Synergistic Impacts of online and offline social participation on older adults’ subjective well-being: evidence from the Canadian Longitudinal Study on Aging

ABSTRACT

This study investigates the synergistic impacts of online and offline social participation on older adults’ subjective well-being outcomes. By drawing on the socio-emotional selectivity perspective, we conduct a cohort analysis using the Canadian Longitudinal Study on Aging data and find that while online participation alone may increase loneliness, engaging in offline participation will make online participation beneficial. Loneliness serves as a mediating mechanism such that engaging in both online and offline social participation can indirectly enhance satisfaction with life by reducing loneliness. We further find a significant moderating effect of social support, which mitigates the negative impact of loneliness on life satisfaction.

KEYWORDS:

• CLSA
• online social participation
• ageing
• social support
• loneliness
• national survey

Acknowledgments

This research was made possible using the data/biospecimens collected by the Canadian Longitudinal Study on Aging (CLSA). Funding for the Canadian Longitudinal Study on Aging (CLSA) is provided by the Government of Canada through the Canadian Institutes of Health Research (CIHR) under grant reference: LSA 94473 and the Canada Foundation for Innovation, as well as the following provinces, Newfoundland, Nova Scotia, Quebec, Ontario, Manitoba, Alberta, and British Columbia. This research has been conducted using the CLSA dataset [insert Dataset name and version number here], under Application Number [insert your CLSA project number here]. The CLSA is led by Drs. Parminder Raina, Christina Wolfson and Susan Kirkland.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Disclaimer

The opinions expressed in this manuscript are the author’s own interpretation of the results and do not reflect the views of the Canadian Longitudinal Study on Aging.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/0960085X.2023.2229283

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Notes

1. As shown in the model, we use a longitudinal design to align with the socio-emotional selectivity perspective and better reflect the nature of the phenomenon. A longitudinal design is recommended for disentangling causal effects and understanding enduring influences over time. Our primary outcome of interest, life satisfaction, requires longitudinal experience. This approach allows us to theorise the longitudinal impacts of older adults’ online and offline social participation.

2. Medical Outcomes Study (MOS) is one of the most widely accepted scale to access various dimensions of social support. After the scale’s initial development by Sherbourne and Stewart (1991), numerous studies have adapted it, translated it into various languages, and tested its psychometric properties (e.g., D. Anderson et al., 2005; Arredondo, 2012; Holden et al., 2014). Besides the support for positive social interactions (the dimensions we use in this study), the other three dimensions in MOS are emotional and informational support (or attachment and guidance), tangible support (or material aids), and affectionate support (or expression of love). Although we do not theorise these three dimensions, they are statistically controlled in the empirical model.

3. Statistics Canada 2022 https://www.statcan.gc.ca/en/subjects-start/older_adults_and_population_aging

4. https://agewell-nce.ca/archives/10884.

5. CLSA study surveyed adults with age above 45. To align with our research interest on older adults, we excluded the sample younger than 55.

6. The incomplete data falls within one of the following conditions: 1) missing value is present on the variables used in our study; 2) participants refused to answer a question for the variables used in our study; and 3) participants do not know the answer to a question.

7. While the average score approach is commonly used, its potential limitations have been discussed in the literature. Therefore, we conducted additional analysis using the weighted composite score approach suggested in Hair et al. (2017). The results are consistent with those obtained from the average score approach.

8. CLSA publications have also reported test-retest reliability for specific constructs. Although the reported constructs are not necessarily used in our study, they provide additional evidence regarding the reliability and validity of the CLSA survey in general. A sample of these reports includes Beauchamp et al. (2021), Gilsing et al. (2018), and Dogra et al. (2018).

9. We thank the anonymous reviewer for this suggestion.

10. Model #4, #9, #21 are ID numbers used in the SPSS Process documentation by Hayes (2017).

11. Due to the binary quantification of PSP, less variance existed in this measure. As such, two levels, namely low and high PSP were extracted from the data.