THE EFFECTIVENESS OF THE COMBINATION OF NATURAL AND MUROTTAL MUSIC IN PREVENTING DEPRESSION IN THE ELDERLY

Rahayu Sumaningsih

Abstract


The elderly are an elderly group who are prone to depression, due to their lack of ability to adapt to changes in themselves due to physical, mental and social setbacks. This study explains the effect of a combination of natural and murotal music on preventing depression in the elderly. The study used a quasi-experimental design with a pretest-posttest design with the intervention and control groups, the intervention group was given a combination of natural and murotal music therapy for 30 minutes and lasted for 3 consecutive days the instrument used the Geriantri Depression Scale (GDS), Finding the mean before and after after intervention then compared with control with t test statistic. The most age characters based on age 60 to 69 years (52.5 %), the results of the Intervention group's Depression Level of Mean Pre and Post there was a decrease of 13.4. value v (value) p = 0.000 <0.05. While the control group there is a decrease in the value of v (value) p = 0.002 <0.05. At the level of depression based on stage at pre normal 0, mild depression 5, moderate depression 12, major depression 3. Post intervention became normal 4, mild depression 13, moderate depression 2 and severe depression 1. While the control group was normal 0, mild depression 2, moderate depression 15, major depression 3 to normal 1, mild depression 8, moderate depression 9 and severe depression 2. Classical and Murotal music combinations were more effective in reducing depression levels in the elderly pre-intervention compared to post-intervention. In the control group there was a decrease in depression levels, although it was not significant . There was a two-level lower reduction in depression rates in the intervention group compared to the control group.

 

 

Keywords: Natural music, Murotal, Old Age

Keywords


old age depression

References


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Copyright (c) 2023 Rahayu Sumaningsih

"HEALTH NOTIONS" ISSN: 2580-4936 (online version only), published by Humanistic Network for Science and Technology    

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