In this PhD thesis, we aimed to improve understanding of the study progression and success of autistic students in higher education by comparing them to students with other disabilities and students without disabilities. We studied their background and enrollment characteristics, whether barriers in progression existed, how and when possible barriers manifested themselves in their student journey, and how institutions should address these issues. We found autistic students to be different from their peers but not worse as expected based on existing findings. We expect we counterbalanced differences because we studied a large data set spanning seven cohorts and performed propensity score weighting. Most characteristics of autistic students at enrollment were similar to those of other students, but they were older and more often male. They more often followed an irregular path to higher education than students without disabilities. They expected to study full time and spend no time on extracurricular activities or paid work. They expected to need more support and were at a higher risk of comorbidity than students with other disabilities. We found no difficulties with participation in preparatory activities. Over the first bachelor year, the grade point averages (GPAs) of autistic students were most similar to the GPAs of students without disabilities. Credit accumulation was generally similar except for one of seven periods, and dropout rates revealed no differences. The number of failed examinations and no-shows among autistic students was higher at the end of the first semester. Regarding progression and degree completion, we showed that most outcomes (GPAs, dropout rates, resits, credits, and degree completion) were similar in all three groups. Autistic students had more no-shows in the second year than their peers, which affected degree completion after three years. Our analysis of student success prediction clarified what factors predicted their success or lack thereof for each year in their bachelor program. For first-year success, study choice issues were the most important predictors (parallel programs and application timing). Issues with participation in pre-education (absence of grades in pre-educational records) and delays at the beginning of autistic students’ studies (reflected in age) were the most influential predictors of second-year success and delays in the second and final year of their bachelor program. Additionally, academic performance (average grades) was the strongest predictor of degree completion within three years. Our research contributes to increasing equality of opportunities and the development of support in higher education in three ways. First, it provides insights into the extent to which higher education serves the equality of autistic students. Second, it clarifies which differences higher education must accommodate to support the success of autistic students during their student journey. Finally, we used the insights into autistic students’ success to develop a stepped, personalized approach to support their diverse needs and talents, which can be applied using existing offerings.
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Rationale, aims and objective: Primary Care Plus (PC+) focuses on the substitution of hospital-based medical care to the primary care setting without moving hospital facilities. The aim of this study was to examine whether population health and experience of care in PC+ could be maintained. Therefore, health-related quality of life (HRQoL) and experienced quality of care from a patient perspective were compared between patients referred to PC+ and to hospital-based outpatient care (HBOC). Methods: This cohort study included patients from a Dutch region, visiting PC+ or HBOC between December 2014 and April 2018. With patient questionnaires (T0, T1 and T2), the HRQoL and experience of care were measured. One-to-two nearest neighbour calliper propensity score matching (PSM) was used to control for potential selection bias. Outcomes were compared using marginal linear models and Pearson chi-square tests. Results: One thousand one hundred thirteen PC+ patients were matched to 606 HBOC patients with well-balanced baseline characteristics (SMDs <0.1). Regarding HRQoL outcomes, no significant interaction terms between time and group were found (P > .05), indicating no difference in HRQoL development between the groups over time. Regarding experienced quality of care, no differences were found between PC+ and HBOC patients. Only travel time was significantly shorter in the HBOC group (P ≤ .001). Conclusion: Results show equal effects on HRQoL outcomes over time between the groups. Regarding experienced quality of care, only differences in travel time were found. Taken as a whole, population health and quality of care were maintained with PC+ and future research should focus more on cost-related outcomes.
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Individuals with autism increasingly enroll in universities, but little is known about predictors for their success. This study developed predictive models for the academic success of autistic bachelor students (N=101) in comparison to students with other health conditions (N=2465) and students with no health conditions (N=25,077). We applied propensity score weighting to balance outcomes. The research showed that autistic students’ academic success was predictable, and these predictions were more accurate than predictions of their peers’ success. For first-year success, study choice issues were the most important predictors (parallel program and application timing). Issues with participation in pre-education (missingness of grades in pre-educational records) and delays at the beginning of autistic students’ studies (reflected in age) were the most influential predictors for the second-year success and delays in the second and final year of their bachelor’s program. In addition, academic performance (average grades) was the strongest predictor for degree completion in 3 years. These insights can enable universities to develop tailored support for autistic students. Using early warning signals from administrative data, institutions can lower dropout risk and increase degree completion for autistic students.
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Background: An adaptation of multisystemic therapy (MST) was piloted to find out whether it would yield better outcomes than standard MST in families where the adolescent not only shows antisocial or delinquent behaviour, but also has an intellectual disability. Method: To establish the comparative effectiveness of MST‐ID (n = 55) versus standard MST (n = 73), treatment outcomes were compared at the end of treatment and at 6‐month follow‐up. Pre‐treatment differences were controlled for using the propensity score method. Results: Multisystemic therapy‐ID resulted in reduced police contact and reduced rule breaking behaviour that lasted up to 6 months post‐treatment. Compared to standard MST, MST‐ID more frequently resulted in improvements in parenting skills, family relations, social support, involvement with pro‐social peers and sustained positive behavioural changes. At follow‐up, more adolescents who had received MST‐ID were still living at home. Conclusions: These results support further development of and research into the MST‐ID adaptation.
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It is well-documented that international enterprises are more productive. Only few studies have explored the effect of internationalization on productivity and innovation at the firm-level. Using propensity score matching we analyze the causal effects of internationalization on innovation in 10 transition economies. We distinguish between three types of internationalization: exporting, FDI, and international outsourcing. We find that internationalization causes higher levels of innovation. More specifically, we show that (i) exporting results in more R&D, higher sales from product innovation, and an increase in the number of international patents (ii) outward FDI increases R&D and international patents (iii) international outsourcing leads to higher sales from product innovation. The paper provides empirical support to the theoretical literature on heterogeneous firms in international trade that argues that middle income countries gain from trade liberalization through increases in firm productivity and innovative capabilities.
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Study orientation tools are frequently grounded in the notion that achieving person-environment (PE) fit is key to academic success. Nevertheless, the literature reveals two notable gaps: the focus on predictive rather than explanatory role of PE fit within a broader set of variables, and its varying impact on outcomes across study programmes. This study aimed to address these gaps by investigating the relative importance of PE fit within a comprehensive set of pre-enrolment predictors to predict programme-specific persistence. We analysed data from 1305 prospective first-year students across five study programmes, with at least 200 students per programme. Data analysis included propensity score weighting and logistic LASSO regressions with cross-validation. The results indicated prediction accuracy in each programme ranging from 67% to 77% in the training data, which reduced to 50–75% in the test data, reflecting good prediction of persistence but challenges in predicting dropout. Inspection of the retained predictors revealed varying predictors across study programmes, with interest and skill fit variables representing the largest effects. This study underscores the necessity of programme-specific predictions to understand the relationship between PE fit and first-year persistence. The findings lay the groundwork for more personalised feedback in study orientation tools.
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Objectives: Hospital admission in older adults is associated with unwanted outcomes such as readmission, institutionalization, and functional decline. To reduce these outcomes, the Netherlands introduced an alternative to hospital-based care: the Acute Geriatric Community Hospital (AGCH). The AGCH is an acute care unit situated outside of a hospital focusing on early rehabilitation and comprehensive geriatric assessment. The objective of this study was to evaluate if AGCH care is associated with decreasing unplanned readmissions or death compared with hospital-based care. Design: Prospective cohort study controlled with a historic cohort. Setting and Participants: A (sub)acute care unit (AGCH) and 6 hospitals in the Netherlands; participants were acutely ill older adults. Methods: We used inverse propensity score weighting to account for baseline differences. The primary outcome was 90-day readmission or death. Secondary outcomes included 30-day readmission or death, time to death, admission to long-term residential care, occurrence of falls and functioning over time. Generalized logistic regression models and multilevel regression analyses were used to estimate effects. Results: AGCH patients (n = 206) had lower 90-day readmission or death rates [odds ratio (OR) 0.39, 95% CI 0.23-0.67] compared to patients treated in hospital (n = 401). AGCH patients had a lower risk of 90-day readmission (OR 0.38, 95% CI 0.21-0.67) but did not differ on all-cause mortality (OR 0.89, 95% CI 0.44-1.79) compared with the hospital control group. AGCH patients had lower 30-day readmission or death rates. Secondary outcomes did not differ. Conclusions and Implications: AGCH patients had lower rates of readmission and/or death than patients treated in a hospital. Our results support further research on the implementation and cost-effectiveness of AGCH in the Netherlands and other countries seeking alternatives to hospital-based care.
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Adaptive survey design has attracted great interest in recent years, but the number of case studies describing actual implementation is still thin. Reasons for this may be the gap between survey methodology and data collection, practical complications in differentiating effort across sample units and lack of flexibility of survey case management systems. Currently, adaptive survey design is a standard option in redesigns of person and household surveys at Statistics Netherlands and it has been implemented for the Dutch Health survey in 2018. In this article, the implementation of static adaptive survey designs is described and motivated with a focus on practical feasibility.
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Het doel van dit onderzoek is te onderzoeken onder welke omstandigheden en onder welke condities relatief moderne modelleringstechnieken zoals support vector machines, neural networks en random forests voordelen zouden kunnen hebben in medisch-wetenschappelijk onderzoek en in de medische praktijk in vergelijking met meer traditionele modelleringstechnieken, zoals lineaire regressie, logistische regressie en Cox regressie.
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Objective. Clinicians may use implicit or explicit motor learning approaches to facilitatemotor learning of patients with stroke. Implicit motor learning approaches have shown promising results in healthy populations. The purpose of this study was to assess whether an implicit motor learning walking intervention is more effective compared with an explicit motor learning walking intervention delivered at home regarding walking speed in people after stroke in the chronic phase of recovery. Methods. This randomized, controlled, single-blind trial was conducted in the home environment. The 79 participants, who were in the chronic phase after stroke (age = 66.4 [SD = 11.0] years; time poststroke = 70.1 [SD = 64.3] months; walking speed = 0.7 [SD = 0.3] m/s; Berg Balance Scale score = 44.5 [SD = 9.5]), were randomly assigned to an implicit (n = 38) or explicit (n = 41) group. Analogy learning was used as the implicit motor learning walking intervention, whereas the explicit motor learning walking intervention consisted of detailed verbal instructions. Both groups received 9 training sessions (30 minutes each), for a period of 3 weeks, targeted at improving quality of walking. The primary outcome was walking speed measured by the 10-MeterWalk Test at a comfortable walking pace. Outcomes were assessed at baseline, immediately after intervention, and 1 month postintervention. Results. No statistically or clinically relevant differences between groups were obtained postintervention (between-group difference was estimated at 0.02 m/s [95% CI = −0.04 to 0.08] and at follow-up (between-group difference estimated at −0.02 m/s [95% CI = −0.09 to 0.05]). Conclusion. Implicit motor learning was not superior to explicit motor learning to improve walking speed in people after stroke in the chronic phase of recovery. Impact. To our knowledge, this is the first study to examine the effects of implicit compared with explicit motor learning on a functional task in people after stroke. Results indicate that physical therapists can use (tailored) implicit and explicit motor learning strategies to improve walking speed in people after stroke who are in the chronic phase of recovery.
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