conclusion, summary and recommendations.

MUSIC AND DEPRESSION 2

Section 4: Results and Findings

Descriptive quantitative data

Results to the demographics

Results obtained below indicates that several participants in this study are male with a percentage of 85, followed by females (15%).

Table 1 Gender

Gender
	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Male	85	85.0	85.0	85.0
	Female	15	15.0	15.0	100.0
	Total	100	100.0	100.0

In the table below, it can be seen that the highest percentage belongs to 29-39 years of age (35%), followed by 18-28 years (28%), 40-50 years (22%), and 51 years and above (15%).

Table 2 Age

Age
	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	18 to 28 years	28	28.0	28.0	28.0
	29 to 39 years	35	35.0	35.0	63.0
	40 to 50 years	22	22.0	22.0	85.0
	51 and above years	15	15.0	15.0	100.0
	Total	100	100.0	100.0

Results to hypotheses

The first hypothesis investigated was:

H1 – Music has a positive impact on the reduction in depression.

Table 3 Results to the first hypothesis

Model Summary
Model	R	R Square	Adjusted R Square	Std. The error of the Estimate
1	.789a	.623	.619	.40403
a. Predictors: (Constant), Music

In the table above, the percentage of R-square is 62.3%, due to which it can be argued that Music can be used for predicting the value of depression. When R-square is more than 40%, it means that the variable perfectly fits the model.

ANOVA
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	26.429	1	26.429	161.909	.000b
	Residual	15.997	98	.163
	Total	42.427	99
a. Dependent Variable: ReductionInDepression
b. Predictors: (Constant), Music

ANOVA table helps understand the hypothesis and accept or reject it. When F's value is more significant than one and significantly less than 0.05, the idea is born. The value of significance in the table above is 0.000, based on which first hypothesis has been received.

Coefficients
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
	B	Std. Error	Beta
1	(Constant)	.423	.156		2.707	.008
	Music	.847	.067	.789	12.724	.000
a. Dependent Variable: ReductionInDepression

The table of coefficients identifies whether there is a positive or negative relationship between the variables. The value of t is equivalent to 12.724. Hence, Music decreases depression by 12.724 times. Beta is 78.9%. Therefore Music is directly and positively associated with a reduction in depression.

Results to the second hypothesis

The second hypothesis investigated was:

H2 – Music therapy results in a reduction in depression.

Table 4 results to the second hypothesis

Model Summary
Model	R	R Square	Adjusted R Square	Std. The error of the Estimate
1	.461a	.213	.205	.58383
a. Predictors: (Constant), music therapy

In the table above, R-square is 21.3%. Hence music therapy moderately fits into the model.

ANOVA
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	9.022	1	9.022	26.469	.000b
	Residual	33.404	98	.341
	Total	42.427	99
a. Dependent Variable: ReductionInDepression
b. Predictors: (Constant), music therapy

Music therapy helps reduce depression because the value of significance is less than 0.05 and F is greater than 1. Therefore, the hypothesis has been accepted.

Coefficients
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
	B	Std. Error	Beta
1	(Constant)	1.067	.255		4.176	.000
	MusicTherapy	.582	.113	.461	5.145	.000
a. Dependent Variable: ReductionInDepression

A coefficient value above indicates that t is positive and high, with a value of 5.145. based on the value of t, music therapy can reduce depression by 5.145 times. Similarly, Beta's value is positive and equivalent to 46.1%, based on which music therapy increases the chances of depression reduction by 46.1%.

Summary of hypotheses

The summary of hypotheses results can be seen below:

Table 5 Summary of Hypotheses

S.no	Hypotheses	Status
1	H1 – Music has a positive impact on the reduction in depression.	Accepted
2	H2 – Music therapy results in a reduction in depression.	Accepted

Discussion

In this investigation, the aim was to find out the role of Music in treating depression. For this reason, two hypotheses were deployed, and a quantitative approach was adopted. The results helped me understand that Music is a good tool for treating depression because it reported positive music outcomes. Similar results were obtained by the study of Steward et al. (2019), arguing that Music plays a vital role in treating depression because it allows a person to slowly engage and forget about his past. However, they also argued that it takes time. These results are highly relevant to ancient studies in different nations because they also regarded Music as one of the best tools for treating depression.

One more hypothesis tested in this study was related to music therapy and its role in depression reduction. The findings are in support of the statement that music therapy moderately heals depression. The value of significance in the second hypothesis is also less than 0.05; hence theory is accepted. The results obtained are similar to Tang et al. (2020) and Gotell (2018), who argued that many nations use music therapies for reducing depression. However, Garrido et al. (2017) argued that many countries still face issues in developing effective music therapies, due to which their Music does not help in healing depression. Therefore, it can be summarised that music therapy is good for treating depression. However, it should be good.

Ethical considerations

Before carrying out this investigation, the mutual consent form was obtained from the respondents. Only the ones willing to participate were provided, and no one was forced. The results were not used for any other purpose except for generating the results of this investigation.

Limitations and implications

This study had a limited number of respondents. This study was only carried out locally, and international people suffering from depression were not involved. The sample size was small (100) even when many people suffering from depression issues are many. This investigation can be beneficial for music developers and psychologists to develop Music for healing depressed people. With this investigation's help, the government and clinics would create more effective Music to treat depressed people.

References

Garrido, S., Eerola, T., &McFerran, K. (2017). Group rumination: Social interactions around Music in people with depression. Frontiers in psychology, 8, 490.

Stewart, J., Garrido, S., Hense, C., &McFerran, K. (2019). Music used for mood regulation: Self-awareness and conscious listening choices in young people with tendencies to depression. Frontiers in psychology, 10, 1199.

Tang, Q., Huang, Z., Zhou, H., & Ye, P. (2020). Effects of music therapy on depression: A meta-analysis of randomized controlled trials. PloS one, 15(11), e0240862.