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Dusa Marn-Vukadinovic and Helena Jamnik

Context:

Valid patient-based outcome instruments are necessary for comprehensive patient care that focuses on all aspects of health, from impairments to participation restrictions.

Objective:

To validate the Slovenian translation of Medical Outcome Survey (MOS) Short Form Health Survey (SF-36) and to assess relations among various knee measurements, activity tested with Oxford Knee Score (OKS) and health-related quality of life as estimated with SF-36 domains.

Design:

Descriptive validation study.

Setting:

Isokinetic laboratory in outpatient rehabilitation unit.

Participants:

101 subjects after unilateral sport knee injury.

Interventions:

All subjects completed the SF-36 and OKS, and isokinetic knee-muscle strength output at 60°/s was determined in 78 participants. Within a 3-d period, 43 subjects completed the SF-36 and OKS questionnaires again.

Main Outcome Measures:

Reliability testing included internal consistency and test–retest reliability. Correlations between SF-36 subscales and OKS were calculated to assess construct validity, and correlation between SF-36 subscales and muscle strength was calculated to assess concurrent validity.

Results:

Chronbach α was above .78 for all SF-36 subscales. ICCs ranged from .80 to .93. The correlation between OKS and the physical-functioning subscale, showing convergent construct validity, was higher (r = .83, P < .01) than between OKS and mental health (r = .50, P < .01), showing divergent construct validity. Knee-extensor weakness negatively correlated with physical-functioning (r = −.59, P < .01) and social-functioning (r = −.43, P < .01) subscales.

Conclusions:

The Slovenian translation of the SF-36 is a reliable and valuable tool. The relationships between knee-muscle strength and activity and between knee-muscle strength and SF-36 subscales in patients after sport knee injury were established.

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Carrie M. Geremia, Kelli L. Cain, Terry L. Conway, James F. Sallis and Brian E. Saelens

them are lengthy, costly to use, or have rarely been validated for their ability to explain park use, PA, or other outcomes. 20 For example, the EAPRS instrument is a reliable and comprehensive measure of park features and quality. 17 EAPRS has been used to examine whether the number of park features

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Heontae Kim and Minsoo Kang

battery life of the camera is dependent on the image capture rate, which can be up to 360 images per hour. Figure  2 offers samples of photos taken using the device. Validation of the Autographer as a criterion measure suggests that the absolute mean difference between the starting and ending points of

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Antonio Dello Iacono, Stephanie Valentin, Mark Sanderson and Israel Halperin

, et al . Validity of an isometric midthigh pull dynamometer in male youth athletes . J Strength Cond Res . 2018 ; 32 ( 2 ): 490 – 493 . PubMed ID: 29189578 29189578 10.1519/JSC.0000000000002324 14. Urquhart M , Bishop C , Turner AN . Validation of a crane scale for the assessment of

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James L. Farnsworth II, Todd Evans, Helen Binkley and Minsoo Kang

sample used to validate the KOOS was limited to a specific demographic group (age, sex, etc), the validity of the instrument would only be supported for that particular group. Another major limitation of classical test theory models is that error is considered consistent across all ranges of scores. The

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Wei-Ting Hsu and Min Pan

that the measures of the model were appropriate and that the global teacher RISE support construct was supported. The hierarchical structure of the TRSS is shown in Figure  1 . Figure 1 —Validated hierarchical structure of teacher RISE support. RISE = relation-inferred self-efficacy. Study 3 The

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Daniel Milton, Paul R. Appleton, Anna Bryant and Joan L. Duda

derived from scales based purely within AGT. Thus, it is possible that the SDT-based climate dimensions are not accurately defined nor sufficiently captured in the MCPES. Recently, Appleton et al. ( 2016 ) adopted Duda’s framework to inform the development and initial validation of the EDMCQ, a scale that

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Tatiane Piucco, Fernando Diefenthaeler, Rogério Soares, Juan M. Murias and Guillaume Y. Millet

J Sports Med . 2007 ; 28 : 823 – 828 . doi:10.1055/s-2007-964986 10.1055/s-2007-964986 17534782 25. Petrella NJ , Montelpare WJ , Nystrom M , Plyley M , Faught BE . Validation of the FAST skating protocol to predict aerobic power in ice hockey players . Appl Physiol Nutr Metab

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Natalie Anderton, Megan E. Newhouse, Barbara E. Ainsworth, Ingrid E. Nygaard, Marlene J. Egger and Janet M. Shaw

Background:

Measuring historical physical activity in epidemiologic research depends on self-report. We aimed to describe data reporting errors women made in completing 2 validated questionnaires: Lifetime Physical Activity Questionnaire (LPAQ) and Occupational Questionnaire (OQ).

Methods:

Participants—229 women aged 38 to 65 years—completed questionnaires on paper (n = 160) or by web interface (n = 69). One research assistant collected questionnaire data, identified potential errors and contacted participants to trouble-shoot errors.

Results:

Women made mean 9.7 (SD 11.2) errors on paper and 7.1 (SD 6.2) errors on electronic versions of the LPAQ and 2.6 (SD 3.8) and 1.1 (SD 1.4) errors on paper and electronic versions of the OQ, respectively. Fewer mistakes were made on electronic versions of both questionnaires combined (8.5 ± 6.1) when compared with the paper versions (12.7 ± 13.1). Only ~2% of the sample completed all questionnaires without detectable errors. The most common errors were reporting activities or frequencies inconsistently between past year survey and the current age epoch, reporting more years than allowed by age epoch and missing information.

Conclusions:

Despite the implications of “self-report” questionnaires, we recommend researchers provide participants with additional instructions, either verbally or as written tip sheet or both, and follow-up after questionnaire completion to correct mistakes as needed.

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Jared M. Tucker, Greg Welk, Sarah M. Nusser, Nicholas K. Beyler and David Dzewaltowski

Background:

This study was designed to develop a prediction algorithm that would allow the Previous Day Physical Activity Recall (PDPAR) to be equated with temporally matched data from an accelerometer.

Methods:

Participants (n = 121) from a large, school-based intervention wore a validated accelerometer and completed the PDPAR for 3 consecutive days. Physical activity estimates were obtained from PDPAR by totaling 30-minute bouts of activity coded as ≥4 METS. A regression equation was developed in a calibration sample (n = 91) to predict accelerometer minutes of moderate to vigorous physical activity (MVPA) from PDPAR bouts. The regression equation was then applied to a separate, holdout sample (n = 30) to evaluate the utility of the prediction algorithm.

Results:

Gender and PDPAR bouts accounted for 36.6% of the variance in accelerometer MVPA. The regression model showed that on average boys obtain 9.0 min of MVPA for each reported PDPAR bout, while girls obtain 4.8 min of MVPA per bout. When applied to the holdout sample, predicted minutes of MVPA from the models showed good agreement with accelerometer minutes (r = .81).

Conclusions:

The prediction equation provides a valid and useful metric to aid in the interpretation of PDPAR results.