Erratum: Indian adolescents' perceptions of anaemia and its preventive measures: A qualitative study - ERRATUM.

[This corrects the article DOI: 10.1017/jns.2024.4.].

Indian adolescents' perceptions of anaemia and its preventive measures: Aqualitative study.

High prevalence of anaemia is a severe public health problem in several low- and middle-income countries like India. A qualitative inquiry was designed to understand the perceptions of adolescents regarding anaemia and anaemia prevention measures. Convenience sampling was employed to recruit 39 adolescents (19 girls; 20 boys) from Tikari, India. Interviews were carried out in the local language, audio-recorded and transcribed verbatim. Hemoglobin concentration was also assessed from a single drop of capillary blood using the HemoCue, and the participants were asked to share their Science/Biology and Home Science textbooks. Interview data was analysed thematically. Descriptive statistics were used to examine the distributions of the hemoglobin data while textbooks were analysed using content analysis to verify the coverage of anaemia and anaemia-related matter. Seven themes were identified: (i) Poor understanding of the term anaemia; (ii) Minimal discussion about anaemia in classroom; (iii) Limited knowledge about symptoms of anaemia; (iv) Limited awareness about prevention and cure of anaemia; (v) Perception of iron folic acid and deworming tablets among students; (vi) Lack of contribution of health workers in the prevention of anaemia; (vii) No knowledge of 'Anemia free India' programme. More than half of the sample had anaemia (16.7% mild anaemia, 33.3% moderate anaemia, 2.8% severe anaemia). Content analysis revealed that there was limited discussion about anaemia in both Home Science and Science textbooks. Behavioural interventions should focus on inculcating healthy culinary and dietary practices and addressing the gaps in knowledge and understanding of anaemia and its prevention among adolescents.

How do adolescents classify foods as healthy and unhealthy?: A qualitative inquiry from rural India.

Indian adolescents exhibit obesogenic dietary habits including low intake of fruits and vegetables and increasing consumption of fast food and carbonated beverages. Adolescents' classification of healthy and unhealthy foods is likely to have significant implications for their dietary behaviour, and consequently, their health. However, there is limited evidence about the ways Indian adolescents classify foods as healthy or unhealthy. Hence, this qualitative study was designed to explore how Indian adolescents classify nutritious or non-nutritious food choices. Convenience sampling was used to recruit the study participants from Tikari village in Uttar Pradesh, India. Underpinned by the social constructivist lens, the adolescents were interviewed face-to-face in Hindi. All the interactions were digitally recorded, transcribed verbatim, and translated into English prior to data analysis. Transcribed data were analysed thematically using inductive as well as deductive coding, and subsequently, conceptual themes were extracted. A total of thirty-nine adolescents (twenty boys; nineteen girls) aged 10-19 years participated in this qualitative inquiry. The adolescents classified healthy and unhealthy foods based on the following six themes: (i) Food groups and nutrients; (ii) Health and immunity; (iii) Type of ingredient; (iv) Place and time of food preparation; (v) Packaging; and (vi) Parental influence. These findings can inform school-based food literacy interventions to foster healthy dietary habits and cooking skills among Indian adolescents.

Indian adolescents' perceptions of packaged food and food labels - A qualitative inquiry.

In the last two decades, India has witnessed a dramatic rise in the consumption of packaged foods, especially among adolescents. Food labelling is often recognised as an instrumental population-based approach which can enable consumers to make informed food choices by providing all the necessary details about the food product on the packaging. In the Indian context, where adolescent obesity and the ensuing non-communicable diseases are escalating, it is crucial to understand adolescents' views on the use of non-nutritious packaged foods and food labels. Therefore, the aim of this qualitative inquiry was to explore Indian adolescents' perceptions regarding the consumption of packaged food and use of food labels. Convenience sampling was employed to recruit 29 boys and 15 girls (aged 10-19 years) from rural Varanasi, India. Semi-structured, face-to-face interviews were conducted in the local language. Interview recordings were transcribed verbatim and translated to English. Narrative data were subjected to thematic analysis using NVivo software program. The adolescents reported frequent consumption of packaged food like potato chips, biscuits, chocolates, deep-fried Indian snacks both at school and home. Packaged foods were regarded as tasty, safe, and fresh. Brand name, date of expiry and cost were often read by the study respondents. Nevertheless, they reported difficulty in understanding other components of the label (e.g., nutrition information) and they were not aware of the negative impact of consuming unhealthy packaged foods. Nearly all the respondents insisted that food labels should be written in the local language for easy understanding. These emerging findings underscore the need to design school-based food literacy programs for vulnerable Indian adolescents to address obesity and diet-related complications in early adulthood.

Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy.

The Endoscopy Computer Vision Challenge (EndoCV) is a crowd-sourcing initiative to address eminent problems in developing reliable computer aided detection and diagnosis endoscopy systems and suggest a pathway for clinical translation of technologies. Whilst endoscopy is a widely used diagnostic and treatment tool for hollow-organs, there are several core challenges often faced by endoscopists, mainly: 1) presence of multi-class artefacts that hinder their visual interpretation, and 2) difficulty in identifying subtle precancerous precursors and cancer abnormalities. Artefacts often affect the robustness of deep learning methods applied to the gastrointestinal tract organs as they can be confused with tissue of interest. EndoCV2020 challenges are designed to address research questions in these remits. In this paper, we present a summary of methods developed by the top 17 teams and provide an objective comparison of state-of-the-art methods and methods designed by the participants for two sub-challenges: i) artefact detection and segmentation (EAD2020), and ii) disease detection and segmentation (EDD2020). Multi-center, multi-organ, multi-class, and multi-modal clinical endoscopy datasets were compiled for both EAD2020 and EDD2020 sub-challenges. The out-of-sample generalization ability of detection algorithms was also evaluated. Whilst most teams focused on accuracy improvements, only a few methods hold credibility for clinical usability. The best performing teams provided solutions to tackle class imbalance, and variabilities in size, origin, modality and occurrences by exploring data augmentation, data fusion, and optimal class thresholding techniques.