With the current rapid increase in digital technology adoption, understanding the relationship between technological proficiency and self-esteem is crucial to older adults. This study explores the mechanisms through which technological proficiency influences self-esteem, particularly considering its associations with technological engagement, self-efficacy, social participation, and autonomy. By using a narrative review approach, this study synthesizes recent findings from gerontology and psychology to examine these relationships. The analysis shows that higher technological proficiency enhances self-esteem by boosting self-efficacy, fostering social participation, and promoting greater autonomy. Older adults who are skilled in using digital tools exhibit greater confidence in managing daily activities and maintaining their social networks, contributing to their psychological resilience. Conversely, lower technological proficiency is linked to frustration, social exclusion, and diminished self-esteem, exacerbated by the digital divide. However, despite these insights, much remains unexplored; for example, no longitudinal study has been conducted to capture the dynamic relations between technological proficiency and self-esteem. These findings suggest that further research is needed to learn more about how technological proficiency influences self-esteem and recommend clinical ways of supporting older adults in their current stage.

HRMARS is well established journal publisher based in Pakistan. It is publishing prominent journals in social sciences since 2011.

Background: Male nurses form a minority group in many healthcare institutions and can face gender-based stereotypes, patient refusal, gender role assignment, marginalization in the workplace, and questioning of their suitability for working in caring professions. This scoping review examines the literature on gender discrimination, psychological well-being, and adaptation in professional contexts among male nurses and male nursing students. Methods: This scoping review was performed according to the PRISMA-ScR guidelines. Searches were performed in Scopus and Web of Science databases and complemented with the use of pre-designed Google Scholar keyword searches. Included studies had a focus on male nurses, men in nursing, or male nursing students and were concerned with gender discrimination, stereotypes, discrimination, psychological well-being, emotional labor, professional identity, burnout, job satisfaction, adaptation, education, organizational support, or retention. Data were extracted and analyzed using narrative and thematic approaches. Results: Forty included studies were identified. Four major themes were revealed: (1) gender discrimination and stereotyping; (2) psychological and professional effects; (3) coping strategies and professional adaptation; and (4) organizational responses and support mechanisms. The included studies reported patient refusal, discomfort in intimate care, gendered role assignment, workplace marginalization, and masculinity-related stereotypes. These experiences were discussed in relation to emotional labor, identity conflict, reduced sense of belonging, burnout, job dissatisfaction, work engagement, and turnover intention. Conclusions: Gender discrimination against male nurses should be understood as both an interpersonal and organizational issue.

Background/Objectives: Large language models (LLMs) may support healthcare workforce allocation, but their decisions can be sensitive to demographic cues and decision architecture. This study examined gender–task congruity, Candidate-A dependence under the tested decision architecture, and patient-gender-conditioned nursing allocation. Methods: Three provider-specific LLM configurations were audited across 24 nursing tasks. Male and female nurses were professionally equivalent and counterbalanced across Candidate A/B; patient gender was varied in six intimate-care tasks. Sixty conditions were repeated three times per model, yielding 540 valid outputs. Results: Male nurses were selected in 50.0% of Technical/Procedural and Relational/Educational allocations. Candidate A was selected in all 288 observations, although 285 (99.0%) assigned identical suitability scores. Because A/B assignment was bundled with labeling, presentation order, evaluation order, and response-template anchoring, this pattern indicates Candidate-A dependence under the tested decision architecture rather than an isolated position effect. Changing patient gender from female to male produced 57 female-to-male nurse switches and no reverse switches (p < 0.001). Conclusions: The audited configurations showed no generalized gender–task pattern but demonstrated decision-architecture dependence and patient-gender-conditioned allocation. Fairness audits should assess equivalent-candidate handling, patient preference, and counterfactual stability.

HRMARS is well established journal publisher based in Pakistan. It is publishing prominent journals in social sciences since 2011.