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Record W2738629269 · doi:10.1016/j.sjpain.2017.07.009

Chronic disruptive pain in emerging adults with and without chronic health conditions and the moderating role of psychiatric disorders: Evidence from a population-based cross-sectional survey in Canada

2017· article· en· W2738629269 on OpenAlexafffundabout
Rana A. Qadeer, Lilly Shanahan, Mark A. Ferro

Bibliographic record

VenueScandinavian Journal of Pain · 2017
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsUniversity of WaterlooMcMaster University
FundersCanada Research Chairs
KeywordsMedicineChronic painOdds ratioLogistic regressionCross-sectional studyCommunity healthConfidence intervalPopulationPsychiatryOrdered logitDemographyPublic healthInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND AND AIMS: There has been a growth in the proportion of emerging adults vulnerable to pain-related sequelae of chronic health conditions (CHCs). Given the paucity of research during this important developmental period, this study investigated the association between CHCs and chronic disruptive pain among emerging adults and the extent to which psychiatric disorders moderate this association. METHODS: Data come from the 2012 Canadian Community Health Survey - Mental Health (CCHS-MH). This cross-sectional survey included 5987 participants that were 15-30 years of age and self-reported their CHCs (n=2460, 41%) and the extent to which pain impacted daily functioning using items from the Health Utilities Index Mark 3 (HUI 3). Group comparisons between respondents with CHCs and healthy controls were made using chi-square tests. Odds ratios (OR) and 95% confidence intervals (CI) were computed from ordinal logistic regression models adjusting for sociodemographic covariates. Product-term interactions between CHCs and psychiatric disorders were included in the models to explore moderating effects. All analyses were weighted to maintain representativeness of the study sample to the Canadian population. RESULTS: =222.28, p<0.001). Similarly, in logistic regression models, participants with CHCs had greater odds of reporting chronic disruptive pain (OR=4.94, 95% CI=4.08-5.99). Alcohol (β=-0.66; p=0.025) and drug abuse/dependence disorders (β=-1.24; p=0.012) were found to moderate the association between CHCs and chronic disruptive pain. Specifically, the probability of chronic disruptive pain was higher for emerging adults without CHCs and with alcohol or drug disorders; however, among participants with CHCs, probability was higher for those without these disorders. CONCLUSIONS: There is a robust association between CHCs and chronic disruptive pain. The moderating effects suggest that alcohol or drug disorders are especially harmful for emerging adults without CHCs and contribute to higher levels of chronic disruptive pain; however, among those with CHCs, alcohol and illicit drugs may be used as a numbing agent to blunt chronic disruptive pain. IMPLICATIONS: Findings from this study have implications for the integration and coordination of services to design strategies aimed at managing chronic disruptive pain and preventing pain-related disabilities later in life. Within the health system, healthcare providers should engage in dialogues about mental health and substance use regularly with emerging adults, be proactive in screening for psychiatric disorders, and continue to monitor the impact of pain on daily functioning. Given the age range of emerging adults, there is tremendous opportunity for clinicians to work cooperatively with colleagues in the education system to support emerging adults with and without CHCs. Overall, clinicians, researchers, educators, and those in social services should continue to be mindful of the complex interrelationships between physical and mental health and chronic disruptive pain and work cooperatively to optimize health outcomes and prevent pain-related disabilities among emerging adults.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.015
GPT teacher head0.313
Teacher spread0.298 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2017
Admission routes3
Has abstractyes

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