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Mental Hospitals in India: Reforms for the future

2018· review· en· W2885857925 on OpenAlex
Avinash Desousa, Muktesh Daund, Sushma Sonavane, Amresh Shrivastava, Sanjay Kumawat

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIndian Journal of Psychiatry · 2018
Typereview
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsWestern UniversityLawson Health Research Institute
Fundersnot available
KeywordsMental healthPsychosocialWorkforceGovernment (linguistics)CommissionMental illnessStigma (botany)MedicineModernization theoryAccountabilityPolitical scienceEconomic growthNursingPsychiatryPublic relations

Abstract

fetched live from OpenAlex

Mental hospitals are an integral part of mental health services in India. It is an interesting story how mental hospitals have responded to the challenges of contemporary period they were built in. It is beyond doubt that it is a progressive journey along with advances in mental health both in India and internationally. As in other countries, mental hospitals in India have responded to the social challenges, disparities, and poor resources of workforce and fiscal investment. Historically, there have been changes and three major reforms are needed, namely attempt to facilitate discharge and placing patients back into the family, introducing teaching and research in mental hospitals, and accountability to civil rights as per the requirements of the National Human Rights Commission. In this review, we explore the brief history of mental hospitals in India and examine the reforms in the clinical, administrative, and psychosocial areas of these hospitals and progress in teaching and research. We finally summarize and conclude the necessity and the relevance of mental hospitals in India akin to modern psychiatric practice. We believe that mental hospitals have an important and perhaps a central role in mental health services in India. Its modernization to address issues of long-term stay, burden on caregivers, stigma, research and teaching including undergraduate and postgraduate training, new curriculum, and training for nonpsychiatric professionals and primary care physicians are necessary components of the role of mental hospitals and responsibilities of both government and nongovernmental sectors. Last but not the least, it is obligatory for mental hospitals to ensure that evidence-based treatments are implemented and that the standard of care and respect of civil and human rights of the patients and families are provided while involving the people's participation in its functioning.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.938
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.399
Teacher spread0.373 · 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