growth analysis
Recently Published Documents


TOTAL DOCUMENTS

1510
(FIVE YEARS 222)

H-INDEX

52
(FIVE YEARS 6)

Author(s):  
Tiara Ratz ◽  
Claudia R. Pischke ◽  
Claudia Voelcker-Rehage ◽  
Sonia Lippke

Abstract Background This study aimed to identify latent moderate-to-vigorous intensity physical activity (MVPA) and sedentary behavior (SB) trajectories in older adults participating in a randomized intervention trial and to explore associations with baseline social-cognitive predictors. Methods Data were assessed at baseline (T0, participants were inactive or had recently become active), after a ten-week physical activity intervention (T1), and a second 24-week intervention phase (T2). Latent class growth analysis was used on accelerometer-assessed weekly MVPA and daily SB, respectively (n = 215 eligible participants). Activity changes within trajectory classes and baseline social-cognitive predictor differences between trajectory classes were analyzed. Results A “stable insufficient MVPA” (n = 197, p for difference in MVPA level at T0 and T2 (pT0-T2) = .789, effect size (Cohen’s d) = .03) and a “stable high MVPA” trajectory (n = 18, pT0-T2 = .137, d = .39), as well as a “slightly decreasing high SB” (n = 63, p for difference in SB (pT0-T2) = .022, d = .36) and a “slightly increasing moderate SB” trajectory (n = 152, pT0-T2 = .019, d = .27) emerged. Belonging to the “stable high MVPA” trajectory was associated with higher action planning levels compared to the “stable insufficient MVPA” trajectory (M = 5.46 versus 4.40, d = .50). Belonging to the “decreasing high SB” trajectory was associated with higher action self-efficacy levels compared to the “increasing moderate SB” trajectory (M = 5.27 versus 4.72, d = .33). Conclusions Change occurred heterogeneously in latent (not directly observed) subgroups, with significant positive trajectories only observed in the highly sedentary. Trial registration German Registry of Clinical Trials, DRKS00016073, Registered 10 January 2019.


2021 ◽  
Author(s):  
Davide Golinelli ◽  
Alberto Grassi ◽  
Dario Tedesco ◽  
Francesco Sanmarchi ◽  
Simona Rosa ◽  
...  

Abstract Background. Patient-Reported Outcome Measures (PROMs) are an extensively used tool to assess and improve the quality of healthcare services. PROMs are affected by individual characteristics in patients undergoing hip arthroplasty (HA). The aim of this study is to identify distinct groups of patients with unique score-trajectories using the Latent Class Growth Analysis (LCGA) technique and to determine patients’ features associated with these groups.Methods. We conducted a prospective, cohort study analyzing PROMs questionnaires (Euro Quality 5 Dimensions 3L, EQ-5D-3L, Euro-Quality-Visual-Analytic-Score, EQ-VAS, Hip disability and Osteoarthritis Outcome Score, HOOS-PS) administered to patients undergoing elective HA at successive time points. For each score, LCGA was carried out to identify subgroups of patients assessed pre-operatively, and at 6 and 12 months after HA. Multinomial logistic regression was used to identify the demographic and clinical characteristics associated with the latent trajectories.Results. We identified three distinct trajectories for each PROM score. These trajectories indicated high response heterogeneity to the HA among the patients (n=991): one trajectory showing an improvement at 6 months followed by a plateau, a second trajectory showing a lower starting level followed by a consistent improvement, and a third trajectory showing a modest improvement at 6 months followed by a modest decline at 12 months. Patient’s gender, ASA score ≥3, obesity and the main diagnosis were significantly associated with different PROMs trajectories.Conclusions. These findings underline the importance of patient-centered care, supporting the usefulness of integrating PROMs data alongside routinely collected healthcare records for guiding clinical care and maximizing patient outcomes. Trial registration number: Protocol version (1.0) and trial registration data are available on the platform www.clinicaltrial.gov with the identifier NCT03790267, posted on December 31, 2018.


Sign in / Sign up

Export Citation Format

Share Document