Effect of Aromatherapy Massage on Depression and Anxiety of Elderly Adults: a Randomized Controlled Trial
Bibliographic record
Abstract
Introduction: This study investigated the effect of aromatherapy massage with lavender, chamomile, and rosemary oils on the depression and anxiety of elderly adults living in nursing homes. Methods: This randomized controlled trail was conducted on elderly adults living in nursing homes in Kerman, Iran. Through convenience sampling, 38 elderly adults were recruited and assessed using demographic questionnaire and Hospital Anxiety Depression Scale (HADS), respectively. Then, elderly adults were randomly allocated to either a control (19) or an intervention (19) group through block randomization. Elderly adults in the intervention group received aromatherapy massage using lavender, chamomile, and rosemary. Each massage session lasted 20 min and was performed three times per week for two three-week periods with an intervening one-week break, while their counterparts in the control group solely received routine nursing homes care services. HADS Scale completed with repeated measurements before the intervention, at the end of the third week, at the beginning of the fifth week and at the end of the seventh week. Results: According to the results, mean anxiety in the intervention group went from 11.9 ± 4 to 6.26 ± 3.38 (p <.0001), and the mean depression went from 9.94 ± 3.2 to 4.15 ± 2.14, indicating that anxiety and depression were significantly reduced com-pared with before intervention (p <.0001). Conclusion: Aromatherapy massage with lavender, chamomile, and rosemary oils is effective in significantly reducing anxiety and depression of elderly adults living in the nursing homes.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".