Investigating Mental Health During the COVID-19 Pandemic : A Conceptual Analysis of Thwarted Belongingness, Loneliness, and Social Isolation
Bibliographic record
Abstract
The coronavirus disease 2019 (COVID-19) has brought unprecedented challenges to global populations since its outbreak in December 2019. Given the strict quarantine mandates, many researchers and health experts have been concerned about the unknown immediate and long-term psychological effects of physical distancing. This article investigates this phenomenon by evaluating the constructs thwarted belongingness, social isolation, and loneliness through the method of conceptual analysis. First, linguistic attention is given to the clarification of conceptual overlap, vagueness, and inconsistencies in construct meaning and application. Second, phenomenological descriptions are used to examine the congruity between psychological constructs and lived experience during the pandemic. Third, the novel inclusion of identity and the significance of space are applied to ascertain the contextual dimensions and mechanisms of quarantine measures and physical distancing. Lastly, this article concludes by discussing the valuable role that philosophy and conceptual analysis have in the field of psychology and COVID-19 research.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.030 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| 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".