The external test is the tenth and final building block of the first and second stage of the Business Model Template (BMT). You will test the viability of the business model concept you have developed so far. You can test your business model idea against all kinds of...
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Background There currently is no field test available for measuring maximal exercise capacity in people with stroke. Objective To determine the feasibility, reproducibility and validity of the Shuttle Test (ST) to measure exercise capacity in people with stroke. Design Longitudinal study design. Setting Rehabilitation department, day care centres from a nursing home and private practices specialized in neuro rehabilitation. Subjects People with subacute or chronic stroke. Interventions A standardized protocol was used to determine feasibility, reproducibility and validity of the 10-meter Shuttle Test (10mST). Main measures Number of shuttles completed, 1stVentilatory Threshold (1stVT). Results The associations of the number of shuttles completed and cardiopulmonary capacity as measured with a portable gas analyser were r > 0.7, confirming good convergent validity in subacute and chronic people with stroke. Criterion validity, however, indicates it is not a valid test for measuring maximal cardiopulmonary capacity (VO2max). Only 60% of participants were able to reach the 1stVT. Higher cardiopulmonary capacity and a higher total score of the lower extremity Motricity Index contributed significantly to a higher number of shuttles walked (p = 0.001). Conclusions The Shuttle Test may be a safe and useful exercise test for people after stroke, but may not be appropriate for use with people who walk slower than 2 km/h or 0.56 m/s.
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De balans tussen de belastbaarheid van sporters en de belasting moeten zo goed mogelijk afgestemd zijn om optimale trainingseffecten te realizeren. Er wordt onderscheid gemaakt tussen externe en interne trainingsbelasting, wat duidt op de belasting die extern of intern door de sporter wordt ervaren. Het sturen en bewaken van de balans wordt bij professionele sporters doorgaans verzorgd door (para)medische professionals en/of sportwetenschappers. Doordat er tegenwoordig vele manieren van test- en meettechnologie zijn om o.a. interne en externe belasting te meten is er een grote hoeveelheid aan data beschikbaar in de praktijk, waarvan het verwerken en analyseren arbeidsintensief is. Daarom is er vanuit de praktijk de behoefte om deze data snel inzichtelijk te maken. Vanuit het project is daarom een belastingsmonitor ontwikkeld o.b.v. big data technologieën. Het doel van dit rapport is een praktijkvalidatie van de belastingmonitor. Hierbij wordt enerzijds gekeken naar de verzamelde data door de praktijkpartners en anderzijds wordt onderzocht of veranderingen in ratio's tussen interne:externe belasting een valide manier is om veranderingen in fysieke fitheid te meten?Data door de praktijkpartners zijn op diverse manieren en voor diverse variabelen verzameld. De variabelen zijn onder te delen in de kopjes: (I) individuele kenmerken, (II) externe belasting, (III) interne belasting, (IV) herstel en (V) psychosociale stress. Doordat de diverse sportclubs variabelen verzamelen die zij van belang achten is het niet mogelijk geweest om 1 database op te stellen welke alle variabelen bevat. Hierin zou immers duidelijk moeten zijn wat per variabelen de definitie is, welke per sportclub kan verschillen. Voor toekomstige projecten is het wenselijk om hier uniformiteit in aan te brengen voor aanvang van het project. Dit zal eenvoudiger zijn naarmate ruwe data beschikbaar is, omdat het onwaarschijnlijk is dat de sportclubs hun definities aanpassen. De gebruikte meetinstrumenten en -methodes zijn voor het overgrote deel overeenkomstig uit de wetenschappelijke literatuur en tevens overeenkomstig met de wetenschappelijke standaard. Kanttekening is dat er voor dit rapport geen zicht is op de daadwerkelijke uitvoering van de betreffende metingen.De vraag of de veranderingen in ratio's tussen interne:externe belasting een valide manier is om veranderingen in fysieke fitheid te meten is beantwoord door gebruik te maken van een dataset van 1 voetbalclub (van 3 teams) over 2 seizoenen. Er gekeken of veranderingen in ratio's opgesteld uit diverse maten voor interne belasting (ervaren mate van inspanning en load) en externe belasting (totaal gelopen afstand en totaal gelopen afstand op hoge snelheid) met diverse tijdsintervallen een relatie vertoonden met veranderingen in fysieke fitheid, gemeten met gestandaardiseerde submaximale inspanningstesten. Uit de resultaten bleek dat er geen relatie is gevonden tussen vooraf genoemde variabelen. Er blijken diverse obstakels te zijn waardoor de verandering in ratio’s mogelijk niet correleren met de verandering in interne belasting tijdens fysieke testen. De belastingsmonitor kan dus niet gebruikt worden om fysieke fitheid van sporters inzichtelijk te maken wanneer gekeken wordt naar de opgestelde ratio’s tussen interne en externe belasting. Fysieke testen blijven hiervoor nog steeds noodzakelijk, omdat deze het beste beeld geven van de huidige fysieke fitheid van de sporters. De belastingsmonitor is daarom, voor nu, alleen geschikt voor het afzonderlijk inzichtelijk maken van de diverse variabelen uit de dataset.
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Er is onderzoek gedaan naar het gebruik van HeatSavr voor energiebesparing bij zwembaden.
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The following guidelines address issues related specifically to sign language tests and testing of children since most of the existing guidelines focus on tests for adult learners. Links are provided to existing guidelines for test development, such as from the International Testing Commission (ITC), or the European Association of Language Testing and Assessment (EALTA), which include more general, construct-independent issues on (language) tests to provide additional/in-depth information. The guidelines stated here serve as a point of reference to develop, evaluate, and use tests, both for children or adult learners of a sign language. To investigate specific topics more in-depth, we recommend using existing guidelines (see Additional resources and guidelines for (language) test development) or refer to publications on sign language test development and adaptation (see Selected references
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OBJECTIVE: The association between groin pain and range of motion is poorly understood. The aim of this study was to develop a test to measure sport specific range of motion (SSROM) of the lower limb, to evaluate its reliability and describe findings in non-injured (NI) and injured football players.DESIGN: Case-controlled.SETTING: 6 Dutch elite clubs, 6 amateur clubs and a sports medicine practice.PARTICIPANTS: 103 NI elite and 83 NI amateurs and 57 football players with unilateral adductor-related groin pain.MAIN OUTCOME MEASURES: Sport specific hip extension, adduction, abduction, internal and external rotation of both legs were examined with inclinometers. Test-retest reliability (ICC), standard error of measurement (SEM) and minimal detectable change (MDC) were calculated. Non-injured players were compared with the injured group.RESULTS: Intra and inter tester ICCs were acceptable and ranged from 0.90 to 0.98 and 0.50-0.88. SEM ranged from 1.3 to 9.2° and MDC from 3.7 to 25.6° for single directions and total SSROM. Both non-injured elite and amateur players had very similar total SSROM in non-dominant and dominant legs (188-190, SD ± 25). Injured players had significant (p < 0.05) total SSROM deficits with 187(SD ± 31)° on the healthy and 135(SD ± 29)° on the injured side.CONCLUSION: The SSROM test shows acceptable reliability. Loss of SSROM is found on the injured side in football players with unilateral adductor-related groin pain. Whether this is the cause or effect of groin pain cannot be stated due to the study design. Whether restoration of SSROM in injured players leads to improved outcomes should be investigated in new studies.
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Physical and psychosocial stress and recovery are important performance determinants. A holistic approach that monitors these performance determinants over a longer period of time is lacking. Therefore this study aims to investigate the effect of a player’s physical and psychosocial stress and recovery on field-test performance. In a prospective non-experimental cohort design 10 female Dutch floorball players were monitored over 6 months. To monitor physical and psychosocial stress and recovery, daily training-logs and three-weekly the Recovery-Stress Questionnaire for Athletes (RESTQ-Sport) were filled out respectively. To determine field-test performance 6 Heart rate Interval Monitoring System (HIMS) and 4 Repeated Modified Agility T-test (RMAT) measurements were performed. Multilevel prediction models were applied to account for within-players and between-players field-test performance changes. The results show that more psychosocial stress and less psychosocial recovery over 3 to 6 weeks before testing decrease HIMS performance (p≤0.05). More physical stress over 6 weeks before testing improves RMAT performance (p≤0.05). In conclusion, physical and psychosocial stress and recovery affect submaximal interval-based running performance and agility up to 6 weeks before testing. Therefore both physical and psychosocial stress and recovery should be monitored in daily routines to optimize performance.
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OBJECTIVE: To further test the validity and clinical usefulness of the steep ramp test (SRT) in estimating exercise tolerance in cancer survivors by external validation and extension of previously published prediction models for peak oxygen consumption (Vo2peak) and peak power output (Wpeak).DESIGN: Cross-sectional study.SETTING: Multicenter.PARTICIPANTS: Cancer survivors (N=283) in 2 randomized controlled exercise trials.INTERVENTIONS: Not applicable.MAIN OUTCOME MEASURES: Prediction model accuracy was assessed by intraclass correlation coefficients (ICCs) and limits of agreement (LOA). Multiple linear regression was used for model extension. Clinical performance was judged by the percentage of accurate endurance exercise prescriptions.RESULTS: ICCs of SRT-predicted Vo2peak and Wpeak with these values as obtained by the cardiopulmonary exercise test were .61 and .73, respectively, using the previously published prediction models. 95% LOA were ±705mL/min with a bias of 190mL/min for Vo2peak and ±59W with a bias of 5W for Wpeak. Modest improvements were obtained by adding body weight and sex to the regression equation for the prediction of Vo2peak (ICC, .73; 95% LOA, ±608mL/min) and by adding age, height, and sex for the prediction of Wpeak (ICC, .81; 95% LOA, ±48W). Accuracy of endurance exercise prescription improved from 57% accurate prescriptions to 68% accurate prescriptions with the new prediction model for Wpeak.CONCLUSIONS: Predictions of Vo2peak and Wpeak based on the SRT are adequate at the group level, but insufficiently accurate in individual patients. The multivariable prediction model for Wpeak can be used cautiously (eg, supplemented with a Borg score) to aid endurance exercise prescription.
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In this study we measured the performance times on the Wheelchair Mobility Performance (WMP) test during different test conditions to see if the performance times changed when wheelchair settings were changed. The overall performance time on the WMP test increased when the tire pressure was reduced and also when extra mass was attached to the wheelchair. It can be concluded that the WMP test is sensitive to changes in wheelchair settings. It is recommended to use this field-based test in further research to investigate the effect of wheelchair settings on mobility performance time. Objective: The Wheelchair Mobility Performance (WMP) test is a reliable and valid measure to assess mobility performance in wheelchair basketball. The aim of this study was to examine the sensitivity to change of the WMP test by manipulating wheelchair configurations. Methods: Sixteen wheelchair basketball players performed the WMP test 3 times in their own wheelchair: (i) without adjustments (“control condition”); (ii) with 10 kg additional mass (“weighted condition”); and (iii) with 50% reduced tyre pressure (“tyre condition”). The outcome measure was time (s). If paired t-tests were significant (p < 0.05) and differences between conditions were larger than the standard error of measurement, the effect sizes (ES) were used to evaluate the sensitivity to change. ES values ≥0.2 were regarded as sensitive to change. Results: The overall performance times for the manipulations were significantly higher than the control condition, with mean differences of 4.40 s (weight – control, ES = 0.44) and 2.81 s (tyre – control, ES = 0.27). The overall performance time on the WMP test was judged as sensitive to change. For 8 of the 15 separate tasks on the WMP test, the tasks were judged as sensitive to change for at least one of the manipulations. Conclusion: The WMP test can detect change in mobility performance when wheelchair configurations are manipulated. https://www.medicaljournals.se/jrm/content/html/10.2340/16501977-2341
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The purpose of this study was to assess predictive value of a new submaximal rowing test (SmRT) on 2,000-m ergometer rowing time-trial performance in competitive rowers. In addition, the reliability of the SmRT was investigated. Twenty-four competitive male rowers participated in this study. After determining individual HRmax, all rowers performed an SmRT followed by a 2,000-m rowing ergometer time trial. In addition, the SmRT was performed 4 times (2 days in between) to determine the reliability. The SmRT consists of two 6-minute stages of rowing at 70 and 80% HRmax, followed by a 3-minute stage at 90% HRmax. Power was captured during the 3 stages, and 60 seconds of heart rate recovery (HRR60s) was measured directly after the third stage. Results showed that predictive value of power during the SmRT on 2,000-m rowing time also increased with stages. CVTEE% is 2.4, 1.9, and 1.3%. Pearson correlations (95% confidence interval [95% CI]) were −0.73 (−0.88 to −0.45), −0.80 (−0.94 to −0.67), and −0.93 (−0.97 to −0.84). 2,000-m rowing time and HRR60s showed no relationship. Reliability of power during the SmRT improved with the increasing intensity of the stages. The coefficient of variation (CVTEM%) was 9.2, 5.6, and 0.4%. Intraclass correlation coefficients (ICC) and 95% CI were 0.91 (0.78–0.97), 0.92 (0.81–0.97), and 0.99 (0.97–1.00). The CVTEM% and ICC of HRR60s were 8.1% and 0.93 (0.82–0.98). In conclusion, the data of this study shows that the SmRT is a reliable test that it is able to accurately predict 2,000-m rowing time on an ergometer. The SmRT is a practical and valuable submaximal test for rowers, which can potentially assist with monitoring, fine-tuning and optimizing training prescription in rowers.
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