The study of human development across the lifespan is inherently about patterns across time. Although many developmental questions have been tested with cross-sectional comparisons of younger and older persons, understanding of development as it occurs requires a longitudinal design, repeatedly observing the same individual across time. Development, however, unfolds across multiple time scales (i.e., moments, days, years) and encompasses both enduring changes and transient fluctuations within an individual. Measurement burst designs can detect such variations across different timescales, and disentangle patterns of variations associated with distinct dimensions of time periods. Measurement burst designs are a special type of longitudinal design in which multiple “bursts” of intensive (e.g., hourly, daily) measurements are embedded in a larger longitudinal (e.g., monthly, yearly) study. The hybrid nature of these designs allow researchers to address questions not only of cross-sectional comparisons of individual differences (e.g., do older adults typically report lower levels of negative mood than younger adults?) and longitudinal examinations of intraindividual change (e.g., as individuals get older, do they report lower levels of negative mood?) but also of intraindividual variability (e.g., is negative mood worse on days when individuals have experienced an argument compared to days when an argument did not occur?). Researchers can leverage measurement burst designs to examine how patterns of intraindividual variability unfolding over short timescales may exhibit intraindividual change across long timescales in order to understand lifespan development. The use of measurement burst designs provides an opportunity to collect more valid and reliable measurements of development across multiple time scales throughout adulthood.

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Background: Effective patient-provider communication (PPC) can improve clinical outcomes and therapeutic alliance. While PPC may have improved over time due to the implementation of various policies for patient-centered care, its nationwide trend remains unclear.

Background Little is known about the long‐term cognitive impact of internet usage among older adults. This research characterized the association between various measures of internet usage and dementia. Methods We followed dementia‐free adults aged 50–64.9 for a maximum of 17.1 (median = 7.9) years using the Health and Retirement Study. The association between time‐to‐dementia and baseline internet usage was examined using cause‐specific Cox models, adjusting for delayed entry and covariates. We also examined the interaction between internet usage and education, race‐ethnicity, sex, and generation. Furthermore, we examined whether the risk of dementia varies by the cumulative period of regular internet usage to see if starting or continuing usage in old age modulates subsequent risk. Finally, we examined the association between the risk of dementia and daily hours of usage. Analyses were conducted from September 2021 to November 2022. Results In 18,154 adults, regular internet usage was associated with approximately half the risk of dementia compared to non‐regular usage, CHR (cause‐specific hazard ratio) = 0.57, 95% CI = 0.46–0.71. The association was maintained after adjustments for self‐selection into baseline usage (CHR = 0.54, 95% CI = 0.41–0.72) and signs of cognitive decline at the baseline (CHR = 0.62, 95% CI = 0.46–0.85). The difference in risk between regular and non‐regular users did not vary by educational attainment, race‐ethnicity, sex, and generation. In addition, additional periods of regular usage were associated with significantly reduced dementia risk, CHR = 0.80, 95% CI = 0.68–0.95. However, estimates for daily hours of usage suggested a U‐shaped relationship with dementia incidence. The lowest risk was observed among adults with 0.1–2 h of usage, though estimates were non‐significant due to small sample sizes. Conclusions Regular internet users experienced approximately half the risk of dementia than non‐regular users. Being a regular internet user for longer periods in late adulthood was associated with delayed cognitive impairment, although further evidence is needed on potential adverse effects of excessive usage.

BACKGROUND:Little is known about disparities in pain treatment associated with weight status despite prior research on weight-based discrepancies in other realms of healthcare and stigma among clinicians. OBJECTIVE: To investigate the association between weight status and the receipt of prescription analgesics in a nationally representative sample of adults with back pain, adjusting for the burden of pain. DESIGN: Cross-sectional analyses using the Medical Expenditure Panel Survey (2010-2017). PARTICIPANTS: Five thousand seven hundred ninetyone civilian adults age ≥ 18 with back pain. MAIN MEASURES: We examine the odds of receiving prescription analgesics for back pain by weight status using logistic regression. We study the odds of receiving (1) any pain prescription, (2) three pain prescription categories (opioid only, non-opioid only, the combination of both), and (3) opioids conditional on having a pain prescription. KEY RESULTS: The odds of receiving pain prescriptions increase monotonically across weight categories, when going from normal weight to obesity II/III, despite adjustments for the burden of pain. Relative to normal weight, higher odds of receiving any pain prescription is associated with obesity I (OR = 1.30 [95% CI = 1.04-1.63]) and obesity II/III (OR = 1.72 [95% CI = 1.36-2.18]). Obesity II/III is also associated with higher odds of receiving opioids only (OR = 1.53 [95% CI = 1.16-2.02]), non-opioids only (OR = 1.77 [95% CI = 1.21-2.60]), and a combination of both (OR = 2.48 [95% CI = 1.44-4.29]). Obesity I is associated with increased receipt of non-opioids only (OR = 1.55 [95% CI = 1.07-2.23]). Conditional on having a pain prescription, the odds of receiving opioids are comparable across weight categories. CONCLUSIONS: This study suggests that, relative to those with normal weight, adults with obesity are more likely to receive prescription analgesics for back pain, despite adjustments of the burden of pain. Hence, the possibility of weight-based undertreatment is not supported. These findings are reassuring because individuals with obesity generally experience a higher prevalence of back pain. The possibility of over-treatment associated with obesity, however, may warrant further investigation.