Literature Collection

Dual-task paradigms that combine cognitive and motor tasks offer a valuable lens for detecting subtle impairments in cognitive and physical functioning, especially in older adults. This study used artificial neural network (ANN) modeling to predict clinical, cognitive, and psychosocial outcomes from integrated gait, speech-linguistic, demographic, physiological, and psychological data collected during single- and dual-task conditions. Forty healthy adults (ages 20-84) completed physical, cognitive, and psychosocial assessments and a dual-task walking task involving cell phone use. ANN models were optimized using hyperparameter tuning and k-fold cross-validation to predict outcomes such as the Montreal Cognitive Assessment (MOCA), Trail Making Tests (TMT A and B), Activities-Specific Balance Confidence (ABC) Scale, Geriatric Depression Scale (GDS), and measures of memory, affect, and social support. The models achieved high accuracy for MOCA (100%), ABC (80%), memory function (80%), and social support satisfaction (75%). Feature importance analyses revealed key predictors such as speech-linguistic markers and sensory impairments. First-person plural pronoun used and authenticity of internal thoughts during dual-task emerged as strong predictors of MOCA and memory. Models were less accurate for complex executive tasks like TMT A and B. These findings support the potential of ANN models for the early detection of cognitive and psychosocial changes.

The increase in prescription and illicit opioid use since 2000 has become an urgent public health crisis. While the opioid epidemic spans racial, regional, and socioeconomic divides, women have surfaced as one demographic affected by opioid use and related sequelae. Certain federal and state regulations, secondary to the Child Abuse Prevention and Treatment Act, strip pregnant women with opioid use disorders of the ability to engage autonomously with their health care clinician while simultaneously impeding their ability to achieve and sustain recovery. The purpose of this article is to explore current health policy that impacts pregnant women who use opioids. Recommendations to improve care, broadly, will be highlighted to include access to contraceptive services, universal screening for perinatal substance use, and access to appropriate treatment strategies. Policy modifications to facilitate these recommendations are discussed. The Centers for Disease Control and Prevention Policy Analytical Framework was utilized to derive recommendations. The recommendations are relevant to advanced practice registered nurses and midwives who have the potential to treat substance use in women, to women's health and pediatric registered nurses, and to nursing administrators who are involved in decision-making in obstetric and pediatric settings.