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': 90
  • PROVINCE: 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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