How can we improve antidepressant adherence in the management of depression? A targeted review and 10 clinical recommendations
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
- Candidate categories
- Meta-epidemiology (narrow)
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: Other designConsensus signal: none
- Genre
- Candidate signal: ReviewConsensus signal: Review
- Teacher disagreement score
- 0.907
- Threshold uncertainty score
- 1.000
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.339 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
Adherence to antidepressants is crucial for optimal treatment outcomes when treating depressive disorders. However, poor adherence is common among patients prescribed antidepressants. This targeted review summarizes the main factors associated with poor adherence, interventions that promote antidepressant adherence, pharmacological aspects related to antidepressant adherence, and formulates 10 clinical recommendations to optimize antidepressant adherence. Patient-related factors associated with antidepressant non-adherence include younger age, psychiatric and medical comorbidities, cognitive impairment, and substance use disorders. Prescriber behavior-related factors include neglecting medical and family histories, selecting poorly tolerated antidepressants, or complex antidepressant regimens. Multi-disciplinary interventions targeting both patient and prescriber, aimed at improving antidepressant adherence, include psychoeducation and providing the patient with clear behavioral interventions to prevent/minimize poor adherence. Regarding antidepressant choice, agents with individually tailored tolerability profile should be chosen. Ten clinical recommendations include four points focusing on the patient (therapeutic alliance, adequate history taking, measurement of depressive symptoms, and adverse effects improved access to clinical care), three focusing on prescribing practice (psychoeducation, individually tailored antidepressant choice, simplified regimen), two focusing on mental health services (improved access to mental health care, incentivized adherence promotion and monitoring), and one relating to adherence measurement (adherence measurement with scales and/or therapeutic drug monitoring).
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.
The record
- Venue
- Brazilian Journal of Psychiatry
- Topic
- Treatment of Major Depression
- Field
- Medicine
- Canadian institutions
- Centre for Addiction and Mental Health
- Funders
- Medical Research CouncilSunovionTeva Pharmaceutical IndustriesNational Health and Medical Research CouncilServierPfizerNational Institutes of HealthH. Lundbeck A/SBeyond BlueAllerganBristol-Myers Squibb
- Keywords
- MedicinePsychoeducationAntidepressantPsychological interventionTolerabilityPsychiatryMental healthMajor depressive disorderDepression (economics)Adverse effectIntensive care medicineCognitionPharmacologyAnxiety
- Has abstract in OpenAlex
- yes