Symptoms of Anxiety and Depression Among Teens and Adults in the Thalassemia Longitudinal Cohort Study.
Bibliographic record
Abstract
Abstract Abstract 555 Background and Significance: Individuals with chronic medical conditions are vulnerable to symptoms of anxiety and depression. Promoting healthy emotional functioning is important not only to psychological well-being, but also to physical health as it has been shown to impact adherence to medical regimens. Thalassemia is an inherited blood disorder which requires lifelong intervention and may be associated with treatment and disease-related complications that impact both the length and quality of life for most who are affected. While several studies have examined the prevalence of anxiety and depressive symptoms in patients with thalassemia, most have been conducted with small, homogeneous samples of children. In addition, the one study which examined psychological adjustment in adults included patients from only one medical center (Messina et al.; Intern Emerg Med, 3:339, 2008). Further, few studies have examined demographic, medical, and psychosocial variables possibly correlated with the occurrence of these symptoms. Understanding the factors that are related to the experience of depressive and anxiety symptoms may help us to identity individuals at risk and help in developing targeted interventions. 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. Specifically, we hypothesized that (1) anxiety and depressive symptoms in this sample would be similar to the rates of these symptoms in individuals diagnosed with other chronic medical conditions and higher than in individuals without chronic medical conditions; (2) symptoms of depression and anxiety would be inversely correlated with measures of adherence (i.e., subjective report, ferritin); and (3) symptoms of depression and anxiety would be inversely correlated with functional health and well-being. Method: Data on quality of life and mental health self assessments were collected as part of the Thalassemia Longitudinal Cohort (TLC), a multi-center multinational study conducted by the NHLBI-sponsored Thalassemia Clinical Research Network. The current analysis included 281 participants (14-58 years old, M age=27.83; 52% female) who completed the Hospital Anxiety and Depression Scale (HADS), a 14-item questionnaire examining presence of anxiety and depression symptoms. Participants also completed a measure of functional health and well-being (SF-36), as well as questions related to adherence to their medical regimen. In addition, as part of the larger TLC study, medical data such as ferritin and method of chelation was collected. Results: 32% of participants indicated experiencing at least mild symptoms of anxiety and 11% at least mild symptoms of depression. While these rates are higher than rates of symptoms of depression and anxiety found in the general population, they are similar to rates found in other groups with chronic illness (e.g., diabetes). Older age, female gender, and chelation with deferoxamine (as compared to deferasirox) were factors that were significantly associated with anxiety and/or depression and were statistically controlled for in subsequent analyses. Symptoms of depression, but not anxiety, were inversely correlated with subjective reports of adherence (p<.05), although not with ferritin levels. However, a significant correlation in the expected direction between subjective report of adherence and ferritin was found (p<.01). Finally, as hypothesized, both symptoms of depression and anxiety were significantly and negatively correlated with functional health and well-being (p<.0001). Conclusion: While the majority of patients with thalassemia do not report significant symptoms of anxiety and depression, the rates are higher than in the general population. Given that symptoms of anxiety and depression were associated with poor adherence and lower functional health and well-being, regular screening for anxiety and depression symptoms could help to identify at risk individuals in order to provide them with appropriate psychological support with the goal of improving both emotional and physical health. Disclosures: Porter: Novartis: Research Funding. Thompson:Novartis: Research Funding. Neufeld:Novartis: Research Funding.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| 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".