Identifying Work-Related Psychosomatic Stressors in Healthcare Workers: A Qualitative Exploration
Bibliographic record
Abstract
This study aimed to explore and identify the organizational, psychosocial, and behavioral factors contributing to psychosomatic stress among healthcare workers in the United States through an in-depth qualitative analysis of their lived experiences. A qualitative exploratory design was employed to capture healthcare workers’ subjective experiences of psychosomatic stress. Twenty-three participants, including nurses, physicians, technicians, and administrative staff, were purposively selected from hospitals and clinics across the United States. Data were collected through semi-structured interviews conducted face-to-face or via secure online platforms. Interviews were transcribed verbatim and analyzed thematically using NVivo 14 software. Thematic analysis followed the Braun and Clarke (2006) framework, allowing the identification of recurrent patterns and relationships among concepts. Data collection continued until theoretical saturation was reached. Three main themes emerged: (1) Organizational and structural stressors—including work overload, administrative pressure, resource scarcity, and unsafe working conditions—were linked to chronic fatigue, headaches, and sleep disturbances; (2) Psychosocial and emotional stressors—such as compassion fatigue, interpersonal strain, and work–family conflict—contributed to emotional exhaustion and physical symptoms; and (3) Psychosomatic manifestations and coping responses—showing how stress materialized as physical pain, anxiety, and maladaptive behaviors, while some workers adopted adaptive coping strategies like mindfulness and peer support. The findings suggest that psychosomatic stress in healthcare settings stems from systemic imbalance rather than individual vulnerability, confirming strong interdependence between emotional and physiological domains. The study highlights that healthcare workers’ psychosomatic distress is rooted in organizational dysfunction and emotional overload.
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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 | 0.038 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.009 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".