The role of physical pain in global functioning of people with serious mental illness

Distributions of recorded pain in mental health records: a natural language processing based study

OBJECTIVE

The objective of this study is to determine demographic and diagnostic distributions of physical pain recorded in clinical notes of a mental health electronic health records database by using natural language processing and examine the overlap in recorded physical pain between primary and secondary care.

DESIGN, SETTING AND PARTICIPANTS

The data were extracted from an anonymised version of the electronic health records of a large secondary mental healthcare provider serving a catchment of 1.3 million residents in south London. These included patients under active referral, aged 18+ at the index date of 1 July 2018 and having at least one clinical document (≥30 characters) between 1 July 2017 and 1 July 2019. This cohort was compared with linked primary care records from one of the four local government areas.

OUTCOME

The primary outcome of interest was the presence of recorded physical pain within the clinical notes of the patients, not including psychological or metaphorical pain.

RESULTS

A total of 27 211 patients were retrieved. Of these, 52% (14,202) had narrative text containing relevant mentions of physical pain. Older patients (OR 1.17, 95% CI 1.15 to 1.19), females (OR 1.42, 95% CI 1.35 to 1.49), Asians (OR 1.30, 95% CI 1.16 to 1.45) or black (OR 1.49, 95% CI 1.40 to 1.59) ethnicities, living in deprived neighbourhoods (OR 1.64, 95% CI 1.55 to 1.73) showed higher odds of recorded pain. Patients with severe mental illnesses were found to be less likely to report pain (OR 0.43, 95% CI 0.41 to 0.46, p<0.001). 17% of the cohort from secondary care also had records from primary care.

CONCLUSION

The findings of this study show sociodemographic and diagnostic differences in recorded pain. Specifically, lower documentation across certain groups indicates the need for better screening protocols and training on recognising varied pain presentations. Additionally, targeting improved detection of pain for minority and disadvantaged groups by care providers can promote health equity.

Depressive symptoms and health-related quality of life in a heterogeneous psychiatric sample: conditional indirect effects of pain severity and interference

BACKGROUND

Few studies have examined clinically relevant mechanisms that underlie the association between two important indices of recovery- depression severity and health-related quality of life (HRQOL) in psychiatric outpatients. This study aimed to explicate the roles of pain interference and pain severity as mediating and moderating mechanisms in the relationship between depressive symptoms and HRQOL.

METHODS

Data from 290 outpatients diagnosed with schizophrenia (n = 102), depressive (n = 98), and anxiety (n = 90) disorders were examined. Participants completed a set of questionnaires that queried their sociodemographic statuses, current pain severity and interference levels, depression severity levels, and HRQOL. Subsequently, mediation and moderation analyses were conducted.

RESULTS

Analyses revealed that pain interference fully mediated the relationship between depressive symptoms and physical (34% of the total effect) but not mental HRQOL. At high pain levels (+ 1 SD from mean), depressive symptoms may interfere with physical quality of life through pain interference, but this was not present at low pain levels (- 1 SD from mean).

CONCLUSIONS

Prolonged pain symptoms could negatively influence psychiatric recovery beyond the physical aspect of HRQOL. These results thus imply a need to detect and manage severe physical pain complaints at the acute stage in psychiatric outpatients.

Personalized Biometrics of Physical Pain Agree with Psychophysics by Participants with Sensory over Responsivity

The study of pain requires a balance between subjective methods that rely on self-reports and complementary objective biometrics that ascertain physical signals associated with subjective accounts. There are at present no objective scales that enable the personalized assessment of pain, as most work involving electrophysiology rely on summary statistics from a priori theoretical population assumptions. Along these lines, recent work has provided evidence of differences in pain sensations between participants with Sensory Over Responsivity (SOR) and controls. While these analyses are useful to understand pain across groups, there remains a need to quantify individual differences more precisely in a personalized manner. Here we offer new methods to characterize pain using the moment-by-moment standardized fluctuations in EEG brain activity centrally reflecting the person’s experiencing temperature-based stimulation at the periphery. This type of gross data is often disregarded as noise, yet here we show its utility to characterize the lingering sensation of discomfort raising to the level of pain, individually, for each participant. We show fundamental differences between the SOR group in relation to controls and provide an objective account of pain congruent with the subjective self-reported data. This offers the potential to build a standardized scale useful to profile pain levels in a personalized manner across the general population.