Study Designs for Effectiveness and Translation Research

Mercer, Shawna L.; DeVinney, Barbara J.; Fine, Lawrence J.; Green, Lawrence W.; Dougherty, Denise

doi:10.1016/j.amepre.2007.04.005

Cited by 199 publications

(191 citation statements)

References 40 publications

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“…Many researchers have argued that our research tools have become limited, particularly in the domain of behavioral health interventions [1][2][3][4][5][6][7][8][9]. The reasons for their arguments vary, but include an overreliance on randomized controlled trials, the slow pace and high cost of such trials, and the lack of attention to individual differences.…”

Section: Generality Optimization Research Designs Singlecase Designsmentioning

confidence: 99%

“…In light of the limitations of traditional designs and advances in data collection methods, a growing number of researchers have advocated for alternative research designs [2,7,10]. Specifically, one family of research designs, known as single-case designs (SCDs), has been proposed as a useful way to establish the preliminary efficacy of health interventions [3].…”

Section: Generality Optimization Research Designs Singlecase Designsmentioning

confidence: 99%

“…Like all SCDs, this design can be applied to individual participants, clusters of individuals, health care agencies, and communities. These designs are also referred to as interrupted time-series designs [1] and stepped wedge designs [7].…”

Section: Multiple-baseline Designsmentioning

confidence: 99%

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Optimizing behavioral health interventions with single-case designs: from development to dissemination

Dallery

Raiff

2014

Behav. Med. Pract. Policy Res.

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Over the past 70 years, single-case design (SCD) research has evolved to include a broad array of methodological and analytic advances. In this article, we describe some of these advances and discuss how SCDs can be used to optimize behavioral health interventions. Specifically, we discuss how parametric analysis, component analysis, and systematic replications can be used to optimize interventions. We also describe how SCDs can address other features of optimization, which include establishing generality and enabling personalized behavioral medicine. Throughout, we highlight how SCDs can be used during both the development and dissemination stages of behavioral health interventions.

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Section: Generality Optimization Research Designs Singlecase Designsmentioning

confidence: 99%

Section: Generality Optimization Research Designs Singlecase Designsmentioning

confidence: 99%

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Optimizing behavioral health interventions with single-case designs: from development to dissemination

Dallery

Raiff

2014

Behav. Med. Pract. Policy Res.

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“…To identify recommended evaluation methods for community-based interventions we reviewed: (i) the UK Medical Research Council's guidelines for developing and evaluating complex interventions (18) ; (ii) recommendations from an expert group on research designs for complex, multilevel health interventions sponsored by the US National Institutes of Health and the Centers for Disease Control and Prevention (19) ; and (iii) selected research design and evaluation texts (20)(21)(22) . We also examined reviews of methodological issues of past community-based health intervention trials (12,13,(23)(24)(25) .…”

Section: Guidance Regarding Rigorous Evaluation Of Complex Interventionsmentioning

confidence: 99%

Strengthening the rigour of population-wide, community-based obesity prevention evaluations

Wolfenden

Wiggers

2012

Public Health Nutr.

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Objective: The aim of the present study was to review the methodological literature regarding evaluation methods for complex public health interventions broadly and, based on such methods, to critically reflect on the evaluation of contemporary community-based obesity prevention programmes. Design: A systematic review of the methods and community-based literature was performed by one reviewer. Results: The review identified that there is considerable scope to improve the rigour of community-based obesity prevention programmes through: prospective trial registration; the use of more rigorous research designs, particularly where routine databases including an objective measure of adiposity are available; implementing strategies to quantify and reduce the risk of selective non-participation bias; the development and use of validated instruments to assess intervention impacts; reporting of intervention process and context information; and more comprehensive analyses of trial outcomes. Conclusions: To maximise the quality and utility of community-based obesity prevention evaluations, programme implementers and evaluators need to carefully examine the strengths and pitfalls of evaluation decisions and seek to maximise evaluation rigour in the context of political, resource and practical constraints.

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“…Further, by limiting the study to specific diagnostic groups, and not considering the study settings, an indication of outcome generalizability and translational utility could not be ascertained. 32,43 Thus, there is a key gap in the literature examining research outputs among smokers with a mental illness. Examining change in research outputs in this field is particularly important given recent high-profile publications identifying smoking and mental illness as a priority area for increased research attention.…”

Section: Introductionmentioning

confidence: 99%

Smoking and Mental Illness: A Bibliometric Analysis of Research Output Over Time

Metse¹,

Wiggers²,

Wye³

et al. 2016

NICTOB

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Introduction: The prevalence of smoking among persons with a mental illness has remained unchanged, being 2-3 times higher than the general population in high-income countries. Assessment of the volume and characteristics of research output over time can assist in identifying research priorities to promote progress within a field. The aim of this study was to undertake such an assessment in the field of smoking and mental illness. Methods: A descriptive repeat cross-sectional study was conducted of peer-reviewed publications in Medline and PsycINFO for the periods 1993-1995, 2003-2005, and 2013-2015. Publications were classified as data-or non-data-based; data-based publications were further categorized by study type, population, setting, and for intervention-focused publications by level of evidence and research translation phase. Results: Included were 547 articles published in 1993-1995 (n = 65), 2003-2005 (n = 153), and 2013-2015 (n = 329). The number and proportion of data-based publications significantly increased over time, although their focus remained predominantly descriptive (≥83%); less than 14% of publications in any period had an intervention focus. The proportion of publications reporting on study populations with multiple diagnostic categories and recruiting from nonmental health settings, significantly increased from 1993-1995 to 2003-2005, however then plateaued by 2013-2015. The level of evidence provided by intervention-focused publications was suggested to increase over time, however there was no evident variation in translation phase. Conclusions: Research has increased over time to characterize smoking among those with a mental illness; however more is needed to inform the development and implementation of effective cessation interventions for this group. Implications: This is the first study to examine the volume and characteristics of research publications in the field of smoking and mental illness over time. The number of publications increased fivefold between

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Study Designs for Effectiveness and Translation Research

Cited by 199 publications

References 40 publications

Optimizing behavioral health interventions with single-case designs: from development to dissemination

Optimizing behavioral health interventions with single-case designs: from development to dissemination

Strengthening the rigour of population-wide, community-based obesity prevention evaluations

Smoking and Mental Illness: A Bibliometric Analysis of Research Output Over Time

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