Florida Best Practice Psychotherapeutic Medication Guidelines for Adults With Major Depressive Disorder
Bibliographic record
Abstract
OBJECTIVE: Herein we provide the 2015 update for the Florida Best Practice Psychotherapeutic Medication Guidelines (FPG) for major depressive disorder (MDD). The FPG represent evidence-based decision support for practitioners providing care to adults with MDD. PARTICIPANTS: The consensus meeting included representatives from the Florida Agency for Health Care Administration (FAHCA), advocacy members, academic experts in MDD, and multidisciplinary mental health clinicians, as well as health policy experts. The FAHCA provided funding support for the FPG. EVIDENCE: Evidence was limited to results from adequately powered, randomized, double-blind, placebo-controlled trials; in addition, pooled-, meta-, and network-analyses were included. Recommendations were based on consensus arrived at by the multistakeholder Florida Expert Panel. Articles selected were identified on the electronic search engine PubMed with the dates 2010 to present. The search terms were major depressive disorder, psychopharmacology, antidepressants, psychotherapy, neuromodulation, complementary alternative medicines, pooled-analysis, meta-analysis, and network-analysis. Bibliographies of the identified articles were manually searched for additional citations not identified in the original search. CONSENSUS PROCESS: A consensus meeting comprising all representatives took place on September 25-26, 2015, in Tampa, Florida. Guiding principles (eg, emphasis on the most rigorous evidence for efficacy, safety, and tolerability) were discussed, defined, and operationalized prior to review of extant data. As MDD often pursues a recurrent and chronic course, principles of practice, measurement-based care, and comprehensive assessment and management of overall physical and mental health were emphasized. Evidence supporting pretreatment major depressive episode specifiers (eg, mixed features, anxious distress) and the role of pharmacogenomics (and other biological-behavioral markers) in informing treatment selection were comprehensively discussed. Algorithmic priority was assigned to agents with relatively greater therapeutic index (ie, efficacy) and minimal propensity for safety and tolerability disadvantages. CONCLUSIONS: The updated 2015 FPG provide concise, pragmatic, evidence-based decision support for treatment selection and sequencing for adults with MDD. Principles of practice include measurement-based care, priority to both psychiatric and medical comorbidity, identification of DSM-5-defined specifiers (eg, mixed features), suicide risk assessment, and evaluation of cognitive symptoms. The FPG have purposefully aimed to minimize emphasis on "expert opinion" and instead differentially emphasized extant evidence for pharmacologic treatments.
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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 | 0.018 | 0.066 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".