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Dean Dudley, Victoria Goodyear and David Baxter

Background:

The United Nations Educational, Cultural and Scientific Organization (UNESCO) recognizes quality physical education (QPE) must, along with physical, social and affective educative goals, seek to improve the health status of youth (UNESCO, 2015). Health-Optimizing Physical Education (HOPE) is a model of physical education (PE) that seeks this goal but is creating much debate in the discipline (Sallis et al., 2012).

Purpose:

The aim of this paper is to present a conceptual assessment framework for QPE and HOPE on which future assessment protocols may be based that serve both health and educative goals.

Methods/Data analysis:

Policy and literature pertaining to QPE and HOPE were reviewed and compared for similarities and differences. This was followed by an analysis of literature on assessment in the health and education disciplines. These analyses provided the authors with the insight to propose a new model of assessment for HOPE models to implement QPE.

Results:

Many similarities exist in the policy of QPE and the published literature on HOPE. However, the measurement model of assessment can often circumvent two important assessment functions for education settings that need to be addressed in a wider QPE and Models-Based Practice (MBP) context. Conclusions: HOPE models were established using an interventionist mindset and are therefore well suited to integrating well-defined MBP pedagogies as appropriate ‘intervening’ strategies by using a clinical approach to teaching and assessment. To date, they have lacked an assessment framework that has been capable of addressing both the health and educative goals that both HOPE and MBP seek to achieve. This paper provides new insight by reimagining the role MBPs and assessment practices have to play in the health and education nexus.

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Shannon J. FitzGerald, Carolyn E. Barlow, James B. Kampert, James R. Morrow Jr., Allen W. Jackson and Steven N. Blair

Background:

The beneficial effects of cardiorespiratory fitness on mortality are well known; however, the relation of muscular fitness, specifically muscular strength and endurance, to mortality risk has not been thoroughly examined. The purpose of the current study is to determine if a dose-response relation exists between muscular fitness and mortality after controlling for factors such as age and cardiorespiratory fitness.

Methods:

The study included 9105 men and women, 20–82 years of age, in the Aerobics Center Longitudinal Study who have completed at least one medical examination at the Cooper Clinic in Dallas, TX between 1981 and 1989. The exam included a muscular fitness assessment, based on 1-min sit-up and 1-repetition maximal leg and bench press scores, and a maximal treadmill test. We conducted mortality follow-up through 1996 primarily using the National Death Index, with a total follow-up of 106,046 person-years. All-cause mortality rates were examined across low, moderate, and high muscular fitness strata.

Results:

Mortality was confirmed in 194 of 9105 participants (2.1%). The age- and sex-adjusted mortality rate of those in the lowest muscular fitness category was higher than that of those in the moderate fitness category (26.8 vs. 15.3 per 10,000 person-years, respectively). Those in the high fitness category had a mortality rate of 20.6 per 10,000 person-years. The moderate and high muscular fitness groups had relative risks of 0.64 (95%CI = 0.44–0.93) and 0.80 (95%CI = 0.49–1.31), adjusting for age, health status, body mass index, cigarette smoking, and cardio-respiratory fitness when compared with the low muscular fitness group.

Conclusions:

Mortality rates were lower for individuals with moderate/high muscular fitness compared to individuals with low muscular fitness. These findings warrant further research to confirm the apparent threshold effect between low and moderate/high muscular fitness and all-cause mortality.

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Jeff S. Volek, Noel D. Duncan, Scott A. Mazzetti, Margot Putukian, Ana L. Gómez and William J. Kraemer

In order to examine the effects of heavy resistance training and the influence of creatine supplementation on nonperformance measures of health status, 19 healthy resistance-trained men were matched and then randomly assigned in a double-blind fashion to either a creatine (n = 10) or placebo (n = 9) group. Periodized heavy resistance training was performed 3—4 times per week for 12 weeks. During the first week of training, creatine subjects consumed 25 g creatine monohydrate per day, while the placebo group ingested an equal number of placebo capsules. Five grams of supplement per day was consumed for the remainder of the study. Body composition, fasting serum creatinine, lipo-proteins and triglycerides, and reported changes in body function were determined prior to and after 12 weeks of training and supplementation. After training, significant increases in body mass and fat-free mass were greater in creatine (5.2 and 4.3 kg, respectively) than placebo (3.0 and 2.1 kg. respectively) subjects. There was no change in percent body fat. Dietary energy and macronutrient distribution was not significantly different during Weeks 1 and 12. Serum creatinine was significantly elevated in creatine subjects after 1(11.6%) and 12 weeks (13.8%); however, values were within normal limits for healthy men. There were no effects of training or supplementation on serum total cholesterol, HDL-cholesterol, LDL-cholesterol. or triglycerides. In healthy men, a 12-week heavy resistance training program, with or without creatine supplementation, did not significantly influence serum lipid profiles, subjective reports of body functioning, or serum creatinine concentrations.

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Hsin-Yen Yen and Hsuan Hsu

, public sectors, and countries; Cheadle et al., 2018 ). Individuals’ characteristics and current health status affect whether they engage in healthy behaviors. According to the Health Belief Model, the way individuals perceive the current severity of their health status impacts their attitudes toward

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Ashleigh J. Sowle, Sarah L. Francis, Jennifer A. Margrett, Mack C. Shelley and Warren D. Franke

(age, gender, ethnicity, self-reported health status, living arrangements, marital status, and contact with younger adults), self-reported PA readiness-to-change, self-efficacy to overcome perceived barriers to PA, and PA self-efficacy. Education status and cognitive status were not measured. Self

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Research Improving Health Status through Physical Activity for Individuals with Chronic Pulmonary Diseases Alain Varray * Alain Varray * 4 2006 23 2 111 128 10.1123/apaq.23.2.111 A Multi-Level Examination of Personality, Exercise, and Daily Life Events for Individuals with Physical Disabilities

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Carina Bauer, Christine Graf, Anna M. Platschek, Heiko K. Strüder and Nina Ferrari

American College of Obstetricians and Gynecologists 21 in less than 150 minutes per week and at least 150 minutes per week. Furthermore, the type of exercise during pregnancy was assessed to document the women’s preferred types of sports. Current and General Health Status A standardized questionnaire was

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Concentration: A Randomized Crossover Trial Laura A. Brocklebank * Rob C. Andrews * Angie Page * Catherine L. Falconer * Sam Leary * Ashley Cooper * 8 2017 14 8 617 625 jpah.2016-0366 10.1123/jpah.2016-0366 Combining Activity-Related Behaviors and Attributes Improves Prediction of Health Status in

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Viviane Ribeiro de Ávila, Teresa Bento, Wellington Gomes, José Leitão and Nelson Fortuna de Sousa

: functional capacity, physical aspect, bodily pain, general health status, vitality and energy, social aspects, emotional aspect, and mental health; and have been published in the English language. The exclusion criteria were: fractures (stress, pediatric, pathological, calcaneus, tibial pilon, diaphyseal of

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Diego Munguia-Izquierdo, Carmen Mayolas-Pi, Carlos Peñarrubia-Lozano, Federico Paris-Garcia, Javier Bueno-Antequera, Miguel Angel Oviedo-Caro and Alejandro Legaz-Arrese

included questions about sociodemographic status, training, athletic performance, and health status. There was no time limit for completing the questionnaires. The questionnaires took an average of 40 minutes to complete, and the Internet design prevented missing data. The cyclists were classified into 2