Since the end of 2019, the global pandemic of coronavirus disease 2019 (COVID-19) has changed our daily life as well as our patterns of patient management. Although vaccinations and possible herd immunity have generated hope for overcoming COVID-19, social isolation including social distancing, quarantine and lockdowns will continue until therapeutics for COVID-19 are available.

Good social relationships, however, were found to have a positive effect on cardiovascular disease, psychological disease, as well as cognitive dysfunction. Although social isolation was associated with reduced COVID-19 transmission, it can affect the poor prognosis for patients with various underlying diseases, and social isolation increases the risk of deterioration of physical function and cognitive dysfunction.1-4

Mild cognitive impairment (MCI), which is known as a pre-dementia stage, can often be reverted to normal cognition. Estimates of improvement or reversion from MCI back to normal cognition have been quite varied, ranging from 6% to 53%, depending in part on diagnostic criteria or duration of follow-up.5, 6 Clinically, the identification of factors associated with reversion from MCI to normal cognition is very important. These factors include better baseline cognitive function, more mental activities, better physical condition, less brain atrophy, some MCI features and less informant-based memory complaints.6

Although social relationships have been restricted in many ways during the COVID-19 pandemic, substitutive contactless interactions are available. Thus, we evaluated the association of reversion from MCI with social networks including online and technology-assisted communications. Of the total 292 participants who were diagnosed with MCI at baseline from November 2019, we retrospectively evaluated 258 participants (43% male) aged 70.5 ± 9.7 years who were subsequently classified with either normal cognition (n = 44) or repeat diagnosis of MCI (n = 214) after about 18.0 ± 0.6 months (34 participants who progressed from MCI to dementia were excluded). The associations with reversion were investigated for baseline factors that included demographics (age, sex and education), patient-based cognitive and psychological factors (Montreal Cognitive Assessment [MoCA], Global Deterioration Scale, Geriatric Depression Scale and instrumental activities of daily living), informant-based information (Informant Questionnaire on Cognitive Decline in the Elderly [IQCODE] and Neuropsychiatric Inventory), and MCI features (amnestic MCI vs. non-amnestic MCI or multi-domain MCI vs. single-domain MCI), and longitudinal changes between baseline and follow-up in social networks were measured by the modified Berkman–Syme Social Network Index (SNI),4 a composite measure of various types of social connections including online and technology-assisted in-person or group communication or activities, with a higher score indicating a greater network. The study was approved by the Institutional Ethical Review Board (2021AS0131).

The results of the logistic regression analyses are presented in the Fig. 1. To increase the power to detect associations and to anticipate the likely possibility from using the partial information available, we generated 10 imputed values for each participant with missing data, yielding 10 complete datasets. With complete-case and multiple imputation, both analyses revealed more likely in participants with the higher MoCA score and increased SNI score and less likely in participants with impaired IQCODE result and multiple-domain MCI.

Three logistic regression models for odds of reversion from MCI to normal cognition. CI, confidence interval; f.up, follow-up; GDpS, Geriatric Depression Scale; GDS, global deterioration scale; IADL, instrumental activities of daily living; IQCODE, Informant Questionnaire on Cognitive Decline in the Elderly; MCI, mild cognitive impairment; MoCA, Montreal Cognitive Assessment; NPI, neuropsychiatric inventory; OR, odds ratio; SNI, social network index. Bold numbers indicate statistical significance (P < 0.05). aGray rhombus and line in plot were represented as OR and 95% CI in univariable regression analysis. Because there were some missing variables, numbers of available data in univariable analysis were 251 in IQCODE, 247 in GDpS, 208 in NPI, 252 in SNI baseline, 257 in SNI f.up, and 252 in SNI change, but the number of the other variables was 10 complete datasets. bBlack circle and line in plot represent OR and 95% CI in multivariable regression analysis with backward-elimination methods with probability for removal of variables with P < 0.20, which was evaluated on the complete dataset (n = 174). cBlack square and line in plot represent OR and 95% CI in multivariable regression analysis on the multiple imputation process (n = 258, 10 complete datasets).

Our results should be interpreted with caution given the disadvantages associated with retrospective analyses with a relatively small sample size. However, when social factors are considered, which is a modifiable factor, an increased social network was consistently associated with aspects of reversion from MCI as well as better baseline cognitive function, less informant-based memory complaints and less multiple impaired domains of cognition.

In conclusion, an increased social network may play important roles in reversion from MCI to normal cognition. The many limitations in social networking during the era of the COVID-19 pandemic cause decreased interactions with neighbors, relatives and acquaintances.1 However, one of the practical recommendations for the management of cognitive dysfunction during the COVID-19 pandemics includes promotion of social networks should be continued through online and technology-assisted methods.1, 2 A social network is one of the important potential modifiable factors for the prognosis of MCI, suggesting that continuous social networking should be considered for patients with cognitive dysfunction.

The author declares no conflict of interest.

Anonymized data related to the current article are available and will be shared by request from any qualified investigator. Persons interested in obtaining access to the data should contact the corresponding author (M.H.P.).