Exploring Definitions and Experiences of Loneliness: Insights From Interviews With Children and Early Adolescents in Italy
Bibliographic record
Abstract
ABSTRACT Loneliness represents a negative feeling that arises when individuals perceive a discrepancy between actual and desired social relationships. The present study explored the meanings and personal experiences of loneliness in children and early adolescents in Italy. Participants included 139 children and early adolescents aged 8–14 years ( M = 10.76 years, SD = 1.71; 80 girls, 57.6%) who completed a semi‐structured interview online. Different dimensions emerged from the coding process, providing evidence of the multidimensional nature of loneliness, defined and experienced through different dimensions (e.g., cognitive, emotional, and regarding interpersonal context). Results from descriptive analyses (i.e., frequencies and percentages) showed that most of the participants defined loneliness in terms of physical separation from others. Also, participants discussed loneliness in relation to both their family and peers. Some children and adolescents expressed experiencing loneliness voluntarily. Children and early adolescents reported to feel sadness, anger, and other emotions as boredom, happiness, and fear in association with loneliness. Finally, we examined gender and grade differences between the dimensions with a series of chi‐square tests and ANOVAs. Results revealed that primary school children and boys defined and experienced loneliness using the physical separation dimension. Middle‐school children defined loneliness using the cognitive dimension more frequently. Overall, the present study offers a richer understanding of the meanings and experiences of loneliness in youth and highlights the importance of considering developmental, gender, and cultural factors when studying loneliness.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".