Challenges of Increasing Childcare Center Compliance With Nutrition Guidelines: A Randomized Controlled Trial of an Intervention Providing Training, Written Menu Feedback, and Printed Resources

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Abstract

Purpose:

To assess the effectiveness of an intervention including training, provision of written menu feedback, and printed resources on increasing childcare compliance with nutrition guidelines.

Design:

Parallel group randomized controlled trial.

Setting:

Hunter New England region, New South Wales, Australia.

Participants:

Forty-four childcare centers that prepare and provide food on-site to children while in care.

Intervention:

The intervention was designed using the Theoretical Domains Framework, targeted managers, and cooks and included implementation strategies that addressed identified barriers.

Measures:

Outcomes included the proportion of menus providing food servings (per child) compliant with overall nutrition guideline recommendations and each individual food group assessed via menu assessments. Cook knowledge of recommendations, intervention acceptability, adverse events, and barriers were also assessed via questionnaires with cooks and managers.

Analysis:

Logistic regression models, adjusted for baseline values of the outcome.

Results:

At baseline and follow-up, zero centers in the intervention and control groups were compliant with the overall menu guidelines or for the vegetable and meat food groups. Follow-up between-group differences in compliance for discretionary (33.3 vs 5, P = .18), dairy (41.7 vs 15, P = .16), breads and cereals (8.3 vs 10 P = 1.00), and fruit (16.7 vs 10, P = .48) were all nonsignificant. Relative to the control group, intervention centers showed a significantly greater increase in percentage of cooks with correct knowledge for vegetable servings (93.3 vs 36.4, P = .008).

Conclusion:

Although the application of the theoretical framework produced a broader understanding of the determinants of menu compliance, due to the complexity of guidelines, limited follow-up support, lower training uptake, and low intervention dose, the intervention was not effective in supporting the practice change required.

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Making sense of implementation theories, models and frameworks

Per Torgeir E Nilsen (2015)

Background Implementation science has progressed towards increased use of theoretical approaches to provide better understanding and explanation of how and why implementation succeeds or fails. The aim of this article is to propose a taxonomy that distinguishes between different categories of theories, models and frameworks in implementation science, to facilitate appropriate selection and application of relevant approaches in implementation research and practice and to foster cross-disciplinary dialogue among implementation researchers. Discussion Theoretical approaches used in implementation science have three overarching aims: describing and/or guiding the process of translating research into practice (process models); understanding and/or explaining what influences implementation outcomes (determinant frameworks, classic theories, implementation theories); and evaluating implementation (evaluation frameworks). Summary This article proposes five categories of theoretical approaches to achieve three overarching aims. These categories are not always recognized as separate types of approaches in the literature. While there is overlap between some of the theories, models and frameworks, awareness of the differences is important to facilitate the selection of relevant approaches. Most determinant frameworks provide limited “how-to” support for carrying out implementation endeavours since the determinants usually are too generic to provide sufficient detail for guiding an implementation process. And while the relevance of addressing barriers and enablers to translating research into practice is mentioned in many process models, these models do not identify or systematically structure specific determinants associated with implementation success. Furthermore, process models recognize a temporal sequence of implementation endeavours, whereas determinant frameworks do not explicitly take a process perspective of implementation.

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Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review.

Amit X Garg, Neill K. J. Adhikari, Heather McDonald … (2005)

Developers of health care software have attributed improvements in patient care to these applications. As with any health care intervention, such claims require confirmation in clinical trials. To review controlled trials assessing the effects of computerized clinical decision support systems (CDSSs) and to identify study characteristics predicting benefit. We updated our earlier reviews by searching the MEDLINE, EMBASE, Cochrane Library, Inspec, and ISI databases and consulting reference lists through September 2004. Authors of 64 primary studies confirmed data or provided additional information. We included randomized and nonrandomized controlled trials that evaluated the effect of a CDSS compared with care provided without a CDSS on practitioner performance or patient outcomes. Teams of 2 reviewers independently abstracted data on methods, setting, CDSS and patient characteristics, and outcomes. One hundred studies met our inclusion criteria. The number and methodologic quality of studies improved over time. The CDSS improved practitioner performance in 62 (64%) of the 97 studies assessing this outcome, including 4 (40%) of 10 diagnostic systems, 16 (76%) of 21 reminder systems, 23 (62%) of 37 disease management systems, and 19 (66%) of 29 drug-dosing or prescribing systems. Fifty-two trials assessed 1 or more patient outcomes, of which 7 trials (13%) reported improvements. Improved practitioner performance was associated with CDSSs that automatically prompted users compared with requiring users to activate the system (success in 73% of trials vs 47%; P = .02) and studies in which the authors also developed the CDSS software compared with studies in which the authors were not the developers (74% success vs 28%; respectively, P = .001). Many CDSSs improve practitioner performance. To date, the effects on patient outcomes remain understudied and, when studied, inconsistent.