Early childhood risk factors for later onset of pediatric chronic pain: a multi-method longitudinal study.

BACKGROUND: Pediatric chronic pain (i.e., pain lasting ≥ 3 months) is prevalent, disabling, and costly. It spikes in adolescence, interrupts psychosocial development and functioning, and often co-occurs with mental health problems. Chronic pain often begins spontaneously without prior injuries and/or other disorders. Prospective longitudinal cohort studies following children from early childhood, prior to chronic pain onset, are needed to examine contributing factors, such as early pain experiences and mental health. Using data from a longitudinal community pregnancy cohort (All Our Families; AOF), the present study examined the associations between early developmental risk factors, including early childhood pain experiences and mental health symptoms, and the onset of pediatric chronic pain at ages 8 and 11 years. METHODS: Available longitudinal AOF data from child age 4 months, as well as 1, 2, 3, 5, 8, and 11 years, were used. Mothers reported their child's pain experiences (e.g., hospitalizations, vaccinations, gut problems) at each timepoint from 4 months to 8 years, child chronic pain at age 8, and child mental health symptoms at ages 5 and 8 years. Children reported their chronic pain frequency and interference at age 11. Adaptive least absolute shrinkage and selection operator (LASSO) regressions were used to select predictor variables. Complete case analyses were complemented by multiple imputation using chained equation (MICE) models. RESULTS: Gut problems, emergency room visits, frequent pain complaints, and headaches at age 5 or earlier, as well as female sex, were associated with increased risk of maternal reported child chronic pain at age 8. Maternal reported chronic pain at age 8 was associated with higher levels of child-reported pain frequency and pain interferences at age 11. Boys self-reported lower levels of pain interference at age 11. CONCLUSIONS: Some, but not all, painful experiences (e.g., gut problems, ER visits, pain complaints) in early life contribute to pediatric chronic pain onset and should be considered for screening and early intervention.

Development and validation of the Cannabis Exposure in Pregnancy Tool (CEPT): a mixed methods study.

BACKGROUND: Evidence of associations between prenatal cannabis use (PCU) and maternal and infant health outcomes remains conflicting amid broad legalization of cannabis across Canada and 40 American states. A critical limitation of existing evidence lies in the non-standardized and crude measurement of prenatal cannabis use (PCU), resulting in high risk of misclassification bias. We developed a standardized tool to comprehensively measure prenatal cannabis use in pregnant populations for research purposes. METHODS: We conducted a mixed-methods, patient-oriented tool development and validation study, using a bias-minimizing process. Following an environmental scan and critical appraisal of existing prenatal substance use tools, we recruited pregnant participants via targeted social media advertising and obstetric clinics in Alberta, Canada. We conducted individual in-depth interviews and cognitive interviewing in separate sub-samples, to develop and refine our tool. We assessed convergent and discriminant validity internal consistency and 3-month test-retest reliability, and validated the tool externally against urine-THC bioassays. RESULTS: Two hundred fifty four pregnant women participated. The 9-item Cannabis Exposure in Pregnancy Tool (CEPT) had excellent discriminant (Cohen's kappa = -0.27-0.15) and convergent (Cohen's kappa = 0.72-1.0) validity; as well as high internal consistency (Chronbach's alpha = 0.92), and very good test-retest reliability (weighted Kappa = 0.92, 95% C.I. [0.86-0.97]). The CEPT is valid against urine THC bioassay (sensitivity = 100%, specificity = 82%). CONCLUSION: The CEPT is a novel, valid and reliable measure of frequency, timing, dose, and mode of PCU, in a contemporary sample of pregnant women. Using CEPT (compared to non-standardized tools) can improve measurement accuracy, and thus the quality of research examining PCU and maternal and child health outcomes.