The Associations Among Self-Isolation During COVID-19,Depressive Symptoms,and Financial Stress: The Moderation of Technology Use for Relationship Maintenance
Restricted accessResearch articleFirst published online April, 2025
The Associations Among Self-Isolation During COVID-19,Depressive Symptoms,and Financial Stress: The Moderation of Technology Use for Relationship Maintenance
The purpose of this study was to examine the moderating effects of technology use for relationship maintenance on the longitudinal associations among self-isolation during COVID-19, depressive symptoms, and financial stress. Participants were 606 (53% female; M age = 20.36, SD = .99; 57% Caucasian) emerging adults. Data were collected in May 2020 (Time 1) and again in November 2020 (Time 2). Findings revealed that increases in self-isolation during COVID-19 related positively to technology use for relationship maintenance, Time 2 depressive symptoms, and Time 2 financial stress. High use of technology for relationship maintenance buffered against the negative effects of self-isolation during COVID-19 on emerging adults’ depressive symptoms and financial stress at Time 2, whereas lower use strengthened the positive relationship. These findings suggest the importance of considering the implications of societal crises or pandemics on emerging adults’ mental health and financial stress.
BeachS.FinchamF.KatzJ. (1998). Marital therapy in the treatment of depression: Toward a third generation of therapy and research. Clinical Psychology Review, 18(6), 635–661. https://doi.org/10.1016/s0272-7358(98)00023-3
2.
CampbellE.MurrayC. (2015). Measuring the impact of technology on couple relationships: The development of the technology and intimate relationship assessment. Journal of Couple & Relationship Therapy, 14(3), 254–276. https://doi.org/10.1080/15332691.2014.953657
CoyneS.StockdaleL.BusbyD.IversonB.GrantD. M. (2011). “I luv u :)!”: A descriptive study of the media use of individuals in romantic relationships. Family Relations, 60(2), 150–162. https://doi.org/10.1111/j.1741-3729.2010.00639.x
GiuntellaO.HydeK.SaccardoS.SadoffS. (2021). Lifestyle and mental health disruptions during COVID-19. PNAS, 118(9), Article e2016632118. https://doi.org/10.1073/pnas.2016632118
7.
GoldsteinH.CarpenterJ.KenwardM. G.LevinK. A. (2009). Multilevel models with multivariate mixed response types. Statistical Modeling, 9(3), 173–197. https://doi.org/10.1177/1471082x0800900301
Holt-LunstadJ.SmithT.LaytonJ. B. (2010). Social relationships and mortality risk: A meta-analytic review. PLoS Medicine, 7(1), e1000316–e1000320. https://doi.org/10.1371/journal.pmed.1000316
11.
JohnsonA.HaighM.BeckerJ.CraigE. A.WigleyS. (2008). College students’ use of relational management strategies in email in long distance and geographically close relationships. Journal of Computer-Mediated Communication, 13(2), 381–404. https://doi.org/10.1111/j.1083-6101.2008.00401.x
12.
KarneyB.StoryL.BradburyT. (2005). Marriages in context: Interactions between chronic and acute stress among newly-weds. In RevensonT.KayserK.BodenmannE. (Eds.), Couples coping with stress: Emerging perspectives on dyadic coping (pp. 13–32). American Psychological Association.
13.
KunarA.NayarK. R. (2020). COVID 19 and its mental health consequences. Journal of Mental Health.
14.
MorganA.BoxallH. (2020). Social isolation, time spent at home, financial stress and domestic violence during the COVID-19 pandemic. Trends and Issues, 609(1), 1–18.
NeustaedterC.GreenbergS. (2012). Intimacy in long-distance relationships over video chat. In Proceedings of the 2012 ACM annual conference on human factors in computing systems (pp. 753–762). Association for Computing Machinery.
17.
NorthernJ. J.O’BrienW. H.GoetzP. (2010). The development, evaluation, and validation of a financial stress scale for undergraduate students. Development, 51(1), 79–92. https://doi.org/10.1353/csd.0.0108
PettitJ. W.RobertsR. E.LewinsohnP. M.SeeleyJ. R.YaroslavskyI. (2011). Developmental relations between perceived social support and depressive symptoms through emerging adulthood: Blood is thicker than water. Journal of Family Psychology, 25(1), 127–136. https://doi.org/10.1037/a0022320
20.
PietromonacoP.CollinsN. (2017). Interpersonal mechanisms linking close relationships to health. American Psychologist, 72(6), 531–542. https://doi.org/10.1037/amp0000129
21.
QuartagnoM.GrundS.CarpenterJ. (2019). jomo: A flexible package for two-level joint modelling multiple imputation. The R Journal, 11(2), 205–228. https://doi.org/10.32614/rj-2019-028
22.
RadloffL. S. (1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1(3), 385–401. https://doi.org/10.1177/014662167700100306
23.
ReknesI.VisockaiteG.LiefoogheA.LovakovA.EinarsenS. V. (2019). Locus of control moderates the relationship between exposure to bullying behaviors and psychological strain. Frontiers in Psychology, 10, Article 1323. https://doi.org/10.3389/fpsyg.2019.01323
24.
RezvanP. H.LeeK. J.SimpsonJ. A. (2015). The rise of multiple imputation: A review of the reporting implementation of the method in medical research. BMC Medical Research Methodology, 15(1), 30–43.
25.
SchaferJ. L. (1997). Analysis of incomplete multivariate data. Chapman and Hall.
26.
SchaferJ. L.YucelR. M. (2002). Computational strategies for multivariate linear mixed- effects models with missing values. Journal of Computation and Graphical Statistics, 11(2), 437–457. https://doi.org/10.1198/106186002760180608
27.
SeligmanM. E. P. (1975). Helplessness: On depression, development, and death. W H Freeman/Times Books/ Henry Holt & Co.
SterneJ. A.WhiteI. R.CarlinJ. B.SprattM.RoystonP.KenwardM. G.WoodA. M.CarpenterJ. R. (2009). Multiple imputation for missing data in epidemiological and clinical research: Potential and pitfalls. BMJ, 338(1), b2393. https://doi.org/10.1136/bmj.b2393
30.
ValentineG. (2016). Globalizing intimacy: The role of information and communication technologies in maintaining and creating relationships. Women Studies Quarterly, 34(1), 365–393.
