Ankita Kankaria

Introduction Despite implementation of the National Programme for Prevention and Control of Non-Communicable Diseases (NP-NCD), screening coverage for oral, breast and cervical cancers remains below 2%. Screening quality is inadequately addressed and delays in diagnosis and treatment initiation continue to persist. This multisite implementation research aims to improve district-level coverage and quality of screening, early diagnosis and timeliness of treatment initiation through a model co-developed within the NP-NCD context. Methods and analysis The study will be conducted in three phases across seven districts in diverse regions of India. In phase I (formative), the current status, barriers and facilitators of cancer screening, diagnosis and treatment initiation under NP-NCD will be assessed. In phase II (optimisation), a model (package of implementation strategies) will be co-developed and iteratively optimised with multistakeholder engagement at the subdistrict level to improve screening coverage and quality and strengthen the referral system for early diagnosis and treatment initiation. In phase III (scale-up and evaluation), the model will be implemented at the district level and evaluated for improvements in screening, early diagnosis and treatment initiation. A convergent mixed-methods design will be used, incorporating household surveys, facility assessments and stakeholder interviews. Implementation Research Logic Model will guide planning, execution and evaluation in the present study. Determinants of screening coverage and quality, early diagnosis and treatment initiation will be assessed using the Consolidated Framework for Implementation Research. Implementation strategies for the model will be finalised using the Expert Recommendations for Implementing Change framework. Implementation and service outcomes will be evaluated using the Reach, Effectiveness, Adoption, Implementation and Maintenance framework. Ethics and dissemination Ethical approval has been obtained from all study sites. The study findings will be disseminated at the state, national and global levels through meetings and conferences and submitted to a peer-reviewed journal for publication. Trial registration number CTRI/2025/08/092672.

Objectives To assess and compare the diagnostic accuracy of non-ophthalmologist-led diabetic retinopathy screening (DRS) at health and wellness centres (HWCs) and offline artificial intelligence (AI)-assisted community-based screening, using specialist grading as the reference standard in India. Design, settings and participants Pragmatic diagnostic accuracy study in primary healthcare settings. The settings included HWCs and community-based screening sites in rural Block Boothgarh, Mohali District, Punjab, India. A total of 600 people with diabetes aged ≥30 years were enrolled across three screening models: (1) non-ophthalmologist-led DRS at the HWC, (2) AI-assisted smartphone-based DRS in the community and (3) standard referral-based care. Retinal images were captured using non-mydriatic fundus cameras and independently graded by two masked human graders; a senior retina specialist resolved any disagreements. The AI was assessed for its ability to detect diabetic retinopathy (DR) and referable diabetic retinopathy (RDR). Diagnostic performance metrics were reported. Results The non-ophthalmologist-led model demonstrated 86.4% sensitivity (95% CI 65.1% to 97.1%) and 94.3% specificity (95% CI 88.5% to 97.7%) for DR detection, with an ungradability rate of 8%. For RDR, sensitivity reached 95.8% (95% CI 78.9% to 99.9%) and specificity was 93.1% (95% CI 88.0% to 96.5%). The offline AI-assisted model achieved 93.3% sensitivity (95% CI 68.1% to 99.8%) and 85.1% specificity (95% CI 76.9% to 91.2%) for RDR, but with a higher ungradability rate (38%), mainly due to cataracts and poor image quality. Both approaches effectively identified referable cases; however, the non-ophthalmologist-led model demonstrated greater accuracy and operational feasibility. Conclusions This study demonstrates that non-ophthalmologist-led DRS at HWCs can enhance access to primary care. Offline AI-enabled screening demonstrates potential for community use but is currently limited by image quality and binary classification outputs. Integrating both approaches may strengthen DRS coverage in resource-limited settings. Clinical trials registry of India CTRI/2022/10/046283.

Introduction: The menstrual cup is a sustainable, cost-effective, and eco-friendly alternative to traditional menstrual hygiene products, offering long-term comfort and protection. This study aims to assess knowledge and perception regarding menstrual cups among healthcare personnel and explore their perception of the menstrual cup. Methods: A cross-sectional mixed-method study was conducted among 248 female healthcare personnel at a tertiary care institute in northern India. A semi-structured questionnaire was used to collect quantitative data and an in-depth interview guide among 31 participants was used to explore perceptions about the cup. Knowledge was assessed across eight domains, and a score was calculated. A score of “8” was considered as having adequate knowledge and any score between “1-7” was considered partial knowledge and a score of “0” as no knowledge. Categorical variables were presented as frequency (%) and continuous variables as mean (±SD). A Chi-square test was conducted to see the association of sociodemographic characteristics with adequate knowledge. A P -value < 0.05 was considered significant. The qualitative data were coded, thematically analyzed, and triangulated with quantitative data. Results: Very few (1.7%) of the participants had adequate knowledge about the cup regarding its size , type of material, method of insertion and removal, cleaning, duration of use, and source of obtaining the cup . The perceived barriers to cup usage were limited knowledge, pain in using a menstrual cup, fear of infection, sudden expulsion of the cup from the body, retention in the body, or loss of virginity . Current users reported cups as a better alternative to sanitary napkins, being free of side effects, cheaper, convenient, and eco-friendly. Conclusion: There is a need to equip healthcare professionals with adequate knowledge about the menstrual cup and address their misconceptions. This will potentially help women adopt safe, cost-effective, and eco-friendly menstrual hygiene methods like a menstrual cup.

Background: Artificial intelligence (AI) algorithms offer an effective solution to alleviate the burden of diabetic retinopathy (DR) screening in public health settings. However, there are challenges in translating diagnostic performance and its application when deployed in real-world conditions. Objective: This study aimed to assess the technical feasibility of integration and diagnostic performance of validated DR screening (DRS) AI algorithms in real-world outpatient public health settings. Methods: Prior to integrating an AI algorithm for DR screening, the study involved several steps: (1) Five AI companies, including four from India and one international company, were invited to evaluate their diagnostic performance using low-cost nonmydriatic fundus cameras in public health settings; (2) The AI algorithms were prospectively validated on fundus images from 250 people with diabetes mellitus, captured by a trained optometrist in public health settings in Chandigarh Tricity in North India. The performance evaluation used diagnostic metrics, including sensitivity, specificity, and accuracy, compared to human grader assessments; (3) The AI algorithm with better diagnostic performance was integrated into a low-cost screening camera deployed at a community health center (CHC) in the Moga district of Punjab, India. For AI algorithm analysis, a trained health system optometrist captured nonmydriatic images of 343 patients. Results: Three web-based AI screening companies agreed to participate, while one declined and one chose to withdraw due to low specificity identified during the interim analysis. The three AI algorithms demonstrated variable diagnostic performance, with sensitivity (60%-80%) and specificity (14%-96%). Upon integration, the better-performing algorithm AI-3 (sensitivity: 68%, specificity: 96, and accuracy: 88·43%) demonstrated high sensitivity of image gradability (99.5%), DR detection (99.6%), and referral DR (79%) at the CHC. Conclusions: This study highlights the importance of systematic AI validation for responsible clinical integration, demonstrating the potential of DRS to improve health care access in resource-limited public health settings.

Background: We evaluated a pilot mobile health (mHealth) intervention aimed at improving postnatal maternal and infant health. The intervention featured provider-led group sessions for education, health care communication, in-person care referrals, and virtual mHealth support for postpartum mothers through weekly calls, texts, interactive voice response (IVR), and a phone app. Objective: We aimed to assess the preliminary effectiveness of the pilot mHealth intervention, MeSSSSage (Maa Shishu Swasthya Sahayak Samooh, which means maternal and child health support group), on infant health knowledge, behaviors, and outcomes at 6 months post partum. We focus on maternal knowledge of infant danger signs and optimal young child feeding practices at 6 months post partum and also evaluate maternal care-seeking behaviors for infants, adherence to age-appropriate immunization, and infant and young child feeding practices such as early initiation of breastfeeding and complementary feeding. Methods: We evaluated the preliminary effectiveness of an intervention on maternal health knowledge among 135 participants in Punjab, India, who completed pre- and postintervention surveys. The intervention, led by research personnel with backgrounds similar to community health officers, aimed to empower society and support universal health coverage if successful. We assessed changes in knowledge of maternal danger signs and the appropriate age for introducing different food groups over 6 months post partum. Additionally, we examined postintervention differences in health-seeking behavior for infants, adherence to age-appropriate immunizations, and adoption of breastfeeding and complementary feeding practices among women in the synchronous (group call), asynchronous (IVR and app), and control arms. Results: Of 12 infant risk factors, maternal knowledge of infant danger signs remained low (mean range: 1.85-2.31 preintervention and 1.81-2.22 postintervention). Participants in the synchronous arm had a statistically significant higher mean increase (mean difference: 0.87, 95% CI 0.06‐1.69) compared to the control arm. Participants in synchronous arms had nearly 3-fold increased odds of infant health checkup by a clinical provider than asynchronous arm participants (odds ratio [OR] 2.72, 95% CI 1.02-7.23). No significant differences were noted in age-appropriate vaccine coverage among infants between arms, though vaccination coverage was more than 80% across all arms. Early initiation of breastfeeding remained low across all arms (~47%). Conclusions: Our pilot study on group-based mHealth education and virtual social support during the postnatal phase showed modest yet promising results. Rigorous testing is crucial to strengthening the limited evidence base for group-oriented mHealth approaches.

Introduction: Early screening is recommended to prevent vision impairment (VI) and blindness globally due to diabetic retinopathy (DR). We aim to analyze the factors influencing the implementation of DR screening models in primary healthcare facilities. Methods: A pragmatic three-arm observational study will be conducted in the district of Mohali in Punjab, India. The study will compare three equal-sized groups with type 2 diabetes mellitus (T2DM) at age 30 and above. The T2DM participants and healthcare providers (HCPs) will be interviewed to identify the barriers to retinal examinations in primary healthcare settings. The study includes a comprehensive economic evaluation to determine the cost-effectiveness of implementing different DR screening models in primary health settings. The present study will use the RE-AIM framework (reach, effectiveness, adoption, implementation, and maintenance), to assess the implementation of two DR screening interventions and the extent of variation in outcomes. Qualitative and quantitative data collected from participants and research team observations will be examined to report on the five RE-AIM domains. Discussion: A screening program should ensure early detection and referral for DR treatment before it results in irreversible vision loss. However, understanding the problems of accessing DR screening and estimating the cost-effectiveness of such programs in a primary health setting is important before allocating public health resources.

Background: Artificial intelligence applications for diabetic retinopathy grading have rapidly advanced but it is essential that these potential solutions are assessed for their diagnostic performance and cost-effectiveness. This review assesses evidence on the diagnostic accuracy and cost-effectiveness of automated image software for DR screening using human graders as the reference standard. Method: A systematic review of (i): diagnostic test accuracy (DTA) studies and (ii) economic evaluations (EE). For DTA studies, a literature search of Web of Science, MEDLINE (PubMed), EMBASE, Ovid, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane Database of Systematic Reviews (CDSR) from January 2000 to May 2023. For EEs, the DTA search strategy will be adapted to include economic search terms. Specialist databases (NHS Economic Evaluation Database; Cost-effectiveness Analysis Registry, Health Technology Assessment (HTA) database) will be searched from inception to May 2023. All titles and abstracts identified will be screened. For potentially eligible studies full-text screening will be conducted. Eligible studies will be those comparing the grading of fundus images by AI with retinal examination by trained professionals. Data extraction will be tailored to the type of study (DTA or EE) using a prespecified data extraction form. Data extracted will include source, study methods, participant characteristics, disease characteristics, index and reference test, data collection methods, costing component, costing characteristics, and outcome. For DTAs, risk of bias will be assessed using Quality Assessment of Diagnostic Studies- Comparative (QUADAS-C). For EEs the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) will be used. Two independent reviewers will be involved in study selection, screening, data extraction, and risk of bias assessment. Any disagreement in these steps will be resolved by discussion or a third reviewer. For DTA studies, study results will be summarised as pooled sensitivity and specificity, summary receiver operating curve, and accuracy and prevalence adjusted and bias-adjusted kappa. For EE, data will be summarised in a narrative summary. Discussion: This study will provide insights into the AI software's diagnostic accuracy and its cost-effectiveness for DR screening. Trial registration: PROSPERO, CRD42021244269

Background: Structural and cultural barriers limit Indian women’s access to adequate postnatal care and support despite their importance for maternal and neonatal health. Targeted postnatal education and support through a mobile health intervention may improve postnatal recovery, neonatal care practices, nutritional status, knowledge and care seeking, and mental health. Objective: We sought to understand the feasibility and acceptability of our first pilot phase, a flexible 6-week postnatal mobile health intervention delivered to 3 groups of women in Punjab, India, and adapt our intervention for our next pilot phase, which will formally assess intervention feasibility, acceptability, and preliminary efficacy. Methods: Our intervention prototype was designed to deliver culturally tailored educational programming via a provider-moderated, voice- and text-based group approach to connect new mothers with a social support group of other new mothers, increase their health-related communication with providers, and refer them to care needed. We targeted deployment using feature phones to include participants from diverse socioeconomic groups. We held moderated group calls weekly, disseminated educational audios, and created SMS text messaging groups. We varied content delivery, group discussion participation, and chat moderation. Three groups of postpartum women from Punjab were recruited for the pilot through community health workers. Sociodemographic data were collected at baseline. Intervention feasibility and acceptability were assessed through weekly participant check-ins (N=29), weekly moderator reports, structured end-line in-depth interviews among a subgroup of participants (15/29, 52%), and back-end technology data. Results: The participants were aged 24 to 28 years and 1 to 3 months postpartum. Of the 29 participants, 17 (59%) had their own phones. Half of the participants (14/29, 48%) attended ≥3 of the 6 calls; the main barriers were childcare and household responsibilities and network or phone issues. Most participants were very satisfied with the intervention (16/19, 84%) and found the educational content (20/20, 100%) and group discussions (17/20, 85%) very useful. The participants used the SMS text messaging chat, particularly when facilitator-moderated. Sustaining participation and fostering group interactions was limited by technological and sociocultural challenges. Conclusions: The intervention was considered generally feasible and acceptable, and protocol adjustments were identified to improve intervention delivery and engagement. To address technological issues, we engaged a cloud-based service provider for group calls and an interactive voice response service provider for educational recordings and developed a smartphone app for the participants. We seek to overcome sociocultural challenges through new strategies for increasing group engagement, including targeting midlevel female community health care providers as moderators. Our second pilot will assess intervention feasibility, acceptability, and preliminary effectiveness at 6 months. Ultimately, we seek to support the health and well-being of postpartum women and their infants in South Asia and beyond through the development of efficient, acceptable, and effective intervention strategies.

Background: As mobile phone uptake in India continues to grow, there is also continued interest in mobile platform–based interventions for health education. There is a significant gender gap in mobile phone access—women’s access to mobile phones is constrained by economic and social barriers. Pregnancy and postpartum care is one of many targets for mobile health (mHealth) interventions that particularly rely upon women’s access to and facility with mobile phone use. Objective: We aimed to describe the dynamics and patterns of married pregnant and postpartum women’s mobile phone access and use (among both phone owners and nonowners) who participated in an mHealth postpartum care intervention and to identify potential barriers to their participation in mobile platform–based interventions. Methods: A secondary analysis was performed on mixed methods data obtained for a pilot mHealth intervention for postpartum care of mothers in rural Punjab from July 2020 to February 2021. Two formative sources included exploratory in-depth interviews among postpartum women (n=20; 1-3 months postpartum) and quantitative maternal health survey among women who were pregnant or who had recently given birth (n=102). We also utilized mixed methods intervention assessment data from early postpartum women who participated in the pilot intervention (n=29), including intervention moderator perspectives. Qualitative and quantitative analyses were performed, and pertinent findings were grouped thematically. Results: The majority of women owned a phone (maternal health survey: 75/102, 74%; demographic survey: 17/29, 59%), though approximately half (53/102, 52%) still reported sharing phones with other family members. Sharing a phone with female family members typically allowed for better access than sharing with male family members. Some households had strict preferences against daughters-in-law having phones, or otherwise significantly restricted women’s phone access. Others reported concerns about phone use–related health hazards for mother and infant during the pregnancy or postpartum period. Conclusions: These findings suggest nuance regarding what is meant by women’s phone ownership and access—there were numerous additional constraints on women’s use of phones, particularly during pregnancy and the postpartum period. Future research and mHealth interventions should probe these domains to better understand the dynamics governing women’s access, use, and fluency with mobile phones to optimally design mHealth interventions.