The health-related associations of appropriate levels of movement behaviors (ie, physical activity [PA], sedentary behavior [SB], and sleep, across a 24-h period1–3) in children and adolescents have been described and led to an increased interest by public health authorities in this new 24-hour movement paradigm. As such, some countries have developed4–6 24-hour movement guidelines for young children, children, and adolescents, and the World Health Organization has also developed PA, SB, and sleep guidelines for young children.7 These new guidelines, incorporating sleep, SB, and PA, demand adaptation of the current monitoring and surveillance instruments to accurately assess movement behaviors in an integrated way and to assess compliance with such guidelines. The accurate measurement of movement behavior levels and patterns is paramount to better understand the health-related associations of these behaviors, determining its correlates and predictors, monitoring 24-hour movement patterns and levels, and to evaluate the effectiveness of interventions. Although the accurate assessment of movement behaviors is important for research, policy, and practice, measuring them is a challenging and complex procedure.
There are many methods to assess movement behaviors in children and adolescents. While accelerometers are accurate instruments to assess movement behaviors,8–15 in large-scale epidemiological studies and clinical contexts, questionnaires are preferred due to their practicality, simplicity, and affordability.8,16–19 Accelerometer-derived results are dependent on researcher decisions on data reduction, the potential use of algorithms or imputation techniques, and are labour-intensive.16,20 On the other hand, questionnaires can collect specific contextual details (eg, domains) that objective measures are unable to.8,16,21 However, assessing movement behaviors with questionnaires has several limitations, such as measurement errors and reporting bias, given that questionnaires’ responses are often influenced by social desirability, language interpretation, complexity of the questionnaire, age, and season.8,18,19,22 Additionally, if the questionnaires’ development methods and the measurement properties are poor or unclear, the risk of misclassification, bias, and inaccurate results is high.23
Assessing children and adolescents’ movement behaviors with questionnaires can be even more challenging than in adults. Indeed, comparing to adults, children and adolescents have greater difficulties in reporting past movement behaviors due to their unstable patterns24,25 and cognitive differences, particularly in the ability to think abstractly and perform detailed recall,17 leading to an overestimation of PA’s intensity and volume.26 It is also known that the younger the children are, the lower their ability to recall and report movement behaviors, which is often solved via proxy-report by parents or caregivers.27–30
Recently, 3 systematic reviews on measurement properties of PA questionnaires31–33 reported several methodological limitations and weak measurement properties, together with a lack of studies reporting measurement error and content validity. Concerning SB questionnaires, a systematic review8 concluded that, for most questionnaires, validity and reliability evidence was of low quality, and there was a wide methodological diversity between studies. More recently, 2 systematic reviews32,34 also reported no conclusive recommendation about the best available questionnaire to measure SB in children and adolescents. Regarding sleep questionnaires for children and adolescents, research has shown that the existing ones often do not report psychometric properties,35 and many typically focus on assessing sleep disorders.19,35,36 A meta-analysis9 on sleep duration questionnaires reported that most studies used accelerometers as the criterion measure for validation, and these are likely to have acceptable reliability. However, current evidence does not allow for identification of the best questionnaire to evaluate these movement behaviors in an integrated fashion, under the new 24-hour movement paradigm.
Considering the new 24-hour movement behavior paradigm, examining the combination of behaviors composing a day seems vital to better understand the complexity of the interactions between these behaviors and their health effects. The existing reviews on questionnaires’ measurement properties to assess sleep, SB, and PA were focused on questionnaires assessing each behavior in isolation, without considering questionnaires assessing more than one behavior. Therefore, there is a tangible need to analyze the questionnaires measuring each movement behavior individually, as well as the questionnaires that measure movement behavior combination over 24 hours. Such scrutiny will increase our understanding regarding validity and reliability of existing questionnaires measuring movement behaviors as time-dependent behaviors, with the potential to help researchers and policy makers interested in assessing each movement behavior individually or any combination of movement behaviors, to choose the instrument with the best trade-off between measurement properties quality, population, and study purpose, in children and adolescents. In this sense, we aim to systematically review the literature on measurement properties of self- and proxy-reported questionnaires assessing all movement behaviors, individually or in combination, in children and adolescents.
Methods
COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) guidelines for systematic reviews of patient-reported outcome measures37 were adapted for this review. These are in accordance with the Cochrane Handbook for systematic reviews of interventions38 and the PRISMA statement for reporting systematic reviews and meta-analyses.39 The adaptation of the COSMIN guidelines consisted in using only the guidelines for each measurement property that suited the structure and response options of the included questionnaires. For example, the COSMIN foresees the evaluation of Patient‐Reported Outcome Measures, created in a reflective model (with scales and subscales), and structural and internal validity may be performed, which was not the case for the questionnaires included; therefore, these types of evaluation were not carried out. This review’s information is presented slightly different than that proposed by COSMIN’s to accommodate the specificities of the included questionnaires. Population, Intervention, Control, Outcome (PICO) used in this study can be found in Supplementary Material S1 (available online).
Eligibility Criteria
The inclusion criteria were the following: (1) children and adolescents (younger than 17.9 y); (2) minimum sample size of 50 participants for validity studies40; (3) studies reporting validity and test–retest reliability results37,41 of self-reported or proxy-reported questionnaires that were developed specifically to measure sleep, SB, or PA, or their combination; and (4) studies written in English, Spanish, French, Portuguese, German, Italian, or Chinese.
The exclusion criteria were the following: (1) studies using doubly labeled water as criterion measure, given that it assesses total energy expenditure and not only PA energy expenditure41,42; (2) studies evaluating questionnaires aimed solely at predicting or detecting a given health condition, designed for specific populations (eg, chronic, autoimmune and infectious diseases, sleep disorders, athletes, pregnant women) or focused only on lifetime sleep, SB, and/or PA; (3) studies reporting measurement properties of questionnaires not designed to validate an original questionnaire (eg, reported linguistic validation); (4) studies reporting sleep, SB, and/or PA measurement properties of logs, diaries, or interviews; and (5) grey literature (eg, thesis, book chapters), abstracts, reviews, meta-analyses, commentaries, cost-effectiveness studies, and pilot studies.
Information Sources and Search Strategy
We systematically searched 4 electronic databases: PubMed, PsycINFO, SPORTDiscus, and EMBASE (June 2021), without temporal limits of search. Additional studies were identified by manually searching references from the retrieved papers and authors personal libraries, to ensure no relevant studies were overlooked.
The electronic databases were searched for variations of the terms “children,” “adolescents,” “sleep,” “sedentary behavior,” “physical activity,” “movement behaviors,” “questionnaire,” and “measurement properties” (for a detailed search strategy see Supplementary Material S2 [available online]). The search terms were adapted for each specific electronic database to ensure the quality of the systematic searching.
Screening
Three authors independently selected potentially relevant studies based on titles, abstracts, and full texts. Disagreements were discussed with a fourth author. The study selection procedure was conducted via the Central Access Database for Impact Assessment of Crop Genetic Improvement Technologies (CADIMA) software.43
Data Extraction
A standardized data extraction form was developed by 2 authors, to gather relevant information from the included studies (see Supplementary Material S3 [available online]) regarding the characteristics of the questionnaire, the methods, and measurement properties’ results. Data were extracted by 3 authors and checked by a fourth author.
Given this review’s characteristics, data extraction on content and measurement properties was based on COSMIN guidelines,37 the Taxonomy of Self-reported Sedentary Behavior Tools framework,44 and the Quality Assessment of Physical Activity Questionnaire Checklist.41 The Edinburgh Framework45 for validity and reliability in PA and SB measurement was also considered. When needed, adaptations were made to integrate sleep as a movement behavior. The data were collected independently by 6 authors and disagreements were resolved by discussion with another author. The definitions for the outcome variables used in this systematic review are explained below.
Studies’ Risk of Bias Assessment
The Risk of Bias checklist developed by COSMIN37 was used to assess the methodological quality of the included studies. This checklist has a 4-point scale (ie, “very good,” “adequate,” “doubtful,” or “inadequate”) and contains items on criterion validity, reliability, measurement error, and responsiveness. For each measurement property, different design requirements and statistical methods were rated based on COSMIN standards,37 and therefore, the overall rating was determined based on “the worst score counts” method.
The criteria for each item can be found in COSMIN guidelines.37 For reliability, in line with previous work,46 we defined an “adequate” time interval between test and retest as follows: >1 day and ≤3 months for questionnaires recalling a usual week/month, >1 day and ≤2 weeks for questionnaires recalling the previous week, >1 day and ≤1 week for questionnaires recalling the previous day, and >1 day and ≤1 year for questionnaires recalling the previous year. Data were independently collected by 5 authors and disagreements were discussed with another author.
Effect Measures
Quality of Measurement Properties
To appraise the quality of measurement properties’ results, COSMIN guidelines37 were followed. All measurement properties were rated against quality criteria for good measurement properties,47 and each result was rated as “inadequate” (–), “doubtful” (?), or “adequate” (+). Studies were classified as “doubtful” when its design or method was not well reported.
For the overall rating of the studies’ quality, if 75% of the results per study were “adequate,” the overall rating was also considered “adequate.”
Criterion Validity
Studies were classified as having “adequate criterion validity” (ie, the extent of the correlation between a measure and another already considered as being a criterion or gold standard) when the results for correlations between the questionnaire and the criterion instrument (ie, accelerometer, pedometer for walking measures) were ≥0.70 (with a statistically significant P value < .05). Although there is no gold standard to measure all movement behaviors, the accelerometer was considered an appropriate criterion measure because it is an instrument able to accurately measure all movement behaviors, and it is widely used as a criterion comparison measure in validation studies of movement behaviors questionnaires, particularly in children and adolescents.48
Convergent Validity
For convergent validity (ie, the extent of the agreement with another [noncriterion] measure that should assess the same behavior parameter based on face and content validity), a study was rated with “adequate convergent validity” if the correlation between the questionnaire and the other assessments related to the behavior in question (eg, between self-reported PA intensity and objectively measured VO2max) was ge;.5 and P value < .05. Equally, a study was rated with “adequate convergent validity” if the correlations between a similar self-reported instrument and the questionnaire were ≥.7 and P value < .05.
Reliability
For reliability test–retest (ie, the extent to which test scores are consistent from one test administration to the next, keeping the same conditions, such as researcher, timing, preparation), intraclass correlation coefficients (ICCs) for continuous variables or weighted kappas for categorical variables ≥.70 were considered “adequate”; given that Pearson or Spearman correlation coefficients do not take into account systematic errors,49 only correlations ≥.80 were rated “adequate.”42
Measurement Error
Measurement error (eg, how close the scores on repeated administrations are), expressed in the unit of the questionnaire (ie, limits of agreement, SEM, smallest detectable change), was considered “adequate” when the smallest detectable change or limits of agreement were smaller than minimal important change, and “doubtful” when minimal important change was not defined by the study’s authors. Responsiveness (ie, the ability of an instrument to detect change over time in the construct to be measured; refers to the validity of a change score) was considered “adequate” when the result was in accordance with the hypothesis or if the area under the curve was ≥0.70, and “doubtful” when no hypothesis was defined.
Evaluation of Content Validity
We applied a subjective reviewers’ rating to assess the content validity of all included questionnaires, as recommended by COSMIN.37 In this evaluation, all questionnaires’ items were rated as “adequate” (+) or “inadequate” (−), considering: (1) items’ relevancy for the construct, population, and context of use (ie, the item had to be directly related to the construct or behavior evaluated); (2) response options and recall period appropriateness for construct, population, and context of use (ie, closed response options were considered inappropriate because they do not capture the movement continuum; the recall period and context had to be clearly stated); (3) comprehensiveness of the construct, population, and context of the use of interest (ie, key aspects, such as duration or intensity related to the construct or behavior had to be clearly stated); and (4) language appropriateness of the response options and items (ie, clear and simple language).
When the questionnaire form was not embedded in the article, we searched it online. If the questionnaires were not found online, authors were contacted, requesting the questionnaires, at least twice, separated by a minimum of 2 weeks. If it was not possible to access the questionnaire (online unavailability or authors lack of response), we rated it as “cannot be determined.”
Synthesis Methods
Given the specificity of this review and the diversity of the included studies in terms of methodology used and results reported, a meta-analysis was not possible. As such, we chose to present a narrative synthesis of the results, per property measurement and age group and organized it in the respective tables (as presented in the “Results” section).
Results
Search Results
The search yielded 9382 studies after removing duplicates. Six studies were added after a manual search. After screening titles and abstracts, 70 full texts were selected and 29 were included, describing 37 questionnaires. The reasons for full texts’ exclusion are described in Figure 1.
—Study selection process flowchart. n indicates number of studies.
Citation: Journal of Physical Activity and Health 20, 1; 10.1123/jpah.2022-0399
Synthesis Results
Content Description
The characteristics of the included questionnaires are presented in Table 1. Twenty questionnaires measured PA (2 in children,30,50 16 in adolescents,30,50–61 and 2 in both62,63); 6 measured SB (1 in children,64 4 in adolescents64–67 and, 1 in both68); and 1 measured sleep duration in children and adolescents.69 Eight questionnaires measured behaviors’ combinations, namely PA and SB (1 in children,70 3 in adolescents55,71,72 and, 4 in both73–76), and 2 measured sleep, SB, and PA in children and adolescents.77 Out of the 37 questionnaires included, 7 were proxy-reported.30,50,64,69,76,77 There were no questionnaires (proxy reports) designed for babies and toddlers (<3 y of age).
Content Characteristics of the Included Movement Behavior Questionnaires
| Questionnaire | Age group, country | Mode of administration | Domains | Response method | Units of measurement | Scores | Recall period/assessment period | No. of items | Parameters |
|---|---|---|---|---|---|---|---|---|---|
| Physical activity | |||||||||
| CLASS—Proxy30 | Children (5–6 y), Australia | Proxy-reported | Leisure; sports; total PA | Continuous: times/wk; min or h/d | min or h/d | Frequency MPA; frequency VPA; duration MPA; duration VPA intensity | Usual weekday and weekend day in a typical week | 30 activities + 6 | F; D; I; M |
| SAYCARE PA Q C50 | Children (3–10 y), South America | Proxy-reported | School; leisure; transportation | Participate yes/no; if yes, continuous: frequency, duration, and intensity | min/d PA school; min/wk PA leisure; min/d PA commuting | PA at school; time spent PA leisure; PA commuting; MPA; VPA; total PA; guideline’s compliance | Past week | 47 | F; D; I |
| O-O-S PAQ51 | Adolescents (11 y), Finland | Self-reported | Out of school (leisure and sports) | Rating scale: h/wk and times/wk (10 options) | min/d and times/wk | MVPA duration and MVPA frequency | Usual week during weekdays | 2 | F; D |
| HPAQ52 | Adolescents (11–16 y), Brazil | Self-reported | Sports; transportation | Continuous: h/d; d/wk; mo/y | min/wk; min/y | Weekly PA score; yearly PA score | Past year | 7–17 | F; D; M |
| 3DPAR53 | Adolescents (11–14 y), United States | Self-reported | Before, during, after school | For each activity rate, its intensity across 4 categories | Number of 30-min blocks per intensity MVPA and VPA | MVPA; VPA | Past 3 d | ? | F; D; I; M |
| YRBS54 | Adolescents (12.7 [0.6] y), United States | Self-reported | Total PA by intensity | Continuous: min/d | min/d | Meeting guidelines | Past week in weekdays and weekend days | 2 | F; D; I |
| SAPAC53 | Adolescents (11–14 y), United States | Self-reported | Before, during, after school | Checklist of responses (continuous: min/d) | min/d | MVPA; VPA | Past 3 d | ? | F; D; I; M |
| HBSC PAQ55 | Adolescents (13–18 y), Norway | Self-reported | Outside school | Rating scale | Categories: “Low activity” represents “one day a week or less” or “one hour a week or less”; “moderate activity” represents “2–3 days a week” or “2–3 hours a week”; “high activity” represents “four days a week or more” or “four hour a week or more” | Frequency; duration; frequency, 3 categories; duration, 3 categories | Usual week, outside school | 2 | F; D |
| MGLTEQ56 | Adolescents (12–14 y), United States | Self-reported | Total PA by intensities | Continuous: d/wk | d/wk | Strenuous; moderate; mild | Usual week in summer and school time | 3 | F; I |
| OPAQ57 | Adolescents (13–14 y), United Kingdom | Self-reported | Transport; physical education; school sport; after school sport | Continuous: d/wk, min/wk; list of activities | METs/wk | MPA; VPA; MVPA | Past week in weekdays and weekend days | 8 | F; D |
| APARQ58 | Adolescents (13–15 y), Australia | Self-reported | Organized sports, games; nonorganized physical activities | List of activities; continuous: times/wk; h/time | METs | Energy expenditure (winter/summer; organized/nonorganized: inactive, adequate, vigorous) | Usual week during summer school terms and during winter school terms (excluding vacations) | 12 (up to 84) | F; D; M |
| PYPAA59 | Adolescents (12–16 y), United States | Self-reported | Leisure | Checklist; continuous: min/activity | MET-h/wk | Overall leisure physical activity in h/wk; MET-h/wk; VPA-h/wk | Past year | 3 (up to 33) | F; D; M |
| cPAQ60 | Adolescents (11–16 y), Malaysia | Self-reported | School; after-school; household | ? | METs | LPA; MPA; VPA | Past year | 71 | F; D; I, M |
| S-I PA M61 | Adolescents (14.7 [0.5] y), Australia | Self-reported | MVPA | Continuous (number of d) | Number of d | MVPA | Past week | 1 | F; D; I |
| MPA and VPA S Q54 | Adolescents (14.6 [1.4] y), United States | Self-reported | General MPA and VPA | Continuous (times/wk) | Number of d | 30- and 60-min MPA and 20-min VPA (past week, typical week, and composites [average]) | Past week and typical week | 6 | F; D; I |
| PACE + PAM54 | Adolescents (12.1 [0.9] y), United States | Self-reported | General MVPA | Continuous (d/wk) | Number of d | MVPA | Past week and typical week | 1 per recall period | F; D; I |
| SAYCARE PA Q A50 | Adolescents (11–18 y), South America | Self-reported | School; leisure; transportation | Participate yes/no; if yes, continuous: frequency, duration, and intensity | min/d PA school; min/wk PA leisure; min/d PA commuting | PA at school; time spent PA leisure; PA commuting; MPA; VPA; total PA; guideline’s compliance | Past week | 47 | F; D; I |
| CLASS–Proxy and self30 | Adolescents (10–12 y), Australia | Proxy- reported and self-reported | Leisure; sports; total PA | Continuous: times/wk; min or h/d | min or h/d | Frequency MPA; frequency VPA; duration MPA; duration VPA intensity | Usual weekday and weekend day in a typical week | 30 activities + 6 | F; D; I; M |
| Fels PAQ62 | Children and adolescents (7–19 y), United States | Self-reported | Sport; leisure; transportation; home | Rating scale: 1 (sometimes) to 3 (regularly) | Points (reflecting intensity—METs—and frequency) | Total score; sport score; leisure score; work score | Past year | 8 | F; I |
| MoMo63 | Children and adolescents (9–17 y), Germany | Self-reported | Total PA; sports; physical education | Continuous (times/wk; min/wk); rating scale for intensity (1 [shortness breath] to 3 [much sweating]) | min/wk | General PA; PA in school; recreational sports outside clubs | Past week | 28 | F; D; I; M |
| Sedentary behavior | |||||||||
| SAYCARE SB Q C64 | Children (3–10 y), Argentina, Peru, Colombia, Uruguay, Chile, and Brazil | Proxy-reported for children (parents) | TV; computer use; studying (adolescents); video games; passive play (children) | Continuous: min/d | min/wk | Total SB and achieving or not achieving the recommended limit of less than 120 min/d of SB | Past week in weekdays and weekend days | 8 | F; D; I; M |
| EAQT-SB65 | Adolescents (11–15 y), United States | Self-reported | TV (and videos or playing video games) and computer use | Rating scale (1 [less than 1 h] to 6 [5 or more h]) | h/d | Weekday TV (school period); weekend TV (school period); weekend TV (summer); weekday TV (summer); computer use; weekday average | Weekday; weekend in summer and school time | 5 | D; M |
| Helena SB Q66 | Adolescents (12.5–17.5 y); Europe | Self-reported | TV viewing; computer games; console (video) games; internet for nonstudy reasons (hobbies); internet for study reasons; and study time (out of scholar schedule) | Rating scale (0 min to >4 h) | h/d | Weekly time and total score; weekend time | Usual day in week and weekend days | 12 | D |
| SIT-Q-7d67 | Adolescents (15–16 y), The Netherlands | Self-reported | TV; computer; motorized transport; school; gaming | Checklist and continuous: min/activity | min/wk | Weekday ST; weekend day ST; average ST | Past week in week and weekend days | 24 | F; D; M |
| SAYCARE SB Q A64 | Adolescents (11–18 y), Argentina, Peru, Colombia, Uruguay, Chile, and Brazil | Self-reported for adolescents | TV; computer use; studying (adolescents); video games; passive play (children) | Continuous: min/d | min/wk | Total SB and achieving or not achieving the recommended limit of less than 120 min/d of SB | Past week in weekdays and weekend days | 8 | F; D; I; M |
| YLSBQ68 | Children and adolescents (8–18 y), Spain | Self-reported | Screen time (watching TV/videos; playing computer/video games and internet surfing); NSST-educational (doing homework/study with computer; doing homework/study without computer and reading for fun); NSST-social (sitting and talking; talking on the telephone; listening to music); NSST-others (sitting to rest; doing cognitive hobbies [ie, doing puzzles or playing cards] and traveling on motorized transport) | Rating scale (0 min to 5 h or 0 to 2 h 30 min) | Average min/d | Weekday ST; weekend ST; average day ST | Past week in average weekday and weekend day | 24 | F; D |
| Sleep | |||||||||
| CCTQ69 | Children and adolescents (4–11 y), United States | Proxy-reported | Night sleep period; naps | Continuous: h and min of waking up, going to bed, lights turned off; and min to falling asleep; min per nap | Sleep onset (calculated by h and min of waking up, going to bed, lights turned off; and min to falling asleep); h per nap | Sleep period | Typical weekday and weekend day | 12 | F |
| Physical activity + sedentary behavior | |||||||||
| GAQ70 | Children (8–9 y), United States | Self-reported | Leisure; sedentary behaviors (TV; using computer; video games; on telephone) | Checklist and rating scale (3 points: none; less than 15 min; more than 15 min) | MET-weighted average was computed; score based on time spend on sedentary behavior | Total PA score; (weighted) MET values; GAQ summary score | Past day; usually day | 27 for physical activity; 7 for sedentary behavior | F; D; M |
| ENERGY-C Q71 | Adolescents (10–12 y), Belgium, Greece, Hungary, The Netherlands, Norway, and Spain. | Self-reported | Transport; sports; computer use; TV; leisure | Continuous: d/wk; min/d; h/wk; h/d | d/wk; min/d; h/wk; h/d | Bike to school; walk to school; car to school; public transport to school; first sport; second sport; sport past day; computer use in free time in week and weekend days; past day TV; past day computer use | Past week and past day, in weekend and weekdays | 15 | F; D |
| IPAQ55 | Adolescents (13–18 y), Norway | Self-reported | Leisure | Continuous: d/wk and min/d | d/wk and min/d | Sitting; LPA; MPA; VPA; walking | Usual or past week in week and weekend days | ? | F; D |
| SHAPES physical activity questionnaire72 | Adolescents (11–18 y), Canada | Self-reported | Sports; transportation; leisure physical activities; screen time | Continuous: time/d | min/wk | VPA; MPA; MVPA; screen time | Past week | 45 | F; D; I |
| MARCA73 | Children and adolescents (9–13.5 y), Australia | Self-reported | All forms of activity (organized and nonorganized physical activity, sedentary activity, incidental activity, etc) | Continuous: time spent in each activity | MET-weighted average was computed; score based on time spend on sedentary behavior | PAL; MVPA; lying down, sitting, standing or in locomotion | Past day in weekday, weekend, holiday or day off from school | Segmented day format (web-based) | D; I; M |
| peas@tees74 | Children and adolescents (9–10 y), England | Self-reported | Sedentary, household, and play activities, structured; transport | Continuous: time spent in each activity | MET-weighted average was computed; score based on time spend on sedentary behavior | MVPA | Usual day in school day and weekend day | Segmented day format (web-based) | D; I; M |
| HSK75 | Children and adolescents (9–14 y), United States | Self-reported | Active play or sport; sedentary behaviors (TV; using computer; video games; on telephone) | Rating scale | h/d | Hours of active play or sport; hours of sedentary activities | Usual day of past month | 2 | F; D |
| PQPASB76 | Children and adolescents (6–10 and 13–14 y), Swiss | Proxy-reported | For PA: leisure For SB: screen-time; study; leisure; reading | Rating scale: never, less than 30 min, 30 min to 1 h, 1–2 h, 2–4 h, and more than 4 h/d | min/d | SB score and PA score (the categorized time intervals were transformed into a continuous variable using the intervals’ midpoints and an assumed maximum of 8 h); watching TV/video/DVD; sitting at a computer/playing Nintendo/electronic games; doing homework; reading; playing a musical instrument; playing quietly/other quiet activities; traveling by car/public transport; time spent outdoors; playing vigorously active indoors; playing vigorously active outdoors; cycling; time spent breathing hard and sweating; attending sports training (outside school); frequency of physical activity bouts with parents; active commuting to school; comparison with other children of the same age and sex | Usual weekday and weekend day | List of activities | F; D; M |
| Physical activity + sedentary behavior + sleep | |||||||||
| Daughter Questionnaire77 | Children and adolescents (8.5–12.7 y), United Kingdom | Self-reported | Light activity (standing); moderate activity (walking); and vigorous activity (sports); TV/VCR/video games; ST; sleep | Continuous: h/d | h/d | Sleep; sitting; standing; walking; exercise; TV/VCR/video games | Usual day, in school day and weekend day | Three timetables (school, weekend, TV) | D; I |
| Mother and Father Questionnaires77 | Children and adolescents (8.5–12.7 y), United Kingdom | Proxy-reported | Light activity (standing); moderate activity (walking); and vigorous activity (sports); TV/VCR/video games; ST; sleep | Continuous: h/d | h/d | Sleep; sitting; standing; walking; exercise; TV/VCR/video games | Usual day, in school day and weekend day | ? | D; I |
Abbreviations: ?, doubtful; 3DPAR, 3-d Physical Activity Recall; APARQ, Adolescent Physical Activity Recall Questionnaire; CCTQ, Children’s ChronoType Questionnaire; CLASS—Proxy and self, The Children’s Leisure Activities Study Survey—Proxy and self-reported; CLASS—Proxy, The Children’s Leisure Activities Study Survey—Proxy; cPAQ, computer-based physical activity questionnaire; D, duration; EAQT-SB, Eating and Activity Questionnaire Trial—Sedentary Behavior questions; ENERGY-C Q, ENERGY-Child Questionnaire; F, frequency; Fels PAQ, Fels Physical Activity Questionnaire; GAQ, GEMS Activity Questionnaire; HBSC PAQ, Health Behavior in Schoolchildren Physical Activity Questionnaire; Helena SB Q, HELENA screen time-based sedentary behavior questionnaire; HPAQ, Habitual Physical Activity Questionnaire; HSK, Heart Smart Kids; I, intensity; IPAQ, International Physical Activity Questionnaire; LPA, light physical activity; M, mode; MARCA, multimedia activity recall for children and adolescents; METs, Metabolic equivalent; MGLTEQ, Modified Godin-Leisure-Time Exercise Questionnaire; MoMo, MoMo-Physical-Activity-Questionnaire for Adolescents; MPA and VPA S Q, moderate and Vigorous Physical Activity Screening Questionnaire; MPA, Moderate Physical Activity; MVPA, moderate to vigorous physical activity; n, sample number; NSST, nonscreen sedentary time; O-O-S PAQ, Out-of-School Physical Activity Questionnaire; OPAQ, Oxford Physical Activity Questionnaire; PA, physical activity; PACE + PAM, PACE + adolescent physical activity measure; PAL, physical activity level; PACE, patient-centered assessment and counseling for exercise; PQPASB, Parental Questionnaire for Physical Activity and Sedentary Behavior; PYPAA, past year physical activity in adolescents; SAPAC, Self-Administered Physical Activity Checklist; SAYCARE PA Q A, SAYCARE Physical Activity Questionnaire for adolescents; SAYCARE PA Q C, SAYCARE Physical Activity Questionnaire for children; SAYCARE SB Q A, South American Youth Cardiovascular and Environmental sedentary behavior questionnaire for adolescents; SAYCARE SB Q C, South American Youth Cardiovascular and Environmental sedentary behavior questionnaire for Children; SB, sedentary behavior; SHAPES, School Health Action, Planning and Evaluation System; S-I PA M, single-item physical activity measure; SIT-Q-7d, last-7-d sedentary behavior questionnaire; ST, sitting time; VPA, vigorous physical activity; YLSBQ, Youth Leisure-time Sedentary Behavior Questionnaire; YRBS, Youth Risk Behavior Survey.
Regarding PA questionnaires,30,50,51,53–63 70% assessed multidomain PAs, with leisure-time PA (out of school or after school) being the most frequent domain assessed (measured in 12/20 questionnaires). The most prevalent response method was the continuous method (75%; 15/20), focusing on different metrics (eg, min/d; times/wk). The most frequent measurement units (75%; 15/20) were temporal (ie, min/wk/d; h/d; times/wk). Most questionnaires assessed multiple scores (90%; 18/20). Recall periods varied from past week (40%; 8/20), usual week (30%, 6/20), past year (20%, 4/20), usual day (5%; 1/20), to past 3 days (10%, 2/20). The assessment period was specified in 40% of the PA questionnaires (8/20). The number of items included in the PA questionnaires ranged from 1 to 84.
All SB questionnaires64–68 assessed its multidomains, with screen time being present in all included questionnaires. Out of the 6 questionnaires, 364,67 used the continuous response method, with the remaining using rating scales.65,66,68 Time-focused measurement units were used in all questionnaires (ie, min/h/d/wk). All questionnaires assessed multiple scores, depending on the domain evaluated. Past week was the most frequent recall period (67%; 4/6), and all questionnaires specified the assessment period. The number of items included in the questionnaires ranged from 5 to 24.
One questionnaire assessed sleep duration,69 with 12 questions. The response method was continuous; the measurement unit was time (hours and minutes) for bed and waking times, and for lights turned off, minutes to falling asleep and minutes per nap. The score was the sleep period. The recall period was a typical day, with assessment periods for weekdays and weekend days.
The questionnaires combining PA and SB,55,70–76 mostly assessed the behaviors through multidomain (88%; 7/8), with leisure PA and screen-time SB domains being the most predominant (63%; 5/8). Continuous method was the most prevalent response method (63%, 5/8); and all questionnaires used temporal metrics (eg, minutes per day). The measurement units were focused on temporal metrics in all but 3 questionnaires70,73,74 which determined METs. Most questionnaires assessed PA and SB through multiple scores (88%; 7/8). The recall periods were divided into usual day per week (50%; 4/8) and/or past day per week (63%; 5/8). The assessment period was specified in 63% of the questionnaires (5/8). The number of items included in the questionnaires ranged from 2 to 45. One questionnaire was organized in a list of activities76 and 2 were segmented by day format.72,73
Two questionnaires assessed PA, SB, and sleep,77 one proxy- and the other self-reported. The questionnaires were focused on light, moderate, and vigorous PA time, screen, and sitting time, and sleep duration. The response method was continuous (hours per day), the measurement unit was hours per day, and the questionnaire assessed multiple scores (3 for PA, 2 for SB, and 1 for sleep). The recall period was a typical day, and the assessment periods were on a school day and on a weekend day.
Among the included questionnaires, none were designed to assess the movement behaviors considering the 24-hour movement behavior paradigm.
Content Validity
Considering all questionnaires included, 55.3% showed “adequate” content validity. Regarding PA questionnaires, 5 were considered “inadequate” (4 in adolescents52,55,56,59 and 1 in children and adolescents62). Seven questionnaires were not available (1 in children,30 5 in adolescents,30,53,60 and 1 in both63); therefore, their content validity could not be determined. For SB, 3 questionnaires were rated with “inadequate” content validity (2 in adolescents65,66 and 1 in children and adolescents68). The sleep questionnaire was rated with “adequate” content validity. For PA and SB, one questionnaire in children70 was rated with “inadequate” content validity. For the combination of PA, SB, and sleep, the questionnaires were not available; therefore, their content validity could not be determined. The main reason for the content validity inadequacy was the response options not being considered adequate (ie, closed response, rating scales). Content validity results and its details are provided in Supplementary Material S4 (available online).
Validity
Table 2 summarizes the results of questionnaires’ validity. No questionnaire showed overall “adequate” criterion validity. The computer-based physical activity questionnaire60 showed “adequate” convergent validity. The most frequently calculated coefficients were Pearson and Spearman correlations and ICCs coefficients. Limits of agreement were examined in 10.5% of the questionnaires (3/29) through Bland and Altman plots.
Validity Results
| Questionnaire | Sample | Validity | Overall quality | ||
|---|---|---|---|---|---|
| n; %girls; age mean (SD) or age range, y | Type of validity | Comparison measure | Results | ||
| PA | |||||
| CLASS—Proxy30 | 58; 63% girls; 5–6 y | Criterion | Accelerometer, ActiGraph AM7164-2.2C; wear time: N.R.; site: N.R.; epoch: N.R. | MPA (rho = −0.06); VPA (rho = −0.04); total PA (rho = −0.04); total accelerometer raw movement counts per day (rho = 0.05) | − |
| SAYCARE PA Q C50 | Children: 82; 54.4% girls; 3–10 y | Criterion | Accelerometer, ActiGraph GTX3, wear time: 7 d; site: hip mounted; epoch: 5 s | MPA (rho = 0.60*); VPA (rho = 0.27); total PA (rho = 0.44*); agreement guidelines (kappa = .40) | − |
| O-O-S PAQ51 | 126; N.R.; 11 y | Criterion | Accelerometer, ActiGraph GTX3, wear time: 7 d; site: hip mounted; epoch: 15 s | MVPA duration (r = .25); MVPA frequency (r = .25) | − |
| HPAQ52 | 94; 68.1% girls; 11–16 y | Convergent | VO2max (ml/kg/min) | Weekly physical activity score (rho = 0.15); yearly physical activity score (rho = 0.23) | − |
| Total speed (km/h) | Weekly physical activity score (rho = 0.14); yearly physical activity score (rho = 0.23) | − | |||
| Total time (s) | Weekly physical activity score (rho = 0.14); yearly physical activity score (rho = 0.26) | − | |||
| Maximum heart rate | Weekly physical activity score (rho = 0.10); yearly physical activity score (rho = 0.16) | − | |||
| Waist circumference (cm) | Weekly physical activity score (rho = −0.12); yearly physical activity score (rho = −0.06) | − | |||
| 3DPAR53 | 157; N.R.; 11–14 y | Criterion | Accelerometer, ActiGraph (empirical thresholds); wear time: 3 d; site: N.R.; epoch: 30 s | Overall period MVPA (r = .28**); Monday MVPA (r = .49***); Sunday MVPA (r = .26**); Saturday MVPA (r = .06); overall period VPA (r = .16); Monday VPA (r = .31**); Sunday VPA (r = .15); Saturday VPA (r = .02) | − |
| Accelerometer, ActiGraph (standard thresholds); wear time: 3 d; site: N.R.; epoch: 30 s | Overall period MVPA (r = .20); Monday MVPA (r = .24*); Sunday MVPA (r = .19); Saturday MVPA (r = .16); overall period VPA (r = .29**); Monday VPA (r = .42***); Sunday VPA (r = .18); Saturday VPA (r = .24**) | − | |||
| YRBS54 | 125, 52.5% girls; 12.2 (0.6) | Criterion | Accelerometer, ActiGraph model 7164; wear time: 7 d; site: hip; epoch: 60 s | Meeting MPA guideline (≥30 min/d for ≥5 d/wk) = 20.8% of agreement; sensitivity = 0.23; specificity = 0.92; meeting VPA guideline (≥20 min/d for ≥3 d/wk) = 19.2% of agreement; sensitivity = 0.86 | ? |
| SAPAC53 | 154; N.R.; 11–14 y | Criterion | Accelerometer, ActiGraph (empirical thresholds); wear time: 3 d; site: N.R.; epoch: 30 s | Overall period MVPA (r = .24**); Monday MVPA (r = .31**); Sunday MVPA (r = .18); Saturday MVPA (r = .21*); overall period VPA (r = .28**); Monday VPA (r = .44); Sunday VPA (r = .15); Saturday VPA (r = .23*) | − |
| Accelerometer, ActiGraph (standard thresholds); wear time: 3 d; site: N.R.; epoch: 30 s | Overall period MVPA (r = .31***); Monday MVPA (r = .50***); Sunday MVPA (r = .28**); Saturday MVPA (r = .14); overall period VPA (r = .19); Monday VPA (r = .32***); Sunday VPA (r = .19*); Saturday VPA (r = .04) | − | |||
| HBSC PAQ55 | 67; 55% girls; 13–18 y | Convergent | VO2peak | Frequency (rho = 0.39**); duration (rho = 0.33**); frequency categories (rho = 0.36**); duration categories (rho = 0.29*) | − |
| Criterion | Accelerometer, ActiReg (total energy expenditure); wear time: 7 d; site: chest and thigh; epoch: N.R. | Frequency (rho = 0.20); duration (rho = 0.23); frequency categories (rho = 0.22); duration categories (rho = 0.22) | − | ||
| Accelerometer, ActiReg (average physical activity level); wear time: 7 d; site: chest and thigh; epoch: N.R. | Frequency (rho = 0.02); duration (rho = 0.01); frequency categories (rho = 0.02); duration categories (rho = −0.02) | ||||
| MGLTEQ56 | 114; 59.6% girls; 12–14 y | Criterion | Accelerometer, ActiGraph; wear time: 7 d; site: right hip; epoch: 60 s | MPA (r = .23**); VPA (r = .13) | − |
| OPAQ57 | 51; 47.1% girls; N.R. | Criterion | Accelerometer, Caltrac; wear time: 4 d; site: waist; epoch: N.R. | VPA (r = .33*); MVPA (r = .32*); MPA (r = .01) | − |
| APARQ58 | 1072; 48% girls; 12.1 y; grade 8 | Convergent | 20-m shuttle run test | Energy expenditure boys (r = .15***); energy expenditure girls (r = .21***) | − |
| 954; 45% girls; 15.1 y; grade 10 | Energy expenditure boys (r = .14**); energy expenditure girls (r = .39***) | − | |||
| PYPAA59 | 100; 53% girls; 16.6 y | Convergent | BMI | Boys: h/wk (rho = −0.04), MET-h/wk (rho = −0.06), VPA-h/wk (rho = −0.13); girls: h/wk (rho = −0.09), MET-h/wk (rho = −0.13), VPA-h/wk (rho = −0.08) | − |
| 1-mile run | Boys: h/wk (rho = −0.18), MET-h/wk (rho = −0.20), VPA-h/wk (rho = −0.13); girls: h/wk (rho = −0.43*), MET-h/wk (rho = −0.47*), VPA-h/wk (rho = −0.45*) | − | |||
| Sit and reach | Boys: h/wk (rho = 0.15), MET-h/wk (rho = 0.15), VPA-h/wk (rho = 0.04); girls: h/wk (rho = 0.15), MET-h/wk (rho = 0.14), VPA-h/wk (rho = 0.02) | − | |||
| Pull-ups | Boys: h/wk (rho = 0.17), MET-h/wk (rho = 0.16), VPA-h/wk (rho = −0.01); girls: h/wk (rho = −0.06), MET-h/wk (rho = −0.06), VPA-h/wk (rho = −0.06) | − | |||
| Grip strength | Boys: h/wk (rho = 0.04), MET-h/wk (rho = 0.04), VPA-h/wk (rho = −0.02); girls: h/wk (rho = 0.05), MET-h/wk (rho = 0.14), VPA-h/wk (rho = 0.25) | − | |||
| cPAQ60 | 180; N.R.; N.R. | Convergent | 7-d PALog | Total PA duration, min/d: boys (rho = 0.72***); total PA duration, min/d: girls (rho = 0.54***); total PA duration, min/d: both (rho = 0.63***); Bland–Altman (data not shown): reasonably good agreement between the cPAQ and PALog, with most PA measures fell within a mean ± 2 SD | + |
| S-I PA M61 | 123; 38.2%; 14.7 (0.5) y | Criterion | Accelerometer, ActiGraph; wear time: 7 d; site: waist belt; epoch: 15 s | MVPA (accelerometer wear time of 480 MVPA min/d criteria; r = .43 [95% CI, .23 to .62]***); MVPA (accelerometer wear time of 600 MVPA min/d criteria; r = .44 [95% CI, .24 to .63]***) | − |
| MPA and VPA S Q54 | 57; 65% girls; 13.9 (1.7) y | Criterion | Accelerometer, CSA; wear time: 7 d; site: right hip; epoch: N.R. | VPA typical week (r = .31); VPA past week (r = .36); VPA composite (r = .37); 30-min MPA typical week (r = .20); 30-min MPA past week (r = .26); 30-min MPA composite (r = .26); 60-min MPA typical week (r = .46); 60-min MPA past week (r = .37); 60-min MPA composite (r = .47) | − |
| PACE +PAM54 | 138; 65% girls; 12.1 (0.9) y | Criterion | Accelerometer, CSA; wear time: 7 d; site: right hip; epoch: N.R. | MVPA (r = .40**) | − |
| SAYCARE PA Q A50 | Adolescents: 60; 55.7% girls; 11–18 y | Criterion | Accelerometer GTX3; wear time: 7 d; site: waist; epoch: 5 s | MPA (rho = 0.11); VPA (rho = 0.65*); total PA (rho = 0.88*); adolescent kappa agreement guidelines (kappa = .51*) | − |
| Fels PAQ62 | 229; 56.7%; 7–19 y | Criterion | Accelerometer, Actiwatch; wear time: 6 d; site: N.R.; epoch: 60 s | Elementary school: total score (r = .32), sport score (r = .32), leisure score (r = .28), work score (r = .08); middle school: total score (r = .12), sport score (r = .07), leisure score (r = .28), work score (r = −.13); high school: total score (r = .11), sport score (r = .34), leisure score (r = .20), work score (r = −.08) | − |
| MoMo63 | 109, 44% girls; 8–17 y | Criterion | Accelerometer, ActiGraph GT1M; wear time: N.R.; site: N.R.; epoch: N.R. | General PA (r = .29); PA in school (r = .04); recreational sports outside clubs (r = .10) | − |
| SB | |||||
| SAYCARE SB Q C64 | 93; 50% girls; 3–10 y | Criterion | Accelerometer, ActiGraph GT3X; wear time: 7 d; site: waist; epoch: 5 s | SB weekdays (min/d) (rho = −0.10); SB weekend days (min/d) (rho = 0.40**); SB total days (min/d) (rho = 0.07); SB weekdays (Bland–Altman: mean difference = −459.5 [100.9] min/d; LoA = −661.4 to −257.6 min/d); SB weekend (Bland–Altman: mean difference = −332.6 (138.5) min/d; LoA = −609.6 to −55.6 min/d); SB total days (Bland–Altman: mean difference = −420.2 [100.3] min/d; LoA = −620.9 to −219.5) | − |
| EAQT-SB65 | 245; 58.8%; 11–15 y | Convergent | Log of TV viewing and computer use daily during 7 d | Weekday TV (rho = 0.46***); weekend TV (rho = 0.37***); weekday average TV (rho = 0.47***); computer use (rho = 0.40**) | − |
| Helena SB Q66 | 2048; 59.2% girls; 12.5–17.5 y | Criterion | Accelerometer, ActiGraph GT1M, wear time: 7 d; site: lower back; epoch: N.R. | Girls: TV viewing—not significant, computer use—not significant, console games—not significant, internet nonstudy—P ≤ .05 between tertile 1 and tertile 2, internet for study—not significant; Boys: TV viewing—not significant, computer use—P ≤ .05 between tertile 1 and tertile 3 and tertile 2 and tertile 3, console games—not significant, internet nonstudy—P ≤ .05 between tertile 1 and tertile 3, internet for study—P ≤ .05 between tertile 1 and tertile 2 and between tertile 1 and tertile 3, study—P ≤ .05 between tertile 1 and tertile 3 and between tertile 2 and tertile 3, total SB weekdays—P ≤ .05 between tertile 1 and tertile 2 and between tertile 1 and tertile 3, total SB weekend days—P ≤ .05 between tertile 1 and tertile 2 and between tertile 1 and tertile 3 | − |
| SIT-Q-7d67 | 62; 58% girls; 15–16 y | Criterion | activPAL; wear time: N.R.; site: N.R.; epoch: N.R. | SB weekday total (rho = 0.42***); SB weekend day total (rho = 0.02); SB average day total (rho = 0.29*) | − |
| SAYCARE SB Q A64 | 94; 50% girls; 11–18 y | Criterion | Accelerometer, ActiGraph GT3X; wear time: 7 d; site: waist; epoch: 5 s | SB weekdays (min/d) (rho = −0.11); SB weekend days (min/d) (rho = 0.36**); SB total days (min/d) (rho = 0.05); SB weekdays (Bland–Altman: mean difference = −449.3 [87.0] min/d; LoA = −623.3 to −275.3 min/d); SB weekend days (Bland–Altman: mean difference = −399.7 [105.0] min/d; LoA = −609.6 to −189.7 min/d); SB total days (Bland–Altman: mean difference = −435.1 [66.3] min/d; LoA = −566.6 to −302.6) | − |
| YLSBQ68 | 1207; N.R.; 8–18 years | Criterion | Accelerometer, ActiGraph; wear time: 7 d; site: lower back; epoch: 2 s | Weekday sitting time (r = .36***); weekend sitting time (r = .20**); average day sitting time (r = .36**); average day (Bland–Altman: mean difference = 19.86 min/d; LoA = −280.04 to 319.76 min/d); average day (Bland–Altman: mean difference = 19.86 min/d; LoA = −280.04 to 319.76 min/d); weekdays (Bland–Altman: mean difference = 5.63 min/d; LoA = −246.17 to 257.43 min/d); weekend days (Bland–Altman: mean difference = 45.24 min/d; LoA = −298.54 to 389.02 min/d) | − |
| Sleep | |||||
| CCTQ69 | 85; N.R.; 4–11 y | Criterion | Accelerometer, Actiwatch Plus (AW4), wear time: 6–14 d; site: nondominant wrist; epoch: 60 s | Sleep period (weekday) d = 0.59***; sleep period (weekend day) d = 0.83*** | − |
| PA + SB | |||||
| GAQ70 | 68; 100% girls; 8–9 y | Criterion | Accelerometer, MTI/CSA; wear time: N.R.; site: N.R.; epoch: 60 s | 18 physical activities/past day (MET weighted score) (r = .28*); 18 physical activities/usual day (MET weighted score) (r = .30*) | − |
| ENERGY-C Q71 | 96; N.R.; 10–12 y | Convergent | Interview | Bike to school (d/wk) (ICC = .81; %agreement = 73%); bike to school (min/d) (ICC = .66; %agreement = 75%); walk to school (d/wk) (ICC = .84; %agreement = 75%); walk to school (min/d) (ICC = .59; %agreement = 74%); car to school (d/wk) (ICC = .84; %agreement = 80%); public transport to school (d/wk) (ICC = .81; %agreement = 96%); one sport (h/wk) (ICC = .71; %agreement = 50%); second sport (h/wk) (ICC = 1.00; %agreement = 36%); sport past day (h/wk) (ICC = .22; %agreement = 50%); computer use in free time (h/weekday) (ICC = .35); computer use in free time (h/weekend day) (ICC = .67; %agreement = 37%); TV (h/past day) (ICC = .70; %agreement = 44%); computer use in free time (h/past day) (ICC = .28; %agreement = 39%) | − |
| IPAQ55 | 67; 55% girls; 13–18 y | Convergent | VO2peak | VPA d/wk (rho = 0.26*); VPA min/d (rho = −0.32*); MPA d/wk (rho = −0.03); MPA min/d (rho = 0.13); walking days/wk (rho = 0.12); walking min/d (rho = −0.14); sitting min/d (rho = 0.18); 3 categories (“low,” “moderate,” and “high” activities; rho = 0.32**) | − |
| Criterion | Accelerometer, ActiReg (total energy expenditure); wear time: 7 d; site: chest and thigh | VPA d/wk (rho = 0.19); VPA min/d (rho = −0.14); MPA d/wk (rho = 0.07); MPA min/d (rho = 0.01); walking days/wk (rho = 0.15); walking min/d (rho = 0.24); sitting min/d (rho = −0.04); 3 categories (“low,” “moderate,” and “high” activities; rho = 0.09) | − | ||
| Accelerometer, ActiReg (average physical activity level); wear time: 7 d; site: chest and thigh | VPA d/wk (rho = 0.09); VPA min/d (rho = −0.08); MPA d/wk (rho = 0.05); MPA min/d (rho = 0.01); walking d/wk (rho = 0.13); walking min/d (rho = 0.43**); sitting min/d (rho = −0.29); 3 categories (“low,” “moderate,” and “high” activities; rho = −0.03) | − | |||
| SHAPES72 | 53; 47% girls; N.R. | Criterion | Accelerometer, ActiGraph AM7164; wear time: N.R.; site: right hip; epoch: 60 s | MVPA min/d (r = .44*); VPA min/d (r = .25); MPA min/d (r = .31*); energy expenditure daily average (r = .44***) | − |
| MARCA73 | 66; 50% girls; 9–13 y | Criterion | Accelerometer, ActiGraph; wear time: 1 d; site: N.R.; epoch: 60 s | PAL (r = .45**); MVPA min (r = .35)**; locomotion min (r = .37**) | − |
| peas@tees74 | 157; N.R.; N.R. | Criterion | Accelerometer, ActiGraph GT-256; wear time: 5 d; site: right hip; epoch: 60 s | MVPA min (rho = 0.23*); MVPA (LoA = −146 to 105 [95% CI, −31 to –11] min/d; bias = −21 min/d) | − |
| HSK75 | 103; 91% girls; 9–14 y | Convergent | HABITS questionnaire | Activity (rho = 0.38***); sedentary (rho = 0.65***) | − |
| PQPASB76 | 167; 71% girls; 6–10 and 13–14 y | Criterion | Accelerometer, ActiGraph Model AM7164; wear time: 7 d; epoch: 60 s | SB score (rho = 0.55***); watching TV/video/DVD (rho = 0.32***); sitting at a computer/playing Nintendo/electronic games (rho = 0.32***); doing homework (rho = 0.53***); reading (rho = 0.32); playing a musical instrument (rho = 0.12); playing quietly/other quiet activities (rho = −0.10); traveling by car/public transport (rho = 0.05); PA score (rho = 0.46**); time spent outdoors (rho = 0.33***); playing vigorously active indoors (rho = 0.30***); playing vigorously active outdoors (rho = 0.48***) | − |
| Cycling (rho = 0.19*); time spent breathing hard and sweating (rho = 0.15); attending sports training (outside school) (rho = −0.15) | − | ||||
| PA + SB + sleep | |||||
| Daughter Questionnaire77 | 69 girls; 8.5–12.7 y | Convergent | Activity diary | School day: sleeping (ICC = .52), sitting (ICC = .40), standing/light (ICC = .29), walking/moderate (ICC = .46), exercising/vigorous (ICC = .19), TV/VCR/video games (ICC = .38); weekend day: sleeping (ICC = .32), sitting (ICC = .32), standing/light (ICC = .42), walking/moderate (ICC = .25), exercising/vigorous (ICC = .23), TV/VCR/video games (ICC = .31) | − |
| Mother and Father Questionnaires77 | 69 girls; 8.5–12.7 y | Convergent | Activity diary | Mothers, school day: sleeping (ICC = −.35), sitting (ICC = .03), standing/light (ICC = −.22), walking/moderate (ICC = .18), exercising/vigorous (ICC = −.03), TV/VCR/video games (ICC = .54); mothers, weekend day: sleeping (ICC = −.37), sitting (ICC = .15), standing/light (ICC = −.24), walking/moderate (ICC = .39), exercising/vigorous (ICC = .4), TV/VCR/video games (ICC = .31); fathers, school day: sleeping (ICC = −.46), sitting (ICC = .04), standing/light (ICC = −.40), walking/moderate (ICC = .07), exercising/vigorous (ICC = −.04), TV/VCR/video games (ICC = .52); fathers, weekend day: sleeping (ICC = −.38), sitting (ICC = .10), standing/light (ICC = −.37), walking/moderate (ICC = .15), exercising/vigorous (ICC = .05), TV/VCR/video games (ICC = .40) | − |
Abbreviations: −, inadequate; +, adequate; ?, doubtful; 3DPAR, 3-d Physical Activity Recall; 7-d PALog, 7 day physical activity log; APARQ, Adolescent Physical Activity Recall Questionnaire; BMI, body mass index; CCTQ, Children’s ChronoType Questionnaire; CI, confidence interval; CLASS—Proxy and self, The Children’s Leisure Activities Study Survey—Proxy and self-reported; CLASS—Proxy, The Children’s Leisure Activities Study Survey—Proxy; cPAQ, computer-based physical activity questionnaire; CSA, Computer Science Application; EAQT-SB, Eating and Activity Questionnaire Trial—Sedentary Behavior questions; ENERGY-C Q, ENERGY-Child Questionnaire; Fels PAQ, Fels Physical Activity Questionnaire; GAQ, GEMS Activity Questionnaire; HBSC PAQ, Health Behavior in Schoolchildren Physical Activity Questionnaire; Helena SB Q, HELENA screen time-based sedentary behavior questionnaire; HPAQ, Habitual Physical Activity Questionnaire; HSK, Heart Smart Kids; ICC, intraclass correlation coefficient; IPAQ, International Physical Activity Questionnaire; LoA, limits of agreement; LPA, light physical activity; MARCA, multimedia activity recall for children and adolescents; MGLTEQ , Modified Godin Leisure-Time Exercise Questionnaire; MoMo, MoMo-Physical-Activity-Questionnaire for Adolescents; MPA and VPA S Q, moderate and Vigorous Physical Activity Screening Questionnaire; MPA, Moderate Physical Activity; MTI, Manufacturing Technology Inc., MVPA, moderate to vigorous physical activity; n, sample number; N.R., not reported; NSST, nonscreen sedentary time; O-O-S PAQ, Out-of-School Physical Activity Questionnaire; OPAQ, Oxford Physical Activity Questionnaire; PA, physical activity; PACE + PAM, PACE + Adolescent Physical Activity Measure; PAL, physical activity level; PQPASB, Parental Questionnaire for Physical Activity and Sedentary Behavior; PYPAA, past year physical activity in adolescents; SAPAC, Self-Administered Physical Activity Checklist; SAYCARE PA Q A, SAYCARE Physical Activity Questionnaire for adolescents; SAYCARE PA Q C, SAYCARE Physical Activity Questionnaire for children; SAYCARE SB Q A, South American Youth Cardiovascular and Environmental sedentary behavior questionnaire for adolescents; SAYCARE SB Q C, South American Youth Cardiovascular and Environmental sedentary behavior questionnaire for Children; SB, sedentary behavior; SHAPES, School Health Action, Planning and Evaluation System; S-I PA M, single-item physical activity measure; SIT-Q-7d, last-7-d sedentary behavior questionnaire; ST, sitting time; VPA, vigorous physical activity; YLSBQ, Youth Leisure-time Sedentary Behavior Questionnaire; YRBS, Youth Risk Behavior Survey. *P ≤0.05; **P ≤ 0.001; ***P ≤ 0.0001.
In PA questionnaires, the most frequently used criterion measure was the accelerometer (90%; 18/20). The strongest criterion validity was “Total PA” score from SAYCARE Physical Activity Questionnaire for adolescents50 (rho = 0.88), which was rated with “adequate” criterion validity. Convergent validity was measured in the Habitual Physical Activity Questionnaire,52 Health Behavior in Schoolchildren Physical Activity Questionnaire,55 Adolescent Physical Activity Recall Questionnaire,58 past year physical activity in adolescents,59 and computer-based physical activity questionnaire,60 with computer-based physical activity questionnaire being the only questionnaire showing “adequate” convergent validity against a 7-day PA log.60
Regarding SB, no questionnaire exhibited overall “adequate” criterion or convergent validity. The accelerometer was the criterion measure in all questionnaires that assessed criterion validity. The Eating and Activity Questionnaire Trial—Sedentary Behavior questions65 was the only questionnaire evaluated against a convergent measure (7-d log of television viewing and computer use). None of the scores from the questionnaire showed “adequate” criterion or convergent validity.
The only sleep questionnaire included69 was evaluated against a criterion measure (accelerometer), and its validity was considered “inadequate.”
Concerning the questionnaires combining PA and SB, none showed overall criterion or convergent validity. The accelerometer was the criterion measure used to assess criterion validity, in all questionnaires. Regarding criterion validity, none of the questionnaires were rated with “adequate” criterion validity. Convergent validity was measured in the ENERGY-Child Questionnaire,71 International Physical Activity Questionnaire,55 and Heart Smart Kids.75 Some scores of the ENERGY-Child Questionnaire71 were considered to have “adequate” convergent validity, against an interview.
Regarding questionnaires combining all movement behaviors, both were evaluated against a convergent measure (diary), and only the sleeping score from the Daughter Questionnaire77 showed “adequate” validity (ICC = .52).
Concerning the validity of the various domains of the movement behaviors (eg, the different PA intensities), there were no clear differences between domains and no patterns were identified favoring one domain over another.
Reliability and Measurement Error
Table 3 shows the summary of the questionnaires’ reliability results. The time between test and retest ranged from 1 day to 1 year. The most often used statistical approaches to assess reliability were correlations (Pearson and Spearman) and ICCs. Measurement error was evaluated only in the multimedia activity recall for children and adolescents (MARCA)73 questionnaire. The overall measurement error quality for the MARCA was rated as “doubtful” due to the minimal important change not reported.
Reliability Results
| Questionnaire | Sample | Reliability | Overall quality | |
|---|---|---|---|---|
| n; %girls; age mean (SD) or age range, y | Time between test and retest | Results | ||
| PA | ||||
| CLASS—Proxy30 | 58; 63% girls; 5–6 y | At least 14 d | Total MPA frequency (ICC = .74***); total MPA duration (ICC = .49***); overall total PA frequency (ICC = .83***); overall total PA duration (ICC = .76***) | + |
| SAYCARE PA Q C50 | 49.8% girls; 3–10 y | 15 d | PA commuting (rho = 0.28); PA school (rho = 0.31*); leisure PA (rho = 0.33*); MPA (rho = 0.37*); VPA (rho = 0.89*); total PA (rho = 0.56*); agreement guidelines kappa = .32 | − |
| O-O-S PAQ51 | 151; N.R.; 11 y | 30 d | MVPA duration (ICC = .65); MVPA frequency (ICC = .64) | − |
| HPAQ52 | 94; 68.1% girls; 11–16 y | 2 wk | Weekly physical activity score (ICC = .61); yearly physical activity score (ICC = .68) | − |
| 3DPAR53 | 92; N.R.; 11–14 y | 1 d | Overall period MVPA (r = .67*); Monday MVPA (r = .66*); Sunday MVPA (r = .49*); overall period VPA (r = .63*); Monday VPA (r = .73*); Sunday VPA (r = .37) | − |
| YRBS54 | 125; 52.5% girls; 12.2 (0.6) y | 15 d | MPA item (ICC = .51*); VPA item (ICC = .46*) | − |
| SAPAC53 | 65; N.R.; 11–14 y | 1 d | Overall period MVPA (r = .68*); Monday MVPA (r = .71*); Sunday MVPA (r = .63*); overall period VPA (r = .83*); Monday VPA (r = .69*); Sunday VPA (r = .82*); overall period MVPA (r = .68*) | − |
| HBSC PAQ55 | 71; 56.3% girls; 13–18 y | 8–12 d | Frequency (ICC = .73); duration (ICC = .71) | + |
| MGLTEQ56 | 250; 58.8% girls; 12–14 y | 1 wk | Mild-intensity school time (r = .48**; %agreement = 35.6%; kappa = .40); MPA school time (r = .51**; %agreement = 27.6%; kappa = .36); VPA school time (r = .68**; %agreement = 33.2%; kappa = .49); mild-intensity summertime (r = .56**; %agreement = 34.8%; kappa = .43); MPA summertime (r = .50**; %agreement = 26.4%; kappa = .38); VPA summertime (r = .56**; %agreement = 24.8%; kappa = .37) | − |
| OPAQ57 | 87; 44.8% girls; N.R. | 2 wk | MPA (ICC = .76*); VPA (ICC = .80*); MVPA (ICC = .91*) | + |
| APARQ58 | 121; 48% girls, 12.7 y | 2 wk | Grade 8, boys: summer total energy expenditure (ICC = .30), summer organized energy expenditure (ICC = .39), summer nonorganized energy expenditure (ICC = .30), winter total energy expenditure (ICC = .49), winter organized energy expenditure (ICC = .64), winter nonorganized energy expenditure (ICC = .54); grade 8, girls: summer total energy expenditure (ICC = .52), summer organized energy expenditure (ICC = .50), summer nonorganized energy expenditure (ICC = .48), winter total energy expenditure (ICC = .36), winter organized energy expenditure (ICC = .41), winter nonorganized energy expenditure (ICC = .33); grade 10, boys: summer total energy expenditure (ICC = .79), summer organized energy expenditure (ICC = .52), summer nonorganized energy expenditure (ICC = .68), winter total energy expenditure (ICC = .52), winter organized energy expenditure (ICC = .40), winter nonorganized energy expenditure (ICC = .65); grade 10, girls: summer total energy expenditure (ICC = .86), summer organized energy expenditure (ICC = .87), summer nonorganized energy expenditure (ICC = .86), winter total energy expenditure (ICC = .91), winter organized energy expenditure (ICC = .63), winter nonorganized energy expenditure (ICC = .90) | − |
| PYPAA59 | 100; 53% girls; 16.6 y | 1 mo | h/wk (rho = 0.79); MET-h/wk (rho = 0.85**); VIG-h/wk (rho = 0.91**) | − |
| 1 y | h/wk (rho = 0.66**); MET-h/wk (rho = 0.72**); VIG-h/wk (rho = 0.72**) | |||
| cPAQ60 | 35 Malaysian boys; N.R. | 2 wk | Total PA, h/wk (ICC = .90*); LPA (ICC = .93*); MPA (ICC = .43); VPA (ICC = .68*) | − |
| 45 Chinese boys; N.R. | Total PA, h/wk (ICC = .91*); LPA (ICC = .63*); MPA (ICC = .79*); VPA (ICC = .87*) | |||
| 59 Malaysian girls; N.R. | Total PA, h/wk (ICC = .51*); LPA (ICC = .26); MPA (ICC = .71*); VPA (ICC = .71*) | |||
| 64 Chinese girls; N.R. | Total PA, h/wk (ICC = .84*); LPA (ICC = .75*); MPA (ICC = .86*); VPA (ICC = .69*) | |||
| S-I PA M61 | 123; 38.2%; 14.7 (0.5) y | 2 wk | MVPA (ICC = .75***) | + |
| MPA and VPA S Q54 | 250; 56% girls; 14.6 (1.4) y | 2 wk | VPA typical week (ICC = .67); VPA past week (ICC = .66); VPA composite (ICC = .76); 30-min MPA typical week (ICC = .55); 30-min MPA past week (ICC = .64); 30-min MPA composite (ICC = .71); 60-min MPA typical week (ICC = .65); 60-min MPA past week (ICC = .72); 60-min MPA composite (ICC = .79) | − |
| PACE + PAM54 | 73; 65% girls; 12.1 (0.9) y | 24 h to 1 month | MVPA (ICC = .77) | + |
| SAYCARE PA Q A50 | 177; 58.3% girls; 11–18 y | PA commuting (rho = 0.51*); PA school (rho = 0.63*); leisure PA (rho = 0.68*); MPA (rho = 0.36*); VPA (rho = 0.93*); total PA (rho = 0.60*); agreement guidelines (kappa = .56*) | − | |
| CLASS—Proxy and self30 | 111; 27% girls; 10–12 y | 7 d (self-report) and at least 14 d (proxy-report) | Total MPA frequency (proxy: ICC = .67***; self-report: ICC = .57***); total MPA duration (proxy: ICC = .58***; self-reported: ICC = .37**); overall total PA frequency (proxy: ICC = .69***; self-reported: ICC = .36**); overall total PA duration (proxy: ICC = .74***; self-reported: ICC = .24) | − |
| Fels PAQ62 | 229; 56.7%; 7–19 y | 6 d | Elementary school: total score (r = .70), sport score (r = .62), leisure score (r = .54), work score (r = .48); middle school: total score (r = .62), sport score (r = .64), leisure score (r = .49), work score (r = .68); high school: total score (r = .71), sport score (r = .76), leisure score (r = .65), work score (r = .58) | − |
| MoMo63 | 109; 44% girls; 8–17 y | 1 wk | General PA (ICC = .74**); PA in school (ICC = .60**); recreational sports outside clubs (ICC = .64**) | − |
| SB | ||||
| SAYCARE SB Q C64 | 55; 40% girls; 3–10 y | 2 wk | Total SB time weekdays (min/d) (rho = 0.45**); total SB time weekend day (min/d) (rho = 0.51**); total SB time total days (min/d) (rho = 0.70*); meeting ≤120 min/d (%) weekdays (kappa = .52*); meeting ≤120 min/d (%) weekend days (kappa = .83*); meeting ≤120 min/d (%) total days (kappa = .83*) | − |
| EAQT-SB65 | 245; 58.8%; 11–15 y | 1 wk | Weekday TV (school period) (rho = 0.68***; kappa = .55; %agreement = 48.16); weekend TV (school period) (rho = 0.61***; kappa = .51; %agreement = 45.31); weekend TV (summer) (rho = 0.58***; kappa = .46; %agreement = 40.82); weekday TV (summer) (rho = 0.55***; kappa = .42; %agreement = 35.10); computer use (rho = 0.60***; kappa = .49; %agreement = 50.20) | − |
| Helena SB Q66 | 183; 57%; 12.5–17.5 y | 1 wk | TV week (kappa = .71); computer week (kappa = .82); computer week (kappa = .82); video games week (kappa = .82); internet nonstudy week (kappa = .86); internet study week (kappa = .46); study week (kappa = .73); TV weekend (kappa = .68); computer weekend (kappa = .79); video games weekend (kappa = .81); internet nonstudy weekend (kappa = .71); internet study weekend (kappa = .33) | + |
| SIT-Q-7d67 | 20; 42% girls; 15–16 y | 6 d | SB weekday total (ICC = .37); internet study weekend (kappa = .33); SB weekend day total (ICC = .67); SB average day total (ICC = .45) | − |
| SAYCARE SB Q A64 | 106; 61%; 11–18 y | Total SB time weekdays (min/d) (rho = 0.39*); total SB time weekend day (min/d) (rho = 0.34**); total SB time total days (min/d) (rho = 0.50*); meeting ≤120 min/d (%) weekdays (kappa = .15*); meeting ≤120 min/d (%) (weekend days kappa = .08*); meeting ≤120 min/d (%) total days (kappa = .17*) | − | |
| YLSBQ68 | 194; 50.5%; 10–18 y | 1 wk | Weekday: total sedentary time (ICC = .75*), screen time (ICC = .75*), watching TV/videos (ICC = .72*; kappa = .64**), playing computer/video games (ICC = .55*; kappa = .54**), internet surfing (ICC = .73*; kappa = .70**), nonscreen sedentary time—educational (ICC = .70), doing homework/study with computer (ICC = .62*; kappa = .51**), doing homework/study without computer (ICC = .58*; kappa = .53**), reading for fun (ICC = .83*; kappa = .74**), nonscreen sedentary time—social (ICC = .70*), sitting and talking (ICC = .34*; kappa = .27**), listening to music (ICC = .64*; kappa = .61**), talking on the telephone (ICC = .79*; kappa = .73**), nonscreen sedentary time—others (ICC = .57*), sitting to rest (ICC = .41*; kappa = .44**), doing cognitive hobbies (ICC = .46*; kappa = .43**), traveling on motorized transport (ICC = .60*; kappa = .54**); weekend day: total sedentary time (ICC = .72*), screen time (ICC = .74*), watching TV/videos (ICC = .66; kappa = .57**), playing computer/video games (ICC = .65*; kappa = .59**), internet surfing (ICC = .71*; kappa = .65**), nonscreen sedentary time—educational (ICC = .64*), doing homework/study with computer (ICC = .54*; kappa = .53**), doing homework/study without computer (ICC = .50*; kappa = .47**), reading for fun (ICC = .69*; kappa = .64**), nonscreen sedentary time—social (ICC = .67*), sitting and talking (ICC = .46*; kappa = .39**), listening to music (ICC = .68*; kappa = .61**), talking on the telephone (ICC = .77*; kappa = .70**), nonscreen sedentary time—others (ICC = .58*); sitting to rest (ICC = .52*; kappa = .51**), doing cognitive hobbies (ICC = .55*; kappa = .50**), traveling on motorized transport (ICC = .56*; kappa = .49**); average day: total sedentary time (ICC = .76*), screen time (ICC = .77*), watching TV/videos (ICC = .75*), playing computer/video games (ICC = .60*), internet surfing (ICC = .75*), nonscreen sedentary time—educational (ICC = .71*), doing homework/study with computer (ICC = .66*), doing homework/study without computer (ICC = .61*), reading for fun (ICC = .82*), nonscreen sedentary time—social (ICC = .72*), sitting and talking (ICC = .40*), listening to music (ICC = .66*), talking on the telephone (ICC = .82*), nonscreen sedentary time—others (ICC = .63*), sitting to rest (ICC = .50*), doing cognitive hobbies (ICC = .54*), traveling on motorized transport (ICC = .66*) | − |
| Sleep | ||||
| CCTQ69 | 43; N.R.; 4–11 y | 20 d | Sleep period (weekdays) (r = .94); sleep period (weekend days) (r = .79); time of lights-off (weekdays) (r = .90); time of lights-off (weekend days) (r = .85); sleep onset (weekdays) (r = .92); sleep onset (weekend days) (r = .85); wake-up time (weekdays) (r = .89); wake-up time (weekend days) (r = .91) | + |
| PA + SB | ||||
| GAQ70 | 67; 100% girls; 8–9 y | 4 d | 28 activities—past day (r = .78***); 18 activities—past day (r = .70***); TV watching—past day (r = .35***); other sedentary—past day (r = .47***); 28 activities—usual day (r = .82***); 18 activities—usual day (r = .79***); TV watching—usual day (r = .28***); other sedentary—usual day (r = .48***) | − |
| ENERGY-C Q71 | 730; N.R.; 10–12 y | 1 wk | Bike to school (d/wk) (ICC = .94; %agreement = 73%); bike to school (min/d) (ICC = .81; %agreement = 85%); walk to school (d/wk) (ICC = .91; %agreement = 81%); walk to school (min/d) (ICC = .70; %agreement = 70%); car to school (d/wk) (ICC = .91; %agreement = 84%); public transport to school (d/wk) (ICC = .88; %agreement = 96%), first sport (h/wk) (ICC = .74; %agreement = 55%); second sport (h/wk) (ICC = 1.00; %agreement = 43%); sport past day (h/wk) (ICC = .22; %agreement = 28%); computer use in free time (h/weekday) (ICC = .67; %agreement = 41%); computer use in free time (h/weekend days) (ICC = .65; %agreement = 38%); TV (h/past day) (ICC = .68; %agreement = 36%); computer use in free time (h/past day) (ICC = .54; %agreement = 51%) | − |
| IPAQ55 | 71; 56.3% girls; 13–18 y | 8–12 d | VPA d/wk (ICC = .54); VPA min/d (ICC = .30); MPA d/wk (ICC = .55); MPA min/d (ICC = .34); walking d/wk (ICC = .62); walking min/d (ICC = .10); sitting min/d (ICC = .27) | − |
| SHAPES72 | 460; N.R.; N.R. | 1 wk | Weekly VPA (h) (kappa = .40); weekly MPA (h) (kappa = .33); weekly MVPA (h) (kappa = .37); weekly screen time (h) (kappa = .51); PA level (inactive, moderately active, active) (kappa = .58) | − |
| MARCA73 | 37; 44% girls; 9–13 y | Same day (285 min) | PA level (ICC = .93); MVPA min (ICC = .94); locomotion min (ICC = .88; SEM = 0.26.1; upper LoA = 79.2; lower LoA = −65.4) | + |
| Measurement error: PA level (SEM = 0.11; upper LoA = 0.3; lower LoA = −0.30; bias = + 0.001); MVPA (SEM = 18.9; upper LoA = 51.2; lower LoA = −53.4; bias = −1.1); locomotion (SEM = 0.26.1; upper LoA = 79.2; lower LoA = −65.4; bias = + 6.9) | ? | |||
| peas@tees74 | 42; 48% girls; N.R. | 2 d | MVPA (ICC = .69) | − |
| HSK75 | 35; N.R.; 9–14 y | 8 wk | Activity (rho = 0.78***); sedentary (rho = 0.38*) | − |
| PQPASB76 | 125; 53% girls; 6–10 and 13–14 y | 2 wk | Watching TV/video/DVD (rho = 0.60*); sitting at a computer/playing Nintendo/electronic games (ICC = .61*); doing homework (ICC = .56*); reading (ICC = .64*); playing a musical instrument (ICC = .34*); playing quietly/other quiet activities (ICC = .42*); traveling by car/public transport (ICC = .49*); playing vigorously active indoors (ICC = .41*); playing vigorously active outdoors (ICC = .43*); cycling (ICC = .64*) | − |
| PA + SB + sleep | ||||
| Daughter Questionnaire77 | 69 girls; 8.5–12.7 y | 12–16 d | School day: sleeping (ICC = .51), sitting (ICC = .35), standing/light (ICC = .28), walking/moderate (ICC = .48), exercising/vigorous (ICC = .36), TV/VCR/video games (ICC = .84); weekend day: sleeping (ICC = .68); sitting (ICC = .36); standing/light (ICC = .43); walking/moderate (ICC = .32); exercising/vigorous (ICC = .32); TV/VCR/video games (ICC = .81) | − |
| Mother and Father Questionnaires77 | 69 girls; 8.5–12.7 y | 12–28 d | Mothers, school day: sleeping (ICC = .66), sitting (ICC = .21), standing/light (ICC = .11), walking/moderate (ICC = .28), exercising/vigorous (ICC = .72), TV/VCR/video games (ICC = .45); mothers, weekend day: sleeping (ICC = .71), sitting (ICC = .25), standing/light (ICC = .32), walking/moderate (ICC = .33), exercising/vigorous (ICC = .65), TV/VCR/video games (ICC = .82); fathers, school day: sleeping (ICC = .14), sitting (ICC = .20), standing/light (ICC = .32), walking/moderate (ICC = .24), exercising/vigorous (ICC = .75), TV/VCR/video games (ICC = .86); fathers, weekend day: sleeping (ICC = .05), sitting (ICC = .24), standing/light (ICC = .12); walking/moderate (ICC = .13), exercising/vigorous (ICC = .72), TV/VCR/video games (ICC = .79) | − |
Abbreviations: −, inadequate; +, adequate; ?, doubtful; 3DPAR, 3-d Physical Activity Recall; APARQ, Adolescent Physical Activity Recall Questionnaire; CCTQ, Children’s ChronoType Questionnaire; CLASS—Proxy and self, The Children’s Leisure Activities Study Survey—Proxy and self-reported; CLASS—Proxy, The Children’s Leisure Activities Study Survey—Proxy; cPAQ, computer-based physical activity questionnaire; D, duration; EAQT-SB, Eating and Activity Questionnaire Trial—Sedentary Behavior questions; ENERGY-C Q, ENERGY-Child Questionnaire; Fels PAQ, Fels Physical Activity Questionnaire; GAQ, GEMS Activity Questionnaire; HBSC PAQ, Health Behavior in Schoolchildren Physical Activity Questionnaire; Helena SB Q, HELENA screen time-based sedentary behavior questionnaire; HPAQ, Habitual Physical Activity Questionnaire; HSK, Heart Smart Kids; ICC, intraclass correlation coefficient; IPAQ, International Physical Activity Questionnaire; LoA, limits of agreement; LPA, light physical activity; MARCA, multimedia activity recall for children and adolescents; MGLTEQ , Modified Godin-Leisure-Time Exercise Questionnaire; MoMo, MoMo-Physical-Activity-Questionnaire for Adolescents; MPA and VPA S Q, moderate and Vigorous Physical Activity Screening Questionnaire; MPA, Moderate Physical Activity; MVPA, moderate to vigorous physical activity; n, sample number; NA, not applicable; N.R., not reported; NSST, nonscreen sedentary time; O-O-S PAQ, Out-of-School Physical Activity Questionnaire; OPAQ, Oxford Physical Activity Questionnaire; PA, physical activity; PACE + PAM, PACE + Adolescent Physical Activity Measure; PAL, physical activity level; PQPASB, Parental Questionnaire for Physical Activity and Sedentary Behavior; PYPAA, past year physical activity in adolescents; SAPAC, Self-Administered Physical Activity Checklist; SAYCARE PA Q A, SAYCARE Physical Activity Questionnaire for adolescents; SAYCARE PA Q C, SAYCARE Physical Activity Questionnaire for children; SAYCARE SB Q A, South American Youth Cardiovascular and Environmental sedentary behavior questionnaire for adolescents; SAYCARE SB Q C, South American Youth Cardiovascular and Environmental sedentary behavior questionnaire for Children; SB, sedentary behavior; SHAPES, School Health Action, Planning and Evaluation System; S-I PA M, single-item physical activity measure; SIT-Q-7d, last-7-d sedentary behavior questionnaire; VIG, vigorous; VPA, vigorous physical activity; YLSBQ, Youth Leisure-time Sedentary Behavior Questionnaire; YRBS, Youth Risk Behavior Survey.
Seven questionnaires showed overall “adequate” reliability: 5 PA questionnaires (the Children’s Leisure Activities Study Survey—Proxy,30 Health Behavior in Schoolchildren Physical Activity Questionnaire,55 Oxford Physical Activity Questionnaire,57 single-item physical activity measure,61 and PACE + adolescent physical activity measure54); 1 SB questionnaire (HELENA screen time-based sedentary behavior questionnaire66); and the sleep questionnaire (Children’s ChronoType Questionnaire69).
Risk of Bias
Table 4 shows the summary of the risk of bias (RoB) results (details provided in Supplementary Material S5 [available online]). The overall RoB rating for criterion validity was “very low” for 92% of the criterion validity studies. The main cause for the high RoB was the lack of reporting correlation coefficients results. For convergent validity, 72.7% of the studies were classified with overall “high” RoB, with the main reason being insufficient or unknown measurement properties of the comparator. For the overall reliability RoB, 27.3% of the studies were rated with a “very low” RoB; the main reason was an inappropriate interval between test and retest, the absence of similar test conditions in both measurements, and the statistical methods used (eg, correlations instead of ICCs). For the overall RoB rating for measurement error, the MARCA73 questionnaire was classified with “very low” RoB.
Summary of Results
| Questionnaire | Reliability quality | Content validity quality | Risk of bias | ||||
|---|---|---|---|---|---|---|---|
| Validity quality | Validity | Reliability | |||||
| Criterion | Convergent | Criterion | Convergent | ||||
| PA | |||||||
| CLASS—Proxy30 | − | NA | + | CD | 1 | NA | 1 |
| SAYCARE PA Q C50 | − | NA | − | + | 1 | NA | 3 |
| O-O-S PAQ51 | − | NA | − | + | 1 | NA | 2 |
| HPAQ52 | NA | −/−/−/−/− | − | − | 1 | 4 | 2 |
| 3DPAR53 | −/− | NA | − | + | 1 | NA | 3 |
| YRBS54 | − | NA | − | + | 1 | NA | 4 |
| SAPAC53 | −/− | NA | − | CD | 1 | NA | 3 |
| HBSC PAQ55 | −/− | − | + | − | 1 | 4 | 4 |
| MGLTEQ56 | − | NA | − | − | 1 | NA | 3 |
| OPAQ57 | − | NA | + | + | 1 | NA | 3 |
| APARQ58 | NA | − | − | + | NA | 4 | 1 |
| PYPAA59 | NA | −/−/−/−/−/−/−/−/− | − | − | NA | 4 | 3 |
| cPAQ60 | NA | + | − | CD | NA | 2 | 1 |
| S-I PA M61 | − | NA | + | + | 1 | NA | 2 |
| MPA and VPA S Q54 | − | NA | − | + | 1 | NA | 2 |
| PACE + PAM54 | − | NA | + | + | 1 | NA | 3 |
| SAYCARE PA Q A50 | − | NA | − | + | 1 | NA | 3 |
| CLASS—Proxy and self30 | − | NA | − | CD | 1 | NA | 1 |
| Fels PAQ62 | − | NA | − | − | 1 | NA | 2 |
| MoMo63 | − | NA | − | − | 1 | NA | 1 |
| SB | |||||||
| SAYCARE SB Q C64 | − | NA | − | + | 1 | NA | 3 |
| EAQT-SB65 | NA | − | − | − | NA | 4 | 3 |
| Helena SB Q66 | NA | + | − | 4 | NA | 1 | |
| SIT-Q-7d67 | − | NA | − | + | 1 | NA | 2 |
| SAYCARE SB Q A64 | − | NA | − | + | 1 | NA | 3 |
| YLSBQ68 | − | NA | − | − | 1 | NA | 1 |
| Sleep | |||||||
| CCTQ69 | + | NA | + | + | 4 | NA | 3 |
| PA + SB | |||||||
| GAQ70 | − | NA | − | − | 1 | NA | 3 |
| ENERGY-C Q71 | NA | − | − | + | NA | 4 | 1 |
| IPAQ55 | −/− | − | − | + | 1 | 4 | 4 |
| SHAPES72 | − | NA | − | + | 1 | NA | 1 |
| MARCA73 | − | NA | + | + | 1 | NA | 3 |
| peas@tees74 | − | NA | − | + | 1 | NA | 1 |
| HSK75 | − | NA | − | + | NA | 4 | 3 |
| PQPASB76 | − | NA | − | + | 1 | NA | 3 |
| PA + SB + sleep | |||||||
| Daughter Questionnaire77 | NA | − | − | CD | NA | 3 | 1 |
| Mother and Father Questionnaires77 | NA | − | − | CD | NA | 3 | 3 |
Abbreviations: −, inadequate; +, adequate; ?, doubtful; 3DPAR, 3-d Physical Activity Recall; APARQ, Adolescent Physical Activity Recall Questionnaire; CCTQ, Children’s ChronoType Questionnaire; CD, cannot be determined; CLASS—Proxy and self, The Children’s Leisure Activities Study Survey—Proxy and self-reported; CLASS—Proxy, The Children’s Leisure Activities Study Survey—Proxy; cPAQ, computer-based physical activity questionnaire; EAQT-SB, Eating and Activity Questionnaire Trial—Sedentary Behavior questions; ENERGY-C Q, ENERGY-Child Questionnaire; Fels PAQ, Fels Physical Activity Questionnaire; GAQ, GEMS Activity Questionnaire; HBSC PAQ, Health Behavior in Schoolchildren Physical Activity Questionnaire; Helena SB Q, HELENA screen time-based sedentary behavior questionnaire; HPAQ, Habitual Physical Activity Questionnaire; HSK, Heart Smart Kids; IPAQ, International Physical Activity Questionnaire; LPA, light physical activity; MARCA, multimedia activity recall for children and adolescents; MGLTEQ , Modified Godin-Leisure-Time Exercise Questionnaire; MoMo, MoMo-Physical-Activity-Questionnaire for Adolescents; MPA and VPA S Q, moderate and Vigorous Physical Activity Screening Questionnaire; MPA, Moderate Physical Activity; MVPA, moderate to vigorous physical activity; n, sample number; NA, not applicable; NSST, nonscreen sedentary time; O-O-S PAQ, Out-of-School Physical Activity Questionnaire; OPAQ, Oxford Physical Activity Questionnaire; PA, physical activity; PACE + PAM, PACE + Adolescent Physical Activity Measure; PAL, physical activity level; PQPASB, Parental Questionnaire for Physical Activity and Sedentary Behavior; PYPAA, past year physical activity in adolescents; SAPAC, Self-Administered Physical Activity Checklist; SAYCARE PA Q A, SAYCARE Physical Activity Questionnaire for adolescents; SAYCARE PA Q C, SAYCARE Physical Activity Questionnaire for children; SAYCARE SB Q A, South American Youth Cardiovascular and Environmental sedentary behavior questionnaire for adolescents; SAYCARE SB Q C, South American Youth Cardiovascular and Environmental sedentary behavior questionnaire for Children; SB, sedentary behavior; SHAPES, School Health Action, Planning and Evaluation System; S-I PA M, single-item physical activity measure; SIT-Q-7d, last-7-d sedentary behavior questionnaire; VPA, vigorous physical activity; YLSBQ, Youth Leisure-time Sedentary Behavior Questionnaire; YRBS, Youth Risk Behavior Survey. Note: 1, very low risk of bias; 2, low risk of bias; 3, medium risk of bias; 4, high risk of bias.
Summary of Findings
Table 4 summarizes the results of the content, convergent and criterion validity, reliability, measurement error, and RoB for each measurement property.
Discussion
This systematic review described questionnaires measuring sleep, SB, and PA, or its combination, in children and adolescents, and included 30 self-reported questionnaires and 7 proxy-reported. Contentwise, the questionnaires varied in the assessed domains, response method, measurement units, scores, recall, and assessment periods; such diversity between questionnaires hindered comparisons between them and the choice of some over others. Concerning validity, none of the questionnaires showed overall “adequate” criterion validity, and the RoB was “very low” in 92% of the studies with criterion validity. Only one questionnaire showed “adequate” convergent validity,60 and 72.7% of the studies were rated with an overall “high” RoB. Seven questionnaires showed “adequate” reliability and 27.3% of the studies were rated with a “very low” RoB. However, no questionnaires showed “adequate” criterion validity and reliability simultaneously.
The proxy-reported questionnaires were mostly directed at parents or caregivers of children aged 3–10 years, and only the The Children’s Leisure Activities Study Survey—Proxy30 and Children’s ChronoType Questionnaire69 showed “adequate” reliability. None of the proxy-reported questionnaires showed “adequate” validity. Indeed, the younger the children, the more difficult it is for them to report past movement behaviors.17 This review did not find proxy reports directed at toddlers’ parents or caregivers. Considering that the 24-hour movement guidelines have been developed for young children4,6,7, there is a need for proxy reports with adequate validity and reliability for this age group.
Following the cutoff points suggested by COSMIN,37 the quality of the questionnaires’ validity was frequently considered “inadequate.” This may happen because questionnaires are known to have several limitations (eg, measurement error and reporting bias due to social desirability, language, interpretation, questionnaire’s complexity, age, and seasonal variation8,18,19,22), particularly when applied to children and adolescents, where issues related to recall or comprehension of the questionnaires,17 and the unstable patterns of movement behaviors throughout the day,24,25 may be more present than in adults. For these reasons, proxy reports by parents and other caregivers may be a possible solution,27–30 despite the known difficulties of this method.78
Regarding reliability, the overall quality of the results was frequently “inadequate.” Furthermore, the statistical procedures used were often considered “inadequate,” especially due to the commonly use of Pearson or Spearman correlations, instead of ICCs or kappas, as it has been suggested.79 Seven questionnaires showed overall “adequate” reliability (5 PA questionnaires30,54,55,57,61; 1 SB questionnaire,66 and the sleep questionnaire69). However, none of these questionnaires showed “adequate” validity; a required criteria for questionnaire validation purposes (ie, a questionnaire must present at least “adequate” overall validity and reliability37,41). Low validity and reliability were also found in other similar reviews,8,9,31–34 which also reported several methodological limitations of the included questionnaires. Furthermore, if the development method and the measurement properties are poor or not well clarified, the risk of misclassification, bias, and inaccurate results is high.23
Our results align with a recently published systematic review80 on measurement properties of 24-hour movement behavior questionnaires, in adults and older adults, which reported several methodologic limitations in the included questionnaires, showing inadequate validity and reliability scores and insufficient measurement properties.
From a public health and epidemiology point of view, given the intrinsic and empirical interactions between sleep, SB, and PA, there is a tangible need to develop accurate self-reported and proxy-reported questionnaires, to measure movement behaviors levels in an integrated fashion. These will allow researchers, public health professionals, and policy makers to push forward the (1) monitoring of 24-hour movement behaviors, (2) assessing 24-hour movement guidelines compliance, (3) analyzing the health-related associations of movement behaviors combinations, and (4) promoting the healthy 24-hour movement behaviors. The same concern has been raised with the launch of the new World Health Organization PA and SB guidelines for adults.81
Limitations and Strengths
This review described and appraised questionnaires’ content and measurement properties following the best practices proposed by the COSMIN guidelines, which is a strength of our work. The eligibility criterion (eg, minimum of 50 participants for validity studies; inclusion of questionnaires with both validity and reliability) is another strength of our work, as it excluded questionnaires with specific methodological shortcomings or with incomplete validation processes. Using the cutoff points proposed by COSMIN to evaluate the quality of measurement properties elevated the demanding of the appraisal of content and measurement properties of the included questionnaires. Also, to the best of our knowledge, this review comprises the largest number of questionnaires assessing movement behaviors, in children and adolescents, including an extensive description of the questionnaires’ content.
In terms of limitations, comparing questionnaires’ measurement properties is complex, mainly due to the diversity of the methodologies and results, including different domains, scores, recall periods, comparison measures, reporting units, and statistics. The use of the COSMIN guidelines may have led, at least in part, to loss of information and dichotomization (eg, adequate or inadequate) due to the mechanistic way of analyzing the data. For example, a given questionnaire may be classified as having an overall “inadequate” validity; however, the questionnaire might be appropriate to apply when the intention aim is to evaluate specific constructs from the items with “adequate” validity scores. Finally, as we followed an adaptation of the COSMIN guidelines and other reviews have followed other assumptions and guidelines with different cutoffs, direct comparisons between reviews should be carefully done.
Conclusion
The questionnaires included in this review showed considerable diversity in content and, for the most part, inadequate validity and reliability scores. Existing questionnaires have insufficient measurement properties, and none were developed considering the 24-hour movement behavior paradigm. These results emphasize the intricacy of assessing movement behaviors in isolation and in combination and highlight the need for better questionnaires measuring each movement behavior and new questionnaires to measure 24-hour movement behavior combinations. Additionally, the existence of 24-hour movement guidelines raises the need to adapt or develop de novo self- and proxy-reported measures to assess 24-hour movement behavior levels and patterns, as well as guidelines compliance, in children and adolescents.
The current review confirms previous systematic reviews’ findings showing that most questionnaires have insufficient measurement properties and extends it to questionnaires assessing more than one movement behavior. Based on our results regarding the included questionnaires’ measurement properties and content, we cannot recommend one or a set of questionnaires to accurately measure children and adolescents’ movement behaviors, considering the new 24-hour movement paradigm in youth.
Acknowledgments
This review was registered on the PROSPERO database (CRD42021235171). The review protocol was not published. This work was supported by the Portuguese Foundation for Science and Technology (grant numbers: FCT/UIDB/00617/2020, LA/P/0064/2020, PTDC/SAU-DES/0166/2021, CEECIND/01089/2017, CEECIND/01069/2017, and UI/BD/150675/2020). The funding agencies played no role in the study design; the collection, analysis, and interpretation of data; the writing of the report; and in the decision to submit the article for publication. The data are available upon reasonable request from the authors.
References
- 1.↑
Pedišić Ž, Dumuid D, Olds T. Integrating sleep, sedentary behaviour, and physical activity research in the emerging field of time-use epidemiology: definitions, concepts, statistical methods, theoretical framework, and future directions. Kinesiology. 2017;49(2):252–269.
- 2.
Carson V, Tremblay MS, Chaput J-P, Chastin SF. Associations between sleep duration, sedentary time, physical activity, and health indicators among Canadian children and youth using compositional analyses. Appl Physiol Nutr Metab. 2016;41(6):S294–S302. doi:10.1139/apnm-2016-0026
- 3.↑
Carson V, Chaput J-P, Janssen I, Tremblay MS. Health associations with meeting new 24-hour movement guidelines for Canadian children and youth. Prev Med. 2017;95:7–13. doi:10.1016/j.ypmed.2016.12.005
- 4.↑
Okely AD, Ghersi D, Hesketh KD, et al. A collaborative approach to adopting/adapting guidelines—the Australian 24-hour movement guidelines for the early years (Birth to 5 years): an integration of physical activity, sedentary behavior, and sleep. BMC Public Health. 2017;17(suppl 5):869. doi:10.1186/s12889-017-4867-6
- 5.
Tremblay MS, Carson V, Chaput J-P, et al. Canadian 24-hour movement guidelines for children and youth: an integration of physical activity, sedentary behaviour, and sleep. Appl Physiol Nutr Metab. 2016;41(6):S311–S327. doi:10.1139/apnm-2016-0151
- 6.↑
Tremblay MS, Chaput J-P, Adamo KB, et al. Canadian 24-hour movement guidelines for the early years (0–4 years): an integration of physical activity, sedentary behaviour, and sleep. BMC Public Health. 2017;17(suppl 5):874. doi:10.1186/s12889-017-4859-6
- 7.↑
World Health Organization. Guidelines on Physical Activity, Sedentary Behaviour and Sleep for Children Under 5 Years of Age. World Health Organization; 2019.
- 8.↑
Lubans DR, Hesketh K, Cliff D, et al. A systematic review of the validity and reliability of sedentary behaviour measures used with children and adolescents. Obes Rev. 2011;12(10):781–799. doi:10.1111/j.1467-789X.2011.00896.x
- 9.↑
Nascimento-Ferreira MV, Collese TS, de Moraes ACF, Rendo-Urteaga T, Moreno LA, Carvalho HB. Validity and reliability of sleep time questionnaires in children and adolescents: a systematic review and meta-analysis. Sleep Med Rev. 2016;30:85–96. doi:10.1016/j.smrv.2015.11.006
- 10.
Meltzer LJ, Montgomery-Downs HE, Insana SP, Walsh CM. Use of actigraphy for assessment in pediatric sleep research. Sleep Med Rev. 2012;16(5):463–475. doi:10.1016/j.smrv.2011.10.002
- 11.
Aminian S, Hinckson EA. Examining the validity of the ActivPAL monitor in measuring posture and ambulatory movement in children. Int J Behav Nutr Phys Act. 2012;9:119. doi:10.1186/1479-5868-9-119
- 12.
Basterfield L, Adamson AJ, Pearce MS, Reilly JJ. Stability of habitual physical activity and sedentary behavior monitoring by accelerometry in 6- to 8-year-olds. J Phys Act Health. 2011;8(4):543–547. doi:10.1123/jpah.8.4.543
- 13.
Trost SG, Mciver KL, Pate RR. Conducting accelerometer-based activity assessments in field-based research. Med Sci Sports Exerc. 2005;37(suppl 11):S531–S543. doi:10.1249/01.mss.0000185657.86065.98
- 14.
Sadeh A. The role and validity of actigraphy in sleep medicine: an update. Sleep Med Rev. 2011;15(4):259–267. doi:10.1016/j.smrv.2010.10.001
- 15.↑
Kinder JR, Lee KA, Thompson H, Hicks K, Topp K, Madsen KA. Validation of a hip-worn accelerometer in measuring sleep time in children. J Pediatr Nurs. 2012;27(2):127–133. doi:10.1016/j.pedn.2010.11.004
- 16.↑
Welk GJ, Corbin CB, Dale D. Measurement issues in the assessment of physical activity in children. Res Q Exerc Sport. 2000;71(suppl 2):59–73. doi:10.1080/02701367.2000.11082788
- 17.↑
Sallis JF. Self-report measures of children’s physical activity. J Sch Health. 1991;61(5):215–219. doi:10.1111/j.1746-1561.1991.tb06017.x
- 18.↑
Strath SJ, Kaminsky LA, Ainsworth BE, et al. Guide to the assessment of physical activity: clinical and research applications: a scientific statement from the American Heart Association. Circulation. 2013;128(20):2259–2279. doi:10.1161/01.cir.0000435708.67487.da
- 19.↑
Erwin AM, Bashore L. Subjective sleep measures in children: self-report. Front Pediatr. 2017;5:22. doi:10.3389/fped.2017.00022
- 20.↑
Toftager M, Kristensen PL, Oliver M, et al. Accelerometer data reduction in adolescents: effects on sample retention and bias. Int J Behav Nutr Phys Act. 2013;10:140. doi:10.1186/1479-5868-10-140
- 21.↑
Lippke S, Voelcker-Rehage C, Bültmann U. Assessing your client’s physical activity behavior, motivation, and individual resources. In: Nigg CR, ed. ACSM’s Behavioral Aspects of Physical Activity and Exercise. Wolters Kluwer Health/Lippincott Williams & Wilkins; 2013:39–69.
- 22.↑
Sallis JF, Saelens BE. Assessment of physical activity by self-report: status, limitations, and future directions. Res Q Exerc Sport. 2000;71(suppl 2):1–14. doi:10.1080/02701367.2000.11082780
- 23.↑
Lagerros YT. Physical activity—the more we measure, the more we know how to measure. Eur J Epidemiol. 2009;24(3):119–122. doi:10.1007/s10654-009-9316-0
- 24.↑
Baquet G, Stratton G, Van Praagh E, Berthoin S. Improving physical activity assessment in prepubertal children with high-frequency accelerometry monitoring: a methodological issue. Prev Med. 2007;44(2):143–147. doi:10.1016/j.ypmed.2006.10.004
- 25.↑
Mattocks C, Tilling K, Ness A, Riddoch C. Article commentary: improvements in the measurement of physical activity in childhood obesity research; lessons from large studies of accelerometers. Clin Med Pediatr. 2008;2:S1127. doi:10.4137/CMPed.S1127
- 26.↑
Hussey J, Bell C, Gormley J. The measurement of physical activity in children. Phys Ther Rev. 2007;12(1):52–58. doi:10.1179/108331907X174989
- 27.↑
Corder K, Ekelund U, Steele RM, Wareham NJ, Brage S. Assessment of physical activity in youth. J Appl Physiol. 2008;105(3):977–987. doi:10.1152/japplphysiol.00094.2008
- 28.
Loprinzi PD, Cardinal BJ. Measuring children’s physical activity and sedentary behaviors. J Exerc Sci Fit. 2011;9(1):15–23. doi:10.1016/S1728-869X(11)60002-6
- 29.
Harro M. Validation of a questionnaire to assess physical activity of children ages 4–8 years. Res Q Exerc Sport. 1997;68(4):259–268. doi:10.1080/02701367.1997.10608007
- 30.↑
Telford A, Salmon J, Jolley D, Crawford D. Reliability and validity of physical activity questionnaires for children: the Children’s Leisure Activities Study Survey (CLASS). Pediatr Exerc Sci. 2004;16(1):64–78. doi:10.1123/pes.16.1.64
- 31.↑
Chinapaw MJ, Mokkink LB, van Poppel MN, van Mechelen W, Terwee CB. Physical activity questionnaires for youth. Sports Med. 2010;40(7):539–563. doi:10.2165/11530770-000000000-00000
- 32.↑
Hidding LM, Chinapaw MJ, van Poppel MN, Mokkink LB, Altenburg TM. An updated systematic review of childhood physical activity questionnaires. Sports Med. 2018;48(12):2797–2842. doi:10.1007/s40279-018-0987-0
- 33.↑
Biddle SJ, Gorely T, Pearson N, Bull FC. An assessment of self-reported physical activity instruments in young people for population surveillance: project ALPHA. Int J Behav Nutr Phys Act. 2011;8(1):1–9. doi:10.1186/1479-5868-8-1
- 34.↑
Hidding LM, Altenburg TM, Mokkink LB, Terwee CB, Chinapaw MJ. Systematic review of childhood sedentary behavior questionnaires: what do we know and what is next? Sports Med. 2017;47(4):677–699. doi:10.1007/s40279-016-0610-1
- 35.↑
Spruyt K, Gozal D. Pediatric sleep questionnaires as diagnostic or epidemiological tools: a review of currently available instruments. Sleep Med Rev. 2011;15(1):19–32. doi:10.1016/j.smrv.2010.07.005
- 36.↑
Spruyt K, Gozal D. Development of pediatric sleep questionnaires as diagnostic or epidemiological tools: a brief review of dos and don’ts. Sleep Med Rev. 2011;15(1):7–17. doi:10.1016/j.smrv.2010.06.003
- 37.↑
Prinsen CA, Mokkink LB, Bouter LM, et al. COSMIN guideline for systematic reviews of patient-reported outcome measures. Qual Life Res. 2018;27(5):1147–1157. doi:10.1007/s11136-018-1798-3
- 38.↑
Higgins JP, Thomas J, Chandler J, et al. Cochrane Handbook for Systematic Reviews of Interventions. John Wiley & Sons; 2019.
- 39.↑
Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71. doi:10.1136/bmj.n71
- 41.↑
Terwee CB, Mokkink LB, van Poppel MN, Chinapaw MJ, van Mechelen W, de Vet HC. Qualitative attributes and measurement properties of physical activity questionnaires. Sports Med. 2010;40(7):525–537. doi:10.2165/11531370-000000000-00000
- 42.↑
van Poppel MNM, Chinapaw MJM, Mokkink LB, van Mechelen W, Terwee CB. Physical activity questionnaires for adults: a systematic review of measurement properties. Sports Med. 2010;40(7):565–600. doi:10.2165/11531930-000000000-00000
- 43.↑
Kohl C, McIntosh EJ, Unger S, et al. Online tools supporting the conduct and reporting of systematic reviews and systematic maps: a case study on CADIMA and review of existing tools. Environ Evid. 2018;7:8. doi:10.1186/s13750-017-0113-z
- 44.↑
Dall P, Coulter EH, Fitzsimons C, Skelton D, Chastin SF. TAxonomy of Self-reported Sedentary behaviour Tools (TASST) framework for development, comparison and evaluation of self-report tools: content analysis and systematic review. BMJ Open. 2017;7(4):e013844. doi:10.1136/bmjopen-2016-013844
- 45.↑
Kelly P, Fitzsimons C, Baker G. Should we reframe how we think about physical activity and sedentary behaviour measurement? Validity and reliability reconsidered. Int J Behav Nutr Phys Act. 2016;13:32. doi:10.1186/s12966-016-0351-4
- 46.↑
Sattler MC, Jaunig J, Tösch C, et al. Current evidence of measurement properties of physical activity questionnaires for older adults: an updated systematic review. Sports Med. 2020;50(7):1271–1315. doi:10.1007/s40279-020-01268-x
- 47.↑
Terwee CB, Bot SD, de Boer MR, et al. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol. 2007;60(1):34–42. doi:10.1016/j.jclinepi.2006.03.012
- 48.↑
Migueles JH, Cadenas-Sanchez C, Ekelund U, et al. Accelerometer data collection and processing criteria to assess physical activity and other outcomes: a systematic review and practical considerations. Sports Med. 2017;47(9):1821–1845. doi:10.1007/s40279-017-0716-0
- 50.↑
Nascimento‐Ferreira MV, De Moraes ACF, Toazza‐Oliveira PV, et al. Reliability and validity of a questionnaire for physical activity assessment in South American children and adolescents: the SAYCARE study. Obesity. 2018;26(suppl 1):S23–S30. doi:10.1002/oby.22116
- 51.↑
Määttä S, Nuutinen T, Ray C, Eriksson JG, Weiderpass E, Roos E. Validity of self-reported out-of-school physical activity among Finnish 11-year-old children. Arch Public Health. 2016;74:11. doi:10.1186/s13690-016-0123-2
- 52.↑
Florindo AA, Romero A, Peres SV, Silva MV, Slater B. Development and validation of a physical activity assessment questionnaire for adolescents. Rev Saúde Pública. 2006;40(5):802–809. doi:10.1590/S0034-89102006000600009
- 53.↑
McMurray RG, Ring KB, Treuth MS, et al. Comparison of two approaches to structured physical activity surveys for adolescents. Med Sci Sports Exerc. 2004;36(12):2135. doi:10.1249/01.MSS.0000147628.78551.3B
- 54.↑
Prochaska JJ, Sallis JF, Long B. A physical activity screening measure for use with adolescents in primary care. Arch Pediatr Adolesc Med. 2001;155(5):554–559. doi:10.1001/archpedi.155.5.554
- 55.↑
Rangul V, Holmen TL, Kurtze N, Cuypers K, Midthjell K. Reliability and validity of two frequently used self-administered physical activity questionnaires in adolescents. BMC Med Res Methodol. 2008;8:47. doi:10.1186/1471-2288-8-47
- 56.↑
Gao S, Harnack L, Schmitz K, et al. Reliability and validity of a brief tool to measure children’s physical activity. J Phys Act Health. 2006;3(4):415–422. doi:10.1123/jpah.3.4.415
- 57.↑
Lubans DR, Sylva K, Osborn Z. Convergent validity and test-retest reliability of the Oxford physical activity questionnaire for secondary school students. Behav Change. 2008;25(1):23–34. doi:10.1375/bech.25.1.23
- 58.↑
Booth ML, Okely AD, Chey T, Bauman A. The reliability and validity of the adolescent physical activity recall questionnaire. Med Sci Sports Exerc. 2002;34(12):1986–1995. doi:10.1097/00005768-200212000-00019
- 59.↑
Aaron DJ, Kriska AM, Dearwater SR, Cauley JA, Metz KF, LaPorte RE. Reproducibility and validity of an epidemiologic questionnaire to assess past year physical activity in adolescents. Am J Epidemiol. 1995;142(2):191–201. doi:10.1093/oxfordjournals.aje.a117618
- 60.↑
Teo PS, Nurul-Fadhilah A, Foo LH. Development of a new computer-based physical activity questionnaire to estimate habitual physical activity level in Malaysian adolescents. J Sci Med Sport. 2013;16(4):327–331. doi:10.1016/j.jsams.2012.06.012
- 61.↑
Scott JJ, Morgan PJ, Plotnikoff RC, Lubans DR. Reliability and validity of a single‐item physical activity measure for adolescents. J Paediatr Child Health. 2015;51(8):787–793. doi:10.1111/jpc.12836
- 62.↑
Treuth MS, Hou N, Young DR, Maynard LM. Validity and reliability of the Fels physical activity questionnaire for children. Med Sci Sports Exerc. 2005;37(3):488–495. doi:10.1249/01.MSS.0000155392.75790.83
- 63.↑
Jekauc D, Wagner MO, Kahlert D, Woll A. Reliabilität und validität des momo-aktivitätsfragebogens für jugendliche (momo-afb). Diagnostica. 2013;59(2):100–111.
- 64.↑
De Moraes ACF, Nascimento-Ferreira MV, de Moraes Forjaz CL, et al. Reliability and validity of a sedentary behavior questionnaire for South American pediatric population: SAYCARE study. BMC Med Res Methodol. 2020;20(1):5. doi:10.1186/s12874-019-0893-7
- 65.↑
Schmitz KH, Harnack L, Fulton JE, et al. Reliability and validity of a brief questionnaire to assess television viewing and computer use by middle school children. J Sch Health. 2004;74(9):370–377. doi:10.1111/j.1746-1561.2004.tb06632.x
- 66.↑
Rey-López JP, Ruiz JR, Ortega FB, et al. Reliability and validity of a screen time-based sedentary behaviour questionnaire for adolescents: the HELENA study. Eur J Public Health. 2012;22(3):373–377. doi:10.1093/eurpub/ckr040
- 67.↑
Busschaert C, De Bourdeaudhuij I, Van Holle V, Chastin SF, Cardon G, De Cocker K. Reliability and validity of three questionnaires measuring context-specific sedentary behaviour and associated correlates in adolescents, adults and older adults. Int J Behav Nutr Phys Act. 2015;12:117. doi:10.1186/s12966-015-0277-2
- 68.↑
Cabanas-Sánchez V, Martínez-Gómez D, Esteban-Cornejo I, Castro-Piñero J, Conde-Caveda J, Veiga ÓL. Reliability and validity of the Youth Leisure-time Sedentary Behavior Questionnaire (YLSBQ). J Sci Med Sport. 2018;21(1):69–74. doi:10.1016/j.jsams.2017.10.031
- 69.↑
Werner H, LeBourgeois MK, Geiger A, Jenni OG. Assessment of chronotype in four- to eleven-year-old children: reliability and validity of the Children’s Chronotype Questionnaire (CCTQ). Chronobiol Int. 2009;26(5):992–1014. doi:10.1080/07420520903044505
- 70.↑
Treuth MS, Sherwood NE, Butte NF, et al. Validity and reliability of activity measures in African-American girls for GEMS. Med Sci Sports Exerc. 2003;35(3):532–539. doi:10.1249/01.MSS.0000053702.03884.3F
- 71.↑
Singh AS, Vik FN, Chinapaw MJ, et al. Test-retest reliability and construct validity of the ENERGY-child questionnaire on energy balance-related behaviours and their potential determinants: the ENERGY-project. Int J Behav Nutr Phys Act. 2011;8:136. doi:10.1186/1479-5868-8-136
- 72.↑
Wong SL, Leatherdale ST, Manske SR. Reliability and validity of a school-based physical activity questionnaire. Med Sci Sports Exerc. 2006;38(9):1593–1600. doi:10.1249/01.mss.0000227539.58916.35
- 73.↑
Ridley K, Olds TS, Hill A. The multimedia activity recall for children and adolescents (MARCA): development and evaluation. Int J Behav Nutr Phys Act. 2006;3:10. doi:10.1186/1479-5868-3-10
- 74.↑
McLure SA, Reilly JJ, Crooks S, Summerbell CD. Development and evaluation of a novel computer-based tool for assessing physical activity levels in schoolchildren. Pediatr Exerc Sci. 2009;21(4):506–519. doi:10.1123/pes.21.4.506
- 75.↑
Gance-Cleveland B, Schmiege S, Aldrich H, Stevens C, Scheller M. Reliability and validity of HeartSmartKids: a survey of cardiovascular risk factors in children. J Pediatr Health Care. 2018;32(4):381–386. doi:10.1016/j.pedhc.2018.01.003
- 76.↑
Bringolf-Isler B, Mäder U, Ruch N, Kriemler S, Grize L, Braun-Fahrländer C. Measuring and validating physical activity and sedentary behavior comparing a parental questionnaire to accelerometer data and diaries. Pediatr Exerc Sci. 2012;24(2):229–245. doi:10.1123/pes.24.2.229
- 77.↑
Ching PL, Dietz WH. Reliability and validity of activity measures in preadolescent girls. Pediatr Exerc Sci. 1995;7(4):389–399. doi:10.1123/pes.7.4.389
- 78.↑
Pate RR. Physical activity assessment in children and adolescents. Crit Rev Food Sci Nutr. 1993;33(4–5):321–326. doi:10.1080/10408399309527627
- 79.↑
Streiner DL, Norman GR, Cairney J.Health Measurement Scales: A Practical Guide to Their Development and Use. Oxford University Press; 2015.
- 80.↑
Rodrigues B, Encantado J, Carraça E, et al. Questionnaires measuring movement behaviours in adults and older adults: content description and measurement properties. A systematic review. PLoS One. 2022;17(3):e0265100. doi:10.1371/journal.pone.0265100
- 81.↑
Troiano RP, Stamatakis E, Bull FC. How can global physical activity surveillance adapt to evolving physical activity guidelines? Needs, challenges and future directions. Br J Sports Med. 2020;54(24):1468–1473. doi:10.1136/bjsports-2020-102621
