61 research outputs found
Association Between Sedentary Time and Quality of Life From the Osteoarthritis Initiative: Who Might Benefit Most From Treatment?
Objective To investigate the relationship between sedentary behavior and quality-adjusted life years (QALYs) among participants in the Osteoarthritis Initiative. Design Longitudinal, observational design. Setting Osteoarthritis Initiative cohort. Participants
Individuals (N=1794) from a prospective, multicenter longitudinal cohort were classified into quantile groups based on average daily sedentary time (most sedentary, quartile 1 [Q1] â„11.6h; 10.7h†Q2 Interventions Not applicable. Main Outcome Measures Individual QALYs were estimated over 2 years from the area under the curve of health-related utility scores derived from the Medical Outcomes Study 12-Item Short-Form Health Survey versus time. The relationship between baseline sedentary behavior and median 2-year QALYs was estimated using quantile regression adjusted for socioeconomic factors and body mass index. Results Lower QALYs over 2 years were more frequently found among the most sedentary (Q1, median 1.59), and QALYs increased as time spent in baseline sedentary behavior decreased (median QALYs for Q2, 1.64; Q3, 1.65; Q4, 1.65). The relationship of sedentary time and median QALY change was only significant for the most sedentary Q1 group, where an additional hour of sedentary behavior significantly reduced QALYs by â.072 (95% confidence interval, â.121 to â.020). Conclusions Our findings suggest that individuals with the most extreme sedentary profiles may be vulnerable to additional losses of quality of life if they become more sedentary. Targeting these individuals to decrease sedentary behavior has the potential to be cost-effective
Physical Activity Minimum Threshold Predicting Improved Function in Adults With LowerâExtremity Symptoms
Objective
To identify an evidenceâbased minimum physical activity threshold to predict improved or sustained high function for adults with lowerâextremity joint symptoms. Methods
Prospective multisite data from 1,629 adults, age â„49 years with symptomatic lowerâextremity joint pain/aching/stiffness, participating in the Osteoarthritis Initiative accelerometer monitoring substudy were clinically assessed 2 years apart. Improved/high function in 2âyear gait speed and patientâreported outcomes (PROs) were based on improving or remaining in the best (i.e., maintaining high) function quintile compared to baseline status. Optimal thresholds predicting improved/high function were investigated using classification trees for the legacy federal guideline metric requiring 150 minutes/week of moderateâvigorous (MV) activity in bouts lasting 10 minutes or more (MVâbout) and other metrics (total MV, sedentary, light intensity activity, nonsedentary minutes/week). Results
Optimal thresholds based on total MV minutes/week predicted improved/high function outcomes more strongly than the legacy or other investigated metrics. Meeting the 45 total MV minutes/week threshold had increased relative risk (RR) for improved/high function (gait speed RR 1.8, 95% confidence interval [95% CI] 1.6, 2.1 and PRO physical function RR 1.4, 95% CI 1.3, 1.6) compared to less active adults. Thresholds were consistent across sex, body mass index, knee osteoarthritis status, and age. Conclusion
These results supported a physical activity minimum threshold of 45 total MV minutes/week to promote improved or sustained high function for adults with lowerâextremity joint symptoms. This evidenceâbased threshold is less rigorous than federal guidelines (â„150 MVâbout minutes/week) and provides an intermediate goal towards the federal guideline for adults with lowerâextremity symptoms
Redesigning Systems to Improve Teamwork and Quality for Hospitalized Patients (RESET): Study Protocol Evaluating the Effect of Mentored Implementation to Redesign Clinical Microsystems
Background: A number of challenges impede our ability to consistently provide high quality care to patients hospitalized with medical conditions. Teams are large, team membership continually evolves, and physicians are often spread across multiple units and floors. Moreover, patients and family members are generally poorly informed and lack opportunities to partner in decision making. Prior studies have tested interventions to redesign aspects of the care delivery system for hospitalized medical patients, but the majority have evaluated the effect of a single intervention. We believe these interventions represent complementary and mutually reinforcing components of a redesigned clinical microsystem. Our specific objective for this study is to implement a set of evidence-based complementary interventions across a range of clinical microsystems, identify factors and strategies associated with successful implementation, and evaluate the impact on quality.
Methods: The RESET project uses the Advanced and Integrated MicroSystems (AIMS) interventions. The AIMS interventions consist of 1) Unit-based Physician Teams, 2) Unit Nurse-Physician Co-leadership, 3) Enhanced Interprofessional Rounds, 4) Unit-level Performance Reports, and 5) Patient Engagement Activities. Four hospital sites were chosen to receive guidance and resources as they implement the AIMS interventions. Each study site has assembled a local leadership team, consisting of a physician and nurse, and receives mentorship from a physician and nurse with experience in leading similar interventions. Primary outcomes include teamwork climate, assessed using the Safety Attitudes Questionnaire, and adverse events using the Medicare Patient Safety Monitoring System (MPSMS). RESET uses a parallel group study design and two group pretest-posttest analyses for primary outcomes. We use a multi-method approach to collect and triangulate qualitative data collected during 3 visits to study sites. We will use cross-case comparisons to consider how site-specific contextual factors interact with the variation in the intensity and fidelity of implementation to affect teamwork and patient outcomes.
Discussion: The RESET study provides mentorship and resources to assist hospitals as they implement complementary and mutually reinforcing components to redesign the clinical microsystems caring for medical patients. Our findings will be of interest and directly applicable to all hospitals providing care to patients with medical conditions.
Trial Registration: NCT03745677. Retrospectively registered on November 19, 2018
Preferences for Physical Activity: a Conjoint Analysis Involving People with Chronic Knee Pain
Objective
To investigate individual preferences for physical activity (PA) attributes in adults with chronic knee pain, to identify clusters of individuals with similar preferences, and to identify whether individuals in these clusters differ by their demographic and health characteristics. Design
An adaptive conjoint analysis (ACA) was conducted using the Potentially All Pairwise RanKings of all possible Alternatives (PAPRIKA) method to determine preference weights representing the relative importance of six PA attributes. Cluster analysis was performed to identify clusters of participants with similar weights. Chi-square and ANOVA were used to assess differences in individual characteristics by cluster. Multinomial logistic regression was used to assess associations between individual characteristics and cluster assignment. Results
The study sample included 146 participants; mean age 65, 72% female, 47% white, non-Hispanic. The six attributes (mean weights in parentheses) are: health benefit (0.26), enjoyment (0.24), convenience (0.16), financial cost (0.13), effort (0.11) and time cost (0.10). Three clusters were identified: Cluster 1 (n = 33): for whom enjoyment (0.35) is twice as important as health benefit; Cluster 2 (n = 63): for whom health benefit (0.38) is most important; and Cluster 3 (n = 50): for whom cost (0.18), effort (0.18), health benefit (0.17) and enjoyment (0.18) are equally important. Cluster 1 was healthiest, Cluster 2 most self-efficacious, and Cluster 3 was in poorest health. Conclusions
Patients with chronic knee pain have preferences for PA that can be distinguished effectively using ACA methods. Adults with chronic knee pain, clustered by PA preferences, share distinguishing characteristics. Understanding preferences may help clinicians and researchers to better tailor PA interventions
A Randomized Trial of a Motivational Interviewing Intervention to Increase Lifestyle Physical Activity and Improve Self-Reported Function in Adults with Arthritis
Background
Arthritis is a leading cause of chronic pain and functional limitations. Exercise is beneficial for improving strength and function and decreasing pain. We evaluated the effect of a motivational interviewing-based lifestyle physical activity intervention on self-reported physical function in adults with knee osteoarthritis (KOA) or rheumatoid arthritis (RA). Methods
Participants were randomized to intervention or control. Control participants received a brief physician recommendation to increase physical activity to meet national guidelines. Intervention participants received the same brief baseline physician recommendation in addition to motivational interviewing sessions at baseline, 3, 6, and 12 months. These sessions focused on facilitating individualized lifestyle physical activity goal setting. The primary outcome was change in self-reported physical function. Secondary outcomes were self-reported pain and accelerometer-measured physical activity. Self-reported KOA outcomes were evaluated by the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) for KOA (WOMAC scores range from 0 to 68 for function and 0 to 20 for pain) and the Health Assessment Questionnaire (HAQ) for RA. Outcomes were measured at baseline, 3, 6, 12, and 24 months. Multiple regression accounting for repeated measures was used to evaluate the overall intervention effect on outcomes controlling for baseline values. Results
Participants included 155 adults with KOA (76 intervention and 79 control) and 185 adults with RA (93 intervention and 92 control). Among KOA participants, WOMAC physical function improvement was greater in the intervention group compared to the control group [difference = 2.21 (95% CI: 0.01, 4.41)]. WOMAC pain improvement was greater in the intervention group compared to the control group [difference = 0.70 (95% CI: â0.004, 1.41)]. There were no significant changes in physical activity. Among RA participants, no significant intervention effects were found. Conclusion
Participants with KOA receiving the lifestyle intervention experienced modest improvement in self-reported function and a trend toward improved pain compared to controls. There was no intervention effect for RA participants. Further refinement of this intervention is needed for more robust improvement in function, pain, and physical activity
The SOS-framework (Systems of Sedentary behaviours): an international transdisciplinary consensus framework for the study of determinants, research priorities and policy on sedentary behaviour across the life course: a DEDIPAC-study.
BACKGROUND: Ecological models are currently the most used approaches to classify and conceptualise determinants of sedentary behaviour, but these approaches are limited in their ability to capture the complexity of and interplay between determinants. The aim of the project described here was to develop a transdisciplinary dynamic framework, grounded in a system-based approach, for research on determinants of sedentary behaviour across the life span and intervention and policy planning and evaluation.
METHODS: A comprehensive concept mapping approach was used to develop the Systems Of Sedentary behaviours (SOS) framework, involving four main phases: (1) preparation, (2) generation of statements, (3) structuring (sorting and ranking), and (4) analysis and interpretation. The first two phases were undertaken between December 2013 and February 2015 by the DEDIPAC KH team (DEterminants of DIet and Physical Activity Knowledge Hub). The last two phases were completed during a two-day consensus meeting in June 2015.
RESULTS: During the first phase, 550 factors regarding sedentary behaviour were listed across three age groups (i.e., youths, adults and older adults), which were reduced to a final list of 190 life course factors in phase 2 used during the consensus meeting. In total, 69 international delegates, seven invited experts and one concept mapping consultant attended the consensus meeting. The final framework obtained during that meeting consisted of six clusters of determinants: Physical Health and Wellbeing (71% consensus), Social and Cultural Context (59% consensus), Built and Natural Environment (65% consensus), Psychology and Behaviour (80% consensus), Politics and Economics (78% consensus), and Institutional and Home Settings (78% consensus). Conducting studies on Institutional Settings was ranked as the first research priority. The view that this framework captures a system-based map of determinants of sedentary behaviour was expressed by 89% of the participants.
CONCLUSION: Through an international transdisciplinary consensus process, the SOS framework was developed for the determinants of sedentary behaviour through the life course. Investigating the influence of Institutional and Home Settings was deemed to be the most important area of research to focus on at present and potentially the most modifiable. The SOS framework can be used as an important tool to prioritise future research and to develop policies to reduce sedentary time
Transcriptional Profiling of Synovial Macrophages Using Minimally Invasive UltrasoundĂą Guided Synovial Biopsies in Rheumatoid Arthritis
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/144312/1/art40453_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144312/2/art40453.pd
Developmental trajectories of physical activity and television viewing during adolescence among girls: National Growth and Health Cohort Study
Obesity and other modifiable factors for physical inactivity measured by accelerometer in adults with knee osteoarthritis.
Variance estimation of partial population attributable fraction and its applications.
Variance estimation of partial population attributable fraction and its applications
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