Handbook of Organization Measurement

Psychological Detachment

construct.psychological_detachment

The complete model → · Measurement plan →

§3The math on what we know

Synthesized priors from the live registry: pooled r, studies (k), total N, top study grade, and heterogeneity. Rows flagged for heterogeneity or single-study evidence are directional, not settled — read them as a central tendency.

What drives psychological detachment

PredictorrkNGradeConfidence
Job Demands−0.25128,507Asingle study
Job Resources+0.10115,010Asingle study

What psychological detachment predicts

OutcomerkNGradeConfidence
Burnout−0.3617,007Asingle study
Job Satisfaction+0.26210,588AI²≈0.96
Contextual Performance−0.1312,106Asingle study
Creativity−0.1112,398Asingle study
Task Performance+0.0914,551Asingle study
Work Engagement−0.01117,259Csingle study

§4As a model node

Where psychological detachment sits when you drop it into a model — what feeds it, what it moves. Read left to right as a small, actionable causal claim.

Inputs (drivers)

  • Job Demands−0.25
  • Job Resources+0.10
Psychological Detachment

Outputs (outcomes)

  • Burnout−0.36
  • Job Satisfaction+0.26
  • Contextual Performance−0.13
  • Creativity−0.11
Composed live from the Principia registry. Effect sizes are synthesized priors (random-effects meta-analysis); grades are the top study-quality grade in each pool; I² is pooled heterogeneity. Source-instrument item wording is withheld pending copyright clearance (PRN-207); the Principia rendering is owned and shown in full.