Background: Malnutrition among expectant mothers in underdeveloped areas is abundant and a serious public health concern. This study examines how maternal empowerment affects nutritional outcomes among under-five children in developing Asian nations. Objective: With an emphasis on nutritional outcomes, including stunting, wasting, and underweight, the main objective of this study is to investigate the connection between mother empowerment and child malnutrition and explore how better child health in developing Asian nations can be achieved through empowering mothers. Methods: Using Demographic and Health Survey (DHS) data of ten emerging Asian countries from three regions of Asia, this study evaluates maternal empowerment using the composite maternal empowerment index (CMEI) and examines how it relates to children’s nutritional health. For the assessment of the significance of the association between maternal empowerment and child health outcomes, statistical analysis was conducted. Results: Our results indicated that maternal empowerment and child health have a statistically significant relationship, especially regarding a reduction in the prevalence of stunting, wasting, and underweight conditions in children. At the same time, maternal education showed a significant role in reducing malnutrition in children in all three regions of Asia. Conclusion: In conclusion, developing Asian nations require empowering women. Also, it is essential to initiate nutrition programs, extension education, and synergistic working models that are especially suited to rural women. By strengthening mothers’ roles in promoting their children’s health, these initiatives can help solve the widespread problem of child malnutrition.

Purpose: This study aimed to identify and assess artificial intelligence (AI)-based mental health interventions based on multiple criteria, including effectiveness and accuracy, accessibility and usability, ethical and privacy concerns, psychological and human factors and integration with traditional healthcare. Design/methodology/approach: Primary data were collected from mental health professionals, AI and healthcare researchers, patients/users, healthcare administrators and AI developers in Punjab, Pakistan. The Dynamic Grey Relational Analysis (DGRA) was used for ranking the interventions. Additionally, the Kruskal–Wallis test (KWT) was conducted to examine the significance of demographic variables such as gender, age, education, marital status and participant category. For comparative analyses the TOPSIS and the Analytical Ordinal Priority Approach (AOPA) models were used. Findings: The results indicated that therapeutic effectiveness was the most significant factor. The KWT results showed no significant differences among demographic groups, suggesting that therapeutic effectiveness is consistently the most critical AI-based mental health intervention across different participant categories. Originality/value: This study is the first of its kind to apply the multi-model framework to analyze AI-based mental health interventions. The findings provide valuable insights for policymakers, healthcare practitioners and AI developers to enhance the effectiveness and integration of AI-driven mental health solutions.

Healthcare provider's distributional shortages, especially in developing countries, result in a slowdown in progress towards better healthcare outcomes

Background: Suicide and self-injury are serious public health concerns, especially in young populations, owing to multiple social, cultural, and gender determinants. Qualitative evidence exploring narratives regarding the factors behind suicide among young women is rare in Pakistan. Objective: The present study aims to explore the complex dimensions of suicide or self-injury among young women of Southern Punjab. Methods: Semi-structured interviews were conducted in a marginalized district in South Punjab, with participants consenting to in-person meetings at their homes or phone interviews. We collected detailed accounts of fifteen deceased girls or self-harm survivors, with insights provided by close relatives of the victims. Results: Our findings identified several conducive factors to suicidality, including receiving insults in front of others, low self-esteem, household pressures, work burdens, unfulfilled romantic desires, feelings of worthlessness, cheating in love, marriage without choice, and engagement in risky behaviors. These causes could be categorized into personal (such as an inferiority complex), social (a lack of family support and frequent conflicts), and cultural factors (forced marriages). Conclusions: Our study advocates for empowering women through education and restricting access to suicide means, such as pesticides or Paraphenylenediamine (PPD). Moreover, the government should take strict measures to discourage the forced marriage of young females in rural contexts. This study highlights the importance of integrating suicide prevention initiatives with research efforts within Pakistan’s healthcare system.