ArticlePLOS digital health2025
The NASSS (Non-Adoption, Abandonment, Scale-Up, Spread and Sustainability) framework use over time: A scoping review.
Article in PLOS digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A NASSS framework-guided systematic review and exploratory modelling of digital health interventions for polypharmacy management in older adults.BMC geriatrics · 2025Pooled it
- Trial
- The Nursing Implementation Complexity Tool for Digital Technology Implementation in Nursing: Design Science Research Study.Journal of medical Internet research · 2026Article
- Implementing Telemedicine for Neonatal Care: Tutorial on a Practical Toolkit Based on Multinational Experience.Journal of medical Internet research · 2026Article
- AI for Health Care Quality and Patient Safety: Scoping Review of Diagnostic, Predictive, and Decision Support Applications.Journal of medical Internet research · 2026Article
- Developing a readiness evaluation framework for public hospital-led digital home nursing services in China: a Delphi-AHP study.BMC nursing · 2026Article
- Digital Hesitancy Among Nurses and Physicians in Anesthesia and Intensive Care: A Cross-Sectional Study from Romania.Nursing reports (Pavia, Italy) · 2026Article
- End-user perspectives on design and implementation of a novel SkinScan3D (SS3D) device for monitoring Kaposi Sarcoma in East Africa: a qualitative study.medRxiv : the preprint server for health sciences · 2026Article
- The Multicriteria Decision Analysis for Extended Reality (MCDA-XR) Governance Framework for Health Care Adoption: Mixed Methods Development Study.Journal of medical Internet research · 2026Article
- Review
- Implementing a Commercial AI Fracture Detection Tool in Health Care Using the Non-Adoption, Abandonment, Scale-Up, Spread, and Sustainability Framework: A Formative Evaluation Study.JMIR formative research · 2026Article
- Human-AI collaboration for dysphagia rehabilitation from effectiveness to implementation complexity: a systematic review.NPJ digital medicine · 2026Article
- Artificial Intelligence in Peripheral Artery Disease: A Science Advisory From the American Heart Association.Circulation. Population health and outcomes · 2026Review
- Using the NASSS-Complexity Assessment Tool to Evaluate the Implementation of "Cadê O Kauê?": Chat-Story Intervention for Youth Participation in Mental Health Promotion in Brazil.Journal of medical Internet research · 2026Article
- Helping Older Veterans Use Mental Health Apps: Qualitative Interviews and Development of a New Program.JMIR formative research · 2026Article
- Evaluating the usability and practicality of AI-enabled smartphone-based obstetric ultrasound in Sierra Leone: a mixed-methods study.BMC pregnancy and childbirth · 2026Article
- Acceptability of Telehealth as the Default Modality for Multiple Sclerosis Care in Switzerland: Cross-Sectional Study.JMIR mHealth and uHealth · 2026Article
- Structural models for spreading and scaling digital health initiatives: A scoping review protocol.PloS one · 2026Article
- Digital Health Technology Adoption Among Chinese Physicians: Latent Profile Analysis and Cross-Sectional Study.Journal of medical Internet research · 2025Article
- Procurement and early deployment of artificial intelligence tools for chest diagnostics in NHS services in England: a rapid, mixed method evaluation.EClinicalMedicine · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Non-adoption, Abandonment, Scale-up, Spread, Sustainability (NASSS) framework (2017) was established as an evidence-based, theory-informed tool to predict and evaluate the success of implementing health and care technologies. While the NASSS is gaining popularity, its use has not been systematically described. Literature reviews on the applications of popular implementation frameworks, such as the RE-AIM and the CFIR, have enabled their advancement in implementation science. Similarly, we sought to advance the science of implementation and application of theories, models, and frameworks (TMFs) in research by exploring the application of the NASSS in the five years since its inception. We aim to understand the characteristics of studies that used the NASSS, how it was used, and the lessons learned from its application. We conducted a scoping review following the JBI methodology. On December 20, 2022, we searched the following databases: Ovid MEDLINE, EMBASE, PsychINFO, CINAHL, Scopus, Web of Science, and LISTA. We used typologies and frameworks to characterize evidence to address our aim. This review included 57 studies that were qualitative (n=28), mixed/multi-methods (n=13), case studies (n=6), observational (n=3), experimental (n=3), and other designs (e.g., quality improvement) (n=4). The four most common types of digital applications being implemented were telemedicine/virtual care (n=24), personal health devices (n=10), digital interventions such as internet Cognitive Behavioural Therapies (n=10), and knowledge generation applications (n=9). Studies used the NASSS to inform study design (n=9), data collection (n=35), analysis (n=41), data presentation (n=33), and interpretation (n=39). Most studies applied the NASSS retrospectively to implementation (n=33). The remainder applied the NASSS prospectively (n=15) or concurrently (n=8) with implementation. We also collated reported barriers and enablers to implementation. We found the most reported barriers fell within the Organization and Adopter System domains, and the most frequently reported enablers fell within the Value Proposition domain. Eighteen studies highlighted the NASSS as a valuable and practical resource, particularly for unravelling complexities, comprehending implementation context, understanding contextual relevance in implementing health technology, and recognizing its adaptable nature to cater to researchers' requirements. Most studies used the NASSS retrospectively, which may be attributed to the framework's novelty. However, this finding highlights the need for prospective and concurrent application of the NASSS within the implementation process. In addition, almost all included studies reported multiple domains as barriers and enablers to implementation, indicating that implementation is a highly complex process that requires careful preparation to ensure implementation success. Finally, we identified a need for better reporting when using the NASSS in implementation research to contribute to the collective knowledge in the field.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.