Consumer escapism: Scale development, validation, and physiological associations
Bibliographic record
Abstract
The notion that individuals use consumption to escape unpleasant states is of great interest to both marketing researchers and managers, yet no measurement scale for consumer escapism exists. Moreover, escapism is theoretically linked to aversive physiological reactions that could be measured through smart devices, yet no empirical evidence backs up this claim. By integrating different theoretical perspectives on consumer escapism, we develop and validate a three-factor, nine-item Consumer Escapism Scale that consists of reality detachment, cognitive distraction, and anticipated relief. Six studies including two field studies provide scale purification tests, discriminant and nomological validity, experimental and predictive validity, and evidence for a significant association between the proposed measurement scale and aversive physiological reactions. Our findings equip managers with both self-report and physiological metrics to measure consumers’ desire to escape, and inform actionable strategies on when to market such escapes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".