Advancing the pragmatic measurement of sustainment: a narrative review of measures
Bibliographic record
Abstract
BACKGROUND: Sustainment, an outcome indicating an intervention continues to be implemented over time, has been comparatively less studied than other phases of the implementation process. This may be because of methodological difficulties, funding cycles, and minimal attention to theories and measurement of sustainment. This review synthesizes the literature on sustainment measures, evaluates the qualities of each measure, and highlights the strengths and gaps in existing sustainment measures. Results of the review will inform recommendations for the development of a pragmatic, valid, and reliable measure of sustainment. METHODS: A narrative review of published sustainment outcome and sustainability measures (i.e., factors that influence sustainment) was conducted, including appraising measures in the Society of Implementation Research Collaboration (SIRC) instrument review project (IRP) and the Dissemination and Implementation Grid-Enabled Measures database initiative (GEM-D&I). The narrative review used a snowballing strategy by searching the reference sections of literature reviews and definitions of sustainability and sustainment. Measures used frequently and judged to be comprehensive and/or validated by a team of implementation scientists were extracted for analysis. RESULTS: Eleven measures were evaluated. Three of the included measures were found in the SIRC-IRP, three in the GEM-D&I database, (one measure was in both databases) and six were identified in our additional searches. Thirteen constructs relating to sustainment were coded from selected measures. Measures covered a range of determinants for sustainment (i.e., construct of sustainability) as well as constructs of sustainment as an outcome. Strengths of the measures included, development by expert panels knowledgeable about particular interventions, fields or contexts, and utility in specific scenarios. A number of limitations were found in the measures analyzed including inadequate assessment of psychometric characteristics, being overly intervention or context specific, being lengthy and/or complex, and focusing on outer context factors. CONCLUSION: There is a lack of pragmatic and psychometrically sound measures of sustainment that can be completed by implementation stakeholders within inner context settings (e.g., frontline providers, supervisors).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | high |
| grok | MetaresearchMeta-epidemiology (broad) Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | medium |
| opus | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | medium |
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 | 0.130 | 0.407 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.017 | 0.019 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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, unvalidatedLabeled directly by 3 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".