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How infants spend time in everyday life is an important source of day-to-day, infant-to-infant, and age-related variability in development. Here, we measured the frequency of macro-level activity categories-playing, eating and drinking, napping, going on errands, bathing and dressing, watching media, book reading, and being comforted-in infants aged 4-7 and 10-13 months recruited from across the United States (55% female assigned at birth; 40% male assigned at birth; 5% unknown). Unlike past work that used retrospective estimates, we used an ecological momentary assessment sampling method to obtain direct reports of activities from infants' caregivers via text-message surveys. The resulting data illustrate that play is the most frequent activity within the first year, accounting for half of infants' waking time. Other frequent activities, such as mealtimes and errands, contribute significantly to how infants spend their time. Older infants spend more time playing and eating/drinking and less time napping and being comforted than younger infants. Importantly, different macro-level activities facilitate or constrain infants' moment-to-moment behaviors, such as holding objects, sitting, and standing, suggesting that the composition of infants' daily routines shapes opportunities for perceptual-motor learning.

BackgroundMany contributing factors can influence individuals' health, and these factors may not affect health outcomes equally. This study compared the importance of 38 predictors of health-related quality of life (HRQOL) and 2-y mortality for US older adults.MethodsData were from the Medicare Health Outcome Survey Cohort 23 (baseline 2020, follow-up 2022). This study included participants ≥65 y (N = 142,551). HRQOL measures included physically unhealthy days (PUD), mentally unhealthy days (MUD), and activity limitation days (ALD) from the Healthy Days questions and 3 measures from the Veterans RAND 12-Item Health Survey (VR-12). A variable's importance was measured as the average gain in R2 after adding the variable in all submodels.ResultsFor physical health (PUD), pain interfered with daily activities was the most important predictor with an importance score (I) of 8.4, indicating that this variable contributed 8.4% variance of PUD. Other leading predictors included pain interfered with socializing (I = 7.3) and pain rating (I = 6.7). For mental health (MUD), depression (I = 11.6) was far more important than any of the other predictors, contributing 38% of the total importance. For perceived disability (ALD), pain interfered with socializing was the most important predictor (I = 8.3), followed by difficulty doing errands (I = 6.1) and pain interfered with activities (I = 6.0). Of note, this general pattern was consistent for VR-12 HRQOL measures. Variables' importance scores for 2-y morality were very different from that for HRQOL. Age (I = 2.8) and difficulty doing errands (I = 2.6) were the most important variables.ConclusionsThis study demonstrated a large discrepancy in the variables' importance for HRQOL and 2-y mortality. Functional limitations/disabilities and geriatric syndromes were more important for the prediction of HRQOL than were chronic conditions and other factors combined.HighlightsFor older adults, large differences were found in variable importance for explaining health-related quality of life (HRQOL) and 2-y mortality among 38 explanatory variables, including functional limitations, geriatric syndromes, chronic conditions, and other factors.Pain and pain interference, difficulty doing errands, difficulty concentrating, memory problems, problems with walking/balance, and depression were the most important predictors of HRQOL.Age, marital status, education, difficulty doing errands, congestive heart failure, chronic obstructive pulmonary disease, and any cancer were more important for 2-y mortality than HRQOL.Health care providers and policy makers should focus on the impact of multimorbidity and the interaction between often multifactorial conditions, as opposed to focusing only on individual diseases.

The only functional impairment data available for all Medicare beneficiaries identify those who qualified for Medicare before age 65 years due to work-related disability. This administrative measure omits impairments arising after age 64 years or affecting nonwork-related activities. Surveys may offer more accurate assessments, but survey data on functional limitations are not routinely available. Claims data may provide a practical, scalable alternative. To describe the development of a survey-based index of functional limitations and a new claims-based model for predicting limitations. Data from respondents to the 2024 Medicare fee-for-service (FFS) Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey were used to create the FFS CAHPS functional limitations index (FCFLI), a measure of the extent to which functional limitations affect overall health and the benchmark for the study's claims-based measure. The FCFLI scores of respondents were linked to Medicare FFS claims from April 2023 to March 2024 to develop a claims-based predictive model (FCFLI-claims). The final model was applied to all FFS beneficiaries enrolled in Medicare Parts A and B during the same period. The FCFLI was derived from beneficiaries' self-rated health and ability to perform 6 basic activities of daily living and 1 instrumental activities of daily living (collectively, I/ADLs). Nine sets of claims-based indicators of functional impairment were used to predict FCFLI scores. Data were collected from 67 596 respondents (53.4% female; mean [SD] age, 75 [8] years). In the FCFLI model, all I/ADL indicators were negatively associated with self-rated health, with the largest effect estimates for difficulty walking (-13.9 points; 95% CI, -14.6 to -13.2 points) and running errands (-11.7 points; 95% CI, -12.7 to -10.8 points). In the FCFLI-claims model, 14 claims indicators had relative importance values that were 5% or greater of the maximum value. The model reliably identified beneficiaries with functional limitations (80.4% positive predictive value). Applied to the 2024 Medicare FFS population, approximately 12% were identified as likely to have functional limitations. Nearly 63% (approximately 2 450 000) of those identified by the algorithm were not identified by Centers for Medicare & Medicaid Services administrative measure of disability, which focuses on limitations that develop before age 65 years. In this cross-sectional study, FCFLI-claims identified beneficiaries likely to have functional limitations who could be prioritized for a survey assessment to verify the algorithm's results. Integrating this information with entitlement data could enhance Centers for Medicare & Medicaid Services' monitoring of functional status, especially among age-eligible beneficiaries.

Populations worldwide are aging, intensifying the challenge of meeting long-term care (LTC) needs. While formal LTC programs aim to address this demand, less is known about how they interact with informal caregiving and affect caregiver health and labor outcomes. This paper exploits the staggered expansion of Medicaid Home and Community-Based Services (HCBS) waivers across U.S. states to examine these effects. Using data from 1998 to 2018 with approximately 20,600 observations, our sample consists of individuals aged 40-70 who are initially healthy and report no activities of daily living (ADL) limitations, allowing us to assess their responses to expanded formal care availability for their parents. We implement a two-way fixed effects difference-in-differences (TWFE DiD) framework to estimate causal effects. We find that HCBS expansions increase the likelihood of providing any informal care by 5 percentage points (14% relative to the mean), personal care by 2 percentage points (20%), and errands by 5 percentage points (14%). These increases are temporary, vanishing within two to three years. Short-run health declines and small labor force reductions follow the same pattern, with no persistent adverse effects. Our findings challenge the view that formal and informal care are solely substitutes. HCBS can complement certain non-intensive caregiving activities without long-term harm, highlighting the need for LTC policies that account for the dynamic relationship between formal services and family care.

Perceived social support - feeling cared for and having access to a reliable network - has been linked to reduced stress and burnout, and greater quality of life among medical students. Yet, how perceived support systems evolve throughout medical school remains little explored. We examined how medical students' perceived social support systems shift during medical school adaptively to students' changing academic and emotional needs. Between January and May 2023, we conducted six hour-long group interviews with a cross-sectional convenience sample of 50 medical students (graduating Classes of 2023, 2024, 2025, and 2026) enrolled at a small, community-based medical school in the Midwestern US. Using collaborative interpretation to analyze our interview notes, we found that students shifted their reliance on peer and non-medical support systems (e.g., family, friends, and significant others), but seldom felt supported by both simultaneously. Early in training, peers offered solidarity in an unfamiliar and demanding academic setting, while non-medical supporters were perceived as lacking understanding of the medical school experience. Transitional periods - particularly those preceding the USMLE Step 1 exam, clinical clerkship, and application for residency - coincided with greater emotional stress and dissatisfaction with support, often tied to conflicting notions of students' social availability or medical expertise. Students most valued instrumental support, such as help with meals and errands, during intensive exam preparation, while emotional support was more relevant during clinical rotations. Notably, reliance on peer support diminished during clerkship, but re-emerged during the shared challenges of the residency application. Our findings suggest that medical students' social support needs are dynamic and context-dependent. We recommend targeted interventions, including guidance for non-medical supporters and instrumental support services during high-stress study periods. Our results align with broader literature and offer actionable insights. Enhancing perceived social support across all years of training is essential for fostering resilience and long-term well-being in future physicians.

The integration of robots into clinical practice requires careful consideration of their alignment with nursing workflows, patient needs, and clinical contexts. This scoping review aimed to support effective technology adoption by systematically identifying and classifying how robots are used in hospital-based nursing practice using standardized nursing terminology. A scoping review following Arksey and O'Malley's five-stage framework. A structured search was conducted in five peer-reviewed databases (PubMed, Web of Science, Cochrane Library, CINAHL, and EMBASE) for studies published between January 2019 and July 24, 2025. The data were analyzed to classify the types of nursing tasks supported by the robots. Robotic functions were classified into direct care, indirect care, and associated work using standardized nursing terminology, Hurst's framework, and the Clinical Care Classification system to provide a codified and structured analysis of nursing tasks. A total of 40 studies were included in the final review. Thirty-three focused on direct care with robots, primarily supporting psychological, physiological, and functional care. The key interventions included coping support, emotional support, infection control, and vital sign monitoring. Only one study involved indirect care, and nine focused on associated work, such as errands and cleaning. Robots are primarily used for direct care, such as emotional support and monitoring, while their role in indirect care-requiring professional judgment including documentation-remains limited. This suggests that future development should prioritize user-centered designs and ethical guidelines aligned with actual clinical needs. Properly implemented robotic technology will serve as a strategic tool to enhance nursing efficiency and improve practice environments amidst chronic workforce shortages. By categorizing robotic functions using standardized nursing terminology, this review offers a structured understanding of how robots can support nursing. These insights help identify tasks that can be delegated to robots during crises, such as pandemics or staffing shortages, allowing nurses to focus on essential patient care.

Social determinants of health play a critical role in mental health outcomes, yet their influence on access to and response to transcranial magnetic stimulation (TMS) for major depressive disorder (MDD) remains poorly understood. As TMS is an effective intervention for treatment-resistant depression and may serve a clinically vulnerable population, characterizing the social context of patients receiving TMS is essential. We examined social needs and assets in a TMS-treated cohort and evaluated their relationship to treatment response, hypothesizing greater social need burden among non-responders. We conducted a retrospective analysis of adults who received an acute course of TMS for MDD at Butler Hospital between 2019 and 2021. Depressive symptom severity, response, and remission were assessed using the Inventory of Depressive Symptomatology-Self Report (IDS-SR). Social needs and assets were measured using a modified Accountable Health Communities Health-Related Social Needs (AHC-HRSN) Screening Tool, including items assessing community engagement. Seventy-four patients were included in the analysis. Baseline social needs were not significantly associated with TMS response or remission. Patients accessing TMS generally demonstrated high levels of social assets and minimal deficits in basic needs and substance use; however, most reported social isolation and substantial functional impairment. Several domains of self-reported social needs improved following TMS treatment, independent of clinical response. Patients receiving TMS exhibited relatively high social assets despite pronounced psychosocial burden associated with depression. Several self-reported psychosocial domains improved following treatment, including isolation/loneliness, difficulty with concentration, and ability to complete errands independently. These findings suggest that TMS may coincide with functional improvements beyond depressive symptom reduction and highlights opportunities to integrate supportive psychosocial services alongside treatment that may further optimize clinical outcomes and reduce social unmet needs. Further investigation is needed to understand how social context influences access to and outcomes of TMS care.

Human activity recognition (HAR) from wearable sensor data traditionally identifies atomic movements (e.g., sit, stand, walk). However, many medical fields require recognizing functional activities-higher-level, goal-directed behaviors (e.g., errands, socialize, work). Functional activity recognition is critical for cognitive health assessment, rehabilitation, post-surgical recovery, and chronic disease management, yet remains largely unexplored due to its inherent complexity and variability for in-the-wild settings. This work addresses these challenges by investigating methods for functional HAR and introducing a novel approach that augments feature representations with feature token-transformer embeddings to improve classification performance. We compare a range of machine learning and deep learning methods, analyzing their ability to generalize across a diverse population. Additionally, we present ArWISE, a large-scale functional activity dataset collected longitudinally from n = 503 participants, consisting of over 32 million labeled points. Our experiments demonstrate the advantages of incorporating feature embeddings into functional HAR models, particularly in handling real-world variability and data sparsity. By bridging the gap between atomic movement recognition and functional behavior modeling, this work lays the foundation for more advanced, behavior-aware applications in digital health and human-centered AI.

Individuals with one or more socially stigmatized identities experience extensive health disparities, resulting in poorer health outcomes. However, most studies consider the effects of only individual stigmatized identities. We aimed to quantitatively estimate the additive and multiplicative effects of stigmatized identities on self-reported overall health. We used survey data from 387,411 participants in the All of Us Research Program, which has assembled a disease-agnostic cohort intended to reflect the US population, to statistically estimate the first- and second-order effects of 47 stigmatized identities on self-reported overall health. We used a linear model to estimate the effects of individual and pairwise stigmas on self-ratings of overall health. We began by aiming to create cohorts for all 93 stigmatized identities previously found to affect health, of which 47 (51%) could be practicably examined. We first modeled individual stigmas alone to contrast the results with those that included both individual and pairwise stigmas. After using the false discovery rate to adjust for testing multiple hypotheses in the collective model, 29 individual and 116 pairs of stigmas had statistically significant effects on self-reported overall health. All significant individual effects were negative or neutral except for skin cancer. Those with the largest negative effect on self-rated overall health were difficulty walking or climbing stairs, unemployed or unable to work, difficulty with errands, and low educational attainment. Pairs of intersecting stigmas had a mix of negative and positive incremental effects, indicating that some stigmatized identities are negative modifiers, such as depression, and other combinations are less negative than the sum of their individual negative effects, such as having difficulty with multiple types of activities of daily living. The individual stigmas with the largest number of statistically significant stigma pairs were unemployed or unable to work (14/47, 30%); depression and low income (11/47 each, 24%); and difficulty walking or climbing stairs, cognitive difficulties, obesity, and skin cancer (8/47 each, 17%). Taken together, numerous pairs of stigmatized identities significantly affect self-reported overall health. While each stigmatization has both direct and indirect effects on health, the relative importance of direct and indirect effects will vary. Many of these are aligned with prior literature, and others warrant further exploration. While the large sample size of this study is a strength, we were unable to model higher-order intersectionality and encourage future research exploring this. The individual and pairwise identities with significant negative effects should be incorporated into research and clinical care by considering the multidimensionality of individuals and how that affects their overall health.

Driving at night increases crash risks due to reduced visibility, higher speeds from lighter traffic, and greater chances of impaired or drowsy driving. However, current literature lacks a comprehensive analysis of nighttime drivers' demographics, reasons for driving at night, and the link between nighttime exposure and crash risk. Using the 2021-2023 American Driving Survey (ADS), this study examines nighttime driving exposure among U.S. drivers by age, gender, race/ethnicity, education, employment, region, and residence type. The analysis measures average daily nighttime trips, minutes, and miles driven per driver and explores trip purposes across demographic groups. Additionally, this study assesses nighttime fatality risks by age, gender, and region using Fatality Analysis Reporting System (FARS) data combined with ADS exposure estimates. Findings show that drivers under 65, males, those with lower education levels, and residents of the Midwest, South, and West had higher nighttime driving exposure. Commuting, errands, and social trips were the primary purposes of nighttime driving. Nighttime fatality risks were generally higher for young and middle-aged male drivers and those in the Midwest, South, and West. These findings provide a foundation for evidence-based policies and interventions aimed at improving nighttime road safety for all road users, including enhancing road infrastructure in communities with high nighttime travel, and optimizing resource allocation.

Executive deficits in schizophrenia are a major concern due to their strong impact on everyday functioning. Clinical neuropsychology offers several types of tools to assess executive functioning, including traditional, naturalistic, and self-rated measures. This study aimed to examine the predictive value of these different executive assessments on daily functional outcomes in schizophrenia patients. 40 individuals diagnosed with schizophrenia and 52 controls were included. All participants completed traditional executive tests (Digit Span, Trail Making Test, Color Word Interference Test, Verbal Fluency), naturalistic assessments (Paper version of the Errands Test and an alternate version of the Executive Function Performance Test [EFPT]), and a self-report measure (Behavior Rating Inventory of Executive Function-Adult Version [BRIEF-A]). Functional status was assessed using the Specific Level of Functioning Scale (SLOF). Results showed that, compared to controls, schizophrenia patients demonstrated lower executive performance and reported greater executive difficulties in daily life. After controlling for potential confounds, only the level of cueing required on the alternate EFPT and the BRIEF-A Global Executive Composite independently predicted functioning, explaining 36% of the variance in the SLOF Activities domain. These findings support the systematic inclusion of naturalistic and self-rated executive measures in neuropsychological assessments, alongside traditional tests, prior to implementing psycho-social interventions in schizophrenia.

The objective of the study is to assess the relationship between functional limitation and use of dental services among older American adults; and whether this relationship is independent from socioeconomic factors. We used data pertaining to older American adults aged 60 years and over from the 2022 Behavioral Risk Factor Surveillance System (BRFSS). Functional limitation was indicated by difficulties in hearing, seeing, concentrating or remembering, walking or climbing stairs, dressing or bathing, and doing errands alone. Use of dental service was indicated by one or more dental visit within the past year. Logistic regression was conducted to assess the association between any limitation and use of dental service adjusting for income, education, health insurance, smoking, tooth extraction, age, sex and ethnicity. The analysis included 142,095 participants. Dental visit within past year, and functional limitations were reported by 67.4% and 39.7% of the participants, respectively. Functional limitation was negatively associated with dental visit in the previous year with Odds Ratios 0.69 (95% Confidence Intervals: 0.65, 0.74) in the fully adjusted model. Functional limitation could be a potential and additional barrier to use of dental services among older Americans. Public health strategies should consider alternative care models for those with functional limitations.

Objective: The objective of this study was to examine how functional, mental, and physical health outcomes differ between younger (<age 50) and older (&#x2265;age 50) stroke survivors. Methods: Data from adult stroke survivors examined health-related outcomes (physical and mental health) over the past 30 days. Logistic regression models were used for binary functional outcomes, and Poisson regression models were used to estimate count outcomes for poor mental and physical health days. Results: Compared with older adults, younger stroke survivors were more likely to report difficulty concentrating or remembering (41.1% vs. 23.2%, p < 0.0001) and difficulty doing errands alone (27.11% vs. 23.67%, p = 0.00), but less likely to report difficulty walking or climbing stairs (34.3% vs. 47.6%, p < 0.0001). Additionally, younger adults with stroke reported significantly more poor mental health days (10.81 vs. 5.76, p < 0.0001) than older adults. In adjusted models, being out of work or out of the labor force was consistently associated with greater odds of functional limitations (e.g., OR for activity difficulty = 2.07, 95% CI: 1.56-2.75) and higher counts of poor mental and physical health days. Younger stroke survivors who were out of the labor force had significantly greater odds of difficulty concentrating (OR = 2.02, 95% CI: 1.17-3.48) and increased days of poor mental (IRR = 1.27, 95% CI: 1.19-1.70) and physical health (IRR = 1.26, 95% CI: 1.19-1.53). Conclusions: These findings highlight the intersection of age and employment on stroke outcomes. Younger stroke survivors face unique and disproportionate challenges in functional and mental health.

Shared sanitation facilities are critical for universal access to sanitation. This exploratory study examines the role that free shared sanitation facilities play in equalizing sanitation access in peri-urban India, where, despite extensive state-led efforts towards universal access, household toilets remain infeasible for the country&#x2019;s poorest citizens. We conducted one-on-one semi-structured interviews with 39 shared sanitation facility users in two peri-urban communities in Jharkhand, India. Participants were recruited after they used the sanitation facility. Data were analyzed using both deductive and inductive coding and thematic analysis. We found that clean and safe community sanitation facilities were used by people when at home, and were used both by those with and without a home toilet. We also found (consistent with previous work) that when people were outside of the home for work, school, and errands, they often needed but did not have access to usable toilets. These findings suggest why, and under what conditions, shared sanitation facilities are essential to realizing the human right to sanitation. Shared facilities are complements to, and not substitutes for, household facilities. Global sanitation targets, therefore, should be modified to reflect the role of well-maintained shared sanitation in meeting the goal of universal access.