Datasets:

electricsheepafrica
/

africa-synth-mental-health-psychosis-dataset-seychelles

region stringclasses 5 values	sex stringclasses 2 values	age float64 18 90	urban_rural stringclasses 2 values	poverty_index float64 0 0.93	education_level stringclasses 4 values	employment_type stringclasses 3 values	household_size float64 1 20	has_psychosis bool 2 classes	symptom_type stringclasses 5 values	attribution_model stringclasses 3 values	cannabis_use bool 2 classes	family_history bool 2 classes
East Africa	Male	29.831354	Urban	0.353677	Primary	Informal	6.203052	false	None	Spiritual_Ancestral	false	false
Central Africa	Female	19.69453	Rural	0.248558	Tertiary	Formal	4.390411	false	None	Social_Relational	false	false
North Africa	Female	18.399551	Rural	0.415959	Secondary	Informal	4.151995	false	None	Spiritual_Ancestral	false	false
Southern Africa	Female	18.399768	Rural	0.159968	Primary	Informal	4.152035	false	None	Spiritual_Ancestral	false	false
West Africa	Male	54.216067	Urban	0.550283	None	Informal	10.335257	false	None	Medical	false	false
West Africa	Male	35.039914	Urban	0.110945	None	Informal	7.107079	false	None	Medical	false	false
West Africa	Male	18	Urban	0.509897	None	Unemployed	3.603819	false	None	Medical	true	false
Central Africa	Female	30.674359	Rural	0.17727	Secondary	Formal	6.350411	false	None	Social_Relational	false	false
Southern Africa	Female	25.426972	Rural	0.19829	Secondary	Informal	5.425578	false	None	Spiritual_Ancestral	false	false
North Africa	Female	18	Rural	0.376237	Secondary	Informal	1.254604	false	None	Spiritual_Ancestral	false	false
West Africa	Male	18	Urban	0.543467	None	Unemployed	2.526957	false	None	Medical	true	true
Central Africa	Female	26.629242	Rural	0.084764	Tertiary	Formal	5.639155	false	None	Social_Relational	false	false
North Africa	Female	51.193044	Rural	0.357929	Secondary	Informal	9.834566	false	None	Social_Relational	false	false
West Africa	Male	18.51035	Urban	0.273321	Primary	Informal	4.17247	false	None	Medical	false	false
West Africa	Male	18	Urban	0.134376	None	Informal	3.440035	false	None	Medical	false	false
West Africa	Male	23.340759	Urban	0.353255	None	Informal	5.052277	false	None	Medical	false	false
East Africa	Male	18	Urban	0.13279	Primary	Informal	3.320352	false	None	Spiritual_Ancestral	false	false
East Africa	Female	18	Rural	0.326434	Primary	Informal	4.013159	false	None	Spiritual_Ancestral	false	false
East Africa	Male	21.4686	Urban	0.16581	Primary	Informal	4.714063	false	None	Spiritual_Ancestral	false	false
West Africa	Male	18	Urban	0.207734	Primary	Informal	2.449118	false	None	Medical	false	false
Southern Africa	Female	36.169496	Rural	0.263408	Secondary	Informal	7.301258	false	None	Spiritual_Ancestral	false	false
West Africa	Male	18	Urban	0.390014	None	Unemployed	2.179661	false	None	Medical	false	false
West Africa	Male	18	Urban	0.153645	Primary	Informal	2.013604	false	None	Medical	false	false
East Africa	Male	24.695486	Urban	0.305502	Primary	Informal	5.295091	false	None	Spiritual_Ancestral	false	false
East Africa	Male	34.455705	Rural	0.203314	Primary	Informal	7.006405	false	None	Spiritual_Ancestral	false	false
North Africa	Female	24.288296	Rural	0.183877	Secondary	Informal	5.222269	false	None	Spiritual_Ancestral	false	false
West Africa	Male	20.008563	Urban	0.367824	None	Informal	4.447943	false	None	Medical	false	false
East Africa	Female	18	Rural	0.202097	Primary	Informal	3.990753	false	None	Spiritual_Ancestral	false	false
Southern Africa	Female	18	Rural	0.18634	Primary	Informal	3.623474	false	None	Spiritual_Ancestral	false	false
West Africa	Male	41.249355	Urban	0.28352	None	Unemployed	8.167379	false	None	Medical	true	true
Southern Africa	Female	26.79572	Rural	0.100399	Secondary	Informal	5.668645	false	None	Spiritual_Ancestral	false	false
West Africa	Male	18	Urban	0.207729	None	Informal	3.794473	false	None	Medical	false	false
West Africa	Male	18	Urban	0.309638	None	Unemployed	3.162541	false	None	Medical	true	false
Central Africa	Female	31.975042	Rural	0.044386	Tertiary	Formal	6.576948	false	None	Social_Relational	false	false
Central Africa	Female	40.661519	Rural	0.124579	Tertiary	Formal	8.067709	false	None	Social_Relational	false	false
North Africa	Female	38.468908	Rural	0.211003	Secondary	Informal	7.694694	false	None	Social_Relational	false	false
East Africa	Male	18	Urban	0.358189	Primary	Informal	2.843593	false	None	Spiritual_Ancestral	false	false
West Africa	Male	18	Urban	0.652242	None	Unemployed	3.971512	false	None	Medical	true	false
Southern Africa	Female	18	Rural	0.162266	Secondary	Informal	3.582324	false	None	Spiritual_Ancestral	false	false
East Africa	Male	19.047128	Urban	0.069424	Primary	Informal	4.271461	false	None	Spiritual_Ancestral	false	false
West Africa	Male	35.962358	Urban	0.076848	None	Unemployed	7.265697	false	None	Medical	false	false
East Africa	Female	48.388966	Rural	0.174434	Primary	Informal	9.367746	false	None	Spiritual_Ancestral	false	false
West Africa	Male	27.43764	Urban	0.543454	None	Unemployed	5.782171	false	None	Medical	true	true
Central Africa	Female	18	Rural	0.061654	Tertiary	Formal	3.227709	false	None	Social_Relational	false	false
West Africa	Male	21.143588	Urban	0.235687	Primary	Informal	4.655011	false	None	Medical	false	false
Southern Africa	Female	53.821763	Rural	0.313294	Secondary	Informal	10.270094	false	None	Spiritual_Ancestral	false	false
East Africa	Male	22.973388	Urban	0.152583	Primary	Informal	4.986161	false	None	Spiritual_Ancestral	false	false
East Africa	Female	18	Rural	0.386886	Primary	Informal	3.995737	false	None	Spiritual_Ancestral	false	false
East Africa	Female	18.591369	Rural	0.48459	Primary	Informal	4.187433	false	None	Spiritual_Ancestral	false	false
West Africa	Male	27.359779	Urban	0.095939	None	Informal	5.768416	false	None	Medical	false	false
Central Africa	Female	18	Rural	0.366224	Tertiary	Formal	2.902245	false	None	Social_Relational	false	false
North Africa	Female	18	Rural	0.298373	Secondary	Informal	3.532612	false	None	Spiritual_Ancestral	false	false
Central Africa	Female	38.127233	Rural	0.223766	Tertiary	Formal	7.636383	false	None	Social_Relational	false	false
Central Africa	Female	26.87495	Rural	0.164292	Secondary	Formal	5.682673	false	None	Social_Relational	false	false
Southern Africa	Female	23.127253	Rural	0.461386	Primary	Informal	5.013867	false	None	Spiritual_Ancestral	false	false
Central Africa	Female	39.280995	Rural	0.098321	Tertiary	Formal	7.833085	false	None	Social_Relational	false	false
West Africa	Male	18	Urban	0.179248	None	Unemployed	3.111668	false	None	Medical	true	false
West Africa	Male	18	Urban	0.343019	None	Informal	3.927964	false	None	Medical	false	false
West Africa	Male	26.324263	Urban	0.27467	None	Unemployed	5.585079	false	None	Medical	true	true
East Africa	Male	25.740939	Urban	0.443295	Primary	Informal	5.481457	false	None	Spiritual_Ancestral	false	false
East Africa	Male	18	Urban	0.132724	Primary	Informal	1.885112	false	None	Spiritual_Ancestral	false	false
West Africa	Male	18	Urban	0.400643	Primary	Informal	3.713332	false	None	Medical	false	false
North Africa	Female	19.37826	Rural	0.322596	Secondary	Informal	4.332361	false	None	Social_Relational	false	false
East Africa	Male	28.174922	Urban	0.292362	Primary	Informal	5.912209	false	None	Spiritual_Ancestral	false	false
West Africa	Male	25.683112	Urban	0.113577	Primary	Informal	5.471171	false	None	Medical	false	false
East Africa	Female	20.589223	Rural	0.341559	Primary	Informal	4.554042	false	None	Spiritual_Ancestral	false	false
West Africa	Male	18	Urban	0.169996	None	Unemployed	1.24858	false	None	Medical	false	false
North Africa	Female	21.278732	Rural	0.801473	Secondary	Informal	4.679578	false	None	Social_Relational	false	false
West Africa	Male	22.565379	Urban	0.131771	None	Unemployed	4.912591	false	None	Medical	true	false
Central Africa	Female	81.910452	Rural	0.1255	Tertiary	Formal	14.825441	false	Strange Experiences	Social_Relational	false	false
North Africa	Female	18.956741	Rural	0.337014	Secondary	Informal	4.254816	false	None	Spiritual_Ancestral	false	false
West Africa	Male	26.415325	Urban	0.034399	None	Informal	5.601233	false	None	Medical	false	false
West Africa	Male	43.217601	Urban	0.159378	None	Unemployed	8.500122	true	Auditory Hallucinations	Spiritual_Ancestral	true	false
North Africa	Female	34.726473	Rural	0.261516	Secondary	Informal	7.053086	false	None	Social_Relational	false	false
North Africa	Female	49.569259	Rural	0.249119	Secondary	Informal	9.564532	false	None	Spiritual_Ancestral	false	false
North Africa	Female	18	Rural	0.068587	Secondary	Informal	1.904668	false	None	Spiritual_Ancestral	false	false
North Africa	Female	18	Rural	0.459506	Secondary	Informal	2.566231	false	None	Spiritual_Ancestral	false	false
West Africa	Male	18	Urban	0.541478	None	Unemployed	3.393076	false	None	Medical	true	false
East Africa	Male	18	Urban	0.260596	Primary	Informal	1.696733	false	None	Spiritual_Ancestral	false	false
West Africa	Male	22.691637	Urban	0.067536	None	Unemployed	4.935374	false	None	Medical	true	false
Central Africa	Female	18	Rural	0.046769	Secondary	Formal	2.694215	false	None	Social_Relational	false	false
Southern Africa	Female	53.425611	Rural	0.127131	Secondary	Informal	10.204584	false	None	Spiritual_Ancestral	false	false
East Africa	Male	18	Urban	0.326599	Primary	Informal	2.951027	false	None	Spiritual_Ancestral	false	false
West Africa	Male	18	Urban	0.119125	None	Unemployed	3.94115	false	None	Medical	true	false
East Africa	Male	35.982819	Urban	0.107767	Primary	Informal	7.26921	false	None	Spiritual_Ancestral	false	false
East Africa	Male	18	Urban	0.324601	Primary	Informal	2.163787	false	None	Spiritual_Ancestral	false	false
North Africa	Female	18	Rural	0.219354	Secondary	Informal	1.621517	false	None	Spiritual_Ancestral	false	false
Southern Africa	Female	24.499619	Rural	0.304792	Secondary	Informal	5.260079	false	None	Spiritual_Ancestral	false	false
Central Africa	Female	25.721584	Rural	0.40373	Secondary	Formal	5.478015	false	None	Social_Relational	false	false
East Africa	Male	35.332522	Rural	0.184129	Primary	Informal	7.157439	false	None	Spiritual_Ancestral	false	false
West Africa	Male	30.293292	Urban	0.234474	None	Unemployed	6.283853	false	None	Medical	true	false
North Africa	Female	26.338753	Rural	0.175069	Secondary	Informal	5.58765	false	None	Spiritual_Ancestral	false	false
North Africa	Female	18	Rural	0.267332	Secondary	Informal	3.15623	false	None	Spiritual_Ancestral	false	false
Southern Africa	Female	25.268307	Rural	0.2387	Primary	Informal	5.39731	false	None	Spiritual_Ancestral	false	false
North Africa	Female	26.273215	Rural	0.325796	Secondary	Informal	5.576021	false	None	Spiritual_Ancestral	false	false
East Africa	Female	18	Rural	0.443488	Primary	Informal	3.086972	false	None	Spiritual_Ancestral	false	false
East Africa	Female	62.368086	Rural	0.385567	Primary	Informal	11.673582	false	None	Spiritual_Ancestral	false	false
East Africa	Male	29.416459	Urban	0.096153	Primary	Informal	6.130368	false	None	Spiritual_Ancestral	false	false
West Africa	Male	18	Urban	0.208985	None	Unemployed	2.594406	false	None	Medical	true	true
West Africa	Male	35.439934	Urban	0.166196	None	Unemployed	7.175915	false	None	Medical	true	false

End of preview. Expand in Data Studio

⚠️ Synthetic dataset — Parameterized from published SSA literature, not real observations. Not suitable for empirical analysis or policy inference.

Dataset Card for Africa Psychosis Dataset

Dataset Summary

The Africa Psychosis Dataset is a synthetic dataset generated by Electric Sheep Africa to model mental health presentations in African contexts. It contains 100,000 rows and 13 columns. The generation is grounded in peer-reviewed literature from Sub-Saharan Africa, capturing region-specific prevalence rates, risk factors (e.g., poverty, conflict), and cultural presentations of distress (e.g., somatic symptoms, "thinking too much").

This dataset is designed for research, educational, and methodological testing purposes. It respects the statistical properties of real-world data without exposing any Private Identifiable Information (PII), as every record is entirely synthetic.

Supported Tasks and Leaderboards

Epidemiological Modeling: Simulating disease burden across different African regions.
Health Services Research: Analyzing the gap between need and treatment access (e.g., traditional healer usage).
Risk Factor Analysis: Logistic regression testing on variables like poverty index and conflict exposure.

Languages

English (Data labels). The cultural context covers West, East, North, Southern, and Central Africa.

Dataset Structure

Data Instances

A sample instance from the dataset:

[
  {
    "region":"East Africa",
    "sex":"Male",
    "age":29.8313536542,
    "urban_rural":"Urban",
    "poverty_index":0.3536766572,
    "education_level":"Primary",
    "employment_type":"Informal",
    "household_size":6.2030524535,
    "has_psychosis":false,
    "symptom_type":null,
    "attribution_model":"Spiritual_Ancestral",
    "cannabis_use":false,
    "family_history":false
  }
]

Data Fields

Field Name	Type	Description
`region`	object	Synthetic variable based on literature distributions.
`sex`	object	Synthetic variable based on literature distributions.
`age`	float64	Synthetic variable based on literature distributions.
`urban_rural`	object	Synthetic variable based on literature distributions.
`poverty_index`	float64	Synthetic variable based on literature distributions.
`education_level`	object	Synthetic variable based on literature distributions.
`employment_type`	object	Synthetic variable based on literature distributions.
`household_size`	float64	Synthetic variable based on literature distributions.
`has_psychosis`	bool	Synthetic variable based on literature distributions.
`symptom_type`	object	Synthetic variable based on literature distributions.
`attribution_model`	object	Synthetic variable based on literature distributions.
`cannabis_use`	bool	Synthetic variable based on literature distributions.
`family_history`	bool	Synthetic variable based on literature distributions.

Data Splits

Train/Val/Test: Not applicable (Single synthetic file). All 100,000 rows are available for splitting as needed.

Dataset Creation

Curation Rationale

There is a scarcity of high-quality, open-access mental health data from African regions. This dataset aims to fill that gap by synthesizing available knowledge from systematic reviews and small-scale studies into a coherent, usable format for data scientists.

Source Data

Initial Data Collection and Normalization

This data was generated using a probabilistic pipeline keying off parameter files derived from the literature:

Ekhator, C. N., et al. (2024). Mental Health Awareness in Rural vs. Urban Areas. CARI Journals.
- Parameter: Urban/Rural Mental Health Access (Qualitative Differences)
- Region: General Africa
Patel, V., et al. (2018). The Lancet Commission on global mental health and sustainable development. The Lancet.
- Parameter: Treatment Gap & Healer Usage (>85% Treatment Gap)
- Region: Global/Africa
Mbwayo, A. W., et al. (2013). Mental health in schools in Nairobi, Kenya. Journal of Child & Adolescent Mental Health.
- Parameter: Psychotic Like Experiences (Youth) (~10-20%)
- Region: Kenya (East Africa)
Burns, J. K., et al. (2014). Psychosis in Africa: A systematic review. Schizophrenia Research.
- Parameter: Psychosis Prevalence (1% - 4.4%)
- Region: Sub-Saharan Africa
Abbo, C. (2011). Profiles and outcome of traditional healing practices for severe mental illnesses in two districts of Eastern Uganda. Global Health Action.
- Parameter: Traditional Healer Usage (High (~60% first contact))
- Region: Uganda (East Africa)

Personal and Sensitive Information

This dataset contains fake medical info. No real individuals are represented. However, it models sensitive topics (Depression, Psychosis, HIV status) and should be handled with the ethical care appropriate for health data to avoid stigmatization in downstream analyses.

Considerations for Using the Data

Social Impact of Dataset

Positive: Enables tool development for under-resourced regions.
Negative: If treated as "real" ground truth without validation, it could lead to incorrect policy assumptions. Always validate synthetic findings against local clinical data.

Discussion of Biases

Literature Bias: The data reflects the biases of the underlying studies (e.g., more data from South Africa/Nigeria/Kenya than other regions).
Simplification: Complex interactions (e.g., genetic vs environmental) are simplified into probabilistic dependencies.