Loneliness and Social Isolation Factors Under the Prolonged COVID-19 Pandemic in Japan: 2-Year Longitudinal Study
Bibliographic record
Abstract
BACKGROUND: Worsening loneliness and social isolation during the COVID-19 pandemic have become serious public health concerns worldwide. Despite previous research reporting persistent loneliness and social isolation under repeated emergency declarations and prolonged pandemics, long-term studies are needed to identify the actual conditions of loneliness and social isolation, and the factors that explain them. OBJECTIVE: In this study, 3 web-based surveys were conducted at 1-year intervals during the 2 years after the first state of emergency to examine changes in loneliness and social isolation and the psychosocial factors associated with them in the Japanese population. METHODS: The first survey (phase 1, May 11-12, 2020) was conducted at the end of the first emergency declaration period, the second survey (phase 2, June 14-20, 2021) was conducted at the end of the third emergency declaration period, and the third survey (phase 3, May 13-30, 2022) was conducted when the state of emergency had not been declared but many COVID-19-positive cases occurred during this period. We collected data on 3892 inhabitants (n=1813, 46.58% women; age: mean 50.3, SD 13.4 y) living in the 4 prefectures where emergency declaration measures were applied in phases 1 and 2. A linear mixed model analysis was performed to examine the association between psychosocial variables as explanatory variables and loneliness scores as the dependent variable in each phase. RESULTS: While many psychosocial and physical variables showed improvement for the 2 years, loneliness, social isolation, and the relationship with familiar people deteriorated, and the opportunities for exercise, favorite activities, and web-based interaction with familiar people decreased. Approximately half of those experiencing social isolation in phase 1 remained isolated throughout the 2-year period, and a greater number of people developed social isolation than those who were able to resolve it. The results of the linear mixed model analysis showed that most psychosocial and physical variables were related to loneliness regardless of the phase. Regarding the variables that showed a significant interaction with the phase, increased altruistic preventive behavior and a negative outlook for the future were more strongly associated with severe loneliness in phase 3 (P=.01 to <.001), while the association between fewer social networks and stronger loneliness tended to be more pronounced in phase 2. Although the interaction was not significant, the association between reduced face-to-face interaction, poorer relationships with familiar people, and increased loneliness tended to be stronger in phase 3. CONCLUSIONS: This study found that loneliness and social isolation remained unresolved throughout the long-term COVID-19 pandemic. Additionally, in the final survey phase, these issues were influenced by a broader and more complex set of factors compared to earlier phases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".