Medically unexplained pain and suicidal ideation among US adults

BACKGROUND

Chronic pain is an established risk factor for suicide. Pain syndromes are complex to diagnose, particularly in cases with limited evidence of injury or pathology. The goal of this study is to assess whether pain of unknown origin (i.e., medically-unexplained pain, MUEP) is more strongly associated with suicide behaviors than pain with a diagnostic explanation.

METHODS

Data comes from the National Comorbidity Survey-Replication, a nationally-representative sample of US adults. Analysis was limited to participants with a lifetime history of any type of chronic pain (n = 3421), which were categorized as having medically-explained pain (MEP, e.g., pain due to a specific health condition or resulting from an injury identified in an x-ray) or MUEP. Logistic regression, using survey procedures, was used to assess the relationship between lifetime MUEP and lifetime history of suicidal ideation and attempts.

RESULTS

Approximately 1 in 10 (11.6 %) adults with chronic pain had MUEP. Those with MUEP reported earlier age of pain onset and more impairment due to health problems. Suicidal ideation was reported by 18.7 % of those with MEP and 28.4 % of those with MUEP. In fully-adjusted models, MUEP was associated with 1.60 times (95 % CI: 1.17-2.18) higher odds of suicidal ideation, and 1.89 (1.25-2.83) higher odds of suicide attempt, compared to MEP.

LIMITATIONS

Cross-sectional analysis; MUEP assessed by self-report.

CONCLUSIONS

Among adults with chronic pain, those with MUEP are more likely to report suicide behaviors. Findings illustrate a role for diagnostic and treatment processes in the relationship between pain and suicide.

Experiences of care coordination among older adults in the United States: Evidence from the Health and Retirement Study

INTRODUCTION

The goal of this study was to examine variation in patient experiences and perceptions of care coordination across sociodemographic and health factors.

METHODS

Data come from the 2016 Health and Retirement Study (N = 1, 216). Three domains of coordination were assessed: 1) Perceptions (e.g., patient impressions of provider-provider communication), 2) Tangible supports (e.g., meeting with a care coordinator, being accompanied to appointments), and 3) Technical supports (e.g., use of a "patient portal"). Logistic regression was used to quantify the frequency of each domain and examine variation by racial minority status, socioeconomic status, and health status.

RESULTS

Approximately 42% of older adults perceived poor care coordination, including 14.8% who reported receiving seemingly conflicting advice from different providers. Only one-third had ever met with a formal care coordinator, and 40% were occasionally accompanied to appointments. Although racial minorities were less likely to have access to technical supports, they were more likely to use them. Better perceived coordination was associated with higher care satisfaction (Odds Ratio: 1.43, 95% CI: 1.27-1.61).

CONCLUSIONS

Important gaps in care coordination remain for older adults.

PRACTICE IMPLICATIONS

Providers should consider assessing patient perceptions of care coordination to address these gaps in an equitable manner.

A Data Science Approach to Estimating the Frequency of Driving Cessation Associated Suicide in the US: Evidence From the National Violent Death Reporting System

Driving cessation is a common transition experienced by aging adults that confers both a symbolic and literal loss of independence due to the central role of automobiles for mobility in the US. Prior research has shown that driving cessation has negative implications for mental health, social participation, and access to healthcare. Given these sequelae of driving cessation and prior work showing that late-life transitions related to independence (e.g., transitioning into residential care) are associated with suicide, we sought to estimate the frequency of driving cessation associated suicide. Data include suicide (n = 59,080) and undetermined (n = 6,862) deaths aged ≥55 from the National Violent Death Reporting System (NVDRS, 2003-2017). Each case in the NVDRS has both quantitative data (e.g., demographic characteristics) and qualitative text narratives, derived from coroner/medical examiner reports, which describe the most salient circumstances and features of each death. To identify cases associated with driving cessation, we employed a supervised random forest algorithm to develop a Natural Language Processing (NLP) classifier. Identified driving cessation associated cases were then categorized and characterized using descriptive statistics and qualitative content analysis. From 2003 to 2017, there were an estimated 305 cases of suicide/undetermined deaths associated with driving cessation in the NVDRS, representing 0.04% of all cases. Cases associated with driving cessation were older, more likely to be male, more likely to have a physical health problem, more likely to have experienced a recent crisis, and more likely to have lived in a rural county than other decedents. Qualitative analysis identified functional impairment, alcohol-related driving limitations, loss of employment, and recent car accidents as common themes among cases associated with driving cessation. This analysis illustrates the utility of NLP in identifying novel correlates of suicide in later life. Although driving cessation associated suicide is a rare outcome, further research is warranted on understanding the conditions under which driving cessation is associated with suicidal behavior, and how to support the well-being of aging adults during these types of major life transitions.

Not discussed: Inequalities in narrative text data for suicide deaths in the National Violent Death Reporting System

Background

The rate of suicide in the US has increased substantially in the past two decades, and new insights are needed to support prevention efforts. The National Violent Death Reporting System (NVDRS), the nation’s most comprehensive registry of suicide mortality, has qualitative text narratives that describe salient circumstances of these deaths. These texts have great potential for providing novel insights about suicide risk but may be subject to information bias.

Objective

To examine the relationship between decedent characteristics and the presence and length of NVDRS text narratives (separately for coroner/medical examiner (C/ME) and law enforcement (LE) reports) among 233,108 suicide and undetermined deaths from 2003–2017.

Methods

Generalized estimating equations (GEE) logistic and quasi-Poisson modeling was used to examine variation in the narratives (proportion of missing texts and character length of the non-missing texts, respectively) as a function of decedent age, sex, race/ethnicity, education, marital status, military history, and homeless status. Models adjusted for site, year, location of death, and autopsy status.

Results

The frequency of missing narratives was higher for LE vs. C/ME texts (19.8% vs. 5.2%). Decedent characteristics were not consistently associated with missing text across the two types of narratives (i.e., Black decedents were more likely to be missing the LE narrative but less likely to be missing the C/ME narrative relative to non-Hispanic whites). Conditional on having a narrative, C/ME were significantly longer than LE (822.44 vs. 780.68 characters). Decedents who were older, male, had less education and some racial/ethnic minority groups had shorter narratives (both C/ME and LE) than younger, female, more educated, and non-Hispanic white decedents.

Conclusion

Decedent characteristics are significantly related to the presence and length of narrative texts for suicide and undetermined deaths in the NVDRS. Findings can inform future research using these data to identify novel determinants of suicide mortality.

Beyond Depression: Estimating 12-Months Prevalence of Passive Suicidal Ideation in Mid- and Late-Life in the Health and Retirement Study

OBJECTIVES

To provide valid estimates of the 12-month prevalence of passive suicidal ideation among older adults, without conditioning on depression status, using the Health and Retirement Study (HRS).

METHODS

Data come from the 2012 HRS (n = 17,434) and 2004/5 Baltimore Epidemiologic Catchment Area (ECA) Study (n = 755). In the HRS, passive suicidal ideation (i.e., thought a lot about death-your own, someone else's, or death in general) is only assessed on respondents who reported dysphoria/anhedonia; in the ECA, ideation is assessed on all respondents, regardless of depression. We compare two approaches to estimating the 12-month prevalence of passive suicidal ideation in the HRS without conditioning on depression symptoms: 1) a probit selection model within the HRS, and 2) a prediction model developed using appended ECA data applied to the HRS.

RESULTS

Using observed data alone on those who screened positive for depression, 6% of older adults reported passive suicidal ideation in the past year. Depending on the approach used, between 5.4% and 9.2% of HRS respondents who screened negative for depression would have reported passive suicidal ideation had they been assessed. Correcting for this selection bias, between 10.9% and 13.4% of U.S. adults over age 50 experienced passive suicidal ideation in 2012.

CONCLUSIONS

Population surveillance of suicidal ideation among older adults is biased by survey approaches that only assess ideation in the context of depression.

Suicide Among Older Adults Living in or Transitioning to Residential Long-term Care, 2003 to 2015

Importance

Almost 25% of Medicare beneficiaries live in residential long-term care (LTC) (eg, independent or assisted living facility or nursing home). There are few reliable statistics on completed suicide in LTC, in part because of data limitations.

Objectives

To estimate the number of suicides associated with residential LTC (ie, among persons in a facility, transitioning into or out of a facility, or otherwise associated with LTC) among adults 55 and older and, secondarily, to identify whether machine learning tools could improve the quality of suicide surveillance data.

Design, Setting, and Participants

Cross-sectional epidemiologic study (conducted in 2018) of restricted-access data from the National Violent Death Reporting System (NVDRS) (2003-2015) using restricted-access case narratives from suicides and undetermined deaths among adults 55 years and older in 27 states. Participants were all suicides and undetermined deaths (N = 47 759) among persons 55 years and older.

Exposure

Long-term care cited in the coroner/medical examiner case narrative, whether as a reason for self-harm or the injury location, identified using machine learning natural language processing (NLP) algorithms plus manual review of texts.

Main Outcomes and Measures

Number and characteristics (eg, demographics, health history, and means of injury) of suicides associated with LTC. The κ statistic was used to estimate the reliability of the existing NVDRS injury location codes relative to cases identified by the algorithm.

Results

Among 47 759 persons 55 years and older (median age, 64 years; 77.6% male; 90.0% non-Hispanic white), this study identified 1037 suicide deaths associated with LTC, including 428 among older adults living in LTC, 449 among older adults transitioning to LTC, and 160 otherwise associated with LTC. In contrast, there were only 263 cases coded with the existing NVDRS location code "supervised residential facility," which had poor agreement with cases that the algorithm identified as occurring in LTC (κ statistic, 0.30; 95% CI, 0.26-0.35).

Conclusions and Relevance

Over a 13-year period, approximately 2.2% of suicides among adults 55 years and older were associated with LTC in some manner. Clinicians, administrators, and policy makers should consider ways to promote the mental health and well-being of older adults experiencing functioning limitations and their families. Natural language processing may be a useful way to improve abstraction of variables in the NVDRS.