Geopersonality of Preventable Death in the United States: Anger-Prone States and Opioid Deaths

Concurrent and lagged associations among pain medication use, pain, and negative affect: a daily diary study of people with chronic low back pain

ABSTRACT

People with chronic pain often attempt to manage pain and concurrent emotional distress with analgesic substances. Habitual use of such substances-even when not opioid-based-can pose side effect risks. A negative reinforcement model has been proposed whereby relief of pain and emotional distress following medication consumption increases the likelihood that the experience of elevated pain and distress will spur further medication use. People with chronic low back pain (N = 105) completed electronic diary assessments 5 times/day for 14 consecutive days. Lagged and cross-lagged analyses focused on links between time 1 pain and negative affect (NA) and time 2 analgesic medication use and vice versa. Sex differences were also explored. Primary results were as follows: (1) participants on average reported taking analgesic medication during 41.3% of the 3-hour reporting epochs (29 times over 14 days); (2) time 1 within-person increases in pain and NA predicted time 2 increases in the likelihood of ingesting analgesic medications; (3) time 1 within-person increases in medication use predicted time 2 decreases in pain and NA; and (4) lagged associations between time 1 pain/NA and time 2 medication use were strongest among women. Findings suggest that the use of analgesic medications for many people with chronic pain occurs frequently throughout the day. Results support the validity of a negative reinforcement model where pain and distress lead to pain medication use, which in turn leads to relief from pain and distress.

Mental disorder and opioid overdose: a systematic review

PURPOSE

This systematic review summarizes and presents the current state of research quantifying the relationship between mental disorder and overdose for people who use opioids.

METHODS

The protocol was published in Open Science Framework. We used the PECOS framework to frame the review question. Studies published between January 1, 2000, and January 4, 2021, from North America, Europe, the United Kingdom, Australia, and New Zealand were systematically identified and screened through searching electronic databases, citations, and by contacting experts. Risk of bias assessments were performed. Data were synthesized using the lumping technique.

RESULTS

Overall, 6512 records were screened and 38 were selected for inclusion. 37 of the 38 studies included in this review show a connection between at least one aspect of mental disorder and opioid overdose. The largest body of evidence exists for internalizing disorders generally and mood disorders specifically, followed by anxiety disorders, although there is also moderate evidence to support the relationship between thought disorders (e.g., schizophrenia, bipolar disorder) and opioid overdose. Moderate evidence also was found for the association between any disorder and overdose.

CONCLUSION

Nearly all reviewed studies found a connection between mental disorder and overdose, and the evidence suggests that having mental disorder is associated with experiencing fatal and non-fatal opioid overdose, but causal direction remains unclear.

Exploring the Association Between the "Big Five" Personality Traits and Fatal Opioid Overdose: County-Level Empirical Analysis

BACKGROUND

Opioid-related deaths constitute a problem of pandemic proportions in the United States, with no clear solution in sight. Although addressing addiction-the heart of this problem-ought to remain a priority for health practitioners, examining the community-level psychological factors with a known impact on health behaviors may provide valuable insights for attenuating this health crisis by curbing risky behaviors before they evolve into addiction.

OBJECTIVE

The goal of this study is twofold: to demonstrate the relationship between community-level psychological traits and fatal opioid overdose both theoretically and empirically, and to provide a blueprint for using social media data to glean these psychological factors in a real-time, reliable, and scalable manner.

METHODS

We collected annual panel data from Twitter for 2891 counties in the United States between 2014-2016 and used a novel data mining technique to obtain average county-level "Big Five" psychological trait scores. We then performed interval regression, using a control function to alleviate omitted variable bias, to empirically test the relationship between county-level psychological traits and the prevalence of fatal opioid overdoses in each county.

RESULTS

After controlling for a wide range of community-level biopsychosocial factors related to health outcomes, we found that three of the operationalizations of the five psychological traits examined at the community level in the study were significantly associated with fatal opioid overdoses: extraversion (β=.308, P<.001), neuroticism (β=.248, P<.001), and conscientiousness (β=.229, P<.001).

CONCLUSIONS

Analyzing the psychological characteristics of a community can be a valuable tool in the local, state, and national fight against the opioid pandemic. Health providers and community health organizations can benefit from this research by evaluating the psychological profile of the communities they serve and assessing the projected risk of fatal opioid overdose based on the relationships our study predict when making decisions for the allocation of overdose-reversal medication and other vital resources.