Testing the leadership and organizational change for implementation (LOCI) intervention in substance abuse treatment: a cluster randomized trial study protocol
Bibliographic record
Abstract
BACKGROUND: Evidence-based practice (EBP) implementation represents a strategic change in organizations that requires effective leadership and alignment of leadership and organizational support across organizational levels. As such, there is a need for combining leadership development with organizational strategies to support organizational climate conducive to EBP implementation. The leadership and organizational change for implementation (LOCI) intervention includes leadership training for workgroup leaders, ongoing implementation leadership coaching, 360° assessment, and strategic planning with top and middle management regarding how they can support workgroup leaders in developing a positive EBP implementation climate. METHODS: This test of the LOCI intervention will take place in conjunction with the implementation of motivational interviewing (MI) in 60 substance use disorder treatment programs in California, USA. Participants will include agency executives, 60 program leaders, and approximately 360 treatment staff. LOCI will be tested using a multiple cohort, cluster randomized trial that randomizes workgroups (i.e., programs) within agency to either LOCI or a webinar leadership training control condition in three consecutive cohorts. The LOCI intervention is 12 months, and the webinar control intervention takes place in months 1, 5, and 8, for each cohort. Web-based surveys of staff and supervisors will be used to collect data on leadership, implementation climate, provider attitudes, and citizenship. Audio recordings of counseling sessions will be coded for MI fidelity. The unit of analysis will be the workgroup, randomized by site within agency and with care taken that co-located workgroups are assigned to the same condition to avoid contamination. Hierarchical linear modeling (HLM) will be used to analyze the data to account for the nested data structure. DISCUSSION: LOCI has been developed to be a feasible and effective approach for organizations to create a positive climate and fertile context for EBP implementation. The approach seeks to cultivate and sustain both effective general and implementation leadership as well as organizational strategies and support that will remain after the study has ended. Development of a positive implementation climate for MI should result in more positive service provider attitudes and behaviors related to the use of MI and, ultimately, higher fidelity in the use of MI. TRIAL REGISTRATION: This study is registered with Clinicaltrials.gov ( NCT03042832 ), 2 February 2017, retrospectively registered.
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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 | 0.045 | 0.033 |
| Meta-epidemiology (narrow) | 0.008 | 0.005 |
| Meta-epidemiology (broad) | 0.011 | 0.005 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.072 | 0.012 |
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".