The lived experience of patients going under hyperbaric oxygen therapy in Saudi Arabia: A phenomenological study
Bibliographic record
Abstract
Hyperbaric oxygen therapy (HBOT) has emerged as an effective treatment or adjunct therapy for various disorders, prioritizing improving oxygen delivery to tissues. This qualitative inquiry aims to explore the psychological experiences of patients undergoing their first hyperbaric session, focusing on the emotional responses and information needs of patients. The study addresses the gap in understanding patient experiences and seeks to contribute to holistic care approaches and improved health outcomes for patients undergoing HBOT. Using a phenomenological-hermeneutical approach, this study engaged 6 participants from KAASH in Taif City who had undergone at least 1 HBOT session. Data were collected through in-person interviews using a semistructured guide, focusing on patients' initial HBOT experiences. Giorgi 4-step method was applied for data analysis, allowing for rich descriptions and thematic categorization of the participants' lived experiences. The analysis is centered around "Walking into the unknown" with emerged subthemes (feeling anxious or being calm; immediate or evolving outcomes; formal orientation and management; success stories and self-learning) organized under 2 revised categories, "Transitioning from fear to reassurance" and "Navigating the path of understanding." The study also highlighted the critical role of healthcare providers in addressing information gaps and enhancing patient preparedness. The findings revealed the importance of comprehensive patient education and effective communication by healthcare providers to alleviate initial fears and improve treatment experiences for HBOT patients. Future research should expand to other regions and include healthcare providers' perspectives to further validate these findings and enhance HBOT practices. Integrating psychological support into the treatment process may also benefit patients, promoting holistic care and improving overall health outcomes.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 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".