Olfactory Functioning and Depression: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Research has demonstrated a reduction in olfactory functioning in patients with schizophrenia. This research has led to examination of olfactory functioning in other mental disorders, such as depression. There is a great deal of variation in the results generated from such research, and it remains unclear as to how olfactory functioning is associated with or impacted by depression. METHOD: The current review examined the literature in accordance with PRISMA guidelines in order to generate a better understanding of this relationship and to identify if and what aspects of olfactory processing are altered. Through examination of the available literature from the databases PubMed, Ovid Medline, CINAL, and PsychINFO, 15 manuscripts were selected to determine if there was a difference in olfactory processing-specifically central and peripheral processing-between depressed individuals and non-depressed controls. RESULTS: < 0.05). LIMITATIONS: There is still a lack of definitive conclusions due to variation of which olfactory process was altered. CONCLUSION: Given the differences in the methodology and design of these studies, a possible solution that could eliminate the lack of clarity and reduce variation would be to adhere to a single, thorough methodology that examines and separates central and peripheral olfactory processing. Future research employing a uniform and validated methodology could provide more definitive conclusions as to how and if olfactory functioning is related depression.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".