Handbook of Organization Measurement
Openness to Experience Measures
construct.openness_to_experience_measures
§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 openness to experience measures
| Predictor | r | k | N | Grade | Confidence |
|---|---|---|---|---|---|
| Job Complexity | +0.34 | 1 | 50 | A | single study |
What openness to experience measures predicts
| Outcome | r | k | N | Grade | Confidence |
|---|---|---|---|---|---|
| Burnout | +0.24 | 1 | 50 | A | single study |
§4As a model node
Where openness to experience measures 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 Complexity+0.34
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Openness to Experience Measures
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Outputs (outcomes)
- Burnout+0.24