Barriers and Facilitators for Translating Skills into Clinical Practice in Primary Psychiatry Care: Primary Care Doctors’ Survey Through the Lens of Implementation Research

Abstract

Background:

Though integrating psychiatric care into primary care is thought to be a pivotal step, a huge gap remains in translating this training into clinical practice at primary health centers (PHCs) in India. To address this, we aim to explore the perspectives of the primary care doctors (PCDs) from an implementation research angle.

Methods:

An anonymous online survey with a semi-structured questionnaire gathered PCDs’ perspectives on integrating primary care psychiatry training into India’s healthcare system, focusing on Acceptability, Adoption, Appropriateness, and Feasibility subsets based on the conceptual framework for implementation outcomes. The survey reached 7,200 PCDs via a pan-India mental health capacity-building program, with 124 PCDs from 5 states participating. A 134 PCDs completed the Fidelity questionnaire. PCDs were grouped by mental health training status for comparative analysis. A mixed-method analysis was conducted on the data.

Results:

Overall, PCDs reported high ratings across the subsets of Acceptability (91.1%–91.9%), Feasibility (75.8%–91.9%), Adoption (87.9%–93.5%), and Appropriateness (89.5%–92.7%). Clinical practice outcomes in terms of Fidelity (33.6%–52.2%) remained limited. Mental health training was significantly linked to increased comfort in managing mental health issues at PHCs (Acceptability subset, χ² = 4.79, p = .02), a greater readiness to start screening for mental health disorders (Adoption subset, χ² = 4.73 p = .03) and increased prescription practice at PHC for mental health disorders (Fidelity subset, χ² = 4.01, p = .04). Qualitative data analysis identified barriers such as stigma, time constraints, limited access to medications, staff shortages, and inadequate follow-up systems that hindered effective integration of mental health care at PHCs.

Conclusions:

Though psychiatry training of PCDs improves resource availability, addressing systemic challenges is essential for ensuring effective mental health service delivery at the primary care level.

Keywords

Primary care psychiatry primary care doctors implementation research clinical skill translation implementation outcomes

Key Messages

While primary care doctors found integrating mental health care into PHCs acceptable, feasible, and appropriate, actual delivery of care as intended (fidelity) remained limited.

Mental health training significantly increased doctors’ comfort, readiness to screen, and prescribing practices for mental health conditions, showing it is an effective and scalable intervention.

Challenges such as stigma, time constraints, medication shortages, staffing issues, and inadequate follow-up systems continue to hinder effective integration of primary care psychiatry services.

In primary mental healthcare, a significant challenge persists between the acquisition of knowledge and its practical application, particularly for transitioning into clinical roles. It is estimated that at least 20% of primary care patients suffer from a psychiatric disorder; however, 50%–75% of these cases remain undetected and untreated, despite the inclusion of primary psychiatry care training in: Indian mental health policies and District Mental Health Program, operational arm of National Mental Health Program.^1–4 This gap is often exacerbated by organizational, professional, and systemic barriers that impede effective skill translation, leading to suboptimal patient outcomes and increased provider frustration.⁵ Several mental health capacity-building initiatives have been launched in the past decade to strengthen primary doctors in India to bridge this functional treatment gap.^6–9 While some outcome indicators have been documented from the program perspective, there has been limited exploration of these aspects through the lens of implementation science.

Implementation research (IR) plays a crucial role in addressing this issue, although it is sometimes overlooked within the health sciences.¹⁰ This field focuses on the real-world application of policies, programs, and interventions, examining the “what, why, and how” of implementation. Unlike traditional research, IR works within the complexities of everyday environments. By utilizing qualitative, quantitative, and mixed methods, IR generates actionable insights to improve the effectiveness and scalability of health initiatives, ultimately enhancing public health outcomes.¹¹

Central to IR is the investigation of how evidence-based practices are integrated into routine care, considering not only the intervention itself but also contextual factors like organizational settings, policies, and individual attitudes.^5,12,13 The Conceptual Framework for Implementation Outcomes, developed by Proctor et al. (2011), defines key measures to assess how effectively evidence-based interventions are implemented in practice. By focusing on outcomes such as acceptability, adoption, appropriateness, fidelity, feasibility, sustainability, etc., the framework helps evaluate the success of implementation efforts independently from clinical outcomes. This approach supports better integration and long-term use of interventions in real-world settings.¹⁴ An integral part of the implementation science is gathering perspectives from all stakeholders to improve the structure of healthcare delivery at the grassroots level.

This study aims to critically explore the perspectives of primary care doctors (PCDs) on the integration of mental healthcare into primary care settings, employing a novel approach through IR outcome variables. This approach, hitherto unexplored in the literature concerning Indian primary healthcare environments, seeks to systematically assess PCDs’ “Acceptability,” “Feasibility,” “Adoption,” “Appropriateness,” and “Fidelity” of psychiatry care integration. Through this, we also seek to identify the key barriers and facilitators that have shaped the application of acquired skills in clinical practice. Identifying these determinants within primary healthcare can inform policy changes and organizational improvements that enhance primary psychiatry care delivery and patient outcomes.^15,16

Methods

From April 2022 to November 2024, National Institute of Mental Health and Neurosciences (NIMHANS) implemented a large-scale digital mental health capacity-building program, engaging a total of 7248 PCDs from nine Indian states.¹⁷ With approval from the institutional ethics committee, we set out to gather responses from all available PCD nominees (n = 7,248) of the digital training program during the post-training phase, spanning from July 2024 to November 2024. As participation in the digital training program was voluntary, PCD engagement varied across states, and many nominated PCDs could not attend/complete the digital training. Digital consent was obtained from the 124 PCDs who volunteered to participate in an anonymous online survey. A thoughtfully designed, semi-structured questionnaire was employed in the survey to evaluate PCDs’ perceptions regarding the integration of mental healthcare into primary care. The questionnaire included key implementation outcome variables¹¹ including “Acceptability,” “Feasibility,” “Adoption,” and “Appropriateness”; and descriptive responses from PCDs, capturing their personal experiences and the challenges of delivering psychiatric care within primary health centers (PHCs). Although “Fidelity” is a core implementation variable,¹¹ related questions were sent separately after we realized they had been inadvertently omitted from the initial survey. Responses to the initial set of questions were received from 124 PCDs, while 134 PCDs completed the fidelity section; these 134 included the original 124 PCDs, allowing us to analyze both datasets as a single group.

These online surveys were distributed to all the district-specific, pre-established groups of PCDs on a popular online messaging platform, which were formed during their enrolment in the digital training program. Figure 1 summarizes the process of conducting the survey. PCDs were enrolled in the online survey irrespective of their attendance status in NIMHANS digital training.

Figure 1.

*The 134 PCDs included all the original 124 respondents. NIMHANS: National Institute of Mental Health and Neurosciences, PCD: Primary Care Doctors.

Developing the Questionnaire

A series of panel discussions was carried out among the project team, which included nine psychiatrists and three faculty members in charge with extensive research experience. The discussions focused on creating a semi-structured questionnaire to gather PCDs’ perceptions through key implementation outcome variables: “Acceptability,” “Feasibility,” “Adoption,” and “Appropriateness” as defined by Peters et al., as well as descriptive open-ended questions inquiring experience, challenges encountered, and suggestions for delivering psychiatric care within PHCs.¹¹ Subsequently, a separate anonymous online survey was developed to include an additional outcome measure: “Fidelity,” as defined by Peters et al., to assess the likelihood of patients being screened and started on treatment at the PHC in the past month by PCDs. These semi-structured questionnaires were not designed to evaluate the direct impact of our digital training program; instead, they aimed to capture broader perspectives of PCDs on the very idea of integrating any form of primary care psychiatry training. The digital program served as a mere conduit to engage a larger and more diverse pool of PCDs, which would have been challenging to accomplish at this scale due to limited resources. Table 1 demonstrates the operational definitions of these variables in the context of the task of identifying and treating uncomplicated psychiatric disorders at PHCs, which were utilized to make the semi-structured questionnaires. The answers were collected on a four-point Likert scale: “Very much,” “Somewhat,” “Very little,” and “Not at all.”

Statistical Analysis

Descriptive statistics, including frequencies and percentages, were initially used to summarize the responses for each item in Table 1. The Likert scale responses, which typically range from “Very much” to “Very little,” were treated as ordinal data. The responses were assigned numerical values (e.g., 2 = “Very much” & “Somewhat,” 1 = “Very little” and “Not at all”) to facilitate further analysis.

Table 1.

Definition of Implementation Outcome Variables for the Semi-structured Questionnaire.

Variable	Operational Definition
Acceptability	“The perceived agreeability of PCDs on integrating mental healthcare into primary care and their willingness to engage with it. It refers to how agreeable and comfortable PCDs are to diagnose and treat uncomplicated psychiatric conditions, as well as initiating first-line treatment (after undergoing training).”
Adoption	“The intention or initial decision to implement the task of integrating mental healthcare into primary care, as well as the actual action of doing so. It examines whether (shortly after the training) PCDs made an initial decision and attempted to identify and treat individuals with uncomplicated psychiatric disorders in the PHCs.”
Appropriateness	“The perceived relevance of the task of integrating mental healthcare into primary care within PHCs or for patients. It relates to whether PCDs, both appropriate and relevant, consider the identification and treatment of uncomplicated psychiatric disorders for the patients who routinely visit PHCs.”
Feasibility	“The perceived practicality of implementing mental healthcare delivery within PHCs. It addresses how feasible it is for the PCDs to carry out the task of identifying and treating uncomplicated psychiatric disorders within PHCs.”
*Fidelity	“The degree to which integrating mental healthcare into primary care is implemented as originally recommended, designed, or planned. This includes aspects of adherence, integrity, and the quality of mental health delivery. It pertains to the extent to which PCDs have been able to identify and treat uncomplicated psychiatric conditions as part of their routine practice within PHCs.”

*In the current context, the subjective aspect of fidelity is considered, as any single objective measure has not been identified, and the study was not designed to incorporate such an approach.

The semi-structured questionnaire evaluated the training status of all PCDs, offering them the following options: online mental health training from NIMHANS, DMHP training in mental health, no mental health training, or other (with a space for a descriptive response). PCDs could select multiple options based on their training experiences. Responses were categorized into two groups: “With Psychiatry Training,” which included those who had pursued any additional psychiatric training beyond their undergraduate studies (MBBS), and “Without Psychiatry Training,” which comprised those who had not received any supplementary psychiatric training post-undergraduate studies.^a

Additionally, inferential statistical methods, such as χ² tests, were employed to examine associations between demographic variables and response patterns. Fisher’s exact test was employed whenever the expected cell value in one or more cells was <5. Data were analyzed using licensed SPSS software version 29, and results were reported with 95% confidence interval and p < .05 to establish significance of findings. As the descriptive questions were incorporated within the anonymous online survey, only responses from consenting PCDs were obtained and analyzed. Descriptive written responses from PCDs about their experiences and challenges were analyzed using thematic analysis based on Braun and Clarke’s six-step approach.¹⁸ This involved immersing in the data, generating initial codes, identifying and refining themes, and producing a coherent report. To maintain methodological rigor, the first and second authors independently coded the data and then discussed any discrepancies to reach consensus.

Results

The PCDs from Karnataka comprised approximately 63% of the sample, with the remaining officers from Maharashtra, Goa, Telangana, and Uttarakhand (Table 2). Of the 124 PCDs, 99 had received training in mental health, either through DMHP or NIMHANS (Table 2).

Table 2.

Distribution of Primary Care Doctors (PCDs) Based on States and Training.

	Frequency (%)
State
Goa	9 (7.3%)
Karnataka	78 (62.9%)
Maharashtra	23 (18.5%)
Telangana	9 (7.3%)
Uttarakhand	5 (4%)
Total	124 (100%)
Training status
*“With psychiatry training”	99 (79.8%)
• DMHP training in mental health for primary care • NIMHANS pan-India digital mental health training in primary care psychiatry	30 (24.2%) 69 (55.6%)
“Without psychiatry training”	25 (20.2%)
Total	124 (100%)

*Without psychiatry training: PCDs who had not undergone any additional training in psychiatry after their undergraduate studies.

DMHP: District Mental Health Program.

Table 3 has the summary of the responses (1 = Very little, not at all; 2 = Very much, somewhat) from 124 PCDs in the subsets of “Acceptability,” “Feasibility,” “Adoption,” and “Appropriateness” of integrating mental healthcare/training into primary healthcare. Very much and somewhat responses ranged from 91.1% to 91.9% for Acceptability (A1–A4), 87.9%–93.5% for Adoption (B1–B2), 89.5%–92.7% for Appropriateness (C1–C2), and 75.8%–91.9% for Feasibility (D1–D2). When grouped based on the status of mental health training, there was a significant association of the training with felt comfort in diagnosing and practicing (“Acceptability” subset A2) (χ² = 4.79, p = .02) and attempt to start doing so (“Adoption” subset B1) (χ² = 4.73, p = .03).

Table 3.

Frequency Distribution of Survey Responses of all PCDs and Comparison Among the PCD Training Groups.

Questions	Responses (1 = “Very Little” & “Not At All”) (2 = “Very Much” & “Somewhat”)	All PCDs	PCDs Training Groups		χ²/Fisher’s Exact Value (df = 1)	p Value
Questions		All PCDs	With Psychiatry Training	Without Psychiatry Training	χ²/Fisher’s Exact Value (df = 1)	p Value
A: Acceptability
A1. Do you agree with integrating mental health training for primary care providers to diagnose and initiate first-line treatment for commonly prevalent mental illnesses as part of routine care?	1	10 (8.1%)	8 (8.1%)	2 (8%)	0.00*	.98**
	2	114 (91.9%)	91 (91.9%)	23 (92%)	0.00*	.98**
A2. How comfortable are you with diagnosing and treating mental health conditions because of the training?	1	11 (8.9%)	6 (6.1%)	5 (20%)	4.79	.02
	2	113 (91.1%)	93 (93.9%)	20 (80%)	4.79	.02
A3. Do you see any significant advantages to incorporating the training on mental health services into routine primary care?	1	11 (8.9%)	8 (8.1%)	3 (12%)	0.37	.53
	2	113 (91.1%)	91 (91.9%)	22 (88%)	0.37	.53
A4. How credible do you think it is for trained primary care providers to diagnose and treat mental illnesses	1	10 (8.1%)	7 (7.1%)	3 (12%)	0.65	.41
	2	114 (91.9%)	92 (92.9%)	22 (88%)	0.65	.41
B: Adoption
B1. Following your training, how likely were you to start identifying persons with mental health problems in the community?	1	8 (6.5%)	4 (4%)	4 (16%)	4.73	.03
	2	116 (93.5%)	95 (96%)	21 (84%)	4.73	.03
B2. Following your training, how likely were you to start treating identified mental health problems in the community?	1	15 (12.1%)	11 (11.1%)	4 (16%)	0.45	.50
	2	109 (87.9)	88 (88.9%)	21 (84%)	0.45	.50
C: Appropriateness
C1. Is the training on identifying and treating uncomplicated mental health disorders appropriate for the patients who visit PHCs routinely?	1	13 (10.5%)	8 (8.1%)	5 (20%)	3.02	.08
	2	111 (89.5%)	91 (91.9%)	20 (80%)	3.02	.08
C2. How relevant do you consider addressing mental health issues with patients who routinely visit PHCs for care as part of your training?	1	9 (7.3%)	5 (5.1%)	4 (16%)	3.55	.05
	2	115 (92.7%)	94 (94.9%)	21 (84%)	3.55	.05
D: Feasibility
D1. How practical do you believe it is to integrate the training on identification and treatment of non-complicated psychiatric disorders into the routine workflow of PHCs?	1	10 (8.1%)	8 (8.1%)	2 (8%)	0.00*	1.00**
	2	114 (91.9%)	91 (91.9%)	23 (92%)	0.00*	1.00**
D2. How well do the current resources at PHCs support the implementation of the mental health training?	1	30 (24.2%)	22 (22.2%)	8 (32%)	1.04	.32
	2	94 (75.8%)	77 (77.8%)	17 (68%)	1.04	.32

PCD: Primary care doctors, PHC: Primary health care.

*Fisher’s exact test value.

**Fisher’s exact two-sided significance.

Of the 134 PCDs who filled the Fidelity questionnaire, 108 PCDs had received training in mental health, either through DMHP or NIMHANS (Table 4).

Table 4.

Distribution of PCDs Based on Psychiatry Training for the Fidelity Questionnaire.

PHC	Frequency (%)
With psychiatry training	108 (80.6%)
• DMHP training in mental health for primary care • NIMHANS digital mental health training in primary care psychiatry	34 (25.4%) 74 (55.2%)
*Without psychiatry training	26 (19.4%)
Total	134 (100%)

*Without psychiatry training: PCDs who have not undergone any additional training in psychiatry after undergraduate studies.

Very much and somewhat responses for “Fidelity” ranged from 33.6% to 52.2%. Only 33.6% PCDs were very much-somewhat likely to screen/diagnose mental health disorders in their PHC in the past month. However, a significant association was seen between the mental health training and prescription practice at PHC for mental health disorders (|² = 4.01, p = .04) ( Table 5 ).

Table 5.

Frequency Distribution of “Fidelity” Responses of Overall PCDs and Comparison Among the Training Groups.

Questions	Responses (1 = Very Little & Not At All) (2 = Very Much & Somewhat)	Overall PCDs	PCDs Training Groups		χ² Value (df = 1)	p Value
Questions		Overall PCDs	With Psychiatry Training	Without Psychiatry Training	χ² Value (df = 1)	p Value
E: Fidelity
E1. Of the total patients seen last month, how likely were you to screen/diagnose the patients as having one or more mental health disorders?	1	89 (66.4%)	73 (67.6%)	16 (61.5%)	0.34	.55
	2	45 (33.6%)	35 (32.4%)	10 (38.5%)	0.34	.55
E2. Of those screened positive/diagnosed with psychiatric conditions last month by you, how likely were you to start them on treatment at the PHC?	1	64 (47.8%)	47 (43.5%)	17 (65.4%)	4.01	.04
	2	70 (52.2%)	61 (56.5%)	9 (34.6%)	4.01	.04

PCD: primary care doctors, PHC: primary health care.

Table 6 summarizes the thematic analysis of responses of PCDs on mental health training and clinical practice experiences at PHCs. Mental health training improved diagnostic skills, prescribing competency, and psychiatric knowledge, but challenges included issues with digital training concentration and scheduling conflicts. In terms of mental healthcare delivery at PHCs, a facilitator was found to be the trainer in mental health disorders.

Table 6.

Qualitative Analysis Results of Descriptive Responses in Survey by PCDs: Prominent Themes and Subthemes with Categories.

Themes	Subthemes	Categories
Mental health training	Impact	Improved diagnostic competency, improved prescribing competency, enhanced psychiatric knowledge, practical application, usefulness of collaborative consultations post-training in boosting confidence, early detection at PHC, reduced stigma
	Challenges	Difficulty in coordination in digital training, scheduling conflicts with duty hours, and other concurrent trainings
	Suggestions	Repeated mop-up trainings, case-based discussions, hybrid training, scheduling training after busy OPD hours, periodic assessments, visual content modules for easy grasp, and extended handholding
Mental healthcare delivery at primary health centers	Facilitators	Training in mental health disorders, felt the need for psychiatric practice at PHC
	Barriers	Stigma, time constraints in busy OPD, poor medication adherence, poor psychiatric medication resources, lack of continuous supply of psychiatric medications at PHCs, high caseload in PHCs, lack of a robust follow-up system, lack of workforce at PHCs, counselling difficulties
	Suggestions	Need for further training, advanced training in child and substance use disorders, to resolve logistic issues at PHC related to medications and workforce shortage

PCD: Primary care doctors, PHC: primary health care, OPD: outpatient department.

Discussion

Utilizing a novel approach through IR variables, this study has highlighted the key attitudes of PCDs on integrating psychiatric practice into primary healthcare in India. Through a mixed-methods analysis, it seeks to offer deeper insights into PCDs’ perceptions around primary psychiatry care and the influence of mental health training on their practices.

When evaluating the PCDs’ perceptions on “Acceptability,” “Feasibility,” “Adoption,” and “Appropriateness” of integrating mental health services into primary healthcare, nearly all PCDs provided high ratings (responses: Very much+ somewhat) across all domains (Table 4). Although no significant association was found with training status and overall “Acceptability,” “Feasibility,” “Adoption,” or “Appropriateness,” a notable exception was observed in the subsets of “Acceptability” (A2) and “Adoption” (B1) (Table 4). Specifically, psychiatry training was significantly associated with increased comfort in managing mental health issues and a greater willingness to begin identifying and screening mental health disorders. These results align with Mittal et al. and Muke SS et al., who found digital technology to be a feasible and acceptable method for training Indian primary healthcare providers in mental health.^19,20 However, despite the positive “Acceptability,” “Feasibility,” and perceived “Appropriateness” of integrating mental health services into primary care in all PCDs, there has been limited impact on clinical practice outcomes. This is evident in “Fidelity” data, where only 33.6% of PCDs reported efficiently screening for or diagnosing mental health disorders at PHCs in the past month, and only 52.2% felt confident in initiating psychiatric medications for diagnosed patients. Even among the digitally trained PCDs, only 32.4% reported efficient screening at PHCs, and 56.5% initiated psychiatric medications for the diagnosed patients (Table 5). The responses on “Fidelity” indicated no statistically significant difference in the likelihood of screening or diagnosing psychiatric illnesses at PHCs between PCDs with and without prior psychiatry training. This finding has broader implications beyond PCD motivation, as it also reflects real-world facilitators and barriers that may have influenced screening practices. This highlights the necessity to explore the barriers to practicing primary care psychiatry at PHCs. Qualitative analysis outcomes from Table 6 might shed light on some of the underlying reasons for these challenges. PCDs at PHCs report encountering multiple obstacles in delivering psychiatric care, including the stigma surrounding mental health, time constraints in busy outpatient departments, and issues with medication adherence. In addition, limited access to psychiatric medications, inconsistent supply, and high patient volumes further complicate care delivery. The lack of a structured follow-up system, insufficient staff and medications, and difficulties in providing effective counselling exacerbate these challenges. Together, these barriers prevent PCDs from providing comprehensive mental health services, underscoring the need for systemic improvements, enhanced training, and better resource allocation to integrate mental health care into primary healthcare settings effectively. While the baseline likelihood of screening appears comparable across both groups, it is noteworthy that a significant association was found between psychiatry training and the likelihood of initiation of treatment at PHCs by PCDs, that is, Fidelity, emphasizing that training contributed to improved prescribing practices (Table 5). This suggests that psychiatry training enhances the ease of PCDs not only to diagnose but also to effectively initiate the management of mental health disorders at the primary care level. Similar findings have been reported in various existing studies.^21–23

The qualitative analysis of descriptive responses from PCDs illuminated several critical themes concerning mental health training, its impact, associated challenges, and proposed enhancements (Table 6). The impact of training was particularly evident in the improvement of PCD’s felt diagnostic and prescribing competencies, the expansion of psychiatric knowledge, and the enhanced ability to apply theoretical learning in clinical settings. Notably, the training was credited with fostering early detection of psychiatric disorders at PHCs and reducing the pervasive stigma surrounding mental health issues. However, the challenges identified included difficulties in maintaining focus during digital training formats, scheduling conflicts with duty hours, and limited opportunities for hands-on experience with diverse clinical cases. In terms of suggestions for improvement, PCDs emphasized the necessity for repeated mop-up training sessions, case-based discussions, and the integration of hybrid training models. Additionally, the incorporation of visual aids in training materials was recommended to facilitate better understanding. The analysis further revealed that while facilitators, such as specialized mental health training and the recognized need for psychiatric expertise at PHCs, contributed to positive outcomes, barriers such as stigma, time limitations, inadequate medication adherence, and resource shortages hindered effective mental health delivery. To address these challenges, PCDs advocated for further training and advanced training modules in child and substance use disorders, as well as the resolution of logistical issues at PHCs, including medication shortages and staff shortages, to improve the overall efficacy of mental healthcare services at PHCs (Table 6). A qualitative research carried out on PHC workers in Rajasthan in 2024 similarly reported gaps in competencies, community stigma, medication adherence, and limited PHC resources as key barriers, highlighting how the lack of standardized mental health training in primary healthcare workers amplifies these barriers.²⁴

A notable limitation of this study lies in its reliance on convenience sampling, as it was conducted during the implementation of a large-scale digital mental health capacity-building program.¹⁷ There is a possibility that those who consented to participate in the survey may have had a more positive attitude toward the training, which could introduce some bias in the positive responses. However, the survey included a substantial representation of PCDs who had not received any mental health training beyond their undergraduate education. Notably, their responses were largely similar to those of PCDs who had undergone training. Therefore, it is reasonable to conclude that any potential bias was minimal. Conversely, the untrained PCDs who participated in the surveys may represent a particularly motivated subgroup with above-average baseline skills, which could account for the similarity in their responses with the trained group-suggesting even greater potential in real-world settings with proper training. Furthermore, the anonymity of the survey was intentionally designed to mitigate any biases related to participation. While the response rate may be considered suboptimal, with only 134 out of 7,248 PCDs participating in the online survey, this can be attributed to several contextual factors. The study was conceptualized during the final phase of the program, when medical training had concluded and certificates had already been distributed, diminishing the incentive for most PCDs to engage. Additionally, the messaging platform used for survey distribution concurrently served multiple other functions, including reminders for monthly interim reports, collaborative video consultations, post-assessment forms, dissemination of IEC materials, and certificate distribution, all of which may have contributed to the survey being overlooked. Future studies should incorporate prospective longitudinal designs and region-specific approaches, utilizing larger sample sizes to enhance generalizability and offer a more nuanced understanding of the factors that influence the successful integration of practices into clinical settings. This study was subject to inherent limitations characteristic of online surveys, as delineated by Andrade C et al.²⁵ Although the survey was distributed to defined district-specific groups of medical officers, the voluntary nature of participation may have introduced respondent bias. To mitigate this, anonymity was employed as a strategic measure to reduce bias and enhance response rates. Additionally, disparities in digital literacy and engagement may have contributed to the low response rate, thereby limiting the generalizability of the findings. Nonetheless, considering the fully digital framework of the program and our intent to evaluate its feasibility within this paradigm, deploying an online survey was the most methodologically sound approach.

This mixed-method study explored the barriers and facilitators that affect the translation of skills into clinical practice from an IR perspective. Understanding these factors from the PCDs’ point of view is essential, as it can inform the refinement of policies and ensure that early interventions facilitate smoother transitions from training to practice, ultimately supporting the long-term integration of evidence-based practices in primary healthcare environments. Klaic et al., in their overview of systematic reviews, emphasized that the scalability and sustainability of healthcare interventions are strongly influenced by their acceptability, feasibility, and fidelity—factors that are most effectively assessed early in the implementation process and, ideally, through iterative evaluation.²⁶

Conclusions

The acceptability and adoption of integrating psychiatry care into primary care, along with the extent of its actual implementation (fidelity), show significant improvement with psychiatry training in PCDs, making it a scalable and sustainable intervention. However, several barriers, particularly those related to administrative and resource constraints, continue to hinder progress.

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

In the preparation of this work, 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(s) 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.

Note

References

Ogunsemi

, Oluwole

, Abasiubong

, . Detection of mental disorders with the Patient Health Questionnaire in primary care settings in Nigeria. Ment Illn, 2010; 2(1): e10.

van Ginneken

, Jain

, Patel

, . The development of mental health services within primary care in India: Learning from oral history. Int J Ment Health Syst, 2014; 8(1): 30.

Singh

. District Mental Health Program - Need to look into strategies in the era of Mental Health Care Act, 2017, and moving beyond Bellary Model. Indian J Psychiatry, 2018; 60(2): 163–164.

Gupta

and Sagar

National Mental Health Policy, India (2014): Where have we reached?

Indian J Psychol Med, 2022; 44(5): 510–515.

Rogers

, Pablo

Hernando S

, Núñez-Fernández

, . Barriers and facilitators in the implementation of an evidence-based health promotion intervention in a primary care setting: a qualitative study. J Health Organ Manag, 2021; 35(9): 349–367.

Manjunatha

, Kumar

, Math

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

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.

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.

Kumar

, Das

, Agarwal

, . Capacity building of primary care physician working at remote Uttarakhand, India: An integrated tertiary care approach during COVID 19 pandemic. J Family Med Prim Care, 2021; 10(2): 820.

10.

Eccles

and Mittman

. Welcome to implementation science. Implement Sci, 2006; 1(1): 1.

11.

Peters

, Adam

, Alonge

, . Implementation research: What it is and how to do it. BMJ, 2013; 347: f6753.

12.

Fostering implementation of health services research findings into practice: A consolidated framework for advancing implementation science. Implement Sci [Internet]. [cited December 8, 2024]. Available from: https://implementationscience.biomedcentral.com/articles/10.1186/1748-5908-4-50.

13.

Kirk

, Kelley

, Yankey

, . A systematic review of the use of the Consolidated Framework for Implementation Research. Implement Sci, 2016; 11: 72.

14.

Proctor

, Silmere

, Raghavan

, . Outcomes for implementation research: Conceptual distinctions, measurement challenges, and research agenda. Adm Policy Ment Health, 2011; 38(2): 65–76.

15.

Crable

, Biancarelli

, Walkey

, . Barriers and facilitators to implementing priority in-patient initiatives in the safety net setting. Implement Sci Commun, 2020; 1(1): 35.

16.

Nilsen

Making sense of implementation theories, models, and frameworks. Implement Sci, 2015; 10: 53.

17.

Shah

, Sabhahit

, Patley

, A pan India digitally driven capacity building program to strengthen primary mental healthcare: Summary of its implementation and performance evaluation. Indian J Psychol Med, 2025;XX:1–9.

18.

Braun

and Clarke

Using thematic analysis in psychology. Qual Res Psychol, 2006; 3(2): 77–101.

19.

Muke

, Shrivastava

, Mitchell

, . Acceptability and feasibility of digital technology for training community health workers to deliver brief psychological treatment for depression in rural India. Asian J Psychiatr, 2019; 45: 99–106.

20.

Mittal

, Suchandra

, Nirisha

, . Telepsychiatry-based on-consultation training: Acceptability and feasibility from primary care doctors and psychiatrists. J Psychiatry Spectrum, 2022; 1(2): 94–99.

21.

Pahuja

, Kumar

, Uzzafar

, . An impact of a digitally driven primary care psychiatry program on the integration of psychiatric care in the general practice of primary care doctors. Indian J Psychiatry, 2020; 62(6): 690–696.

22.

Nanjudaswamy

, Joseph

, Sethi

, . Digitally driven short- and intermediate-term courses of primary care psychiatry for doctors: A theme-based analysis and performance audit. Indian J Psychol Med, 2024. DOI: 10.1177/02537176241297339.

23.

Suchandra

, Maheshwari

, Patley

, . Technology-driven innovative model for integrating mental healthcare into primary care: Example from Chhattisgarh, India. Psychiatry Res, 2025; 349: 116533. DOI: 10.1016/j.psychres.2025.116533.

24.

Sangwan

, Kansara

, Matoria

, . Perceptions of primary healthcare providers for screening and management of mental health disorders in India: A qualitative study. Front Public Health, 2024; 12: 1446606.

25.

Andrade

. The limitations of online surveys. Indian J Psychol Med, 2020; 42(6): 575–576. DOI: 10.1177/0253717620957496.

26.

Klaic

, Kapp

, Hudson

, . Implementability of healthcare interventions: An overview of reviews and development of a conceptual framework. Implement Sci, 2022; 17: 10.

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