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Whitley MD, Perez LG, Castro G, Larson A, Derose KP. Modifying Text Messages from a Faith-Based Physical Activity Intervention with Latino Adults in Response to the COVID-19 Pandemic. COMMUNITY HEALTH EQUITY RESEARCH & POLICY 2024; 44:399-407. [PMID: 36651265 PMCID: PMC9852972 DOI: 10.1177/2752535x221150009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
BACKGROUND Text messages are useful for health promotion and can be modified during public health emergencies. PURPOSE Describe how we developed and implemented a physical activity (PA) text messaging component within a faith-based intervention, modified the text message content in response to the COVID-19 pandemic and evaluated participants' perceptions of the modified text messages. RESEARCH DESIGN AND STUDY SAMPLE PA promotion text messages were delivered to predominately Spanish-speaking, churchgoing Latino adults (n = 284) in Los Angeles, California. In 2020, we modified the messages to disseminate COVID-19-related information and support and share virtual PA resources. DATA COLLECTION AND ANALYSIS We analyzed quantitative and qualitative survey data to gauge participants' experiences with the text messages. RESULTS COVID-19 related text messages were a feasible, acceptable addition to a PA intervention for a sample of Latinos. CONCLUSIONS Throughout the pandemic, the messages enabled continued communication and support for PA and protection from COVID-19 in a population at high-risk of health inequities.
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Affiliation(s)
- Margaret D Whitley
- Behavioral and Policy Sciences Department, RAND Corporation, Santa Monica, CA, USA
| | - Lilian G Perez
- Behavioral and Policy Sciences Department, RAND Corporation, Santa Monica, CA, USA
| | - Gabriela Castro
- Behavioral and Policy Sciences Department, RAND Corporation, Santa Monica, CA, USA
| | - Anne Larson
- California State University, Los Angeles, Los Angeles, CA, USA
| | - Kathryn P Derose
- Behavioral and Policy Sciences Department, RAND Corporation, Santa Monica, CA, USA
- Department of Health Promotion & Policy, University of Massachusetts Amherst, Amherst, MA, USA
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Halloway S, Buchholz SW, Odiaga JA, Bavis MP, Lemke S, Cygan HR, Kalensky M, Pelt PP, Braun LT, Tafini S, Opdycke A, Knudson KA, Daniel M, Wilbur J. DNP-PhD Collaboration in NINR-Funded Physical Activity Trials: A Series of Case Studies. West J Nurs Res 2023; 45:592-598. [PMID: 37114846 DOI: 10.1177/01939459231168699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
Collaboration between Doctor of Nursing Practice (DNP) scholars and Doctor of Philosophy (PhD) scholars is crucial to efficiently advance and disseminate nursing science. Also, DNP-PhD collaboration can help achieve priorities outlined in the recent National Institute of Nursing Research (NINR) Strategic Plan. The purpose of this series of case studies is to describe exemplars of ongoing DNP-PhD collaborations across three NINR-funded trials (1 completed, 2 ongoing) testing physical activity interventions for women at risk for cardiovascular disease. In our three physical activity intervention trials for women, we categorized examples of DNP-PhD collaboration by the four phases of the team-based research model (development, conceptualization, implementation, and translation). Across all three trials, DNP and PhD scholars contributed successfully to all phases of research in an iterative manner. Future work should focus on expanding DNP-PhD collaboration in behavioral trials, which can inform adapted, contemporary models of iterative DNP-PhD collaboration.
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Affiliation(s)
- Shannon Halloway
- Department of Biobehavioral Nursing Science, University of Illinois Chicago College of Nursing, Chicago, IL, USA
| | | | - Janice A Odiaga
- Department of Women, Children, and Family Nursing, Rush University College of Nursing, Chicago, IL, USA
| | - Margaret Perlia Bavis
- Department of Community, Systems, and Mental Health Nursing, Rush University College of Nursing, Chicago, IL, USA
| | - Sally Lemke
- Department of Women, Children, and Family Nursing, Rush University College of Nursing, Chicago, IL, USA
- Office of Community Health Equity and Engagement, Affirm: The Rush Center for Gender, Sexuality, and Reproductive Health, Rush University Medical Center, Chicago, IL, USA
| | - Heide R Cygan
- Department of Community, Systems, and Mental Health Nursing, Rush University College of Nursing, Chicago, IL, USA
| | - Melissa Kalensky
- Department of Community, Systems, and Mental Health Nursing, Rush University College of Nursing, Chicago, IL, USA
| | | | | | - Susan Tafini
- University Cardiologists, Rush University Medical Center, Chicago, IL, USA
| | - Anita Opdycke
- Northwestern University Health Service, Chicago, IL, USA
| | - Krista A Knudson
- Institute for Translational Medicine, Rush University, Hartland, WI, USA
| | - Manju Daniel
- Department of Community, Systems, and Mental Health Nursing, Rush University College of Nursing, Chicago, IL, USA
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Buchholz SW, Wilbur J, Halloway S, Schoeny M, Johnson T, Vispute S, Kitsiou S. Study protocol for a sequential multiple assignment randomized trial (SMART) to improve physical activity in employed women. Contemp Clin Trials 2020; 89:105921. [PMID: 31899371 PMCID: PMC7242143 DOI: 10.1016/j.cct.2019.105921] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Revised: 12/20/2019] [Accepted: 12/23/2019] [Indexed: 01/09/2023]
Abstract
INTRODUCTION Physical activity monitors, motivational text messages, personal calls, and group meetings, have proven to be efficacious physical activity interventions. However, individual participant response to these interventions varies drastically. A SMART design (sequential multiple assignment randomized trial) provides an effective way to test interventions that start with an initial treatment and then transition to an augmented treatment for non-responders. We describe a SMART to determine the most effective adaptive intervention to increase physical activity (steps, moderate-to-vigorous physical activity) and improve cardiovascular health among employed women who are not regularly physically active. The SMART uses combinations of four treatments: 1) enhanced physical activity monitor (Fitbit wearable activity monitor and mobile app with goal setting and physical activity prescription), 2) text messages, 3) personal calls, and 4) group meetings. METHODS Participants (N = 312) include women ages 18-70 employed at a large academic medical center. Women will be randomized to an initial intervention, either an enhanced physical activity monitor or enhanced physical activity monitor + text messaging. Non-responders to the initial intervention at 2 months will be randomized to either personal calls or groups meetings for the next 6 months. At 8 months, all participants will return to only an enhanced physical activity monitor until their final 12-month assessment. DISCUSSION Results of this study will add to the literature on improving physical activity in employed women. This study will identify effective interventions for women who respond to less intensive treatments, while maximizing benefits for those who need a more intensive approach.
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Affiliation(s)
- Susan W Buchholz
- Rush University, College of Nursing, Chicago, IL, United States of America.
| | - JoEllen Wilbur
- Rush University, College of Nursing, Chicago, IL, United States of America
| | - Shannon Halloway
- Rush University, College of Nursing, Chicago, IL, United States of America
| | - Michael Schoeny
- Rush University, College of Nursing, Chicago, IL, United States of America
| | - Tricia Johnson
- Rush University, College of Health Sciences, Chicago, IL, United States of America
| | - Sachin Vispute
- Rush University, College of Nursing, Chicago, IL, United States of America
| | - Spyros Kitsiou
- University of Illinois at Chicago, College of Applied Health Sciences, Chicago, IL, United States of America
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Smith DM, Duque L, Huffman JC, Healy BC, Celano CM. Text Message Interventions for Physical Activity: A Systematic Review and Meta-Analysis. Am J Prev Med 2020; 58:142-151. [PMID: 31759805 PMCID: PMC6956854 DOI: 10.1016/j.amepre.2019.08.014] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Revised: 08/07/2019] [Accepted: 08/08/2019] [Indexed: 01/28/2023]
Abstract
CONTEXT Despite clear health benefits, many individuals fail to achieve the recommended levels of physical activity. Text message interventions to promote physical activity hold promise owing to the ubiquity of cell phones and the low expense of text message delivery. EVIDENCE ACQUISITION A systematic review and meta-analysis were performed to examine the impact of text message interventions on physical activity. Searches of PubMed, PsycINFO, Scopus, Cochrane, and ClinicalTrials.gov databases from inception to December 2017 were performed to identify studies investigating one-way text message interventionss to promote physical activity. A subset of RCTs, including an objective (accelerometer-based) physical activity outcome, were included in random-effects meta-analyses in 2018. EVIDENCE SYNTHESIS The systematic search revealed 944 articles. Of these, 59 were included in the systematic review (12 1-arm trials and 47 controlled trials; n=8,742; mean age, 42.2 years; 56.2% female). In meta-analyses of 13 studies (n=1,346), text message interventionss led to significantly greater objectively measured postintervention steps/day (Cohen's d=0.38, 95% CI=0.19, 0.58, n=10 studies). Analysis of postintervention moderate-to-vigorous physical activity found a similar but not statistically significant effect (Cohen's d=0.31, 95% CI= -0.01, 0.63, n=5 studies). Interventions with more components, tailored content, and interventions in medical populations led to nonsignificantly larger effect sizes compared with text message interventions without these features. CONCLUSIONS Text message interventions lead to higher objectively measured postintervention physical activity compared with control groups. More extensive, well-controlled studies are needed to examine this relationship further and identify characteristics of effective text message interventions.
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Affiliation(s)
- Diana M Smith
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts
| | - Laura Duque
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts
| | - Jeff C Huffman
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts
| | - Brian C Healy
- Harvard Medical School, Boston, Massachusetts; Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts
| | - Christopher M Celano
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts; Harvard Medical School, Boston, Massachusetts.
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Whitley MD, Payán DD, Flórez KR, Williams MV, Wong EC, Branch CA, Derose KP. Feasibility and acceptability of a mobile messaging program within a church-based healthy living intervention for African Americans and Latinos. Health Informatics J 2019; 26:880-896. [PMID: 31203706 DOI: 10.1177/1460458219853408] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Church-based programs can act on multiple levels to improve dietary and physical activity behaviors among African Americans and Latinos. However, the effectiveness of these interventions may be limited due to challenges in reaching all congregants or influencing behavior outside of the church setting. To increase intervention impact, we sent mobile messages (text and email) in English or Spanish to congregants (n = 131) from predominantly African American or Latino churches participating in a multi-level, church-based program. To assess feasibility and acceptability, we collected feedback throughout the 4-month messaging intervention and conducted a process evaluation using the messaging platform. We found that the intervention was feasible to implement and acceptable to a racially ethnically diverse study sample with high obesity and overweight rates. While the process evaluation had some limitations (e.g. low response rate), we conclude that mobile messaging is a promising, feasible addition to church-based programs aiming to improve dietary and physical activity behaviors.
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Shrestha N, Kukkonen‐Harjula KT, Verbeek JH, Ijaz S, Hermans V, Pedisic Z. Workplace interventions for reducing sitting at work. Cochrane Database Syst Rev 2018; 12:CD010912. [PMID: 30556590 PMCID: PMC6517221 DOI: 10.1002/14651858.cd010912.pub5] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND A large number of people are employed in sedentary occupations. Physical inactivity and excessive sitting at workplaces have been linked to increased risk of cardiovascular disease, obesity, and all-cause mortality. OBJECTIVES To evaluate the effectiveness of workplace interventions to reduce sitting at work compared to no intervention or alternative interventions. SEARCH METHODS We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, CINAHL, OSH UPDATE, PsycINFO, ClinicalTrials.gov, and the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) search portal up to 9 August 2017. We also screened reference lists of articles and contacted authors to find more studies. SELECTION CRITERIA We included randomised controlled trials (RCTs), cross-over RCTs, cluster-randomised controlled trials (cluster-RCTs), and quasi-RCTs of interventions to reduce sitting at work. For changes of workplace arrangements, we also included controlled before-and-after studies. The primary outcome was time spent sitting at work per day, either self-reported or measured using devices such as an accelerometer-inclinometer and duration and number of sitting bouts lasting 30 minutes or more. We considered energy expenditure, total time spent sitting (including sitting at and outside work), time spent standing at work, work productivity and adverse events as secondary outcomes. DATA COLLECTION AND ANALYSIS Two review authors independently screened titles, abstracts and full-text articles for study eligibility. Two review authors independently extracted data and assessed risk of bias. We contacted authors for additional data where required. MAIN RESULTS We found 34 studies - including two cross-over RCTs, 17 RCTs, seven cluster-RCTs, and eight controlled before-and-after studies - with a total of 3,397 participants, all from high-income countries. The studies evaluated physical workplace changes (16 studies), workplace policy changes (four studies), information and counselling (11 studies), and multi-component interventions (four studies). One study included both physical workplace changes and information and counselling components. We did not find any studies that specifically investigated the effects of standing meetings or walking meetings on sitting time.Physical workplace changesInterventions using sit-stand desks, either alone or in combination with information and counselling, reduced sitting time at work on average by 100 minutes per workday at short-term follow-up (up to three months) compared to sit-desks (95% confidence interval (CI) -116 to -84, 10 studies, low-quality evidence). The pooled effect of two studies showed sit-stand desks reduced sitting time at medium-term follow-up (3 to 12 months) by an average of 57 minutes per day (95% CI -99 to -15) compared to sit-desks. Total sitting time (including sitting at and outside work) also decreased with sit-stand desks compared to sit-desks (mean difference (MD) -82 minutes/day, 95% CI -124 to -39, two studies) as did the duration of sitting bouts lasting 30 minutes or more (MD -53 minutes/day, 95% CI -79 to -26, two studies, very low-quality evidence).We found no significant difference between the effects of standing desks and sit-stand desks on reducing sitting at work. Active workstations, such as treadmill desks or cycling desks, had unclear or inconsistent effects on sitting time.Workplace policy changesWe found no significant effects for implementing walking strategies on workplace sitting time at short-term (MD -15 minutes per day, 95% CI -50 to 19, low-quality evidence, one study) and medium-term (MD -17 minutes/day, 95% CI -61 to 28, one study) follow-up. Short breaks (one to two minutes every half hour) reduced time spent sitting at work on average by 40 minutes per day (95% CI -66 to -15, one study, low-quality evidence) compared to long breaks (two 15-minute breaks per workday) at short-term follow-up.Information and counsellingProviding information, feedback, counselling, or all of these resulted in no significant change in time spent sitting at work at short-term follow-up (MD -19 minutes per day, 95% CI -57 to 19, two studies, low-quality evidence). However, the reduction was significant at medium-term follow-up (MD -28 minutes per day, 95% CI -51 to -5, two studies, low-quality evidence).Computer prompts combined with information resulted in no significant change in sitting time at work at short-term follow-up (MD -14 minutes per day, 95% CI -39 to 10, three studies, low-quality evidence), but at medium-term follow-up they produced a significant reduction (MD -55 minutes per day, 95% CI -96 to -14, one study). Furthermore, computer prompting resulted in a significant decrease in the average number (MD -1.1, 95% CI -1.9 to -0.3, one study) and duration (MD -74 minutes per day, 95% CI -124 to -24, one study) of sitting bouts lasting 30 minutes or more.Computer prompts with instruction to stand reduced sitting at work on average by 14 minutes per day (95% CI 10 to 19, one study) more than computer prompts with instruction to walk at least 100 steps at short-term follow-up.We found no significant reduction in workplace sitting time at medium-term follow-up following mindfulness training (MD -23 minutes per day, 95% CI -63 to 17, one study, low-quality evidence). Similarly a single study reported no change in sitting time at work following provision of highly personalised or contextualised information and less personalised or contextualised information. One study found no significant effects of activity trackers on sitting time at work.Multi-component interventions Combining multiple interventions had significant but heterogeneous effects on sitting time at work (573 participants, three studies, very low-quality evidence) and on time spent in prolonged sitting bouts (two studies, very low-quality evidence) at short-term follow-up. AUTHORS' CONCLUSIONS At present there is low-quality evidence that the use of sit-stand desks reduce workplace sitting at short-term and medium-term follow-ups. However, there is no evidence on their effects on sitting over longer follow-up periods. Effects of other types of interventions, including workplace policy changes, provision of information and counselling, and multi-component interventions, are mostly inconsistent. The quality of evidence is low to very low for most interventions, mainly because of limitations in study protocols and small sample sizes. There is a need for larger cluster-RCTs with longer-term follow-ups to determine the effectiveness of different types of interventions to reduce sitting time at work.
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Affiliation(s)
- Nipun Shrestha
- Victoria UniversityInstitute for Health and Sport (IHES)MelbourneVictoriaAustralia
| | - Katriina T Kukkonen‐Harjula
- South Karelia Social and Health Care District EksoteRehabilitationValto Käkelän katu 3 BLappeenrantaFinland53130
| | - Jos H Verbeek
- Finnish Institute of Occupational HealthCochrane Work Review GroupTYÖTERVEYSLAITOSFinlandFI‐70032
| | - Sharea Ijaz
- Population Health Sciences, Bristol Medical School, University of BristolNIHR CLAHRC West at University Hospitals Bristol NHS Foundation TrustLewins Mead, Whitefriars BuildingBristolUKBS1 2NT
| | - Veerle Hermans
- Vrije Universiteit BrusselFaculty of Psychology & Educational Sciences, Faculty of Medicine & PharmacyPleinlaan 2BrusselsBelgium1050
| | - Zeljko Pedisic
- Victoria UniversityInstitute for Health and Sport (IHES)MelbourneVictoriaAustralia
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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: 51] [Impact Index Per Article: 8.5] [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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Shrestha N, Kukkonen‐Harjula KT, Verbeek JH, Ijaz S, Hermans V, Pedisic Z. Workplace interventions for reducing sitting at work. Cochrane Database Syst Rev 2018; 6:CD010912. [PMID: 29926475 PMCID: PMC6513236 DOI: 10.1002/14651858.cd010912.pub4] [Citation(s) in RCA: 77] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND A large number of people are employed in sedentary occupations. Physical inactivity and excessive sitting at workplaces have been linked to increased risk of cardiovascular disease, obesity, and all-cause mortality. OBJECTIVES To evaluate the effectiveness of workplace interventions to reduce sitting at work compared to no intervention or alternative interventions. SEARCH METHODS We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, CINAHL, OSH UPDATE, PsycINFO, ClinicalTrials.gov, and the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) search portal up to 9 August 2017. We also screened reference lists of articles and contacted authors to find more studies. SELECTION CRITERIA We included randomised controlled trials (RCTs), cross-over RCTs, cluster-randomised controlled trials (cluster-RCTs), and quasi-RCTs of interventions to reduce sitting at work. For changes of workplace arrangements, we also included controlled before-and-after studies. The primary outcome was time spent sitting at work per day, either self-reported or measured using devices such as an accelerometer-inclinometer and duration and number of sitting bouts lasting 30 minutes or more. We considered energy expenditure, total time spent sitting (including sitting at and outside work), time spent standing at work, work productivity and adverse events as secondary outcomes. DATA COLLECTION AND ANALYSIS Two review authors independently screened titles, abstracts and full-text articles for study eligibility. Two review authors independently extracted data and assessed risk of bias. We contacted authors for additional data where required. MAIN RESULTS We found 34 studies - including two cross-over RCTs, 17 RCTs, seven cluster-RCTs, and eight controlled before-and-after studies - with a total of 3,397 participants, all from high-income countries. The studies evaluated physical workplace changes (16 studies), workplace policy changes (four studies), information and counselling (11 studies), and multi-component interventions (four studies). One study included both physical workplace changes and information and counselling components. We did not find any studies that specifically investigated the effects of standing meetings or walking meetings on sitting time.Physical workplace changesInterventions using sit-stand desks, either alone or in combination with information and counselling, reduced sitting time at work on average by 100 minutes per workday at short-term follow-up (up to three months) compared to sit-desks (95% confidence interval (CI) -116 to -84, 10 studies, low-quality evidence). The pooled effect of two studies showed sit-stand desks reduced sitting time at medium-term follow-up (3 to 12 months) by an average of 57 minutes per day (95% CI -99 to -15) compared to sit-desks. Total sitting time (including sitting at and outside work) also decreased with sit-stand desks compared to sit-desks (mean difference (MD) -82 minutes/day, 95% CI -124 to -39, two studies) as did the duration of sitting bouts lasting 30 minutes or more (MD -53 minutes/day, 95% CI -79 to -26, two studies, very low-quality evidence).We found no significant difference between the effects of standing desks and sit-stand desks on reducing sitting at work. Active workstations, such as treadmill desks or cycling desks, had unclear or inconsistent effects on sitting time.Workplace policy changesWe found no significant effects for implementing walking strategies on workplace sitting time at short-term (MD -15 minutes per day, 95% CI -50 to 19, low-quality evidence, one study) and medium-term (MD -17 minutes/day, 95% CI -61 to 28, one study) follow-up. Short breaks (one to two minutes every half hour) reduced time spent sitting at work on average by 40 minutes per day (95% CI -66 to -15, one study, low-quality evidence) compared to long breaks (two 15-minute breaks per workday) at short-term follow-up.Information and counsellingProviding information, feedback, counselling, or all of these resulted in no significant change in time spent sitting at work at short-term follow-up (MD -19 minutes per day, 95% CI -57 to 19, two studies, low-quality evidence). However, the reduction was significant at medium-term follow-up (MD -28 minutes per day, 95% CI -51 to -5, two studies, low-quality evidence).Computer prompts combined with information resulted in no significant change in sitting time at work at short-term follow-up (MD -10 minutes per day, 95% CI -45 to 24, two studies, low-quality evidence), but at medium-term follow-up they produced a significant reduction (MD -55 minutes per day, 95% CI -96 to -14, one study). Furthermore, computer prompting resulted in a significant decrease in the average number (MD -1.1, 95% CI -1.9 to -0.3, one study) and duration (MD -74 minutes per day, 95% CI -124 to -24, one study) of sitting bouts lasting 30 minutes or more.Computer prompts with instruction to stand reduced sitting at work on average by 14 minutes per day (95% CI 10 to 19, one study) more than computer prompts with instruction to walk at least 100 steps at short-term follow-up.We found no significant reduction in workplace sitting time at medium-term follow-up following mindfulness training (MD -23 minutes per day, 95% CI -63 to 17, one study, low-quality evidence). Similarly a single study reported no change in sitting time at work following provision of highly personalised or contextualised information and less personalised or contextualised information. One study found no significant effects of activity trackers on sitting time at work.Multi-component interventions Combining multiple interventions had significant but heterogeneous effects on sitting time at work (573 participants, three studies, very low-quality evidence) and on time spent in prolonged sitting bouts (two studies, very low-quality evidence) at short-term follow-up. AUTHORS' CONCLUSIONS At present there is low-quality evidence that the use of sit-stand desks reduce workplace sitting at short-term and medium-term follow-ups. However, there is no evidence on their effects on sitting over longer follow-up periods. Effects of other types of interventions, including workplace policy changes, provision of information and counselling, and multi-component interventions, are mostly inconsistent. The quality of evidence is low to very low for most interventions, mainly because of limitations in study protocols and small sample sizes. There is a need for larger cluster-RCTs with longer-term follow-ups to determine the effectiveness of different types of interventions to reduce sitting time at work.
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Affiliation(s)
- Nipun Shrestha
- Victoria UniversityInstitute for Health and Sport (IHES)MelbourneAustralia
| | - Katriina T Kukkonen‐Harjula
- South Karelia Social and Health Care District EksoteRehabilitationValto Käkelän katu 3 BLappeenrantaFinland53130
| | - Jos H Verbeek
- Finnish Institute of Occupational HealthCochrane Work Review GroupTYÖTERVEYSLAITOSFinlandFI‐70032
| | - Sharea Ijaz
- Population Health Sciences, Bristol Medical School, University of BristolNIHR CLAHRC West at University Hospitals Bristol NHS Foundation TrustLewins Mead, Whitefriars BuildingBristolUKBS1 2NT
| | - Veerle Hermans
- Vrije Universiteit BrusselFaculty of Psychology & Educational Sciences, Faculty of Medicine & PharmacyPleinlaan 2BrusselsBelgium1050
| | - Zeljko Pedisic
- Victoria UniversityInstitute for Health and Sport (IHES)MelbourneAustralia
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Rehman H, Kamal AK, Sayani S, Morris PB, Merchant AT, Virani SS. Using Mobile Health (mHealth) Technology in the Management of Diabetes Mellitus, Physical Inactivity, and Smoking. Curr Atheroscler Rep 2017; 19:16. [PMID: 28243807 DOI: 10.1007/s11883-017-0650-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
PURPOSE OF REVIEW Cardiovascular mortality remains high due to insufficient progress made in managing cardiovascular risk factors such as diabetes mellitus, physical inactivity, and smoking. Healthy lifestyle choices play an important role in the management of these modifiable risk factors. Mobile health or mHealth is defined as the use of mobile computing and communication technologies (i.e., mobile phones, wearable sensors) for the delivery of health services and health-related information. In this review, we examine some recent studies that utilized mHealth tools to improve management of these risk factors, with examples from developing countries where available. RECENT FINDINGS The mHealth intervention used depends on the availability of resources. While developing countries are often restricted to text messages, more resourceful settings are shifting towards mobile phone applications and wearable technology. Diabetes mellitus has been extensively studied in different settings, and results have been encouraging. Tools utilized to increase physical activity are expensive, and studies have been limited to resource-abundant areas and have shown mixed results. Smoking cessation has had promising initial results with the use of technology, but mHealth's ability to recruit participants beyond those actively seeking to quit has not been established. mHealth interventions appear to be a potential tool in improving control of cardiovascular risk factors that rely on individuals making healthy lifestyle choices. Data related to clinical impact, if any, of commercially available tools is lacking. More studies are needed to assess interventions that target multiple cardiovascular risk factors and their impact on hard cardiovascular outcomes.
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Affiliation(s)
| | | | - Saleem Sayani
- Aga Khan Development Network eHealth Resource Centre for Asia and Africa, Karachi, Pakistan
| | | | - Anwar T Merchant
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina and WJB Dorn VA Medical Center, Columbia, SC, USA
| | - Salim S Virani
- Section of Cardiology, Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX, USA. .,Section of Cardiovascular Research, Department of Medicine, Baylor College of Medicine, Houston, TX, USA. .,Health Services Research and Development (152), Michael E. DeBakey Veterans Affairs Medical Center, 2002 Holcombe Blvd., Houston, TX, 77030, USA.
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