Reliability and Validity of a Computerized and Dutch Version of the International Physical Activity Questionnaire (IPAQ)

Journal of Physical Activity and Health, 2005, 2, 63-75 2005 Human Kinetics Publishers, Inc. Reliability and Validity of a Computerized and Dutch Version of the International Physical Activity Questionnaire (IPAQ) Corneel Vandelanotte, Ilse De Bourdeaudhuij, Renaat Philippaerts, Michael Sjöström, and James Sallis Background: The purpose of this study was to examine the reliability and validity of a newly developed computerized Dutch version of the International Physical Activity Questionnaire (IPAQ). Methods: Subjects (N = 53) completed the computerized IPAQ at three specified times. Subjects wore a CSA activity monitor during seven full days and simultaneously completed a 7-d physical activity diary. Finally, respondents filled out a paper and pencil IPAQ. Results: Intraclass correlation coefficient ranged from 0.60 to 0.83. Correlations for total physical activity between the computerized IPAQ and the CSA activity counts were moderate (min: r = 0.38; kcal: r = 0.43). Correlations with the physical activity diary were also moderate (min: r = 0.39; kcal: r = 0.46). Correlations between the computerized and the paper and pencil IPAQ were high (min: r = 0.80; kcal: r = 0.84). Conclusions: The computerized Dutch IPAQ is a reliable and reasonably valid physical activity measurement tool for the general adult population. Key Words: computer, accelerometer, diary, self-report, measurement Self-administered questionnaires are a popular method of assessing physical activity. They can reach large populations at low cost, they do not alter the behavior under study, they can reach a wide range of ages and target groups, and they can assess all the dimensions of physical activity. 1 Computerized assessment can further increase these advantages. Rapid development of information technology makes this new form of questionnaire administration possible. Computerized assessment has time-saving potential because data can be automatically stored on Vandelanotte, De Bourdeaudhuij, and Philippaerts are with the Dept of Movement and Sport Sciences, Faculty of Medicine and Health Sciences, Ghent University, 9000 Ghent, Belgium. Sjöström is with the Unit for Preventive Nutrition at Novum, Dept of Biosciences, Karolinska Institute, 141 57 Huddinge, Sweden. Sallis is with the Dept of Psychology, San Diego State University, San Diego, CA 92103. 63

64 Vandelanotte et al. file, reducing hours of data entry and the risk of lost data. 2,3 A major advantage of computerized questionnaires, in comparison to hard copy questionnaires, is that they can be programmed to eliminate missing data, forcing subjects to answer all questions. 2 Complex skip-patterns can be used to help subjects and to avoid superfluous questions. 3 Internet-mediated assessment enables researchers to reach large populations quickly 2 and might even be more effective in reaching certain target populations who might not otherwise be interested in the assessment of physical activity. 4 Despite the advantages of computerized assessment, self-reporting still has several drawbacks. Many subjects have difficulty estimating the intensity in which they engage in activities. 5 This type of inaccurate perception, 5 together with recall errors 6 and social desirability bias 1 can lead to overreporting of physical activity. 1,6 Physical activity questionnaires could be less accurate in assessing light to moderate activities compared to high intensity activities. 5,7,8 Further, physical activity is a complex behavior with considerable day-to-day variation, which self-assessment questionnaires can not reflect. 6 These drawbacks stress the importance of assessing the validity and reliability of newly developed questionnaires in the population for which they will be used. Motion sensors, and in particular the Computer Science and Applications, Inc. (CSA) 9 accelerometer, have been proven to give a valid and objective measure of physical activity. 10-13 Because of their small size, unobtrusive nature, and ease of use, 14,15 their ability to store data over long periods, 7,14 and their ability to provide objective estimates of the frequency, intensity, and duration of physical activity, 7,16 they can be used as a good reference method to assess validity of physical activity questionnaires. 8 Another approach, often used in validating physical activity recalls, is the use of a diary, in which subjects continuously record their activities over several days. 5,17,18 It is argued that international comparisons of physical activity are valuable and might only be feasible using self-assessed questionnaires. 19 Such comparisons, however, are largely impossible because numerous and often incomparable operalizations of physical activity are being used. The International Consensus Group for Physical Activity Measurement realized the need for the development of an international standardized assessment technique, and developed the International Physical Activity Questionnaire (IPAQ). 19,20 The purpose of the IPAQ is to provide a common instrument that can be used internationally to obtain physical activity surveillance data. A test of the IPAQ s international reliability and validity has been done, and the results were acceptable. 20 The IPAQ produced repeatable data (Spearman s ρ clustered around 0.8) and criterion validity had a median ρ of about 0.3, which was comparable to most other self-report validation studies. A European study, 21,22 however, was less positive about the IPAQ, however, and indicated that more research is needed to further investigate and improve the quality of the IPAQ for use in Europe. The purpose of this study was to examine the reliability and validity of a newly developed computerized Dutch version of the IPAQ in a sample of adults, using CSA accelerometers and 7-d physical activity diaries. Further, it sought to examine the comparability of computerized and paper and pencil formats of the IPAQ.

IPAQ Reliability and Validity 65 Subjects Method Subjects, ranging in age from 25 to 55 y, were recruited in and around the Belgian city of Ghent. Sixty-three subjects volunteered for this study, of which 5 dropped out during data gathering because of time constraints and lack of motivation. Overall, our sample had a high level of education (88.5%), most had a job (72.1%), of which most had a white-collar job (93.3%). The majority (55.8%) of our subjects lived in a large city or in a rural city (37.7%); 50.8% lived with a partner, 18% lived alone, and 31.1% were still living with their parents. Three subjects had very high physical activity measures (mean + 3 standard deviation) and were defined as outliers. One was excluded because of insufficient CSA data: days with less than 600 min of registration were removed and all data were removed if less than 5 d were registered. One subject was excluded because of technical problems concerning the computerized questionnaire, leaving 53 subjects that complied with all requirements. Table 1 presents an overview of their descriptive data and physical activity measures. After procedures were explained, each subject signed an informed consent statement approved by the Ghent University Ethics Committee. Study Protocol The same protocol as outlined in the IPAQ reliability, validity, and prevalence studies manual of operation (version 8, March 3, 2000; University of South Carolina) was used in this study. The data collection comprised 3 contacts with subjects, called contact 1, 2, and 3. Contacts were at the university or subjects homes (a portable computer was provided by the research team). A member of the research team was present during all 3 contacts, regardless of location. At contact 1 (day 0), the protocol was outlined, the informed consent signed, and the subjects tracking form obtained. An appointment form was used to ensure that subjects would be present at contacts 2 and 3. Subjects weight and height were measured. Next, a computerized demographics form and computerized IPAQ were administered and subjects were familiarized with the CSA accelerometer. To ensure 7 full days of recording, they were instructed to wear the CSA from then on until contact 2. The CSAs were programmed to start recording at 07:00 the day after contact 1 (at day 1). Subjects were also given a form on which to record each activity performed without wearing the CSA (e.g. swimming, showering) and were given a CSA instruction form to ensure correct use. Finally, subjects were asked to complete a 7-d physical activity diary during the CSA recording period, also starting at day 1. Contact 2 was a week after contact 1, at day 8. Subjects turned in the CSAs, the recording form, and the physical activity diary. CSA data were downloaded and stored immediately. Next, the computerized IPAQ was administered again. Contact 3 was more than 3 d after contact 2 (at day 11, 12, 13, or 14). For their convenience, subjects could choose between the 4 d. Again, subjects completed the computerized IPAQ. Subjects who complied with the study protocol were rewarded with 4 movie theater tickets.

66 Vandelanotte et al. Table 1 Means and Standard Deviations for Participants Age, Height, Weight, Body Mass Index, Total Physical Activity (Low + Moderate + High Intensity Physical Activity), High Intensity Physical Activity, and Moderate Intensity Physical Activity Total sample Men Women (N = 53) (n = 23) (n = 30) Characteristic Mean SD Mean SD Mean SD Age (y) 30.9 11.0 31.2 11.4 30.7 10.9 height (m) 1.73 0.01 1.82 0.08 1.67 0.06 weight (kg) 68.9 13.1 80.2 11.5 60.2 5.3 body mass index (kg/m 2 ) 22.8 2.9 24.1 2.8 21.6 2.5 Computerized IPAQ (min/wk) Contact 1 total PA (min) 552.6 437.3 589.6 433.2 524.3 445.6 high-intensity PA (min) 149.8 197.7 207.4 226.8 105.6 162.6 moderate-intensity PA (min) 200.9 272.6 253.0 380.8 161.0 139.6 Contact 2 total PA (min) 506.8 365.1 589.1 424.8 443.6 304.5 high-intensity PA (min) 137.4 191.6 203.0 232.6 87.0 136.9 moderate-intensity PA (min) 172.3 196.9 206.1 257.5 146.3 132.8 Contact 3 total PA (min) 527.9 383.8 561.8 419.1 503.0 360.9 high-intensity PA (min) 125.6 162.3 152.3 170.4 106.0 156.2 moderate-intensity PA (min) 206.3 263.7 218.2 323.7 197.6 215.0 Paper and pencil IPAQ (min/wk) total PA (min) 539.1 389.9 593.5 422.5 497.4 364.7 high-intensity PA (min) 136.8 204.0 206.5 259.0 83.3 129.9 moderate-intensity PA (min) 202.8 218.9 225.6 242.7 185.3 201.8 7-d diary last wk activity (min/wk) total PA (min) 1736.9 591.0 1499.2 509.2 1919.3 591.9 high-intensity PA (min) 108.1 155.6 141.7 176.0 82.3 135.4 moderate-intensity PA (min) 338.8 356.8 276.6 302.1 386.6 391.9 CSA last wk activity (min/wk) total PA (min) 4690.3 790.6 4608.6 871.8 4757.4 726.4 high-intensity PA (min) 33.8 41.3 50.3 48.2 20.3 29.0 moderate-intensity PA (min) 286.4 165.9 368.0 169.8 219.2 130.8 Note. SD, standard deviation; PA = physical activity.

IPAQ Reliability and Validity 67 Subjects completed a paper and pencil IPAQ 3 d after contact 3. The paper and pencil questionnaire was given at contact 3 and subjects were instructed to wait exactly 3 d before completing it and to immediately send it back to the research team in the postage-paid envelope provided. Instruments Computerized IPAQ. The computerized IPAQ used in this study was entirely based on the long, self-administered, usual week-long IPAQ found in the IPAQ manual of operation. The questionnaire consists of 5 categories: job-related physical activity (vigorous, moderate, and walking), transportation physical activity (motor vehicle, cycling, and walking), housework, house maintenance, and caring for family (vigorous and moderate in garden, moderate inside home), recreation, sport, and leisure-time physical activity (vigorous, moderate, and walking) and time spent sitting (week day or weekend day). For each topic in each category, subjects reported the number of days per week and the time per day they usually spent doing the activity. For walking and cycling an additional question on pace was added. To be reported, an activity should have lasted for at least 10 min continuously. A Dutch translation was made by two independent translators according to the translate and back-translate protocol. Next, this Dutch version was computerized, with no alteration of the original item sequence. Each computer page contained only one question and skip patterns were used to eliminate questions that did not need to be answered. All questions had to be answered before the subjects could proceed. Energy expenditure in kilocalories (kcal) was calculated using a MET (multiples of resting metabolic rate) value for each activity category on the questionnaire and the subject s body weight. The use of MET values also allowed the calculation of time spent in different categories of physical activity: low intensity physical activity (< 3.00 METs), moderate intensity physical activity (3.00 to 5.99 METs), vigorous intensity physical activity (> 6.00 METs). These MET values were based on the physical activity compendium by Ainsworth et al. 23, 24 and equal to those reported by Craig et al. 20 Paper and Pencil IPAQ. The paper and pencil IPAQ used in this study was a Dutch version of the long, self-administered, 7-d IPAQ. The translation process was identical to that described above. This questionnaire was used as a reference measure to assess the comparability of the computerized IPAQ. The same MET categorization was used as with the computerized IPAQ. A 12-country reliability and validity study showed that the IPAQ is able to produce repeatable data. 20 Test retest reliability for the long IPAQ questionnaires showed Spearman correlation coefficients ranging from 0.96 to 0.46, but most were in the area of 0.80, indicating very good repeatability. Criterion validity of the self-report IPAQ data against CSA accelerometers showed a fair to moderate agreement between the two measures. The pooled Spearman correlation coefficient for the long IPAQ questionnaire was 0.33, comparable to most other self-report validation studies. A European study 21,22 was less positive about the IPAQ, with test retest correlation coefficients that ranged between 0.30 and 0.50, which appears to be rather low for a reliability test. This indicates that more research is needed to further investigate and improve the quality of the IPAQ for use in Europe.

68 Vandelanotte et al. CSA Accelerometer. The Computer Science and Applications, Inc. model 7164 9 accelerometer was used as an objective reference method. It is a uniaxial accelerometer that measures acceleration/deceleration in the vertical direction and is designed to detect acceleration ranging in magnitude from 0.05 to 2.0 G with a frequency response between 0.25 and 2.5 Hz. These frequencies were chosen to detect normal body movement and to filter out high frequency movement, such as might occur while riding in a car. 9 The CSA is small (5 4 1.5 cm), light, (43 g) and unobtrusive to wear. Activity counts, resulting from a piezo-electric bender element, are summed over a user-defined sampling period (epoch). At the end of each epoch the activity counts are stored and the accumulator resets to zero. For the present study a 1 min epoch was used. At the end of the 7-d recording period, stored data were downloaded to a desktop computer, and then converted into a Microsoft Excel file for subsequent analysis. A complete technical description of the CSA has been published. 25 Monitors were worn just above the right hipbone and firmly held in place by an elastic belt. Subjects were requested to wear the CSA during waking hours, removing the monitor only for water-based activities and sleeping. Physical Activity Diary. A 7-d physical activity diary was another reference method used to assess the validity of the computerized IPAQ. It was designed for this study and was similar to other commonly used physical activity diaries. 5 Together with an instruction form, subjects were given seven physical activity monitoring forms (one for each day). For each hour, subjects documented the amount of time spent within the same five categories found on the computerized IPAQ (see above); only sleeping was added as a sixth category. For each activity registered on the diary, subjects recorded the following information: a letter indicating the physical activity category (e.g., T for transportation), a short description of the activity, a subjective estimate of the intensity of the activity (light, moderate, or hard), and the duration of the activity in minutes. Similar to the computerized IPAQ, subjects were asked to only register activities that lasted for at least 10 min. To calculate energy expenditure in kcal, MET values were based on the physical activity compendium by Ainsworth et al., 23,24 and subjects body weight. The same MET categorization was used as with the computerized IPAQ. Data Reduction The CSA data were reduced with custom software. Minute-by-minute activity counts were summed for each day, and daily activity counts were summed into total weekly activity counts. Total weekly activity counts of subjects missing 1 or 2 d of CSA registration were converted to 7 d to ensure that CSA activity counts of all subjects were comparable. Total weekly activity counts were also calculated for intensity categories, namely: low, moderate, and high intensity physical activity, moderate and high intensity physical activity together, and total physical activity. This separation into categories was done using cut off scores published by Freedson et al. 10 : less than 1952 CSA counts per min is light physical activity (< 3.00 METs), between 1952 and 5724 counts is moderate physical activity (3.00 to 5.99 METs), between 5725 and 9498 counts is hard physical activity (6.00 to 8.99 METs) and more than 9498 counts is very hard physical activity (> 8.99 METs).

IPAQ Reliability and Validity 69 This subdivision into categories also allowed the calculation of time spent in each category. Activity counts in the different categories were directly used to analyze validity, because it has been suggested that a conversion of CSA activity counts into energy expenditure could produce significant error. 10 Statistics All analyses were performed using SPSS version 10.0 (SPSS, Inc., Chicago, IL). Test-retest reliability coefficients were determined using single measure intraclass correlation coefficients (ICC) computed between the computerized IPAQ administration at contacts 1, 2, and 3 together. For validity, Spearman rank-order correlation coefficients were computed to compare the computerized IPAQ administered at contact 2 with CSA activity counts, the 7-d physical activity diary and paper and pencil IPAQ. Spearman correlation coefficients were chosen because self-reported physical activity data were not normally distributed. All reported correlations are between corresponding physical activity categories, e.g., CSA high-intensity physical activity was correlated with computerized IPAQ high-intensity physical activity, diary job-related physical activity was correlated with computerized IPAQ job-related physical activity, and so on. Paired sample t-tests were used to determine if there were differences between the computerized IPAQ at contact 2 with the paper and pencil IPAQ, the physical activity diary, and the CSA minutes. Statistical significance was set at an alpha level of 0.05. Reliability Results Single measure ICCs, expressed in minutes of physical activity (min) or in kilocalories energy expenditure (kcal), for the three computerized IPAQ administrations are shown in Table 2. These correlations ranged from ICC = 0.60 to 0.83. The ICC for total PA was 0.69 when expressed in minutes and kilocalories. Highest ICCs were for high intensity (min: ICC = 0.81, kcal: ICC = 0.82), job-related (min: ICC = 0.83, kcal: ICC = 0.80), and leisure-time (min: ICC = 0.82, kcal: ICC = 0.81) physical activity. Lowest ICCs were for moderate intensity (min: ICC = 0.62, kcal: ICC = 0.63) and transportation (min: ICC = 0.60, kcal: ICC = 0.60) physical activity. Validity Spearman correlation coefficients between the computerized IPAQ at contact 2 and CSA measures are shown in Table 3. The correlation for total physical activity was 0.38 (P < 0.01) when expressed in minutes and 0.43 (P < 0.01) when expressed in kilocalories. The highest correlations were found for high-intensity physical activity (min: r = 0.42, P < 0.01; kcal: r = 0.45, P < 0.01). Nonsignificant correlations were found for low (min: r = 0.01, kcal: r = 0.01) and moderate (min: r = 0.13, kcal: r = 0.19) intensity physical activity. Also shown in Table 3 are the correlations between the computerized IPAQ and the 7 d physical activity diary. These correlations were similar to CSA activity count correlations. For total physical activity, a correlation of 0.39 (P < 0.01)

70 Vandelanotte et al. Table 2 Single Measure Intraclass Correlations (ICC) for the Computerized IPAQ Administered at Contacts 1, 2, and 3 ICC in minutes ICC in energy expenditure (kcal) Total PA 0.69 0.69 High + moderate PA 0.66 0.69 High-intensity PA 0.81 0.82 Moderate-intensity PA 0.62 0.63 Low-intensity PA 0.73 0.76 Job-related PA 0.83 0.80 Transportation PA 0.60 0.60 Household PA 0.74 0.71 Leisure-time PA 0.82 0.81 Note. PA, physical activity. Table 3 Spearman Correlations Between the Computerized IPAQ at Contact 2 and CSA Activity Counts, the 7-Day Physical Activity Diary and the Paper and Pencil IPAQ CSA Physical Paper and activity activity pencil counts diary IPAQ min kcal min kcal min kcal Total PA 0.38** 0.43** 0.39** 0.46** 0.80** 0.84** High + moderate PA 0.37** 0.42** 0.45** 0.46** 0.80** 0.86** High-intensity PA 0.42** 0.45** 0.79** 0.79** 0.87** 0.93** Moderate-intensity PA 0.13 0.19 0.32* 0.23 0.77** 0.78** Low-intensity PA 0.01 0.01 0.21 0.15 0.86** 0.84** Job-related PA 0.22 0.23 0.85** 0.85** Transportation PA 0.50** 0.52** 0.80** 0.84** Household PA 0.42** 0.53** 0.88** 0.87** Leisure-time PA 0.63** 0.67** 0.93** 0.95** Note. PA, physical activity; *P < 0.05; **P < 0.01

IPAQ Reliability and Validity 71 when expressed in minutes and 0.46 (P < 0.01) when expressed in kilocalories was found. Again, nonsignificant correlations were found for low intensity (min: r = 0.21, ns; kcal: r = 0.15, ns) and moderate intensity (kcal: r = 0.23, ns) physical activity. The highest correlations were for high intensity (min: r = 0.79, P < 0.01; kcal: r = 0.79, P < 0.01) and leisure-time (min: r = 0.63, P < 0.01; kcal: r = 0.67, P < 0.01) physical activity. High correlations were found between the computerized IPAQ and the paper and pencil IPAQ (Table 3), ranging from r = 0.77 to r = 0.95 (P < 0.01). Highest correlations were found for leisure-time physical activity (min: r = 0.93, P < 0.01; kcal: r = 0.95, P < 0.01). Paired samples t-test showed no significant differences between total physical activity on the computerized IPAQ [t(52) = 0.78, ns] and total physical activity on the paper and pencil IPAQ. No significant difference was found between moderate + high intensity physical activity on the computerized IPAQ and moderate + high intensity physical activity on the physical activity diary [t(52) = 1.42, ns]. This was also the case when moderate + high intensity physical activity computerized IPAQ was compared to moderate + high intensity physical activity in min on the CSA [t(52) = 0.61, ns]. Discussion This study examined the reliability and validity of a newly developed Dutch computerized IPAQ. When measuring the test retest reliability of a questionnaire, intraclass correlation coefficients (ICC) from 0.75 or higher are considered good to very good. 3 In this study the ICC reliability measures ranged from 0.60 to 0.83, thus showing a moderate to high reliability for the computerized IPAQ. Reliability of the total physical activity was 0.69. The reliability of high intensity and leisuretime physical activity (ICC from 0.81 to 0.82) was better than the reliability of moderate intensity physical activity (ICC from 0.62 to 0.63). This is probably caused by the more unstable nature of moderate intensity physical activity resulting in a recall bias as compared to high intensity or leisure-time physical activity which is more structured. 5,17 The reliability values found in this study are comparable with those found in the study from Craig et al., 20 which found values ranging from 0.96 to 0.46, but most were around 0.80. In a review 1 containing reliability results for 7 self-report physical activity measures, values ranged from 0.34 to 0.89. Correlations between computerized IPAQ and CSA activity (min: r = 0.38, kcal: r = 0.43) supported the validity of the IPAQ. These correlations are at least as good as other self-report physical activity measures evaluated in adults, 26,27 and are also comparable with the international IPAQ validity study, which found a correlation of about 0.33 for the long IPAQ version. 20 In a review containing the validation results for 7 self-report physical activity measures, Sallis and Saelens 1 reported validity correlations ranging from 0.14 to 0.53, with a median of about 0.30. Nevertheless, most of our correlations were moderate and several reasons might explain this. First, the computerized IPAQ hardly measures low-intensity physical activity, yet a large portion of the day is typically spent in sedentary or light activity, and thus a large part of the CSA activity counts represent physical activity at low

72 Vandelanotte et al. intensity. Second, several authors state that it is very difficult to obtain a good measure of low and moderate physical activity using self-administered questionnaires. 5,17 These activities are being accumulated throughout the day and the number and diversity of these activities is large, resulting in very poor recall. These authors further state that high intensity physical activities, being more structured and stable over time, are much more easily recalled. The higher correlations, in this study, for high intensity and leisure-time physical activity compared to low and moderate intensity physical activity illustrate this point. Third, it has been reported that subjects tend to overreport the time spent in high-intensity physical activity and underreport the time spent in light activity. 1,13 CSA accelerometers are known to do the opposite: they underreport high intensity physical activities and overreport low intensity physical activities. 13 Fourth, the computerized IPAQ version used in this study measured usual week physical activity whereas the CSA measured last week s physical activity. When the computerized IPAQ at contact 2 was compared to the 7 d physical activity diary higher correlations were found. The correlations for total physical activity (min: r = 0.39, kcal: r = 0.46) supported the validity of the IPAQ. Leisuretime and high intensity physical activity in particular correlated very well with the physical activity diary. Further, it was found that the total week (minutes) physical activity recorded using the physical activity diary was more than 3 times higher as compared to total week physical activity recorded using the computerized IPAQ. A similar pattern was observed with the CSA total minutes of activity, with CSA total activity minutes being much higher than those reported on the computerized IPAQ. The discrepancy was caused by the overrepresentation of lowintensity physical activity on the diary and the CSA. This overrepresentation of low-intensity physical activity was also observed by other researchers. 28 When the low-intensity physical activity minutes were removed from all measures, similar physical activity values were obtained. Given that the aim of the computerized IPAQ is to measure moderate- to high-intensity physical activity, it could be argued that the validity of the computerized IPAQ is expressed more accurately by omitting low-intensity physical activity from the correlations. As with the CSA, the diary measured the last 7 d physical activity whereas the IPAQ measured usual physical activity, possibly influencing the correlations negatively. Finally, the slightly higher correlations obtained by the physical activity diary as compared to the CSA activity counts are probably the result of shared method variance because the IPAQ and diary were both self-reports. 29 The correlations between the computerized IPAQ and the paper and pencil IPAQ were all very high, and there were no significant differences in means. These results demonstrate that the computerized IPAQ is generally equivalent to the hard copy IPAQ. Taking into account the advantages of computerized questionnaires, mentioned earlier, the computerized version might be preferable. Computerized assessment, however, has also some drawbacks. Paper and pencil questionnaires allow subjects to see how many items there are and pace themselves accordingly; to skip around, rather than answering the questions in sequence; they can also go back easily to earlier questions, to change them or check for consistency. 3 Further, a selection bias is possible given that not everyone can handle a computer or is willing to do so. Moreover, Internet-mediated assessments can further increase this selection bias as large parts of the population do not have access to the Internet.

IPAQ Reliability and Validity 73 Computerized questionnaires, however, like the one in this study, can be developed so that they are simple and well explained. Studies have also found that most people are comfortable in front of a computer. 3 Despite these drawbacks, we believe computerized assessment of physical activity has the potential to become a very important assessment technique in the future. Considering the minutes spent in total usual week physical activity, compared to CSA data, it appears that the computerized IPAQ overestimates the amount of high-intensity physical activity while underestimating moderate intensity physical activity. This complex pattern has been seen in several previous studies. 1 A limitation of this study is that this overestimation can be neither confirmed nor refuted because there are known limitations to using accelerometers as validity criteria. 6 Another limitation might be the small sample size, which makes it difficult to generalize these results to larger populations. Further, most subjects had a high education and white-collar jobs, which makes it difficult to generalize the results to individuals with a lower level of education or a lower level of socioeconomic status. A strength of this study is that it is one of the first to examine the reliability and validity of a computerized physical activity questionnaire. It is particularly valuable to evaluate a computerized version of the international physical activity questionnaire because present results suggest researchers from other countries can develop equivalent versions of hard copy and computerized IPAQ surveys. Finally, it is interesting to note that the correlations between the physical activity diary and the computerized IPAQ at contact 1 are very similar, but slightly higher compared to the reported values of contact 2 as shown in Table 3. In summary, our results indicate that the computerized IPAQ is a reliable and reasonably valid physical activity measurement tool for the adult population. Additional research should be conducted to determine the reliability and validity of computerized IPAQs in other languages and to determine population subgroups for whom the computerized version might not be appropriate. Acknowledgments This study was supported by Ghent University and the Flemish Fund for Scientific Research. The authors thank Maastricht University for supplying the software used for computerizing the IPAQ questionnaire, the IPAQ Reliability and Validity Committee for providing the IPAQ Manual of Operation for Reliability, Validity, and Prevalence Studies (version 8, March 3, 2000; University of South Carolina), the Centers for Disease Control and Prevention in Atlanta, GA for the loan of 20 CSAs, and the Karolinska Institute in Stockholm for the use of their CSA data-reduction software. References 1. Sallis JF, Saelens BE. Assessment of physical activity by self-report: status, limitations, and future directions. Res Q Exerc Sport. 2000;71:S1-14. 2. Ridley K, Doliman J, Olds T. Development and validation of a computer delivered physical activity questionnaire (CDPAQ) for children. Ped Exerc Sci. 2001;13:35-46. 3. Steiner DL, Norman GR. Health Measurement Scales: a practical guide to their development and use. 2nd. ed. Oxford: Oxford University Press, 1995.

74 Vandelanotte et al. 4. Fotheringham MJ, Wonnacott RL, Owen N. Computer use and physical inactivity in young adults: public health perils and potentials of new information technologies. Ann Behav Med. 2000;22:269-275. 5. Montoye HJ, Kemper HCG, Saris WHM, Washburn RA. Measuring physical activity and energy expenditure. Champaign, IL: Human Kinetics, 1996. 6. Freedson PS, Miller K. Objective monitoring of physical activity using motion sensors and heart rate. Res Q Exerc Sport. 2000; 71:S21-S29. 7. Bassett DR Jr., Ainsworth BE, Swartz AM, Strath SJ, O Brien WL, King GA. Validity of four motion sensors in measuring moderate intensity physical activity. Med Sci Sports Exerc. 2000;32:S471-S480. 8. Bassett DR Jr. Validity and reliability issues in objective monitoring of physical activity. Res Q Exerc Sport. 2000;71:S30-S36. 9. Computer Science and Applications, Inc. Activity Monitor Operator s Manual, Model 7164. Shalimar, FL: Computer Science and Applications, 1997. 10. Freedson PS, Melanson E, Sirard J. Calibration of the Computer Science and Applications, Inc. accelerometer. Med Sci Sports Exerc. 1998;30:777-781. 11. Melanson EL Jr., Freedson PS. Validity of the Computer Science and Applications, Inc. (CSA) activity monitor. Med Sci Sports Exerc. 1995;27:934-940. 12. Nichols JF, Morgan CG, Chabot LE, Sallis JF, Calfas KJ. Assessment of physical activity with the Computer Science and Applications, Inc., accelerometer: laboratory versus field validation. Res Q Exerc Sport. 2000;71:36-43. 13. Sirard JR, Melanson EL, Li L, Freedson PS. Field evaluation of the Computer Science and Applications, Inc. physical activity monitor. Med Sci Sports Exerc. 2000;32: 695-700. 14. Hendelman D, Miller K, Baggett C, Debold E, Freedson P. Validity of accelerometry for the assessment of moderate intensity physical activity in the field. Med Sci Sports Exerc. 2000;32:S442-S449. 15. Welk GJ, Blair SN, Wood K, Jones S, Thompson RW. A comparative evaluation of three accelerometry-based physical activity monitors. Med Sci Sports Exerc. 2000;32: S489-S497. 16. Cooper AR, Page A, Fox KR, Misson J. Physical activity patterns in normal, overweight and obese individuals using minute-by-minute accelerometry. Eur J Clin Nutr. 2000;54:887-894. 17. Washburn RA, Heath GW, Jackson AW. Reliability and validity issues concerning largescale surveillance of physical activity. Res Q Exerc Sport. 2000;71:S104-S113. 18. Ainsworth BE, Montoye HJ, Leon AS. Methods of assessing physical activity during leisure and work. In: Bouchard C, Shephard RJ, eds. Physical activity, fitness and health: the model and key concepts. Champaign, IL: Human Kinetics, 1994:146-158. 19. Booth M. Assessment of physical activity: an international perspective. Res Q Exerc Sport. 2000;71:S114-S120. 20. Craig CL, Marshall AL, Sjostrom M, Bauman AE, Booth ML, Ainsworth B, et al. International Physical Activity Questionnaire (IPAQ): 12-country reliability and validity. Med Sci Exerc Sport. 2003;35:1381-1395. 21. Rütten A, Ziemainz H, Schena F, Stahl T, Stiggelbout M, Vanden Auweele Y, Vuillemin A, et al. Using different physical activity measurements in eight European countries. Results of the European Physical Activity Sureveillance System (EUPASS) time series survey. Public Health Nutr. 2003;6:371-376

IPAQ Reliability and Validity 75 22. Rütten A, Vuillemin A, Ooijendijk WTM, Schena F, Sjörström M, Stalh T, et al. Physical activity monitoring in Europe. The European activity surveillance system (EUPASS) approach and indicator testing. Public Health Nutr. 2003;6:377-384. 23. Ainsworth BE, Haskell WL, Leon AS, Jacobs DR Jr., Montoye HJ, Sallis JF, et al. Compendium of physical activities: classification of energy costs of human physical activities. Med Sci Sport Exerc. 1993;25:71-80. 24. Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, et al. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc. 2000;32:S498-S504. 25. Tyron WW, Williams R. Fully proportional actigraphy: a new instrument. Behav Res Meth Instr Comp. 1996;28:392-403. 26. Ainsworth BE, Bassett DR Jr., Strath SJ, Swartz AM, O Brien WL, Thompson RW, et al. Comparison of three methods for measuring the time spent in physical activity. Med Sci Sport Exerc. 2000;32:S457-S464. 27. De Abajo S, Larriba R, Marquez S. Validity and reliability of the Yale Physical Activity Survey in Spanish elderly. J Sport Med Phys Fitness. 2001;41:479-485. 28. Pols MA, Peeters PH, Ocke MC, Slimani N, Bueno-de-Mesquita HB, Collette HJ. Estimation of reproducibility and relative validity of the questions included in the EPIC Physical Activity Questionnaire. Int J Epidemiol. 1997;26:S181-S189. 29. Wareham NJ, Rennie KL. The assessment of physical activity in individuals and populations: why try to be more precise about how physical activity is assessed? Int J Obes Relat Metab Disord. 1998;22: S30-S38.