Data · dataset · 2026
Study 2: characteristics of cases on resident dismissal at the Dutch conciliation board - Study 2D: Unprofessional behaviours in GP residents
Listed in IISH Dataverse and ODISSEI Portal — shown once because both records carry DOI 10.34894/jknqbg
Description
Summary
This study examined descriptions of behaviour and insufficiencies from conciliation board cases of 24 residents who were dismissed from training and challenged their programme director’s decision (between 2011 and 2020). Research Questions How to classify and describe the characteristics of GP residents in the Netherlands who litigated before the conciliation board (RGS-GC) against dismissal from their GP training? Which deficiencies could be identified within the CanMEDS competency domains?
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To which extent did these competencies overlap within an individual? Which typical qualifications were used to describe unprofessional behaviours? Framework CanMEDS + 4I’s model on unprofessional behaviours
Methods
Qualitative analysis using thematic analysis, collecting and describing illustrative examples of resident behaviour according to the 4I’s model’s categories. Source 24 Conciliation board cases of GP residents Data Description file:2D GP Excel Data Anon) Tabs GP (password = GP) o Identifier: randomized number o Year of training at time of dismissal number between (0-6) 2 decimal max o Gender: M=1/F0, M=Male/F=Female o 4I’s (Y/N=1/0): Failure to engage (Involvement), Dishonesty (Integrity), Disrespect (Interaction), Poor-self-awareness (Introspection), description from case law in Dutch o CanMEDS: 1=insufficient/0=sufficient Professionalism, Communication, Collaboration, Management, Medical Expertise, Scholar, Health advocacy, Number of insufficient CanMEDS o Years of training of detection of problems (Y/N=1/0) o APC: insufficient score on patient communication test (Y/N=1/0) o LHK: insufficient on at least one knowledge test Y/N=1/0 o Sick leave during training? >2weeks Y/N=1/0 o Functioned well before sickness Y/N=1/0 o Previously enrolled in GP training programme?
Y/N=1/0 o Remediation programme applied? Y/N=1/0 o Cultural/Language difficulties? Y/N=1/0 Remediation (password = rem): remediation present Y/N=1/0, type of remediation (copied statements anonymized from case law), formal remediation (Y/N=1/0), other forms of remediation (Y/N=1/0), case characteristics (specific features regarding remediation, progress or programme directors decision), professionalism insufficient?
(Y/N=1/0). Capacity (password = capp): calculation with numbers from the Dutch National Capacity Body Overview cases. In the period 2011 - 2020 there were 229 requests for conciliation. 98 were ultimately withdrawn by the applicants, resulting in unpublished decisions. 3 were inadmissible, because filed too late. 8 cases were not about dismissal. 96 cases were excluded based on specialty Eventually, 24 cases were previously in training for family medicine.
Links
Where it is published
- Dataverse dataset page dataverse.nl/dataset.xhtml?persistentId=doi%3A10.34894%2FJKNQBG ↗
landing page · from datasets iisg amsterdam
- Dataverse dataset page portal.odissei.nl/dataset.xhtml?persistentId=doi%3A10.34894%2FJKNQBG ↗
landing page · from portal odissei nl
- DOI doi.org/10.34894/jknqbg ↗
DOI / persistent id · from datasets iisg amsterdam
Catalogue records · 2
- Dataverse API dataverse.nl/api/datasets/:persistentId/?persistentId=doi%3A10.34894%2FJKNQ… ↗
metadata API · from datasets iisg amsterdam
- Dataverse API portal.odissei.nl/api/datasets/:persistentId/?persistentId=doi%3A10.34894%2FJKNQ… ↗
metadata API · from portal odissei nl
Topics
- Stated by source
- Social Sciences · Social Sciences
- From keywords
- Medicine & Health · Medicine & Health · Psychology & Behavioral Science · Psychology & Behavioral Science · Social Science · Social Science
- Inferred from text
- Epidemiology 70%
Provenance · 2 source records, 15 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| IISH Dataverse | doi:10.34894/JKNQBG | 10 d ago | JSON v1 |
| ODISSEI Portal | doi:10.34894/JKNQBG | 6 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:4202 | enrichment · datasets iisg amsterdam | taxonomy-embedding@1.1.0 | title+keywords+description (70%) |
| concepts[field].dataverse_subject:social-sciences | source · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| concepts[field].dataverse_subject:social-sciences | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| concepts[field].local:field:medicine-health | mapping · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| concepts[field].local:field:medicine-health | mapping · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| concepts[field].local:field:psychology-behavioral | mapping · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| concepts[field].local:field:psychology-behavioral | mapping · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| created_date | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | |
| description | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /description |
| publication_date | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | |
| title | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | /name |
| updated_date | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 | |
| version_label | source · datasets iisg amsterdam | connector:datasets_iisg_amsterdam@1.0.0 |