Browse Items (16481 total)
Sort by:
-
Dispositional Mindfulness and Perceived Stress in Psychiatric and Nonpsychiatric Physicians: A Facet-level Pilot Study
OBJECTIVES: Perceived stress is a significant concern among health care professionals, with potential consequences for mental health and clinical performance. This study examined associations between dispositional mindfulness and perceived stress among Indian physicians working in psychiatric and nonpsychiatric specializations within hierarchical systems with limited institutional support. METHODS: In this cross-sectional pilot study, 62 clinicians (39 nonpsychiatric and 23 psychiatric physicians) completed the Perceived Stress Scale and the Five Facet Mindfulness Questionnaire-Short Form. Independent samples t tests compared perceived stress and mindfulness scores between the groups. Correlations and linear regression analyses were conducted to examine relationships between mindfulness and perceived stress. RESULTS: No statistically significant differences were found between psychiatric and nonpsychiatric physicians in perceived stress, t(59)=0.98, P=0.329, d=0.27, or total mindfulness, t(59)=-1.31, P=0.186, d=0.35. Across the sample, higher dispositional mindfulness was strongly associated with lower perceived stress, r(60)=-0.65, P<0.001, r=0.43, particularly for the Describe and Acting with Awareness facets. Linear regression indicated that mindfulness was significantly related to perceived stress, ?=-0.65, t=-6.66, P<0.001, accounting for 42.5% of the variance. CONCLUSIONS: These findings cautiously suggest that dispositional mindfulness may serve as a potential psychological resource for stress regulation and burnout prevention among clinicians. Further research is warranted to validate these associations in larger and more diverse samples and to explore practical applications within wellness initiatives. Copyright 2026 Wolters Kluwer Health, Inc. All rights reserved. -
Telehealth-Delivered Mindfulness-Based Exposure and Response Prevention for Sexual Obsessive-Compulsive Disorder with Comorbid Depression: Feasibility and Clinical Outcomes
Sexual Obsessive-Compulsive Disorder (S-OCD), when comorbid with Major Depressive Disorder (MDD), presents significant treatment challenges due to heightened distress, avoidance behaviors, and cognitive inflexibility. While Exposure and Response Prevention (EX/RP) remains the gold standard for OCD, its efficacy in S-OCD cases complicated by MDD is less established. This case-series study examines the feasibility and effectiveness of Telehealth-delivered Mindfulness-Based Exposure and Response Prevention (Telehealth-delivered MB-EX/RP) in treating individuals with S-OCD and comorbid MDD. Five participants underwent 17 bi-weekly therapy sessions delivered via a digital platform. Standardized assessments of OCD severity, depressive symptoms, obsessive beliefs, mindfulness, and mental well-being were conducted at pre-treatment, post-treatment, and a four-month follow-up. Results demonstrated significant reductions in S-OCD and depressive symptoms, along with sustained improvements in mindfulness and well-being. The digital format facilitated accessibility and engagement, suggesting that Telehealth-delivered MB-EX/RP is a viable intervention for individuals with S-OCD and comorbid MDD. Findings highlight the potential of mindfulness-enhanced digital interventions in addressing complex OCD presentations, warranting further investigation in larger clinical trials. The Author(s) 2025 -
Toward a Kashmiri Cultural Psychology: Integrating Indigenous Knowledge and Mental Health
This paper presents a critical theoretical intervention addressing epistemic imbalance in mental health research and practice related to Kashmir. It (a) develops conceptual frameworks elucidating indigenous healing rooted in Sufi mysticism, communal networks, and culturally specific coping strategies; (b) identifies and theorizes culturally derived constructs essential for contextually appropriate mental health infrastructures and interventions, emphasizing epistemic justice and locally situated knowledge; and (c) demonstrates culturally grounded interventions that foreground indigenous epistemologies on their own terms, addressing the limitations and potential dominance of Western clinical models. By centering Kashmiriyat, the Valleys indigenous cultural ethos that encompasses communal solidarity, shrine-centered spiritual practices, and historically rooted coping strategies guiding everyday communal and spiritual life, this work reconceptualizes resilience as collective and historically situated. The proposed framework enriches global psychological theory and offers innovative models of culturally congruent and socially transformative interventions for conflict-affected societies. 2026, PsychOpen. All rights reserved. -
Reclaiming the Ethical Foundations of Mindfulness: Toward a Dharma-Guided Clinical Paradigm
Mindfulness-based interventions (MBIs) have gained clinical prominence yet often omit the ethical and ontological dimensions central to Buddhist traditions. Building on the public health analysis by Oman (2025) of mindfulness along 14 axes (A1A14), which finds alignment on prevention, stress/mental health, resilience, and multisectoral collaboration but identifies gaps in epidemiologic foundations, multilevel intervention design, cultural/religious adaptation, equity, and attention to the collective attentional environment, we propose a Dharma-guided model that directly addresses these implementation challenges (A6A13). Specifically, we outline: (a) culturally responsive adaptations that preserve ethical integrity; (b) multilevel delivery (individual, group, institution, and community) through stepped-care and community-owned pathways; (c) clinician competencies in intercultural/interreligious literacy; (d) metrics and study designs that build the missing epidemiologic base; and (e) interventions responsive to societys attentional environment. This public health-oriented translation repositions MBIs as vehicles for existential insight, moral development, and culturally grounded healing with population-level relevance, complementing the agenda of Oman (2025) and advancing an implementation-ready framework for diverse settings. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025. -
Mindfulness in treatment-seeking adults with comorbid obsessive-compulsive and major depressive disorders: Mediating effects of obsessive beliefs and mental well-being
Background: Mindfulness-based interventions have shown promise in alleviating symptoms associated with obsessive?compulsive disorder (OCD) and major depressive disorder (MDD). However, the specific mechanisms that drive these effects, mainly through obsessive beliefs and mental well?being, are seldom examined. Aim: To explore the mechanisms by which mindfulness influences symptom severity in adults with comorbid OCD and MDD, focusing on the mediating roles of obsessive beliefs and mental well-being. Methods: Primary data from 60 treatment-seeking adults with comorbid OCD and MDD were analyzed. Ordinary least-squares path analysis was employed to examine the mediating roles of obsessive beliefs and mental well-being in the relationship between mindfulness and the severity of OCD and MDD symptoms. Results: Mindfulness was significantly associated with reduced symptom severity for both OCD (? = ? 0.40, P < 0.001) and MDD (? = ? 0.49, P < 0.001). For MDD, obsessive beliefs (? = ? 0.20, P < 0.001) and mental well?being (? = ? 0.33, P < 0.001) significantly mediated the relationship. In contrast, no significant indirect effects were observed for OCD symptoms through obsessive beliefs (? = ? 0.10, P = 0.16) or mental well?being (? = ? 0.08, P = 0.20). Conclusion: These findings highlight the distinct mechanisms of mindfulness in comorbid OCD and MDD, underscoring the importance of customized interventions based on specific pathways. 2025 Indian Journal of Psychiatry. -
Mindlessness by design: how digital platforms shape the psychological, behavioral and civic experiences of Generation Z
Purpose This paper aims to examine how digital platform architectures shape the psychological, behavioral and civic experiences of Generation Z. It challenges deficit-based views of mindlessness, situating distraction, procrastination and diminished attention within the structural logics of the attention economy rather than individual failure. Design/methodology/approach This commentary synthesizes illustrative and representative evidence from psychological, cognitive, sociological and policy literatures across Indian and global contexts to advance a conceptual account of platform-induced mindlessness as a socio-technical phenomenon, rather than undertaking a systematic or exhaustive review. Findings Excessive smartphone use, algorithmic personalization and media multitasking erode attentional control, academic performance and emotional resilience while weakening face-to-face interaction and civic participation. These patterns reflect engagement-maximization strategies embedded in digital infrastructures and mark a shift from situational distraction to structurally conditioned cognition. Originality/value By reframing mindlessness as a systemic rather than moral issue, this paper advances the concept of structural accountability in digital life. It calls for reforms in platform governance, digital literacy and public policy to promote psychological well-being and civic inclusion through collective and interdisciplinary responsibility. 2026 Emerald Publishing Limited -
Security Threats and Privacy Issues in Cloud Data
The quick advancement of Web-based applications has led to a huge amount of information being scanned and gathered for business examination or scholarly research purposes, which may disregard individual protection. Organizations, industries and individuals data are at stake. In this paper, utilizing on the Web Personal Health Record (PHR) as contextual analysis, first demonstrate the need of inquiry ability approval that lessens the security introduction coming about because of the list items, and build up a versatile structure for authorized private keyword Search (APKS) over encoded cloud information. This particular model proposes two novel answers for APKS given on-going cryptographic crude, hierarchical predicate encryption (HPE). Our answers empower efficient multi-dimensional watchword looks with a run question, permit assignment and renouncement of hunt abilities. Additionally, the proposed system improves the question protection which conceals clients inquiry watchwords against the server. Actualize our plan on an advanced workstation, and exploratory outcomes exhibit its appropriateness for reasonable use. Privacy has seen advancement lately as information mining of the datasets in a dispersed huge information condition has turned into a successful worldwide business which is none other than data management or data analytics which ensures the security of data. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
AI applications at the scheduling and resource allocation schemes in web medium
Resources including business, informational, personal, and financial resources are required, with support from users, to maintain and implement the resource representations. Resource provisioning seeks to meet user needs by supplying the appropriate resources at the appropriate time at a lower cost. A service provider oversees supplying resources to all applications, and among the methods of resource management that they can employ are time-based, cost-based, on-demand, and bargain-based. These general approaches to resource provisioning and scheduling are based on recent developments in heterogeneity in 6G networks, including cloud computing, fog computing, and autonomic computing, to allocate and schedule resources while keeping an eye on service performance and adjusting as needed to meet the needs of cloud users. The proposed work increases resource allocation through cost reduction and, as a result, increases the availability of the services at the device levels without compromising performance parameters such as availability, efficiency, authentication, and authorization. The wide metropolitan area network (6G Networks) wireless heterogeneity is presented in this chapter's technological problems. Memory, network performance, and other factors were heterogeneous in fog nodes. Here, the Load balancing algorithm's Priority ordering is applied to make use of wireless model properties. This chapter focuses on various load balancing and scheduling strategies along with a few machine learning techniques applied to fog nodes and clustering techniques. 2024 selection and editorial matter, Dr. Abraham George and G. Ramana Murthy; individual chapters, the contributors. -
TumorInsight: GAN-Augmented Deep Learning for Precise Brain Tumor Detection
In addition to the shortage in data as well as the low quality of MRI images, one of the most difficult tasks in contemporary medical imaging is the diagnosis of tumors in brain. This work presents a new approach to enhance diagnostic accuracy using sophisticated preprocessing techniques. Combining BRATS 2023 and Cheng et al. datasets to apply cutting-edge deep learning preprocessing methods with Generative Adversarial Networks (GANs), specifically DCGAN, Contrast Limited Adaptive Histogram Equalization (CLAHE), and gamma correction, it aims to significantly improve the quality of MRI images. As a result, updated data should be generated with greater precision and detail, making it possible to identify tumor-affected areas with greater accuracy. Thorough assessment, demonstrated by metrics such as Accuracy (0.98), Specificity (0.99), Sensitivity (0.99), AUC (0.65), Dice Coefficient (0.67), and Precision (0.71), highlights possible advancements in brain tumor identification and treatment, thereby highlighting the effectiveness of the suggested approach. 2024 IEEE. -
Empirical Assessment of Artificial Intelligence Enablers Strengthening Business Intelligence in the Indian Banking Industry: ISM and MICMAC Modelling Approach
Considering the context of the issue based on literature survey and expert opinion, this study investigates the drivers of Artificial Intelligence (AI) implementation, which further strengthens the Business Intelligence (BI) in taking better decision-making industries in India. For the purpose of serving the objective of examining the enablers towards having a smarter AI ecosystem in banking, the relevance of identified enablers from exhaustive literature survey were discussed with the experts from banking sector and AI professionals. Based on their opinion, 15 final enablers were defined based on the data collected have been put through Interpretive Structural Modelling (ISM) that reveals the binary relationship between the enablers to draw a hierarchical conclusion, and then assess the enablers about their independence, linkage, autonomous character, and dependence based on their calculated driving and dependence power through MICMAC analysis. The ISM and MICMAC integrated approaches have been used to establish interdependence among the enablers of AI in banking in India context. The study reveals that strong algorithms result in building quality AI information, and also the efforts from management related to commitment, financial readiness towards technological advancement, training, and skill development are quite essential in making the baking system smarter and would enable the industry to take better management decision. 2023 selection and editorial matter, Deepmala Singh, Anurag Singh, Amizan Omar & S.B Goyal. -
Spectroscopic Studies on Structurally Modified Anthraquinone Azo Hydrazone Tautomer: Theoretical and Experimental Approach
A series of unique four mono-azo substituted anthraquinone analogue were synthesized by using the anthraquinone components in the diazo-coupling technique. The FT-IR, 1H NMR, and HRMS, data were used to confirm the structure of the molecules, and spectroscopic techniques like UV-Vis, and photoluminescence spectroscopy were employed to estimate the photophysical properties of the molecules. The molecular optimized geometry and frontier molecular orbitals were estimated using density functional theory. Further, global chemical reactivity descriptors parameter was theoretically estimated using the value of the highest occupied molecular orbit and lowest unoccupied molecular orbits. The anti-tubercular action of the synthesised dyes were also examined. The results of this biological activity showed that N-isopropyl aniline combined with anthraquinone N-isopropyl aniline had superior anti-tubercular activity when compared to Rifampicin as the standard. As per molecular docking studies, the synthesized compound Q1 showed excellent binding energy (-10.0kcal/mol) among all compounds against the 3ZXR Protein. These results agreed with our in-vitro anti-TB activity results. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Photophysical and antitubercular studies on newly synthesised structurally architectured sulphonamide
This study presents the synthesis and characterisation of four mono-azo sulphonamide derivatives through diazo-coupling electrophilic substitution reactions. The structural analysis of the synthesised molecules was conducted utilising FT-IR, 1H-NMR and HR-MS techniques. Absorption and fluorescence maxima of the synthesised molecules were determined across solvents of varying polarity to explore Solvatochromic behaviour. Density functional theory was employed to elucidate electronic and optical properties, including the computation of HOMOLUMO energies using Gaussian 09W software, with comparisons to experimental data. Molecular electrostatic potential 3D plots identified electrophilic and nucleophilic sites. Solvent interactions were evaluated using KamletAbboud Taft and Catalan parameters. Further, global chemical reactivity descriptors were estimated to ascertain chemical reactivity of the molecules. Additionally, the effectiveness of the colourant anti-tubercular activity was evaluated using in vitro and molecular docking techniques. The biological activity results reveal that methyl-pyridone and barbituric acid coupled with sulphamethizole (SMP and SMB) displayed excellent anti-tubercular activity compared with the standard Gentamycin. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Synthesis, Computational, and Photophysical Probing Studies on Mono-Azo Sulfonamides, and Their Antibacterial Activity
Abstract: Objective: Novel azo-linked substituted sulfonamides were synthesized via diazo coupling with the molecular formula (C9H10N4O2S2, C11H11N3O2S) and characterized by FT-IR, UV-vis, HR-MS, and 1H NMR spectroscopy techniques. The photophysical studies were carried out using experimental techniques. Absorption and fluorescence maxima of all the synthesized molecules were determined by using different solvents. Our synthesized mono-azo derivatives are interested in identifying the cellular target site for sulfonamides (F1-F2) and (P1-P2). The newly synthesized compounds were examined for their in vitro antibacterial activity against Staphylococcus aureus and Escherichia coli strains. Methods: In this study, we focused on the sulfonamide architecture. Antibacterial activity of compound (F1), (F2), (P1), and (P2) derivatives was studied by measuring the diameter of the inhibition zone, using the Disc-agar diffusion method. Results and Discussion: Density functional theory was used to demonstrate the electronic and optical properties of the synthesized molecules. In the correlation between the HOMOLUMO energy gap, the derivative (F1) shows a higher (3.9866 eV) and (F2) shows a lower (3.2063 eV) excitation energy. The synthesized compound (F1) looks into antibacterial activity, exhibited more zone inhibition 25 mm in the concentration 75 L/mL in gram-negative bacteria when compared with the common antibiotic Ciprofloxacin. Additionally, the results emerged from the in silico molecular docking studies the compound (F2) showed highest binding energy against cyclin-dependent kinase (?Gb = 9.8 kcal/mol). Conclusions: The synthesized four mono-azo sulfonamide derivatives (F1), (F2), (P1), and (P2) are reported in photophysical, CDFT, antibacterial, and molecular docking studies with relevant results. Pleiades Publishing, Ltd. 2024. -
Spectroscopic Studies on Structurally Modified Anthraquinone Azo Hydrazone Tautomer: Theoretical and Experimental Approach
A series of unique four mono-azo substituted anthraquinone analogue were synthesized by using the anthraquinone components in the diazo-coupling technique. The FT-IR, 1H NMR, and HRMS, data were used to confirm the structure of the molecules, and spectroscopic techniques like UV-Vis, and photoluminescence spectroscopy were employed to estimate the photophysical properties of the molecules. The molecular optimized geometry and frontier molecular orbitals were estimated using density functional theory. Further, global chemical reactivity descriptors parameter was theoretically estimated using the value of the highest occupied molecular orbit and lowest unoccupied molecular orbits. The anti-tubercular action of the synthesised dyes were also examined. The results of this biological activity showed that N-isopropyl aniline combined with anthraquinone N-isopropyl aniline had superior anti-tubercular activity when compared to Rifampicin as the standard. As per molecular docking studies, the synthesized compound Q1 showed excellent binding energy (-10.0kcal/mol) among all compounds against the 3ZXR Protein. These results agreed with our in-vitro anti-TB activity results. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. -
Photophysical and antitubercular studies on newly synthesised structurally architectured sulphonamide
This study presents the synthesis and characterisation of four mono-azo sulphonamide derivatives through diazo-coupling electrophilic substitution reactions. The structural analysis of the synthesised molecules was conducted utilising FT-IR, 1H-NMR and HR-MS techniques. Absorption and fluorescence maxima of the synthesised molecules were determined across solvents of varying polarity to explore Solvatochromic behaviour. Density functional theory was employed to elucidate electronic and optical properties, including the computation of HOMOLUMO energies using Gaussian 09W software, with comparisons to experimental data. Molecular electrostatic potential 3D plots identified electrophilic and nucleophilic sites. Solvent interactions were evaluated using KamletAbboud Taft and Catalan parameters. Further, global chemical reactivity descriptors were estimated to ascertain chemical reactivity of the molecules. Additionally, the effectiveness of the colourant anti-tubercular activity was evaluated using in vitro and molecular docking techniques. The biological activity results reveal that methyl-pyridone and barbituric acid coupled with sulphamethizole (SMP and SMB) displayed excellent anti-tubercular activity compared with the standard Gentamycin. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Memetic Spider Monkey Optimization for Spam Review Detection Problem
Spider monkey optimization (SMO) algorithm imitates the spider monkey's fission-fusion social behavior. It is evident through literature that the SMO is a competitive swarm-based algorithm that is used to solve difficult real-life problems. The SMO's search process is a little bit biased by the random component that drives it with high explorative searching steps. A hybridized SMO with a memetic search to improve the local search ability of SMO is proposed here. The newly developed strategy is titled Memetic SMO (MeSMO). Further, the proposed MeSMO-based clustering approach is applied to solve a big data problem, namely, the spam review detection problem. A customer usually makes decisions to purchase something or make an image of someone based on online reviews. Therefore, there is a good chance that the individuals or companies may write spam reviews to upgrade or degrade the stature or value of a trader/product/company. Therefore, an efficient spam detection algorithm, MeSMO, is proposed and tested over four complex spam datasets. The reported results of MeSMO are compared with the outcomes obtained from the six state-of-art strategies. A comparative analysis of the results proved that MeSMO is a good technique to solve the spam review detection problem and improved precision by 3.68%. 2023 Mary Ann Liebert, Inc., publishers. -
BSSA: Binary Salp Swarm Algorithm with Hybrid Data Transformation for Feature Selection
Feature selection is a technique commonly used in Data Mining and Machine Learning. Traditional feature selection methods, when applied to large datasets, generate a large number of feature subsets. Selecting optimal features within this high dimensional data space is time-consuming and negatively affects the system's performance. This paper proposes a new binary Salp Swarm Algorithm (bSSA) for selecting the best feature set from transformed datasets. The proposed feature selection method first transforms the original data-set using Principal Component Analysis (PCA) and fast Independent Component Analysis (fastICA) based hybrid data transformation methods; next, a binary Salp Swarm optimizer is used for finding the best features. The proposed feature selection approach improves accuracy and eliminates the selection of irrelevant features. We validate our technique on fifteen different benchmark data sets. We conduct an extensive study to measure the performance and feature selection accuracy of the proposed technique. The proposed bSSA is compared to Binary Genetic Algorithm (bGA), Binary Binomial Cuckoo Search (bBCS), Binary Grey Wolf Optimizer (bGWO), Binary Competitive Swarm Optimizer (bCSO), and Binary Crow Search Algorithm (bCSA). The proposed method attains a mean accuracy of 95.26% with 7.78% features on PCA-fastICA transformed datasets. The results show that bSSA outperforms the existing methods for the majority of the performance measures. 2013 IEEE. -
Internet addiction and the role of AI in online compulsive buying behaviour
The internet's availability profoundly impacted many aspects of modern life, including business and communication. One of its most notable effects is the development of internet addiction, which has drawn much attention because of its behavioural and psychological ramifications. This addiction can have detrimental effects on one's social, professional, and personal life. It frequently presents as excessive and uncontrollable using the internet. One important area where obsessive online shopping behaviour is one where internet addiction is becoming more evident. This chapter explores the relationship between obsessive online shopping and internet addiction, emphasizing how artificial intelligence is transforming consumer decision-making. This chapter aims to investigate how compulsive purchase behaviour can be made worse by internet addiction and the degree to which AI-driven algorithms play a role in this phenomenon. Several mitigation measures can be used to alleviate the negative effects of obsessive buying behaviour led by AI. 2025, IGI Global Scientific Publishing. All rights reserved. -
Effectiveness of Systematic Group Counselling in Enhancing Academic Performance, Emotional Intelligence and Moral Values of College Students with Unsatisfactory Academic Performance
International Journal of Multidisciplinary Sciences and Research, Vol-1 (1), pp. 86-91. ISSN-2321-4872