Health and subjective wellbeing: Data in this component refers to self-reported physical health, life satisfaction, and the most common symptoms of poor mental health: worry and depression. Self-reported mental health measures come from the Centers for Disease Control and Prevention (CDC) to measure healthy days [6]. Life satisfaction measures and questions about how happy, worried, and depressed, the respondent felt the day before (scale 0-10) comes from the OECD guidelines to measure subjective wellbeing [5]. This information reported by sub-groups allows establishing differences in subjective wellbeing during the pandemic. Table 6 presents the descriptive statistics of this component.

Table 6.

Health and subjetive well-being.

Health perception (%)
Excellent	24
Very good	33
Good	42
Fair	0
Poor	1
Life satisfaction (average-scale 0–10)	7,8
Anxiety and stress (average-scale 0–10)	6,5
Happy (average-scale 0–10)	6,9
Worried (average-scale 0–10)	5,6
Depressed (average-scale 0–10)	3,8

The questionnaire was piloted before implementation, and several adjustments were made after releasing the survey. In total, 638 self-employed and informal workers participated in the study.

1.3. Data set college students wellbeing

Data was collected thought an online survey in a private university in Cali, Colombia, one month after school closing in the country. A structured survey with nine sections was the instrument designed for this study. Participants were asked questions regarding the following factors:

Demographic information: Questions in this section inquired about students age, semester (the largest share of academic programs has ten semesters), and gender. Table 7 presents the descriptive statistics of this section.

Table 7.

Demographic data.

	Average
Average age (years)	20
Average semester	5
Female (%)	56

Subjective wellbeing: The module of subjective wellbeing was constructed using questions from OECD guidelines to measure subjective wellbeing [5]. In total, four questions from the core measure were introduced. One that evaluates the overall life satisfaction, which serves as the primary measure of life satisfaction, and three more that correspond to an affect assessment of this component, asks respondents the frequency of happiness, worry, and depression. All questions are formulated on a scale of 0-10. Table 8 presents the descriptive statistics of this section.

Table 8.

Subjective well-being.

	Average scale 0–10
Life satisfaction	6,8
Happy	6,0
Worried	6,4
Depressed	4,5

Concerns and perceptions of COVID-19: This section inquires about an array of factors related to the COVID-19 pandemic and the impact on student's life. Questions include worry for the infection of COVID-19, favorability/perception of government measures, concerns about the pandemic's financial consequences, news updates, and perceptions about online teaching and working independently. This component's information seeks to provide an overall picture of how COVID-19 affects students' perceptions and increases concerns. Table 9 presents the tabulation of these questions.

Table 9.

Concerns and perceptions of covid-19.

	Average scale 0–10
I am concerned about my health.	6,0
I am concerned about the health of my loved ones.	8,5
I am taking all the protective measures recommended by the media and the government.	8,9
With government measures, I feel isolated.	6,8
I consider that the quarantine is an individual responsibility and not of the government.	6,2
I enjoy having time to spend with my family	7,2
I enjoy being able to disconnect from my daily activities	5,3
I feel more productive working at home or independently.	3,2
I keep informed and read the news about the COVID-19.	6,3
I am concerned about the financial consequences of the COVID-19.	8,3
The probability that my loved ones or I being infected is high.	5,3
I feel that in last days my anxiety and stress levels have increased.	7,5
I consider that the government is taking all the necessary measures to overcome the crisis.	5,9
I consider that the government provides sufficient information in these cases.	4,9
I am amused by memes and jokes about the COVID-19.	6,4
I feel that with the help of technology I am ready to continue my activities from home.	5,4
I always check the sources of information to be reliable, before commenting or sharing the news.	8,4
I am concerned that the COVID-19 will affect my academic performance.	8,2
I am comfortable with the online classes.	3,6

Emotions and coping strategies: In this section, respondents are inquired about coping strategies and emotions. In particular, information about optimism, happiness, stress, emotional closeness (family, friends, and romantic partner), and gratitude. This information has the purpose of analyzing the correlation of COVID-19 with negative emotions (stress). Likewise, the survey allows examining whether positive emotions like optimism, gratitude, and being close to loved ones help to mediate the negative consequences of the pandemic. The survey includes a short version of the originally ten-item-long life orientation test to measure optimism [7] and a short version of a gratitude self-reported questionnaire, validated to Spanish [8]. All questions are on a scale of 0-10, and it is possible to build composite indicators using factor analysis. Table 10 presents the descriptive statistics of this section.

Table 10.

Emotions and coping strategies.

	Average scale 0–10
In difficult times I usually hope for the best	6,5
I getting relax easily	5,0
I am always optimistic about the future	6,2
I really enjoy hangout with my friends	7,3
It is important to me always be busy	6,2
I don't get upset easily	5,4
Overall, I hope more good things than bad things happen to me	7,1
How happy are you with	Average scale 0–10
Your life overall	7,3
At this moment in your life	6,1
Yourself	6,5
Your physical appearance	6,4
Your ability to communicate with others	6,5
Your health overall	7,6
What you have achieved in your life so far	7,2
The college	7,0
Your college classmates	7,5
How stressed are you with:	Average scale 0–10
Your life overall	5,9
The college	7,5
Your home	5,2
The financial situation of your home	5,6
The lack of time	6,7
Your future	7,4
	Average scale 0–10
How often do you use stress management techniques:
Breathe deeply	5,1
Count to ten	2,3
Praying	3,9
Meditating	3,1
Listen to music	8,2
Doing exercise	5,3
Stretching exercises	5,3
Talking or calling someone	5,6
Imagine something pleasant	4,8
Look at the big picture of the problem	5,6
Writing down the factors that stress me	2,0
Thank everyday	5,1
How emotionally close do you feel to your loved ones:	Average scale 0–10
Parents	7,4
Friends	6,8
Couple	5,0
College classmates	5,9
How much do you agree with?	Average scale 0–10
I have a lot to thank life Average scale 0 -10	8,4
If I had to make a gratitude list, it would be very long	8,0
When I look at the world I have a lot to thank	8,0
I am grateful with a lot of people	7,7
As time goes by, I appreciate more the people, events and situations that are part of my life	8,2

In terms of internal correlation, most of the scales (excluding emotional closeness alpha of 0.4), have a high correlation within the items at each scale with an alpha above 0.7. Table 11 presents the scales internal correlation.

Table 11.

Scales internal correlations.

Subjective wellbeing	Obs	Sign	Item-test correlation	alpha
Life satisfaction	651	+	0.7550	0.7193
Happy	651	+	0.8377	0.6441
Worried	651	-	0.6533	0.7955
Depressed	651	-	0.8186	0.6628
Test scale				0.7655
Optimism	Obs	Sign	Item-test correlation	alpha
In difficult times I usually hope for the best	651	+	0.7265	0.6749
I getting relax easily	651	+	0.6250	0.7068
I am always optimistic about the future	651	+	0.8100	0.6454
I really enjoy hangout with my friends	651	+	0.5596	0.7254
It is important to me always be busy	651	+	0.3814	0.7695
I don't get upset easily	651	+	0.5369	0.7315
Overall, I hope more good things than bad things happen to me	651	+	0.7258	0.6751
Test scale				0.7381
How happy are you with	Obs	Sign	Item-test correlation	alpha
Your life overall	651	+	0.8100	0.8646
At this moment in your life	651	+	0.7198	0.8742
Yourself	651	+	0.8285	0.8625
Your physical appearance	651	+	0.7024	0.8760
Your ability to communicate with others	651	+	0.6745	0.8788
Your health overall	651	+	0.6777	0.8784
What you have achieved in your life so far	651	+	0.7727	0.8686
The college	651	+	0.6860	0.8776
Your college classmates	651	+	0.6401	0.8821
Test scale				0.8862
How stressed are you with:	Obs	Sign	Item-test correlation	alpha
Your life overall	651	+	0.7631	0.7274
The college	651	+	0.7601	0.7285
Your home	651	+	0.6493	0.7657
The financial situation of your home	651	+	0.6280	0.7723
The lack of time	651	+	0.6631	0.7614
Your future	651	+	0.6966	0.7505
Test scale				0.7840
How often do you use stress management techniques:	Obs	Sign	Item-test correlation	alpha
Breathe deeply	651	+	0.5680	0.7248
Count to ten	651	+	0.5125	0.7327
Praying	651	+	0.4656	0.7390
Meditating	651	+	0.5910	0.7215
Listen to music	651	+	0.4000	0.7476
Doing exercise	651	+	0.4815	0.7369
Stretching exercises	651	+	0.5720	0.7243
Talking or calling someone	651	+	0.4630	0.7394
Imagine something pleasant	651	+	0.5192	0.7317
Look at the big picture of the problem	651	+	0.5294	0.7303
Writing down the factors that stress me	651	+	0.4919	0.7355
Thank everyday	651	+	0.5931	0.7212
Test scale				0.7490
Gratitude	Obs	Sign	Item-test correlation	alpha
I have a lot to thank life	651	+	0.8708	0.8767
If I had to make a gratitude list, it would be very long	651	+	0.8717	0.8764
When I look at the world I have a lot to thank	651	+	0.8712	0.8766
I am grateful with a lot of people	651	+	0.8232	0.8920
As time goes by, I appreciate more the people, events and situations that are part of my life	651	+	0.8159	0.8943
Test scale				0.9044

The questionnaire was piloted 20 times prior implementation with college students. Minor adjustments were made after the pilot.

2. Experimental Design, Materials and Methods

2.1. Data set adults wellbeing

The questionnaire for this survey used validated scales for subjective wellbeing (as described in the data section). Researchers created variables about the consequences of COVID-19. The data of this survey was collected in April 2020 using “Typeform,” an online provider of pooling templates. The survey was piloted before its release. Researchers used several strategies for increasing sampling and data collection:

• 1Short video: The survey was introduced by a short video explaining the purpose of the study and providing information about the findings of previous measures of subjective wellbeing and mental health before the pandemic unfolded. Participants were encouraged to participate in an academic project.
• 2Reward for participation: After completing the survey, respondents had the option to download a gratitude journal and a stress management dairy designed for this study. This reward was explained in the introductory video.
• 3Web page: POLIS, the research center promoting this survey, created a web page with the details of the study. Information about the webpage is accessible at: https://www.icesi.edu.co/polis/
• 4Social networks and academic networks: The survey was distributed through social network pages of Universidad Icesi and POLIS. Likewise, several academics and journalists contributed to the distribution of the survey.

In total 984 valid observations were gathered, 941 responses were from individuals living in Colombia. Respondents gave their consent to use the information for academic purposes and this survey is covered by the ethics committee approval of CaliBRANDO survey (code # 076). Analysis related to this data set is available at: https://www.icesi.edu.co/polis/. A policy brief aiming at informing local policy makers was distributed in late May 2020 [9].

2.2. Data set informal workers wellbeing

The questionnaire for this survey used validated scales for subjective wellbeing and health status (as described in the data section). Researchers created variables about the economic consequences of COVID-19 and used questions from previous research conducted with informal workers in Colombia [10,11]. The survey was created in "Typeform," a web server for pooling, data was collected in May 2020, after month and half of the quarantine in Colombia. The survey took about 15 min to complete. Data collection used a snowball sampling strategy through a network of over 15 students participating in the project and five researchers. The total number of valid observations is 638. In Cali, the third-largest city in Colombia, the total sample was 484. This total number of observations for Cali makes a statistically representative sample for the city's informal workers' population with a margin error of 4.2% and a confidence level of 95%.

2.3. Data set college students wellbeing

The questionnaire for this survey used validated scales for subjective wellbeing, optimism and gratitude (as described in the data section). Researchers created variables about the consequences of COVID-19. The survey was created in "Typeform," a web server for pooling, the data was collected between in April 2020, after one month of school closing in Colombia as a consequence of the COVID-19 pandemic. The survey took about 12-15 minutes to complete. Several outlets were used to distribute the survey. First, professors sent emails to students participating in their classes. Latter, two strategies were combined: emails to students' distribution lists and student associations posted the survey link on their social networks. Six hundred thirty-four students completed the survey, 10% of the university's undergrad population, making a satisfactory rate compared to the median web survey participation [12].

Students downloaded a gratitude journal and a stress management dairy designed for this study at the end of the survey as a reward for participation.

Ethics Statement

The ethics committee of Universidad Icesi approved the surveys before implementation (code # 076, Code # 287, Code #278), respondents provide consent to use the information for academic purposes.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.