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Record W4400404929 · doi:10.1101/2024.07.08.24310056

The National Psychiatric Morbidity Survey of Pakistan (2022): Prevalence, socio-demographic and disability correlates

2024· preprint· en· W4400404929 on OpenAlex
Raza-Ur Rahman, David V. Sheehan, Afzal Javed, Sameena Ahmad, Kamran Shafiq, Uzma Kanwal, Muhammad Iqbal Afridi, Asad Tamizuddin Nizami, Ghareaghaji Asl Rasool, Rizwan Taj, Muhammad Akram Ansari, Saeed Farooq, Anjum Memon, Y Hana, Muhammad Ayub

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsnot available
FundersYork University
KeywordsPsychiatryMedicineDemographyGeographySociology

Abstract

fetched live from OpenAlex

Abstract Background National psychiatric morbidity surveys have shown a wide range of prevalence of psychiatric disorders across different countries. Pakistan with its sociocultural and ethnic diversity, has the fifth largest population in the world. There was no prior high-quality nationally representative data on the prevalence of psychiatric disorders and their socio-demographic correlates for Pakistan. To fill this gap in the planning of mental health services, the Pakistan Psychiatric Society conducted the National Psychiatric Morbidity Survey (NPMS) of Pakistan, in the years 2019-2022. Aim To estimate the prevalence and socio-demographic correlates of psychiatric morbidity in a representative sample of Pakistan. Methods The cross-sectional NPMS collected data from the four provinces of Pakistan. After selection through a three-stage, stratified, random cluster sampling technique we interviewed 17,773 adults above the age of 18. We used the MINI International Neuropsychiatric Interview (MINI Version 7.0.2) to evaluate psychiatric morbidity. Current and lifetime precise and weighted prevalence is reported according to ICD-10 (International Classification of Disease-10 th version). We used multivariate logistic regression to investigate the association between the risk of psychiatric illness and sociodemographic variables. National Bio-ethic Committee of Pakistan granted approval of survey. Results The lifetime and current weighted prevalence of all psychiatric disorder is 37.91% (95% Confidence Interval (CI) =37.22-38.59) and 32.28% (95% CI=31.62-32.94) respectively. The weighted prevalence of common psychiatric disorders in Pakistan included Mood Disorders (F30-F39; 19.62%), Neurotic and Stress-related Disorders (F40 F48; 24.81%), Psychotic Disorders (F20-F29; 4.52%) and Mental and Behavioural Problems due to Psychoactive Substance use (F10-F19; 0.85%). The psychiatric disorders had an association with age, female gender, urban living, lower income and being divorced. Among participants, 6.17% acknowledged suicidality in the past month, while 1.05% acknowledged a lifetime suicide attempt. Conclusion The NPMS is the first nationally representative study of psychiatric morbidities in Pakistan. The data from this survey can be utilized for designing and implementing mental health services and support programmes in the country.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.896

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.375
Teacher spread0.335 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it