Browsing by Author "Schroeder, Matthew"
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Item Association Between Quality of Life and Depression in Dyads of Older Primary Care Patients and Family Members(Oxford University Press, 2022-12-20) Fowler, Nicole; Perkins, Anthony; Park, Seho; Schroeder, Matthew; Boustani, Malaz; School of NursingFamilial dyads experience illness as an interdependent unit. We evaluate the association of quality of life (QOL), as measured by physical (PCS) and mental health component (MCS) scores, with depression in dyads of older primary care patients and a family member. This is a cross sectional, descriptive study where QOL and depression were measured concurrently in the dyad using baseline data from 1809 dyads enrolled in a trial testing the benefits and harms of Alzheimer’s disease and related dementias (ADRD) screening. QOL was measured with the SF-36, depression was measured with the PHQ-9, and the association of depression with QOL was examined using an actor-partner interdependence model with distinguishable dyads. Patient mean (SD) age was 73.7 (5.7) years; 53.1% women; 85.1% white; 13.4% black. Family member mean (SD) age was 64.2 (13) years; 67.7% women; 13.4% black. A patient’s spouse/partner were 64.8% of family members. After controlling for dyadic relationship and gender, significant actor effects of depression on PCS for patient (β= -1.39; p< 0.001) and family member (β =-0.954; p< 0.001), and significant partner effects of depression on PCS for patient (β=-0.15, p< 0.05) and family member (β =-0.18; p< 0.01). There were significant actor effects of depression on MCS for patient (β =-1.2; p< 0.001) and family member (β=-1.2; p< 0.001), but depression had a significant partner effect on MCS only for patient (β = -0.08; p< 0.05). Among dyads participating in an ADRD screening trial, dyads with higher depression had lower QOL. Family member depression was associated with decreased family member and patient QOL.Item Association Between Subjective Cognitive Decline and Strength Training in US Adults Aged 45+ Years(Oxford University Press, 2022-12-20) Schroeder, Matthew; Waring, Molly; Fowler, Nicole; Pagoto, Sherry; Medicine, School of MedicineSubjective cognitive decline (SCD) can be an early marker for Alzheimer’s disease and related dementias. Data supports physical activity to delay cognitive impairment and to improve cognitive functioning. We examined strength training engagement by middle-aged and older US adults with and without SCD. We used data from 121, 059 participated aged 45 years or older from the 2019 Behavioral Risk Factor Surveillance System (BRFSS) from 31 states and Washington, D.C. SCD was assessed by asking participants if they had experienced confusion or memory loss during the past 12 months (yes/no). Participants reported how often they engaged in strength training (e.g., using weight machine, free weights) in the past month. We dichotomized strength training engagement as meeting physical activity recommendations (2+ times weekly) or not (< 2 times weekly). An adjusted logistic regression model, controlling for confounding variables, estimated the likelihood of strength training in relation to SCD. Analyses were weighted; results are nationally representative. SCD was reported by 11.0% (SE: 0.2%) of middle-aged and older US adults. Three in 10 (29.1%; SE: 0.7%) of US middle-aged and older adults who reported SCD engaged in strength training 2+ times a week compared to 34.0% (SE: 0.3%) of US adults without SCD (aOR, 0.9; 95% CI: 0.9-1.0). While middle-aged and older US adults with SCD were less likely to strength train than those without SCD, only a third engaged in recommended strength training regardless of SCD status. Primary care providers should encourage strength training among middle-aged and older adults regardless of cognitive status.Item Development of Written Materials for Participants in an Alzheimer's Disease and Related Dementias Screening Trial(Sage, 2022-04-12) Head, Katharine J.; Hartsock, Jane A.; Bakas, Tamilyn; Boustani, Malaz A.; Schroeder, Matthew; Fowler, Nicole R.; Communication Studies, School of Liberal ArtsGiven that participants' experiences in clinical trials include a variety of communication touchpoints with clinical trial staff, these communications should be designed in a way that enhances the participant experience by paying attention to the self-determination theoretical concepts of competence, autonomy, and relatedness. In this feature, we argue that clinical trial teams need to consider the importance of how they design their written participant communication materials, and we explain in detail the process our multidisciplinary team took to design written materials for the patient and family caregiver participants in our Alzheimer's disease and related dementias (ADRD) screening trial. This article concludes with suggested guidance and steps for other clinical trial teams.Item Impact of a Driving Decision Aid on Decisional Conflict Among Older Adult Drivers and their Study Partners(Oxford University Press, 2022-12-20) Fowler, Nicole; Johnson, Rachel; Peterson, Ryan; Schroeder, Matthew; DiGuiseppi, Carolyn; Han, Duke; Hill, Linda; Betz, Marian; Medicine, School of MedicineForty-four million US licensed drivers are ≥65 years old and at higher crash risk. Decision-making about stopping or continuing driving is difficult and often involves family and friends. This study examines if decision conflict about changing driving habits is associated between older adult drivers and their study partners (SPs) (i.e., family member or friend). Data were from a multi-site trial assessing a driving decision aid. Decision conflict about stopping or continuing driving for drivers and their SPs were measured with the Decision Conflict Scale (DCS). Dyadic associations between drivers’ and SPs’ DCS scores pre- and post-decision aid implementation were analyzed using an actor-partner interdependence model. Among 228 driver-SP dyads, driver mean (SD) age was 77.1 (5.1) years; 50.0% female; 98.7% non-Hispanic; 94.7% white; and 97.8% urban-dwelling. SPs mean age was 66.1 years (13.9); 65.8% female; 95.6% non-Hispanic; 92.1% white; and commonly the driver’s spouse (54.6%) or adult child (21.1%). Most drivers (71.7%) and SPs (63.3%) had baseline DCS scores < 25 (drivers mean 18.5 (SD 12.3); SPs 20.5 (16.8)), suggesting low decision conflict. DCS was correlated within dyads at baseline (r=0.18, p < 0.01), and baseline DCS was associated with post-decision aid DCS (p < 0.001 for SPs [β=0.73] and drivers [β=0.73]). While SPs’ baseline DCS was not associated with drivers’ post-decision aid DCS, drivers’ baseline DCS and SPs’ post-decision DCS were (β=0.10; p=0.036). Higher decision conflict about driving felt by older drivers is frequently shared by their SPs, in whom decision conflict may persist even after a driving decision aid intervention.Item Loneliness and Quality of Life in Older Adult Primary Care Patients(Oxford University Press, 2023-12-21) Williams-Farrelly, Monica; Schroeder, Matthew; Li, Claudia; Fowler, Nicole; Medicine, School of MedicineLoneliness, defined as the perceived discrepancy in an individual’s desired and actual social relationships, is common among older adults. Loneliness among older adult primary care patients is lacking, considering the implications it has on physical and mental health. Our objective was to determine the relationship between loneliness and quality of life (QOL) in older adult primary care patients. Data come from the Caregiver Outcomes of Alzheimer’s Disease Screening (COADS) study, an ongoing randomized controlled trial evaluating benefits and risks of Alzheimer’s disease and related dementias screening among older primary care patients and their family members. Loneliness (5-item NIH Toolbox), quality of life (QOL)—as measured by physical and mental health component scores— and depression (PHQ-9) and anxiety symptomatology (GAD-7) were measured among primary care patients aged 65 and older from April 2020 to September 2021. Spearman correlation analyses reveal that loneliness was moderately correlated with mental health (r(601) = -.43, p< 0.001), anxiety (r(601) =.44, p< 0.001), and depression (r(601) = .42, p< 0.001), while weakly correlated with physical health (r(601) = -.15, p< 0.001). After conducting unadjusted and adjusted linear regression models, we found that loneliness was associated with both lower mental (p< 0.001) and physical health component scores (p< 0.001). Furthermore, loneliness remained significantly associated with worse mental health when adjusting for depression, anxiety, sociodemographic characteristics, and comorbidity. Primary care providers should discuss loneliness with their older adult patients and provide resources to help patients develop and maintain meaningful social relationships.Item Predicting Participant Engagement in a Social Media–Delivered Lifestyle Intervention Using Microlevel Conversational Data: Secondary Analysis of Data From a Pilot Randomized Controlled Trial(JMIR, 2022-07-28) Xu, Ran; Divito, Joseph; Bannor, Richard; Schroeder, Matthew; Pagoto, Sherry; Medicine, School of MedicineBackground: Social media-delivered lifestyle interventions have shown promising outcomes, often generating modest but significant weight loss. Participant engagement appears to be an important predictor of weight loss outcomes; however, engagement generally declines over time and is highly variable both within and across studies. Research on factors that influence participant engagement remains scant in the context of social media-delivered lifestyle interventions. Objective: This study aimed to identify predictors of participant engagement from the content generated during a social media-delivered lifestyle intervention, including characteristics of the posts, the conversation that followed the post, and participants' previous engagement patterns. Methods: We performed secondary analyses using data from a pilot randomized trial that delivered 2 lifestyle interventions via Facebook. We analyzed 80 participants' engagement data over a 16-week intervention period and linked them to predictors, including characteristics of the posts, conversations that followed the post, and participants' previous engagement, using a mixed-effects model. We also performed machine learning-based classification to confirm the importance of the significant predictors previously identified and explore how well these measures can predict whether participants will engage with a specific post. Results: The probability of participants' engagement with each post decreased by 0.28% each week (P<.001; 95% CI 0.16%-0.4%). The probability of participants engaging with posts generated by interventionists was 6.3% (P<.001; 95% CI 5.1%-7.5%) higher than posts generated by other participants. Participants also had a 6.5% (P<.001; 95% CI 4.9%-8.1%) and 6.1% (P<.001; 95% CI 4.1%-8.1%) higher probability of engaging with posts that directly mentioned weight and goals, respectively, than other types of posts. Participants were 44.8% (P<.001; 95% CI 42.8%-46.9%) and 46% (P<.001; 95% CI 44.1%-48.0%) more likely to engage with a post when they were replied to by other participants and by interventionists, respectively. A 1 SD decrease in the sentiment of the conversation on a specific post was associated with a 5.4% (P<.001; 95% CI 4.9%-5.9%) increase in the probability of participants' subsequent engagement with the post. Participants' engagement in previous posts was also a predictor of engagement in subsequent posts (P<.001; 95% CI 0.74%-0.79%). Moreover, using a machine learning approach, we confirmed the importance of the predictors previously identified and achieved an accuracy of 90.9% in terms of predicting participants' engagement using a balanced testing sample with 1600 observations. Conclusions: Findings revealed several predictors of engagement derived from the content generated by interventionists and other participants. Results have implications for increasing engagement in asynchronous, remotely delivered lifestyle interventions, which could improve outcomes. Our results also point to the potential of data science and natural language processing to analyze microlevel conversational data and identify factors influencing participant engagement. Future studies should validate these results in larger trials.Item Remember Stuff: A Pilot Feasibility Trial Of Dyadic-Focused Technology To Support People With Adrd(Oxford University Press, 2022) Manoharan, Sneha; Schroeder, Matthew; Slaven, James; Higbie, Anna; Mullholand, Mary Ellen; Fowler, Nicole; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public HealthTechnology to support caregivers of people with Alzheimer’s disease or related dementias (ADRD) with tasks may be the next frontier for caregiving research. This single-arm 90-day pilot trial tested the usability, feasibility, and acceptability of a software system called RememberStuff® (R/S) by Eperture. We also tested R/S’s impact on caregiver burden. R/S includes a web-based portal where caregivers add information to a touch screen used by patients. R/S is organized around four main features– Calendar, Messaging, Activities, and Remember, a personalized task list. We collected data from dyads at baseline, 30-, 60-, and 90-days. Measures included the Healthy Aging Brain Care (HABC) monitor, System Usability Scale (SUS), and satisfaction scales indicating caregiver’s willingness to use and behavioral intention. We approached caregivers of patients with ADRD seen in primary care clinics. Of the 469 participants reached, 278 (59.28%) refused, 156 (33.26%) were ineligible due to nursing home placement and 35 dyads were enrolled (7.46%). Among enrolled participants, 65.7% completed data up to 90 days. 73.5% of the caregivers lived with the patients. Mean caregiver age was 59.1 years; 67.7% are female; 88.2% are white. Willingness to use R/S was consistent across time from 30 days (M=3.9, SD=0.7) through 90 days (M=3.8, SD=1.1), while usability decreased (30 days M=57.7, SD=7.5 to 90 days M=54.9, SD 8.7). Caregiver’s overall HABC monitor also decreased from baseline (M=29.0, SD=13.1) to 90 days (M=27.2, SD=12.2) indicating less burden at 90 days. These findings support the feasibility of R/S technology to support caregivers of people with ADRD.Item The Relationship Between Socioeconomic Disadvantage And Dementia Caregiver Burden(Oxford University Press, 2022) Beverly, Alexis; Baucco, Christina; Park, Seho; Schroeder, Matthew; Johns, Shelley; Judge, Katherine; Fowler, Nicole; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public HealthMore than 16 million people provide unpaid care to someone with Alzheimer’s disease or a related dementia (ADRD) in the United States. These caregivers frequently report experiencing psychological and physical burden. Prior research shows that socioeconomic disadvantaged neighborhoods have higher rates of ADRD, but little is known about caregiver burden. We hypothesized more socioeconomic disadvantage is associated with higher caregiver burden. We performed a secondary analysis using baseline data on dementia caregivers (n=132) enrolled in the Indiana University Telephone Acceptance and Commitment Therapy for Caregivers (TACTICs) pilot trials. Mean (SD) caregiver age was 61.6 (11.6) years; 83.3% women; 78.8% white; 19.7% black. Seventy-two percent of the caregivers lived with the care recipient and 50.8% reported moderate dementia severity. A linear regression model examined the relationship between caregiver’s national Area Deprivation Index (ADI) score (ranging from 1–100 with higher scores indicating greater socioeconomic disadvantage) and caregiver burden. The following covariates were included: age, sex, race, education, shared residence with care-recipient, health status, anxiety, depression, and dementia severity of care recipient. Higher ADI was associated with lower caregiver burden (β=-0.222, p < 0.001). Caregiver burden has a significant negative relationship with ADI and dementia severity (p<-.001 and 0.046, respectively) and positive relationship with anxiety (p=0.014) controlling other covariates in the model. Although we found no support for the hypothesis, further research should examine these factors with how caregiver’s ADI may impact other psychosocial wellbeing outcomes. Discussion will highlight the need for caregivers to have access to resources that can aid them through their experience.