Mental Health Awareness

Abstract

The rapid growth of digital platforms and e-commerce has made recommendation systems essential for helping users discover relevant products while improving customer satisfaction and business revenue. Traditional recommendation approaches, such as Collaborative Filtering (CF) and Content-Based Filtering (CBF), face challenges including popularity bias, data sparsity, limited diversity, and poor transparency. Popularity bias disproportionately favors well-known products and large vendors, reducing visibility for small businesses, MSMEs, and regional sellers. Additionally, many deep learning recommendation models function as \"black boxes,\" making it difficult for users to understand why products are recommended. To overcome these limitations, the proposed research introduces a Hybrid, Fairness-Aware, and Explainable Recommendation System tailored for Indian e-commerce platforms. The system combines Collaborative Filtering, Content-Based Filtering, and lightweight deep learning techniques to improve recommendation accuracy and diversity. Fairness-aware methods, including exposure balancing, fair sampling, and re-ranking algorithms, are incorporated to reduce popularity bias and provide equitable exposure for smaller sellers. Explainable AI (XAI) techniques such as SHAP and LIME are integrated to generate clear, human-understandable explanations for recommendations, enhancing transparency and user trust. The framework also includes role-based governance dashboards for users, managers, and administrators to monitor recommendation quality, fairness metrics, and model performance while complying with Responsible AI principles and India\'s Digital Personal Data Protection Act (2023). The proposed architecture follows a three-tier design consisting of a Next.js/React frontend, a Node.js/Express backend, and a FastAPI-based machine learning microservice with MongoDB for data storage. The hybrid recommendation score combines collaborative, content-based, and neural recommendation outputs, while fairness-aware re-ranking adjusts item exposure to improve equity. The system supports personalized recommendations, feedback collection, fairness monitoring, model versioning, and real-time explanations. Evaluation focuses on recommendation accuracy (Precision@K and NDCG), fairness metrics, explainability, and governance capabilities. Experimental results indicate that the hybrid model enhances recommendation relevance, significantly reduces exposure imbalance through fairness-aware ranking, and improves user trust through explainable recommendations, making it a scalable and responsible solution for modern e-commerce environments.

Introduction

Mental health is a fundamental aspect of overall well-being, influencing emotional, psychological, and social functioning. Despite its importance, mental health remains underrecognized, particularly in low- and middle-income countries such as India, where stigma, limited awareness, and inadequate healthcare infrastructure prevent timely diagnosis and treatment. Mental health disorders—including depression, anxiety, bipolar disorder, schizophrenia, and substance use disorders—are increasing due to factors such as academic pressure, social expectations, rapid urbanization, poverty, unemployment, trauma, and excessive social media use. Young people are especially vulnerable, with most mental health conditions developing before the age of 24.

A major barrier to mental healthcare is the widespread stigma associated with mental illness, which leads to discrimination, delayed help-seeking, and social isolation. Limited availability of trained mental health professionals, insufficient healthcare facilities, poor integration of mental health into primary healthcare, and unequal access in rural areas further widen the treatment gap. These challenges have significant social and economic consequences, including reduced productivity, increased healthcare costs, and diminished quality of life.

Mental health awareness and literacy are essential for reducing stigma, improving early detection, and encouraging individuals to seek professional help. Community-based awareness programs, educational initiatives, counselling services, and social media campaigns have shown promise in promoting mental health knowledge and changing public attitudes. Education plays a crucial role in dispelling misconceptions, increasing empathy, and fostering supportive communities. Digital technologies, including the internet, mobile applications, and social media, provide effective platforms for delivering mental health information and support to wider populations.

The paper also discusses India's National Mental Health Programme (NMHP), which aims to integrate mental healthcare into general health services, promote community participation, and improve access to mental health services. However, implementation challenges such as inadequate funding, workforce shortages, and limited district-level planning continue to affect its effectiveness.

Future directions emphasize integrated, community-centered, and technology-enabled mental healthcare. Strengthening public awareness, reducing stigma through education, improving workplace and school-based mental health programs, expanding digital interventions, and increasing investment in mental healthcare infrastructure are identified as key priorities. Overall, the study highlights that improving mental health requires coordinated efforts involving healthcare systems, governments, educational institutions, families, communities, and digital platforms to ensure accessible, equitable, and stigma-free mental healthcare.

Conclusion

A new strategy is necessary given the shortcomings of previous mental health initiatives in less developed nations. Social media offers both opportunities and challenges for raising awareness of mental health issues dueto its large public conversation. Effective public health campaigns are still hampered by the inaccurate categorisation of mental health information, despite advancements. Collaboration with community members who are already involved in online activities should be a part of future endeavours. Further research on universal, school-based mental health interventions using long-term follow-ups and randomised controlled trial methods is also necessary. Innovative teaching strategies and interventions focused on people\'s willingness to change show promise. Lastly, innovative technical solutions, strong media participation, and comprehensive government policies can greatly address mental health challenges.

References

[1] Kolappa K, Henderson DC, Kishore SP. No physical health without mental health: Lessons unlearned? Bull World Health Organ. 2013;91:3–3A Cited Here|PubMed| CrossRef|Google Scholar [2] Prince M, Patel V, Saxena S, Maj M, Maselko J, Phillips MR, et al No health without mental health Lancet. 2007;370:859–77 Cited Here|PubMed| CrossRef|Google Scholar [3] Murray CJ, Atkinson C, Bhalla K, et al. The state of US health, 1990-2010: burden of diseases, injuries, and risk factors. JAMA. 2013; 310(6): 591-608 [4] Patel V, Goel DS, Desai R.Scaling up services formental and neurological disorders in low-resource settings Int Health. 2009;1:37–44 Cited Here| PubMed| CrossRef|Google Scholar [5] Saraceno B, van Ommeren M, Batniji R, Cohen A, Gureje O, Mahoney J, et al Barriers to improvement of mentalhealthservicesinlow-incomeandmiddle-incomecountriesLancet.2007;370:1164–74CitedHere| PubMed| CrossRef|Google Scholar [6] PatelV,SaxenaS.Transforminglives,enhancingcommunities–InnovationsinglobalmentalhealthNEnglJ Med. 2014;370:498–501 Cited Here|View Full Text| PubMed| CrossRef|Google Scholar [7] Rebello TJ, MarquesA, Gureje O, Pike KM. Innovative strategies forclosing the mentalhealth treatment gap globallyCurrOpinPsychiatry.2014;27:308–14CitedHere|ViewFullText|PubMed|CrossRef|Google Scholar [8] World Health Organization. World Health Statistics 2016. 2016 Geneva 27, Switzerland World Health Organization Cited Here [9] Merikangas KR, He JP, Burstein M,etal.Lifetime prevalenceof mentaldisorders in U.S.adolescents:results from the National Comorbidity Survey Replication--AdolescentSupplement (NCS-A). J Am Acad Child Adolesc Psychiatry. 2010; 49(10): 980-989. [10] Patel V, Ramasundarahettige C, Vijayakumar L, Thakur JS, Gajalakshmi V, Gururaj G, et al Suicide mortalityinIndia:AnationallyrepresentativesurveyLancet.2012;379:2343–51CitedHere|PubMed| CrossRef|Google Scholar [11] Farie AM, Cowen EL, Smith M. The development and implementation of a rural consortium program to provide early, preventive school mental health services. Community Ment Health J. 1986; 22(2): 94-103. [12] WorldHealthOrganization.PhysicalInactivity:AGlobalPublicHealthProblemAvailablefrom:http://wwwwhoint/dietphysicalactivity/factsheet_inactivity/en/indexhtml[Lastaccessedon4/13/2019]. CitedHere|Google Scholar [13] Richards J, Thorogood M, Hillsdon M, Foster C. Face-to-face versus remote and web 2.0 interventions for promoting physical activity. Cochrane Database Syst Rev 2013;30(9):CD010393. Cited Here|Google Scholar Indian Council of Medical research. Mental health research in India (Technical monograph on ICMR research studies in India). New Delhi; Indian council of Medical Research, 2005: 5-7 DirectorGeneralofHealthServices(DGHS):NationalMentalHealthProgrammeforIndia.NewDelhi, MinistryofHealthandFamilyWelfare;1982 [14] Isaac M.K, Srinivasa Murthy R, Chandrasekar C.R et al. Decentralised training for PHC medical officers ofa district - the Bellary approach. In Varghese A (eds) Continuing Medical Education Vol. VI. Calcutta: Indian Psychia1tric Society; 1986. [15] Isaac MK. District Mental Health Programme at Bellary. Community Mental News – Issue No. 11 and 12. Bangalore: Indian Council of Medical Research – Centre for Advanced Research on Community Mental Health; 1988. [16] Nagarajiah, Reddamma K, Chandrasekar C.R et al. Evaluation of short-term training in mental health for multipurpose workers. Indian Journal of Psychiatry 1994; 36:12-17. [17] Naik A.N, Parthasarathy R. Isaac M.K. Families of rural mentally ill and treatment adherence in district mental health programme, International Journal of Social Psychiatry 1996; 42:168-172. [18] Naik AN, Isaac M, Parthasarathy R et al. The perception and experience of health personnel about integration of mental health in general health services. Indian Journal of Psychiatry 1994; 36: 18- 21. [19] MinistryofHealth&FamilyWelfare,GovernmentofIndia:AnnualReport:2013-14 [20] MathersCD, Loncar D. Projectionsof globalmortality and burden of disease from2002 to 2030. PLoS Med 2006; 3: e442.Cited Here|Google Scholar [21] India State-Level Disease Burden Initiative Mental Disorders Collaborators. The burden of mental disorders acrossthestatesofIndia:TheGlobalBurdenofDiseasestudy1990-2017.LancetPsychiatry2020;7:148–61.CitedHere|PubMed|CrossRef|GoogleScholar [22] SinghOP.StartlingsuicidestatisticsinIndia:Timeforurgentaction.IndianJPsychiatry2022;64:431–2.CitedHere|PubMed|CrossRef|GoogleScholar [23] GargK,Kumar CN,Chandra PS.Numberof psychiatristsinIndia:Babystepsforward,buta longwaytogo. [24] IndianJPsychiatry2019;61:104–5.CitedHere|PubMed|GoogleScholar [25] Dhyani A, Gaidhane A, Choudhari SG, Dave S, Choudhary S. Strengthening response toward promoting mental health in India:Anarrative review. Cureus 2022; 14: e30435.Cited Here|Google Scholar [26] Substance Abuse and Mental Health Services Administration (SAMHSA). 2021 NSDUH Annual National Report. Available from https://www.samhsa.gov/data/re port/2021-nsduh-annual-national-report, accessed on October 13, 2023.Cited Here [27] The Times of India. Focus on students\' mental health. Available from:https://www.timesofindia.indiatimes.com/city/bhubaneswar/focus-on-students-mental-health/articleshow/100203371.cms?from= HYPERLINK \"https://www.timesofindia.indiatimes.com/city/bhubaneswar/focus-on-students-mental-health/articleshow/100203371.cms?from=mdr\" HYPERLINK\"https://www.timesofindia.indiatimes.com/city/bhubaneswar/focus-on-students-mental-health/articleshow/100203371.cms?from=mdr HYPERLINK\"https://www.timesofindia.indiatimes.com/city/bhubaneswar/focus-on-students-mental-health/articleshow/100203371.cms?from=mdr\"mdr,accessedonSeptember29,2023.CitedHere [28] Garg S, Kharb A, Bansal K. What covariates drive medical students to the brink of suicidal ideation, plan, andattempt?Adouble-centric cross-sectionalstudyina resource-constrainedruralsettinginNorthIndia.Indian J Psychiatry 2023; 65: 431–42.Cited Here|PubMed| CrossRef|Google Scholar [29] NationalInstituteofMentalHealthandNeurosciences(NIMHANS).Nationalmentalhealthsurvey2. [30] Availablefrom:https://www.indianmhs.nimhans.ac.in,accessedonSeptember29,2023.CitedHere [31] MurthyRS.NationalMentalHealthSurveyof India2015-2016.IndianJPsychiatry2017;59:21–6. [32] Dias A, Azariah F, Anderson SJ, Sequeira M, Cohen A, Morse JQ, et al. Effect of a lay counselor intervention on prevention of major depression in older adults living in low- and middle-income countries:A randomized clinical trial. JAMA Psychiatry 2019; 76: 13–20. [33] Sekhon H, Lavin P, Vacaflor B, Rigas C, Cinalioglu K, Su CL, et al. Isolating together during COVID-19:Results from the Telehealth Intervention Program for older adults. Front Med (Lausanne) 2022; 9: 948506. [34] Nikolitch K, Laliberté V, Yu C, Strychowsky N, Segal M, Looper KJ, et al. Tolerability and suitability of brief group mindfulness-oriented interventions in psychiatric inpatients:a pilot study. Int J Psychiatry Clin Pract 2016; 20: 170–4. [35] M. Thirunavukarasu, P. Thirunavukarasu. Training and National deficit of psychiatrists in India – Acritical analysis. Indian J Psychiatry 52, Supplement, January 2010.

Copyright

Copyright © 2026 Vanshika Karande, Pranjali Kadam, Aakansha More, Rajendra Patil. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.