Folk Music Therapy in Community-Based Mental Health Education for the Elderly: An Educational Intervention Study Based on Empirical Evidence from Chongqing

Net Journals. 25 Akintola Road, Sapele, Delta State, 331107, Nigeria. e-mail: service@netjournals.org; Web site: https://www.netjournals.org/aer_index.html

Y

8

Folk Culture; Music Therapy; Well Being; Mental Health; Older Adults; Nursing Homes; Depression (Psychology); Anxiety; Cultural Influences; Emotional Response; Foreign Countries; Psychological Patterns

UCLA Loneliness Scale; Zung Self Rating Depression Scale

2354-2160

This study explores the effectiveness of folk music therapy as an educational intervention to promote psychological well-being among elderly residents in a community nursing home in Chongqing, China. Guided by a pre--post experimental design, the study recruited ten older adults who reported symptoms of depression and anxiety, along with ten cultural and clinical informants who provided contextual perspectives. Participants engaged in structured listening sessions featuring classical Guqin compositions, accompanied by reflective dialogues designed to enhance cultural identity, emotional regulation, and social connectedness. Quantitative analysis revealed significant reductions in depression (t = 3.21, p < 0.01) and anxiety (t = 2.94, p < 0.05), with moderate decreases in loneliness. Qualitative findings further indicated that participants internalized therapeutic strategies as educational resources, reporting enhanced self-awareness, resilience, and cultural belonging. These results suggest that folk music therapy, when situated within a community education framework, can serve both therapeutic and pedagogical functions, bridging mental health support with cultural transmission. The study highlights the value of integrating traditional music into gerontological education to foster active aging and proposes future research directions for expanding sample diversity, testing longitudinal effects, and innovating intergenerational and digital models.

As Provided

2026

EJ1492710