Questionnaires Measuring 24-Hour Movement Behaviors in Childhood and Adolescence: Content Description and Measurement Properties—A Systematic Review

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Bruno Rodrigues Faculty of Sport, Research Centre in Physical Activity, Health and Leisure, University of Porto, Porto, Portugal

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Jorge Encantado CIPER, Faculdade de Motricidade Humana, Lisboa, Portugal

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Eliana Carraça CIDEFES (Centro de Investigação em Desporto, Educação Física e Exercício e Saúde), Universidade Lusófona, Lisboa, Portugal

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João Martins CIPER, Faculdade de Motricidade Humana, Lisboa, Portugal
Centro de Estudos de Educação, Faculdade de Motricidade Humana e UIDEF, Instituto de Educação, Universidade de Lisboa, Lisboa, Portugal

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Adilson Marques CIPER, Faculdade de Motricidade Humana, Lisboa, Portugal

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Luís Lopes Faculty of Sport, Research Centre in Physical Activity, Health and Leisure, University of Porto, Porto, Portugal
Northern Region Health Administration, Porto, Portugal

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Eduarda Sousa-Sá Faculty of Sport, Research Centre in Physical Activity, Health and Leisure, University of Porto, Porto, Portugal
CIDEFES (Centro de Investigação em Desporto, Educação Física e Exercício e Saúde), Universidade Lusófona, Lisboa, Portugal
Early Start, School of Education, Faculty of the Arts, Social Sciences and Humanities, Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, NSW, Australia

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Dylan Cliff Early Start, School of Education, Faculty of the Arts, Social Sciences and Humanities, Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, NSW, Australia

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Romeu Mendes Northern Region Health Administration, Porto, Portugal
Laboratory for Integrative and Translational Research in Population Health, Porto, Portugal
EPIUnit–Instituto de Saúde Pública, Universidade do Porto, Porto, Portugal

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Rute Santos Faculty of Sport, Research Centre in Physical Activity, Health and Leisure, University of Porto, Porto, Portugal
Laboratory for Integrative and Translational Research in Population Health, Porto, Portugal

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Free access

JPAH 2024 Award Winner: Best Review Article

Background: We aim to systematically review the literature on measurement properties of self- and proxy-reported questionnaires measuring 24-hour movement behaviors in children and adolescents. Methods: PubMed, PsycINFO, SPORTDiscus, and EMBASE were searched until June 2021. Studies were included if the sample size for validity studies had 50 participants (minimum) and included, at least, both validity and test–retest reliability results of questionnaires. The review followed an adaptation of the Consensus-based Standards for the selection of health Measurement INstruments guidelines, to evaluate the quality of measurements properties of the questionnaires (content, convergent and criterion validity, reliability, measurement error, and responsiveness), as well as the risk of bias of each measurement property. Results: This review included 29 studies, describing 37 questionnaires. Sixty-eight percent showed “adequate” content validity. None of the questionnaires showed overall “adequate” criterion validity, and the risk of bias was “very low” for 92%. One questionnaire showed “adequate” convergent validity, and 73% of the studies were classified with a “high risk of bias.” Seven questionnaires showed “adequate” reliability, and 27.3% of the studies were rated with a “very low risk of bias.” None of the questionnaires showed “adequate” criterion validity and reliability, simultaneously. Conclusions: Existing questionnaires have insufficient measurement properties, and none considered the 24-hour movement behavior paradigm. These results highlight the need for better questionnaires of movement behavior combinations, to improve the monitoring and surveillance systems of 24-hour movement behaviors in this population.

The health-related associations of appropriate levels of movement behaviors (ie, physical activity [PA], sedentary behavior [SB], and sleep, across a 24-h period13) 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 developed46 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,815 in large-scale epidemiological studies and clinical contexts, questionnaires are preferred due to their practicality, simplicity, and affordability.8,1619 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.2730

Recently, 3 systematic reviews on measurement properties of PA questionnaires3133 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.

Figure 1
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,30,5061 and 2 in both62,63); 6 measured SB (1 in children,64 4 in adolescents6467 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 both7376), 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).

Table 1

Content Characteristics of the Included Movement Behavior Questionnaires

QuestionnaireAge group, countryMode of administrationDomainsResponse methodUnits of measurementScoresRecall period/assessment periodNo. of itemsParameters
Physical activity
 CLASS—Proxy30Children (5–6 y), AustraliaProxy-reportedLeisure; sports; total PAContinuous: times/wk; min or h/dmin or h/dFrequency MPA; frequency VPA; duration MPA; duration VPA intensityUsual weekday and weekend day in a typical week30 activities + 6F; D; I; M
 SAYCARE PA Q C50Children (3–10 y), South AmericaProxy-reportedSchool; leisure; transportationParticipate yes/no; if yes, continuous: frequency, duration, and intensitymin/d PA school; min/wk PA leisure; min/d PA commutingPA at school; time spent PA leisure; PA commuting;

MPA; VPA; total PA; guideline’s compliance
Past week47F; D; I
 O-O-S PAQ51Adolescents (11 y), FinlandSelf-reportedOut of school (leisure and sports)Rating scale: h/wk and times/wk (10 options)min/d and times/wkMVPA duration and MVPA frequencyUsual week during weekdays2F; D
 HPAQ52Adolescents (11–16 y), BrazilSelf-reportedSports; transportationContinuous: h/d; d/wk; mo/ymin/wk; min/yWeekly PA score; yearly PA scorePast year7–17F; D; M
 3DPAR53Adolescents (11–14 y), United StatesSelf-reportedBefore, during, after schoolFor each activity rate, its intensity across 4 categoriesNumber of 30-min blocks per intensity MVPA and VPAMVPA; VPAPast 3 d?F; D; I; M
 YRBS54Adolescents (12.7 [0.6] y), United StatesSelf-reportedTotal PA by intensityContinuous: min/dmin/dMeeting guidelinesPast week in weekdays and weekend days2F; D; I
 SAPAC53Adolescents (11–14 y), United StatesSelf-reportedBefore, during, after schoolChecklist of responses (continuous: min/d)min/dMVPA; VPAPast 3 d?F; D; I; M
 HBSC PAQ55Adolescents (13–18 y), NorwaySelf-reportedOutside schoolRating scaleCategories: “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 categoriesUsual week, outside school2F; D
 MGLTEQ56Adolescents (12–14 y), United StatesSelf-reportedTotal PA by intensitiesContinuous: d/wkd/wkStrenuous; moderate; mildUsual week in summer and school time3F; I
 OPAQ57Adolescents (13–14 y), United KingdomSelf-reportedTransport; physical education; school sport; after school sportContinuous: d/wk, min/wk; list of activitiesMETs/wkMPA; VPA; MVPAPast week in weekdays and weekend days8F; D
 APARQ58Adolescents (13–15 y), AustraliaSelf-reportedOrganized sports, games; nonorganized physical activitiesList of activities; continuous: times/wk; h/timeMETsEnergy 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
 PYPAA59Adolescents (12–16 y), United StatesSelf-reportedLeisureChecklist; continuous: min/activityMET-h/wkOverall leisure physical activity in h/wk; MET-h/wk; VPA-h/wkPast year3 (up to 33)F; D; M
 cPAQ60Adolescents (11–16 y), MalaysiaSelf-reportedSchool; after-school; household?METsLPA; MPA; VPAPast year71F; D; I, M
 S-I PA M61Adolescents (14.7 [0.5] y), AustraliaSelf-reportedMVPAContinuous (number of d)Number of dMVPAPast week1F; D; I
 MPA and VPA S Q54Adolescents (14.6 [1.4] y), United StatesSelf-reportedGeneral MPA and VPAContinuous (times/wk)Number of d30- and 60-min MPA and 20-min VPA (past week, typical week, and composites [average])Past week and typical week6F; D; I
 PACE + PAM54Adolescents (12.1 [0.9] y), United StatesSelf-reportedGeneral MVPAContinuous (d/wk)Number of dMVPAPast week and typical week1 per recall periodF; D; I
 SAYCARE PA Q A50Adolescents (11–18 y), South AmericaSelf-reportedSchool; leisure; transportationParticipate yes/no; if yes, continuous: frequency, duration, and intensitymin/d PA school; min/wk PA leisure; min/d PA commutingPA at school; time spent PA leisure; PA commuting; MPA; VPA; total PA; guideline’s compliancePast week47F; D; I
 CLASS–Proxy and self30Adolescents (10–12 y), AustraliaProxy- reported and self-reportedLeisure; sports; total PAContinuous: times/wk; min or h/dmin or h/dFrequency MPA; frequency VPA; duration MPA; duration VPA intensityUsual weekday and weekend day in a typical week30 activities + 6F; D; I; M
 Fels PAQ62Children and adolescents (7–19 y), United StatesSelf-reportedSport; leisure; transportation; homeRating scale: 1 (sometimes) to 3 (regularly)Points (reflecting intensity—METs—and frequency)Total score; sport score; leisure score; work scorePast year8F; I
 MoMo63Children and adolescents (9–17 y), GermanySelf-reportedTotal PA; sports; physical educationContinuous (times/wk; min/wk); rating scale for intensity (1 [shortness breath] to 3 [much sweating])min/wkGeneral PA; PA in school; recreational sports outside clubsPast week28F; D; I; M
Sedentary behavior
 SAYCARE SB Q C64Children (3–10 y), Argentina, Peru, Colombia, Uruguay, Chile, and BrazilProxy-reported for children (parents)TV; computer use; studying (adolescents); video games; passive play (children)Continuous: min/dmin/wkTotal SB and achieving or not achieving the recommended limit of less than 120 min/d of SBPast week in weekdays and weekend days8F; D; I; M
 EAQT-SB65Adolescents (11–15 y), United StatesSelf-reportedTV (and videos or playing video games) and computer useRating scale (1 [less than 1 h] to 6 [5 or more h])h/dWeekday TV (school period); weekend TV (school period); weekend TV (summer); weekday TV (summer); computer use; weekday averageWeekday; weekend in summer and school time5D; M
 Helena SB Q66Adolescents (12.5–17.5 y); EuropeSelf-reportedTV 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/dWeekly time and total score; weekend timeUsual day in week and weekend days12D
 SIT-Q-7d67Adolescents (15–16 y), The NetherlandsSelf-reportedTV; computer; motorized transport; school; gamingChecklist and continuous: min/activitymin/wkWeekday ST; weekend day ST; average STPast week in week and weekend days24F; D; M
 SAYCARE SB Q A64Adolescents (11–18 y), Argentina, Peru, Colombia, Uruguay, Chile, and BrazilSelf-reported for adolescentsTV; computer use; studying (adolescents); video games; passive play (children)Continuous: min/dmin/wkTotal SB and achieving or not achieving the recommended limit of less than 120 min/d of SBPast week in weekdays and weekend days8F; D; I; M
 YLSBQ68Children and adolescents (8–18 y), SpainSelf-reportedScreen 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/dWeekday ST; weekend ST; average day STPast week in average weekday and weekend day24F; D
Sleep
 CCTQ69Children and adolescents (4–11 y), United StatesProxy-reportedNight sleep period; napsContinuous: h and min of waking up, going to bed, lights turned off; and min to falling asleep; min per napSleep onset (calculated by h and min of waking up, going to bed, lights turned off; and min to falling asleep); h per napSleep periodTypical weekday and weekend day12F
Physical activity + sedentary behavior
 GAQ70Children (8–9 y), United StatesSelf-reportedLeisure; 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 behaviorTotal PA score; (weighted) MET values; GAQ summary scorePast day; usually day27 for physical activity; 7 for sedentary behaviorF; D; M
 ENERGY-C Q71Adolescents (10–12 y), Belgium, Greece, Hungary, The Netherlands, Norway, and Spain.Self-reportedTransport; sports; computer use; TV; leisureContinuous: d/wk; min/d; h/wk; h/dd/wk; min/d; h/wk; h/dBike 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 usePast week and past day, in weekend and weekdays15F; D
 IPAQ55Adolescents (13–18 y), NorwaySelf-reportedLeisureContinuous: d/wk and min/dd/wk and min/dSitting; LPA; MPA; VPA; walkingUsual or past week in week and weekend days?F; D
 SHAPES physical activity questionnaire72Adolescents (11–18 y), CanadaSelf-reportedSports; transportation; leisure physical activities; screen timeContinuous: time/dmin/wkVPA; MPA; MVPA; screen timePast week45F; D; I
 MARCA73Children and adolescents (9–13.5 y), AustraliaSelf-reportedAll forms of activity (organized and nonorganized physical activity, sedentary activity, incidental activity, etc)Continuous: time spent in each activityMET-weighted average was computed; score based on time spend on sedentary behaviorPAL; MVPA; lying down, sitting, standing or in locomotionPast day in weekday, weekend, holiday or day off from schoolSegmented day format (web-based)D; I; M
 peas@tees74Children and adolescents (9–10 y), EnglandSelf-reportedSedentary, household, and play activities, structured; transportContinuous: time spent in each activityMET-weighted average was computed; score based on time spend on sedentary behaviorMVPAUsual day in school day and weekend daySegmented day format (web-based)D; I; M
 HSK75Children and adolescents (9–14 y), United StatesSelf-reportedActive play or sport; sedentary behaviors (TV; using computer; video games; on telephone)Rating scaleh/dHours of active play or sport; hours of sedentary activitiesUsual day of past month2F; D
 PQPASB76Children and adolescents (6–10 and 13–14 y), SwissProxy-reportedFor 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/dmin/dSB 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 sexUsual weekday and weekend dayList of activitiesF; D; M
Physical activity + sedentary behavior + sleep
 Daughter Questionnaire77Children and adolescents (8.5–12.7 y), United KingdomSelf-reportedLight activity (standing); moderate activity (walking); and vigorous activity (sports); TV/VCR/video games; ST; sleepContinuous: h/dh/dSleep; sitting; standing; walking; exercise; TV/VCR/video gamesUsual day, in school day and weekend dayThree timetables (school, weekend, TV)D; I
 Mother and Father Questionnaires77Children and adolescents (8.5–12.7 y), United KingdomProxy-reportedLight activity (standing); moderate activity (walking); and vigorous activity (sports); TV/VCR/video games; ST; sleepContinuous: h/dh/dSleep; sitting; standing; walking; exercise; TV/VCR/video gamesUsual 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,30,50,51,5363 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 questionnaires6468 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,55,7076 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.

Table 2

Validity Results

QuestionnaireSampleValidityOverall quality
n; %girls; age mean (SD) or age range, yType of validityComparison measureResults
PA
 CLASS—Proxy3058; 63% girls; 5–6 yCriterionAccelerometer, 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 C50Children: 82; 54.4% girls; 3–10 yCriterionAccelerometer, ActiGraph GTX3, wear time: 7 d; site: hip mounted; epoch: 5 sMPA (rho = 0.60*); VPA (rho = 0.27); total PA (rho = 0.44*); agreement guidelines (kappa = .40)
 O-O-S PAQ51126; N.R.; 11 yCriterionAccelerometer, ActiGraph GTX3, wear time: 7 d; site: hip mounted; epoch: 15 sMVPA duration (r = .25); MVPA frequency (r = .25)
 HPAQ5294; 68.1% girls; 11–16 yConvergentVO2max (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 rateWeekly 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)
 3DPAR53157; N.R.; 11–14 yCriterionAccelerometer, ActiGraph (empirical thresholds); wear time: 3 d; site: N.R.; epoch: 30 sOverall 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 sOverall 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**)
 YRBS54125, 52.5% girls; 12.2 (0.6)CriterionAccelerometer, ActiGraph model 7164; wear time: 7 d; site: hip; epoch: 60 sMeeting 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?
 SAPAC53154; N.R.; 11–14 yCriterionAccelerometer, ActiGraph (empirical thresholds); wear time: 3 d; site: N.R.; epoch: 30 sOverall 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 sOverall 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 PAQ5567; 55% girls; 13–18 yConvergentVO2peakFrequency (rho = 0.39**); duration (rho = 0.33**); frequency categories (rho = 0.36**); duration categories (rho = 0.29*)
CriterionAccelerometer, 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)
 MGLTEQ56114; 59.6% girls; 12–14 yCriterionAccelerometer, ActiGraph; wear time: 7 d; site: right hip; epoch: 60 sMPA (r = .23**); VPA (r = .13)
 OPAQ5751; 47.1% girls; N.R.CriterionAccelerometer, Caltrac; wear time: 4 d; site: waist; epoch: N.R.VPA (r = .33*); MVPA (r = .32*); MPA (r = .01)
 APARQ581072; 48% girls; 12.1 y; grade 8Convergent20-m shuttle run testEnergy expenditure boys (r = .15***); energy expenditure girls (r = .21***)
954; 45% girls; 15.1 y; grade 10Energy expenditure boys (r = .14**); energy expenditure girls (r = .39***)
 PYPAA59100; 53% girls; 16.6 yConvergentBMIBoys: 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 runBoys: 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 reachBoys: 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-upsBoys: 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 strengthBoys: 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)
 cPAQ60180; N.R.; N.R.Convergent7-d PALogTotal 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 M61123; 38.2%; 14.7 (0.5) yCriterionAccelerometer, ActiGraph; wear time: 7 d; site: waist belt; epoch: 15 sMVPA (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 Q5457; 65% girls; 13.9 (1.7) yCriterionAccelerometer, 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 +PAM54138; 65% girls; 12.1 (0.9) yCriterionAccelerometer, CSA; wear time: 7 d; site: right hip; epoch: N.R.MVPA (r = .40**)
 SAYCARE PA Q A50Adolescents: 60; 55.7% girls; 11–18 yCriterionAccelerometer GTX3; wear time: 7 d; site: waist; epoch: 5 sMPA (rho = 0.11); VPA (rho = 0.65*); total PA (rho = 0.88*); adolescent kappa agreement guidelines (kappa = .51*)
 Fels PAQ62229; 56.7%; 7–19 yCriterionAccelerometer, Actiwatch; wear time: 6 d; site: N.R.; epoch: 60 sElementary 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)
 MoMo63109, 44% girls; 8–17 yCriterionAccelerometer, 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 C6493; 50% girls; 3–10 yCriterionAccelerometer, ActiGraph GT3X; wear time: 7 d; site: waist; epoch: 5 sSB 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-SB65245; 58.8%; 11–15 yConvergentLog of TV viewing and computer use daily during 7 dWeekday TV (rho = 0.46***); weekend TV (rho = 0.37***); weekday average TV (rho = 0.47***); computer use (rho = 0.40**)
 Helena SB Q662048; 59.2% girls; 12.5–17.5 yCriterionAccelerometer, 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-7d6762; 58% girls; 15–16 yCriterionactivPAL; 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 A6494; 50% girls; 11–18 yCriterionAccelerometer, ActiGraph GT3X; wear time: 7 d; site: waist; epoch: 5 sSB 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)
 YLSBQ681207; N.R.; 8–18 yearsCriterionAccelerometer, ActiGraph; wear time: 7 d; site: lower back; epoch: 2 sWeekday 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
 CCTQ6985; N.R.; 4–11 yCriterionAccelerometer, Actiwatch Plus (AW4), wear time: 6–14 d; site: nondominant wrist; epoch: 60 sSleep period (weekday) d = 0.59***; sleep period (weekend day) d = 0.83***
PA + SB
 GAQ7068; 100% girls; 8–9 yCriterionAccelerometer, MTI/CSA; wear time: N.R.; site: N.R.; epoch: 60 s18 physical activities/past day (MET weighted score) (r = .28*); 18 physical activities/usual day (MET weighted score) (r = .30*)
 ENERGY-C Q7196; N.R.; 10–12 yConvergentInterviewBike 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%)
 IPAQ5567; 55% girls; 13–18 yConvergentVO2peakVPA 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**)
CriterionAccelerometer, ActiReg (total energy expenditure); wear time: 7 d; site: chest and thighVPA 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 thighVPA 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)
 SHAPES7253; 47% girls; N.R.CriterionAccelerometer, ActiGraph AM7164; wear time: N.R.; site: right hip; epoch: 60 sMVPA min/d (r = .44*); VPA min/d (r = .25); MPA min/d (r = .31*); energy expenditure daily average (r = .44***)
 MARCA7366; 50% girls; 9–13 yCriterionAccelerometer, ActiGraph; wear time: 1 d; site: N.R.; epoch: 60 sPAL (r = .45**); MVPA min (r = .35)**; locomotion min (r = .37**)
 peas@tees74157; N.R.; N.R.CriterionAccelerometer, ActiGraph GT-256; wear time: 5 d; site: right hip; epoch: 60 sMVPA min (rho = 0.23*); MVPA (LoA = −146 to 105 [95% CI, −31 to –11] min/d; bias = −21 min/d)
 HSK75103; 91% girls; 9–14 yConvergentHABITS questionnaireActivity (rho = 0.38***); sedentary (rho = 0.65***)
 PQPASB76167; 71% girls; 6–10 and 13–14 yCriterionAccelerometer, ActiGraph Model AM7164; wear time: 7 d; epoch: 60 sSB 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 Questionnaire7769 girls; 8.5–12.7 yConvergentActivity diarySchool 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 Questionnaires7769 girls; 8.5–12.7 yConvergentActivity diaryMothers, 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.

Table 3

Reliability Results

QuestionnaireSampleReliabilityOverall quality
n; %girls; age mean (SD) or age range, yTime between test and retestResults
PA
 CLASS—Proxy3058; 63% girls; 5–6 yAt least 14 dTotal MPA frequency (ICC = .74***); total MPA duration (ICC = .49***); overall total PA frequency (ICC = .83***); overall total PA duration (ICC = .76***)+
 SAYCARE PA Q C5049.8% girls; 3–10 y15 dPA 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 PAQ51151; N.R.; 11 y30 dMVPA duration (ICC = .65); MVPA frequency (ICC = .64)
 HPAQ5294; 68.1% girls; 11–16 y2 wkWeekly physical activity score (ICC = .61); yearly physical activity score (ICC = .68)
 3DPAR5392; N.R.; 11–14 y1 dOverall 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)
 YRBS54125; 52.5% girls; 12.2 (0.6) y15 dMPA item (ICC = .51*); VPA item (ICC = .46*)
 SAPAC5365; N.R.; 11–14 y1 dOverall 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 PAQ5571; 56.3% girls; 13–18 y8–12 dFrequency (ICC = .73); duration (ICC = .71)+
 MGLTEQ56250; 58.8% girls; 12–14 y1 wkMild-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)
 OPAQ5787; 44.8% girls; N.R.2 wkMPA (ICC = .76*); VPA (ICC = .80*); MVPA (ICC = .91*)+
 APARQ58121; 48% girls, 12.7 y2 wkGrade 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)
 PYPAA59100; 53% girls; 16.6 y1 moh/wk (rho = 0.79); MET-h/wk (rho = 0.85**); VIG-h/wk (rho = 0.91**)
1 yh/wk (rho = 0.66**); MET-h/wk (rho = 0.72**); VIG-h/wk (rho = 0.72**)
 cPAQ6035 Malaysian boys; N.R.2 wkTotal 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 M61123; 38.2%; 14.7 (0.5) y2 wkMVPA (ICC = .75***)+
 MPA and VPA S Q54250; 56% girls; 14.6 (1.4) y2 wkVPA 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 + PAM5473; 65% girls; 12.1 (0.9) y24 h to 1 monthMVPA (ICC = .77)+
 SAYCARE PA Q A50177; 58.3% girls; 11–18 yPA 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 self30111; 27% girls; 10–12 y7 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 PAQ62229; 56.7%; 7–19 y6 dElementary 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)
 MoMo63109; 44% girls; 8–17 y1 wkGeneral PA (ICC = .74**); PA in school (ICC = .60**); recreational sports outside clubs (ICC = .64**)
SB
 SAYCARE SB Q C6455; 40% girls; 3–10 y2 wkTotal 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-SB65245; 58.8%; 11–15 y1 wkWeekday 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 Q66183; 57%; 12.5–17.5 y1 wkTV 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-7d6720; 42% girls; 15–16 y6 dSB weekday total (ICC = .37); internet study weekend (kappa = .33); SB weekend day total (ICC = .67); SB average day total (ICC = .45)
 SAYCARE SB Q A64106; 61%; 11–18 yTotal 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*)
 YLSBQ68194; 50.5%; 10–18 y1 wkWeekday: 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
 CCTQ6943; N.R.; 4–11 y20 dSleep 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
 GAQ7067; 100% girls; 8–9 y4 d28 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 Q71730; N.R.; 10–12 y1 wkBike 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%)
 IPAQ5571; 56.3% girls; 13–18 y8–12 dVPA 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)
 SHAPES72460; N.R.; N.R.1 wkWeekly 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)
 MARCA7337; 44% girls; 9–13 ySame 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@tees7442; 48% girls; N.R.2 dMVPA (ICC = .69)
 HSK7535; N.R.; 9–14 y8 wkActivity (rho = 0.78***); sedentary (rho = 0.38*)
 PQPASB76125; 53% girls; 6–10 and 13–14 y2 wkWatching 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 Questionnaire7769 girls; 8.5–12.7 y12–16 dSchool 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 Questionnaires7769 girls; 8.5–12.7 y12–28 dMothers, 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.

Table 4

Summary of Results

QuestionnaireReliability qualityContent validity qualityRisk of bias
Validity qualityValidityReliability
CriterionConvergentCriterionConvergent
PA
 CLASS—Proxy30NA+CD1NA1
 SAYCARE PA Q C50NA+1NA3
 O-O-S PAQ51NA+1NA2
 HPAQ52NA−/−/−/−/−142
 3DPAR53−/−NA+1NA3
 YRBS54NA+1NA4
 SAPAC53−/−NACD1NA3
 HBSC PAQ55−/−+144
 MGLTEQ56NA1NA3
 OPAQ57NA++1NA3
 APARQ58NA+NA41
 PYPAA59NA−/−/−/−/−/−/−/−/−NA43
 cPAQ60NA+CDNA21
 S-I PA M61NA++1NA2
 MPA and VPA S Q54NA+1NA2
 PACE + PAM54NA++1NA3
 SAYCARE PA Q A50NA+1NA3
 CLASS—Proxy and self30NACD1NA1
 Fels PAQ62NA1NA2
 MoMo63NA1NA1
SB
 SAYCARE SB Q C64NA+1NA3
 EAQT-SB65NANA43
 Helena SB Q66NA+4NA1
 SIT-Q-7d67NA+1NA2
 SAYCARE SB Q A64NA+1NA3
 YLSBQ68NA1NA1
Sleep
 CCTQ69+NA++4NA3
PA + SB
 GAQ70NA1NA3
 ENERGY-C Q71NA+NA41
 IPAQ55−/−+144
 SHAPES72NA+1NA1
 MARCA73NA++1NA3
 peas@tees74NA+1NA1
 HSK75NA+NA43
 PQPASB76NA+1NA3
PA + SB + sleep
 Daughter Questionnaire77NACDNA31
 Mother and Father Questionnaires77NACDNA33

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,2730 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,8,9,3134 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.

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  • Collapse
  • Expand
  • Figure 1

    —Study selection process flowchart. n indicates number of studies.

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