ODISSEI (Open Data Infrastructure for Social Science and Economic Innovations)
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Drugs Monologen interview Hans Plomp
No full textDrugs Monologen was een digital storytelling en oral history project van de Open Universiteit (Faculteit Cultuurwetenschappen) en het Poppi Drugs Museum dat liep van oktober 2023 tot oktober 2025. Het project draaide om het bestuderen van de Nederlandse drugsgeschiedenis vanuit het perspectief van mensen die zelf drugs gebruikten in de periode ca. 1960-2000. In dit kader vonden 28 oral history interviews en 5 thematische groepsinterviews plaats. Daarnaast werd een speciale app ontwikkeld waarmee deelnemers op de Drugs Monologen website hun eigen historische ‘monoloog’ konden vertellen en bijdragen aan het onderzoek. Deze laatste methode leverde 51 monologen op. De oral history interviews, groepsinterviews en monologen waarvoor van de verteller toestemming werd verkregen voor gebruik voor toekomstig onderzoek zijn hier bewaard. Bij alle Nederlandstalige items is een transcriptie toegevoegd. Dit item maakt deel uit van deze datacollectie. Vanwege de privacygevoelige aard van de data kunnen deze alleen worden geraadpleegd na via de daartoe bestemde knop toestemming te hebben aangevraagd en verkregen voor toegang tot deze dataset
Replication Data for: Literatuurhistorisch redeneren met oog voor de ander.
No full textDatasets met resultaten uit pre- & posttests, interviewtranscripten, enquêteuitslagen en kwalitatieve data (werk van vwo5-leerlingen) bij het onderzoek 'Literatuurhistorisch redeneren met oog voor de ander. Naar een onderzoeksdidactiek voor Nederlandse literatuurgeschiedenis in de vwo-bovenbouw.
Relationship between employment and treatment adherence
No full textThis dataset contains qualitative survey data on workplace related variables and adherence to treatment. The dataset was used for a study on the relationship between work-related factors and adherence to treatment among people with a chronic condition. The dataset was compiled based on multiple questionnaires, as part of the Dutch National Panel of the Chronically ill and Disabled. The dataset contains self-reported data from 309 individuals with one or more chronic illnesses, who have paid work and use medication. Variables include several background variables (e.g. age, sex, level of education, number of chronic conditions), work-related variables (type of contract, hours of work, level of physical job demands, level of psychological job demands, employment type and limitations at work) and treatment adherence data (adherence to treatment appointments and to medication). Data on inclusion at work is available for the subset of people working for an employer (n=255) and data on medication self-efficacy of available for a subset of 114 participants. Data collection took place between November 2020 and July 2022. The following validated instruments are available in the dataset:
The Perceived Group Inclusion Schale (PGIS, specified for the work context), the Self-Efficacy for Appropriate Medication Use Scale (SEAMS, with additional work-related questions) and The Partners in Health (PiH) scale
Data of a randomized controlled trial of the Happy Lessons program: a school-based program to prevent depressive symptoms and strengthen well-being among Dutch pre-vocational students
No full textThis pilot randomized controlled trial (RCT) investigates the effectiveness of Happy Lessons (HL). This school-based program aims to prevent depression symptoms and enhance well-being among Dutch pre-vocational students. Classes within schools were randomized to intervention group (n = 124) or waitlist control group (n = 143). Students (n = 267, aged 11 to 15) completed questionnaires at baseline, 3- and 6-months follow-up. See the study protocol paper for a description of the data collection and collected variables.
Study protocol: Rombouts, M., Duinhof, E. L., Kleinjan, M., Kraiss, J. T., Shields-Zeeman, L., & Monshouwer, K. (2022). A school-based program to prevent depressive symptoms and strengthen well-being among pre-vocational students (Happy Lessons): protocol for a cluster randomized controlled trial and implementation study. BMC public health, 22(1), 139
Data for the PhD thesis "Towards a Framework for Land Conflicts Management in Oyo State, Nigeria"
No full textThis dataset contains data used in the research entitled Towards a Framework for Land Conflict Management in Oyo State, Nigeria. It includes interview data, focus group discussion data, qualitative data collected through a questionnaire for generalisability and validation and analysis of the data
How do medical students' expectations shape their experiences of well-being programmes?
No full textThis study examines the role of expectations in shaping students’ experiences of student support. Our research question is “How do medical students' expectations of a student support system shape, and are shaped by, institutional rules and processes?” We interviewed 13 medical students and reviewed internal institution documents. We conclude that student expectations matter in shaping their experiences of student support systems.<BR
Replication Data for Chapter 4
No full textVariables corresponds to each variable introduced and detailed explained in the paper. The database is presented in a panel data format that allows the replicability of the econometric estimates
Study 5: The best of two worlds: Gathering validity evidence for an integrated instructional design model for skills training and academic education at a military academy.
No full textTitle
The best of two worlds: Gathering validity evidence for an integrated instructional design model for skills training and academic education at a military academy.
Authors,
Hornstra, S. P. A., Hoogenboezem, J. A., Durning, S. J., & Van Mook, W. N. K. A.
Summary
This study describes the gathering of validity evidence for the integrated instructional design model (i.e. TrEd ID model) from academic educators at the Netherlands Defence Academy through focus group sessions.
At a military academy, officer cadets master military skills and strategic thinking through military training and academic education respectively. In frequently complex and dynamic operational settings, officers typically need to perform military skills and strategic thinking simultaneously. As a result, it is crucial that officer cadets learn to integrate military skills and strategic thinking in a relevant way. However, military training and academic education are often separated learning tracks, lacking a common language and common methods. Addressing this issue, an innovative integrated instructional design framework was created in order to cater the requirements of both military training and academic education. To gather validity evidence (the systematic collection and evaluation of diverse data sources to substantiate the credibility and accuracy of the assessment interpretations and ensure their alignment with the intended purpose) for this so-called TrEd ID model, we conducted a focus group study with academic educators from the Netherlands Defence Academy. The results of this study indicate that the TrEd ID model effectively meets the demands of both of these learning tracks. Additionally, the results offer valuable insights for its potential implementation. Future research could focus on obtaining further validity evidence for the TrEd ID model from other stake holders in the officer cadets’ learning process. Further research could also investigate the necessary practical guidelines for implementing the TrEd model at a military academy.
Software
ATLAS.ti (v24).
Methods
Focus group sessions: Thematic analysis.
Data description
Audio recording and transcript Officer education (Academic educators).<BR
Study 1: Understanding healthcare efficiency—an AI-supported narrative review of diverse terminologies used
No full textSummary
Background
Physicians have become more responsible for pursuing healthcare efficiency. However, contemporary literature uses multiple terminologies to describe healthcare efficiency. To identify which term is best suitable for medical education to equip physicians to contribute to healthcare efficiency delivery in clinical practice, we performed a narrative review to elucidate these terms' meanings, commonalities, and differences.
Methods
The PubMed-database was searched for articles published in 2019-2024 describing healthcare efficiency terminology. Eligible articles conceptually described and applied relevant terminologies for physicians, while empirical studies and practice-specific articles were excluded. The screening was supported by an open-source artificial intelligence tool (ASReview), which prioritizes articles through machine learning. Two reviewers independently screened the resulting articles, resolving disagreements by consensus. Final eligibility was determined through predefined inclusion criteria.
ResultsOut of 3,655 articles identified, 26 met the inclusion criteria. Key terminologies: cost-effectiveness, high-value care, low-value care, and value-based healthcare, were identified, and explored into more depth. ‘Value’ is central in all terms, but our findings reveal that the perspectives herein differ on what constitutes value. Within cost-effectiveness, resource allocation to the population’s needs drives decision-making—maximizing value at population-level. Within value-based healthcare, patient-centricity guides decision-making—maximizing value at individual patient-level. High-value and low-value care are somewhat ambiguous, depending solely on cost-effectiveness results or patient preferences to determine whether care is considered as low or high value.
Conclusions Cost-effectiveness may be too rigid for patient-physician interactions, while value-based healthcare might not ensure sustainable care. As physicians are both stewards of finite societal resources and advocates of individual patients, integrating cost-effectiveness (resource allocation for population needs) and value-based healthcare (individualized care plans) seems necessary. Both terms emphasize delivering high-value care and avoiding low-value care. We suggest that medical education: (1) train (future) physicians to apply healthcare efficiency principles through case-based discussion, (2) use the cost-effectiveness plane to evaluate treatments, (3) deepen knowledge of diagnostic and treatment procedures’ costs within evidence-based guidelines, and (4) enhance communication skills supporting a healthcare efficiency-driven open shared decision-making with patients.
Relevant documents
The screening process, including both the reviewers their decisions, can be viewed in 'Decisions of Screening Process’. <BR
Chapter 2: International Online Collaboration Competencies in Higher Education Students: a Systematic Review
No full textSummary
In chapter 2 we describe a systematic review aiming to identify competencies relevant to international online collaboration, learning and evaluation strategies of IOCCs published in the scientific literature. This study was guided by the research question “What competencies, instructional designs and evaluation methods are described for international online collaboration in the existing literature?”. 516 studies were reviewed, and data from 14 full texts were analysed. Six competency domains emerged, namely (1) information and communication technology (ICT), (2) intercultural and cultural, (3) communication and language, (4) self-management and organization, (5) collaboration, and (6) domain-specific, together including 112 IOCCs. For teaching international online collaboration, mostly collaborative learning or problem- and case-based learning had been applied. We found that the competencies involved in international online collaboration are fragmented, and that mostly single competency domains such as intercultural competency or language competency have been evaluated, making a holistic approach of competency promotion and evaluation for IOCCs difficult.
Description of the attached file
The attached file provides the abstract review guide, the review plan, and the 505 included abstracts (11 duplicates removed) for the systematic review:Dataverse_Chapter 2_Kolm Alexandra.xlx