Journal
FRONTIERS IN PSYCHOLOGY
Volume 12, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fpsyg.2021.663890
Keywords
pain rating; interpretation of pain; clinical reporting; self-report; attribution bias
Categories
Funding
- Department of Psychological and Brain Sciences
- College of Liberal Arts at Texas AM University
- NSF Graduate Research Fellowship
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Factors such as personal motivations, trust in providers, and financial concerns impact how individuals report pain. People may overstate pain to receive better medical responses, but some choose not to exaggerate their pain. Biases in perception of one's own and others' pain may lead to distortion in pain reporting.
Complex factors influence how people report and interpret numerical pain ratings. Such variability can introduce noise and systematic bias into clinical pain assessment. Identification of factors that influence self-rated pain and its interpretation by others may bolster utility of these scales. In this qualitative study, 338 participants described motivations for modulating their own pain reports relative to a numerical pain scale (0-10), as well as perceptions of others' pain reporting modulation. Responses indicated that people over-report pain to enhance provider belief/responsiveness or the likelihood of pain relief, and out of fear of future pain or potential illness. Concerns of how one's pain affects and is perceived by others, and financial concerns motivated pain under-reporting. Unprompted, many participants reported never modulating their pain ratings, citing trust in providers and personal ethics. Similar reasons were assumed to motivate others' pain ratings. However, participants often attributed others' over-reporting to internal causes, and their own to external. This bias may underlie common assumptions that patients over-report pain for nefarious reasons, distort interpretation of pain reports, and contribute to pain invalidation. Recognition of patient concerns and one's own personal biases toward others' pain reporting may improve patient-provider trust and support precision of numerical pain ratings.
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