Implementation of Healthy Eating Interventions in Center-Based Childcare: The Selection, Application, and Reporting of Theories, Models, and Frameworks

Vale, Marjorie Lima do; Farmer, Anna; Ball, Geoff D.C.; Gokiert, Rebecca; Maximova, Katerina; Thorlakson, Jessica

doi:10.1177/0890117119895951

Cited by 5 publications

(8 citation statements)

References 87 publications

(113 reference statements)

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“…A strength of this study is the eligibility criteria, which facilitated the large number of eligible articles relative to pre-existent bibliometric studies of TMF applications in implementation research ( 20 – 22 ). The study also summarizes TMF applications in clinical AI research, a prominent and growing category of digital health implementation research which had not yet been subject to any similar bibliometric studies.…”

Section: Discussionmentioning

confidence: 99%

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Evaluating the translation of implementation science to clinical artificial intelligence: a bibliometric study of qualitative research

Hogg

Al-Zubaidy

Keane

et al. 2023

Front. Health Serv.

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IntroductionWhilst a theoretical basis for implementation research is seen as advantageous, there is little clarity over if and how the application of theories, models or frameworks (TMF) impact implementation outcomes. Clinical artificial intelligence (AI) continues to receive multi-stakeholder interest and investment, yet a significant implementation gap remains. This bibliometric study aims to measure and characterize TMF application in qualitative clinical AI research to identify opportunities to improve research practice and its impact on clinical AI implementation.MethodsQualitative research of stakeholder perspectives on clinical AI published between January 2014 and October 2022 was systematically identified. Eligible studies were characterized by their publication type, clinical and geographical context, type of clinical AI studied, data collection method, participants and application of any TMF. Each TMF applied by eligible studies, its justification and mode of application was characterized.ResultsOf 202 eligible studies, 70 (34.7%) applied a TMF. There was an 8-fold increase in the number of publications between 2014 and 2022 but no significant increase in the proportion applying TMFs. Of the 50 TMFs applied, 40 (80%) were only applied once, with the Technology Acceptance Model applied most frequently (n = 9). Seven TMFs were novel contributions embedded within an eligible study. A minority of studies justified TMF application (n = 51,58.6%) and it was uncommon to discuss an alternative TMF or the limitations of the one selected (n = 11,12.6%). The most common way in which a TMF was applied in eligible studies was data analysis (n = 44,50.6%). Implementation guidelines or tools were explicitly referenced by 2 reports (1.0%).ConclusionTMFs have not been commonly applied in qualitative research of clinical AI. When TMFs have been applied there has been (i) little consensus on TMF selection (ii) limited description of selection rationale and (iii) lack of clarity over how TMFs inform research. We consider this to represent an opportunity to improve implementation science's translation to clinical AI research and clinical AI into practice by promoting the rigor and frequency of TMF application. We recommend that the finite resources of the implementation science community are diverted toward increasing accessibility and engagement with theory informed practices. The considered application of theories, models and frameworks (TMF) are thought to contribute to the impact of implementation science on the translation of innovations into real-world care. The frequency and nature of TMF use are yet to be described within digital health innovations, including the prominent field of clinical AI. A well-known implementation gap, coined as the “AI chasm” continues to limit the impact of clinical AI on real-world care. From this bibliometric study of the frequency and quality of TMF use within qualitative clinical AI research, we found that TMFs are usually not applied, their selection is highly varied between studies and there is not often a convincing rationale for their selection. Promoting the rigor and frequency of TMF use appears to present an opportunity to improve the translation of clinical AI into practice.

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Section: Discussionmentioning

confidence: 99%

“…Implementation research focused on other categories of healthcare interventions has been characterized through descriptive summaries of TMF selection and usage. These studies act as a frame of reference, but to our knowledge none report on digital health interventions ( 20 – 22 ).…”

Section: Introductionmentioning

confidence: 99%

Evaluating the translation of implementation science to clinical artificial intelligence: a bibliometric study of qualitative research

Hogg

Al-Zubaidy

Keane

et al. 2023

Front. Health Serv.

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“…Similarly, in a systematic review of school-based physical activity and sedentary behaviour interventions, Cassar [ 51 ] reported three of 14 included studies used the RE-AIM framework. A review specific to TMFs within childcare settings identified RE-AIM was used in evaluation of two of the 38 included studies [ 52 ]. Traditionally, RE-AIM is an implementation evaluation framework used to identify and evaluate aspects of the implementation process [ 53 ] and as such, provides essential guidance to the success of implementation strategies and potentially intervention outcomes.…”

Section: Discussionmentioning

confidence: 99%

Adoption, implementation, and sustainability of early childhood feeding, nutrition and active play interventions in real-world settings: a systematic review

Gelman

Whelan

Spiteri

et al. 2023

Int J Behav Nutr Phys Act

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Background Instilling healthy dietary habits and active play in early childhood is an important public health focus. Interventions supporting the establishment of nutrition and active play behaviours in the first years of life have shown positive outcomes and long-term cost-effectiveness, however, most are research trials, with limited evidence regarding real-world application. Implementation science theories, models and frameworks (TMFs) can guide the process of research translation from trial to real-world intervention. The application of TMFs within nutrition and active play intervention studies in early childhood (< 5 years) is currently unknown. This systematic review identified the use of TMFs and barriers/ enablers associated with intervention adoption, implementation, and sustainability in early childhood nutrition and active play interventions implemented under real-world conditions. Methods Six databases were searched for peer-reviewed publications between 2000–2021. Studies were included if primary outcomes reported improvement in diet, physical activity or sedentary behaviours amongst children aged < 5 years and interventions were delivered under real-world conditions within a community and/or healthcare setting. Two reviewers extracted and evaluated studies, cross checked by a third and verified by all authors. Quality assessment of included studies was completed by two authors using the Mixed Methods Appraisal Tool (MMAT). Results Eleven studies comprising eleven unique interventions were included. Studies represented low, middle and high-income countries, and were conducted across a range of settings. Five TMFs were identified representing four of Nilsen’s implementation model categories, predominantly ‘evaluation models’. Ninety-nine barriers/facilitators were extracted across the three intervention phases—Implementation (n = 33 barriers; 33 facilitators), Sustainability (n = 19 barriers; n = 9 facilitators), Adoption (n = 2 barriers; n = 3 facilitators). Identified barriers/facilitators were mapped to the five domains of the Durlak and DuPre framework, with ‘funding’, ‘compatibility’ and ‘integration of new programming’ common across the three intervention phases. Conclusions Findings demonstrate that there is no systematic application of TMFs in the planning, implementation and/or evaluation of early childhood nutrition and active play interventions in real-world settings, and selective and sporadic application of TMFs occurs across the intervention lifespan. This apparent limited uptake of TMFs is a missed opportunity to enhance real-world implementation success. Trial registration PROSPERO (CRD42021243841).

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“…Finally, users of this review should be aware of the commonly acknowledged challenge that implementation studies may not always build on standard criteria for quality reporting of findings. While such standards exist (Pinnock et al, 2017a(Pinnock et al, , 2017b, their widespread use is still pending and insufficient reporting of, for example, implementation interventions or contextual factors, remains a persistent issue (Vale et al, 2020;Wilson et al, 2017) that also may characterize the studies included in this review. Hence, the findings presented here reflect what was reported in included studies and may therefore be incomplete.…”

Section: Discussion and Applications To Practicementioning

confidence: 99%

The Mechanisms of Implementation Support - Findings from a Systematic Integrative Review

Albers

Metz

Burke

et al. 2021

Research on Social Work Practice

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Purpose: Mechanisms of Change (MoC) explain how strategies used to enhance the uptake of evidence in social and human services enable change in the behaviors of individual practitioners, organizational leaders or entire organizations, and systems. One such strategy is the use of implementation support practitioner (ISPs). This study examines the mechanisms through which ISPs facilitate behavior supportive of the implementation of research-supported interventions. Methods: A systematic, integrative review was conducted. The conceptualization of MoCs built on a model by Dalkin and colleagues. Results: Based on a unique combination of knowledge, skills, and attitudes, ISPs install trust in and among their stakeholders and utilize this trust to promote meaningful and relevant learning; provide ongoing opportunities for learning, reflection, and support; help to span boundaries; and positively motivate stakeholders. Discussion: ISPs do not represent a short cut to better implementation. They represent an additional implementation challenge that requires dedicated attention and resources.

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Implementation of Healthy Eating Interventions in Center-Based Childcare: The Selection, Application, and Reporting of Theories, Models, and Frameworks

Cited by 5 publications

References 87 publications

Evaluating the translation of implementation science to clinical artificial intelligence: a bibliometric study of qualitative research

Evaluating the translation of implementation science to clinical artificial intelligence: a bibliometric study of qualitative research

Adoption, implementation, and sustainability of early childhood feeding, nutrition and active play interventions in real-world settings: a systematic review

The Mechanisms of Implementation Support - Findings from a Systematic Integrative Review

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