Psychological, Neuropsychological, and Medical Considerations in Assessment and Management of Pain
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Pain is a common yet challenging problem, particularly following traumatic injuries to the head or neck. It is a complex, multidimensional subjective experience with no clear or objective measures; yet it can have a significantly disabling effect across a wide range of functions. Persisting misconceptions owing to mind-body dualism have hampered advances in its understanding and treatment. In this article, a conceptualization of pain informed by recent research and derived from a more useful biopsychosocial model guides discussion of relevant medical, psychological, and neuropsychological considerations. This pain process model explains chronicity in terms of hyperresponsiveness and dysregulation of inhibitory or excitatory pain modulation mechanisms. Related neurocognitive effects of chronic pain are examined and recommendations for minimizing its confounding effects in neuropsychological evaluations are offered. A biopsychosocial assessment model is presented to guide understanding of the myriad of factors that contribute to chronicity. A brief survey of general classes and samples of the more useful pain assessment instruments is included. Finally, this model offers a rational means of organizing and planning individually tailored pain interventions, and some of the most useful pharmacologic, physical, and behavioral strategies are reviewed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it