Moral Distress Among Consumer Health Information Professionals: An Exploratory Study
Bibliographic record
Abstract
Objectives – In recent years, moral distress has become a topic of interest among health professionals. Moral distress is most commonly described in the nursing literature, and refers to a situation wherein an individual knows the correct action to take, but is constrained from doing so. While moral distress differs from the classic ethical dilemma, in recent years practitioners and theorists have advocated for a broadening of the definition of moral distress. To date, no study has examined another group of individuals who frequently interact with patients and who may be constrained by the confines of their role - Consumer Health Information Professionals (CHIPS). The objective of this study was to determine if CHIPS experience moral distress and/or ethical dilemmas, and to determine what, if any, coping strategies these individuals have developed. Methods – This study employed a mixed methods approach. Quantitative data were gathered via an online survey which was distributed to relevant consumer health information professional electronic mail lists. The survey contained demographic questions and a series of questions related to potential discomfort within the context of work as a consumer health information professional. Qualitative data were also gathered through phone interviews with CHIPS. Interview questions included the participant’s definition of moral distress, professional experiences with moral distress, and any coping strategies to manage said distress. Results – The authors received 213 survey responses. To test whether any of our demographic variables help to explain survey response, we used STATA to calculate Pearson correlation coefficients. Individuals who were more likely to experience discomfort in their occupation as CHIPS included individuals with less experience and individuals who identified as Black and Latinx. Interview data indicated that participants most commonly experienced ethical dilemmas related to censorship, providing prognosis information, and feeling constrained by institutional policies. Few interview participants described scenarios that reflected moral distress. Conclusions – CHIPS do not appear to experience moral distress, at least according to its most narrow definition. CHIPS do consistently experience distinct ethical dilemmas, and the most durable patterns of this phenomenon appear to be related to experience level and racial identity. In recent years, researchers have raised calls to broaden the definition of moral distress from its narrow focus on constraint to include uncertainty, and CHIPs do experience moral uncertainty in their work. Further study is needed to determine how to best address the impacts of discomfort caused by ethical dilemmas among these groups.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".