Symptoms of depression and anxiety in patients with thalassemia: Prevalence and correlates in the thalassemia longitudinal cohort
Bibliographic record
Abstract
Thalassemia is an inherited blood disorder that requires lifelong adherence to a complicated and burdensome medical regimen which could potentially impact emotional functioning of patients. The importance of understanding and promoting healthy emotional functioning is crucial not only to psychological well-being, but also to physical health as it has been shown to impact adherence to medical regimens [1-4]. The current study aimed to [1] determine the prevalence of depressive and anxiety symptoms in adolescent and adult patients with thalassemia; and [2] explore possible demographic, medical, and psychosocial correlates of these symptoms in 276 patients (14-58 years old, M age = 27.83; 52% female). Overall, most patients did not report experiencing significant symptoms of anxiety and depression (33% of participants indicated experiencing symptoms of anxiety and 11% symptoms of depression). Females and older patients were more likely to experience these symptoms than males and younger patients. Symptoms of anxiety and depression were positively associated with self-report of difficulty with adherence and negatively associated with quality of life. Given these findings, regular screening for anxiety and depression symptoms could help to identify at-risk individuals to provide them with appropriate psychological support with the goal of improving both emotional and physical health.
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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".