Is self-reporting workplace activity worthwhile? Validity and reliability of occupational sitting and physical activity questionnaire in desk-based workers

Background: With the advent of workplace health and wellbeing programs designed to address prolonged occupational sitting, tools to measure behaviour change within this environment should derive from empirical evidence. In this study we measured aspects of validity and reliability for the Occupational Sitting and Physical Activity Questionnaire that asks employees to recount the percentage of work time they spend in the seated, standing, and walking postures during a typical workday. Methods: Three separate cohort samples (N = 236) were drawn from a population of government desk-based employees across several departmental agencies. These volunteers were part of a larger state-wide intervention study. Workplace sitting and physical activity behaviour was measured both subjectively against the International Physical Activity Questionnaire, and objectively against ActivPal accelerometers before the intervention began. Criterion validity and concurrent validity for each of the three posture categories were assessed using Spearman's rank correlation coefficients, and a bias comparison with 95 % limits of agreement. Test-retest reliability of the survey was reported with intraclass correlation coefficients. Results: Criterion validity for this survey was strong for sitting and standing estimates, but weak for walking. Participants significantly overestimated the amount of walking they did at work. Concurrent validity was moderate for sitting and standing, but low for walking. Test-retest reliability of this survey proved to be questionable for our sample. Conclusions: Based on our findings we must caution occupational health and safety professionals about the use of employee self-report data to estimate workplace physical activity. While the survey produced accurate measurements for time spent sitting at work it was more difficult for employees to estimate their workplace physical activity

The reliability of strength tests performed in elevated shoulder positions using a handheld dynamometer

CONTEXT: The reliable measurement of shoulder strength is important when assessing athletes involved in overhead activities. Swimmers' shoulders are subject to repetitive humeral elevation and consequently have a high risk of developing movement-control issues and pain. Shoulder-strength tests performed in positions of elevation assist with the detection of strength deficits that may affect injury and performance. The reliability of isometric strength tests performed in positions of humeral elevation without manual stabilization, which is a typical clinical scenario, has not been established

Relationship between mean daily solar exposure and serum 25(OH)D concentrations during the study.

<p>¹Diamonds represent mean daily solar exposure during the study measured as Mega joules/m². Data obtained from the Australian Bureau of Meteorology (<a href="http://www.bom.gov.au/tas/observations/index.shtml" target="_blank">http://www.bom.gov.au/tas/observations/index.shtml</a>). ²Square points and y-axis error bars represent mean and 95% confidence intervals of serum 25(OH)D concentrations (nmol/L) measured at each study time point estimated by repeated-measures mixed methods linear regression; and sign-wave lines were calculated by mathematical modelling using coefficients for sine-wave analysis estimated using repeated-measures nonlinear regression.</p

Amplitude of annual variation in serum 25(OH)D concentrations (nmol/L) in different supplementation groups.

1<p>Mean amplitude of annual variation, estimated by repeated measures non-linear regression using a sine wave model, adjusted for age and gender.</p>2<p>Mean difference of amplitude between 100–600 IU/day and 800 IU/day: 5.2 (95%CI-1.6 to 12.0; p = 0.13).</p>3<p>Comparison of the mean amplitude between non-supplement and supplement groups.</p

Relative proportions of participants ingesting vitamin D supplements during the study and at follow-up.

1<p>Seasonal groupings for winter and spring included data from two time points (i.e. September 2009 and September 2010 for winter and December 2009 and December 2010 for spring).</p>2<p>The relative proportion of participants taking Vitamin D supplements of different doses at the end of different seasons was compared to the relative proportion at the end of Winter (September), estimated using repeated-measures negative binomial regression and expressed as an incidence rate ratio (IRR; 95% confidence intervals; P-values).</p>3<p>Follow-up: at the end of Winter (September) 2011, nine months after the final study time point and after participant were released from restricting vitamin D supplementation (study exclusion criterion was>800 IU/day).</p

Effect of vitamin D supplementation on serum 25(OH)D concentrations (nmol/L) during the study and at follow-up.

1<p>Mean (±standard deviation) and comparison of serum 25(OH)D concentration (nmol/L) in patients with and without (low- and high-dose) supplements at the end of different seasons, estimated by repeated-measures mixed methods linear regression (mean difference; 95% confidence intervals; P-values corrected for multiple comparisons by the Holm method), adjusted for age and time of subject visit.</p>2<p>Large variation in participant numbers (Winter 2009, Spring 2010) is because a small group of participants commenced the study at the end of Winter (September) 2009 and completed at the end of Winter 2010; the majority commenced at the end of Spring (December) 2009 and completed at the end of Spring 2010.</p>3<p>Maximum allowable dose of vitamin D supplements increased between the end of the study and the follow-up appointment.</p

Relative proportions of participants with serum 25(OH)D concentrations (nmol/L) below different clinical thresholds.¹

1<p>Clinical thresholds were chosen to encompass the recommendations in the current literature <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059063#pone.0059063-Ross1" target="_blank">[2]</a><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059063#pone.0059063-PrezLpez1" target="_blank">[4]</a><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059063#pone.0059063-Nowson1" target="_blank">[7]</a><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059063#pone.0059063-BritishAssociationof1" target="_blank">[30]</a><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059063#pone.0059063-DawsonHughes1" target="_blank">[6]</a>. <25 nmol/L = deficient, 25–50 nmol/L = insufficient, 50–75 nmol/L = sufficient, >75 nmol/L = optimal.</p>2<p>Measurements for each time period were made over three weeks at the end of each season. “Winter 2011” represented the follow-up period, nine months after completion of the primary study, and after the participants were released from restricting vitamin D supplementation (study exclusion criterion>800 IU/day).</p>3<p>Number of subjects assessed at each time period are shown, and mean serum 25(OH)D concentration (±standard deviation) were estimated by mixed methods linear regression, adjusted for participant age and time from beginning of study. Large variation in participant numbers (Winter 2009, Spring 2010) is because a small group of participants commenced the study at the end of Winter (September) 2009 and completed at the end of Winter 2010; the majority commenced at the end of Spring (December) 2009 and completed at the end of Spring 2010.</p>4<p>The relative proportion of participants having serum 25(OH)D concentration below different clinical thresholds shown was compared to the relative proportion at the end of Winter (September) 2010 (chosen as the references because the end of Winter 2009 represented the pilot group only), estimated using repeated-measures negative binomial regression and expressed as an incidence rate ratio (IRR; 95% confidence intervals; p-values).</p

The most significant determinants of vitamin D status (serum 25(OH)D concentration, nmol/L).

1<p>Mean serum 25(OH)D concentration (nmol/L) at end of Winter, the mean difference (95% confidence intervals; p-values) at the end of other seasons, and the effect of taking Vitamin D supplements, wearing protective clothing, and percentage body fat mass, were estimated using repeated-measures mixed methods linear regression analysis adjusted for age and time of subject visit. Variables for inclusion in this model were selected using stepwise regression from: Age, gender, sun exposure, sun avoidance, use of sunscreen, wearing hat, wearing protective clothing, weight, vitamin D supplements, dietary vitamin D, dietary fat as percentage of energy, saturated fat as percentage of total fat.</p>2<p>Data was organised into four seasonal groupings, to enable investigation of the determinants of vitamin D status based on season rather than of specific time-points.</p>3<p>The effect of wearing protective clothing and percentage body fat mass (as standardised normal transformations) on serum 25(OH)D concentration was expressed as the slope of the association: one standard deviation rise in each measure was associated with change shown in the table (95% confidence intervals of the slope; p-values).</p

Additional file 1: of Improving physical activity, pain and function in patients waiting for hip and knee arthroplasty by combining targeted exercise training with behaviour change counselling: study protocol for a randomised controlled trial

Participant booklet. (PDF 705 kb

Additional file 2: of Improving physical activity, pain and function in patients waiting for hip and knee arthroplasty by combining targeted exercise training with behaviour change counselling: study protocol for a randomised controlled trial

SPIRIT 2013 Checklist. (DOC 138 kb