Observational measure of implementation progress in community based settings: The Stages of implementation completion (SIC)
Open accessAbstract
BACKGROUND: An increasingly large body of research is focused on designing and testing strategies to improve knowledge about how to embed evidence-based programs (EBP) into community settings. Development of strategies for overcoming barriers and increasing the effectiveness and pace of implementation is a high priority. Yet, there are few research tools that measure the implementation process itself. The Stages of Implementation Completion (SIC) is an observation-based measure that is used to track the time to achievement of key implementation milestones in an EBP being implemented in 51 counties in 53 sites (two counties have two sites) in two states in the United States. METHODS: The SIC was developed in the context of a randomized trial comparing the effectiveness of two implementation strategies: community development teams (experimental condition) and individualized implementation (control condition). Fifty-one counties were randomized to experimental or control conditions for implementation of multidimensional treatment foster care (MTFC), an alternative to group/residential care placement for children and adolescents. Progress through eight implementation stages was tracked by noting dates of completion of specific activities in each stage. Activities were tailored to the strategies for implementing the specific EBP. RESULTS: Preliminary data showed that several counties ceased progress during pre-implementation and that there was a high degree of variability among sites in the duration scores per stage and on the proportion of activities that were completed in each stage. Progress through activities and stages for three example counties is shown. CONCLUSIONS: By assessing the attainment time of each stage and the proportion of activities completed, the SIC measure can be used to track and compare the effectiveness of various implementation strategies. Data from the SIC will provide sites with relevant information on the time and resources needed to implement MTFC during various phases of implementation. With some modifications, the SIC could be appropriate for use in evaluating implementation strategies in head-to-head randomized implementation trials and as a monitoring tool for rolling out other EBPs.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Very few validated measures of implementation processes exist.
“As has been noted in the literature, very few validated measures of implementation processes exist (Hartveit et al., 2019; Chamberlain et al., 2011), requiring researchers rely on laboratory-specific measures.”
From Implementation-as-Usual in Community-Based Organizations Providing Specialized Services to Individuals with Autism Spectrum Disorder: A Mixed Methods Study (2021) · cites this paper as Chamberlain et al., 2011
The Discussion (page unavailable) says the SIC measure’s psychometric properties were still under investigation, but it does not assess how many validated measures of implementation processes existed. Searches for a shortage of validated implementation measures found no passage establishing the claim. (LLM, conf=0.72)
Experimental — accuracy not yet measuredThe Stages of Implementation Completion (SIC) may be used as both a formative and summative tool to measure the rate and depth of implementation.
“Furthermore, there are particular implementation process measures such as the Stages of Implementation Completion (SIC), which may be used as both a formative and summative tool to measure the rate and depth of implementation [73].”
From Ten recommendations for using implementation frameworks in research and practice (2020) · cites this paper as [73]
Outcomes of capacity-building strategies focus on individual and collective self-efficacy and motivation to execute implementation process strategies and on actual completion (extent, quality, timeliness) of those implementation process strategies.
“The outcomes of capacity building strategies focus on individual and collective self-efficacy and motivation to execute implementation process strategies and on their actual completion (extent, quality, timeliness) of those implementation process strategies [6, 35, 36].”
From Beyond “implementation strategies”: classifying the full range of strategies used in implementation science and practice (2017) · cites this paper as [36]
A primary outcome for most of these designs can be a composite process and output score based on speed, quality, and quantity.
“a primary outcome for most of these designs can be constructed as a composite process and output score, using dimensions of speed, quality and quantity (11, 25, 101).”
From An Overview of Research and Evaluation Designs for Dissemination and Implementation (2017) · cites this paper as [25]
Broad systems for measuring implementation process through key milestones, quality, and quantity, such as the Stages of Implementation Completion or similar unobtrusive measures, can likely be used to measure implementation fidelity and progress in diverse conditions.
“Nevertheless, it is likely that broad systems for measuring implementation process through key milestones, quality, and quantity, such as those identified in the Stages of Implementation Completion [86–88], or similar unobtrusive measures [89] can be used to measure implementation fidelity and progress in diverse conditions.”
From “Scaling-out” evidence-based interventions to new populations or new health care delivery systems (2017) · cites this paper as [86]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 24 · Cited by 262
Research works printed but not linked: 1
- Rogers EM Diffusion of innovations 4 New York: Free Press
- Authors
- Chamberlain, P., Brown, C. H., & Saldana, L.
- Affiliations
- University of Miami (US)
- Corresponding author
- Chamberlain, Patricia
- Venue
- Implementation Science
- Published
- 2011-10-06
- Volume
- 6
- Issue
- 1
- Pages
- 116-116
- ISSN
- 1748-5908 (ISSN-L)
- PMC
- PMC3197550
- OpenAlex
- W1993921986
- Cited by
- 262
- References
- 24
- Citations by year
- 2026: 13 · 2025: 21 · 2024: 29 · 2023: 24 · 2022: 22 · 2021: 17 · 2020: 38 · 2019: 21 · 2018: 20 · 2017: 16 · 2016: 5 · 2015: 11 · 2014: 12 · 2013: 8 · 2012: 4
- FWCI
- 14.84
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Implementation Science (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- U.S. Department of Health and Human Services
- National Institute of Mental Health (R01MH076158, DA023920, R25MH080916)
- National Institute on Drug Abuse (P30DA023920, DA023920)
- Topics
- Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
- Health Sciences › Health Professions › General Health Professions › Health Sciences Research and Education
- Social Sciences › Decision Sciences › Management Science and Operations Research › Evaluation and Performance Assessment
- Keywords
- evidence-based programs, community-based implementation, Multidimensional Treatment Foster Care, implementation strategies, implementation monitoring
- MeSH terms
- Adolescent, Child, Community Health Services, Foster Home Care, Humans, Program Evaluation, Program Development, Evidence-Based Practice
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review