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Abstract

Background:

Amid a pan-India digitally driven mental health capacity-building program carried out through National Institute of Mental Health and Neurosciences (NIMHANS) from April 2022 to November 2024, one district stood out, consistently outperforming others across most outcome measures. This study delves into the successful elements of this high-performing model district in South India to uncover the key factors behind its success.

Methods:

In November–December 2023, 69 primary care doctors (PCDs) from Udupi district participated in a six-week digital mental health training. The study utilized a mixed-method approach, analyzing changes in knowledge, attitudes, and practice (KAP) scores pre- and post-training, diagnostic and treatment concordance between PCDs and psychiatrists via collaborative video consultations (CVCs) records, and insights from focus group discussion (FGD) conducted with 12 PCDs.

Results:

About 68.12% of Udupi PCDs attended ≥3 sessions of the training, outperforming both Karnataka state PCDs (22.89%) and PCDs from nine other states (13.24%). Post-training, KAP scores improved significantly (mean difference: 1.89, t: -5.63, p < .001), surpassing the overall program’s PCDs (mean difference: 1.68). Diagnostic concordance with psychiatrists ranged from “Very good” to “Good” (Cohen’s k: 0.6–1.0), while treatment concordance was “Good” to “Fair” (k: 0.3–0.6). FGDs highlighted key success factors, including participant engagement, the perceived need for psychiatric care at PHCs, positive attitudes toward digital training, and strong administrative support.

Conclusion:

Compared to Karnataka as a whole and other states, Udupi district’s standout performance was likely driven by favorable trainee-related factors and adequate administrative support enabled through digital training.

Keywords

District mental health digital mental health training primary care doctors primary mental healthcare Udupi district

Key Messages

This mixed-methods analysis highlights the success of primary care doctors in the Udupi district who participated in a pan-India digital mental health capacity-building program, demonstrating improvements in knowledge acquisition and clinical practice.

The study identifies key enablers of this success—individual motivation, robust administrative support, and a conducive digital learning environment, emphasizing their synergistic role in fostering sustained engagement and effective skill translation.

Our findings offer valuable insights into digital training programs’ design and contextual adaptation in similar settings.

Digitization has significantly transformed healthcare delivery worldwide over the past decade, playing a particularly pivotal role in addressing healthcare challenges in developing countries such as India, where there exists a substantial gap of 80%–90% in treating mental health disorders.^{1, 2} The Mental Health Gap Action Programme (mhGAP) by the World Health Organization (WHO) has strongly emphasized the need to scale up mental health services, which has inspired the development of comprehensive training interventions for non-specialist healthcare workers, such as primary care doctors (PCDs), to enable them to deliver primary psychiatric care within the community.³ Additionally, the recent legislative changes in India’s mental health policies emphasize the importance of task-shifting to achieve universal mental health coverage.⁴ A major challenge in scaling task-shifting is the need to train enough non-specialist health workers to deliver primary psychiatry care and ensure they acquire the necessary clinical skills to maintain high-quality care. The task-shifting model framework, as outlined by Barnett et al., incorporates a primary-deliverer care approach wherein non-specialists serve as the sole providers of treatment, effectively helping reduce the treatment gap within the community, provided they are trained to do so effectively.⁵ The District Mental Health Program (DMHP) in India offers basic training to PCDs in identifying and managing mental health disorders. However, the substantial potential exists to leverage digital technology to deepen and augment their existing competencies.^{6, 7}

A systematic review evaluating the effectiveness of psychiatric interventions involving non-specialists and digital technology in low- and middle-income countries concluded that digital training significantly enhances participant competencies and improves patient outcomes.⁸ The hybrid training delivery model, which combines both onsite and online components, is superior to purely digital training in the existing literature, with the latter often associated with lower participant engagement and less effective translation of clinical skills into practice.^{9, 10} The key objective determinants of a successful healthcare training program include participant engagement, improvement in participant competencies, effective clinical translation of skills, and sustainable patient-related outcomes. There is considerable variability in our current understanding of these factors influencing the success of digitally driven mental health capacity-building training for PCDs.

A district is an ideal unit for primary healthcare interventions in India due to its administrative structure and governance, effective coordination of services, proximity to the local population, and ability to tailor interventions based on local health needs.¹¹ A comprehensive digital mental health capacity-building initiative aimed at empowering frontline healthcare workers of various districts of nine Indian states was launched through National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, Karnataka, India. This program, funded through the corporate social responsibility (CSR) initiative of a multinational agency, was implemented over a period spanning from April 2022 to November 2024.¹⁶ Throughout this program, we had the distinct privilege of observing a near-ideal district, where the convergence of a fortuitous combination of key operational factors played a pivotal role in driving the successful outcomes achieved. This study seeks to provide an in-depth analysis of objective and subjective factors that delineate the essential elements of a successful digital capacity-building program for PCDs within this exemplary district, employing a mixed-methods approach to gain comprehensive insights.

Methods

From November to December 2023, 69 PCDs from the Udupi district participated in a large-scale digital capacity-building program focused on mental health. The flowchart outlining the process for receiving nominations is depicted in Figure 1. The program consisted of six 2-hourly, weekly online training sessions for PCDs covering the identification and management of various mental health disorders, including common mental disorders (CMDs), severe mental disorders (SMDs), and substance use disorders (SUDs) delivered via online video meeting platform from NIMHANS. The module utilized standardized PowerPoint presentations (PPTs) using Clinical Schedules for Primary Care Psychiatry: Version 2.4 (CSP 2.4), developed by NIMHANS, which is a point-of-care manual designed specifically for PCDs containing guidelines for screening, early diagnosis, referral, first-line prescription templates and routine follow-ups of adult patients with psychiatric disorders at out-patient settings of primary health centers.¹² To ensure comprehensive support, extended handholding was provided through real-time collaborative video consultations (CVCs), during which provisional diagnoses and proposed treatment plans from both PCDs and psychiatrists were carefully documented separately. A dedicated team for the model district comprising project coordinators and a psychiatrist was assigned to engage the PCDs via an e-messaging platform throughout the training. This team facilitated sharing Information, Education and Communication (IEC) materials, short quizzes, the CSP manual, and PPTs while actively encouraging the CVC process. Although a dedicated team with a psychiatrist was assigned to each district for online training, the entire pool of psychiatrists carried out the CVCs, not limited to the district-specific teams.

An online form was utilized for standardized pre-training and post-training assessments of knowledge, attitude, and practice (KAP) of PCDs. The KAP assessment was a semi-structured questionnaire developed during the program’s initial phase by a panel of psychiatrists directly involved in project implementation. It comprised 30 items designed to evaluate clinical primary care psychiatry knowledge, attitudes toward mental health, and self-reported psychiatric practices aligned with the training objectives. The instrument underwent content validation through expert review by this panel and was subsequently refined following a pilot phase to improve clarity and relevance. Monthly interim data were also utilized to track progress in reporting identified psychiatric disorders by PCDs. We also employed a qualitative approach through focused group discussion (FGD) with PCDs at the end of their online training. An online FGD was conducted after the online training involving 12 randomly selected PCDs from the Udupi district. The PCDs were divided into three groups: PCDs with over 50% attendance, PCDs with less than 50% attendance, and PCDs who could not attend the training altogether. Four PCDs from each group were randomly selected to participate in the FGD, with the final sample representing all categories equally. An interview guide with questions and prompts vetted by a team of senior psychiatrists addressed PCDs’ expectations before the online training, their experiences throughout the digital training process, perceived barriers encountered, and their recommendations for improvement (Figure 1). A mixed-method analysis was done on the obtained data. IEC approval was obtained for the same.

Figure 1.

MoU: Memorandum of understanding, PCDs: Primary care doctors, KAP: Knowledge, attitude, and practice, CVC: Collaborative video consultations, NIMHANS: National Institute of Mental Health and Neurosciences.

Statistical analysis of pre-and post-training KAP was conducted using a paired-sample t-test, with a p value of less than .05 considered statistically significant. Data obtained through CVCs was analyzed for diagnostic and treatment concordance between PCD and Psychiatrist using Cohen’s kappa coefficient (k). The interpretation of the kappa values was based on data according to Altman (1991) with <0.2: Poor agreement, 0.2–0.4: Fair agreement, 0.41–0.6: Moderate agreement, 0.61–0.8: good agreement and >0.8: very good agreement with a p value of less than .05 considered statistically significant. Thematic analysis was done on the verbatim transcript derived through the online FGD with 12 PCDs. To ensure the reliability of the qualitative findings through FGD, we employed several methodological rigor strategies, including member checking, data triangulation, and peer debriefing. The authors employed structured thematic analysis techniques to obtain prominent themes, giving insights into the facilitators and barriers for the online training module.

Results

Table 1 demonstrates the overall details of the online training module of Udupi PCDs. The average attendance in online sessions was found to be 52.17%. 68.12% of PCDs attended ≥ 50% (3 or more sessions) of the training. According to the program overview statistics, the average engagement of Karnataka state PCDs in online training, with ≥50% session attendance, was 22.89% (n = 622). In contrast, the average engagement for PCDs of all nine states with ≥50% session attendance was 13.24% (n = 960), reported as the national average in the article by Shah H. et al.¹⁶ ≈38% of PCDs qualified the criteria for a completion certificate, which involved attendance of >50%, at least 1 CVC discussion, and successful submission of pre- and post-training KAP assessments. A total of 58 new psychiatric cases were identified at PHC by PCDs through CVCs post-training from the Udupi district - the highest number reported by any district in the Pan-India program.¹⁶

Table 1.

Details of Engagement of PCDs of Udupi District During Online Training.

Udupi District PCDs		Number	Percentage
Total nominations received		69	100%
Pre-assessment filled by:		44	63.76%
Session-wise attendance		27	39.13%
	Session 1 (Introduction)	27	39.13%
	Session 2 (CMD: Depression and suicide)	36	52.17%
	Session 3 (CMD: Anxiety and somatoform disorder)	34	49.27%
	Session 4 (SMD)	39	56.52%
	Session 5 (SUD)	39	56.52%
	Session 6 (Mop-up and pandemic preparedness)	41	59.42%
PCDs with ≥50% attendance (≥3 sessions) in training		47	68.12%
Post-assessment filled by:		37	53.62%
Total CVCs discussed		58	84.09%
Completion certificates		26	37.68%

PCD: Primary care doctors, CMD: Common mental disorders, SMD: Severe mental disorders, SUD: Substance use disorders, CVC: Collaborative video consultations.

Analysis of KAP scores before training (M = 15.31, SD = 2.33) and after the digital training (M = 17.20, SD = 2.18) using paired samples t-test showed statistically significant improvement post-training (mean difference = 1.89, t (34) = –5.63, p = <.001) (Table 2). Although the KAP scores of PCDs across the nine states in the program showed a significant improvement, the mean difference between pre-and post-training KAP scores was 1.68.¹⁶

Table 2.

Analysis of Pre- and Post-assessment KAP (Knowledge, Attitude, and Practice) Scores of PCDs of Udupi District.

PCDs (n)	KAP	Mean	SD	t Value, (pdf)	p Value
35	Pre-training assessment	15.31	2.33	–5.63, (34)	<.001
35	Post-training assessment	17.20	2.18	–5.63, (34)	<.001

PCDs: Primary care doctors, KAP: Knowledge, attitude, and practice, SD: Standard deviation, t: Paired t-test value, df: Degree of freedom.

Diagnostic concordance (Table 3) and treatment concordance (Table 4) analysis in the 58 CVCs, between Udupi PCDs and Psychiatrist at NIMHANS was done using Cohen’s kappa statistics with interpretation of the kappa values based on data according to Altman (1991) and p < .005 as statistically significant. There was a “Very good”/ “perfect” to “Good” agreement between the two in diagnosing all CSP categories (Table 3). Agreement for treatments was “Moderate” for SUDs and “Fair” for CMDs and SMDs. Additionally, in cases where referral for psychiatric emergencies or detailed evaluation by a specialist was required, there was “Good” agreement in identifying such cases (Table 4).

Table 3.

Diagnostic Concordance Analysis Between Udupi PCDs and Psychiatrists in CVCs.

CSP Diagnosis	Cohen’s Kappa (k)	p Value	Agreement
CMD	0.8	<.001	Good
Depression	0.7	<.001	Good
Anxiety disorder	0.6	<.001	Good
Somatoform disorder	1.0	<.001	Very good
SMD	0.9	<.001	Very good
SUD	1.0	<.001	Very good
Alcohol dependence	1.0	<.001	Very good
Tobacco dependence	0.7	<.001	Good

CSP: Clinical schedules for primary care psychiatry: Version 2.4, CMD: Common mental disorders, SMD: Severe mental disorders, SUD: Substance use disorders, CVC: Collaborative video consultations.

Table 4.

Treatment Concordance Analysis Between Udupi PCDs and Psychiatrists in CVCs.

CSP Treatment	Cohen’s Kappa (k)	p Value	Agreement
Antidepressants	0.3	.023	Fair
Antipsychotics	0.3	.01	Fair
Benzodiazepines	0.5	<0.001	Moderate
Counselling	0.4	.001	Moderate
Referral for psychiatric emergency/detailed evaluation by a specialist	0.6	<.001	Good

CSP: Clinical schedules for primary care psychiatry: Version 2.4.

Figure 2 graphically represents the monthly reporting trend of identified psychiatric disorders by Udupi PCDs from September 2023 to May 2024. The post-training period (January 2024–May 2024) shows a sustained increment compared to the pre-training period (September 2023–October 2023) in reporting CMD, SUD, and SMD cases screened by PCDs in PHCs.

A total of 12 PCDs participated in the FGD. The age of the PCDs ranged from 27 to 50 years. The male-to-female ratio was 1:1. The years of experience ranged from 4 to 25 years, with a mean experience of 7.5 years. The three major themes in the FGD analysis were (a) factors contributing to good engagement, (b) factors contributing to poor engagement, and (c) the impact of digital training on clinical practice and patient care. The major themes and subthemes derived from thematic analysis are listed in Table 5.

Figure 2.

*Online training period for Udupi PCDs: November–December 2023.

Discussion

This mixed-methods analysis offers a thorough understanding of 69 PCDs from a South Indian district who took part in our multistate digital capacity-building program. It highlights the positive outcomes and explores the factors contributing to these successes. The purely digital learning method has received mixed findings in the literature, particularly within the healthcare sector, primarily due to limited engagement and challenges in the clinical application of learned skills.^{9, 13} However, our in-depth exploration reveals a contrasting viewpoint and highlights contributing factors such as strong administrative support, inherent participants’ interest, optimized digital module, and extended handholding.

Of the 69 nominated PCDs, 63.76% completed the pre-assessment, with an average attendance of 52.17% across sessions, reflecting both strong initial interest and ongoing engagement in training (Table 1). Furthermore, 53.62% of participants completed the post-assessment, reflecting a reasonable level of follow-through. Despite these fluctuations, 84.09% of PCDs participated in at least one CVC discussion, contributing to managing 58 new psychiatric cases at PHCs, reflecting their strong motivation to apply learned clinical skills in practice. Digital training had a significant positive impact on the participants’ KAP, demonstrating the effectiveness of the training program in enhancing these key areas, consistent with several existing studies in the literature.^7,9,14,15 Furthermore, the improvement in post-training KAP assessment scores for the Udupi district was higher than the national average for all PCDs under the program (Table 2).¹⁶ While formal psychometric analyses such as reliability testing and construct validation have not yet been conducted on KAP form, the iterative development process, as mentioned in the methodology, reasonably assures the instrument’s appropriateness for assessing training outcomes in this implementation context.

The clinical translation of skills following digital training remains challenging to quantify. However, through concordance analysis of CVC data between PCDs and psychiatrists, we found significant alignment in diagnosing various psychiatric disorders and initiating appropriate treatment modalities. Furthermore, PCDs demonstrated a strong ability to identify psychiatric emergencies and referral needs post-training, highlighting the effectiveness of the training in enhancing their clinical capabilities beyond knowledge and attitude (Tables 3 and 4) While it is reasonable to consider the potential for bias due to the psychiatrist’s involvement in both the training and the CVCs, several aspects of the study design helped ensure minimal bias. First, the psychiatrist training the district PCDs was not the sole psychiatrist conducting the CVCs; instead, a team of seven psychiatrists was involved, and consultations were assigned based on availability, ensuring a rotation that reduced individual influence. Although the psychiatrist’s role during CVCs was collaborative rather than evaluative—to support joint clinical decision-making—a structured documentation process was in place. During CVCs, PCDs first presented cases with a provisional diagnosis and treatment plan, after which the psychiatrist independently assessed the patient, provided their diagnosis, and guided the PCD as needed. These interactions were documented, and the concordance analysis was based on comparisons between the PCD’s initial diagnosis/treatment and the final collaborative diagnosis/treatment, using objective CSP 2.4 criteria. An additional testament to the impact of digital training on the clinical practice of PCDs is the sustained increase in the monthly reporting of cases involving CMD, SMD, and SUD, demonstrating the enduring impact of the training well beyond its completion (Figure 2).

A combination of positive and negative factors influenced engagement in digital training. On the positive side, personal interest in psychiatry service, the reputation of the training institute, and the perceived need for expanding psychiatric services at PHCs motivated participants. Strong administrative support, prior orientation meetings, certification incentivization, the flexibility of the training schedule, the convenience of remote access and case-based crisp materials, and visually appealing training content further encouraged participation. The availability of CVCs with specialists as an extended handholding significantly enhanced learning opportunities and reinforced the practical application of digital training in clinical practice. However, challenges, such as a preference for face-to-face learning, lack of interest in psychiatry, and the burden of concurrent training programs, led to disengagement. Logistical barriers like poor network connectivity, scheduling conflicts, and overwhelming text-heavy training content hinder full participation (Table 5). These now-recognized, diverse factors underscore the necessity for tailored approaches to maintain sustained participation in digital training programs.

According to Udupi PCDs, digital training significantly improved clinical practice and patient care, enhancing awareness of psychiatric co-morbidities, diagnostic capacity, and prescription practices (Table 5). It also reduced psychiatric referrals, screening time, and difficulties, promoting better counseling and effective use of the ASHA network for follow-ups. The training contributed to destigmatization and early identification of psychiatric emergencies (Tables 4 and 5). However, barriers such as staff shortages, unavailability of psychiatric medications, negative patient attitudes, and poor medication adherence persist. Participants recommended improved digital platform orientation through pre-training orientation meetings, dedicated training timeslots, mop-up sessions, combination with onsite training, patient-friendly education materials, advanced child psychiatry training, and teleconsultations from PHCs when in need.

Table 5.

FGD Finding from Udupi PCDs: Major Themes, Sub-themes, and Categories.

Themes	Subthemes	Categories
Factors contributing to good engagement in digital training	Participant factors	Personal interest in psychiatry, positive attitude towards digital learning, admiration for the training institute’s reputation and expecting high-quality training, felt need for expanding psychiatric practices at PHCs, high motivation when psychiatric illness in relatives, lack of confidence to prescribe psychiatric medications
	Re-enforcement related factors	Certification of completing training, equipping skills to prescribe, boost in confidence, satisfaction from patient improvement, encouragement from administrators
	Digital module-related factors	Flexibility of schedule, convenience of attending remotely, less text-heavy crisp materials, visual content in training materials, case series-based training materials, benefit of access to training materials post-session for revision, availability of CVCs with specialist
	Administrative factors	Administrative support, training intimation from district health administrators, orientation meetings prior to training, and continuous monitoring by administrators through online messaging groups
Factors contributing to poor engagement in digital training	Participant factors	Personal preference for face-to-face training over online training, lack of interest in psychiatry, feeling burdensome due to various simultaneous trainings, disengagement from training due to few missing sessions, stigma related to psychiatric illness, lack of motivation in non-mandatory training
	Logistic factors	Difficulty concentrating in online sessions during busy OPD, poor network connectivity in rural PHCs, scheduling conflicts with concurrent training programs
	Digital module-related factors	Overwhelming comprehensive modules, weariness from long online sessions
	Administrative factors	Lack of specific allotted time for training, poor administrative support
Impact of digital training in clinical practice and patient care	Improved factors	Increased awareness of psychiatric co-morbidities, enhanced diagnostic capacity, enhanced prescription practice, reduced screening time and difficulty, reduced psychiatric referrals to higher centers, impact of CVCs on extended learning, better counseling practices, utilization of ASHA network for follow-up, destigmatization, early identification of psychiatric emergencies
	Barriers	Shortage of staff in PHC, unavailability of psychiatric medications, negative patient attitudes towards psychiatric treatment, patients lost to follow-up, non-adherence to medications,
	Participant’s recommendations	Need for orientation on digital platform navigation, specific allotted time for digital training by administrators, frequent mop-up training, onsite training following online training, patient-friendly education materials, need for advanced training in child psychiatry, continuous teleconsultation facility at PHC

PHC: Primary health center, CVC: Collaborative video consultations, OPD: Outpatient department.

Figure 3 demonstrates six crucial factors that define the contours of a successful digitally driven mental health capacity-building program yielded through this study. The sole digital learning method has faced mixed views in literature, especially in the healthcare sector. While it offers flexibility, scalability, and accessibility, it has been critiqued for limited engagement among learners and difficulties in translating acquired skills into clinical practice. While the absence of face-to-face interaction and hands-on experience may impede the development of specific practical competencies, refining and enhancing digital module delivery remains a viable approach that can still be explored to mitigate this challenge. Our study identifies key factors that can be used to tailor the digital training module, optimize consistent engagement, and translate clinical skills. The training can be further fortified with an onsite approach to ensure quality patient care. One limitation of the study is the absence of a direct, head-to-head comparison between the Udupi district and other districts, as this was beyond the scope of the current study design. For future research, we recommend adopting a design that addresses this gap, as such comparisons could yield more profound insights into the key determinants of success in exclusively digital training programs.

Figure 3.

Contours of a Successful Digitally-driven Mental Health Capacity-building Program.

In this pan-India digital capacity-building program, the success of the Udupi district highlights the likely causal influence of multiple factors—particularly the interplay of trainee interest/motivation, strong administrative support, and a conducive digital training environment.

Conclusions

This article discusses the outcomes of a mixed-methods analysis of primary care doctors in the Udupi district of South India who participated in a digitally driven mental health capacity-building program. Compared to Karnataka as a whole and other states, Udupi district's better performance was likely driven by favorable trainee-related factors and adequate administrative support. These conditions collectively contributed to the success observed in knowledge acquisition and improvements in clinical practice among the participating doctors.

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 took 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.

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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