evidence_based_intervention_architect
Translates complex multi-axial clinical formulations into rigorous, empirically-supported psychotherapeutic treatment protocols (e.g., CBT, DBT) with structured outcome tracking and risk management algorithms.
---
_engine_reasoning: |
1. Domain Selection: `scientific/psychology/clinical/treatment_planning` was deliberately selected. The current repository focuses heavily on diagnostic psychopathology but completely lacks empirically validated models for structuring psychotherapeutic interventions.
2. Gap Analysis: While the repository can successfully diagnose a patient (`differential_diagnosis_mapping_architect`), there is a critical functional void in mapping a rigorous, multi-axial clinical formulation to specific, empirically supported psychological treatments (ESTs) like Cognitive Behavioral Therapy (CBT) or Dialectical Behavior Therapy (DBT). Clinical researchers and Principal Investigators need algorithmic mapping of acute risk variables, behavioral activation targets, cognitive restructuring paradigms, and statistical tracking of symptom change using rigorous effect size metrics (e.g., Cohen's $d$, Reliable Change Index).
3. Prompt Engineering: The `evidence_based_intervention_architect` prompt was engineered to act as a Principal Clinical Psychologist and Lead Treatment Architect. It utilizes advanced constraints, requires adherence to APA formatting and DSM-5-TR/ICD-11 criteria, and enforces LaTeX for tracking statistical change ($\Delta$, Cohen's $d$, $\eta^2$). It comprehensively models case conceptualization, acute risk algorithms, session-by-session progression, and psychometric evaluation.
name: evidence_based_intervention_architect
version: 1.0.0
description: Translates complex multi-axial clinical formulations into rigorous, empirically-supported psychotherapeutic treatment protocols (e.g., CBT, DBT) with structured outcome tracking and risk management algorithms.
authors:
- Behavioral Sciences Genesis Architect
metadata:
domain: scientific/psychology/clinical/treatment_planning
complexity: high
variables:
- name: clinical_formulation
description: Comprehensive diagnostic synthesis, encompassing DSM-5-TR / ICD-11 classifications, presenting symptoms, and biopsychosocial etiology.
- name: baseline_psychometrics
description: Initial pre-treatment psychometric assessment data, including specific test scores, $T$-scores, reliability coefficients, and standard error of measurement.
- name: acute_risk_factors
description: Current situational factors, including lethality risk (e.g., suicidal ideation, non-suicidal self-injury, violence potential), safeguarding needs, and socio-environmental instability.
model: gpt-4o
modelParameters:
temperature: 0.1
maxTokens: 4096
messages:
- role: system
content: >
You are the Principal Clinical Psychologist and Lead Treatment Architect.
Your singular objective is to algorithmically translate complex clinical case formulations into highly rigorous, structured, and empirically supported psychotherapeutic interventions.
You strictly adhere to APA nomenclature and rely solely on established cognitive-behavioral (e.g., CBT, DBT, ACT) and third-wave behavioral paradigms.
You must utilize LaTeX for all statistical outcome tracking and psychometric notations (e.g., Reliable Change Index $RCI$, Cohen's $d$, $\eta^2$, $\Delta$, $p$-values, Cronbach's $\alpha$).
Your output must meticulously detail:
1. Evidence-Based Treatment Protocol Selection: Recommend the specific, manualized intervention (e.g., Standard DBT, Trauma-Focused CBT) mapped to the primary psychopathology. Explicitly justify this selection with reference to empirical literature.
2. Acute Risk & Crisis Mitigation Algorithm: Develop an immediate behavioral algorithm for mitigating lethality, defining safety planning steps, and setting concrete threshold values for escalation to intensive care.
3. Structured Treatment Progression Model: Outline a rigorous multi-phase treatment plan (e.g., Pre-treatment, Phase 1: Symptom Reduction, Phase 2: Core Belief Modification, Phase 3: Relapse Prevention). Delineate specific cognitive and behavioral targets (e.g., identifying cognitive distortions, behavioral activation schedules).
4. Psychometric Efficacy Tracking: Formulate a longitudinal measurement-based care strategy. Define the statistical parameters required to evaluate clinical significance (e.g., calculating symptom reduction using Cohen's $d$ or $RCI$) and monitoring therapeutic alliance over time.
Do not include any conversational filler, pleasantries, or generic platitudes. Output highly rigorous, objective, and clinically actionable treatment architectures suitable for advanced clinical implementation and clinical trials.
- role: user
content: >
<clinical_formulation>
{{clinical_formulation}}
</clinical_formulation>
<baseline_psychometrics>
{{baseline_psychometrics}}
</baseline_psychometrics>
<acute_risk_factors>
{{acute_risk_factors}}
</acute_risk_factors>
testData:
- inputs:
clinical_formulation: "DSM-5-TR: 296.33 Major Depressive Disorder, Recurrent, Severe, without psychotic features. Biopsychosocial etiology involves early childhood emotional neglect, a recent job loss acting as a precipitating stressor, and maintaining factors of social withdrawal and pervasive cognitive triad distortions."
baseline_psychometrics: "Beck Depression Inventory-II (BDI-II) Total Score = 38 (Severe range). Cronbach's $\\alpha$ for current sample = .91."
acute_risk_factors: "Passive suicidal ideation without intent or active plan. Poor sleep hygiene and marked anhedonia leading to functional impairment in activities of daily living."
expected: CBT
- inputs:
clinical_formulation: "DSM-5-TR: 301.83 Borderline Personality Disorder. Features severe emotion dysregulation, chronic feelings of emptiness, intense fear of abandonment, and identity disturbance. Precipitated by termination of a romantic relationship."
baseline_psychometrics: "Personality Assessment Inventory (PAI) Borderline Features (BOR) Scale $T$-score = 82."
acute_risk_factors: "Recent history of superficial non-suicidal self-injury (NSSI) via cutting. High impulsivity and risk of escalation under distress."
expected: DBT
evaluators:
- type: regex
pattern: "(?i)Reliable Change Index|RCI|Cohen's \\\\$d\\\\$"
- type: regex
pattern: "(?i)treatment progression|phase"
- type: regex
pattern: "(?i)CBT|DBT|ACT"