Opioid craving and opioid-related problems in the daily lives of patients with chronic pain who are prescribed long-term opioid therapy: Exploration using ambulatory assessment methods
Bibliographic record
Abstract
Opioid medications are commonly prescribed to patients with chronic pain, but the use of opioids can be accompanied by problems such as opioid misuse and addiction. Evidence indicates that opioid craving (i.e., the desire and/or urge to use opioids) can increase patients' propensity to misuse opioids. Considerable research has been conducted on the determinants of opioid craving among illicit opioid users, but our understanding of factors contributing to craving among patients with chronic pain who are prescribed opioids has lagged behind. There is reason to believe that symptoms of physical dependence, pain, and psychological distress could contribute to opioid craving, but this needs to be further explored among patients with chronic pain. Little is also known on the contribution of biological factors to opioid craving in this population. Upregulation of the hypothalamic-pituitary-adrenal (HPA) axis has been linked to opioid craving among illicit opioid users, but the contribution of HPA axis activity to opioid craving among medical users of opioids has remained unexplored.The present thesis includes three empirical studies that relied on observational, micro-longitudinal study designs and the use of ambulatory assessment methods. Manuscript 1 explored the day-to-day association between symptoms of physical dependence (i.e., opioid withdrawal symptoms) and opioid craving over 14 days. Results indicated that day-to-day elevations in opioid withdrawal symptoms were associated with heightened opioid craving, and that this association was mediated by negative affect (NA) and catastrophic thinking. These findings suggest that opioid withdrawal symptoms might contribute to increases in negative affect and catastrophic thinking, which in turn might lead to heightened reports of opioid craving. Building upon these findings, Manuscript 2 relied on ecological momentary assessment (EMA) procedures for 10 consecutive days to examine the factors contributing to intra-day fluctuations in opioid craving. The factors contributing to daily opioid intake and opioid misuse were also examined. Findings revealed that intra-day elevations in opioid withdrawal symptoms, pain intensity and catastrophizing significantly contributed to opioid craving. Results also indicated that higher opioid craving levels were associated with greater opioid intake, even after accounting for patients’ opioid withdrawal symptoms, pain intensity, and psychological states. Higher reports of catastrophizing and opioid craving were associated with a greater likelihood of misusing opioids, but these associations were no longer significant when accounting for patients’ levels of pain and other daily variables. Finally, Manuscript 3 relied on EMA procedures involving a combination of self-reported diaries and saliva sampling to examine whether intra-individual variations in HPA axis (i.e., cortisol) activity contributed to patients’ reports of opioid craving. The interactive effects of HPA axis activity and psychological states on opioid craving were also examined. In this study, we found that the association between negative affect and opioid craving was stronger during concurrent elevations in cortisol. These results suggest that upregulation in HPA axis activity might amplify the effects of psychological states, such as NA, on opioid craving. Taken together, findings from the present thesis provide valuable new insights into the factors that contribute to opioid craving, opioid intake, and opioid-related problems among patients with chronic pain who are prescribed long-term opioid therapy. The present thesis might also stimulate further research on the psychological and biological determinants of opioid craving in this population. Importantly, findings from the present thesis could inform the nature of interventions aimed at preventing or reducing opioid-related harms among patients with chronic pain
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".