Children's perspectives on friendships and socialization during the COVID‐19 pandemic: A qualitative approach
Bibliographic record
Abstract
BACKGROUND: Good quality friendships and relationships are critical to the development of social competence and are associated with quality of life and mental health in childhood and adolescence. Through social distancing and isolation restrictions, the COVID-19 pandemic has had an impact on the way in which youth socialize and communicate with friends, peers, teachers and family on a daily basis. In order to understand children's social functioning during the pandemic, it is essential to gather information on their experiences and perceptions concerning the social changes unique to this period. The objective of this study was to document children and adolescents' perspectives regarding their social life and friendships during the COVID-19 pandemic, through qualitative interviews. METHODS: Participants (N = 67, 5-14 years) were recruited in May and June 2020. Semi-structured interviews were conducted via a videoconferencing platform. A thematic qualitative analysis was conducted based on the transcribed and coded interviews (NVivo). RESULTS: The upheavals related to the pandemic provoked reflection among the participants according to three main themes, each of which included sub-themes: (1) the irreplaceable nature of friendship, (2) the unsuspected benefits of school for socialization and (3) the limits and possibilities of virtual socialization. CONCLUSIONS: The collection of rich, qualitative information on the perspectives of children and adolescents provides a deeper understanding of the consequences of the pandemic on their socialization and psychological health and contributes to our fundamental understanding of social competence in childhood.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".