Examining the Impact of Wellness Champions on the Effectiveness of a Workplace Health and Well-Being Program

Implementation and engagement of the SMART Work & Life sitting reduction intervention: an exploratory analysis on intervention effectiveness

BACKGROUND

To enhance the impact of interventions, it is important to understand how intervention engagement relates to study outcomes. We report on the level of implementation and engagement with the SMART Work & Life (SWAL) programme (delivered with (SWAL plus desk) and without a height-adjustable desk (SWAL)) and explore the effects of different levels of this on change in daily sitting time in comparison to the control group.

METHODS

The extent of intervention delivery by workplace champions and the extent of engagement by champions and participants (staff) with each intervention activity was assessed by training attendance logs, workplace champion withdrawal dates, intervention activities logs and questionnaires. These data were used to assess whether a cluster met defined criteria for low, medium, or high implementation and engagement or none of these. Mixed effects linear regression analyses tested whether change in sitting time varied by: (i) the number of intervention activities implemented and engaged with, and (ii) the percentage of implementation and engagement with all intervention strategies.

RESULTS

Workplace champions were recruited for all clusters, with 51/52 (98%) attending training. Overall, 12/27 (44.4%) SWAL and 9/25 (36.0%) SWAL plus desk clusters implemented all main intervention strategies. Across remaining clusters, the level of intervention implementation varied. Those in the SWAL (n = 8 (29.6%) clusters, 80 (32.1%) participants) and SWAL plus desk (n = 5 (20.0%) clusters, 41 (17.1%) participants) intervention groups who implemented and engaged with the most intervention strategies and had the highest percentage of cluster implementation and engagement with all intervention strategies sat for 30.9 (95% CI -53.9 to -7.9, p = 0.01) and 75.6 (95% CI -103.6 to -47.7, p < 0.001) fewer minutes/day respectively compared to the control group at 12 month follow up. These differences were larger than the complete case analysis. The differences in sitting time observed for the medium and low levels were similar to the complete case analysis.

CONCLUSIONS

Most intervention strategies were delivered to some extent across the clusters although there was large variation. Superior effects for sitting reduction were seen for those intervention groups who implemented and engaged with the most intervention components and had the highest level of cluster implementation and engagement.

TRIAL REGISTRATION

ISRCTN11618007. Registered on 24 January 2018. https://www.isrctn.com/ISRCTNISRCTN11618007 .

Emotional Intelligence in Ultra-Marathon Runners: Implications for Recovery Strategy and Stress Responses during an Ultra-Endurance Race

The aim of this research was to investigate the role of trait emotional intelligence (EI) in recovery stress states in a mountain ultra-marathon (MUM) race. Recovery stress states of 13 finishers were assessed before, during, and immediately after the end of an extreme MUM, whereas emotional intelligence was assessed 2 days before the MUM race. Temporal evolutions of recovery stress states were examined. Stress states increased after the race whereas recovery states decreased in all participants. In addition, recovery states were influenced by the trait EI level assessed before the competition. Results supported the hypothesis that trait EI tends to have a positive effect by boosting recovery strategies. In this perspective, trait EI could have a protective role against stress and improve pre-competition mental preparation. High scores of trait EI (in comparison to low scores of trait EI) could have helped athletes to increase recovery states in order to improve their psychological adaptation to one of the most difficult races in the world.

Descriptive Study of Employee Engagement With Workplace Wellness Interventions in the UK

OBJECTIVE

To explore sequential steps of employee engagement in wellness interventions and the impact of wellness interventions on employee health.

METHODS

Using previously collected survey data from 23,667 UK employees, we tabulated intervention availability, awareness, participation, and associated health improvement and compared engagement by participation and risk status.

RESULTS

Employees' awareness of wellness interventions at their workplaces was often low (mean 43.3%, range 11.6%-82.3%). Participation was highest in diet/nutrition initiatives (94.2%) and lowest in alcohol counseling and smoking cessation interventions (2.1%). Employees with health risks were less likely than lower-risk employees to report awareness, participation, and health improvements from wellness interventions addressing the relevant health concern.

CONCLUSION

Employers and policymakers should consider variation in intervention engagement as they plan and implement wellness interventions. Engaging employee populations with higher health risks requires a more targeted approach.

An observation of the impact of tailored messages on participant non-compliance during Desire2Move

We assessed the impact of tailored versus targeted messages on program non-compliance during Desire2Move (D2M), an 8-week eHealth program that promotes physical activity (PA). Participants recorded minutes of PA using MapMyFitness, which counted toward their departments' PA total. Departments were randomized into the targeted messaging (TM) or tailored messaging (TM+) group based on participant-reported goals. Participants who did not provide a goal were assigned to the control group (CG). Eligible participants were employees from invited departments who were non-compliant for at least 1 week of D2M. Upon initial non-compliance, participants across groups received a targeted email message prompting program resumption. For subsequent non-compliance, the TM group continued to receive the same targeted message. The TM+ group received a message tailored to the participant's program goal. The CG group did not receive additional messages. Participants (n = 149) were mostly female (68.5%), staff (44.3%), with an average age of 43.7 (SD = 11.1). Analyses revealed significant group differences in non-compliance between TM+ (M = 2.6, SD = 1.9) and TM (M = 4.0, SD = 2.1), F(16,88) = 3.4, p < .01; d = .64, and between TM+ (M = 2.6, SD = 1.9) and CG (M = 3.8, SD = 2.1), F(1,74) = 13.3, p < .01; d = .56. There was no significant group difference between TM and CG, F(1,80) = 0.1, p = .75; d = .02. Tailored messages improved individual program compliance. More research is needed to assess the relationship between program compliance and PA behavior change.

Brief Exercise at Work (BE@Work): A Mixed-Methods Pilot Trial of a Workplace High-Intensity Interval Training Intervention

Introduction: The efficacy of high-intensity interval training (HIIT) for improving markers of physical fitness and cardiometabolic health is promising. The workplace is one non-laboratory setting where the effectiveness of HIIT could be explored. The aim of this study was to undertake a mixed-methods exploratory pilot trial of a workplace HIIT intervention named Brief Exercise at Work (BE@Work). Methods: Fifty-four healthy employees (mean ± standard deviation [SD] age 46 ± 10 years) from two workplaces in Northeast England were allocated to 8 weeks of thrice-weekly workplace HIIT based on boxing, stair climbing and stepping, comprising 4-7 60 s high-intensity intervals interspersed with 75 s rest (n = 30), or a no-intervention control (n = 24). The primary outcome was the change SD of predicted maximal oxygen consumption (VO2max). Markers of physical fitness, cardiometabolic health and mental well-being were also measured at baseline and follow-up. Participant perceptions of the intervention were explored in post-intervention focus groups (n = 9). Results: Mean (±SD) session attendance was 82% (±15%). Mean peak heart rate across the intervention was 87% of age-predicted maximal heart rate with a within- and between-subject SD of 5.5% and 3.7%, respectively. The SD of changes in predicted VO2max was 6.6 mL·kg-1·min-1 across both groups, which can be used to inform sample size estimations for a future full trial. The control-adjusted mean increase (95% confidence interval) in predicted VO2max was 3.9 (-0.2 to 8.1) mL·kg-1·min-1, corresponding to a Cohen's D of 0.47. We also observed preliminary evidence of small to moderate effects in favour of the intervention group for non-dominant leg extensor muscle power, markers of health-related quality of life, well-being and perceived stress and small to moderate effects in favour of the controls in perceived pain, physical activity and high-density lipoprotein cholesterol. During HIIT, focus group participants reported physiological responses they perceived as unpleasant or tiring (e.g., breathlessness, local muscular fatigue), but also that they felt alert and energised afterwards. Conclusion: The findings of this exploratory pilot trial support the implementation of a definitive randomised controlled trial to quantify the effectiveness of a workplace HIIT intervention.