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Thomas JG, Goldstein CM, Bond DS, Lillis J, Hekler EB, Emerson JA, Espel-Huynh HM, Goldstein SP, Dunsiger SI, Evans EW, Butryn ML, Huang J, Wing RR. Evaluation of intervention components to maximize outcomes of behavioral obesity treatment delivered online: A factorial experiment following the multiphase optimization strategy framework. Contemp Clin Trials 2020; 100:106217. [PMID: 33197609 DOI: 10.1016/j.cct.2020.106217] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 11/06/2020] [Accepted: 11/11/2020] [Indexed: 01/10/2023]
Abstract
BACKGROUND Behavioral lifestyle intervention (BLI) is recommended as a first-line treatment for obesity. While BLI has been adapted for online delivery to improve potential for dissemination while reducing costs and barriers to access, weight losses are typically inferior to gold standard treatment delivered in-person. It is therefore important to refine and optimize online BLI in order to improve the proportion of individuals who achieve a minimum clinically significant weight loss and mean weight loss. STUDY DESIGN Five experimental intervention components will be tested as adjuncts to an established 12-month online BLI: virtual reality for BLI skills training, interactive video feedback, tailored intervention to promote physical activity, skills for dysregulated eating, and social support combined with friendly competition. Following the Multiphase Optimization Strategy (MOST) framework, the components will first be refined and finalized during Preparation Phase pilot testing and then evaluated in a factorial experiment with 384 adults with overweight or obesity. A priori optimization criteria that balance efficacy and efficiency will be used to create a finalized treatment package that produces the best weight loss outcomes with the fewest intervention components. Mediation analysis will be conducted to test hypothesized mechanisms of action and a moderator analysis will be conducted to understand for whom and under what circumstances the interventions are effective. CONCLUSION This study will provide important information about intervention strategies that are useful for improving outcomes of online BLI. The finalized treatment package will be suitable for testing in a future randomized trial in the MOST Evaluation Phase.
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Affiliation(s)
- J Graham Thomas
- Weight Control and Diabetes Research Center, The Miriam Hospital, 196 Richmond St., Providence, RI 02903, USA; Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, 222 Richmond St., Providence, RI 02903, USA.
| | - Carly M Goldstein
- Weight Control and Diabetes Research Center, The Miriam Hospital, 196 Richmond St., Providence, RI 02903, USA; Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, 222 Richmond St., Providence, RI 02903, USA
| | - Dale S Bond
- Weight Control and Diabetes Research Center, The Miriam Hospital, 196 Richmond St., Providence, RI 02903, USA; Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, 222 Richmond St., Providence, RI 02903, USA
| | - Jason Lillis
- Weight Control and Diabetes Research Center, The Miriam Hospital, 196 Richmond St., Providence, RI 02903, USA; Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, 222 Richmond St., Providence, RI 02903, USA
| | - Eric B Hekler
- Department of Family Medicine and Public Health, University of California, San Diego (UCSD), Center for Wireless and Population Health Systems, Qualcomm Institute at UCSD, 9500 Gilman Ave., San Diego, CA 92093, USA
| | - Jessica A Emerson
- Weight Control and Diabetes Research Center, The Miriam Hospital, 196 Richmond St., Providence, RI 02903, USA; Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, 222 Richmond St., Providence, RI 02903, USA
| | - Hallie M Espel-Huynh
- Weight Control and Diabetes Research Center, The Miriam Hospital, 196 Richmond St., Providence, RI 02903, USA; Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, 222 Richmond St., Providence, RI 02903, USA
| | - Stephanie P Goldstein
- Weight Control and Diabetes Research Center, The Miriam Hospital, 196 Richmond St., Providence, RI 02903, USA; Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, 222 Richmond St., Providence, RI 02903, USA
| | - Shira I Dunsiger
- Department of Behavioral and Social Sciences, Brown University School of Public Health, 121 S Main St., Providence, RI 02903, USA
| | - E Whitney Evans
- Weight Control and Diabetes Research Center, The Miriam Hospital, 196 Richmond St., Providence, RI 02903, USA; Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, 222 Richmond St., Providence, RI 02903, USA
| | - Meghan L Butryn
- Department of Psychology, Drexel University, 3141 Chestnut St, Philadelphia, PA 19104, USA
| | - Jeff Huang
- Department of Computer Science, Brown University, 115 Waterman St., Providence, RI 02906, USA
| | - Rena R Wing
- Weight Control and Diabetes Research Center, The Miriam Hospital, 196 Richmond St., Providence, RI 02903, USA; Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, 222 Richmond St., Providence, RI 02903, USA
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Wolfenden L, Goldman S, Stacey FG, Grady A, Kingsland M, Williams CM, Wiggers J, Milat A, Rissel C, Bauman A, Farrell MM, Légaré F, Ben Charif A, Zomahoun HTV, Hodder RK, Jones J, Booth D, Parmenter B, Regan T, Yoong SL. Strategies to improve the implementation of workplace-based policies or practices targeting tobacco, alcohol, diet, physical activity and obesity. Cochrane Database Syst Rev 2018; 11:CD012439. [PMID: 30480770 PMCID: PMC6362433 DOI: 10.1002/14651858.cd012439.pub2] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
BACKGROUND Given the substantial period of time adults spend in their workplaces each day, these provide an opportune setting for interventions addressing modifiable behavioural risk factors for chronic disease. Previous reviews of trials of workplace-based interventions suggest they can be effective in modifying a range of risk factors including diet, physical activity, obesity, risky alcohol use and tobacco use. However, such interventions are often poorly implemented in workplaces, limiting their impact on employee health. Identifying strategies that are effective in improving the implementation of workplace-based interventions has the potential to improve their effects on health outcomes. OBJECTIVES To assess the effects of strategies for improving the implementation of workplace-based policies or practices targeting diet, physical activity, obesity, tobacco use and alcohol use.Secondary objectives were to assess the impact of such strategies on employee health behaviours, including dietary intake, physical activity, weight status, and alcohol and tobacco use; evaluate their cost-effectiveness; and identify any unintended adverse effects of implementation strategies on workplaces or workplace staff. SEARCH METHODS We searched the following electronic databases on 31 August 2017: CENTRAL; MEDLINE; MEDLINE In Process; the Campbell Library; PsycINFO; Education Resource Information Center (ERIC); Cumulative Index to Nursing and Allied Health Literature (CINAHL); and Scopus. We also handsearched all publications between August 2012 and September 2017 in two speciality journals: Implementation Science and Journal of Translational Behavioral Medicine. We conducted searches up to September 2017 in Dissertations and Theses, the WHO International Clinical Trials Registry Platform, and the US National Institutes of Health Registry. We screened the reference lists of included trials and contacted authors to identify other potentially relevant trials. We also consulted experts in the field to identify other relevant research. SELECTION CRITERIA Implementation strategies were defined as strategies specifically employed to improve the implementation of health interventions into routine practice within specific settings. We included any trial with a parallel control group (randomised or non-randomised) and conducted at any scale that compared strategies to support implementation of workplace policies or practices targeting diet, physical activity, obesity, risky alcohol use or tobacco use versus no intervention (i.e. wait-list, usual practice or minimal support control) or another implementation strategy. Implementation strategies could include those identified by the Effective Practice and Organisation of Care (EPOC) taxonomy such as quality improvement initiatives and education and training, as well as other strategies. Implementation interventions could target policies or practices directly instituted in the workplace environment, as well as workplace-instituted efforts encouraging the use of external health promotion services (e.g. gym membership subsidies). DATA COLLECTION AND ANALYSIS Review authors working in pairs independently performed citation screening, data extraction and 'Risk of bias' assessment, resolving disagreements via consensus or a third reviewer. We narratively synthesised findings for all included trials by first describing trial characteristics, participants, interventions and outcomes. We then described the effect size of the outcome measure for policy or practice implementation. We performed meta-analysis of implementation outcomes for trials of comparable design and outcome. MAIN RESULTS We included six trials, four of which took place in the USA. Four trials employed randomised controlled trial (RCT) designs. Trials were conducted in workplaces from the manufacturing, industrial and services-based sectors. The sample sizes of workplaces ranged from 12 to 114. Workplace policies and practices targeted included: healthy catering policies; point-of-purchase nutrition labelling; environmental supports for healthy eating and physical activity; tobacco control policies; weight management programmes; and adherence to guidelines for staff health promotion. All implementation interventions utilised multiple implementation strategies, the most common of which were educational meetings, tailored interventions and local consensus processes. Four trials compared an implementation strategy intervention with a no intervention control, one trial compared different implementation interventions, and one three-arm trial compared two implementation strategies with each other and a control. Four trials reported a single implementation outcome, whilst the other two reported multiple outcomes. Investigators assessed outcomes using surveys, audits and environmental observations. We judged most trials to be at high risk of performance and detection bias and at unclear risk of reporting and attrition bias.Of the five trials comparing implementation strategies with a no intervention control, pooled analysis was possible for three RCTs reporting continuous score-based measures of implementation outcomes. The meta-analysis found no difference in standardised effects (standardised mean difference (SMD) -0.01, 95% CI -0.32 to 0.30; 164 participants; 3 studies; low certainty evidence), suggesting no benefit of implementation support in improving policy or practice implementation, relative to control. Findings for other continuous or dichotomous implementation outcomes reported across these five trials were mixed. For the two non-randomised trials examining comparative effectiveness, both reported improvements in implementation, favouring the more intensive implementation group (very low certainty evidence). Three trials examined the impact of implementation strategies on employee health behaviours, reporting mixed effects for diet and weight status (very low certainty evidence) and no effect for physical activity (very low certainty evidence) or tobacco use (low certainty evidence). One trial reported an increase in absolute workplace costs for health promotion in the implementation group (low certainty evidence). None of the included trials assessed adverse consequences. Limitations of the review included the small number of trials identified and the lack of consistent terminology applied in the implementation science field, which may have resulted in us overlooking potentially relevant trials in the search. AUTHORS' CONCLUSIONS Available evidence regarding the effectiveness of implementation strategies for improving implementation of health-promoting policies and practices in the workplace setting is sparse and inconsistent. Low certainty evidence suggests that such strategies may make little or no difference on measures of implementation fidelity or different employee health behaviour outcomes. It is also unclear if such strategies are cost-effective or have potential unintended adverse consequences. The limited number of trials identified suggests implementation research in the workplace setting is in its infancy, warranting further research to guide evidence translation in this setting.
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Affiliation(s)
- Luke Wolfenden
- University of NewcastleSchool of Medicine and Public HealthCallaghanNSWAustralia2308
- Hunter Medical Research InstituteNew LambtonAustralia
- Hunter New England Local Health DistrictHunter New England Population HealthWallsendAustralia
| | - Sharni Goldman
- University of NewcastleSchool of Medicine and Public HealthCallaghanNSWAustralia2308
| | - Fiona G Stacey
- University of Newcastle, Hunter Medical Research Institute, Priority Research Centre in Health Behaviour, and Priority Research Centre in Physical Activity and NutritionSchool of Medicine and Public HealthCallaghanNSWAustralia2287
| | - Alice Grady
- University of NewcastleSchool of Medicine and Public HealthCallaghanNSWAustralia2308
- Hunter Medical Research InstituteNew LambtonAustralia
- Hunter New England Local Health DistrictHunter New England Population HealthWallsendAustralia
| | - Melanie Kingsland
- University of NewcastleSchool of Medicine and Public HealthCallaghanNSWAustralia2308
| | - Christopher M Williams
- University of NewcastleSchool of Medicine and Public HealthCallaghanNSWAustralia2308
- Hunter Medical Research InstituteNew LambtonAustralia
- Hunter New England Local Health DistrictHunter New England Population HealthWallsendAustralia
| | - John Wiggers
- University of NewcastleSchool of Medicine and Public HealthCallaghanNSWAustralia2308
- Hunter Medical Research InstituteNew LambtonAustralia
- Hunter New England Local Health DistrictHunter New England Population HealthWallsendAustralia
| | - Andrew Milat
- NSW Ministry of HealthCentre for Epidemiology and EvidenceNorth SydneyNSWAustralia2060
- The University of SydneySchool of Public HealthSydneyAustralia
| | - Chris Rissel
- Sydney South West Local Health DistrictOffice of Preventive HealthLiverpoolNSWAustralia2170
| | - Adrian Bauman
- The University of SydneySchool of Public HealthSydneyAustralia
- Sax InstituteThe Australian Prevention Partnership CentreSydneyAustralia
| | - Margaret M Farrell
- US National Cancer InstituteDivision of Cancer Control and Population Sciences/Implementation Sciences Team9609 Medical Center DriveBethesdaMarylandUSA20892
| | - France Légaré
- Université LavalCentre de recherche sur les soins et les services de première ligne de l'Université Laval (CERSSPL‐UL)2525, Chemin de la CanardièreQuebecQuébecCanadaG1J 0A4
| | - Ali Ben Charif
- Centre de recherche sur les soins et les services de première ligne de l'Université Laval (CERSSPL‐UL)Université Laval2525, Chemin de la CanardièreQuebecQuebecCanadaG1J 0A4
| | - Hervé Tchala Vignon Zomahoun
- Centre de recherche sur les soins et les services de première ligne ‐ Université LavalHealth and Social Services Systems, Knowledge Translation and Implementation Component of the SPOR‐SUPPORT Unit of Québec2525, Chemin de la CanardièreQuebecQCCanadaG1J 0A4
| | - Rebecca K Hodder
- University of NewcastleSchool of Medicine and Public HealthCallaghanNSWAustralia2308
- Hunter Medical Research InstituteNew LambtonAustralia
- Hunter New England Local Health DistrictHunter New England Population HealthWallsendAustralia
| | - Jannah Jones
- University of NewcastleSchool of Medicine and Public HealthCallaghanNSWAustralia2308
- Hunter New England Local Health DistrictHunter New England Population HealthWallsendAustralia
| | - Debbie Booth
- University of NewcastleAuchmuty LibraryUniversity DriveCallaghanNSWAustralia2308
| | - Benjamin Parmenter
- University of NewcastleSchool of Medicine and Public HealthCallaghanNSWAustralia2308
| | - Tim Regan
- University of NewcastleThe School of PsychologyCallaghanAustralia
| | - Sze Lin Yoong
- University of NewcastleSchool of Medicine and Public HealthCallaghanNSWAustralia2308
- Hunter Medical Research InstituteNew LambtonAustralia
- Hunter New England Local Health DistrictHunter New England Population HealthWallsendAustralia
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The Effects of Two Workplace Weight Management Programs and Weight Loss on Health Care Utilization and Costs. J Occup Environ Med 2016; 58:162-9. [PMID: 26849260 DOI: 10.1097/jom.0000000000000586] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
OBJECTIVES The aim of this study was to compare the impact of two worksite weight management (WM [education] and WM+ [education plus counseling]) programs, on health care utilization and costs. Secondarily, compare the intervention groups to an observational control group of obese workers. Finally, evaluate the impact of actual weight loss on these outcomes. METHODS Estimate the change in the WM and WM+ intervention groups. Using propensity score adjustment compare the two intervention groups with the observational control group; and compare those who lost weight with those who did not. RESULTS No significant differences between the two intervention groups, or between these intervention groups and the observational control group. Those who lost weight reduced their overall health care costs. CONCLUSIONS To achieve weight loss and associated morbidity reductions, more extensive and intensive interventions, with more attention to motivation and compliance, are required.
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Larson MJ, LeCheminant JD, Carbine K, Hill KR, Christenson E, Masterson T, LeCheminant R. Slow walking on a treadmill desk does not negatively affect executive abilities: an examination of cognitive control, conflict adaptation, response inhibition, and post-error slowing. Front Psychol 2015; 6:723. [PMID: 26074861 PMCID: PMC4444606 DOI: 10.3389/fpsyg.2015.00723] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2015] [Accepted: 05/15/2015] [Indexed: 12/28/2022] Open
Abstract
An increasing trend in the workplace is for employees to walk on treadmills while working to attain known health benefits; however, the effect of walking on a treadmill during cognitive control and executive function tasks is not well known. We compared the cognitive control processes of conflict adaptation (i.e., congruency sequence effects—improved performance following high-conflict relative to low-conflict trials), post-error slowing (i.e., Rabbitt effect), and response inhibition during treadmill walking (1.5 mph) relative to sitting. Understanding the influence of treadmill desks on these cognitive processes may have implications for worker health and productivity. Sixty-nine individuals were randomized to either a sitting (n = 35) or treadmill-walking condition (n = 34). Groups did not differ in age or body mass index. All participants completed a computerized Eriksen flanker task and a response-inhibition go/no-go task in random order while either walking on a treadmill or seated. Response times (RTs) and accuracy were analyzed separately for each task using mixed model analysis of variance. Separate ANOVAs for RTs and accuracy showed the expected conflict adaptation effects, post-error slowing, and response inhibition effects when collapsed across sitting and treadmill groups (all Fs > 78.77, Ps < 0.001). There were no main effects or interactions as a function of group for any analyses (Fs < 0.79, Ps > 0.38), suggesting no decrements or enhancements in conflict-related control and adjustment processes or response inhibition for those walking on a treadmill versus sitting. We conclude that cognitive control performance remains relatively unaffected during slow treadmill walking relative to sitting.
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Affiliation(s)
- Michael J Larson
- Department of Psychology and Neuroscience Center, Brigham Young University, Provo UT, USA
| | | | - Kaylie Carbine
- Department of Psychology and Neuroscience Center, Brigham Young University, Provo UT, USA
| | - Kyle R Hill
- Department of Psychology and Neuroscience Center, Brigham Young University, Provo UT, USA
| | - Edward Christenson
- Department of Exercise Sciences, Brigham Young University, Provo UT, USA
| | - Travis Masterson
- Department of Exercise Sciences, Brigham Young University, Provo UT, USA
| | - Rick LeCheminant
- Department of Exercise Sciences, Brigham Young University, Provo UT, USA
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