Browse Items (7684 total)
Sort by:
-
Wage Collapse and Gender Differences in Earning in India
The study found that the average daily wages almost increased three times between 1983 and 202122 in rural and urban areas of the country. The average wages rose more rapidly for women than men. We have observed that the wage growth of casual workers increased much faster over the years, reflecting less fluctuation than regular workers. However, at the same time, the growth rate of regular workers has collapsed several times, and in the recent period, the collapse was almost complete. From the analysis of Gini coefficient and decomposition, we observed that wage inequality has come down in India between 201112 and 202122, and much of the differences in earnings are explained by within-group factors. The Author(s), under exclusive licence to Indian Society of Labour Economics 2026. -
The intersection of law and wildlife management: A case study on culling of wild boars in Kerala
The inconvenient truth of wildlife co-existence lies in the circumstantial need of species to capitulate to each others will, but how far are we willing to go? Over the decades, the conservative view of eco-centric legislation has legally blanketed the scheduled species from the human acts of hunting, culling, assaulting, and the like. However, as the human population increases, this protected animal population, particularly those undomesticated ones in predator-less areas of the wild, increases exponentially beyond the land-carrying capacity of their habitats. Thus, the soundness of wildlife co-existence has been profoundly disrupted by wild boars (sus scrofa) through incessant encroachments, agricultural and economic damage, human fatalities, etc. Therefore, in light of the concurrent call for the declaration of vermin status of wild boars under the Wild Life (Protection) Act 1972, the paper aims to ascertain the legal and scientific efficacy of culling wild boars in comparison to the preventive strategies used over the years. This is achievable through a jurisprudential and scientific justification facilitated by the theories of anthropocentrism, eco-centrism, utilitarianism, and categorical imperativeness, alongside the capabilities approach. The research methodology entails a doctrinal approach wherein it contains participative observation, statistics, eco-legal analysis, numerical data, etc. Additionally, in the absence of current data on the wild boar population, an exploratory method has been employed in the study area to form a statistical estimation by speculating the reproductive pattern of wild boars. This evidence depicts the preponderance of understanding the interrelation of multiple disciplines by objectifying the currently understudied damage control methods. The Author(s), under exclusive licence to O.P. Jindal Global University (JGU) 2025. -
Hybrid Quantum Network with Snow Geese-Elk Herd Optimization for Smart Load Shedding in Grids with Electric Vehicles and Photovoltaic Systems
The increasing penetration of variable renewable energy and the growth of electric vehicles (EV) have created an urge for more sophisticated load management methods to ensure grid stability. Conventional load shedding (LS) methods are typically not equipped to manage the unpredictability brought about by these modern additions to the grid. This study introduces an innovative smart load-shedding strategy that uses a hybrid optimization model. At its core is a Quantum Neural Network (QNN), which enables intelligent and data-based load prioritization by evaluating factors such as load criticality, energy usage, responsiveness to demand, and operational flexibility. The required LS amount is calculated through a combined use of Snow Geese Optimization (SGO) and the Elk Herd Optimizer (EHO), with specific attention given to the flexibility offered by EVs to address the variability in photovoltaic (PV) power generation. Testing has been performed on the IEEE 33-bus network reveal a notable decrease in total load demand by around 33%, contributing to improved grid stability, with voltage levels staying close to 0.99 p.u. Additionally, the average load across the network buses dropped by roughly 52%. This hybrid approach not only ensures better performance but also achieves quicker convergence compared to existing optimization methods. The proposed intelligent LS method presents an effective strategy for preserving grid stability amid growing integration of renewables and EV by incorporating QNN with SGO and EHO while accounting for EV adaptability. The Author(s), under exclusive licence to Shiraz University 2025. -
Mathematical Modeling of Concrete Fracture Energy of Notched Specimens Using Experimental Evidence
The tensile stiffness of concrete is an important parameter for crack initiation. The microcrack initiation and propagation regulate the stressstrain behavior and the failure mode of concrete. Therefore, fundamental awareness of the fracture mechanism in terms of fracture energy is a requisite to comprehend concrete behavior. There is research consensus that fracture energy alone does not suffice to characterize the ductility/brittleness and also the size dependency of concrete. Therefore, it is necessary to evaluate the fracture energy and the characteristic length for a realistic assessment of the fracture behavior of concrete. Towards this objective, this study examined the fracture energy of concrete by experimentation, and the fracture energy proposed by various models in the literature. Further, the characteristic length proposed by Hillerborg which depicted both the material influence and the size effect, has been computed. Based on the RILEM50 FM recommendations, 18 specimens with varying grades of concrete and notch depths have been tested and the fracture energy parameters have been evaluated. Also, two regression models with key fracture parameters as variables for two-notch ratios, have been formulated for the concrete fracture energy. The arguments have been supported by experimental evidence. The Author(s), under exclusive licence to Shiraz University 2024. -
Brahma Nirupan of Kabir: A Search for Ultimate Reality
Kabir Das was a fifteenth-century Indian mystic. Saint Kabir's philosophical tenets were extremely simple. He was known as the guiding spirit of the Bhakti movement. According to Kabir, Braham Nirupan is the ultimate reality called Ni-Akshar, which is only possible through Sar Shabda. Charlotte Vaudeville stated in her book named Kabir that Kabir is a weaver, the best-known and the most revered name in Indian tradition(Vaudeville, 1993). By performing service with full loving devotion, one can achieve Sar Shabda and become a Hansa. The liberated soul is blessed and can enjoy the pleasurable experience of Sar Shabda. The iconoclastic Saint Kabir is a symbol of the syncretic culture of India. Kabir refused to say if he was a Hindu or a Muslim. In today's polarized culture, Kabir's vision and love are desperately needed. Caste and religious divisions have exacerbated the fault line in our society. This paper focuses on the concept of Brahma Nirupan and the philosophy of Kabir Das and how in this materialistic world one can seek the ultimate truth while being a part of this world yet not being attached to it. Indian Council of Philosophical Research 2025. -
Are Indians Willing to Pay for Air Quality? Findings from a Contingent Valuation Study
This paper aims to study individual preferences towards ambient air quality improvements in India, through the willingness to pay (WTP) measure. Contingent valuation method is employed to elicit individual WTP for air quality improvements via closed-end double bound questioning technique. Bivariate probit model is estimated based on the data coming from 539 in-person interviews to find key determinants of WTP. Estimation results suggest that place of residence, education, consciousness regarding air pollution, and household income are the key determinants of individual WTP for air quality improvements. Random probit model estimated based on the same data finds the presence of shifting and anchoring anomalies, leading towards bias in the mean WTP estimation from the Bivariate probit model. After correcting those anomalies, the estimated mean WTP is ?255.69 (or $3.09) per month. This is the first study estimating the bias-corrected WTP for air quality enhancements, covering a vast region of India. The Author(s), under exclusive licence to The Indian Econometric Society 2026. -
Role of Social Capital, Environment and Crime in Determining Life Satisfaction in India
Gross Domestic Product is a good indicator for examining the economic condition of any country, but it is an inappropriate indicator for evaluating an individual's well-being. This led to our research question: what determines people's life satisfaction or well-being in a diverse country like India? The present study examines the determinants of life satisfaction in India. To conduct this study, we analysed data from five waves of the World Values Survey spanning from 1990 to 2012, in conjunction with air and water pollution data sourced from various reports by the Central Pollution Control Board (CPCB). Specifically, the study examines the influence of Sulphur Dioxide (SO2) and Nitrogen Dioxide (NO2) as indicators of air pollution and Biochemical Oxygen Demand (BOD) as a measure of water pollution. The impact of the socio-economic variable is as expected, like the positive impact of education, health status, social class, and marital status on life satisfaction. However, one of the paper's main objectives is to examine the effect of social capital, Environmental pollution and incidence of crime on life satisfaction. It has been found that both formal and informal social capital positively affect people's life satisfaction in India. The results show that people who are trustable and sociable are more satisfied than those who are neither. Environmental pollution, such as NO2 and BOD, adversely affects people's satisfaction. The incidence of crime has a significant and negative impact on life satisfaction, particularly among individuals who report higher levels of satisfaction. The Author(s), under exclusive licence to The Indian Econometric Society 2025. -
A generic framework for forecasting lake surface area dynamics using level set segmentation and double exponential smoothing
Water has been a crucial element for the sustenance of civilization throughout history and civilizations have sprung up around a body of water in one form or another. It becomes imperative to address the pressing issue of water shortage and the shrinking size of urban water bodies, which is particularly relevant in Indian cities like Bangalore. The effective management and preservation of these invaluable resources depend on the development of accurate and automated tools to monitor them. The proposed framework introduces a novel approach, combining a level set-based segmentation algorithm with double exponential smoothing to monitor water bodies using multispectral satellite images. In-depth review of nine lakes within Bangalore was carried out using a Landsat time series data set spanning 1987 to 2020. The resulting forecasting model, employing a univariate smoothing methodology, showcased exceptional performance metrics. Notably, it yielded an average error of 0.072 and exhibited a robust correlation coefficient of 0.94 when cross-referenced with proven results. The proposed framework holds great potential for practical implementation in the domain of long-term water body analysis, effectively catering to the requirements of administrative and decision-making entities. Moreover, the adaptability of this framework for the incorporation of additional external factors, as well as its potential to analyze seasonal dynamics, offers exciting avenues for further exploration. The dataset of delineated lake images prepared in this study presents an opportunity for the advancement of image-to-image regression networks, enabling the prediction of both area and shape variations for lakes, thereby enhancing predictive accuracy and insights. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025. -
An integrated care model for elderly in home countries: the role of social work and legal services for transnational families
The need for integrated care for the elderly has grown globally due to ageing populations and the increasing prevalence of chronic health conditions. Many elderly individuals, particularly those in transnational families, face challenges in accessing adequate care and support, as their family members may be dispersed across different countries. This study addresses the role of social work and legal services in supporting elderly individuals in their home countries, focusing on transnational families. The integration of social work practices and legal frameworks is crucial in providing effective care for the elderly in these complex family dynamics. The research explores the challenges faced by elderly individuals and their families, emphasizing the importance of collaboration between social work professionals and legal experts. The study proposes an integrated care model that combines these services to enhance the well-being and rights of elderly individuals in home countries, offering insights into how this model can be applied in transnational family settings. The Author(s), under exclusive licence to Institute for Social and Economic Change 2026. -
Access to clean cooking fuel and discrimination between scheduled and non-scheduled groupsacross urban and rural India
Access to clean cooking fuel constitutes a fundamental element of household well-being and national energy security, particularly for marginalized and socio-economically disadvantaged communities. This paper examines the discrimination in access to clean cooking fuel between Scheduled Caste/Scheduled Tribe (SC/ST) and non-SC/ST households in India. Drawing on data from the National Sample Survey Office (NSSO) 78th Round (202021) Multiple Indicator Survey, the study seeks to quantify the extent of this discrimination and analyze the underlying factors contributing to disparities in clean fuel access. Empirical evidence suggests that non-SC/ST households have significantly greater access to clean cooking fuel than SC/ST households. This disparity is primarily explained by socio-economic variables such as income, education, gender, region, and employment status. However, the decomposition analysis reveals that a considerable portion, 22 percent, of the gap remains unexplained, indicating persistent discrimination that cannot be attributed solely to observable characteristics. The study recommends strengthening last-mile delivery of LPG in SC/ST-dominated areas and integrating energy access with housing programs like PMAY. It also advocates for targeted subsidies linked to caste and income data to support recurring fuel costs. Additionally, the paper emphasizes the need for infrastructure improvements, such as separate kitchens and durable housing, to enable sustained adoption of clean cooking fuels. The Author(s), under exclusive licence to Institute for Social and Economic Change 2025. -
DarcyForchheimerBrinkman flow of a Newtonian fluid through an enclosure with two straight boundaries and one curved boundary
The study examines the flow and heat transfer of a Newtonian fluid in a porous medium inside an enclosure with two straight boundaries and one curved boundary. This setup is important for heat storage and energy systems. The aim of this study is to solve the Brinkman-Forchheimer (BF) equation in an enclosure with two straight and one curved boundary. The research also looks to perform a thorough heat transfer analysis to improve the understanding of thermal behaviour in porous medium BF flow. Additionally, the study calculates the Nusselt number using a compatibility condition to ensure the results are physically consistent. Finally, it fits the Nusselt number as a function of the shape factor (s) and the Forchheimer number (F). This helps in capturing the trends in convective heat transfer behaviour within the medium.The main assumptions include a steady, fully developed flow in the z-direction with a constant axial pressure gradient -, and zero axial velocity (w = 0) on all boundaries. The domain in three-dimensions is defined in cartesian coordinates (x,y,z), with on the curved boundary,ensuring the spatial constraint of the geometry. The quasi-linearisation method is used to linearise the governing equations, resulting in a system of linear algebraic equations that is subsequently solved using the alternate direction implicit (ADI) method with an accuracy of. The findings show that an increase in the shape factor (s) results in a plug flow behaviour and better heat retention, as in higher temperature profiles and centreline velocities. In contrast, higher Forchheimer numbers causes a drop in both velocity and temperature due to increased flow resistance. But as F goes up, the Nusselt number always increases, meaning heat is better transferred through convection. The study also shows that hot spots and heat islands form inside the enclosure, especially when the shape factor is higher, because the heat builds up more quickly when there is less resistance, which is an essential thing to think about for things like heat storage systems, where it is crucial to have better thermal efficiency. The Author(s), under exclusive licence to Springer Nature India Private Limited 2025. -
Fractional operator-based mathematical model for hydrological cycle analysis with machine learning integration
The most important natural resource for maintaining ecosystems, life, and human civilization is water. Climate patterns, hydrological processes, and energy balance are all impacted by the constant movement of water across different parts of the Earths climate system. A new mathematical model is proposed using a fractional order, and this study investigates the four main elements of the hydrological cycle: atmospheric water, rainfall, surface water, and groundwater. The model uses the Caputo fractional operator to account for memory effects and long-term dependencies in water dynamics. A thorough qualitative and quantitative study examines the systems boundedness, stability, existence, and uniqueness. The AdamsBashforthMoulton (ABM) approach is used for numerical simulations, and it shows improved accuracy, stability, and reduced error metrics compared to traditional methods. Furthermore, bifurcation analysis reveals the systems possible behavior. Data-driven parameter estimation and trend forecasting are achieved by integrating Machine Learning (ML) techniques like the random forest regressor to improve predictive capabilities. Visualization tools such as pair plots, box plots, bar plots, and correlation matrix examines the associations between variables. The suggested method provides a strong framework for hydrological cycle modeling, increasing forecasting accuracy for water resource dynamics and climate-driven hydrological changes. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025. -
An Integrated Pythagorean Fuzzy Delphi-AHP Framework for Optimizing Foreign Direct Investment: Key Drivers for Success
Foreign Direct Investment (FDI) plays a pivotal role in global economic development, fostering cross-border collaborations and driving economic growth. Recognizing the significance of optimizing FDI drivers, this study employs a novel approach by integrating the Pythagorean Fuzzy Delphi (PFD) and Pythagorean Fuzzy Analytic Hierarchy Process (PFAHP). The Pythagorean Fuzzy Delphi methodology was used to identify and classify drivers into Technological, Political, Environmental, Social, and Cultural categories. Subsequently, the PFAHP was employed to rank these drivers. The top three prioritized drivers are: advocating for favorable foreign investment policies and trade agreements; implementing advanced cybersecurity measures to safeguard sensitive technology and data; and developing cutting-edge research and development facilities to foster innovation and attract technology-intensive investments. The study concludes by discussing how implementing these top-ranked drivers can significantly enhance FDI by creating a conducive environment for international investment, thereby contributing to economic prosperity and technological advancement. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025. -
Deep CP-CXR: A Deep Learning Model for Classification of Covid-19 and Pneumonia Disease Using Chest X-Ray Images
The global spread of the Coronavirus has caused a disastrous effect, affecting millions of people and making it crucial to take action. Numerous experts have worked extensively to create viable vaccines in the fight against this infectious disease. The current study offers hope by suggesting a deep learning model, Deep CP-CXR, for determining patients with Covid-19 and pneumonia. Our study encompasses two significant investigations. First, we used images from chest X-rays for binary classification to distinguish Covid-19-diagnosed patients from normal patients. Second, using chest X-ray images, we expanded the study to include several groups, such as pneumonia, Covid-19, and normal instances. The results of our studies were extremely promising. The binary classification achieved a remarkable average accuracy of 100%, allowing for accurate classification between Covid-19 patients and normal cases. In addition, the multiple-category classification was able to distinguish between Covid-19, pneumonia, and normal individuals with a remarkable average accuracy of 98.57%. These astounding findings lead us to conclude that the Deep CP-CXR method weve suggested for classifying Covid-19 and pneumonia patients enables medical professionals to perform it accurately. Healthcare providers worldwide will benefit significantly from this development since it has the potential to enhance both the detection and treatment of these ailments. The proposed deep learning approach improves the speed and precision in classifying the disease with which doctors can diagnose and treat their patients effectively. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025. -
Parent-Reported Severity of Autism and Parental Quality of Life: Mediating Role of Stress and Adjustment of Indian Parents
Parents of children with Autism Spectrum Disorder (ASD) often experience heightened emotional distress, difficulties in adjustment, and a compromised quality of life. While the severity of ASD symptoms has been consistently linked to these negative outcomes, the psychological mechanisms underlying these associations remain underexplored. The present study examines the mediating roles of parental stress and adjustment in the relationship between ASD severity and parental quality of life. A cross-sectional correlational study design was employed with 52 parents of children with ASD in Bengaluru, India. Participants completed standardised measures assessing ASD severity, parental stress, adjustment, and quality of life. Data was analysed using Pearsons correlations and mediation analysis with SmartPLS, and ethical approval was obtained prior to data collection. Findings indicate that greater parent-reportASD severity is associated with increased parental stress and adjustment difficulties, while higher stress and poorer adjustment are linked to lower QoL. Mediation analysis demonstrated that parental stress significantly mediated the relationship between ASD severity and QoL (? = ? 0.165, p =.035), whereas parental adjustment did not emerge as a significant mediator (? = ? 0.116, p =.165). The direct effect of parent-reportASD severity on QoL was non-significant (? = 0.108, p =.410). Additionally, parents reporting greater engagement in leisure activities showed higher QoL, highlighting the potential role of adaptive coping and self-care. These findings underscore parental stress as a key mechanism influencing parental well-being and suggest that interventions targeting stress management and leisure engagement may enhance QoL among parents of children with ASD. The Author(s), under exclusive licence to Springer Nature India Private Limited 2026. -
Narratives of Substance Users in Rehabilitation Centers: Exploring Usage, Identity, and Recovery
Addiction and Substance use are complicated issues that have a significant impact on a persons identity and social interactions. To gain a thorough understanding of identity construction and the recovery process, this study aimed to investigate the narratives of substance users in the rehabilitation center. Using a qualitative approach, semi-structured interviews were conducted with 11 participants selected through purposive sampling at a rehabilitation center in Delhi. The data was analyzed using Catherine Riessmans Narrative Analysis. Seven core narratives emerged: Substance as the Main Character, Substance as Air, Nostalgia over Lost Life, Confronting the Reality, Oscillating Recovery, Coexistence of Hope and Despair, and Push and Pull of Support. These narratives illustrate the multifaceted nature of addiction, where substances are not merely consumed but become central to identity, daily existence, and interpersonal relationships. The findings provide insights into the complexities of substance use and recovery by highlighting the constant oscillation between hope and despair in the recovery journey, as well as the ambivalent nature of family and society. The study concludes that substance use cannot be understood solely as a disorder. It often becomes intertwined with an individuals life and narrative. A holistic and humanized approach is necessary to address the personal, familial, and societal factors that influence addiction and recovery. The Author(s), under exclusive licence to Springer Nature India Private Limited 2025. -
Experimental Investigation and Predictive Modelling of Tribological Behaviour in Fly Ash Reinforced Polymer Composites Fabricated via Stereolithography
Tribological evaluation of fly ash-reinforced UV-curable resin composites produced through stereolithography additive manufacturing formed the central focus of this study. Controlled fly ash additions extending up to 2% by weight were examined, and all tests ran under dry sliding conditions. Neat resin was designated as the experimental reference throughout. Even with the modest addition of 0.5% fly ash, wear came down by roughly 9.8%, which was small but directionally significant. Moving to 1% fly ash pushed wear reduction to 16.4%. At 1.5%, the reduction advanced further to 21.3% with all evaluations performed under identical testing conditions. The 2% fly ash specimen produced the highest wear reduction of 25.8% among all compositions examined. Frictional behavior followed a comparable declining trend across filler levels. At 0.5% fly ash COF fell 7.6% below the neat resin value, and at 1% that reduction grew to 12.9%. The 1.5% addition brought friction reduction to 17.4%. Total COF reduction at 2% fly ash reached 20.3%, which confirmed a steady and consistent frictional improvement with progressive filler incorporation. Linear regression and artificial neural networks and XGBoost-based gradient boosting were the three predictive frameworks developed alongside experimental work. All three tracked closely with measured tribological outcomes. Prediction accuracies reached up to 95.4% with lower error values documented across every model. The 2% fly ash formulation stood out as the most effective composition tested. It delivered the strongest combined improvements in wear resistance and friction stability while remaining fully compatible with the operational demands of additive manufacturing. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2026. -
Polyvictimization among Children and Adolescents in India: A Scoping Review of Prevalence, Consequences, and Risk Factors
Polyvictimization, defined as the experience of multiple forms of victimization such as physical, emotional, and sexual abuse, neglect, bullying, and exposure to violence, is a significant but underexplored concern in India. This scoping review set out to map the existing literature on polyvictimization among children and adolescents, with a focus on prevalence, psychological and social consequences, and contextual risk factors. Studies published between 2000 and 2025 were included if they involved Indian participants aged 018 years and addressed more than one type of victimization. The framework given by Arksey and OMalley (2005) was adhered to for the review. Twenty-three studies were included in the review, highlighting that children were often subjected to overlapping victimizations rather than single instances, with emotional and physical abuse most common, alongside neglect, sexual abuse, and bullying. These experiences were consistently linked to depression, anxiety, PTSD, behavioral problems, and poor social functioning, with risks heightened by gender, poverty, family conflict, and institutional settings. Overall, the findings show that polyvictimization is prevalent yet seldom studied as a distinct concept in India, underscoring the need for nationally representative research, clearer definitions, and integrated child protection policies that address the cumulative impact of multiple victimizations. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2026. -
Transition to an Empty Nest: A Phenomenological Exploration of Homemaker Mothers of Out-of-State College Students
This phenomenological study explores the lived experiences of Indian homemaker mothers transitioning to an empty nest, focusing on middle-aged mothers emotional, psychological, and cultural dimensions. Five homemaker mothers, aged between 46 and 50, with at least one child attending an out-of-state college in Bengaluru, participated in semi-structured interviews. Data was analysed using Colaizzis descriptive phenomenological method, which revealed 95 minor themes organised into 9 major themes and 4 overarching categories. The findings highlight a complex emotional intersectionality where feelings of pride and joy in their childrens achievements coexisted with sadness, loneliness, and loss. Cultural expectations surrounding motherhood in India, which emphasises maternal self-sacrifice, further emphasised the emotional challenges the participants face. Coping strategies such as spirituality, social support, and technology emerged as key elements in navigating the transition, with participants often using prayer and digital communication to maintain emotional bonds with their children. The study also found that the empty nest transition triggered a redefinition of parental roles and personal identity. Participants with higher education levels were better equipped to embrace this phase as an opportunity for self-growth, while others struggled with their diminished caregiving role. Technology played a dual roleoffering emotional comfort through digital connection and fostering dependency and frustration. Overall, the empty nest experience for Indian homemaker mothers is emotionally challenging and a potential period of personal rediscovery, shaped by cultural norms and the evolving role of family dynamics. This research provides a culturally specific perspective on a largely Western-studied phenomenon, offering insights for further investigation into the changing maternal identity in India. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025. -
Minority Stress and Mental Health of Indian Non-binary Individuals
This study investigated how Indian non-binary individuals experience minority stress and its impact on mental health, with a focus on the role of social support and coping mechanisms. Semi-structured interviews with eight non-binary participants aged 1823 from Bengaluru revealed four main themes: societal treatment, self-identity, minority stress and mental health, and social support. Findings indicate that experiences with discrimination, misgendering, gender dysphoria, and identity concealment contribute to negative mental health outcomes. However, social support and effective coping strategies were found to positively influence mental health by affirming identity. These results suggest potential avenues for developing targeted interventions and support systems to improve mental health among non-binary individuals. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.