--- id: wiki-2026-0508-burnout title: Burnout category: 10_Wiki/Topics status: verified canonical_id: self aliases: [Occupational Burnout, Job Burnout, Maslach Burnout] duplicate_of: none source_trust_level: A confidence_score: 0.95 verification_status: applied tags: [mental-health, occupational-health, engineering-management, productivity] raw_sources: [] last_reinforced: 2026-05-10 github_commit: pending tech_stack: language: n/a framework: WHO ICD-11 --- # Burnout ## 매 한 줄 > **"매 chronic workplace stress 의 unsuccessful management 의 result — exhaustion + cynicism + reduced efficacy 의 triad"**. Maslach (1981) 의 measurement 의 origin, WHO ICD-11 (2019) 의 의 occupational phenomenon 의 official 의 classification, 2026 remote/hybrid + AI-augmentation 의 era 에서 의 always-on workload 와 skill-decay anxiety 의 의 acute 의 amplification. ## 매 핵심 ### 매 Maslach 3 dimensions - **Emotional Exhaustion**: depleted, drained, "tank empty" - **Depersonalization / Cynicism**: detachment, callousness toward work / colleagues - **Reduced Personal Accomplishment**: efficacy loss, "nothing matters" ### 매 6 mismatch sources (Maslach & Leiter) - **Workload**: chronic overload - **Control**: autonomy 의 lack - **Reward**: recognition 의 absence - **Community**: relationship breakdown - **Fairness**: unequal treatment - **Values**: misalignment with employer ### 매 응용 1. Engineering team early-warning — commit pattern + on-call burden 의 signal. 2. Recovery protocol — sabbatical, role rotation, scope reduction. 3. Prevention — sustainable pace, buffer time, retrospective culture. 4. Post-incident — psychological safety + blameless review. ## 💻 패턴 ### Maslach Burnout Inventory (MBI) — quick screen ```python from dataclasses import dataclass @dataclass class MBIScore: emotional_exhaustion: int # 0-54 depersonalization: int # 0-30 personal_accomplishment: int # 0-48 (reverse) def risk_level(self) -> str: ee_high = self.emotional_exhaustion >= 27 dp_high = self.depersonalization >= 13 pa_low = self.personal_accomplishment <= 31 score = sum([ee_high, dp_high, pa_low]) return ["Low", "Moderate", "High", "Severe"][score] ``` ### Engineering burnout signals (commit telemetry) ```python import pandas as pd def burnout_signals(commits: pd.DataFrame, lookback_days: int = 60) -> dict: """Detect early burnout from commit timestamps.""" recent = commits[commits["ts"] > pd.Timestamp.now() - pd.Timedelta(days=lookback_days)] return { "weekend_pct": (recent["ts"].dt.dayofweek >= 5).mean(), "after_hours_pct": ((recent["ts"].dt.hour < 9) | (recent["ts"].dt.hour > 19)).mean(), "commit_streak_days": longest_consecutive_day_streak(recent["ts"]), "pr_review_latency_p50": recent["review_latency_h"].median(), } # Trigger: weekend > 25% OR streak > 21d OR after-hours > 20% ``` ### On-call rotation fairness (page burden) ```python def on_call_burden(pages: list[dict], engineer: str, window_days: int = 30) -> dict: """ICE-style page-volume + sleep-disruption tracking.""" e_pages = [p for p in pages if p["engineer"] == engineer] sleep_disrupted = [p for p in e_pages if 0 <= p["hour"] < 6] return { "total_pages": len(e_pages), "sleep_disrupted_pages": len(sleep_disrupted), "comp_time_owed_h": len(sleep_disrupted) * 4, } ``` ### Recovery protocol (manager template) ```python @dataclass class RecoveryPlan: duration_weeks: int scope_reduction_pct: float # e.g. 0.5 = halve scope interventions: list[str] @classmethod def for_severity(cls, level: str) -> "RecoveryPlan": return { "Moderate": cls(2, 0.25, ["scope cut", "no on-call"]), "High": cls(4, 0.5, ["sabbatical week", "no meetings", "therapy"]), "Severe": cls(8, 1.0, ["medical leave", "psychiatric eval"]), }[level] ``` ### Sustainable-pace policy (team-level) ```yaml # .team/sustainable-pace.yaml hours: expected_weekly: 40 hard_cap: 50 on_call: rotation_size_min: 6 weekend_compensation: comp_day paging_threshold: 3_per_shift vacation: minimum_consecutive_days: 5 manager_approval_required: false blackout_periods: [] # no blackouts allowed friday_deploy: false weekend_release: false # except emergency ``` ### Post-incident psychological safety ``` Blameless retrospective questions: 1. What did you observe? (no "you should have") 2. What constraint were you under? 3. What would have helped? 4. What systemic gap surfaced? ``` ## 매 결정 기준 | 상황 | Approach | |---|---| | Early signal (1 dimension high) | Scope reduction + check-in | | Moderate (2 dimensions) | Recovery plan + therapy referral | | Severe (3 dimensions) | Medical leave + role evaluation | | Team-wide pattern | Systemic — review WLB, rotation, scope | | Post-major-incident | Blameless retro + comp time | **기본값**: engineering manager 의 default — quarterly MBI screen + commit telemetry + sustainable-pace policy. ## 🔗 Graph - 부모: [[Neuroergonomics]] - 응용: [[Boundaries]] · [[Habit-Formation]] - Adjacent: [[Anxiety]] · [[Ambition]] · [[Soft-Skills-Development]] ## 🤖 LLM 활용 **언제**: burnout signal detection from telemetry, recovery plan draft, retrospective question generation. **언제 X**: clinical diagnosis 의 substitute 의 X — therapy 의 separate. ## ❌ 안티패턴 - **"Resilience training"-only**: individual fix 의 systemic problem 의 mask. - **Pizza & ping-pong**: perks 의 root cause (workload, control) 의 not-address. - **Burnout = weakness**: stigma 의 의 의 의 reporting 의 suppress. - **Manager 의 "just push through"**: short-term gain 의 long-term attrition. ## 🧪 검증 / 중복 - Verified (Maslach & Leiter *The Truth About Burnout*; WHO ICD-11 QD85). - 신뢰도 A. ## 🕓 Changelog | 날짜 | 변경 | |---|---| | 2026-05-08 | Phase 1 | | 2026-05-10 | Manual cleanup — Maslach 3D, MBI, commit telemetry signals, recovery protocol |