Sage Journals: Discover world-class research

Abstract

Background:

India has made significant strides in digital mental health capacity building over the past decade. This pan-India initiative was implemented through National Institute of Mental Health and Neurosciences (NIMHANS) to enhance the delivery of primary mental healthcare by digitally training medical officers (MOs), community health officers (CHOs), and field-level workers (FLWs) of India.

Methods:

Between October 2022 and June 2024, the program engaged MOs, CHOs, and FLWs of Karnataka, Maharashtra, Telangana, Uttarakhand, Bihar, Goa, Kerala, and West Bengal in a standardized six-week-district-wise digital training module curated to identify and manage commonly prevalent psychiatric disorders in primary care settings. Onsite training was conducted for participants in Tripura and Telangana. Participant engagement and changes in knowledge, attitude, and practice (KAP) scores were analyzed for each cadre along with ongoing support through real-time collaborative video consultations (CVCs).

Results:

The program engaged 42,192 participants (7248 MOs, 18,993 CHOs, and 15,951 FLWs) across nine Indian states. Overall, participants attending ≥50% of training revealed higher engagement in CHOs of Bihar (80.51%), followed by MOs of Goa (69.7%), followed by FLWs of West Bengal (64.57%). Paired t-test analysis of KAP scores showed post-training statistically significant (p < .05) improvement for MOs of Karnataka, Maharashtra, Telangana (onsite), and Goa; CHOs of Karnataka, Maharashtra, Telangana (onsite), Tripura (onsite) and Bihar; and FLWs of Karnataka, West Bengal, and Kerala. A total of 1,320 CVCs were conducted, assisting the management of psychiatric disorders in the community.

Conclusion:

Digital capacity building is a viable, scalable, and practical approach for mental health training of frontline workers to improve their clinical KAP.

Keywords

Capacity building primary mental healthcare Pan-India Mental Health Program digital health training tele-mentoring in mental health

Key Messages:

Digital capacity-building in mental health can deliver real, measurable benefits at scale, potentially enhancing provider knowledge, reducing stigma, and improving community mental health outcomes.

Success hinges on strong governance, thoughtful incentivization, and coordinated implementation.

Mental health disorders are the second leading cause of disease burden in terms of years lived with disability (YLDs) and the sixth leading cause of disability-adjusted life years (DALYs) globally. Coupled with a 70–90% treatment gap in India, this situation presents a significant challenge for the country’s healthcare system.^1,2 There is a scarcity of mental health professionals, compounded by stigma, which results in inadequate community outreach. Moreover, existing literature highlights the concept of the “functional treatment gap,” which lies in Indian primary care environments owing to the lack of knowledge for recognizing and treating prevalent mental health disorders in the community.³ This can be addressed, in part, by fortifying the existing primary healthcare system to enhance early recognition and treatment, that is, capacity building. Hence, central and state governments have actively collaborated on various mental health capacity-building initiatives in the last decade, such as the integration of mental health in primary care by district mental health program, the “Atmiyata” program in Maharashtra, “Amma Manasu” (Mother’s mind) in Kerala, and “Manochaitanya” program by Karnataka state government.^4–7 Some limitations of onsite training of primary healthcare workers are lack of scalable outreach, high costs, and inadequate human resources.

In this digital age, leveraging digital methods for capacity building appears feasible and advantageous due to their accessibility, cost-effectiveness, reduced need for human resources, and inherent flexibility. Several digital training initiatives are focusing on mental health capacity building in India, such as the National Institute of Mental Health and Neurosciences (NIMHANS) digital academy online courses, The Karnataka Telemedicine Mentoring and Monitoring Program (KTM), NIMHANS ECHO model, Project ESSENCE in Madhya Pradesh, Project EMPOWER in Gujarat and MINDS community mental health worker program.^8–10 These digital training initiatives have substantially improved frontline workers’ knowledge, attitudes, and practices, helping to reduce stigma and the treatment gap.

Public–private partnerships (PPPs) are vital in transforming mental healthcare systems, particularly in addressing gaps in service delivery, access, and resources. In the mental health sector of developing countries, PPPs can drive innovation and improve outcomes by combining the strengths of both public and private sectors. Governments provide the policy framework, public health infrastructure, and outreach capacity, while private organizations contribute expertise, technology, funding, and efficiency.²¹ This article examines the implementation and performance of a pioneering pan-India, digitally driven capacity-building program for primary mental healthcare conducted by National Institute of Mental Health and Neurosciences (NIMHANS) through funding from a multinational agency. As the first initiative in India, this program addresses the critical treatment gap in mental health through an innovative PPP model. This program aimed to empower primary care doctors/medical officers (MO), community health officers (CHO), and field-level workers (FLW) in nine Indian states. By training all three cadres within the community simultaneously, the program sought to enhance the early identification of psychiatric disorders and facilitate prompt treatment initiation by strengthening the hierarchical referral network in the community.

Methods

The program was initially conceived during the coronavirus disease 2019 (COVID-19) pandemic to equip frontline workers with the skills to address the emerging mental health morbidities in the general population. A memorandum of understanding (MoU) was signed between NIMHANS and the multinational funding agency for the program in March 2022. The program progressed as per the phases shown in Table 1. This digital training program was implemented by NIMHANS over the period from April 2022 to November 2024, encompassing various phases, as shown in Table 1. As the program progressed, this initiative engaged nine states across India in a time-bound manner (Table 1).

Table 1.

Phases of Pan-India Digital Mental Health Capacity Building Program.

Phase	Activity	Duration
Preparatory phase	Recruitment of staff Developing training module contents Enrollment of trainees from various states Signing of memorandum of understanding (MoU) with state governments Need assessment in states Developing strategies for nominations Developing Information, Education, and Communication (IEC) materials	6 months (April 2022–September 2022)
Pilot phase	Conducting pilot training for all three cadres in various states	3 months (October 2022–December 2022)
Modifications phase	Training material Training Schedule Revisiting engagement strategies	1 month (January 2023)
Phase of delivery of training	Medical officers (MOs) Community health officers (CHOs) Field-level workers (FLWs) States: Karnataka, Maharashtra, Telangana (onsite), Uttarakhand, Bihar, Goa, Kerala, West Bengal, Tripura (onsite) Data collection	16 months (February 2023– June 2024)
Analysis phase	Outcome evaluation research, data assessments e-Certifications, report writing and submission	5 months (July 2024–November 2024)

Trainers

The trainers’ team consisted of nine psychiatrists, three clinical psychologists, three psychologists, two psychiatric social workers, two psychiatric nursing officers, and three medical social workers who were collectively involved in the development of training materials, information, education, and communication materials, conducting the training sessions, and providing follow-up support. Two IT professionals and seven project coordinators facilitated online training sessions and managed the data registry.

Training Module, Materials, and Schedule

Curated training modules were specifically developed for this project for the three cadres: MOs, CHOs, and FLWs. Training for CHOs and FLWs was conducted in local languages to enhance comprehension and participation, with materials developed in English and translated into Kannada, Marathi, Hindi, Malayalam, and Telugu. The MO training was conducted in English, which was observed to be a comfortable and appropriate medium. The online classroom teaching training included standardized PowerPoint presentations on introduction to mental health disorders, common mental health disorders (CMD), severe mental health disorders (SMD), substance use disorders (SUD), pandemic preparedness, and Tele-MANAS overview. The MOs’ training utilized Clinical Schedules for Primary Care Psychiatry: Version 2.4 (CSP 2.4), which is a point-of-care manual specifically designed for MOs by NIMHANS containing guidelines for screening, early diagnosis, referral, first-line prescription templates, and routine follow-ups of adult patients with psychiatric disorders at outpatient settings of primary health centers.¹¹ Mental Health Screening and Counselling Tool (MERIT) developed by NIMHANS containing categorical questions for effective mental health disorder screening was integrated into CHOs and FLWs’ modules.¹² The training schedule for MOs and CHOs comprised 120 minutes of weekly online sessions for six weeks, whereas for FLWs, it was for four weeks. Table 2 demonstrates the outline of a model session.

Receiving Nominations and Engagement Strategies

After signing MoU/equivalent written agreements with the respective state government health departments/agencies in the states of Karnataka, Maharashtra, Uttarakhand, Kerala, West Bengal, Goa, and Bihar, the district health administrators were approached by the team to obtain nominations of the consenting participants in all three cadres to schedule the online training (Figure 1). Communication and training materials distribution were handled via dedicated district-wise groups through a popular online messaging platform for seamless information sharing and continuous engagement. Additionally, Telangana MOs, CHOs, and Tripura CHOs were trained on-site at the request of the respective state governments. Participants were given access to specialists at NIMHANS for expert guidance in the screening and management process through instant collaborative video consultations (CVCs), available during working hours on all days, and audio consultations, accessible 24/7 for continuous support as needed. Through CVCs, trainees can seek instant video consultations with the tele-psychiatrist/clinical psychologist for real-time second opinions on patient diagnosis and treatment, also providing follow-up consultations for up to three months.^13,14

Table 2.

Outlines of a Model Online Session of This Digital Program.

Pre-online session preparation (2 days)	Review: The training content and defining learning objectives
	Reliable platform for digital training: Setting up the online video meeting link, ensuring all necessary access (e.g., password protection and waiting room) 2 days prior to the scheduled session, sending participants the link to the session along with a brief outline of what will be covered and timely reminders for the next 2 days though designated messaging groups
	Testing technology: Audio, video, and presentation materials in the allotted studio at NIMHANS (hub).
Conducting the online session (120 minutes)	Session setup: Early log-in by trainer 15 minutes prior to the session, greeting participants as they join, encouraging interaction by unmuting and chat box, encouraging turning the video on when feasible, introduction to the objectives of the session, topic-based virtual case-conference or role-play
	During the session: The content will be presented with more visual aids and fewer texts. Interaction will be encouraged through polls and case scenario discussions
	Ending the session: Summarizing key points, Q&A, case-based discussions, feedback, distribution of session materials, and brief information about the next session
Post-online session follow-up	Review feedback, clarifications of doubts, distribution of relevant materials, continued engagement with district administrators, and encouragement of the CVC process and screening.

CVC: Collaborative video Consultation, Q&A: Questions and Answers.

Figure 1.

MoU: Memorandum of understanding, MO: Medical officers, CHO: Community health officers, FLW: Field level workers, CVC: Collaborative video consultations, PHC: Primary health center, HWC: Health and wellness center, IEC: Information, Education and Communication, NIMHANS: National Institute of Mental Health and Neurosciences.

Data Collection and Certification

Data was collected after obtaining informed verbal consent from all participants involved in digital training, assessment forms, and CVCs. Curated online forms (e-forms) were utilized for pre-training and post-training assessments of Knowledge, Attitude, and Practice (KAP) out of a total score of 28. Monthly, interim, and annual reports (of cases managed) were also utilized to track progress whenever feasible. Focused group discussions were conducted for different cadres in different states to understand the impact and challenges of the training. Training completion e-certificates were distributed after successful completion of training, that is, attendance in more than 80% of online sessions, completion of pre-and post-training assessments, and 1 CVC. Participation e-certificates were distributed to the remainder of the participants who failed to fulfill the earlier criteria. Descriptive impact stories and testimonials from a few district participants were collected post-training. A paired samples T-test was employed to assess the KAP scores before and after the training using licensed SPSS version 29. Only the participants’ scores who completed the pre- and post-KAP forms were analyzed. Institutional Ethics Committee approval was obtained for the same.

Outcome Evaluation

To study the impact and outcome of the program scientifically in MOs, a hybrid cluster randomized control trial was conducted after Institutional Ethics committee approval in the district of Tumkur, Karnataka.^15–17

Results

This digitally driven mental healthcare capacity development program engaged a total of 42,192 participants across all three cadres in the states of Karnataka, Maharashtra, Telangana, Uttarakhand, Bihar, Goa, Kerala, West Bengal, and Tripura in 20 months (Figures 2 and 3).

Figure 2.

MO: Medical Officers, CHO: Community health officers, FLW: Field-level workers.

Figure 3.

MO: Medical officers, CHO: Community health officers, FLW: Field-level workers.

Analysis of attendance during online and onsite training revealed the best and most consistent engagement during onsite training compared to online training, as predicted (Table 3). However, in digital training, Bihar CHOs (80.51%), Goa MOs (69.7%), and West Bengal FLWs (64.57%) showed better participant engagement compared to other states (Table 3).

Quantitative analysis was conducted on pre- and post-training KAP scores using paired samples t-tests for all three trained cadres in each state (Tables 4–6) with p <.05 was considered significant. Statistically significant improvements were observed in KAP assessment scores following online training for MOs in Karnataka, Maharashtra, Telangana(onsite) and Goa (Table 4); for CHOs in Karnataka, Maharashtra, Bihar, Telangana(onsite) and Tripura(onsite) (Table 5); for FLWs in Karnataka, West Bengal, and Kerala (Table 6).

The CVCs were integrated as a form of extended handholding during and three months post-training for all the cadres. One thousand one hundred seventy total CVC cases were discussed during the program. Table 7 summarizes CVCs received during the program from all three cadres identifying and managing psychiatric cases in primary care environments. The “Others” category includes non-CSP psychiatric diagnoses, cases that were not yet diagnosed, and non-psychiatry diagnoses. More details on CVCs can be found in separate articles in this supplement.^18,19

Discussion

This digital capacity-building initiative effectively empowered 42,192 participants over nearly 20 months, significantly advancing mental healthcare delivery within India’s primary healthcare systems. The program’s implementation plan and evolving engagement strategies were instrumental in driving notable improvements in performance outcomes. Despite the challenges inherent in such a large-scale initiative, developing thoughtful and strategic solutions ensured the program’s objectives were successfully achieved amidst real-world implementation complexities.

Maintaining participants’ consistent engagement throughout the online training was the program’s most significant challenge. Various strategies were employed to improve attendance, contributing to sustained participation in several districts. These included pre-training orientation sessions to assess schedule feasibility and familiarize participants with the digital platform; repeated engagement with district administrators to promote attendance; timely reminders via online messaging groups; regular dissemination of IEC materials; continuous encouragement to attend training and complete CVCs; and interactive activities like virtual case conferences and role-plays at the start of training sessions. However, the effectiveness of these strategies fell short in districts where there was little to no engagement from the outset of the training.

The variations in attendance (Table 3) clearly emphasize that engagement is better ensured onsite than online training. The active monitoring support from the state government and district administration influenced participant engagement, which has been reflected in district-wise attendance variations within and across the states. Several factors contributing to the lower attendance in online training were identified, including limited administrative support, lack of incentivization or reinforcement, digital illiteracy, particularly among the FLW cadre, low participant motivation, poor internet connectivity, training during busy work hours, and overlapping online training sessions, especially within the MO cadre. These factors were highlighted in the focused group discussions with these cadres, as discussed in the articles by Shah et al.²⁰ and Pearala et al.,²¹ which also aligns with existing literature.²² As per a systematic review of 19 qualitative studies on digital health interventions done by O’Connor et al., participant motivation remains one of the most significant factors influencing engagement.²³

It is noteworthy that attendance rates are comparatively higher for Bihar CHOs (80.51%) (Table 3) and Goa MOs (≈ 70%) in digital training, which emphasizes the role of strong administrative support. In several districts, such support contributed to high participant engagement. This included prompt responses from administrators, assistance with training schedules, brief yet impactful participation in orientation sessions, and continuous encouragement to meet certification criteria. Another reason for better engagement in Bihar CHOs in online training and Tripura CHOs in onsite training was the involvement of implementation partners working closely with state administrations. These partners facilitated IEC distribution, enhanced engagement, and ensured the smooth execution of training.²⁴ his underscores the critical role of local implementation partners in large-scale capacity-building programs. Another key finding from the program was that CHOs demonstrated higher engagement and significantly better post-assessment scores in online training compared to MOs and FLWs, indicating the CHO cadre’s greater feasibility and adaptability to digital formats.

Table 3.

State-wise Distribution of Participants in All Three Cadres with Attendance of ≥3 Online Sessions (≥ 50%) During the Training.

State	Number of Participants with ≥ 50% Attendance in Training			Total (n, %)
State	MO (n, %)	CHO (n, %)	FLW (n, %)	Total (n, %)
Karnataka	622 (22.89%)	3,480 (47.71%)	3,198 (40.63%)	7,300 (40.82%)
Maharashtra	173 (4.75%)	783 (11.67%)	296 (3.74%)	1,252 (6.86%)
Telangana	11(4.66%)	15(6.35%)	–	26 (5.50%)
Telangana (onsite)	95 (100%)	68 (100%)	–	163 (100%)
Uttarakhand	31(6%)	35 (3.5%)	–	66 (4.71%)
Bihar	–	2,372 (80.51%)	–	2,372 (80.51%)
Tripura (onsite)	–	396 (100%)	–	396 (100%)
Goa	23 (69.7%)	–	–	23 (69.7%)
West Bengal	–	–	113 (64.57%)	113 (64.57%)
Kerala	5 (100%)	12 (100%)	11 (100%)	28 (100%)
Total	960(13.24%)	7,161(37.70%)	3,618(22.68%)	11,739(27.82%)

MO: Medical officers, CHO: Community health officer, FLW: Field level workers, n: Number of participants.

In our program, participants’ KAP scores demonstrated statistically significant improvement across all cadres following both online and onsite training in most states (Tables 4–6). Considering the large sample size, these findings will likely apply on a broader scale. This also replicates the existing evidence on the impact of digital training on frontline workers in mental health.²⁵ Despite consistent efforts to ensure uniform implementation of the training across all states, a few cadres in certain states did not show significant improvement in post-training KAP scores. Insights from focus group discussions with district-level cadres pointed to several contributing factors: poor network connectivity, limited digital literacy, and competing workload during training hours may have affected participants’ ability to engage with the content and retain information fully. Furthermore, irregular attendance and varying levels of personal interest may have influenced participants’ motivation to complete training assessments. The lack of substantial improvement in KAP scores for Kerala, Uttarakhand, and Telangana may be attributed to evidently lower engagement during the training (Table 3) and a limited number of participants (n < 20) submitting assessment forms from those states (Tables 4–6). Given that the training was conducted in the respective local language of each state, language was unlikely to have been a barrier or to have affected training outcomes.

Table 4.

Pre-and Post-training Analysis of KAP Score of MO Cadre.

States	MO (n)	Mean pre-KAP Score (SD)	Mean post-KAP Score (SD)	t	p-value
Karnataka	132	14.17(3.19)	16.01(3.13)	-8.50	<0.001
Maharashtra	238	13.47(2.61)	14.95(3.07)	-6.80	<0.001
Telangana(Online)	8	15.75(2.25)	16.88(2.23)	-2.34	0.051
Telangana(Onsite)	21	14.04(2.80)	18.04(2.24)	-6.56	<0.001
Goa	20	15.05(2.87)	18.05(2.08)	-4.33	<0.001
Kerala	5	13.80(3.03)	16.20(3.63)	-1.07	0.342
Uttarakhand	4	18.50(1.73)	18(2.82)	0.77	0.495
Total	428	13.89(2.88)	15.57(3.14)	-11.05	<0.001

n- Includes only the number of participants who have filled in both pre and post training assessment e-forms, (Degree of freedom= n-1); MO- medical officers, SD- Standard deviation, t- paired sample test t-value, p- two-sided p value.

Table 5.

Pre-and post-training analysis of KAP scores for the CHOs cadre

States	CHO (n)	Mean pre-KAP Score (SD)	Mean post-KAP Score (SD)	t	p-value
Karnataka	552	17.94(4.85)	18.93(5.07)	-5.13	<0.001
Maharashtra	483	17.41(4.69)	18.51(5.23)	-5.83	<0.001
Telangana(Online)	18	16.94(3.53)	19.06(6.00)	-1.59	0.130
Telangana(Onsite)	54	20.00(3.36)	22.07(3.81)	-3.69	<0.001
Bihar	2403	15.54(5.27)	17.39(5.78)	-17.57	<0.001
Tripura (Onsite)	268	18.25(4.55)	22.23(3.47)	-15.39	<0.001
Kerala	9	20.11(3.88)	19.78(6.09)	0.29	0.778
Total	3792	16.40(5.19)	18.15(5.61)	-21.77	<0.001

n- Includes only the number of participants who have filled in both pre and post training assessment e-forms, (Degree of freedom= n-1); CHO- community health officer, SD- Standard deviation, t- paired sample test t-value, p- two-sided p value.

Table 6.

Pre-and post-training analysis of KAP scoresforthe FLW cadre

States	FLW (n)	Mean pre-KAP Score (SD)	Mean post-KAP Score (SD)	t	p-value
Karnataka	343	16.13(2.66)	16.55(2.77)	-2.86	0.004
Maharashtra	31	15.29(3.40)	14.32(3.21)	1.52	0.138
West Bengal	91	18.18(2.70)	19.11(2.32)	-2.98	0.004
Kerala	17	17.41(2.87)	22.24(3.89)	-6.20	<0.001
Total	482	16.50(2.85)	17.09(3.17)	-4.29	<0.001

n- Includes only the number of participants who have filled in both pre and post training assessment e-forms, (Degree of freedom= n-1); FLW- field level workers, SD- Standard deviation, t- paired sample test t-value, p- two-sided p value.

Through ongoing support from CVCs, this program empowered trained frontline workers to manage 476 cases of CMDs, 219 cases of SMDs, and 200 cases of SUDs within the community (Table 7). It is important to clarify that instant CVCs were provided only for cases where the PCDs, CHOs, and FLWs had uncertainties regarding the diagnosis or management of the case. Therefore, the total number of CVCs does not reflect the cases handled during training. Sustained tracking of monthly reports remains a daunting challenge in our country, primarily due to the limitations of the existing public healthcare systems. Arguably, this area requires immediate strengthening, and “all-out” efforts should be dedicated considering the rapid developments in other domains of mental healthcare systems. Tracking the footfalls in out-patient clinics in primary care settings would be one of the sensitive indicators of the performance and success of a mental health program. To address this, digital technology should be utilized more effectively.²⁶ States like Chhattisgarh and Karnataka have set exemplary benchmarks in this regard, providing models that can be easily adapted by other states and Union Territories.²⁷ Returning to the topic of CVCs, they played a pivotal role in fostering collaboration between specialists and frontline workers following online mental health training. They provide real-time feedback on clinical applications and demonstrate the training program’s tangible impact. Continued CVC support also promoted post-training engagement.^18,19 Additionally, CVCs offer a scalable and economically sustainable model for future mental healthcare delivery.²⁸

Table 7.

Summary of Collaborative Video Consultations During the Program.

Cadre	CMD CVCs	SMD CVCs	SUD CVCs	Others	Total
MO	182	53+5^a	75	98	413
CHO	243	126	108	114	591
FLW	51	35	17	63	166
Total	476	219	200	275	1,170

^aCo-morbid SUD with predominant SMD cases.

CVC: Collaborative video consultations, CMD: Common mental disorders, SMD: Severe mental disorders, SUD: Substance use disorders, Others: Non-CSP psychiatric diagnoses + cases which were not yet diagnosed + non-psychiatry diagnoses.

Limitations

One limitation of this digital program was the absence of a structured incentivization plan for training participation. Although e-certificates initially boosted participation, this motivation waned over time. Designing an effective incentivization strategy for such a large-scale digital initiative necessitates the involvement of multiple stakeholders, which may not always be feasible in real-world scenarios. Nevertheless, when logistical challenges were effectively addressed on both ends, the program demonstrated successful participant engagement in digital training. This also calls for robust administrative strategies at the district level to enhance the feasibility of digital training, which would foster greater engagement. Another limitation of the implementation plan was the absence of an onsite training component, which, as evidenced by existing literature and our findings, could have increased participant engagement. However, incorporating onsite training for 42,192 participants would have compromised scalability, cost-effectiveness, and the overall duration of the program. Looking ahead, a hybrid training model that integrates the strengths of both in-person and online training would be ideal, maximizing engagement and enhancing the clinical translation of skills as adopted by the Chhattisgarh Community Mental Healthcare Tele-Mentoring Program (CHaMP) and Bihar primary care doctors blended training by NIMHANS.^29–31

Conclusion

Viewing this digital capacity development program through a realistic lens allows for a practical, grounded assessment of its scalability and impact. It demonstrates that integrating digital technology is a viable approach to achieving meaningful outcomes in primary care in India. Digital training has significantly improved mental health knowledge and outcomes for the community, thereby reducing the treatment gap and decreasing stigma among patients, caregivers, and frontline care providers. It has also fostered healthier attitudes and practices in community mental health. Strong local administrative support, effective incentivization, and collaboration with implementation partners are key to successful large-scale digital mental health training rollout.

Supplemental Material

Supplemental material for this article is available online.

Footnotes

Acknowledgements

Same as the “Introduction” article of this issue (Indian J Psychol Med. 2026;48(1 suppl)).

Declaration of Conflicting Interests

The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Author Channaveerachari Naveen Kumar is the Principal Investigator of this project and supplemental issue. The author did not take part in the peer review or decision-making process for this submission and has no further conflicts to declare.

Declaration Regarding the Use of Generative AI

The authors utilized ChatGPT for only occasional writing assistance. After employing this tool, the authors carefully reviewed and edited the content as necessary and take full responsibility for the final publication.

Ethical Approval

The study was approved by the NIMHANS Institutional Ethics Committee (IEC) (Approval No. NIMHANS/43rd IEC (BEH.SC.DIV) 2023, dated 8th December 2023).

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The pan India training program was funded by a multinational company's CSR grant.

Informed Consent

Informed consent from all participants to take part in the program and for publication was obtained.

References

Sagar

, Dandona

, Gururaj

, . The burden of mental disorders across the states of India: The Global Burden of Disease Study 1990–2017. The Lancet Psychiatry, 2020; 7(2): 148–161.

Jayasankar

, Manjunatha

, Rao

, . Epidemiology of common mental disorders: Results from “National Mental Health Survey” of India, 2016. Indian J Psychiatry, 2022; 64(1): 13–19.

Manjunatha

, Kumar

, Math

, . Designing and implementing an innovative digitally driven primary care psychiatry program in India. Indian J Psychiatry, 2018; 60(2): 236–244.

Gangadhar

, Kumar

, Sadh

, . Mental health programme in India: Has the tide really turned?. Indian J Med Res, 2023; 157(5): 387–394.

Manjunatha

, Singh

and Chaturvedi

. Manochaitanya program for better utilization of primary health centers. Indian J Med Res, 2017; 145(2): 163–165.

Atmiyata, a community champion led psychosocial intervention for common mental disorders: A stepped wedge cluster randomized controlled trial in rural Gujarat, India - PMC [Internet]. [cited September 12, 2024]. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10249851/.

Ganjekar

, Thekkethayyil

and Chandra

. Perinatal mental health around the world: Priorities for research and service development in India. BJPsych Int, 2020; 17(1): 2–5.

Kumar

, Chand

, Manjunatha

, . Impact evaluation of VKN–NIMHANS–ECHO model of capacity building for mental health and addiction: Methodology of two randomized controlled trials. Indian J Psychol Med, 2020; 42(6 Suppl): S80–S86.

Manjunatha

, Parthasarathy

, Paul

, . Karnataka telemedicine mentoring and monitoring program for complete integration of psychiatry in the general health care. Indian J Psychiatry, 2021; 63(2): 171–174.

10.

Tugnawat

, Singh

, Anand

, . ESSENCE: An implementation research program to scale up depression care in rural communities. Psychiatr Serv, 2024; 75(2): 167–177. DOI: 10.1176/appi.ps.202100223.

11.

(PDF) Clinical schedules for primary care psychiatry (CSP), version 2.2 [Internet]. [cited September 6, 2024]. Available from: https://www.researchgate.net/publication/341622841_Clinical_Schedules_for_Primary_Care_Psychiatry_CSP_version_22.

12.

Inter-rater reliability and concurrent validity of a novel mental health screening & counselling tool for community health workers of India - PMC [Internet]. [cited September 6, 2024]. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9129657/.

13.

Jayasankar

, Nirisha

, Manjunatha

, . Are the collaborative video consultations module in diploma in primary care psychiatry helpful. Indian J Psychiatry, 2022; 64(Suppl 3): S516–S520.

14.

Pahuja

, Kumar

, . Collaborative Video consultations from tertiary care based telepsychiatrist to a remote primary care doctor to manage opioid substitution therapy clinic. J Neurosci Rural Pract, 2020; 11(3): 498–501.

15.

Sabhahit

, Das

, Ramachandraiah

, . An effectiveness-implementation hybrid cluster randomized controlled trial to evaluate add-on online mental health training for primary care doctors in influencing their management of commonly prevalent psychiatric disorders: description of the methodology. Indian J Psychol Med. 2026;48(1 suppl):S16-S23.

16.

Jayashri

, Sabbella

, Singh

, . Diagnostic and treatment concordance among primary care doctors delivering mental health care: results from an effectiveness-implementation hybrid cluster randomized controlled trial of an add-on online mental health training. Indian J Psychol Med. 2026;48(1 suppl):S24-S34.

17.

Sabbella

, Ramachandraiah

, Singh

, . Short-term clinical outcomes and implementation insights: a hybrid cluster randomized controlled trial of an "add-on online mental health training" for primary care doctors. Indian J Psychol Med. 2026;48(1 suppl):S35-S45.

18.

Sabbella

, Shah

, Hegde

, . Redefining access to mental health care through sustained tele-mentoring: a report of the instant collaborative video consultations with primary care doctors. Indian J Psychol Med. 2026;48(1 suppl):S75-S81.

19.

Paul

, Patley

, Hegde

, . Provision of mental health care by community health officers through collaborative video consultations: A descriptive analysis. Indian J Psychol Med. 2026;48(1 suppl):S67–S74.

20.

Shah

, Sabbella

, Hegde

, . Understanding the contours of a successful digitally driven capacity building program for primary care doctors: A mixed method study from a high-performing district of Southern India. Indian J Psychol Med. 2025;XX:1–8.

21.

Pearala

, Nujella

, Hegde

, . In-person mental health training and tele-mentoring for community health officers and mid-level health providers in India: A report from Telangana and Tripura, two diverse states of India. Indian J Psychol Med. 2026;48(1 suppl):S57–S66.

22.

Naslund

, Shidhaye

and Patel

Digital technology for building capacity of non-specialist health workers for task-sharing and scaling up mental health care globally. Harv Rev Psychiatry, 2019; 27(3): 181–192.

23.

O’Connor

, Hanlon

, O’Donnell

, . Understanding factors affecting patient and public engagement and recruitment to digital health interventions: A systematic review of qualitative studies. BMC Med Informat Decision Making, 2016; 16(1): 120.

24.

Learning4impact | NISHTHA - Transforming comprehensive healthcare in India [Internet]. [cited September 12, 2024]. Available from: https://www.learning4impact.org/project/nishtha---transforming-comprehensive-healthcare-in-india.

25.

Govindan

, Gandhi

, Nattala

, . Effectiveness of digital learning in community mental health care among nurses in India. Indian J Community Med, 2024; 49(2): 334–341.

26.

Mental Healthcare Management System (e-MANAS) to implement India’s Mental Healthcare Act, 2017: Methodological design, components, and its implications - ClinicalKey [Internet]. [cited January 13, 2025].

27.

Ibrahim

, Pahuja

, Dinakaran

, . The Future of telepsychiatry in India. Indian J Psychol Med, 2020; 42(5 Suppl): 112S–117S.

28.

Moirangthem

, Rao

, Kumar

, . Telepsychiatry as an economically better model for reaching the unreached: A retrospective report from South India. Indian J Psychol Med, 2017; 39(3): 271–275.

29.

Ibrahim

, Malathesh

, Gajera

, . Chhattisgarh community mental healthcare tele-mentoring program (CHaMP): Digitally driven initiative to reach the unreached. Int J Soc Psychiatry, 2022; 68(5): 954–957.

30.

Gajera

, Pandey

, Malathesh

, . Effectiveness of blended versus fully digital training in primary care psychiatry: A retrospective comparison from India. J Neurosci Rural Pract, 2023; 14(1): 91–97.

31.

Bairy

, Ganesh

, Kaur

, . Capacity building in mental health for Bihar: Overview of the 1-year blended training program for non-specialist medical officers. J Neurosci Rural Pract, 2021; 12(2): 229–234.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.10 MB

A Pan India Digitally Driven Capacity Building Program to Strengthen Primary Mental Healthcare: Summary of Its Implementation and Performance Evaluation

Abstract

Background:

Methods:

Results:

Conclusion:

Keywords

Key Messages:

Methods

Trainers

Training Module, Materials, and Schedule

Receiving Nominations and Engagement Strategies

Data Collection and Certification

Outcome Evaluation

Results

Discussion

Limitations

Conclusion

Supplemental Material

Footnotes

Acknowledgements

Declaration of Conflicting Interests

Declaration Regarding the Use of Generative AI

Ethical Approval

Funding

Informed Consent

References

Supplementary Material