Well-Being in Sales: The Role of Non-Financial Rewards in Mental Health and Mental Illness
Bibliographic record
Abstract
Our research examines the effects of non-financial rewards on sales professional’s psychological well-being—understood as the presence of mental health and the absence of diagnosed mental illness. Building on the Job Demands-Resources and Self-determination theories, we argue that non-financial rewards act as job resources, creating psychological capital that helps buffer the daily job demands’ struggles of people in sales. Using data extracted from 13,564 people working in sales-related roles across 36 countries, we find that non-financial rewards do not uniformly mitigate the effects of job demands on well-being, leading to different moderating effects on mental health versus mental illness. In addition to this, unexpectedly, we find that some non-financial rewards combined with certain job demands can potentially increase the risk of mental illness. These insights are critical for the design of sales well-being preventive and reactive interventions and future sales research adopting the Job Demands-Resources in combination with Self-determination theory.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".