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The purpose of this paper was to investigate the prevalence rates of stress, depression and anxiety and their sociodemographic factors linked with the Indian population following the second round of COVID-19 in India.

A cross-sectional study was carried out using an online questionnaire. In total, 505 individuals participated through convenience sampling. To measure anxiety, depression and stress, the Depression Anxiety Stress Scale (DASS-21), a 21-statement self-reported questionnaire, was used.

Multiple regression analyses were performed to evaluate the sociodemographic characteristics associated with depression, stress and anxiety. Results indicated salary/allowances reduction and alcohol consumption were associated with depression. Multiple regression also indicated that salary/allowances reduction, smoking status and alcohol consumption were associated with stress. In addition, this research also showed that chronic disease, salary/allowances reduction, smoking status and alcohol consumption were associated with anxiety.

During the second COVID-19 wave in India, various individuals were affected. Anxiety, depression and stress were common among Indians after the second wave of COVID-19. Along with other actions to restrict the development of COVID-19, the Indian Government and mental health specialists must pay close attention to the inhabitants' mental health. More large-scale studies on various occupations should be conducted, and new mental health factors should be included.

This study provides empirical insights related the sociodemographic factors and stress, anxiety and depression.

The study aims to look at deep eWOM providing behaviour in m-commerce and attempts to explore its antecedents. Personalisation is proposed as an indirect antecedent of deep eWOM providing behaviour mediated by hedonic and utilitarian value perceptions and personal identification.

Based on social-exchange theory, the conceptual model links the study antecedents to deep eWOM providing behaviour. The conceptual model was validated through a multi-country study. A large sample of m-commerce users in the UK (n = 505), India (n = 422) and Vietnam (n = 618) were contacted to collect the data. Data were analysed through structural equations modelling procedure with invariance analysis conducted to ensure that the results from the three samples could be compared. The authors also conducted post-hoc analysis to explore the mediation paths between variables.

The study finds support to the conceptual model across the samples from the three countries. Personalisation is found to increase value perceptions – both utilitarian and hedonic – and personal identification which leads to “deep” eWOM providing behaviour across all the three countries. The serial mediation also provides comparable results across the three countries.

The study contributes to the understanding of deep eWOM providing behaviour – a construct with high practical relevance which has however not been explored sufficiently in current literature. The study also contributes to the literature that analyses the consequences of personalisation in m-commerce.