Best Practices in the Veterans Health Administration's MOVE! Weight Management Program

Kahwati, Leila C.; Lewis, Megan A.; Kane, Heather; Williams, Pam; Nerz, Patrick; Jones, Kenneth R.; Lance, Trang; Vaisey, Stephen; Kinsinger, Linda

doi:10.1016/j.amepre.2011.06.047

Cited by 72 publications

(76 citation statements)

References 12 publications

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“…For example, Kahwati et al [9] examined the structure, policies, and processes that might lead to an effective clinical weight management program in a large national integrated health care system, as measured by mean weight loss among patients treated at the facility. To examine pathways that lead to both better and poorer facility-level weight loss, 11 facilities from among those with the largest weight loss outcomes and 11 facilities from among those with the smallest were included.…”

Section: Identify Casesmentioning

confidence: 99%

“…For example, Kahwati et al [9] examined their truth table and analyzed the data for single conditions and combinations of conditions that were necessary for higher or lower facility-level patient weight loss outcomes. The truth table analysis revealed two necessary conditions and four sufficient combinations of conditions.…”

Section: Qca As An Analytic Techniquementioning

confidence: 99%

“…At the completion of the truth table analysis, Kahwati et al [9] used the qualitative data from site interviews to provide rich examples to illustrate the QCA solutions that were identified, which explained what the solutions meant in clinical practice for weight management. For example, having an involved champion (usually a physician), in combination with low facility accountability, was sufficient for program success (i.e., better weight loss outcomes) and was related to better facility weight loss.…”

Section: Qca As An Analytic Techniquementioning

confidence: 99%

“…Kahwati et al [9] used a mixedmethod approach combining data from key informant interviews, program documents, and electronic health records. Any type of data can be used to inform the calibration of conditions.…”

Section: Identify Conditions and Outcome Setsmentioning

confidence: 99%

“…Researchers in this field developed QCA because probabilistic methods failed to capture the complexity of social phenomena and required large sample sizes [1]. Recently, this method has made inroads into health research and evaluation [9][10][11][12][13] because of several useful features as follows: (1) it models equifinality, which is the ability to identify more than one causal pathway to an outcome (or absence of the outcome); (2) it identifies conjunctural causation, which means that single conditions may not display their effects on their own, but only in conjunction with other conditions; and (3) it implies asymmetrical relationships between causal conditions and outcomes, which means that causal pathways for achieving the outcome differ from causal pathways for failing to achieve the outcome.…”

Section: Introductionmentioning

confidence: 99%

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Using qualitative comparative analysis to understand and quantify translation and implementation

Kane

Lewis

Williams

et al. 2014

Behav. Med. Pract. Policy Res.

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Understanding the factors that facilitate implementation of behavioral medicine programs into practice can advance translational science. Often, translation or implementation studies use case study methods with small sample sizes. Methodological approaches that systematize findings from these types of studies are needed to improve rigor and advance the field. Qualitative comparative analysis (QCA) is a method and analytical approach that can advance implementation science. QCA offers an approach for rigorously conducting translational and implementation research limited by a small number of cases. We describe the methodological and analytic approach for using QCA and provide examples of its use in the health and health services literature. QCA brings together qualitative or quantitative data derived from cases to identify necessary and sufficient conditions for an outcome. QCA offers advantages for researchers interested in analyzing complex programs and for practitioners interested in developing programs that achieve successful health outcomes. KEYWORDS

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Section: Identify Casesmentioning

confidence: 99%

Section: Qca As An Analytic Techniquementioning

confidence: 99%

Section: Qca As An Analytic Techniquementioning

confidence: 99%

Section: Identify Conditions and Outcome Setsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Using qualitative comparative analysis to understand and quantify translation and implementation

Kane

Lewis

Williams

et al. 2014

Behav. Med. Pract. Policy Res.

Self Cite

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Impact of military culture and experiences on eating and weight‐related behavior

Ferrell

Braden

Redondo

2021

Journal Community Psychology

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Disordered eating behaviors and obesity are becoming increasingly common among United States military personnel. However, little research has explored the role of the military environment as it may influence the development of disordered eating among personnel. The present qualitative analysis examined beliefs about how military experiences affected eating and weight-related behaviors. Military personnel who served within the last year and a year or more ago (n = 250) were recruited using Amazon's Mechanical Turk (mTurk). Data included in the present study consisted of participant responses to three open-ended questions, analyzed by means of content and thematic analysis. Analyses yielded eight themes: eating extremely quickly, strict mealtime regimens, the pressure to "make weight," food insecurity, difficulty after military, food quality/content, overeating behavior, and military superior maltreatment. The current study provides a preliminary examination of the role of the military culture and experiences in the development of unhealthy eating and weight-related behaviors and offers suggestions for future research and interventions.

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Antiobesity medication use across the veterans health administration: Patient‐level predictors of receipt

Frayne

Harris

2014

Obesity

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Objective: Pharmacotherapy is an effective adjunct to behavioral interventions to treat obesity; although it is unclear how often medications are integrated into obesity treatment plans and for which patients in the Veterans Health Administration (VHA). Methods: A retrospective cohort study was conducted that examined variation in and predictors of antiobesity medication receipt (orlistat) among > 2 million obese Veterans within 140 facilities nationwide. Results: One-percent of all obese patients using VHA services filled a prescription for orlistat. Veterans were more likely to be treated with orlistat if they had a higher BMI, were female, unmarried, younger, a minority, had home instability, prescribed obesogenic psychiatric medications, had a psychiatric or obesity-related comorbidity, and used MOVE! weight management services. Among those who likely met the criteria for use, 2.5% had at least one orlistat prescription. Facility-level prescription rates varied from 0 to 1% of all obese patients in a VA facility receiving a prescription and 0 to 21% among those who met the criteria for use. Conclusions: Consistent with guidelines recommending that obesity pharmacotherapy be prescribed in conjunction with behavioral therapy, the strongest predictor of receiving orlistat was being enrolled in the MOVE! weight-loss management program.

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Best Practices in the Veterans Health Administration's MOVE! Weight Management Program

Cited by 72 publications

References 12 publications

Using qualitative comparative analysis to understand and quantify translation and implementation

Using qualitative comparative analysis to understand and quantify translation and implementation

Impact of military culture and experiences on eating and weight‐related behavior

Antiobesity medication use across the veterans health administration: Patient‐level predictors of receipt

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