INFLUENCE OF SOCIAL MEDIA ON THE QUALITY OF LIFE OF THE ELDERLY- A PILOT STUDY

Rijitha R. ¹, Dr. Nikhil Kumar Gouda ²

¹Research Scholar, Department of Media and Communication, School of Communication, Central University of Tamil Nadu, Thiruvarur-610 101, India

²Associate Professor and HOD, Department of Journalism and Mass Communication, Central University of Odisha, Koraput-763004, India

		ABSTRACT
		This study examines the influence of social media on the quality of life of elderly individuals, guided by the Uses and Gratifications theory. It focuses on how the elderly engage with social media and the benefits they derive from it. The research aims to provide insights into social media's role in enhancing well-being. Social media engagement will be assessed using the Social Media Use Integration Scale Lawdermilt, S. C. (2020). Self-Me: An Examination of Social Media Usage on the Self-Authorship of College Students (Doctoral Dissertation, University of North Dakota). ProQuest Dissertations Publishing. , while quality of life will be measured via the WHOQOL-BREF scale. A structured survey will be administered to 100 elderly residents in the Chennai District to gather data on usage patterns and perceived life satisfaction. The findings are expected to highlight the psychological and social dimensions of social media use among older adults, offering valuable implications for digital inclusion initiatives and elderly care strategies in an increasingly connected world.
Received 15 October 2024 Accepted 19 November 2025 Published 10 December 2025 Corresponding Author Rijitha. R, rijitha.phd@gmail.com DOI 10.29121/ShodhVichar.v1.i2.2025.62 Funding: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Copyright: © 2025 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License. With the license CC-BY, authors retain the copyright, allowing anyone to download, reuse, re-print, modify, distribute, and/or copy their contribution. The work must be properly attributed to its author.
		Keywords: Social Media, Elderly, Quality of Life, Uses and Gratifications Theory, WHOQOL-BREF, Social Media Use Integration Scale, Chennai District

1. INTRODUCTION

Quality of life (QoL) is a concept that aims to capture the well-being of a population or individual by considering both positive and negative aspects of their existence at a specific point in time. Common facets of QoL include personal health (physical, mental, and spiritual), relationships, educational status, work environment, social status, wealth, a sense of security and safety, freedom, autonomy in decision-making, social belonging, and physical surroundings Teoli, D., and Bhardwaj, A. (2023). Quality of Life. In StatPearls. StatPearls Publishing.. The remarkable increase in the participation of the elderly in the use of the Internet and cell phones has enhanced their sense of social connection. Social media platforms play a significant role in connecting them with family members, friends, and the outside world Patil, A. (2020). Effects of Digital Media on Elderly People. Retrieved March 11, 2023, from. This study aims to explore how social media influences the quality of life by providing older adults with digital literacy, safety, social connections, and mental health-related well-being.

2. Theoretical Framework

This research highlights the Uses and Gratifications Theory (UGT), which significantly influences social media usage patterns. Developed to evaluate users' motivations and gratifications within specific media, the UGT theoretical approach was established by Katz, E., Blumler, J. G., and Gurevitch, M. (1973). Uses and Gratifications Research. Public Opinion Quarterly, 37(4), 509–523..

According to Vinney (2024), scholars suggest several new gratifications that fall into four categories specific to new media features:

1) Different modalities serve new media content, ranging from audio to video to text. These modalities satisfy the need for realism, novelty, or, in the case of virtual reality, the sensation of being in a different place.

2) Agency-based gratifications empower people to create and share information and content, giving individuals a certain degree of control. This can satisfy needs such as agency enhancement, community building, and tailoring content to one's preferences.

3) Interactivity-based gratifications arise from the ability to interact with and impact content in real time, satisfying needs such as responsiveness, choice, and control.

4) Navigability-based gratifications refer to how users move through new media. The navigation offered by different interfaces can significantly affect users' experiences, satisfying needs such as browsing, guidance through navigation, and the enjoyment of exploring spaces and levels in games Vinney, C. (2022, February 7). Uses and Gratifications Theory in Media Psychology. Simply Psychology..

This research employs a quantitative approach within the framework of the Uses and Gratifications Theory, aiming to provide empirical evidence of social media's influence on the quality of life of the elderly.

Aim:

This study aims to discover the influence of social media on the quality of life of the elderly.

Objectives:

1) To determine if socio-demographic factors (Age, individual income, family income, residence, category, education, employment, and living arrangements) affect social media use and quality of life among the elderly.

2) To explore the relationship between social media usage patterns (access, prior experience, frequency, duration, and post-frequency) and the quality of life of the elderly.

3) To examine the relationship between social media use and the quality of life for older adults.

4) To investigate the effect of social media use on the quality of life of the elderly.

3. Method and Data Collection

The researchers employed a cross-sectional quantitative survey method, using a structured questionnaire administered to 100 older adults from community centers, retirement homes, and senior citizen clubs in and around the Chennai District. The survey aimed to assess the impact of social media usage on their quality of life, particularly concerning digital literacy, safety, social connections, and mental well-being. The focus area is Chennai because, as reported in an article by the Times of India, the region is experiencing notable trends in elderly engagement with technology.

Table 1

Table 1 Reliability Analysis
Domain	Cronbach's Alpha	N of Items
Social Integration and Emotional Connection	0.7	6
Integration into social routines	0.78	4
Quality of Life	0.89	26

Table 2

Table 2 Frequency Analysis of Sociodemographic Variables
Sociodemographic Variables	Categories	Mean	SD	Count	%	Chi-Square Value	P Value
Age		63.43	2.66
Gender	Male			46	46.0%	0.64	0.424
	Female			54	54.0%
Religion	Hindu			45	45.0%	33.84	0.000
	Christian			27	27.0%
	Muslim			24	24.0%
	Jain			4	4.0%
Category	Gen			11	11.0	38.480	0.000
	OBC			51	51.0
	SC			22	22.0
	ST			16	16.0
Individual monthly Income		17696	61436
Family Monthly Income		37086	68515
Pension	No			58	58.0%	2.56	0.110
	Yes			42	42.0%
Education	Below high school			24	24.0%	64.3	0.000
	High school			48	48.0%
	Diploma			1	1.0%
	Bachelor degree			18	18.0%
	Master’s degree			9	9.0%
Employment Status	Employed			38	38.0%	5.76	0.016
	Unemployed			62	62.0%
Marital Status	With partner			85	85.0%	46.34	0.000
	Widow			15	15.0%
Living Arrangements	Live by oneself			13	13.0%	9
	Live with family or relatives.			65	65.0%
	Live with spouse			22	22.0%

Table 3

Table 3 Social Media Use
Social media use	Categories	Count	Column N %	Chi-square Vale	P Value
Access social media	On own gadget	65	65.0%	9.000	0.003
	On family members' gadgets	35	35.0%
Preferred social media	Facebook	9	9.0%	98.00	0.000
	WhatsApp	11	11.0%
	YouTube	80	80.0%
Years of experience of social media use	<1 year	7	7.0%	21.560	.001
	1-2 years	18	18.0%
	2-3 years	12	12.0%
	3-4 years	25	25.0%
	4-5 years	10	10.0%
	>5 years	28	28.0%
Frequency of using social media per day	Everyday	8	8.0%	76.00	0.000
	5 - 6 days per week	28	28.0%
	4 days per week	20	20.0%
	1 - 2 days per week	41	41.0%
	1 day fortnightly	2	2.0%
	Less than 1 day fortnightly	1	1.0%
Hours spent on social media per day	< 1 hr	26	26.0%	63.00	0.000
	1-3 hrs	57	57.0%
	3-5 hrs	12	12.0%
	> 5 hrs	5	5.0%

Table 4

Table 4 Social Media Use
Social Media Use	Number of respondents	Percent
FB	29	18.6%
WhatsApp	58	37.2%
Instagram	2	1.3%
YouTube	65	41.7%
Twitter	1	0.6%
ALL	1	0.6%

Table 5

Table 5 Social Integration and Emotional Connection and Integration into Social Routines
Social Integration and Emotional Connection Integration into social routines	SDA	DA	N	A	SA	Mean	SD
I feel disconnected from friends when I have not used social media.	11	68	9	12	0	2.22	0.80
I would like it if everyone used social media to communicate.	5	39	41	15	0	2.66	0.79
I would be disappointed if I could not use social media at all.	10	56	26	6	2	2.34	0.82
I get upset when I can’t log on to social media.	9	62	19	7	3	2.33	0.85
I prefer to communicate with others mainly through social media.	2	80	12	3	3	2.25	0.69
Social media plays an essential role in my social relationships.	9	44	30	15	2	2.57	0.92
I enjoy checking my social media account(s).	1	1	16	79	3	3.82	0.54
I don’t like to use social media (item to be reverse scored).	3	4	22	65	6	3.67	0.78
Using social media is part of my everyday routine.	9	16	19	52	4	3.26	1.07
I respond to content that others share using social media.	5	58	13	22	2	2.58	0.96

Table 6

Table 6 Frequency Analysis and Descriptive Statistics of Each Quality-of-life Item (N=100)
Quality of life items	C1 %	C2 %	C3 %	C4 %	C5 %	Mean	Std. Deviation
Overall QOL	1	6	9	74	10	3.86	0.71
Overall health	3	3	12	78	4	3.77	0.71
Pain	0	7	17	76	0	3.69	0.60
Dependence on medical aids	3	5	21	71	0	3.60	0.72
Positive feelings	0	10	65	22	3	3.18	0.64
Personal beliefs	1	10	53	32	4	3.28	0.74
Concentration	2	9	45	42	2	3.33	0.75
Security and safe	1	2	64	30	3	3.32	0.62
Physical environment	0	12	66	22	0	3.10	0.58
Energy	2	13	70	13	2	3.00	0.65
Bodily image	3	34	39	19	5	2.89	0.92
Financial support	2	6	65	19	8	3.25	0.77
Accessibility of information	4	26	40	27	3	2.99	0.90
Leisure activities	0	31	48	16	5	2.95	0.82
Mobility	0	5	7	84	4	3.87	0.54
Sleep and rest	2	4	13	75	6	3.79	0.70
Activities of daily living	0	6	17	74	3	3.74	0.61
Work capacity	0	1	23	72	4	3.79	0.52
Self-esteem and satisfaction	2	0	22	68	8	3.80	0.67
Personal relationships	0	1	54	41	4	3.48	0.59
Sexual activity	4	2	70	22	2	3.16	0.68
Social support	1	5	59	34	1	3.29	0.62
Living environment	1	2	7	85	5	3.91	0.53
Health care services	0	3	12	79	6	3.88	0.54
Transport	0	1	21	72	6	3.83	0.53
Negative feelings	3	2	18	73	4	3.73	0.71

Table 7

Table 7 Descriptive Statistics for all Domains (N=100)
Domain	Minimum	Maximum	Mean	Std. Deviation
Physical	39.29	82.14	56.79	7.08
Psychological	33.33	79.17	53.13	8.95
Social	25	91.67	57.75	10.54
Environment	34.38	93.75	60.09	10.71
Average Quality of Life	36.12	85.64	56.94	7.34

Table 8

Table 8 The Association Between Sociodemographic Variables Versus the Use of Social Media
Social Media Use			Sociodemographic Variables
		Gender			Religion				Category				Pension		Education					Employment Status		Marital Status			Living Arrangements
		Male		Female	Hindu	Christian	Muslim	Jain	Gen	OBC	SC	ST	No	Yes	Below high school	High school	Diploma	Bachelor degree	Master’s degree	Employed	Unemployed		With partner	Widow	Live by oneself	Live with family or relatives	Live with spouse
Access social media	On own gadget	39		26	34	17	13	1	8	35	16	6	30	35	7	30	1	18	9	24	41		53	12	11	38	16
	On family members’ gadget	7		28	11	10	11	3	3	16	6	10	28	7	17	18	0	0	0	14	21		32	3	2	27	6
Preferred social media	Facebook	7		2	6	1	2	0	0	6	2	1	4	5	1	2	0	6	0	3	6		6	3	2	5	2
	WhatsApp	8		3	4	2	5	0	0	7	2	2	5	6	2	5	0	1	3	3	8		9	2	1	8	2
	YouTube	31		49	35	24	17	4	11	38	18	13	49	31	21	41	1	11	6	32	48		70	10	10	52	18
Years of experience of social media use	<1 year	2		5	2	2	3	0	0	4	0	3	4	3	5	2	0	0	0	3	4		6	1	1	5	1
	1-2 years	8		10	5	8	4	1	1	5	4	8	13	5	12	4	0	2	0	10	8		16	2	1	15	2
	2-3 years	4		8	6	4	2	0	0	4	5	3	6	6	4	7	0	1	0	7	5		10	2	2	8	2
	3-4 years	11		14	9	6	8	2	5	15	5	0	16	9	3	19	1	2	0	5	20		24	1	0	17	8
	4-5 years	4		6	3	4	3	0	1	7	1	1	8	2	0	6	0	3	1	5	5		9	1	1	5	4
	>5 years	17		11	20	3	4	1	4	16	7	1	11	17	0	10	0	10	8	8	20		20	8	8	15	5
Frequency of using social media per day	Everyday	2		6	8	0	0	0	2	5	1	0	3	5	0	5	0	2	1	1	7		4	4	1	5	2
	5 - 6 days per week	15		13	16	6	5	1	4	15	7	2	15	13	2	10	0	9	7	10	18		23	5	6	16	6
	4 days per week	12		8	6	7	6	1	2	12	5	1	13	7	0	15	1	4	0	6	14		18	2	3	13	4
	1 - 2 days per week	16		25	13	13	13	2	3	18	7	13	27	14	20	18	0	2	1	20	21		39	2	2	29	10
	1 day fortnightly	0		2	2	0	0	0	0	1	1	0	0	2	2	0	0	0	0	1	1		0	2	1	1	0
	Less than 1 day fortnightly	1		0	0	1	0	0	0	0	1	0	0	1	0	0	0	1	0	0	1		1	0	0	1	0
Hours spend on social media per day	< 1 hr	7		19	12	5	7	2	3	17	6	0	19	7	7	17	0	1	1	8	18		24	2	1	19	6
	1-3 hrs	30		27	25	18	13	1	5	26	14	12	34	23	15	26	1	13	2	24	33		46	11	11	33	13
	3-5 hrs	6		6	7	3	1	1	2	5	2	3	3	9	2	4	0	3	3	4	8		10	2	1	8	3
	> 5 hrs	3		2	1	1	3	0	1	3	0	1	2	3	0	1	0	1	3	2	3		5	0	0	5	0

Table 9

Table 9 Chi-Square Test of Association Results
		Gender	Religion	Category	Pension	Education	Employment Status	Marital Status	Living Arrangements
Access social media	Chi-square	14.654	6.304	6.48	10.698	28.755	0.091	1.745	3.998
	Sig.	.000^*	0.098	0.09	.001^*	.000^*,	0.762	0.186	0.136
Preferred social media	Chi-square	8.515	5.948	3.972	1.736	20.855	0.756	2.852	1.04
	Sig.	.014^*	0.429	0.68	0.42	.008^*,	0.685	0.24	0.904
Years of experience of social media use in years	Chi-square	4.274	18.171	32.96	8.194	69.779	9.636	6.856	15.508
	Sig.	0.511	0.254	.005^*	0.146	.000^*,	0.086	.232^b	0.115
Frequency of using social media per day	Chi-square	7.325	21.483	19.453	7.189	58.926	5.571	23.062	7.4881
	Sig.	0.198	0.122	0.194	0.207	.000^*	0.35	.000^*	0.679
Hours spend on social media per day	Chi-square	5.29021	8.74676	9.8119	8.5194	30.0059	1.10414	2.823423566	7.0969
	Sig.	0.152	0.461	0.366	.036^*	.003^*	0.776	0.42	0.312

Table 10

Table 10 The Impact of social media (Social Integration and Emotional Connection Integration into Social Routines) Among the Respondents, with Sociodemographic Variables.
Sociodemographic Variables	Categories	Social Integration and Emotional Connection	t/F Value	P Value	Integration into social routines	t/F Value	P Value
		Mean±SD			Mean±SD
Gender	Male	2.46±0.55	1.24	0.22	3.44±0.53	1.988	0.50
	Female	2.34±0.48			3.24±0.47
Religion	Hindu	2.39±0.54	0.163	0.921	3.46±0.51	2.153	0.099
	Christian	2.38±0.54			3.27±0.47
	Muslim	2.45±0.48			3.16±0.51
	Jain	2.29±0.16			3.38±0.48
Category	Gen	2.29±0.34	2.285	0.084	3.32±0.39	4.22	0.008
	OBC	2.48±0.60			3.45±0.56
	SC	2.17±0.35			3.35±0.40
	ST	2.49±0.42			2.95±0.37
Pension	No	2.31±0.35	2.03	0.05	3.26±0.45	1.727	0.87
	Yes	2.52±0.66			3.43±0.56
Education	Below high school	2.25±0.54	0.862	0.49	2.94±0.33	7.028	0.000
	High school	2.40±0.50			3.38±0.48
	Diploma	2.33±0.00			3.50±0.00
	Bachelor degree	2.54±0.58			3.64±0.58
	Master’s degree	2.46±0.36			3.50±0.31
Employment Status	Employed	2.28±0.37	1.83	0.07	3.26±0.46	1.07	0.287
	Unemployed	2.47±0.58			3.38±0.54
Marital Status	With partner	2.35±0.45	2.073	0.041	3.29±0.48	1.821	0.072
	Widow	2.64±0.75			3.55±0.61
Living Arrangements	Live by oneself	2.69±0.62	2.95	0.057	3.58±0.51	2.036	0.136
	Live with family or relatives	2.38±0.50			3.27±0.53
	Live with spouse	2.27±0.44			3.36±0.41
Access social media	On own gadget	2.42±0.54	0.68	0.50	3.49±0.50	4.731	0.0001
	On family members’ gadget	2.35±0.46			3.04±0.36

Table 11

Table 11 The Relationship Between Age, Individual Income, Family Income Versus Social Integration and Emotional Connection and Integration into Social Routines
Sociodemographic variables	Correlation	Social Integration and Emotional Connection	Integration into social routines
Age	Pearson Correlation	-0.036	-.231^*
	P Value	0.725	0.021
Individual monthly Income	Pearson Correlation	-0.111	-.247^*
	P Value	0.271	0.013
Family Monthly Income	Pearson Correlation	0.068	-0.149
	P Value	0.503	0.14
*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).

Table 12

Table 12 The Quality-Of-Life Domain of the Elderly Among the Respondents with Socio-Demographics
Sociodemographic Variables	Categories	Physical	Psychological	Social	Environment	Average of Quality of Life
		Mean (SD)	Mean (SD)	Mean (SD)	Mean (SD)	Mean (SD)
Gender	Male	58.39(8.22)	54.44 (10.37)	60.69 (11.34)	62.84(12.64)	59.09(8.98)
	Female	55.42(5.67)	52.01 (7.45)	55.25 (9.20)	57.75(8.16)	55.11(4.99)
	t value	2.122	1.360	2.649	2.423	2.792
	P value	0.036	0.177	0.009	0.017	0.006
Religion	Hindu	58.57(5.72)	53.61 (7.67)	55.74 (9.86)	60.07(8.45)	57.00(5.53)
	Christian	54.76(6.64)	51.23 (9.23)	59.26 (9.05)	57.99(9.35)	55.81(6.27)
	Muslim	56.10(9.09)	54.86 (11.04)	59.38 (13.53)	63.54(14.44)	58.47(10.96)
	Jain	54.46(7.92)	50.00 (5.89)	60.42 (4.17)	53.91(14.06)	54.70(5.81)
	F value	1.964	0.907	1.004	1.654	0.679
	P value	0.125	0.441	0.394	0.182	0.567
Category	Gen	57.14(7.14)	54.17 (9.86)	53.03 (8.56)	57.10(9.79)	55.36(7.65)
	OBC	58.54(6.82)	55.64 (9.08)	60.95 (10.86)	64.64(11.15)	59.94(7.81)
	SC	58.28(4.73)	51.70 (7.46)	56.44 (10.26)	58.10(4.79)	56.13(3.02)
	ST	48.88(5.49)	46.35 (6.06)	52.60 (7.89)	50.39(7.98)	49.56(3.06)
	F value	10.287	5.218	4.018	10.210	11.083
	P value	0.000	0.002	0.010	0.000	0.000
Pension	No	55.67(5.60)	52.23 (7.77)	56.32 (7.70)	57.92(8.61)	55.53(4.85)
	Yes	58.33(8.56)	54.37 (10.33)	59.72 (13.39)	63.10(12.58)	58.88(9.54)
	t value	1.884	1.181	1.604	2.443	2.296
	P value	0.063	0.240	0.112	0.016	0.024
Education	Below high school	52.83(7.45)	49.31 (8.57)	54.51 (8.51)	51.95(8.13)	52.15(4.16)
	High school	57.37(7.00)	52.95 (8.02)	57.12 (11.27)	60.74(9.62)	57.04(7.40)
	Diploma	60.71(0.00)	45.83 (.00)	50.00 (0.00)	53.13(0.00)	52.42(0.00)
	Bachelor degree	60.32(6.47)	56.94 (11.07)	65.28 (10.00)	67.53(11.94)	62.52(7.94)
	Master’s degree	56.75(2.15)	57.41 (6.17)	55.56 (5.89)	64.24(5.66)	58.49(4.24)
	F value	3.468	2.785	3.444	7.803	6.543
	P value	0.011	0.031	0.011	0.000	0.000
Employment Status	Employed	54.51(6.47)	51.54 (9.01)	56.14 (8.60)	56.17(9.15)	54.59(6.21)
	Unemployed	58.18(7.12)	54.10 (8.85)	58.74 (11.53)	62.50(10.96)	58.38(7.66)
	t value	-2.586	-1.397	-1.198	-2.981	-2.575
	P value	0.011	0.165	0.234	0.004	0.012
Marital Status	With partner	57.02(7.00)	52.65 (8.93)	59.02 (9.55)	59.71(10.39)	57.10(7.11)
	Widow	55.48(7.62)	55.83 (8.88)	50.56 (13.16)	62.29(12.58)	56.04(8.79)
	t value	0.775	-1.275	2.978	-0.861	0.513
	P value	0.440	0.205	0.004	0.392	0.609
Living Arrangements	Live by oneself	54.12(5.98)	53.21 (5.93)	51.92 (11.86)	60.34(9.06)	54.90(6.60)
	Live with family or relatives	56.70(7.54)	53.08 (9.86)	58.21 (10.77)	59.86(11.84)	56.96(8.01)
	Live with spouse	58.60(5.90)	53.22 (7.81)	59.85 (7.98)	60.65(8.16)	58.08(5.45)
	F value	1.673	0.003	2.559	0.048	0.766
	P value	0.193	0.997	0.083	0.953	0.468
Access social media	On own gadget	58.74(6.59)	55.26 (9.35)	58.97 (11.15)	63.32(10.46)	59.07(7.54)
	On family members’ gadget	53.16(6.58)	49.17 (6.61)	55.48 (9.03)	54.11(8.47)	52.98(5.03)
	t value	4.034	3.416	1.595	4.477	4.291
	P value	0.000	0.001	0.114	0.000	0.0000

Table 13

Table 13 The Relationship Between Age, Income, and Quality of Life Among the Respondents.
Sociodemographic variables	Correlation	Physical	Psychological	Social	Environment	Average of Quality of Life
Age	Pearson Correlation	.237^*	.224^*	0.057	0.159	.204^*
	P Value	0.018	0.025	0.572	0.115	0.042
Individual monthly Income	Pearson Correlation	.348^**	0.178	0.134	.327^**	.305^**
	P Value	0.000	0.077	0.183	0.001	0.002
Family Monthly Income	Pearson Correlation	.376^**	.301^**	.216^*	.403^**	.407^**
	P Value	0.000	0.002	0.031	0.000	0.000
Physical	Pearson Correlation		.471^**	.335^**	.650^**	.742^**
	P Value		0.000	0.001	0.000	0.000
Psychological	Pearson Correlation	.471^**		.280^**	.681^**	.767^**
	P Value	0.000		0.005	0.000	0.000
Social	Pearson Correlation	.335^**	.280^**		.509^**	.711^**
	P Value	0.001	0.005		0.000	0.000
Environment	Pearson Correlation	.650^**	.681^**	.509^**		.912^**
	P Value	0.000	0.000	0.000		0.000
Average of Quality of Life	Pearson Correlation	.742^**	.767^**	.711^**	.912^**
	P Value	0.000	0.000	0.000	0.000
*. Correlation is significant at the 0.05 level (2-tailed).
**. Correlation is significant at the 0.01 level (2-tailed).

Table 14

Table 14 The Relationship Between Patterns (Access, Prior Experience, Frequency, Duration, and Post-Frequency) of Social Media Use and the Quality of life of the Elderly.
Social media use	Categories	Social Integration and Emotional Connection	Integration into social routines	Physical	Psychological	Social	Environment	Average of Quality of Life
		Mean (SD)	Mean (SD)	Mean (SD)	Mean (SD)	Mean (SD)	Mean (SD)	Mean (SD)
Access social media	On own gadget	2.42(0.54)	3.49(0.50)	58.74(6.59)	55.26(9.35)	58.97(11.15)	63.32(10.46)	59.07(7.54)
	On family members’ gadget	2.35(0.46)	3.04(0.36)	53.16(6.58)	49.17(6.61)	55.48(9.03)	54.11(8.47)	52.98(5.03)
	t value	0.675	4.731	4.034	3.416	1.595	4.477	4.291
	P Value	0.501	0.000	0.000	0.000	0.000	0.000	0.000
Preferred social media	Facebook	2.61(0.81)	3.75(0.53)	62.70(7.17)	57.41(14.55)	67.59(15.28)	70.14(14.24)	64.46(9.50)
	WhatsApp	2.71(0.79)	3.25(0.60)	62.66(12.10)	63.26(9.65)	60.61(15.85)	71.02(13.56)	64.39(11.22)
	YouTube	2.33(0.40)	3.30(0.48)	55.31(5.30)	51.25(6.87)	56.25(8.33)	57.46(8.06)	55.07(4.98)
	F value	3.791	3.562	10.286	12.027	5.612	15.681	17.220
	P Value	0.026	0.032	0.000	0.000	0.005	0.000	0.000
Years of experience of social media use in years	<1 year	2.02(0.40)	2.93(0.28)	58.16(12.83)	54.76(10.33)	58.33(15.21)	61.61(17.09)	58.22(13.27)
	1-2 years	2.20(0.46)	2.89(0.41)	53.37(9.84)	45.37(8.32)	56.48(12.31)	50.69(12.25)	51.48(7.66)
	2-3 years	2.42(0.47)	3.17(0.53)	53.27(6.36)	49.65(6.52)	52.78(5.43)	57.29(4.49)	53.25(3.36)
	3-4 years	2.34(0.47)	3.30(0.42)	58.43(4.60)	55.00(8.67)	58.67(8.83)	61.25(8.37)	58.34(5.21)
	4-5 years	2.32(0.20)	3.45(0.16)	56.07(2.41)	55.42(4.41)	58.33(8.78)	63.75(3.02)	58.39(3.50)
	>5 years	2.68(0.59)	3.78(0.38)	58.93(5.28)	56.70(8.44)	59.52(11.72)	64.62(9.88)	59.94(7.12)
	F value	17.969	5.085	1.132	1.869	1.412	1.728	0.646
	P Value	0.000	0.003	0.340	0.140	0.244	0.166	0.587
Frequency of using social media per day	Everyday	3.06(0.82)	3.94(0.53)	63.84(7.74)	59.90(9.17)	55.21(14.04)	67.97(12.02)	61.73(8.98)
	5 - 6 days per week	2.42(0.30)	3.61(0.31)	56.89(3.76)	55.65(7.10)	58.33(8.49)	62.17(6.03)	58.26(4.05)
	4 days per week	2.52(0.56)	3.45(0.41)	56.25(4.90)	55.00(8.93)	59.17(11.11)	62.19(11.01)	58.15(7.71)
	1 - 2 days per week	2.25(0.40)	2.99(0.42)	55.31(8.79)	49.29(8.28)	57.32(10.41)	56.02(11.66)	54.49(8.11)
	1 day fortnightly	1.50(0.00)	2.88(0.18)	57.14(0.00)	60.42(2.95)	45.83(17.68)	60.94(15.47)	56.08(7.55)
	Less than 1 day fortnightly	1.67()	3.25()	67.86()	33.33()	75.00()	62.50()	59.67()
	F value	6.666	13.032	2.664	5.199	1.258	2.622	2.018
	P Value	0.000	0.000	0.027	0.000	0.288	0.029	0.083
Hours spent on social media per day	< 1 hr	2.17(0.39)	3.00(0.44)	59.62(7.41)	54.17(8.50)	58.01(10.13)	61.42(10.71)	58.30(7.39)
	1-3 hrs	2.38(0.39)	3.37(0.46)	54.89(6.14)	51.17(7.42)	57.60(9.49)	57.89(9.54)	55.39(5.91)
	3-5 hrs	2.74(0.76)	3.77(0.49)	58.93(8.94)	54.51(10.87)	54.17(12.05)	62.76(10.78)	57.59(8.54)
	> 5 hrs	2.90(0.94)	3.60(0.38)	58.57(5.42)	66.67(11.79)	66.67(17.68)	71.88(15.93)	65.94(12.46)
	F value	5.839	9.025	3.464	5.629	1.698	3.431	4.021
	P Value	0.001	0.000	0.019	0.001	0.173	0.020	0.010

4. Results

The data analysis reveals several significant findings regarding the use of social media among the elderly and its impact on various aspects of their lives. The Cronbach's Alpha value was above 0.7, indicating acceptable reliability for the survey instruments used. Chi-square goodness-of-fit tests revealed significant differences in the proportions of certain sociodemographic variables (P < 0.05). Further chi-square tests indicated substantial differences in the proportions of social media usage categories (P < 0.05), with YouTube (41.7%) and WhatsApp (37.2%) being the most used platforms, followed by Facebook (18.6%), Instagram (1.3%), and Twitter (0.6%). Descriptive statistics showed variations in the quality-of-life domains among the elderly, with the environment (mean = 60.09, SD = 10.71) having the highest scores and psychological well-being (mean = 53.13, SD = 8.95) having the lowest. Chi-square tests also revealed significant associations between sociodemographic variables and social media use (P < 0.05). One-way ANOVA indicated substantial differences in social integration and emotional connection based on sociodemographic variables (P < 0.05). Pearson correlation tests showed significant relationships between age and social integration (P < 0.05), as well as age and individual income (P < 0.05).

Additionally, one-way ANOVA revealed significant associations between certain social media usage variables and quality of life domain scores (P < 0.05). Finally, Pearson correlation tests indicated significant relationships between age and quality of life, as well as income and quality of life (P < 0.05). One-way ANOVA also showed significant differences in quality-of-life domain scores based on social media usage patterns, including access, prior experience, frequency, duration, and posting frequency (P < 0.05).

5. Discussion

The data indicate that social media has become an integral part of the daily lives of the elderly, particularly platforms like YouTube and WhatsApp, which cater to their preferences for video content and messaging. The significant associations between sociodemographic variables and social media use highlight the diverse ways different segments of the elderly population engage with digital platforms. Furthermore, the positive impact of social media on quality-of-life domains underscores the potential benefits of digital inclusion for older adults, promoting social integration and emotional well-being.

The significant relationships between age, income, and social integration emphasize the importance of considering socioeconomic factors when examining the digital behaviors of the elderly. The variations in quality-of-life domains suggest that while social media can enhance certain aspects of life, such as environmental factors and social integration, it may have varying effects on psychological well-being.

6. Limitations and Future Research

This study is limited by its focus on a specific region or demographic, which restricts the generalizability of the findings to broader elderly populations. Additionally, more information regarding the duration of the study is needed to fully assess the effects of long-term social media use. The analysis primarily concentrated on YouTube and WhatsApp, neglecting other potentially relevant platforms, thus limiting the scope of the investigation. While the data suggest associations between social media use and quality of life domains, confounding factors may also influence both variables.

Future research should expand to include diverse elderly populations from various cultural, socioeconomic, and geographic backgrounds. Longitudinal studies are necessary to track the evolving relationship between social media use and well-being over time. Investigating the different impacts of various social media platforms on the elderly is crucial. Employing qualitative methods can provide deeper insights into the experiences and perspectives of elderly social media users. Additionally, exploring potential mediating factors such as social support networks and digital literacy can help clarify the complex relationship between social media use and well-being. Finally, research should examine the potential negative consequences of social media use among the elderly, including privacy concerns, exposure to misinformation, and the risk of addiction.

7. Conclusion

The study underscores the pervasive role of social media in the daily lives of the elderly, with platforms such as YouTube and WhatsApp being particularly significant. The findings reveal substantial associations between sociodemographic variables and social media use, indicating that different segments of the elderly population engage with digital platforms in diverse ways. Social media usage positively influences various quality of life domains, highlighting its potential benefits for social integration and emotional well-being among the elderly. The significant relationships between age, income, and social integration further emphasize the critical role of socioeconomic factors in shaping the digital behaviors of the elderly. While social media enhances several aspects of life, it is essential to consider the varied effects on psychological well-being.

8. RECOMMENDATIONS

Groundwater is a main source for drinking and domestic purposes in study area. So based on the findings of this study we recommend that: community must not depend totally on ground water as main source for fluoride, and community in study area should be use other sources for fluoride intake to obtain on daily required amount of fluoride for protection the health.

CONFLICT OF INTERESTS

None .

ACKNOWLEDGMENTS

None.

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