More sedentary behaviour questionnaires than you can shake a stick at

Last year I received an email from a colleague asking if I could suggest any particular questionnaire for the measurement of sedentary behaviour.  I emailed the list-serve of the Sedentary Behaviour Research Network (SBRN) to ask for input and got a wealth of responses (13 so far, and the list continues to grow).  I put them into a list just before the holidays, and they are all now available via the SBRN website.

I thought it would be a good idea to also publish the list here on Obesity Panacea (feel free to share it widely).  If you have been looking for a way to assess sedentary behaviour in an upcoming study then this list is for you! And if you aren’t sure whether you should use a questionnaire or a more objective measure of sedentary time, this previous post by Dr Dylan Cliff is likely to be of use.  I also highly recommend this systematic review paper by David Lubans and colleagues, which evaluates the validity and reliability of sedentary behaviour questionnaires in the pediatric age group specifically.

The below questionnaires aren’t listed in any particular order (they are posted in the order in which they were received) but I’ve given a few details about each questionnaire to help you figure out which one is best suited for a given study.  The questionnaires vary in terms of the type of sedentary behaviour (total sedentary time, occupational sedentary behaviours, home-based sedentary behaviours, TV viewing, driving time, etc) and their target population (kids, adults, older adults, and hospitalized populations, etc).  So regardless of your particular study, there should be a questionnaire that will meet your needs.

If you know of any other questionnaires that I’ve missed, please send them along via email or as a comment below.  I will do my best to keep the list updated moving forward.  And to join the SBRN list-serve (it’s free!) click here.


Sedentary Behaviour Questionnaires

1. Bouchard Physical Activity Questionnaire

Description: 3-day activity diary, with each day divided into 96 periods of 15 minutes each. Participants asked code the main activity performed during each 15-minute period using a scale from 1 to 9, ranging from sleeping (category 1) to intense manual work (category 9). Sedentary behaviour can be calculated as the sum of time identified as being in category 2 (“Sitting: eating, listening, writing, etc”). (Source)

Available from American Journal of Clinical Nutrition.

2. Previous-Day Recall of Active and Sedentary Behaviours

Description: An interviewer administered previous-day recall of sedentary and active behaviours in adults and adolescents.  Validation study concluded that “Correlations between the PDR and the activPAL were high, systematic reporting errors were low, and the validity of the PDR was comparable with the ActiGraph.”

Available from Medicine and Science in Sports and Exercise.

3. International Physical Activity Questionnaire (IPAQ)

Description: A questionnaire that can be administered in person or over the phone.  Participants are asked to to list the amount of time that they spend sitting at work, at home, while doing course work, during leisure time (including watching television), as well as time spent in a motor vehicle.

Available as both a short-form and long-form questionnaire in 20+ languages/dialects via the IPAQ website.

4. Marshall Sitting Questionnaire

Description: A questionnaire that assessed time spent sitting on weekdays and weekend days: 1) traveling to and from places, 2) at work, 3) watching television, 4) using a computer at home, and 5) for leisure, not including television.

Results and from validation study: “Reliability coefficients were high for weekday sitting time at work, watching television, and using a computer at home (r = 0.84-0.78) but lower for weekend days across all domains (r = 0.23-0.74). Validity coefficients were highest for weekday sitting time at work and using a computer at home (r = 0.69-0.74). With the exception of computer use and watching television for women, validity of the weekend-day sitting time items was low.

Validation/reliability study available from Medicine and Science in Sports and Exercise with full text availablehere.

5. Workplace Sitting Questionnaire (adapted from Marshall Questionnaire)

Description: A measure of total and domain-specific sitting time based on work and non-workdays in adults.  Asks about sitting time (1) while travelling to and from places; (2) while at work; (3) while watching TV; (4) while using a computer at home; and (5) while doing other leisure activities on work and non-workdays.

Results from validation study: “Measuring total sitting time based on a workday, non-workday and on average had fair to excellent test–retest reliability (ICC=0.46–0.90) and had sufficient criterion validity against accelerometry in women (r=0.22–0.46) and men (r=0.18–0.29). Measuring domain-specific sitting at work on a workday was also reliable (ICC=0.63) and valid (r=0.45).

Available from the British Journal of Sports Medicine.

6. SIT-Q

Description: The SIT-Q was developed to assess habitual sedentary behaviour across a variety of domains. It is currently being used in a number of epidemiological studies, including the BETA Trial.

Available for download at the following link: Sit-Q

6.5 SI-Q 7 Day

Description: An expanded version of the SIT-Q using a 7-day reference frame.  The validation study is currently in press at Medicine and Science in Sports and Exercise (a link will be provided once the study is available online).

The questionnaire, as well as recommended scoring, cleaning and processing codes are all available on theMRC Epidemiology website.

7. The Sedentary Behaviour Questionnaire (SBQ)

Description (from the validation paper): “The SBQ was designed to assess the amount of time spent doing 9 behaviors (watching television, playing computer/video games, sitting while listening to music, sitting and talking on the phone, doing paperwork or office work, sitting and reading, playing a musical instrument, doing arts and crafts, sitting and driving/riding in a car, bus, or train). The 9 items were completed separately for weekdays and weekend days. Wording for weekday reporting was, “on a typical weekday, how much time do you spend (from when you wake up until you go to bed) doing the following?”

Results: “ICCs were acceptable for all items and the total scale (range = .51-.93). For men, there were significant relationships of SBQ items with IPAQ sitting time and BMI.

The questionnaire is available here, while the validation paper is available from the Journal of Physical Activity and Health.

8. The Adolescent Sedentary Activity Questionnaire (ASAQ)

Description: A questionnaire designed for use in adolescents, which provides information related to screen time, education (e.g. homework), travel, cultural (reading, crafts, etc) and social (relaxing with friends, going to church, etc) sedentary behaviours.  Has been shown to be valid, reliable, and sensitive to changes in sedentary time.

The full questionnaire and supporting documents are available on the ACAORN website.

9. Rapid Assessment Disuse Index (RADI)

Description:  A tool for rapidly quantifying and tracking the sedentary time and low levels of daily lifestyle physical activity among primary care patients.

Results of the validation study published in the British Journal of Sports Medicine:  ”RADI was temporally stable (intraclass correlation coefficients 0.79), and a higher score was significantly correlated with greater sedentary time (ρ=0.40; p<0.01), fewer sedentary to active transitions (ρ=-0.42; p<0.01), and less light-intensity physical activity (ρ=-0.40; p<0.01). The ability of RADI to detect patients with high levels of sedentary time was fair (AUC=0.72).”

Available via the British Journal of Sports Medicine.

10. Measure of Older Adults’ Sedentary Time (MOST)

Description: A questionnaire that assesses time spent in behaviors common among older adults: watching television, computer use, reading, socializing, transport and hobbies, and a summary measure (total sedentary time).

Results from a validation study: “Test-retest reliability was excellent for television viewing time (ρ (95% CI) = 0.78 (0.63-0.89)), computer use (ρ (95% CI) = 0.90 (0.83-0.94)), and reading (ρ (95% CI) = 0.77 (0.62-0.86)); acceptable for hobbies (ρ (95% CI) = 0.61 (0.39-0.76)); and poor for socializing and transport (ρ < 0.45). Total sedentary time had acceptable test-retest reliability (ρ (95% CI) = 0.52 (0.27-0.70)) and validity (ρ (95% CI) = 0.30 (0.02-0.54)). Self-report total sedentary time was similarly responsive to change (RS = 0.47) as accelerometer-derived sedentary time (RS = 0.39).

MOST questionnaire is available here.  Validation study available via Medicine and Science in Sports and Exercise, and an example of its use is available in PLOS ONE.

11.  Past-day Adults’ Sedentary Time (PAST)

Description: A 7-item questionnaire that asks questions about sedentary behaviours on the previous day.

Results from validation study, published in Medicine and Science in Sports and Exercise: “The PAST had fair to good test-retest reliability (intraclass correlation coefficient = 0.50, 95% confidence interval [CI] = 0.32-0.64). At baseline, the correlation between PAST and activPAL sit/lie time was r = 0.57 (95% CI = 0.39-0.71). The mean difference between PAST at baseline and retest was -25 min (5.2%), 95% limits of agreement = -5.9 to 5.0 h, and the activPAL sit/lie time was -9 min (1.8%), 95% limits of agreement = -4.9 to 4.6 h. The PAST showed small but significant responsiveness (-0.44, 95% CI = -0.92 to -0.04); responsiveness of activPAL sit/lie time was not significant.

PAST questionnaire available here, validation study available via MSSE.

12. LASA Sedentary Behavior Questionnaire

Description: A 10-item questionnaire that asks about weekday and weekend day sedentary behaviour.

Results from the validation study, published in BMC Geriatrics: “Mean total self-reported sedentary time was 10.4 (SD 3.5) h/d and was not significantly different from mean total objective sedentary time (10.2 (1.2) h/d, p = 0.63). Total self-reported sedentary time on an average day (sum often activities) correlated moderately (Spearman’s r = 0.35, p < 0.01) with total objective sedentary time. The correlation improved when using the sum of six activities (r = 0.46, p < 0.01), and was much higher than when using TV watching only (r = 0.22, p = 0.05). The test-retest reliability of the sum of six sedentary activities was 0.71 (95% CI 0.57-0.81).”

The questionnaire is available here, and the validation study is available here.

13. Occupational Sitting and Physical Activity Questionnaire (OSPAQ)

Description: A questionnaire that focuses on workplace sitting and physical activity.

Results from the validation study, published in MSSE“The test–retest intraclass correlation coefficients for occupational sitting, standing, and walking for OSPAQ ranged from 0.73 to 0.90, while that for the modified MOSPA-Q [a separate questionnaire] ranged from 0.54 to 0.89. Comparison of sitting measures with accelerometers showed higher Spearman correlations for the OSPAQ (r = 0.65) than for the modified MOSPA-Q (r = 0.52). Criterion validity correlations for occupational standing and walking measures were comparable for both instruments with accelerometers (standing:r = 0.49; walking:r = 0.27–0.29).”

The questionnaire is available here, and the validation study is available via MSSE.

Category: Sedentary Behaviour | Comments Off

Top 5 New Year’s resolution pitfalls and how to avoid them

new years resolution

“Good resolutions are useless attempts to interfere with scientific laws. Their origin is pure vanity. Their result is absolutely nil.”

-Lord Henry in The Picture of Dorian Gray by Oscar Wilde


Losing weight is the number one resolution people make each year. Getting more exercise or becoming “fit” is usually not far behind in popularity. Seeing as we’re approximately 2 weeks into the New Year, approximately 30% of people who resolved to change their lifestyle this year have already given up. In fact, only about 8% ever succeed in achieving their resolution.

At least some of this spectacularly high recidivism is the result of people setting goals in such a way as to almost guarantee failure, and end up exactly where they started (if not worse off).

Here are the top 5 New Year resolution pitfalls I regularly see people making. By avoiding these, you can increase your odds of being part of that elusive 8% when 2014 comes to an end.
Continue reading »

Category: News, nutrition, Physical Activity | 2 Comments

Participants Needed – Online Survey of Canadian Sport Coaches

Earlier this fall we introduced a new feature where we publicize studies looking for human participants.  Once each month, I will put up a post with short descriptions of studies requiring human subjects.

I have two basic requirements. To be included, a study must:

  1. Have received institutional ethics approval.
  2. Be related in some way to physical activity, sedentary behaviour, diet, or obesity.

Today I have a study from my colleague Kylie McNeill at the University of Ottawa.  The full details can be found below.  Kylie is looking for Canadian sport coaches to fill out her online survey (available here).  Coaches from other country’s are undoubtedly awesome, but this survey is focused on Canadian coaches.

If you happen to be a Canadian sport coach, please consider taking a moment to complete Kylie’s survey.  And if you know a Canadian sport coach, please pass the survey along to them.


Inline image 1Are you a coach of high-level youth athletes? If so, we need to hear from you!

We are researchers from the University of Ottawa and the Norwegian School of Sport Sciences conducting a study on coaches’ stress and well-being. If you coach youth athletes (aged 12-21 years old) competing at the regional, provincial, national and/or international level, and you are currently in-season, we need your help to better understand how coaches manage stressors by completing a brief online survey!

By investing 10-15 minutes of your time, you will assist us in better understanding how coaches can cope more effectively with the demands of their profession in order to ensure their own well-being. An added benefit from your participation may be an increased awareness of your own capacity to manage stressors in order to function optimally in a demanding environment.

To participate, please click the following link:

Know any other coaches? If so, please forward this email to them!

Please note that the survey is available only in English.

Thank you for your time and participation. Please contact us if you have any questions or concerns.


Kylie McNeill (PhD cand) kmcne023@uottawa.ca613-562-5800 ex. 4950

Natalie Durand-Bush (PhD) ndbush@uottawa.ca613-562-5800 ex. 4281

School of Human Kinetics, University of Ottawa, Ottawa, Canada

Pierre-Nicolas Lemyre (PhD) 23 26 24 22

Department of Coaching and Psychology, Norwegian School of Sport Sciences, Oslo, Norway

Category: Peer Reviewed Research | Tagged | Comments Off

We need NON-randomized lifestyle interventions

UPDATE: It has been pointed out in the comments that the real problem is not with randomization per se; the problem is with how we apply the randomization.  With this I completely agree.  On Twitter, Matt Hodgkinson has suggested another model known as a “patient preference trial” which would allow us to keep the benefits of randomization while also getting at some of the issues I bring up in the post. More details on patient preference trials can be found here.

This morning I read a post on the blog of Dr Arya Sharma that meshed very well with an idea that’s been ruminating in my head for quite a while (if you are interested in obesity and don’t read his blog, you are missing out).  In the post, Dr Sharma discussed the results of a new study comparing low carb and high protein diets.

From the post (emphasis mine):

Subjects were randomised to 12 months of a standard-protein diet (protien:fat:carbohydrate ratio 20:30:50 % of energy) and one where energy from carbohydrates was reduced and replaced by protein (30:30:40 % of energy).

Both groups lost a significant amount of weight over 12 months (6.6 Kg on the standard-protein diet, 9.7 Kg on the high-protein diet).

The diets had no impact on kidney function despite improvements in diabetes control.

Of note, only 45 of the 76 volunteers completed the study – a drop-out rate of over 40%

Overall, the study shows that differences in carb to protein ratios matter neither in terms of weight loss nor in their impact on kidney function.

Perhaps, even more importantly, the study shows that trying to keep people on diets – even in clinical trials – is challenging, with almost half the subjects abandoning their diet within 12 months.

As I have noted before, diets only work when you stick with them. Rather than obsessing about the exact composition of your diet, it may be best to chose the one you like best and can actually stay on.

To anyone who follows these things, Dr Sharma’s conclusion makes perfect sense.  And yet we keep doing randomized trials of different lifestyle interventions.  If anything, I think that randomized studies may actually be underselling the benefits of some lifestyle interventions.

Randomized controlled trials are the absolute gold standard when trying to determine the benefit of any sort of health intervention. By randomizing participants to different treatment groups, you are able to more clearly determine the physiological impact of the intervention. Randomized trials are extremely important, and they’ve given us a lot of tremendously useful information about various lifestyle interventions.  So why do I think we need to move away from randomized studies for some lifestyle interventions (at least with effectiveness studies, if not efficacy studies)?

As Dr Sharma notes, lifestyle interventions only work if you actually follow them. If followed, all the major diets lead to reductions in food intake, which will either lead to reduced weight gain or weight loss (assuming no changes in energy expenditure). The problem isn’t with the diets – it is with following the diets.

This is why I think that randomized controlled trials are underselling the benefits of diets and other lifestyle interventions. If you randomly allocate people to a cookie-cutter intervention, it’s not hard to see that the intervention might be wholly inappropriate for many of the participants (not medically, but in terms of being something which they can manage within their lifestyle).

So why not take the opposite approach? Recruit 200 people, and allocate them to 4 different lifestyle interventions. But instead of allocating them randomly, do some sort of survey or interview (including their entire family, if possible) to see which type of intervention is most likely to fit within their lifestyle.

I think there is already a general acceptance among practitioners (good ones at least) that interventions need to be made to fit the individual, and not the other way around. And I know that researchers often talk about the importance of sussing out factors related to adherence, or identifying responders vs non-responders. But I have yet to see the same logic applied to a large scale study. And I don’t know how journal editors would react to a proudly non-randomized study, as this seems anathema to unbiased research. But it seems like a more reasonable approach than forcing people into interventions that we know they aren’t going to follow for more than a few months.



Category: News, Obesity Research, Peer Reviewed Research | 17 Comments

Breaks in sedentary time associated with improved health in kids with family history of obesity

A couple weeks ago one of my thesis papers was published in the journal PLOS ONE, titled “Associations of Sedentary Behavior, Sedentary Bouts and Breaks in Sedentary Time with Cardiometabolic Risk in Children with a Family History of Obesity“.  It’s a cool study (in my humble opinion), getting a bit of media attention here in Canada, so I’ve been eager to share it here on the blog.

I’m trying something a bit different today by posting a short video blog above for those who would rather watch me explain the study rather than read it (email subscribers can view the video on the blog). Similarly, for those who are more visually inclined, below is a poster based on this study which I presented earlier this year at the Canadian Society for Exercise Physiology conference (hat tip to Zen Faulkes for the excellent poster advice  - click to enlarge).

csep posterThe rationale for this study was simple.  Generally, speaking sedentary behaviour (especially screen time) is bad for kids’ health (details here).  But in adults, we know that it’s not just total sedentary time that matters, but also patterns in sedentary time.  

An example of what I mean can be seen in the above figure, which shows two individuals with the same amount of total sedentary time.  However, the person on the left gets most of their sedentary time in prolonged bouts. In other words, when they sit down, they tend to stay sitting for a long time before getting up again.  In contrast, the person on the right rarely sits for more than a few minutes at a time without getting up and moving around; they frequently “interrupt” their sedentary time. A wealth of research (both cross-sectional and experimental) suggests that the person on the left (the prolonger) will be at increased health risk compared to the person on right (the breaker)… if they are adults.

In kids, the situation isn’t so clear.  Studies by my colleagues Rachel Colley and Val Carson have failed to detect any association between breaks in sedentary time and markers of health in large groups of Canadian and American kids.  But those studies looked at kids in the general population.  And generally speaking, kids are pretty healthy.  As a result, it’s sometimes hard to detect significant associations in kids, because they are just too healthy to begin with. The unique thing about the participants in the present study is that they come from the QUALITY cohort.  To be included in this cohort, a child has to have at least one parent with obesity.  As I’ve written recently, this means that these kids are also at increased risk of obesity, as well as related health issues.  So we thought that it might be worth investigating the relationship between breaks in sedentary time and health in this group of kids, since it might be easier to detect than in the general population.

What did we do?

We measured physical activity and sedentary behaviour patterns in all participants for one week, using an Actical accelerometer.  Kids were also asked how much time they spend watching TV, and the amount of time they spend using a computer and playing video games.  We measured a range of individual health risk factors (BMI, waist circumference, insulin, glucose, cholesterol, blood pressure, etc).  Finally, created a global health risk for each participant, based on their values for each of the individual risk factors.

What did we find?

Irrespective of the total time spent sitting or being physically active, the more frequent the breaks in sedentary time, the lower the global health risk.  In other words, frequent breaks from sedentary behaviour seem like a good thing for kids in this cohort. Just to be clear though, this study did not show that increased breaks in sedentary time  led to improved health for these kids.  We only looked at one time point, so we can’t really say that frequent breaks in sedentary time caused kids to have a better health profile.  It’s plausible that being unhealthy led to sitting for more prolonged periods, just like it’s plausible that breaks in sedentary time were good for health.  For now we can’t tell which is the chicken, and which is the egg.

Of relevance to this last point, another one of my thesis papers (published in Metabolism, and available for free download here) actually looked at the health impact of making kids sit for prolonged periods, with and without breaks.  Interestingly, we found no relationship between breaks in sedentary time and health in a group of healthy children.  But that study was looking only at the immediate health-impact of sitting, whereas the current design gets at more of the long-term relationship between breaks and health.  But my point is that this study, like any individual study, should not be considered the definitive answer on breaks in sedentary time and pediatric health.   This study could be a wonky outlier, or it may be the first of many showing this association in kids with elevated health risk.  It’s still interesting and useful, just don’t bet your house that this same relationship will be identical in the next study to come along.  This is why replication studies, although boring and unsexy, are incredibly important in terms of actually understanding the behaviours that influence health.

What else did we find?

Our other interesting (but in no way surprising) finding was that screen time was strongly associated with global health risk in both boys and girls.  In boys it was video games/computer use that were most strongly associated with health risk, while for girls it was TV viewing.  Why the difference?  It probably just comes down to the fact that the boys watched a lot more TV than girls in the cohort.  Either way, screen time is consistently bad for kids, and this is just one more study to add to the pile.

What is the take-home message?

All else being equal, kids with more frequent breaks in their sedentary time were healthier than those with less frequent breaks.

All else being equal, kids with more frequent breaks in their sedentary time were healthier than those with less frequent breaks.

In this group of kids, frequent breaks from sitting were associated with lower risk factors for chronic disease.  We can’t be certain that the breaks caused health to improve, but it’s definitely plausible, especially based on other studies in adults.  At the very least, getting kids to break up their sedentary time is unlikely to have any negative health impacts.  And if you can get your kids to reduce their screen time, it will almost certainly be beneficial to their health.


Category: Obesity Research, Peer Reviewed Research, Sedentary Behaviour | Comments Off

Participant’s Needed – An Online Survey

Earlier this fall we introduced a new feature where we publicize studies looking for human participants.  Once each month, I will put up a post with short descriptions of studies requiring human subjects.

I have two basic requirements. To be included, a study must:

  1. Have received institutional ethics approval.
  2. Be related in some way to physical activity, sedentary behaviour, diet, or obesity.

If I feel a study is inappropriate for some reason, then I won’t post it. But otherwise I’m happy to promote studies in any geographic location, and on any specific population. Research can’t happen without participants, and I’m happy to help people find out about studies that might be of interest to them.  If you have a study you’d like featured on Obesity Panacea, email me at saunders (dot) travis (at) gmail.

This month we have a study from The Chronic Disease Systems Modeling lab at Simon Fraser University.  This study is an online survey, so you can participate from anywhere!  I did the survey this morning and it took less than 10 minutes.  You can find the survey and the full supporting info here.  I’ve posted a brief description of the study below.  If you have a few minutes at lunch today, please take a moment to contribute to this new study!

The Chronic Disease Systems Modeling Laboratory at Simon Fraser University is seeking volunteers (must be 19 or older) to participate in a research study to learn about individuals’ perceptions of factors that influence body weight and how individuals differ in their perceptions.

Participation involves completing an online survey, taking approximately 20 minutes.  Questions ask about demographics, personality traits, and factors related to weight management. Participation is completely anonymous: there is no need to provide personal data such as name, address, or phone number.

Background and Rationale

Obesity is a complex problem impacted by many psychological, physiological and sociological drivers. We want to learn about individuals’ perceptions of factors that influence body weight and how individuals differ in their perceptions.

Principal Investigator

Dr. Diane Finegood, Ph.D. Professor
Department of Biomedical Physiology and Kinesiology
Chronic Disease Systems Modeling Lab
Simon Fraser University
Telephone: 604-714-2771






Category: Miscellaneous, News | Tagged | 3 Comments