Going above and beyond for implementation: the development and validity testing of the Implementation Citizenship Behavior Scale (ICBS)
Bibliographic record
Abstract
BACKGROUND: In line with recent research on the role of the inner context of organizations in implementation effectiveness, this study extends research on organizational citizenship behavior (OCB) to the domain of evidence-based practice (EBP) implementation. OCB encompasses those behaviors that go beyond what is required for a given job that contribute to greater organizational effectiveness. The goal of this study was to develop and test a measure of implementation citizenship behavior (ICB) or those behaviors that employees perform that go above and beyond what is required in order to support EBP implementation. METHODS: The primary participants were 68 supervisors from ten mental health agencies throughout California. Items measuring ICB were developed based on past research on OCB and in consultation with experts on EBP implementation in mental health settings. Supervisors rated 357 of their subordinates on ICB and implementation success. In addition, 292 of the subordinates provided data on self-rated performance, attitudes towards EBPs, work experience, and full-time status. The supervisor sample was randomly split, with half used for exploratory factor analyses and the other half for confirmatory factor analyses. The entire sample of supervisors and subordinates was utilized for analyses assessing the reliability and construct validity of the measure. RESULTS: Exploratory factor analyses supported the proposed two-factor structure of the Implementation Citizenship Behavior Scale (ICBS): (1) Helping Others and (2) Keeping Informed. Confirmatory factor analyses with the other half of the sample supported the factor structure. Additional analyses supported the reliability and construct validity for the ICBS. CONCLUSIONS: The ICBS is a pragmatic brief measure (six items) that captures critical behaviors employees perform to go above and beyond the call of duty to support EBP implementation, including helping their fellow employees on implementation-related activities and keeping informed about issues related to EBP and implementation efforts. The ICBS can be used by researchers to better understand the outcomes of improved organizational support for implementation (i.e., implementation climate) and the proximal predictors of implementation effectiveness. The ICBS can also provide insight for organizations, practitioners, and managers by focusing on key employee behaviors that should increase the probability of implementation success.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".