Characterizing daily physical activity patterns with unsupervised learning via functional mixture models.

Physical inactivity is a significant public health concern. Consideration of inter-individual variations in physical activity (PA) trends can provide additional information about the groups under study to aid intervention design. This study aims to identify latent profiles ("phenotypes") based on daily PA trends among adults living in. This was a secondary analysis of 724 person-level days of accelerometry data from 133 urban-dwelling adults (89% Latinx, age = 19-77 years). We used Actigraph accelerometers and the Actilife software to collect and process 24-hour PA data. We implemented a probabilistic clustering technique based on functional mixture models. Multiple days of data per person were averaged for entry into the models. We evaluated step counts, moderate-intensity PA (MOD), total activity and sedentary minutes as potential model variables. Bayesian Information Criterion (BIC) index was used to select the model that provided the best fit for the data. A 4-cluster resolution provided the best fit for the data (i.e., BIC=-3257, improvements of Δ = 13 and Δ = 7 from 3- and 5-cluster models, respectively). MOD provided the greatest between-cluster discrimination. Phenotype 1 (N = 61) was characterized by a morning peak in PA that declined until bedtime. Later bedtimes and the highest daily PA volume were distinct for phenotype 2 (N = 18), along with a similar peak pattern. Phenotype 3 (N = 29) membership was associated with the lowest PA levels throughout the day. Phenotype 4 was characterized by a more evenly distributed PA during the day, and later waking/bedtimes. Our findings point to distinct, interpretable PA phenotypes based on temporal patterns. Functional clustering of PA data could provide additional actionable points for tailoring behavioral interventions.

Lifetime Trauma and Cardiovascular Health in Latinas.

BACKGROUND: Potentially traumatic experiences throughout the life course are associated with poor cardiovascular health among women. However, research on the associations of trauma with cardiovascular health among Latino populations is limited. Understanding the impact of trauma on cardiovascular health within marginalized populations may provide guidance on developing interventions with a particular focus on preventative care. OBJECTIVE: The purpose of this descriptive cross-sectional study was to examine the associations of lifetime trauma with cardiovascular health among middle-aged and older Latina women. METHODS: Participants were recruited from an existing study in New York City. All participants completed a structured questionnaire to assess lifetime trauma, demographic characteristics (such as age and education), financial resource strain, and emotional support. The Trauma History Questionnaire was used to assess lifetime exposure to potentially traumatic experiences (range 0-24). Cardiovascular health was measured with a validated measure of cardiovascular health from the American Heart Association (Life's Simple 7). We used self-reported and objective data to calculate cardiovascular health scores (range 0-14). Multiple linear regression was used to examine the associations of lifetime trauma with cardiovascular health, adjusted for age, education, financial resource strain, and emotional support. RESULTS: The sample included 50 Latina women with a mean age of 63.1 years, 88% were Dominican, and only 6% had completed a college degree. Women reported an average of 4.8 traumatic experiences. Mean cardiovascular health score was 6.5 (SD = 1.6, range 3-10). Linear regression models found that, after adjusting for age, education, financial resource strain, and emotional support, a higher count of lifetime trauma was associated with worse cardiovascular health. However, this association did not reach statistical significance. DISCUSSION: Women with a higher count of lifetime trauma had worse cardiovascular health scores; this association was not statistically significant. Future studies should investigate associations of lifetime trauma and cardiovascular health in larger and more diverse samples of Latinas. Nurses and other clinicians should incorporate trauma-informed approaches to cardiovascular disease risk reduction to improve the cardiovascular health of Latina women who are survivors of trauma.

A Data Mining Approach for Examining Predictors of Physical Activity Among Urban Older Adults.

The current study applied innovative data mining techniques to a community survey dataset to develop prediction models for two aspects of physical activity (i.e., active transport and screen time) in a sample of urban, primarily Hispanic, older adults (N=2,514). Main predictors for active transport (accuracy=69.29%, precision=0.67, recall=0.69) were immigrant status, high level of anxiety, having a place for physical activity, and willingness to make time for physical activity. The main predictors for screen time (accuracy=63.13%, precision=0.60, recall=0.63) were willingness to make time for exercise, having a place for exercise, age, and availability of family support to access health information on the Internet. Data mining methods were useful to identify intervention targets and inform design of customized interventions.

Application of persuasive systems design principles to design a self-management application user interface for Hispanic informal dementia caregivers: user preferences and perceptions.

OBJECTIVE: We designed an mHealth application (app) user interface (UI) prototype informed by participatory design sessions, persuasive systems design (PSD) principles, and Lorig and Holman's self-management behavior framework to support self-management activities of Hispanic informal dementia caregivers and assessed their perceptions and preferences regarding features and functions of the app. MATERIALS AND METHODS: Our observational usability study design employed qualitative methods and forced choice preference assessments to identify: (1) the relationship between user preferences for UI features and functions and PSD principles and (2) user preferences for UI design features and functions and app functionality. We evaluated 16 pairs of mHealth app UI prototype designs. Eight paper-based paired designs were used to assess the relationship between PSD principles and caregiver preferences for UI features and functions to support self-management. An Apple iPad WIFI 32GB was used to display another 8 paired designs and assess caregiver preferences for UI functions to support the self-management process. RESULTS: Caregivers preferred an app UI with features and functions that incorporated a greater number of PSD principles and included an infographic to facilitate self-management. Moreover, caregivers preferred a design that did not depend on manual data entry, opting instead for functions such as drop-down list, drag-and-drop, and voice query to prioritize, choose, decide, and search when performing self-management activities. CONCLUSION: Our assessment approaches allowed us to discern which UI features, functions, and designs caregivers preferred. The targeted application of PSD principles in UI designs holds promise for supporting personalized problem identification, goal setting, decision-making, and action planning as strategies for improving caregiver self-management confidence.

Patterns of caregiving among patients hospitalized with cardiovascular disease.

BACKGROUND AND OBJECTIVES: Cardiac caregivers may represent a novel low-cost strategy to improve patient adherence to medical follow-up and guidelines and, ultimately, patient outcomes. Prior work on caregiving has been conducted primarily in mental health and cancer research; few data have systematically evaluated caregivers of cardiac patients. The purpose of this study was to evaluate the patterns of caregiving and characteristics of caregivers among hospitalized patients with cardiovascular disease (CVD) to assess disparities in caregiver burden and to determine the potential for caregivers to impact clinical outcomes. SUBJECTS AND METHODS: Consecutive patients admitted to the cardiovascular service line at a university medical center during an 11-month period were included in the Family Cardiac Caregiver Investigation To Evaluate Outcomes (FIT-O) study. Patients (n=4500; 59% white, 62% male, 93% participation rate) completed a standardized interviewer-assisted questionnaire in English or Spanish regarding assistance with medical care, daily activities, and medications in the past year and plans for posthospitalization. In univariate and multiple variable analyses, caregivers were categorized as either paid/professional (eg, nurse/home aide) or nonpaid (eg, family member/friend). RESULTS AND CONCLUSIONS: Among CVD patients, 13% planned to have a paid caregiver and 51% a nonpaid caregiver at discharge. Planned paid caregiving was more prevalent among racial/ethnic minority versus white patients (odds ratio, 1.5; 95% confidence interval, 1.2-1.8); planned nonpaid caregiving prevalence did not differ by race/ethnicity. Most nonpaid caregivers were female (78%). Patients who had nonpaid caregivers in the year prior to hospitalization (28%) reported grocery shopping/meal preparation (32%), transport to/arranging doctor visits (30%), and medication adherence/medical needs (25%) as top tasks caregivers assisted with. Following hospitalization, a majority of patients expect nonpaid caregivers, primarily women, to assist with tasks that have the potential to improve CVD outcomes such as medical follow-up, medication adherence, and nutrition, suggesting that these are important targets for caregiver education.

Digital phenotyping of sleep patterns among heterogenous samples of Latinx adults using unsupervised learning.

OBJECTIVE: This study aimed to identify sleep disturbance subtypes ("phenotypes") among Latinx adults based on objective sleep data using a flexible unsupervised machine learning technique. METHODS: This study was an analysis of sleep data from three cross-sectional studies of the Precision in Symptom Self-Management Center at Columbia University. All studies focused on sleep health in Latinx adults at increased risk for sleep disturbance. Data on total sleep time (TST), time in bed (TIB), wake after sleep onset (WASO), sleep efficiency (SE), number of awakenings (NOA) and the mean length of nightly awakenings were collected using wrist-mounted accelerometers. Cluster analysis of the sleep data was conducted using an unsupervised machine learning approach that relies on mixtures of multivariate generalized linear mixed models. RESULTS: The analytic sample included 494 days of data from 118 adults (Ages 19-77). A 3-cluster model provided the best fit based on deviance indices (ie, DΔ∼ -75 and -17 from 1- and 2- to 3-cluster models, respectively) and likelihood ratio (Pdiff âˆ¼ 0.93). Phenotype 1 (n = 64) was associated with greater likelihood of overall adequate SE and less variability in SE and WASO. Phenotype 2 (n = 11) was characterized by higher NOAs, and greater WASO and TIB than the other phenotypes. Phenotype 3 (n = 43) was characterized by greater variability in SE, bed times and awakening times. CONCLUSION: Robust digital data-driven modeling approaches can be useful for detecting sleep phenotypes from heterogenous patient populations, and have implications for designing precision sleep health strategies for management and early detection of sleep problems.

Investigating the Associations of Everyday Discrimination and Inflammation in Latina Women: A Pilot Study.

INTRODUCTION: Discrimination is associated with negative health outcomes among Latinos. Research on the link between discrimination and inflammation in adults has focused on pro-inflammatory markers rather than characterizing the more informative balance of pro- and anti-inflammatory markers. The purpose of this cross-sectional study was to examine the associations of everyday discrimination with inflammation ratio (defined as the ratio of pro- to anti-inflammatory cytokines) in a sample of middle-aged and older Latinas. METHODS: Latinas were recruited from an existing study in New York City. Participants reported frequency and count of everyday discrimination. Peripheral blood was used to analyze pro- (IL-1B and IL-6) and anti-inflammatory (IL-4 and IL-10) cytokines. The inflammation ratio was calculated by dividing the sum of pro-inflammatory cytokines by the sum of anti-inflammatory cytokines. We used linear regression to assess the link between everyday discrimination and inflammation ratio. RESULTS: The final sample included 40 Latinas (mean age = 63.2 years). Approximately 68% had household incomes less than $15,000. More than half (53%) reported experiencing some form of everyday discrimination. Regression models showed everyday discrimination was not associated with individual pro- and anti-inflammatory cytokines. In adjusted regression models, the frequency of everyday discrimination was not associated with inflammation ratios (B[SE] = 0.57[0.30], p = .07). However, a higher count of everyday discrimination was associated with inflammation ratios (B[SE] = 1.15[0.55], p = .04). CONCLUSIONS: The count of everyday discrimination was positively associated with inflammation in Latina women. Future studies should replicate these findings using longitudinal assessment of discrimination and inflammatory markers.

Development of Pictograms for an Interactive Web Application to Help Hispanic Caregivers Learn About the Functional Stages of Dementia.

Caregivers of persons with dementia need anticipatory guidance about the stages of dementia in order to prepare for the caregiving situations they will face. The study objective was to develop a set of pictograms representing the functional stages of dementia for eventual inclusion in a tailored, educational web application. We used a hybrid iterative participatory design process. A graphic designer prepared prototypes in a flat, minimalistic style. These were then culled and refined based on feedback from 16 Hispanic caregivers in six design sessions in English and Spanish. The resulting 19 pictograms representing the functional stages and substages of dementia were acceptable to and easily comprehended by participants. Short, plain-language captions support comprehension and aid discrimination between similar scenarios. Our participants preferred candid depictions of all aspects of dementia, including bodily functions, but acceptability may vary by population so further testing is warranted prior to deployment with a new population.

Information, communication, and online tool needs of Hispanic family caregivers of individuals with Alzheimer's disease and related dementias.

PURPOSE: To identify the information and communication needs of Hispanic family caregivers for individuals with Alzheimer's Disease and Related Dementias (ADRD) and the manner in which online tools may meet those needs. METHODS: We conducted 11 participatory design sessions with 10 English- and 14 Spanish-speaking urban-dwelling Hispanic family caregivers and gathered data using a survey, collage assemblage, and audio and video recordings. Four investigators analyzed transcripts of audio recordings with a coding framework informed by several conceptual models. RESULTS: Participants had an average age of 59.7 years, were mostly female (79.2%), and had cared for a family member with ADRD for an average of 6.5 years. All participants accessed the Internet at least once a week with 75% ≥ daily. Most used the Internet to look up health information. All participants reported caregiver attributes including awareness of the disease symptoms or behaviors. The majority reported information needs/tasks (91.7%), communication needs/tasks (87.5%), and need for online tools (79.2%). CONCLUSION: Hispanic caregivers of individuals with ADRD reported key information and communication needs/tasks. Only Spanish-speaking participants reported Internet and technology use deficits suggesting the requirement for further technology support. Data show a need for online tools to meet the needs of caregivers.

Helping Hispanic Family Caregivers of Persons With Dementia "Get the Picture" About Health Status Through Tailored Infographics.

BACKGROUND AND OBJECTIVES: Caregivers need to understand their health status and the disabilities of the care recipient to engage in effective health management. Infographics tailored with personal health data are a promising approach to facilitating comprehension, particularly for individuals with low health literacy/limited English proficiency. Such approaches may be especially important for dementia caregivers given the high care burden. RESEARCH DESIGN AND METHODS: Guided by the Health Belief Model and the Data-Frame Theory of Sensemaking, we conducted iterative participatory design sessions with Hispanic family caregivers (N = 16) of persons with dementia. We created multiple prototype infographic designs to display scores on validated instruments of topics such as caregiving burden, overall health, and psychological distress. We retained and refined designs participants judged to be easily comprehensible. Analysis focused on identifying the graphical elements that contributed to the comprehensibility of designs and on evaluating participants' reactions to the designs. RESULTS: Successful infographics used intuitive scaling consistent with caregivers' perspective of dementia as inevitable decline. Participants reacted to infographics by describing the self-management actions they would take to address the health issue at hand. DISCUSSION AND IMPLICATIONS: Tailored infographics supported caregivers' comprehension of their health status and served as cues to engaging in self-management. As such, they should be presented in the context of informational support that can facilitate selection of appropriate next steps. This can mitigate the potential mental and physical health consequences of caregiving and enable caregivers to continue to care for their relatives with dementia with less damage to their own well-being.

Hispanic Dementia Family Caregiver's Knowledge, Experience, and Awareness of Self-Management: Foundations for Health Information Technology Interventions.

PURPOSE: As a first step toward developing a web-based Family-Health Information Management System intervention, we explored Hispanic dementia family caregiver's knowledge, use, and awareness of self-management principles and skills to address health and health care needs for themselves and the person with dementia (PWD). METHOD: Twenty caregivers and 11 caregiver counselors attended an English or Spanish language focus group ranging from 4 to 6 participants. We conducted a directed content analysis informed by Lorig and Holman's conceptualization of self-management. RESULTS: A complement of six skills (i.e., problem solving, decision making, resource utilization, patient-provider partnership, action planning, and self-tailoring) to achieve one of three tasks (i.e., emotional, medical, and role management) can fully represent Hispanic dementia family caregivers' ability to self-manage health and health care needs. While not prominent in our study, caregivers and caregiver counselors pointed out existing and potential uses of personal consumer technology to schedule reminders and search for resources. DISCUSSION: A broad conceptualization of self-management may be necessary to understand Hispanic dementia family caregiver's ability and needs to address emotional, medical, and role challenges of caregiving. CONCLUSIONS: These findings and advances in the use of consumer health information technology support the development of self-management caregiver interventions.

The Influence of Latino Symptom Experience on Participation in Usual Activities and Satisfaction With Participation in Social Roles.

INTRODUCTION: Little is known about the Latino symptom experience and how symptoms influence participation in usual activities and satisfaction with participation in social roles. METHOD: Secondary analysis of survey data collected in community and clinic settings was conducted. Data were collected using Health-Related Quality of Life 30-day items and Patient Reported Outcome Measurement System symptom status scales. Descriptive statistics and univariate linear and multiple linear regression models were computed. RESULTS: Participants ( N = 2,974) were primarily female and Dominican. Most surveys were completed in Spanish and in the community setting; and the clinic sample had more symptoms. In the multiple linear regression for participation in usual activities, as the number of days with symptoms increased, the number of days that poor physical or mental health influenced participation in usual activities increased. In addition, for satisfaction with participation in social roles, as the number of days with pain and levels of depression and anxiety increased, the levels of satisfaction decreased. Spanish survey administration was associated with decreased levels of satisfaction; and recruitment setting was not a significant predictor. CONCLUSION: The study addressed multiple knowledge gaps about the Latino symptom experience.

A Data Mining Approach for Exploring Correlates of Self-Reported Comparative Physical Activity Levels of Urban Latinos.

We applied data mining techniques to a community-based behavioral dataset to build prediction models to gain insights about physical activity levels as the foundation for future interventions for urban Latinos. Our application of data mining strategies identified environment factors including having a convenient location for physical activity and psychological factors including depression as the strongest correlates of self-reported comparative physical activity among hundreds of variables. The data mining methods were useful to build prediction models to gain insights about perceptions of physical activity behavior as compared to peers.

Sometimes more is more: iterative participatory design of infographics for engagement of community members with varying levels of health literacy.

OBJECTIVE: To collaborate with community members to develop tailored infographics that support comprehension of health information, engage the viewer, and may have the potential to motivate health-promoting behaviors. METHODS: The authors conducted participatory design sessions with community members, who were purposively sampled and grouped by preferred language (English, Spanish), age group (18-30, 31-60, >60 years), and level of health literacy (adequate, marginal, inadequate). Research staff elicited perceived meaning of each infographic, preferences between infographics, suggestions for improvement, and whether or not the infographics would motivate health-promoting behavior. Analysis and infographic refinement were iterative and concurrent with data collection. RESULTS: Successful designs were information-rich, supported comparison, provided context, and/or employed familiar color and symbolic analogies. Infographics that employed repeated icons to represent multiple instances of a more general class of things (e.g., apple icons to represent fruit servings) were interpreted in a rigidly literal fashion and thus were unsuitable for this community. Preliminary findings suggest that infographics may motivate health-promoting behaviors. DISCUSSION: Infographics should be information-rich, contextualize the information for the viewer, and yield an accurate meaning even if interpreted literally. CONCLUSION: Carefully designed infographics can be useful tools to support comprehension and thus help patients engage with their own health data. Infographics may contribute to patients' ability to participate in the Learning Health System through participation in the development of a robust data utility, use of clinical communication tools for health self-management, and involvement in building knowledge through patient-reported outcomes.

Factors Influencing Consent for Electronic Data Linkage in Urban Latinos.

Within the context of patient participation in a Learning Health System, this study examined consent rates and factors associated with consent for linking survey data with electronic clinical data in a sample of 2,271 Latinos. Consent rate was 96.3%. Government insurance status and health literacy significantly influenced the odds of consent.

Association between having a caregiver and clinical outcomes 1 year after hospitalization for cardiovascular disease.

Caregivers might represent an opportunity to improve cardiovascular disease outcomes, but prospective data are limited. We studied 3,188 consecutive patients (41% minority, 39% women) admitted to a university hospital medical cardiovascular service to evaluate the association between having a caregiver and rehospitalization/death at 1 year. The clinical outcomes at 1 year were documented using a hospital-based clinical information system supplemented by a standardized questionnaire. Co-morbidities were documented by hospital electronic record review. At baseline, 13% (n = 417) of the patients had a paid caregiver and 25% (n = 789) had only an informal caregiver. Having a caregiver was associated with rehospitalization or death at 1 year (odds ratio [OR] 1.68, 95% confidence interval [CI] 1.45 to 1.95), which varied by paid (OR 2.46, 95% CI 1.96 to 3.09) and informal (OR 1.40, 95% CI 1.18 to 1.65) caregiver status. Having a caregiver was significantly (p <0.05) associated with age ≥65 years, racial/ethnic minority, lack of health insurance, medical history of diabetes mellitus or hypertension, a Ghali co-morbidity index >1, chronic obstructive pulmonary disease, or taking ≥9 prescriptions medications. The relation between caregiving and rehospitalization/death at 1 year was attenuated but remained significant after adjustment (paid, OR 1.64, 95% CI 1.26 to 2.12; and informal, OR 1.20, 95% CI 1.00 to 1.44). In conclusion, the risk of rehospitalization/death was significantly greater among cardiac patients with caregivers and was not fully explained by the presence of traditional co-morbidities. Systematic determination of having a caregiver might be a simple method to identify patients at a heightened risk of poor clinical outcomes.