Datasets:
EDUCATION
int64 30
100
| PROVINCE
stringclasses 24
values | AGE
int64 17
76
| MENTAL DISORDER HISTORY
int64 0
50
| SUIC ATTEMPT HISTORY
int64 0
100
| LIVING WITH SOMEBODY
int64 0
20
| ECONOMIC INCOME
int64 0
50
| DEPRESSION
int64 0
60
| SUIC RISK
int64 0
89
| ANXIETY STATE
int64 1
66
| ANXIETY TRAIT
int64 0
59
| REGION
stringclasses 9
values |
---|---|---|---|---|---|---|---|---|---|---|---|
30 | CABA (Buenos Aires capital) | 30 | 0 | 50 | 20 | 0 | 21 | 37 | 54 | 40 | CABA |
60 | Tierra del Fuego | 30 | 0 | 50 | 0 | 0 | 26 | 46 | 34 | 36 | Patagonia Centro-Sur |
70 | Jujuy | 39 | 50 | 0 | 20 | 0 | 8 | 21 | 33 | 29 | Noroeste |
60 | Jujuy | 36 | 0 | 0 | 0 | 50 | 27 | 70 | 42 | 48 | Noroeste |
30 | Córdoba | 35 | 0 | 0 | 0 | 0 | 9 | 4 | 25 | 12 | Córdoba |
60 | Córdoba | 21 | 0 | 0 | 0 | 0 | 5 | 14 | 20 | 22 | Córdoba |
30 | Misiones | 29 | 0 | 0 | 20 | 0 | 14 | 23 | 25 | 25 | Nordeste-Litoral |
40 | Córdoba | 28 | 50 | 0 | 0 | 50 | 20 | 26 | 28 | 26 | Córdoba |
50 | Buenos Aires provincia | 26 | 0 | 0 | 0 | 50 | 3 | 26 | 10 | 18 | Buenos Aires |
50 | Tierra del Fuego | 36 | 0 | 0 | 0 | 50 | 20 | 50 | 43 | 34 | Patagonia Centro-Sur |
50 | Tierra del Fuego | 24 | 0 | 0 | 0 | 0 | 7 | 14 | 9 | 6 | Patagonia Centro-Sur |
50 | Tierra del Fuego | 30 | 50 | 0 | 20 | 0 | 30 | 59 | 39 | 39 | Patagonia Centro-Sur |
50 | CABA (Buenos Aires capital) | 37 | 0 | 0 | 0 | 0 | 12 | 24 | 41 | 29 | CABA |
50 | Tierra del Fuego | 30 | 0 | 0 | 0 | 50 | 14 | 33 | 28 | 20 | Patagonia Centro-Sur |
60 | Córdoba | 34 | 0 | 0 | 20 | 0 | 5 | 18 | 16 | 11 | Córdoba |
60 | Tierra del Fuego | 26 | 50 | 50 | 0 | 0 | 24 | 54 | 42 | 41 | Patagonia Centro-Sur |
30 | Jujuy | 35 | 0 | 0 | 0 | 0 | 13 | 28 | 41 | 30 | Noroeste |
50 | Tierra del Fuego | 30 | 0 | 0 | 20 | 0 | 3 | 12 | 16 | 14 | Patagonia Centro-Sur |
30 | CABA (Buenos Aires capital) | 33 | 50 | 100 | 0 | 0 | 45 | 73 | 63 | 56 | CABA |
50 | Tierra del Fuego | 30 | 0 | 0 | 0 | 0 | 15 | 26 | 33 | 27 | Patagonia Centro-Sur |
40 | CABA (Buenos Aires capital) | 60 | 50 | 50 | 20 | 0 | 13 | 36 | 19 | 26 | CABA |
30 | Buenos Aires provincia | 35 | 0 | 0 | 20 | 0 | 17 | 31 | 32 | 30 | Buenos Aires |
40 | Buenos Aires provincia | 35 | 0 | 0 | 0 | 0 | 7 | 21 | 29 | 16 | Buenos Aires |
70 | Buenos Aires provincia | 55 | 0 | 0 | 0 | 0 | 16 | 15 | 12 | 20 | Buenos Aires |
60 | Buenos Aires provincia | 24 | 50 | 50 | 0 | 0 | 41 | 73 | 51 | 43 | Buenos Aires |
30 | Córdoba | 39 | 0 | 0 | 0 | 0 | 10 | 19 | 37 | 17 | Córdoba |
60 | Buenos Aires provincia | 27 | 50 | 50 | 0 | 0 | 16 | 40 | 31 | 39 | Buenos Aires |
30 | Córdoba | 39 | 0 | 0 | 0 | 0 | 9 | 18 | 15 | 18 | Córdoba |
60 | Córdoba | 24 | 0 | 0 | 0 | 0 | 15 | 24 | 13 | 33 | Córdoba |
30 | Buenos Aires provincia | 32 | 0 | 50 | 0 | 0 | 22 | 63 | 62 | 42 | Buenos Aires |
70 | Buenos Aires provincia | 20 | 0 | 50 | 0 | 0 | 52 | 78 | 47 | 45 | Buenos Aires |
60 | Buenos Aires provincia | 22 | 0 | 0 | 0 | 0 | 11 | 34 | 49 | 36 | Buenos Aires |
60 | Tierra del Fuego | 28 | 0 | 0 | 0 | 0 | 7 | 11 | 21 | 14 | Patagonia Centro-Sur |
50 | Tierra del Fuego | 59 | 0 | 0 | 0 | 0 | 5 | 16 | 32 | 27 | Patagonia Centro-Sur |
60 | Santa Fe | 57 | 0 | 0 | 0 | 0 | 5 | 10 | 16 | 14 | Santa Fe |
60 | Buenos Aires provincia | 34 | 0 | 0 | 0 | 50 | 12 | 13 | 21 | 19 | Buenos Aires |
30 | Salta | 41 | 0 | 0 | 0 | 0 | 4 | 23 | 29 | 21 | Noroeste |
60 | Salta | 35 | 0 | 0 | 0 | 0 | 12 | 20 | 20 | 20 | Noroeste |
50 | CABA (Buenos Aires capital) | 38 | 0 | 0 | 20 | 50 | 9 | 17 | 16 | 16 | CABA |
60 | Buenos Aires provincia | 26 | 0 | 50 | 0 | 0 | 17 | 40 | 47 | 34 | Buenos Aires |
30 | Córdoba | 34 | 0 | 50 | 20 | 0 | 13 | 20 | 27 | 26 | Córdoba |
60 | Buenos Aires provincia | 20 | 0 | 100 | 0 | 50 | 31 | 42 | 44 | 46 | Buenos Aires |
50 | CABA (Buenos Aires capital) | 29 | 0 | 50 | 20 | 0 | 10 | 15 | 33 | 15 | CABA |
70 | CABA (Buenos Aires capital) | 19 | 0 | 50 | 0 | 50 | 22 | 49 | 54 | 43 | CABA |
50 | Buenos Aires provincia | 41 | 50 | 0 | 20 | 0 | 2 | 2 | 7 | 8 | Buenos Aires |
60 | Córdoba | 49 | 50 | 50 | 0 | 0 | 5 | 21 | 16 | 10 | Córdoba |
50 | Jujuy | 35 | 0 | 0 | 0 | 0 | 11 | 28 | 22 | 18 | Noroeste |
40 | Buenos Aires provincia | 28 | 0 | 0 | 0 | 0 | 10 | 24 | 23 | 23 | Buenos Aires |
40 | Mendoza | 30 | 0 | 50 | 20 | 0 | 2 | 22 | 20 | 19 | Cuyo |
60 | Córdoba | 27 | 0 | 100 | 0 | 0 | 10 | 26 | 33 | 28 | Córdoba |
60 | Córdoba | 50 | 0 | 0 | 0 | 50 | 24 | 27 | 45 | 28 | Córdoba |
40 | Buenos Aires provincia | 35 | 50 | 50 | 0 | 0 | 21 | 56 | 50 | 41 | Buenos Aires |
80 | Tierra del Fuego | 62 | 0 | 0 | 0 | 0 | 0 | 13 | 21 | 23 | Patagonia Centro-Sur |
80 | Tierra del Fuego | 57 | 0 | 0 | 0 | 0 | 4 | 6 | 16 | 7 | Patagonia Centro-Sur |
50 | Córdoba | 31 | 0 | 50 | 0 | 0 | 1 | 29 | 26 | 27 | Córdoba |
50 | Tierra del Fuego | 32 | 0 | 0 | 20 | 0 | 19 | 38 | 56 | 39 | Patagonia Centro-Sur |
60 | Córdoba | 28 | 50 | 0 | 0 | 50 | 10 | 24 | 44 | 29 | Córdoba |
60 | Jujuy | 19 | 50 | 50 | 0 | 0 | 16 | 48 | 33 | 39 | Noroeste |
30 | Córdoba | 34 | 50 | 50 | 20 | 0 | 41 | 42 | 66 | 46 | Córdoba |
60 | Tucumán | 33 | 50 | 0 | 20 | 50 | 2 | 8 | 12 | 15 | Noroeste |
50 | Córdoba | 28 | 0 | 0 | 0 | 0 | 6 | 17 | 22 | 12 | Córdoba |
60 | Córdoba | 52 | 0 | 0 | 20 | 0 | 5 | 6 | 30 | 13 | Córdoba |
50 | Buenos Aires provincia | 47 | 0 | 50 | 20 | 0 | 2 | 13 | 10 | 9 | Buenos Aires |
60 | Córdoba | 28 | 0 | 0 | 0 | 0 | 1 | 12 | 10 | 3 | Córdoba |
60 | Córdoba | 29 | 0 | 0 | 20 | 50 | 20 | 26 | 28 | 28 | Córdoba |
60 | Córdoba | 21 | 0 | 100 | 0 | 0 | 12 | 40 | 17 | 33 | Córdoba |
50 | Córdoba | 26 | 50 | 0 | 0 | 0 | 1 | 19 | 20 | 17 | Córdoba |
60 | Córdoba | 24 | 0 | 0 | 0 | 0 | 14 | 21 | 22 | 20 | Córdoba |
30 | CABA (Buenos Aires capital) | 39 | 0 | 0 | 0 | 0 | 9 | 32 | 33 | 27 | CABA |
50 | CABA (Buenos Aires capital) | 35 | 50 | 0 | 0 | 0 | 2 | 16 | 18 | 16 | CABA |
60 | Córdoba | 74 | 50 | 0 | 20 | 0 | 2 | 16 | 9 | 6 | Córdoba |
50 | Córdoba | 31 | 50 | 50 | 20 | 0 | 16 | 35 | 45 | 36 | Córdoba |
60 | Buenos Aires provincia | 27 | 0 | 0 | 0 | 50 | 17 | 16 | 30 | 27 | Buenos Aires |
60 | Córdoba | 29 | 0 | 0 | 0 | 0 | 3 | 38 | 14 | 24 | Córdoba |
50 | Buenos Aires provincia | 49 | 50 | 100 | 0 | 50 | 22 | 29 | 30 | 32 | Buenos Aires |
60 | Salta | 26 | 0 | 0 | 0 | 50 | 13 | 17 | 23 | 17 | Noroeste |
40 | CABA (Buenos Aires capital) | 37 | 50 | 0 | 0 | 0 | 16 | 20 | 38 | 25 | CABA |
50 | CABA (Buenos Aires capital) | 28 | 50 | 50 | 20 | 0 | 15 | 34 | 34 | 27 | CABA |
60 | Buenos Aires provincia | 43 | 50 | 100 | 0 | 0 | 5 | 26 | 30 | 41 | Buenos Aires |
30 | CABA (Buenos Aires capital) | 40 | 50 | 100 | 20 | 0 | 17 | 57 | 48 | 48 | CABA |
80 | Córdoba | 23 | 50 | 100 | 0 | 50 | 40 | 67 | 57 | 51 | Córdoba |
80 | Córdoba | 39 | 0 | 0 | 0 | 50 | 4 | 18 | 14 | 19 | Córdoba |
70 | Córdoba | 27 | 50 | 100 | 0 | 50 | 46 | 80 | 61 | 50 | Córdoba |
50 | Córdoba | 47 | 50 | 50 | 0 | 0 | 8 | 4 | 27 | 8 | Córdoba |
60 | Córdoba | 27 | 50 | 0 | 0 | 0 | 8 | 21 | 28 | 24 | Córdoba |
70 | Tierra del Fuego | 25 | 0 | 0 | 0 | 0 | 1 | 19 | 10 | 16 | Patagonia Centro-Sur |
60 | Córdoba | 38 | 0 | 100 | 0 | 0 | 11 | 33 | 38 | 26 | Córdoba |
50 | Jujuy | 29 | 0 | 0 | 0 | 0 | 11 | 20 | 28 | 16 | Noroeste |
80 | Córdoba | 43 | 0 | 0 | 0 | 50 | 4 | 16 | 20 | 12 | Córdoba |
50 | Córdoba | 26 | 0 | 0 | 0 | 50 | 29 | 48 | 46 | 33 | Córdoba |
50 | Salta | 27 | 0 | 50 | 0 | 0 | 43 | 41 | 50 | 42 | Noroeste |
70 | Córdoba | 68 | 50 | 100 | 0 | 0 | 0 | 19 | 15 | 15 | Córdoba |
40 | Córdoba | 28 | 0 | 0 | 0 | 0 | 34 | 36 | 56 | 47 | Córdoba |
70 | CABA (Buenos Aires capital) | 19 | 0 | 0 | 0 | 50 | 19 | 17 | 26 | 12 | CABA |
70 | CABA (Buenos Aires capital) | 19 | 0 | 50 | 0 | 0 | 35 | 67 | 37 | 42 | CABA |
60 | CABA (Buenos Aires capital) | 33 | 0 | 50 | 20 | 0 | 18 | 42 | 42 | 41 | CABA |
60 | Salta | 39 | 0 | 0 | 0 | 0 | 13 | 30 | 25 | 20 | Noroeste |
50 | Neuquén | 38 | 0 | 0 | 0 | 0 | 3 | 21 | 13 | 10 | Patagonia Centro-Norte |
50 | Córdoba | 31 | 50 | 0 | 0 | 0 | 13 | 24 | 40 | 30 | Córdoba |
50 | Córdoba | 39 | 0 | 0 | 0 | 0 | 23 | 28 | 31 | 21 | Córdoba |
Mental health of people in Argentina post quarantine COVID-19 Dataset
Dataset Summary
Dataset modified for research from: Levels and predictors of depression, anxiety, and suicidal risk during COVID-19 pandemic in Argentina: The impacts of quarantine extensions on mental health state created by López Steinmetz, Lorena Cecilia for Universidad Nacional de Córdoba. Facultad de Psicología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones Psicológicas; Argentina. http://hdl.handle.net/11086/20168
The dataset underwent modifications as follows: SUB PERIODS and SEX columns were removed. Rows with PROVINCE equal to 'Otro' or 'other' were removed. Additionally, rows with EDUCATION equal to 'Otro' were removed.
The following columns were transformed from non-numeric values to numeric values:
'MENTAL DISORDER HISTORY': {'no': 0, 'yes': 50}
'EDUCATION': {
'Completed postgraduate': 30,
'Incomplete tertiary or university': 60,
'Completed high school': 70,
'Incomplete postgraduate': 40,
'Completed tertiary or university': 50,
'Incomplete high school': 80,
'Incomplete elementary school': 100,
'Completed elementary school': 90}
'SUIC ATTEMPT HISTORY': {'ideation': 50, 'no': 0, 'yes': 100}
'LIVING WITH SOMEBODY': {'no': 20, 'yes': 0}
'ECONOMIC INCOME': {'yes': 0, 'no': 50}
Furthermore, a new column 'REGION' was added to provinces according to the following assignment function:
def assign_region(province):
if province in ['Corrientes', 'Chaco', 'Misiones', 'Formosa', 'Entre Ríos']:
return 'Nordeste-Litoral'
elif province in ['Tucumán', 'Jujuy', 'Salta', 'Catamarca', 'Santiago del Estero']:
return 'Noroeste'
elif province in ['San Luis', 'San Juan', 'Mendoza', 'La Rioja']:
return 'Cuyo'
elif province in ['Neuquén', 'Río Negro', 'La Pampa']:
return 'Patagonia Centro-Norte'
elif province in ['Tierra del Fuego', 'Santa Cruz', 'Chubut']:
return 'Patagonia Centro-Sur'
elif province == 'Santa Fe':
return 'Santa Fe'
elif province == 'Buenos Aires provincia':
return 'Buenos Aires'
elif province == 'Córdoba':
return 'Córdoba'
else:
return 'CABA'
Supported Tasks and Leaderboards
mental-health-arg-post-quarantine-covid19-model
:
The dataset can be used to train a model for Mental health of people in Argentina post quarantine COVID-19.
Languages
The text in the dataset is in Spanish and English
Dataset Structure
Data Instances
{
'EDUCATION': '30',
'PROVINCE': 'CABA (Buenos Aires capital)',
'AGE': '30',
'MENTAL DISORDER HISTORY': '0',
'SUIC ATTEMPT HISTORY': '50',
'LIVING WITH SOMEBODY': '20'
'ECONOMIC INCOME': '0',
'DEPRESSION': '21',
'SUIC RISK': '37',
'ANXIETY STATE': '54',
'ANXIETY TRAIT': '40',
'REGION': 'CABA'
}
Data Fields
EDUCATION
: Maximum level of education attained by the individual, modified: 'Completed postgraduate': 30, 'Incomplete tertiary or university': 60, 'Completed high school': 70, 'Incomplete postgraduate': 40, 'Completed tertiary or university': 50, 'Incomplete high school': 80, 'Incomplete elementary school': 100, 'Completed elementary school': 90PROVINCE
: Name of the province where the individual resides.AGE
: Age of the individual.MENTAL DISORDER HISTORY
: If the individual has a history of mental disorder, modified: 'no': 0, 'yes': 50.SUIC ATTEMPT HISTORY
: If the individual has a history of suicide attempt, modifed: 'ideation': 50, 'no': 0, 'yes': 100.LIVING WITH SOMEBODY
: If the individual lives alone or not, modified: 'no': 20, 'yes': 0.ECONOMIC INCOME
: If the individual has an economic income, modified: 'yes': 0, 'no': 50.DEPRESSION
: Level of depression of the individual.SUIC RISK
: Level of suicide risk of the individual.ANXIETY STATE
: Level of anxiety state at the moment of the individual.ANXIETY TRAIT
: Level of anxiety predisposition of the individual.REGION
: Name of the region where the individual resides.
Dataset Creation
Curation Rationale
This dataset was built for research.
Source Data
Initial Data Collection and Normalization
The data was obtained and created by López Steinmetz, Lorena Cecilia.
Who are the source language producers?
López Steinmetz, Lorena Cecilia.
Considerations for Using the Data
Social Impact of Dataset
The purpose of this dataset is for research, it has data about serious topics related to individuals' mental health. It should not be taken as practical advice for real-life situations, except for the possibility that in the future, the dataset could be improved and discussions with its authors could facilitate extended usage.
Additional Information
Dataset Curators
The dataset was initially created by López Steinmetz and Lorena Cecilia, modified by Farias Federico, Arroyo Guadalupe and Avalos Manuel.
Licensing Information
Except where otherwise noted, this item's license is described as Atribución-NoComercial 4.0 Internacional (http://creativecommons.org/licenses/by-nc/4.0/).
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