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Development and validation of home-based psychosocial self-management interventions in schizophrenia and related disorders in low-resource settings: A mixed methods approach

2024· article· en· W4398146134 on OpenAlexaff
Rakesh Kumar Chadda, Mamta Sood, Nishtha Chawla, Ananya Mahapatra, Rekha Patel, Mohapradeep Mohan, Srividya N. Iyer, Padmavati Ramachandran, R. Thara, Jai Shah, Jason Madan, Max Birchwood, Caroline Meyer, Richard Lilford, Vivek Furtado, Currie Graeme, Swaran P. Singh

Bibliographic record

VenueIndian Journal of Psychiatry · 2024
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsDouglas Mental Health University InstituteMcGill University
Fundersnot available
KeywordsPsychosocialSchizophrenia (object-oriented programming)Psychological interventionIntervention (counseling)PsychiatryResource (disambiguation)Mental healthPsychologyClinical psychologyMedicineComputer science

Abstract

fetched live from OpenAlex

Background: Psychosocial interventions, crucial for recovery in patients with schizophrenia, have often been developed and tested in high income countries. We aimed at developing and validating home-based a booklet based psycho-social intervention with inputs from stakeholders: patients, families, and mental health professionals (MHP) for patients with schizophrenia and related disorders in low resource settings. Methods: We developed a preliminary version of psychosocial intervention booklets based on six themes derived from focus group discussions conducted with patients, families, and MHP. Initially, quantitative assessment of content validity was done by MHP on overall and Content Validity Index of individual items of the specific booklets, followed by in-depth interviews about their views. The booklets were modified based on their inputs. Further, pilot testing of manuals was done on the users - nine pairs of patients and caregivers followed by development of a final version of psycho-social intervention. Results: The percentage content validity of individual modules and overall booklets was ≥78.5% indicating good validity. Most MHP reported that the manuals were relevant and easy to use but were text-heavy, and lengthy. On pilot testing of modified manuals with patients and their family caregivers, majority (77.8%) of them found booklets useful and suggested that there should be separate booklets for both patients and caregivers for providing information and entering separate response for the activities, integrating helpful tips. Language should be simple. Finally, two sets of booklets ("info book" and "workbook") named 'Saksham' (meaning empowered) were created with specific modules (viz., 'Medicine adherence', 'Daily routine', 'Eating right', 'Physical activity', 'Physical health monitoring', 'Self-reliance', and 'Psychoeducation') for patients and caregivers each, in two languages (Hindi and English). Conclusion: Booklets with modules for psychosocial interventions for patients with schizophrenia and their caregivers were developed after establishing content validity and pilot testing.

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.

How this classification was reachedexpand

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.793
Threshold uncertainty score0.470

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.315
Teacher spread0.304 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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