Redefining Access to Mental Health Care Through Sustained Tele-mentoring: A Report of the Instant Collaborative Video Consultations with Primary Care Doctors
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: Mentoring primary care doctors (PCDs) improves their competency and aids in integrating psychiatric care into primary care, especially in resource-constrained settings. This study evaluates the socio-demographic, diagnostic, and treatment profiling of instant collaborative video consultations (i-CVCs) and the diagnostic (domain-wise and disorder-wise) and treatment concordance of PCDs with tele-psychiatrists. Methods: This was a cross-sectional study that was a part of a digitally driven capacity-building program that provided tele-mentoring to PCDs via i-CVCs with tele-psychiatrists. A total of 382 i-CVCs conducted between November 2022 and July 2024 were analyzed for diagnostic and treatment profiling. Concordance between PCDs and tele-psychiatrists was assessed using Cohen’s kappa ( n = 358). Results: Among the domain-wise diagnostic distribution by the tele-psychiatrist, the majority were classified as common mental disorders (CMDs) (47.7%), and among the disorder-wise distribution, the majority was depressive disorder (22.5%). The analysis revealed very good to good diagnostic agreement between PCDs and tele-psychiatrists across major domains: SUD (κ = 0.96), SMD (κ = 0.81), and CMD (κ = 0.75), all with p < .001. Disorder-wise concordance was highest for alcohol disorders (κ = 0.96). Treatment concordance also showed moderate agreement for all the major classes of psychotropic medications (κ = 0.5 to 0.6; p < .001), including antidepressants, antipsychotics, benzodiazepines, and nicotine replacement therapy. i-CVC support was primarily sought for diagnostic/treatment confirmation and clarification on dosage strategies. Conclusions: i-CVCs facilitate real-time learning and improve confidence in managing psychiatric disorders within live primary care clinics, demonstrating a scalable approach to address the treatment gap.
Authors: Chandana Sabbella, Hetashri Shah, Prakyath Ravindranath Hegde, Rahul Patley, Sivakami Sundari S, Narayana Manjunatha, Channaveerachari Naveen Kumar, Suresh Bada Math
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4414329696