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Objective Sit-stand workstations may result in significant reductions in workplace sitting. However, few studies have examined long-term maintenance under real-world conditions. The purpose of this study was to evaluate workplace sitting time, cardio-metabolic biomarkers, and work productivity during a workplace re-design which included the installation of sit-stand workstations. Design Natural experiment with appropriately matched comparison. Methods Office workers from distinct worksites in the same unit were recruited (Intervention, n = 24; Comparison, n = 12). Intervention arm participants received a sit-stand workstation and 4 months of sitting-specific motivational support. The comparison arm received 4 months of ergonomic focused motivational support. Time spent in sitting, standing, and other physical activity were measured by activPAL3c for a week. Cardio-metabolic biomarkers and work productivity were also measured. Assessments occurred at baseline, 4 months, and 18 months. Results At 4 months, work sitting time was reduced by 56.7 ± 89.1 min/8 h workday (d = −0.64), relative to comparison. Standing time (37.4 ± 69.2 min/8 h workday; d = 0.54) and sit-to-stand transitions (3.3 ± 0.4 min/8 h workday, d = 0.44) were also improved relative to comparison. At 18 months, work sitting time reductions (52.6 ± 68.3 min/8 h workday; d = −0.77) and standing time improvements (17.7 ± 54.8 min/8 h workday, d = 0.32) were maintained in the intervention group relative to comparison. Cardio-metabolic and work productivity changes were mixed; however, strongest effects favoring the intervention group were observed at 18 months. Conclusions Sit-stand workstations, accompanied with behavioral support, were effective in reducing workplace and overall daily sitting and increasing standing time in a real-world setting. The effect appears to have been sustained for 18 months, with mixed results in cardio-metabolic and productivity outcomes.

Objectives To compare acute cognitive effects following bouts of standing (STAND), cycling (CYCLE) and walking (WALK) to a sit-only (SIT) condition. Design Randomized cross-over full-factorial study. Methods Nine overweight (BMI = 29 ± 3 kg/m 2 ) adults (30 ± 15 years; 7 females, 2 males) completed four conditions (SIT, STAND, WALK and CYCLE) across a 6 h period with a 7 days washout period between conditions. SIT consisted of uninterrupted sitting. Experimental conditions included intermittent bouts of standing (STAND), cycling (CYCLE) and walking (WALK). A cognitive performance battery (Cogstate) was completed twice in a seated position following bouts of standing and light-intensity physical activity. Mixed-effects models compared between-condition differences in standardized score (z-score), accuracy (%), and speed (log 10 ms). Results Cognitive performance z-score and accuracy measures were higher during STAND, CYCLE and WALK ( P Conclusions Compared to uninterrupted sitting, short bouts of standing or light-intensity cycling and walking may improve acute cognitive performance.

Purpose We evaluated the validity and sensitivity to change of a workplace questionnaire to assess sedentary behavior (SB) during and outside work. Methods Participants wore an activPAL and completed an SB questionnaire at two time points (baseline and 3-month follow-up). Ecological momentary assessments were used to assess workplace location (at desk vs. away from desk). Intraclass correlation coefficients, mean difference, root of mean square error, kappa agreement, and Bland-Altman plots assessed validity. Sensitivity to change after 3 months of intervention was assessed using the standardized effect size. Results Data from 546 participants (age = 45.1 ± 16.4 years, 24.9% males, 72.7% white) were analyzed. Intraclass correlation coefficients ranged from 0.08 to 0.23. SB was overestimated d ¯ ( 95 % CI ) [] by 47.9 (39.2, 56.6) min during work hours but underestimated for both non–work hours and nonworkdays by −38.3 (−47.4, 29.1) and −106.7 (124.0, −89.5) min, respectively. Participants slightly underestimated SB by −3.4 (−12.6, 5.7)% when at their desk but overestimated SB by 2.8 (−2.4, 8.0)% when not at their desk. The questionnaire demonstrated similar standardized effect size (>0.6) to the activPAL for sedentary and standing time. Conclusions Agreement between the questionnaire and activPAL was on par with other self-report measures. The questionnaire yielded valid estimates of at/away from desk SB and was sensitive to change.

The acceptance of novel performance analysis tools in any sporting domain is heavily dependent on the perceived effectiveness determined by the user type. The extent to which these varied needs can be captured and the flexibility within a systems design is investigated within the research presented in this paper through the application of conceptual enterprise models based upon the Computer Integrated Manufacturing Open System Architecture (CIMOSA) modelling framework. The CIMOSA cube has been used to accommodate a generic design that can be adapted into a swimming specific model, the aim being to develop Human Machine Interfaces (HMI’s) that can be simplified, scaled and reused within numerous sporting domains by formally modelling stakeholder requirements.