BACKGROUND: We recently developed a model of stratified exercise therapy, consisting of (i) a stratification algorithm allocating patients with knee osteoarthritis (OA) into one of the three subgroups ('high muscle strength subgroup' representing a post-traumatic phenotype, 'low muscle strength subgroup' representing an age-induced phenotype, and 'obesity subgroup' representing a metabolic phenotype) and (ii) subgroup-specific exercise therapy. In the present study, we aimed to test the construct validity of this algorithm.METHODS: Data from five studies (four exercise therapy trial cohorts and one cross-sectional cohort) were used to test the construct validity of our algorithm by 63 a priori formulated hypotheses regarding three research questions: (i) are the proportions of patients in each subgroup similar across cohorts? (15 hypotheses); (ii) are the characteristics of each of the subgroups in line with their proposed underlying phenotypes? (30 hypotheses); (iii) are the effects of usual exercise therapy in the 3 subgroups in line with the proposed effect sizes? (18 hypotheses).RESULTS: Baseline data from a total of 1211 patients with knee OA were analyzed for the first and second research question, and follow-up data from 584 patients who were part of an exercise therapy arm within a trial for the third research question. In total, the vast majority (73%) of the hypotheses were confirmed. Regarding our first research question, we found similar proportions in each of the three subgroups across cohorts, especially for three cohorts. Regarding our second research question, subgroup characteristics were almost completely in line with the proposed underlying phenotypes. Regarding our third research question, usual exercise therapy resulted in similar, medium to large effect sizes for knee pain and physical function for all three subgroups.CONCLUSION: We found mixed results regarding the construct validity of our stratification algorithm. On the one hand, it is a valid instrument to consistently allocate patients into subgroups that aligned our hypotheses. On the other hand, in contrast to our hypotheses, subgroups did not differ substantially in effects of usual exercise therapy. An ongoing trial will assess whether this algorithm accompanied by subgroup-specific exercise therapy improves clinical and economic outcomes.
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Background: Functional Capacity (FC) is a multidimensional construct within the activity domain of the International Classification of Functioning, Disability and Health framework (ICF). Functional capacity evaluations (FCEs) are assessments of work-related FC. The extent to which these work-related FC tests are associated to bio-, psycho-, or social factors is unknown. The aims of this study were to test relationships between FC tests and other ICF factors in a sample of healthy workers, and to determine the amount of statistical variance in FC tests that can be explained by these factors. Methods: A cross sectional study. The sample was comprised of 403 healthy workers who completed material handling FC tests (lifting low, overhead lifting, and carrying) and static work FC tests (overhead working and standing forward bend). The explainable variables were; six muscle strength tests; aerobic capacity test; and questionnaires regarding personal factors (age, gender, body height, body weight, and education), psychological factors (mental health, vitality, and general health perceptions), and social factors (perception of work, physical workloads, sport-, leisure time-, and work-index). A priori construct validity hypotheses were formulated and analyzed by means of correlation coefficients and regression analyses. Results: Moderate correlations were detected between material handling FC tests and muscle strength, gender, body weight, and body height. As for static work FC tests; overhead working correlated fair with aerobic capacity and handgrip strength, and low with the sport-index and perception of work. For standing forward bend FC test, all hypotheses were rejected. The regression model revealed that 61% to 62% of material handling FC tests were explained by physical factors. Five to 15% of static work FC tests were explained by physical and social factors. Conclusions: The current study revealed that, in a sample of healthy workers, material handling FC tests were related to physical factors but not to the psychosocial factors measured in this study. The construct of static work FC tests remained largely unexplained.
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PURPOSE: Establishing construct validity of the ACS-NL in individuals with Parkinson's disease (PD).METHOD: Discriminative validity was established in 191 community-dwelling individuals with PD using an extreme groups design (Hoehn and Yahr stages 1 and 3). Convergent validity was determined by relating the performance scores of the ACS-NL to the scores of the Canadian Occupational Performance Measure (COPM) and the Parkinson's Disease Questionnaire (PDQ-39) scores, and relating ACS-NL satisfaction scores to the COPM scores and to the Utrecht Scale for Evaluation of Rehabilitation Participation (USER-P).RESULTS: The ACS-NL discriminated between individuals with PD with H&Y stages 1 and 3 (U = 524.5, Z = -5.453). ACS-NL performance scores correlated weakly with COPM scores (r = (0).19) and moderately with PDQ-39 scores (r = 0.44-0.55). The ACS-NL satisfaction scores correlated weakly with COPM scores (r = 0.23), and moderately with USER-P scores (r ≥ 0.40).CONCLUSIONS: This study contributed to the validation of the ACS-NL. The assessment enhances the possibility of monitoring participation in activities in individuals with PD. Implications for Rehabilitation The ACS-NL appears to hold good potential for use in the assessment of participation in activities in individuals with PD. The ACS-NL has added value parallel to administration of other instruments measuring participation (COPM) and quality of life (PDQ-39). This study demonstrates the capacity of the ACS to measure a unique construct of participation and helps to improve the psychometric properties and administration of the ACS-NL in practice.
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Inzet van serious games als scholingsinstrument voor zorgprofessionals of als patiëntinterventie neemt sterk toe. Serious games kunnen kosten besparen en zorgkwaliteit verbeteren. (Potentiële) afnemers vragen, in lijn met het medische onderzoeksparadigma, vaak naar de klinische effectiviteit (internal validity) van deze games. Het gros van de Nederlandse game-ontwikkelaars bestaat echter uit kleine ondernemingen die het aan middelen en expertise ontbreekt om de hiervoor benodigde longitudinale onderzoekstrajecten uit te voeren. Tegelijkertijd tonen mkb’ers, meestal zonder ervan bewust te zijn, tijdens het game-ontwikkelproces al verschillende validiteitsvormen aan volgens het design-onderzoeksparadigma (face validity, construct validity, e.d.). Door dit niet bij hun afnemers kenbaar te maken, komt een constructieve dialoog over validiteit moeilijk op gang en lopen mkb’ers opdrachten mis. Het ontbreekt hen aan een begrippenkader en praktische handvatten. Bestaande raamwerken zijn nog te theorie-gedreven. Om mkb’ers te helpen de 'clash' te overbruggen tussen het medische en het design-onderzoeksparadigma, ontwikkelen lectoraten ICT-innovaties in de Zorg (Hogeschool Windesheim, penvoerder) en Serious Gaming (NHL Stenden Hogeschool) samen met elf mkb’ers, afnemers, studenten en experts in een learning community drie hulpmiddelen: •Checklist: praktische mkb-richtlijnen voor het vaststellen van validiteit; •Beslisboom: op basis waarvan mkb’ers onderbouwd de juiste validatiemethode kunnenselecteren; •Serious game: om samen met (potentiële) afnemers te spelen, zodat verschillende soortenvaliditeit expliciet benoemd worden. De hulpmiddelen worden inhoudelijk gevoed door casestudies waarin mkb’ers gevolgd worden in hoe validiteit momenteel wordt vastgesteld en geëxpliciteerd in het ontwikkelproces. Vervolgens brengen we de ontworpen hulpmiddelen in de mkb-praktijk voor evaluatie. Opgeleverde hulpmiddelen stellen mkb’ers in staat werkbare validatiemethoden toe te passen gedurende het game-ontwikkelproces om acceptabele bewijslast op te leveren voor potentiële afnemers, waardoor hun marktpositie versterkt. Ook draagt het project bij aan operationalisering van bestaande raamwerken en kunnen de hulpmiddelen in game design-curricula worden geïncorporeerd.
Examining in-class activities to facilitate academic achievement in higher educationThere is an increasing interest in how to create an effective and comfortable indoor environment for lecturers and students in higher education. To achieve evidence-based improvements in the indoor environmental quality (IEQ) of higher education learning environments, this research aimed to gain new knowledge for creating optimal indoor environmental conditions that best facilitate in-class activities, i.e. teaching and learning, and foster academic achievement. The academic performance of lecturers and students is subdivided into short-term academic performance, for example, during a lecture and long-term academic performance, during an academic course or year, for example. First, a systematic literature review was conducted to reveal the effect of indoor environmental quality in classrooms in higher education on the quality of teaching, the quality of learning, and students’ academic achievement. With the information gathered on the applied methods during the literature review, a systematic approach was developed and validated to capture the effect of the IEQ on the main outcomes. This approach enables research that aims to examine the effect of all four IEQ parameters, indoor air quality, thermal conditions, lighting conditions, and acoustic conditions on students’ perceptions, responses, and short-term academic performance in the context of higher education classrooms. Next, a field experiment was conducted, applying the validated systematic approach, to explore the effect of multiple indoor environmental parameters on students and their short-term academic performance in higher education. Finally, a qualitative case study gathered lecturers’ and students’ perceptions related to the IEQ. Furthermore, how these users interact with the environment to maintain an acceptable IEQ was studied.During the systematic literature review, multiple scientific databases were searched to identify relevant scientific evidence. After the screening process, 21 publications were included. The collected evidence showed that IEQ can contribute positively to students’ academic achievement. However, it can also affect the performance of students negatively, even if the IEQ meets current standards for classrooms’ IEQ conditions. Not one optimal IEQ was identified after studying the evidence. Indoor environmental conditions in which students perform at their best differ and are task depended, indicating that classrooms should facilitate multiple indoor environmental conditions. Furthermore, the evidence provides practical information for improving the design of experimental studies, helps researchers in identifying relevant parameters, and lists methods to examine the influence of the IEQ on users.The measurement methods deduced from the included studies of the literature review, were used for the development of a systematic approach measuring classroom IEQ and students’ perceived IEQ, internal responses, and short-term academic performance. This approach allowed studying the effect of multiple IEQ parameters simultaneously and was tested in a pilot study during a regular academic course. The perceptions, internal responses, and short-term academic performance of participating students were measured. The results show associations between natural variations of the IEQ and students’ perceptions. These perceptions were associated with their physiological and cognitive responses. Furthermore, students’ perceived cognitive responses were associated with their short-term academic performance. These observed associations confirm the construct validity of the composed systematic approach. This systematic approach was then applied in a field experiment, to explore the effect of multiple indoor environmental parameters on students and their short-term academic performance in higher education. A field study, with a between-groups experimental design, was conducted during a regular academic course in 2020-2021 to analyze the effect of different acoustic, lighting, and indoor air quality (IAQ) conditions. First, the reverberation time was manipulated to 0.4 s in the intervention condition (control condition 0.6 s). Second, the horizontal illuminance level was raised from 500 to 750 lx in the intervention condition (control condition 500 lx). These conditions correspond with quality class A (intervention condition) and B (control condition), specified in Dutch IEQ guidelines for school buildings (2015). Third, the IAQ, which was ~1100 ppm carbon dioxide (CO2), as a proxy for IAQ, was improved to CO2 concentrations under 800 ppm, meeting quality class A in both conditions. Students’ perceptions were measured during seven campaigns with a questionnaire; their actual cognitive and short-term academic performances were evaluated with validated tests and an academic test, composed by the lecturer, as a subject-matter-expert on the taught topic, covered subjects discussed during the lecture. From 201 students 527 responses were collected and analyzed. A reduced RT in combination with raised HI improved students’ perceptions of the lighting environment, internal responses, and quality of learning. However, this experimental condition negatively influenced students’ ability to solve problems, while students' content-related test scores were not influenced. This shows that although quality class A conditions for RT and HI improved students’ perceptions, it did not influence their short-term academic performance. Furthermore, the benefits of reduced RT in combination with raised HI were not observed in improved IAQ conditions. Whether the sequential order of the experimental conditions is relevant in inducing these effects and/or whether improving two parameters is already beneficial, is unknownFinally, a qualitative case study explored lecturers’ and students’ perceptions of the IEQ of classrooms, which are suitable to give tutorials with a maximum capacity of about 30 students. Furthermore, how lecturers and students interact with this indoor environment to maintain an acceptable IEQ was examined. Eleven lecturers of the Hanze University of Applied Sciences (UAS), located in the northern part of the Netherlands, and twenty-four of its students participated in three focus group discussions. The findings show that lecturers and students experience poor thermal, lighting, acoustic, and IAQ conditions which may influence teaching and learning performance. Furthermore, maintaining acceptable thermal and IAQ conditions was difficult for lecturers as opening windows or doors caused noise disturbances. In uncomfortable conditions, lecturers may decide to pause earlier or shorten a lecture. When students experienced discomfort, it may affect their ability to concentrate, their emotional status, and their quality of learning. Acceptable air and thermal conditions in classrooms will mitigate the need to open windows and doors. This allows lecturers to keep doors and windows closed, combining better classroom conditions with neither noise disturbances nor related distractions. Designers and engineers should take these end users’ perceptions into account, often monitored by facility management (FM), during the renovation or construction of university buildings to achieve optimal IEQ conditions in higher education classrooms.The results of these four studies indicate that there is not a one-size fits all indoor environmental quality to facilitate optimal in-class activities. Classrooms’ thermal environment should be effectively controlled with the option of a local (manual) intervention. Classrooms’ lighting conditions should also be adjustable, both in light color and light intensity. This enables lecturers to adjust the indoor environment to facilitate in-class activities optimally. Lecturers must be informed by the building operator, for example, professionals of the Facility Department, how to change classrooms’ IEQ settings. And this may differ per classroom because each building, in which the classroom is located, is operated differently apart from the classroom location in the building, exposure to the environment, and its use. The knowledge that has come available from this study, shows that optimal indoor environmental conditions can positively influence lecturers’ and students’ comfort, health, emotional balance, and performance. These outcomes have the capacity to contribute to an improved school climate and thus academic achievement.
