Media-Based Leisure and Wellbeing: A Study of Older Internet Users

Figures & data

Table 1. Factors and factor loadings for exploratory factor analysis of online and offline media-based leisure activities.

Factor	Activities included in the factor	Factor loading	Variance explained
Social media	Writing entries at forums, blogs, etc. (online)	.760	12.8%
(2.30, .33)	Reading entries at forums, blogs, etc. (online)	.728
	Using social networking services (online)	.502
	Using chat software (online)	.429
Online news	Obtaining news (online)	.812	7.4%
(1.33, .56)	Reading newspapers (online)	.809
Time fillers	Watching TV (offline)	.684	7.2%
(1.29, .17)	Playing games (online)	.668
Offline mass media	Reading newspapers (offline)	.751	6.8%
(1.22, .20)	Reading printed books (offline)	.641
	Listening to the radio (offline)	.509
Online broadcasting	Watching TV (online)	.789	6.3%
(1.13, .19)	Listening to the radio (online)	.631
Alternative books	Reading books in electronic version (offline)	.766	5.7%
(1.03, .06)	Listening to audio books (offline)	.513
Video on demand	Watching videos or DVDs (offline)	.819	5.6%
(1.01, .04)	Downloading music, films etc. (online)	.405

Note. Data were weighted by country. Weighted N = 4,798, Actual N = 8,930. Pairwise case deletion. Principal component extraction and Quatrimax rotation with Kaiser normalisation. Factors included based on eigenvalue of at least 1. Only loadings of at least .4 are presented. The seven factors explained 51.7% of variance. KMO = 0.7. Eigenvalue and Cronbach’s Alpha are in parentheses.

Table 2. The four clusters of older internet users.

Variable	Innovative traditionalists	Entertainment seekers	Selective content consumers	Eclectic media users
Activity factor^1
Social media***	−0.01^b	1.46^a	−0.27^c	−0.40^d
Online news***	0.21^a	0.11^b	0.74^a	−0.53^c
Time fillers***	−0.97^c	0.96^a	−0.19^b	−0.27^b
Offline mass media	−0.05	0.01	−0.08	−0.03
Online broadcasting***	1.26^a	−0.14^b	−0.14^b	−0.14^b
Alternative books***	2.39^a	−0.18^b	−0.24^b	−0.26^b
Video on demand***	0.04^c	0.18^b	0.64^a	−0.43^d
Life satisfaction^2*	7.90^a	7.64^b	7.86^a	7.76
Total online time^3***	3.01^b	3.89^a	2.86^b	1.30^c
Total offline time^3***	7.31^b	8.20^a	6.90^c	5.76^d
Weighted N	362	664	1074	2020
Percentage of sample	8.8	16.1	26.1	49.0

Note. Data were weighted by country. Weighted N = 4798, Actual N = 8980. Significance was tested using one-way ANOVA with LSD Post Hoc Tests. Significant group differences are marked with (a) (b) (c) (d). ¹Standardized means (z score) ²Mean ³Mean in hours. *p < 0.05, **p < 0.01, ***p < 0.001.

Table 3. Background characteristics of Internet user clusters.

Variable	Innovative traditionalists	Entertainment seekers	Selective content consumers	Eclectic media users
Sex
Man	51.7	45.9	59.5	49.7
Woman	48.3	54.1	40.5	50.3
Marital status
Single, divorced, widowed	23.9	32.4	25.9	27.1
Married	76.1	67.6	74.1	72.9
Children
None	40.7	32.0	46.3	39.4
One or more	59.3	68.0	53.7	60.6
Education
Lower than academic	62.2	72.1	54.3	63.0
Academic	37.8	27.9	45.7	37.0
Income
Above average	52.3	31.7	45.7	37.7
Similar or below average	47.7	68.3	54.3	62.3
Place of residence
Big city (incl. suburbs)	50.7	43.3	48.6	45.0
Town or small city	30.1	33.7	33.9	34.3
Country village	15.3	20.7	13.8	16.9
Farm/home in countryside	3.9	2.3	3.8	3.9
Country
Austria	12.6	6.7	19.8	60.9
Canada	9.8	9.7	33.9	46.6
Denmark	4	10.2	34.9	50.9
Israel	6.9	19.1	24.2	49.8
Netherlands	8.3	47.2	13.6	30.8
Romania	2.5	13.3	27.4	56.7
Spain	17.2	12.7	26.2	44
Age (mean)	67.4 [66.7, 68.0]	67.1^b [66.6, 67.5]	68.0^a [67.6, 68.4]	67.8^a [67.5, 68.1]
Health (mean)	7.2^a [7.0, 7.4]	6.7^b [6.6, 6.9]	7.3^a [7.2, 7.4]	7.2^a [7.1, 7.3]

Note. Data represent % of the sample and were weighted by country. Weighted N = 4798, Actual N = 8980. Chi-squared statistics were significant (p < 0.01) for all attribute category cross-tabulations. Health and age were tested using one-way ANOVA and were significant (p < 0.01). (a) (b) (c) (d) mark significant (p < 0.05) differences between groups according to LSD Post-Hoc tests. 95% Confidence intervals are in parentheses.

Table 4. Leisure preferences of Internet user clusters (in %).

Leisure preferences	Innovative traditionalists	Entertainment seekers	Selective content consumers	Eclectic media users
Watch TV	50.6^1	54.8^1	49.8^1	49.5^1
Read books, newspapers or magazines***	41.2^2	31.2^3	41.6^2	45.3^2
Call friends/family on the phone	26.2	25.9	25.4	27.4^3
Visit friends/family**	29.4^3	23.8	22.2	27.2
Visit websites***	24.9	20.9	28.2^3	20.2
Listen to radio**	20.2	14.9	19.2	21.7
Use social network services***	19.3	40.8^2	14.7	12.7
Write emails to friends/family**	17.7	12.5	18.6	15.1
Send SMS to friends/family	12.4	14.3	12.6	10.9
Listen to music on CD, MP3, or similar***	11.4	4.7	8.3	6.4
Watch video or DVD***	7.7	5.7	9.8	4.3
Chat online with friends/family***	7.5	8.3	4.8	3.8

Note. Data was weighted by country. Weighted N = 4798, Actual N = 8980. Significance was tested using chi-square cross-tabulation. (1), (2), (3) mark the three most preferred leisure activities for each cluster. *p < 0.05, **p < 0.01, ***p < 0.001.

Table 5. Clusters and background variables associated with SWB: A linear regression.

Variable	Category	Unstandardised coefficients (B)	Standardised coefficients
			SE	Beta
Constant		2.23	0.25
Cluster^a	Innovative traditionalists	0.05	0.08	.01
	Selective content consumers	−0.09	0.06	−.02
	Eclectic media users	−0.13	0.06	−.04*
Sex (woman)		0.07	0.04	.02
Marital status (married)		0.33	0.04	.09***
Children (one or more)		0.05	0.04	.02
Education (academic)		−0.03	0.04	−.01
Income (above average)		0.035	0.04	.10***
Place of residence^b	Town or smaller village	0.07	0.04	.02
	Country village	0.06	0.05	.01
	Farm/home in countryside	0.10	0.09	.01
Age		0.02	0.01	.08***
Health		0.49	0.01	.54***
Country^c	Austria	0.03	0.09	.01
	Canada	0.04	0.08	.01
	Denmark	0.39	0.11	.06***
	Netherlands	0.22	0.11	.03*
	Romania	0.15	0.10	.02
	Spain	−0.09	0.09	−.02

Note. N = 8980. Listwise case deletion. R² = 0.34; F = 169.56. ^aRef.: Entertainment seekers. ^bRef.: City/suburbs. ^cRef.: Israel. *p < 0.05, **p < 0.01, ***p < 0.001.

Data availability statement

The data that support the findings of this study are available from Galit Nimrod upon reasonable request. Email ID: [email protected]