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    Item type:Publication,
    Barriers To The Practice Of Physical Activity Among Adults According To Socioeconomic Status In Chile
    (2020)
    María Fernanda Sanhueza
    ;
    Rocío Nuche
    ;
    Bárbara Munizaga
    ;
    ;
    Sandra Mahecha-Matsudo
      8
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    Effects of 24-hours/day versus business hours physical therapy intervention in adult intensive care unit patients: a systematic review
    (2018)
    CATALINA MARIA MERINO OSORIO
    ;
    Ana Cristina Castro-Ávila
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    Ruvistay Gutiérrez Arias
    ;
    María Jesús Arriagada
    ;
    Catalina Villanueva
      3
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    Results From Chile’s 2016 Report Card on Physical Activity for Children and Youth
    (2016)
    Nicolas Aguilar-Farias
    ;
    Andrea Cortinez-O’Ryan
    ;
    Kabir P. Sadarangani
    ;
    Astrid Von Oetinger
    ;
    <jats:sec sec-type="background"><jats:title>Background:</jats:title><jats:p>The 2016 Chilean Report Card on Physical Activity for Children and Youth is a review of the evidence across indicators of behaviors, settings, and sources of influence associated with physical activity (PA) of Chilean children and youth.</jats:p></jats:sec><jats:sec sec-type="methods"><jats:title>Methods:</jats:title><jats:p>A Research Work Group reviewed available evidence from publications, surveys, government documents and datasets to assign a grade for 11 indicators for PA behavior based on the percentage of compliance for defined benchmarks. Grades were defined as follows: <jats:italic>A</jats:italic>, 81% to 100% of children accomplishing a given benchmark; <jats:italic>B</jats:italic>, 61% to 80%; <jats:italic>C</jats:italic>, 41% to 60%; <jats:italic>D</jats:italic>, 21% to 40%; <jats:italic>F</jats:italic>, 0% to 20%; <jats:italic>INC</jats:italic>, incomplete data available to assign score.</jats:p></jats:sec><jats:sec sec-type="results"><jats:title>Results:</jats:title><jats:p>Grades assigned were for i) ‘Behaviors that contribute to overall PA levels’: Overall PA, <jats:italic>F</jats:italic>; Organized Sport Participation, <jats:italic>D</jats:italic>; Active Play, <jats:italic>INC</jats:italic>; and Active Transportation, <jats:italic>C</jats:italic>-; ii) ‘Factors associated with cardiometabolic risk’: Sedentary Behavior, <jats:italic>D</jats:italic>; Overweight and Obesity, <jats:italic>F</jats:italic>; Fitness, <jats:italic>F</jats:italic>; and iii) ‘Factors that influence PA’: Family and Peers, <jats:italic>D</jats:italic>; School, <jats:italic>D</jats:italic>; Community and Built Environment, <jats:italic>C</jats:italic>; Government Strategies and Investments, <jats:italic>C</jats:italic>.</jats:p></jats:sec><jats:sec sec-type="conclusions"><jats:title>Conclusions:</jats:title><jats:p>Chile faces a major challenge as most PA indicators scored low. There were clear research and information gaps that need to be filled with the implementation of consistent and regular data collection methods.</jats:p></jats:sec>
      7Scopus© Citations 37
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      1
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    Study protocol and rationale of “the UP project”: evaluating the effectiveness of active breaks on health indicators in desk-based workers
    (2024)
    Carlos Cristi-Montero
    ;
    Ricardo Martínez-Flores
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    Juan Pablo Espinoza-Puelles
    ;
    Laura Favero-Ramirez
    ;
    Natalia Zurita-Corvalan
    <jats:sec><jats:title>Background</jats:title><jats:p>Excessive sedentary time has been negatively associated with several health outcomes, and physical activity alone does not seem to fully counteract these consequences. This panorama emphasizes the essential of sedentary time interruption programs. “The Up Project” seeks to assess the effectiveness of two interventions, one incorporating active breaks led by a professional and the other utilizing a computer application (self-led), of both equivalent duration and intensity. These interventions will be compared with a control group to evaluate their impact on physical activity levels, sedentary time, stress perception, occupational pain, and cardiometabolic risk factors among office workers.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>This quasi-experimental study includes 60 desk-based workers from universities and educational institutes in Valparaiso, Chile, assigned to three groups: (a) booster breaks led by professionals, (b) computer prompts that are unled, and (c) a control group. The intervention protocol for both experimental groups will last 12 weeks (only weekdays). The following measurements will be performed at baseline and post-intervention: cardiometabolic risk based on body composition (fat mass, fat-free mass, and bone mass evaluated by DXA), waist circumference, blood pressure, resting heart rate, and handgrip strength. Physical activity and sedentary time will be self-reported and device-based assessed using accelerometry. Questionnaires will be used to determine the perception of stress and occupational pain.</jats:p></jats:sec><jats:sec><jats:title>Discussion</jats:title><jats:p>Governments worldwide are addressing health issues associated with sedentary behavior, particularly concerning individuals highly exposed to it, such as desk-based workers. Despite implementing certain strategies, there remains a noticeable gap in comprehensive research comparing diverse protocols. For instance, studies that contrast the outcomes of interventions led by professionals with those prompted by computers are scarce. This ongoing project is expected to contribute to evidence-based interventions targeting reduced perceived stress levels and enhancing desk-based employees’ mental and physical well-being. The implications of these findings could have the capacity to lay the groundwork for future public health initiatives and government-funded programs.</jats:p></jats:sec>
      12Scopus© Citations 1
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    Higher physical activity levels are associated with lower prevalence of cardiovascular risk factors in Chile
    (2015)
    Carlos Celis-Morales
    ;
    Carlos Salas
    ;
    Cristian Álvarez
    ;
    Nicolás Aguilar Farías
    ;
    Rodrigo Ramírez Campillos
      20Scopus© Citations 39
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    Six-month post-intensive care outcomes during high and low bed occupancy due to the COVID-19 pandemic: A multicenter prospective cohort study
    <jats:sec id="sec001"> <jats:title>Introduction</jats:title> <jats:p>The COVID-19 pandemic can be seen as a natural experiment to test how bed occupancy affects post-intensive care unit (ICU) patient’s functional outcomes. To compare by bed occupancy the frequency of mental, physical, and cognitive impairments in patients admitted to ICU during the COVID-19 pandemic.</jats:p> </jats:sec> <jats:sec id="sec002"> <jats:title>Methods</jats:title> <jats:p>Prospective cohort of adults mechanically ventilated &gt;48 hours in 19 ICUs from seven Chilean public and private hospitals. Ninety percent of nationwide beds occupied was the cut-off for low versus high bed occupancy. At ICU discharge, 3- and 6-month follow-up, we assessed disability using the World Health Organization Disability Assessment Schedule 2.0. Quality of life, mental, physical, and cognitive outcomes were also evaluated following the core outcome set for acute respiratory failure.</jats:p> </jats:sec> <jats:sec id="sec003"> <jats:title>Results</jats:title> <jats:p>We enrolled 252 participants, 103 (41%) during low and 149 (59%) during high bed occupancy. Patients treated during high occupancy were younger (P<jats:sub>50</jats:sub> [P<jats:sub>25</jats:sub>-P<jats:sub>75</jats:sub>]: 55 [44–63] vs 61 [51–71]; p&lt;0.001), more likely to be admitted due to COVID-19 (126 [85%] vs 65 [63%]; p&lt;0.001), and have higher education qualification (94 [63%] vs 48 [47%]; p = 0.03). No differences were found in the frequency of at least one mental, physical or cognitive impairment by bed occupancy at ICU discharge (low vs high: 93% vs 91%; p = 0.6), 3-month (74% vs 63%; p = 0.2) and 6-month (57% vs 57%; p = 0.9) follow-up.</jats:p> </jats:sec> <jats:sec id="sec004"> <jats:title>Conclusions</jats:title> <jats:p>There were no differences in post-ICU outcomes between high and low bed occupancy. Most patients (&gt;90%) had at least one mental, physical or cognitive impairment at ICU discharge, which remained high at 6-month follow-up (57%).</jats:p> </jats:sec> <jats:sec id="sec005"> <jats:title>Clinical trial registration</jats:title> <jats:p><jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://clinicaltrials.gov/ct2/show/NCT04979897" xlink:type="simple">NCT04979897</jats:ext-link> (clinicaltrials.gov).</jats:p> </jats:sec>
      3Scopus© Citations 3
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    Reliability of a pressure pain threshold protocol: secondary analysis of a longitudinal trial with cluster randomization
    (PeerJ, 2026-02-25)
    Pedro Aguila-Humeres
    ;
    <jats:sec> <jats:title>Background</jats:title> <jats:p>Pressure Pain Threshold (PPT) measurement is a useful method for assessing pain sensitivity when applied with a standardized protocol. However, little is known about the longitudinal stability of reliability estimates when PPT protocols are embedded in randomized controlled trials. This study aimed to estimate the relative and absolute reliability of a PPT algometry protocol in office workers across multiple time points within a six-month pragmatic randomized controlled trial.</jats:p> </jats:sec> <jats:sec> <jats:title>Methods</jats:title> <jats:p>A secondary analysis was conducted from a cluster randomized controlled trial with office workers, where a standardized PPT protocol was applied to the neck, forearm, and lower leg. Measurements were taken bilaterally with three repetitions per site. Measurement reliability was assessed with a two-way mixed-effects intraclass correlation (ICC) model for absolute agreement (3, k), along with the Standard Error of Measurement (SEM) and Minimal Detectable Change (MDC), calculated at baseline, three, and six months, for both intervention and control groups.</jats:p> </jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p> ICC values ranged from 0.84 to 0.95, indicating good to excellent reliability across all time points and body regions. SEM ranged from 0.23 kg/cm <jats:sup>2</jats:sup> to 0.51 kg/cm <jats:sup>2</jats:sup> , and MDC from 0.52 kg/cm <jats:sup>2</jats:sup> to 1.15 kg/cm <jats:sup>2</jats:sup> . These values remained consistent across follow-up periods in both groups, despite expected variability due to the intervention. </jats:p> </jats:sec> <jats:sec> <jats:title>Conclusions</jats:title> <jats:p>The PPT protocol demonstrated high measurement reliability and stable properties over time for each anatomic region and both groups, supporting its use in longitudinal assessments of pain sensitivity in occupational and clinical settings.</jats:p> </jats:sec>
      1
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    Hypoglycemia and glycemic variability of people with type 1 diabetes with lower and higher physical activity loads in free-living conditions using continuous subcutaneous insulin infusion with predictive low-glucose suspend system
    (2023)
    Denise Montt-Blanchard
    ;
    Raimundo Sánchez
    ;
    Karen Dubois-Camacho
    ;
    ;
    María Teresa Onetto
    <jats:sec><jats:title>Introduction</jats:title><jats:p>Maintaining glycemic control during and after physical activity (PA) is a major challenge in type 1 diabetes (T1D). This study compared the glycemic variability and exercise-related diabetic management strategies of adults with T1D achieving higher and lower PA loads in nighttime–daytime and active– sedentary behavior hours in free-living conditions.</jats:p></jats:sec><jats:sec><jats:title>Research design and methods</jats:title><jats:p>Active adults (n=28) with T1D (ages: 35±10 years; diabetes duration: 21±11 years; body mass index: 24.8±3.4 kg/m<jats:sup>2</jats:sup>; glycated hemoglobin A1c: 6.9±0.6%) on continuous subcutaneous insulin delivery system with predictive low glucose suspend system and glucose monitoring, performed different types, duration and intensity of PA under free-living conditions, tracked by accelerometer over 14 days. Participants were equally divided into lower load (LL) and higher load (HL) by median of daily counts per minute (61122). Glycemic variability was studied monitoring predefined time in glycemic ranges (time in range (TIR), time above range (TAR) and time below range (TBR)), coefficient of variation (CV) and mean amplitude of glycemic excursions (MAGE). Parameters were studied in defined hours timeframes (nighttime–daytime and active–sedentary behavior). Self-reported diabetes management strategies were analysed during and post-PA.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Higher glycemic variability (CV) was observed in sedentary hours compared with active hours in the LL group (p≤0.05). HL group showed an increment in glycemic variability (MAGE) during nighttime versus daytime (p≤0.05). There were no differences in TIR and TAR across all timeframes between HL and LL groups. The HL group had significantly more TBR during night hours than the LL group (p≤0.05). Both groups showed TBR above recommended values. All participants used fewer post-PA management strategies than during PA (p≤0.05).</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>Active people with T1D are able to maintain glycemic variability, TIR and TAR within recommended values regardless of PA loads. However, the high prevalence of TBR and the less use of post-PA management strategies highlights the potential need to increase awareness on actions to avoid glycemic excursions and hypoglycemia after exercise completion.</jats:p></jats:sec>
      2Scopus© Citations 6
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    DETECTING SPORTING TALENTS WITH Z-STRATEGY - CROSS SECTIONAL STUDY
    (2020)
    Josivaldo de Souza-Lima
    ;
    ;
    Rodrigo Yáñez-Sepúlveda
    ;
    Victor Keihan Rodrigues Matsudo
    ;
    Sandra Mahecha-Matsudo
    <jats:p>ABSTRACT Introduction: Due to the relationship between early identification of physical and anthropometric characteristics above the population mean in children and adolescents, and success in sports, detecting potential sports talents should be broadly and systematically used as a strategy for the early identification of physical characteristics favorable to the sport in question. However, most studies do not use representative samples, or else they present talent detection without using valid scientific methods. This retrospective, comparative study therefore presents the identification of potential sports talents using the Z Strategy, calculated with anthropometric, neuromotor and physical fitness data. Objective: To identify physical abilities and anthropometric values above what are considered the normal ranges in a population of students in the 8th year of basic education, in Chile. Methods: The sample consisted of 9,429 students from public and private schools (50.9% boys). Data were obtained from a cross-sectional study conducted in 2013. Physical fitness and anthropometric data were recompiled through the Educational Quality Measurement System (Sistema de Medición de la Calidad de Educación – SIMCE) of physical education. The “Z Strategy” was used to detect sports talents by identifying values above the population mean. Results: In at least one variable, a total of 619 male and 623 female students with a standard deviation ≥2 (Z2) were detected. Conclusion: “Z Strategy” was able to detect sports talents of both sexes and of different ages. Level of evidence III; Retrospective comparative study.</jats:p>
    Scopus© Citations 4  2