Socio-Ecological Intervention to Promote Active Commuting to Work: Protocol and Baseline Findings of a Cluster Randomized Controlled Trial in Finland

A social-ecological model of working from home during COVID-19

Working from Home (WFH) is emerging as a critical measure for reducing transport demand. Indeed, the COVID-19 pandemic has revealed that trip avoidance measures, especially WFH, could help address Sustainable Development Goal 11.2 (creating sustainable transport systems in cities) by decreasing commuter trips by private motor vehicles. This study aimed to explore and identify the attributes that supported WFH during the pandemic and construct a Social-Ecological Model (SEM) of WFH within the context of travel behaviour. We conducted in-depth interviews with 19 stakeholders from Melbourne, Australia and found that WFH during COVID-19 has fundamentally changed commuter travel behaviour. There was a consensus among participants that a hybrid-work model will emerge post-COVID-19 (e.g., working three days in the office and two days at home). We identified 21 attributes that influenced WFH and mapped these attributes across the five traditional SEM levels (intrapersonal, interpersonal, institutional, community and public policy). In addition, we proposed a sixth higher-order level: "global", to reflect the worldwide phenomena of COVID-19 and computer programs that also supported WFH. We found that WFH attributes were concentrated at the intrapersonal (individual) and institutional (workplace) levels. Indeed, workplaces are key to supporting WFH in the long-term. Whereby, workplace provision of laptops, office equipment, internet connection and flexible work policies enable WFH, and unsupportive organisational cultures and managers are potential barriers to WFH. This SEM of WFH benefits both researchers and practitioners by providing guidance of the key attributes required to sustain WFH behaviours post-COVID-19.

Workplace pedometer interventions for increasing physical activity

BACKGROUND

The World Health Organization (WHO) recommends undertaking 150 minutes of moderate-intensity physical activity per week, but most people do not. Workplaces present opportunities to influence behaviour and encourage physical activity, as well as other aspects of a healthy lifestyle. A pedometer is an inexpensive device that encourages physical activity by providing feedback on daily steps, although pedometers are now being largely replaced by more sophisticated devices such as accelerometers and Smartphone apps. For this reason, this is the final update of this review.

OBJECTIVES

To assess the effectiveness of pedometer interventions in the workplace for increasing physical activity and improving long-term health outcomes.

SEARCH METHODS

We searched the Cochrane Central Register of Controlled Trials, MEDLINE, Embase, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), Occupational Safety and Health (OSH) UPDATE, Web of Science, ClinicalTrials.gov, and the WHO International Clinical Trials Registry Platform from the earliest record to December 2016. We also consulted the reference lists of included studies and contacted study authors to identify additional records. We updated this search in May 2019, but these results have not yet been incorporated. One more study, previously identified as an ongoing study, was placed in 'Studies awaiting classification'.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) of workplace interventions with a pedometer component for employed adults, compared to no or minimal interventions, or to alternative physical activity interventions. We excluded athletes and interventions using accelerometers. The primary outcome was physical activity. Studies were excluded if physical activity was not measured.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures expected by Cochrane. When studies presented more than one physical activity measure, we used a pre-specified list of preferred measures to select one measure and up to three time points for analysis. When possible, follow-up measures were taken after completion of the intervention to identify lasting effects once the intervention had ceased. Given the diversity of measures found, we used ratios of means (RoMs) as standardised effect measures for physical activity.

MAIN RESULTS

We included 14 studies, recruiting a total of 4762 participants. These studies were conducted in various high-income countries and in diverse workplaces (from offices to physical workplaces). Participants included both healthy populations and those at risk of chronic disease (e.g. through inactivity or overweight), with a mean age of 41 years. All studies used multi-component health promotion interventions. Eleven studies used minimal intervention controls, and four used alternative physical activity interventions. Intervention duration ranged from one week to two years, and follow-up after completion of the intervention ranged from three to ten months. Most studies and outcomes were rated at overall unclear or high risk of bias, and only one study was rated at low risk of bias. The most frequent concerns were absence of blinding and high rates of attrition. When pedometer interventions are compared to minimal interventions at follow-up points at least one month after completion of the intervention, pedometers may have no effect on physical activity (6 studies; very low-certainty evidence; no meta-analysis due to very high heterogeneity), but the effect is very uncertain. Pedometers may have effects on sedentary behaviour and on quality of life (mental health component), but these effects were very uncertain (1 study; very low-certainty evidence). Pedometer interventions may slightly reduce anthropometry (body mass index (BMI) -0.64, 95% confidence interval (CI) -1.45 to 0.18; 3 studies; low-certainty evidence). Pedometer interventions probably had little to no effect on blood pressure (systolic: -0.08 mmHg, 95% CI -3.26 to 3.11; 2 studies; moderate-certainty evidence) and may have reduced adverse effects (such as injuries; from 24 to 10 per 100 people in populations experiencing relatively frequent events; odds ratio (OR) 0.50, 95% CI 0.30 to 0.84; low-certainty evidence). No studies compared biochemical measures or disease risk scores at follow-up after completion of the intervention versus a minimal intervention. Comparison of pedometer interventions to alternative physical activity interventions at follow-up points at least one month after completion of the intervention revealed that pedometers may have an effect on physical activity, but the effect is very uncertain (1 study; very low-certainty evidence). Sedentary behaviour, anthropometry (BMI or waist circumference), blood pressure (systolic or diastolic), biochemistry (low-density lipoprotein (LDL) cholesterol, total cholesterol, or triglycerides), disease risk scores, quality of life (mental or physical health components), and adverse effects at follow-up after completion of the intervention were not compared to an alternative physical activity intervention. Some positive effects were observed immediately at completion of the intervention periods, but these effects were not consistent, and overall certainty of evidence was insufficient to assess the effectiveness of workplace pedometer interventions.

AUTHORS' CONCLUSIONS

Exercise interventions can have positive effects on employee physical activity and health, although current evidence is insufficient to suggest that a pedometer-based intervention would be more effective than other options. It is important to note that over the past decade, technological advancement in accelerometers as commercial products, often freely available in Smartphones, has in many ways rendered the use of pedometers outdated. Future studies aiming to test the impact of either pedometers or accelerometers would likely find any control arm highly contaminated. Decision-makers considering allocating resources to large-scale programmes of this kind should be cautious about the expected benefits of incorporating a pedometer and should note that these effects may not be sustained over the longer term. Future studies should be designed to identify the effective components of multi-component interventions, although pedometers may not be given the highest priority (especially considering the increased availability of accelerometers). Approaches to increase the sustainability of intervention effects and behaviours over a longer term should be considered, as should more consistent measures of physical activity and health outcomes.

Socio-Ecological Natural Experiment with Randomized Controlled Trial to Promote Active Commuting to Work: Process Evaluation, Behavioral Impacts, and Changes in the Use and Quality of Walking and Cycling Paths

Active commuting to work (ACW) has beneficial effects on health, traffic, and climate. However, more robust evidence is needed on how to promote ACW. This paper reports the findings of a multilevel natural experiment with a randomized controlled trial in 16 Finnish workplaces. In Phase 1, 11 workplaces (1823 employees) from Area 1 were exposed to environmental improvements in walking and cycling paths. In Phase 2, five more workplaces (826 employees) were recruited from Area 2 and all workplaces were randomized into experimental group (EXP) promoting ACW with social and behavioral strategies and comparison group (COM) participating only in data collection. Process and impact evaluation with questionnaires, travel diaries, accelerometers, traffic calculations, and auditing were conducted. Statistics included Wilcoxon Signed Ranks Test, Mann-Whitney U-test, and after-before differences with 95% confidence intervals (95% CI). After Phase 1, positive change was seen in the self-reported number of days, which the employees intended to cycle part of their journey to work in the following week (p = 0.001). After Phase 2, intervention effect was observed in the proportion of employees, who reported willingness to increase walking (8.7%; 95% CI 1.8 to 15.6) and cycling (5.5%; 2.2 to 8.8) and opportunity to cycle part of their journey to work (5.9%; 2.1 to 9.7). To conclude, the intervention facilitated employees’ motivation for ACW, which is the first step towards behavior change.

DEBATE: Do interventions based on behavioral theory work in the real world?

BACKGROUND

Behavioral scientists suggest that for behavior change interventions to work effectively, and deliver population-level health outcomes, they must be underpinned by behavioral theory. However, despite implementation of such interventions, population levels of both health outcomes and linked behaviors have remained relatively static. We debate the extent to which interventions based on behavioral theory work in the real world to address population health outcomes.

DISCUSSION

Hagger argues there is substantive evidence supporting the efficacy and effectiveness of interventions based on behavioral theory in promoting population-level health behavior change in the 'real world'. However, large-scale effectiveness trials within existing networks are relatively scarce, and more are needed leveraging insights from implementation science. Importantly, sustained investment in effective behavioral interventions is needed, and behavioral scientists should engage in greater advocacy to persuade gatekeepers to invest in behavioral interventions. Weed argues there is no evidence to demonstrate behavioral theory interventions are genuinely effective in real world settings in populations that are offered them: they are merely efficacious for those that receive them. Despite behavioral volatility that is a normal part of maintaining steady-state population behavior levels creating the illusion of effectiveness, interventions fail in shifting the curve of population behaviors because they focus on individuals rather than populations. Hagger responds that behavioral interventions work in the 'real world' in spite of, not because of, flux in health behaviors, and that the contention that behavioral theory focuses solely on individual behavior change is inaccurate. Weed responds that the focus on extending the controls of efficacy trials into implementation is impractical, uneconomic and futile, and this has squandered opportunities to conduct genuine effectiveness trials in naturalistic settings. Hagger contends that interventions based on behavioral theory are effective in changing population-level behavior in 'real world' contexts, but more evidence on how best to implement them and how to engage policymakers and practitioners to provide sustained funding is needed. Weed argues for a paradigm shift, away from aggregative attempts to effect individual behavior change towards a focus on disrupting social practices, underpinned by understanding social and economic causation of the distribution and acceptance of behaviors in a population.