Validity and Reliability of the Psychodynamic Organizational Diagnostic Instrument SyMOA: Protocol for a Mixed Methods Study
Bibliographic record
Abstract
Background: A comprehensive understanding of organizations is fundamental for implementing successful change measures. However, to date, there is no empirically testable, operationalized systems-psychodynamic organizational diagnostic method that can capture the deeper, more complex dynamics that are crucial for sustainable transformation. To address this gap, we developed the Systematic Multidimensional Organizational Assessment (SyMOA), a qualitative instrument based on an evidence-based clinical diagnostic framework, the Operationalized Psychodynamic Diagnostics III. SyMOA integrates clinical, organizational, and systemic psychodynamic theory and analyzes an organization's challenges based on invisible and unconscious aspects, that is, those lurking beneath the surface. It hypothesizes 3 organizational dimensions: (1) current challenges based on the sociotechnical integration and organizational internal functioning level, (2) internal relationship dynamics, and (3) unconscious organizational conflicts. The SyMOA dimensions are operationalized into a semistructured interview guide and coding protocols for the analysis of the content. By capturing the underlying dynamics, SyMOA aims to provide a deeper understanding of an organization's challenges and establish a solid foundation for targeted interventions. Objective: This study aims to evaluate the validity and intercoder reliability of the SyMOA instrument. Methods: For this purpose, semistructured interviews will be conducted with employees of at least 3 different companies in Germany. The evaluation will be carried out by calculating Krippendorff α to determine intercoder reliability. In addition, construct validity, content validity, and external validity will also be analyzed. Results: Recruitment and training commenced in May 2025. Data collection is planned for the second half of 2025, with analysis to follow thereafter. As this is a study protocol, no results are available yet. At the time of submission, 46 participants have been recruited. Conclusions: This study will give methodological insights into the validity, reliability, feasibility, and acceptability of the SyMOA instrument. The findings are expected to help further instrument refinement and inform the application of systems-psychodynamic approaches in organizational diagnostics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.126 | 0.130 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.038 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".