Perceptions of Insomnia among an Iranian Population: Causes and Responses
Bibliographic record
Abstract
Background and Objective: People’s perceptions toward insomnia are influenced by the socio-cultural context of their lives. Therefore, the purpose of this study was to investigate beliefs, attitudes, and practices of the participants about causes of insomnia and its management. Materials and Methods: Nineteen participants with a self-reported history of insomnia from the community were recruited in this study. Semi-structured qualitative interviews were conducted. The interviews were recorded and tran-scribed verbatim. The transcriptions were analyzed using thematic analysis. Results: Four themes were identified: underlying causes of insomnia, help-seeking barriers, my coping strategies, and good food - bad drugs. Participant’s reactions to insomnia depended on their broader socio-cultural beliefs. Conclusion: Studying these perceptions and responses in our sample would contribute to better understanding of patients’ therapeutic preferences. It would also help to identify effective socio-cultural beliefs on insomnia self-management methods. Identification of these beliefs and practices also can contribute to adaptation of common insom-nia treatments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".