The journey from can I to I can!

In October 2009, eight 10 year-old children from a small village named Lordi Dejgara near Jodhpur, Rajasthan, India, stopped sixteen child marriages

A deep audiovisual approach for human confidence classification

Research on self-efficacy and confidence has spread across several subfields of psychology and neuroscience. The role of one’s confidence is very crucial in the formation of attitude and communication skills. The importance of differentiating the levels of confidence is quite visible in this domain. With the recent advances in extracting behavioral insight from a signal in multiple applications, detecting confidence is found to have great importance. One such prominent application is detecting confidence in interview conversations. We have collected an audiovisual data set of interview conversations with 34 candidates. Every response (from each of the candidate) of this data set is labeled with three levels of confidence: high, medium, and low. Furthermore, we have also developed algorithms to efficiently compute such behavioral confidence from speech and video. A deep learning architecture is proposed for detecting confidence levels (high, medium, and low) from an audiovisual clip recorded during an interview. The achieved unweighted average recall (UAR) reaches 85.9% on audio data and 73.6% on video data captured from an interview session

Scaling up parenting interventions is critical for attaining the sustainable development goals

Of all the potentially modifiable influences affecting children’s development and mental health across the life course, none is more important than the quality of parenting and family life. In this position paper, we argue that parenting is fundamentally linked to the development of life skills that children need in order to achieve the United Nations Sustainable Development Goals. We discuss key principles that should inform the development of a global research and implementation agenda related to scaling up evidence-based parenting support programs. Research over the past 50 years has shown that parenting support programs of varied intensity and delivery modality can improve a wide range of developmental, emotional, behavioral and health outcomes for parents and their children. Such findings have been replicated across culturally and socioeconomically diverse samples, albeit primarily in studies from Western countries. We highlight the evidence for the relevance of parenting interventions for attaining the SDGs globally, and identify the barriers to and strategies for achieving their scale-up. The implications of the global COVID-19 pandemic for the delivery of evidence-based parenting support are also discussed

The association of a novel digital tool for assessment of early childhood cognitive development, 'DEvelopmental assessment on an E-Platform (DEEP)', with growth in rural India: A proof of concept study.

BACKGROUND: There is an urgent need to fill the gap of scalable cognitive assessment tools for preschool children to enable identification of children at-risk of sub-optimal development and to support their timely referral into interventions. We present the associations between growth in early childhood, a well-established marker of cognitive development, and scores on a novel digital cognitive assessment tool called DEvelopmental Assessment on an E-Platform (DEEP) on a sample of 3-year old pre-schoolers from a rural region in north India. METHODS: Between February 2018 and March 2019, 1359 children from the Sustainable Programme Incorporating Nutrition and Games (SPRING) programme were followed up at 3-years age and data on DEEP, anthropometry and a clinical developmental assessment, the Bayley's Scale of Infant and Toddler Development, 3rd edition (BSID-III) was collected. DEEP data from 200 children was used to train a machine learning algorithm to predict their score on the cognitive domain of BSID-III. The DEEP score of the remaining 1159 children was then predicted using this algorithm to examine the cross-sectional and prospective association of growth with the DEEP score. FINDINGS: The magnitude of the concurrent positive association between height-for-age and cognitive z-scores in 3-year olds was similar when cognition was measured by BSID-III (0.20 standard deviations increase for every unit change in specifically age-adjusted height (HAZ), 95% CI = 0.06-0.35) and DEEP (0.26 CI, 0.11-0.41). A similar positive prospective relationship was found between growth at 18 (0.21 CI, 0.17-0.26) and 12-months (0.18 CI, 0.13-0.23) and DEEP score measured at 3-years. Additionally, the relationship between growth and cognitive development was found to be dependant on socioeconomic status (SES). INTERPRETATION: In this study, we suggest the utility of DEEP, a scalable, digital cognitive assessment tool, to measure cognition in preschool children. Further validation in different and larger datasets is necessary to confirm our findings. FUNDING: The SPRING Programme was funded through a Wellcome Trust programme grant and the follow-up study by the Corporate Social Responsibility initiative grant from Madura Microfinance Ltd

The effect of cumulative early life adversities, and their differential mediation through hair cortisol levels, on childhood growth and cognition: Three-year follow-up of a birth cohort in rural India.

Background: Early adversities negatively impact children's growth and development, putatively mediated by chronic physiological stress resulting from these adverse experiences. We aimed to estimate the associations between prospectively measured cumulative early adversities with growth and cognition outcomes in rural Indian preschool children and to explore if hair cortisol concentration (HCC), a measure of chronic physiological stress, mediated the above association. Methods: Participants were recruited from the SPRING cRCT in rural Haryana, India. Adversities experienced through pregnancy and the first year of life were measured in 1304 children at 12-months. HCC was measured at 12-months in 845 of them. Outcome measures were height-for-age-z-score (HAZ), weight-for-age-z-score (WAZ) and cognition, measured in 1124 children followed up at 3-years. Cognition was measured using a validated tablet-based gamified tool named DEEP. Results: Cumulative adversities at 12-months were inversely associated with all outcomes measures at 3-years. Each unit increase in adversity score led to a decrease of 0·08 units [95% confidence interval (CI):-0·11,-0·06] in DEEP-z-score; 0·12 units [-0·14,-0·09] in HAZ and 0·11 units [-0·13,-0·09] in WAZ. 12-month HCC was inversely associated with DEEP-z-score (-0·09 [-0·16,-0·01]) and HAZ (-0·12 [-0·20,-0·04]), but the association with WAZ was not significant (p = 0·142). HCC marginally mediated the association between cumulative adversities and HAZ (proportion mediated = 0·06, p = 0·014). No evidence of mediation was found for the cognition outcome. Conclusions: Cumulative early adversities and HCC measured at 12-months have persistent negative effects on child growth and cognition at 3-years. The association between adversities and these two child outcomes were differentially mediated by HCC, with no evidence of mediation observed for the cognitive outcome. Future studies should focus on other stress biomarkers, and alternate pathways such as the immune, inflammation and cellular ageing pathways, to unpack key mechanisms underlying the established relationship between early adversities and poor child outcomes

From engagement to competency: The pathway to making disability naïve frontline workers competent in the delivery of an evidence-based autism intervention in New Delhi, India

Background: As countries like India improve access to maternal and infant care, the health systems need to develop services that enable all children to thrive. A key demographic which needs to be supported are children with disabilities, such as autism. With an estimated prevalence of one percent, there are over five million young children who need services to support their needs. However, the paucity of specialist care makes access to interventions difficult. In this context a public health research not-for-profit is evaluating the effectiveness of the task-sharing approach to support the delivery of an evidenced social communication intervention for young children with autism. This paper describes the process of engaging and training the non-specialist frontline Accredited Social Health Activists (ASHAs), who are embedded within the Ministry of Health and Family Welfare under the Delhi State Health Mission, to deliver a complex intervention for autism to inform the future scalability of services for neurodevelopmental disorders. Methods: The present study describes the process which included (i) engagement meetings, (ii) recruitment, (iii) training, (iv) internship, and (v) competency evaluation. The shortlisted ASHAs received a 7-day classroom training followed by an internship period with practice cases. Finally, competency assessments, comprising of a test of knowledge and skills through role-plays, was administered. Results: Twenty three Primary Urban Health Centers across seven districts of Delhi were approached and 408 ASHAs were engaged in initial meetings. Telephonic screening with 127 ASHAs resulted in 72 ASHAs being selected for in-person interviews. Of the 45 ASHAs who attended, 33 were shortlisted for training and 18 completed it. Fifteen ASHAs entered the internship of which 7 ASHAs achieved competency. Discussion and conclusion: There was significant attrition along the pathway to having a competent non-specialist worker deliver a complex autism intervention. The lessons learnt from this process can inform the possibility of developing a cadre of disability specific frontline health workers who can deliver evidence-based interventions for neurodevelopmental disorders under supervision

Using mobile health technology to assess childhood autism in low-resource community settings in India: an innovation to address the detection gap

A diagnosis of autism typically depends on clinical assessments by highly-trained professionals. This high resource demand poses a challenge in low-resource settings. Digital assessment of neurodevelopmental symptoms by non-specialists provides a potential avenue to address this challenge. In this study, we provide the proof of principle for such a digital assessment, with a cross-sectional case control field study using mixed methods. We developed and tested an app, START, that can assess autism phenotypic domains (social, sensory, motor) through child performance and parent reports. N=131 children (2-7 years old; 48 autistic, 43 intellectually disabled, and 40 non-autistic typically developing) from low-resource settings in India were assessed using START in home settings by non-specialist health workers. The two groups of children with neurodevelopmental disorders manifested lower social preference, higher sensory sensitivity, and lower fine-motor accuracy compared to their typically developing counterparts. Machine-learning analysis combining all START-derived measures demonstrated 78% classification accuracy for the three groups. Qualitative analysis of the interviews with health workers and families of the participants demonstrated high acceptability and feasibility of the app. These results provide feasibility, acceptability, and proof of principle for START, and demonstrate the potential of a scalable, mobile tool for assessing neurodevelopmental conditions in low-resource settings

Retinal lipid and glucose metabolism dictates angiogenesis through the lipid sensor Ffar1

Tissues with high metabolic rates often use lipids, as well as glucose, for energy, conferring a survival advantage during feast and famine1. Current dogma suggests that high-energy–consuming photoreceptors depend on glucose2, 3. Here we show that the retina also uses fatty acid β-oxidation for energy. Moreover, we identify a lipid sensor, free fatty acid receptor 1 (Ffar1), that curbs glucose uptake when fatty acids are available. Very-low-density lipoprotein receptor (Vldlr), which is present in photoreceptors4 and is expressed in other tissues with a high metabolic rate, facilitates the uptake of triglyceride-derived fatty acid5, 6. In the retinas of Vldlr−/− mice with low fatty acid uptake6 but high circulating lipid levels, we found that Ffar1 suppresses expression of the glucose transporter Glut1. Impaired glucose entry into photoreceptors results in a dual (lipid and glucose) fuel shortage and a reduction in the levels of the Krebs cycle intermediate α-ketoglutarate (α-KG). Low α-KG levels promotes stabilization of hypoxia-induced factor 1a (Hif1a) and secretion of vascular endothelial growth factor A (Vegfa) by starved Vldlr−/− photoreceptors, leading to neovascularization. The aberrant vessels in the Vldlr−/− retinas, which invade normally avascular photoreceptors, are reminiscent of the vascular defects in retinal angiomatous proliferation, a subset of neovascular age-related macular degeneration (AMD)7, which is associated with high vitreous VEGFA levels in humans. Dysregulated lipid and glucose photoreceptor energy metabolism may therefore be a driving force in macular telangiectasia, neovascular AMD and other retinal diseases