ADHD and Chronic Anhedonia: Antecedents of Treatment-Resistant Depression and Suicidality in Adults
Bibliographic record
Abstract
Depression is a chronic and debilitating disorder. Approximately 280 million people live with depression, and more than 700,000 lives are lost due to suicide each year. Treatment-resistant depression (TRD) is a severe form of depression which is highly correlated with comorbid psychiatric disorders such as attention deficit hyperactive disorder (ADHD) and associated with increased suicidality. Anhedonia, the reduced ability to experience pleasure, is associated with various psychiatric conditions, including ADHD. The theoretical framework for this study was the biopsychosocial model. Depression may be diagnosed in accordance with a defined cluster of symptoms, and/or how symptoms are experienced vary by individuals is dependent on biological, psychological, social, and cultural influences, which may in turn influence response to treatment and predict a diagnosis of TRD and risk of suicidal behaviors. This study was a retrospective cross-sectional quantitative study that used archival data from a large tertiary psychiatric clinic based in Toronto, Ontario, Canada. Logistic regression was used to examine whether ADHD and chronic anhedonia alone or in combination predict treatment resistance and suicidality among depressed adults who are referred for psychiatric consultation. Results from this study demonstrate previously undiagnosed/untreated ADHD and chronic anhedonia were significant antecedents to the development of treatment resistance and suicidality in adults with depression. Positive social change may result by clinicians considering ADHD and chronic anhedonia as key risk factors for TRD and suicidality in this population and prioritize its assessment and management.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".