An Updated Systematic Review of Childhood Physical Activity Questionnaires.

BACKGROUND AND
OBJECTIVE: This review is an update of a previous review published in 2010, and aims to summarize the available studies on the measurement properties of physical activity questionnaires for young people under the age of 18 years.
METHODS: Systematic literature searches were carried out using the online PubMed, EMBASE, and SPORTDiscus databases up to 2018. Articles had to evaluate at least one of the measurement properties of a questionnaire measuring at least the duration or frequency of children's physical activity, and be published in the English language. The standardized COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist was used for the quality assessment of the studies.
RESULTS: This review yielded 87 articles on 89 different questionnaires. Within the 87 articles, 162 studies were conducted: 103 studies assessed construct validity, 50 assessed test-retest reliability, and nine assessed measurement error. Of these studies, 38% were of poor methodological quality and 49% of fair methodological quality. A questionnaire with acceptable validity was found only for adolescents, i.e., the Greek version of the 3-Day Physical Activity Record. Questionnaires with acceptable test-retest reliability were found in all age categories, i.e., preschoolers, children, and adolescents.
CONCLUSION: Unfortunately, no questionnaires were identified with conclusive evidence for both acceptable validity and reliability, partly due to the low methodological quality of the studies. This evidence is urgently needed, as current research and practice are using physical activity questionnaires of unknown validity and reliability. Therefore, recommendations for high-quality studies on measurement properties of physical activity questionnaires were formulated in the discussion. PROSPERO REGISTRATION NUMBER: CRD42016038695.

Key Points

Introduction

Numerous studies have demonstrated beneficial effects of physical activity, in particular of moderate to vigorous intensity, on metabolic syndrome, bone strength, physical fitness, and mental health in children and adolescents [1, 2]. In order to monitor trends in physical activity, examine associations between physical activity and health outcomes, and evaluate the effectiveness of physical activity-enhancing interventions, valid, reliable, responsive, and feasible measures of physical activity are needed.

Accelerometers are considered to provide valid and reliable measures of physical activity in children and adolescents [3]. However, accelerometers are not gold standard and underestimate activities such as cycling, swimming, weight lifting, and many household chores. Moreover, physical activity estimates vary depending on subjective decisions in data reduction such as the choice of cut-points for intensity levels, the minimum number of valid days, the minimum number of valid hours per day, and the definition of non-wear time [4]. Furthermore, accelerometers cannot provide information on the type and context of the behavior and are labor-intensive and costly, especially in large populations [5].

Self-report or proxy-report questionnaires are seen as a convenient and affordable way to assess physical activity that can provide information on the context and type of the activity [5, 6]. However, questionnaires have their limitations as well, such as the potential for social desirability and recall bias [6, 7]. Thus, for measuring physical activity a combination of the more objective measures such as accelerometers and self-report questionnaires seems most promising.

A great many questionnaires measuring physical activity in children and adolescents have been developed, with varying formats, recall periods, and types of physical activity recalled. To be able to select the most appropriate questionnaire, an overview of the measurement properties of the available physical activity questionnaires in children and adolescents is highly warranted. In 2010, Chinapaw et al. [8] reviewed the measurement properties of self-report and proxy-report measures of physical activity in children and adolescents. As many studies assessing measurement properties of physical activity questionnaires have been published since then, an update is timely.

Therefore, we aimed to summarize studies that assessed the measurement properties (e.g., responsiveness, reliability, measurement error, and validity) of self-report or proxy-report questionnaires in children and adolescents under the age of 18 years published since May 2009. Furthermore, we aimed to provide recommendations regarding the best available questionnaires, taking into account the best available questionnaires from the previous review.

Methods

This review is an update of the previously published review of Chinapaw et al. [8]. We followed the Preferred Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines and registered the review on PROSPERO (international prospective register of systematic reviews; registration number: CRD42016038695).

Literature Search

Systematic literature searches were carried out in PubMed, EMBASE, and SPORTDiscus (from January 2009 up until April 2018). In PubMed more overlap in time was maintained (search from May 2008), as our previous searches showed that the PubMed time filter can be inaccurate, e.g., due to incorrect labeling of publication dates. The full search strategy can be found in the Electronic Supplementary Material (Online Resource 1).

Search terms in PubMed were used in AND-combination, and related to physical activity (e.g., motor activity, exercise), children and adolescents (e.g., schoolchildren, adolescents), measurement properties (e.g., reliability, reproducibility, validity) [9], and self- or proxy-report measures (e.g., child-reported questionnaire). Medical Subject Heading (MESH), title and abstract (TIAB), and free-text search terms were used, and a variety of publication types (e.g., biography, comment, case reports, editorial) were excluded. In EMBASE, search terms related to physical activity, measurement properties [9], and self- or proxy-report measures were used in AND-combination. The search was limited to children and adolescents (e.g., child, adolescent), and EMBASE-only. EMBASE subject headings, TIAB, and free-text search terms were used. In SPORTDiscus, TIAB and free-text search terms were used in AND-combination, related to physical activity, children and adolescents, and self- or proxy-report measures.

Inclusion and Exclusion Criteria

Studies were eligible for inclusion when (1) the aim of the study was to evaluate at least one of the measurement properties of a self-report or proxy-report physical activity questionnaire, or a questionnaire containing physical activity items; (2) the questionnaire under study at least reported data on the duration or frequency of physical activity; (3) the mean age of the study population was < 18 years; and (4) the study was available in the English language. Studies were excluded in the following situations: (1) studies assessing physical activity using self-report measures administered by an interview (one-on-one assessment) or using a diary; (2) studies evaluating the measurement properties in a specific population (e.g., children who are affected by overweight or obesity); (3) studies examining structural validity and/or internal consistency for questionnaires that represent a formative measurement model; (4) construct validity studies examining the relationship between the questionnaire and a non-physical activity measure, e.g., body mass index (BMI) or percentage body fat; and (5) responsiveness studies that did not use a physical activity comparison measure, e.g., accelerometer, to assess a questionnaire’s ability to detect change.

Selection Procedures

Titles and abstracts were screened for eligible studies by two independent researchers [Lisan Hidding (LH) and either Mai Chinapaw (MC), Mireille van Poppel (MP), Teatske Altenburg (TA), or Lidwine Mokkink (LM)]. Subsequently, full texts were obtained and screened for eligibility by two independent researchers (LH and either TA or MP). A fourth researcher (MC) was consulted in the case of doubt.

Data Extraction

For all eligible studies, two independent reviewers (LH and either TA or MP) extracted data regarding the characteristics of studies and results of the assessed measurement properties, using a structured form. Extracted data regarding the methods and results of the assessed measurement properties included study population, questionnaire under study, studied measurement properties, comparison measures, time interval, statistical methods used, and results regarding the studied measurement properties. In the case of disagreement regarding data extraction, a fourth researcher (MC) was consulted.

Methodological Quality Assessment

Two independent reviewers (LH and either MC or LM) rated the methodological quality of the included studies using the standardized COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist [10-12]. For each measurement property, the design requirements were rated using a 4-point scale (i.e., excellent, good, fair, or poor). The lowest score counts method was applied, e.g., the final methodological quality was scored as poor in the case of a poor score on one of the items. The lowest rated items that determined the final score for each study are shown in Electronic Supplementary Material Online Resource 2. The methodological quality of the content validity studies was not assessed as often little or no information on the development of the questionnaire or on the assessment of relevance, comprehensiveness, and comprehensibility of items was available. One minor adaption to the original COSMIN checklist, also described in a previous review [13], was applied: Percentage of Agreement (PoA) was removed from the reliability box and added to the measurement error box as an excellent statistical method [14]. To assess the methodological quality of test–retest reliability studies, standards previously described by Chinapaw et al. [8] regarding the time interval were applied: between > 1 day and < 3 months for questionnaires recalling a standard week; between > 1 day and < 2 weeks for questionnaires recalling the previous week; and between > 1 day and < 1 week for questionnaires recalling the previous day.

Questionnaire Quality Assessment

Reliability

Reliability is defined as “the degree to which a measurement instrument is free from measurement error” [15]. Test–retest reliability outcomes were considered acceptable under the following conditions: (1) intraclass correlation coefficients and kappa values ≥ 0.70 [16]; or (2) Pearson, Spearman, or unknown correlations ≥ 0.80 [17]. Measurement error is defined as “the systematic and random error of a score that is not attributed to true changes in the construct” [15]. Measurement error outcomes were considered acceptable when the smallest detectable change (SDC) was smaller than the minimal important change (MIC) [16].

The majority of the included studies reported multiple correlations per questionnaire for test–retest reliability, e.g., separate correlations for each questionnaire item. Therefore, an overall evidence rating was applied in order to obtain a final test–retest reliability rating, incorporating all correlations per questionnaire for each study. A positive (+) evidence rating was obtained if ≥ 80% of correlations were acceptable, a mixed (±) evidence rating was obtained when ≥ 50% and < 80% of correlations were acceptable, and a negative (–) evidence rating was obtained when < 50% of correlations were acceptable. For measurement error, no final evidence rating could be applied, as to our knowledge no information on the MIC is available for the included questionnaires. Furthermore, in the case of PoA, higher scores represent less measurement error.

Validity

For validity, three different measurement properties can be distinguished, i.e., content validity, construct validity, and criterion validity [15]. Content validity is defined as “the degree to which the content of a measurement instrument is an adequate reflection of the construct to be measured” [15]. Construct validity is “the degree to which the scores of a measurement instrument are consistent with (a priori drafted) hypotheses” [15]. Hypotheses can concern internal relationships, i.e., structural validity, or relationships with other instruments. Criterion validity is defined as “the degree to which the scores of an instrument are an adequate reflection of a gold standard” [15].

Content validity could not be assessed, as for most studies a justification of choices, e.g., comprehensibility findings based on input from the target population or experts in the field, were missing. A summary of the studies examining content validity has been added in the results section. Since a priori formulated hypotheses for construct validity were often lacking, in line with previous reviews [13, 18] we formulated criteria with regard to the relationships with other instruments; see Table 1 for criteria. The criteria were subdivided by level of evidence, level 1 indicating strong evidence, level 2 indicating moderate evidence, and level 3 indicating weak evidence. Table 1 also includes criteria for criterion validity, e.g., when doubly labeled water was used as a comparison measure for questionnaires aiming to assess physical activity energy expenditure.

Table 1

Constructs of physical activity measured by the questionnaires evaluating construct and/or criterion validity, subdivided by level of evidence, and criteria for acceptable correlations

Constructs of physical activity measured	Level 1	Level 2	Level 3
Physical activity, all constructs (i.e., at least including active transport, sports, physical education, recreational activities, and chores)	Direct observation ≥ 0.70Accelerometer total or activity counts ≥ 0.60aPAEE measured by doubly labeled water ≥ 0.60	Accelerometer vigorous counts, moderate counts, or moderate and vigorous counts ≥ 0.40Pedometer counts ≥ 0.40	Questionnaire, diary, or interview; corresponding constructs ≥ 0.70VO2max ≥ 0.40
Physical activity, not all constructs or timeframes (e.g., excluding time spent at school or chores)	Direct observation ≥ 0.70Accelerometer total or activity counts; corresponding timeframe ≥ 0.60	Accelerometer total or activity counts; total daytime ≥ 0.40Accelerometer moderate and vigorous counts ≥ 0.50	Questionnaire, diary, or interview; corresponding constructs ≥ 0.70VO2max ≥ 0.40
Physical activity, single constructs (e.g., only unstructured free play, cycling, time spent outdoors)		Accelerometer total or activity counts ≥ 0.40Accelerometer moderate and vigorous counts ≥ 0.50Pedometer counts ≥ 0.40	Questionnaire, diary, or interview; corresponding constructs ≥ 0.70VO2max ≥ 0.40Cycle computer ≥ 0.70b
Physical activity energy expenditure	PAEE measured by doubly labeled water ≥ 0.70	Accelerometer total or activity counts ≥ 0.50Pedometer counts ≥ 0.40	Questionnaire, diary, or interview; corresponding constructs ≥ 0.70VO2max ≥ 0.40
Vigorous activity	Accelerometer vigorous counts ≥ 0.60	Accelerometer total or activity counts ≥ 0.40Pedometer counts ≥ 0.40	Questionnaire, diary, or interview; corresponding constructs ≥ 0.70VO2max ≥ 0.60
Moderate and vigorous activity	Accelerometer moderate and vigorous counts ≥ 0.60	Accelerometer total or activity counts ≥ 0.40Pedometer counts ≥ 0.40	Questionnaire, diary, or interview; corresponding constructs ≥ 0.70VO2max ≥ 0.60
Moderate activity	Accelerometer moderate counts ≥ 0.60	Accelerometer total or activity counts ≥ 0.40Pedometer counts ≥ 0.40	Questionnaire, diary, or interview; corresponding constructs ≥ 0.70VO2max ≥ 0.50
Walking	Pedometer, accelerometer walking counts ≥ 0.70	Accelerometer total or activity counts ≥ 0.40	Questionnaire, diary, or interview; corresponding constructs ≥ 0.70

PAEE physical activity energy expenditure, VO maximal oxygen uptake

aPreferably activity counts (i.e., light, moderate, and vigorous); however, as sedentary counts have a minimal contribution, total counts are also acceptable

bIf used as a comparison for cycling

Most construct validity studies examined relationships with other instruments, reporting separate correlations for each questionnaire item. As with reliability, an overall evidence rating was applied incorporating all available correlations for each questionnaire per study (i.e., a positive, mixed, or negative evidence rating was obtained). Since no hypotheses were available for mean differences and limits of agreement, only a description of these results is included in the Results section (Sect. 3).

Inclusion of Results from the Previous Review

To draw definite conclusions regarding the best available questionnaires, the most promising questionnaires based on the previous review [8], i.e., published before May 2009, were also taken into account. As the previous review combined the methodological quality assessment and the questionnaire quality (i.e., results regarding measurement properties) in one rating, we reassessed the methodological and questionnaire quality of these previously published studies. We included only the studies that received a positive rating in the previous review for each measurement property. However, in the previous review, no final rating for measurement error was applied; therefore, all measurement error studies were reassessed and included in the current review. In addition, for construct validity, no final rating was applied in the previous review, as the majority of studies did not formulate a priori hypotheses. We chose to reassess the two studies showing the highest correlations between the questionnaire and an accelerometer, for each age category. The studies below this ‘top 2’ showed such low correlations that they would receive a negative evidence rating using our criteria. Furthermore, we assessed three other studies that formulated a priori hypotheses, as these studies may score higher regarding methodological quality. The reassessed studies are included in Tables 2, 3, 4 in the Results section.

Table 2

Construct validity of physical activity questionnaires for youth sorted by age category, methodological quality, and level of evidence and evidence rating

Questionnaire	Study populationa	Comparison measure	Resultsb,c	Methodological qualityd	Level of evidence and evidence ratinge
Preschoolers (mean age < 6 years)
Preschool-age Children’s Physical Activity Questionnaire (Pre-PAQ) (proxy) [58]	n = 67Age: 3–5 yearsSex: 48% girls	Acc. (Actigraph)(cut-points not reported)	Level 3 Pre-PAQ vs. LPA (Sirard): MD − 4.8, LoA [− 105.4; 96.0], r − 0.07Level 4 Pre-PAQ vs. MPA (Sirard): MD 48.2, LoA [− 24.9; 121.3], r 0.13Level 5 Pre-PAQ vs. VPA (Sirard): MD 1.9, LoA [− 37.5; 41.3], r 0.17Level 4-5 Pre-PAQ vs. MVPA (Sirard): MD 50.1, LoA [− 42.9; 143.1], r 0.17Level 3–5 Pre-PAQ vs. non-sedentary (Reilly): MD 20.9, LoA [− 121.9; 163.7], r 0.16Level 3–5 Pre-PAQ vs. LMVPA (Sirard): MD 45.2, LoA [− 103.6; 194.1], r 0.05	Good	Level 1: –
Modified Burdette proxy report (proxy) [59]	n = 107Age: 3.4 ± 1.2 yearsSex: percentage girls unknown	Acc. (Actigraph)(cut-points: LPA 38–419 counts/15 s.; MVPA ≥ 420 counts/15 s)	PA: vs. total PA min/day, PCC 0.30; vs. MVPA min/day, PCC 0.34	Fair	Level 1: –
Modified Harro proxy report (proxy) [59]	n = 131Age: 3.8 ± 1.3 yearsSex: percentage girls unknown	Acc. (Actigraph)(cut-points: LPA 38–419 counts/15 s; MVPA ≥ 420 counts/15 s)	MVPA: vs. MVPA min/day, PCC 0.10; vs. total PA min/day, PCC 0.09	Fair	Level 1: –
Physical activity questionnaire for parents of preschoolers in Mexico [40]	n = 35Age: 4.4 ± 0.7 years [3–5]Sex: 51% girls	Acc. (Actigraph)(age-specific cut-points used)	MPA vs.  % of time in MPA: Sirard SCC − 0.23, Pate SCC − 0.07VPA vs.  % of time in VPA: Sirard SCC 0.53, Pate SCC 0.41MVPA vs.  % of time in MVPA: Sirard SCC 0.49, Pate SCC 0.34	Poor	Level 1: –
Children’s Physical Activity Questionnaire (CPAQ) (proxy) [60] f	n = 27Age: 4.9 ± 0.7 years [4, 5]Sex: 38% girls	DLWAcc. (Actigraph)(cut-points: MVPA ≥ 3000 or ≥ 1952 cpm)	MVPA: vs. acc. cut-point 3000 cpm SCC 0.42, MD (SD) 235.9 (362.0); vs. acc. cut-point 1952 cpm MD (SD) − 76.5 (361.6)                                                                           PAEE vs. DLW: SCC 0.22, MD (SD) − 14.4 (52.4)	Poor (all comparison measures)	Level 1: –
Physical activity and sedentary behavior proxy questionnaire (based on Canadian Health Measures Survey [CHMS]) (proxy) [61]	n = 87Age: 4–70 monthsSex: 54% girls	Acc. (Actical)(cut-points: LPA 100–1149 cpm; MVPA ≥ 1150 cpm; total PA ≥ 100 cpm)	Total PA vs. total PA min/day: MDg 131 min/day, LoA [–80; 290]h, SROC 0.39 (95% CI 0.19-0.56)Outdoor unstructured free play aside from school daycare setting vs. total PA min/day: SROC 0.30 (95% CI 0.09–0.49)Unstructured play in school/daycare setting vs. total PA min/day: SROC 0.42 (95% CI 0.23–0.58)Structured PA vs. total PA min/day: SROC 0.26 (95% CI 0.05–0.46)	Poor	Level 1: –Level 2: –
Children (mean age ≥ 6 to < 12 years)
Out-of-school Physical Activity questionnaire [62]	n = 126Age: 11 yearsSex: 60% girls (in total sample n = 155)	Acc. (Actigraph)(cut-point: MVPA ≥ 2296 cpm)	MVPA duration vs. MVPA min/day: SCC 0.25, MDg − 6.3 minMVPA frequency vs. MVPA min/day: SCC 0.25	Fair	Level 1: –
Children’s Leisure Activities Study Survey Chinese-version questionnaire (CLASS-C) [50]	n = 139Age: [9–12 years]Sex: 65% girls	Acc. (Actigraph)(age-specific cut-points used)	MPA vs. MPA min/week: boys weekdays SROC 0.21, weekends SROC 0.32, 1 week SROC 0.33, girls weekdays SROC 0.19, weekends SROC 0.22, 1 week SROC 0.29, total sample MD − 18.9 min, LoA [–89.3; 51.5]VPA vs. VPA min/week: boys weekdays SROC 0.35, weekends SROC 0.33, 1 week SROC 0.29, girls weekdays SROC 0.48, weekends SROC 0.19, 1 week SROC 0.43, total sample MD 12.6 min, LoA [–34.8; 60.0]Bland–Altman plot depicts a positive magnitude biasiMVPA vs. MVPA min/week: boys weekdays SROC 0.21, weekends SROC 0.13, 1 week SROC 0.27, girls weekdays SROC 0.44, weekends SROC 0.19, 1 week SROC 0.48, total sample MD − 6.2 min, LoA [–101.5; 89.1]Bland–Altman plot depicts a small positive magnitude biasj	Fair	Level 1: –
Physical Activity Questionnaire for Older Children (PAQ-C) [27] f	n = from 73 (Caltrac) to 97 (activity rating and Godin 1)Age: 11.3 ± 1.4 years [9–14]Sex: 58% girls	Acc. (Caltrac)(no cut-points used)7-day PA recall by interview (PAR)Activity ratingGodin 1 and 2 (leisure time exercise questionnaires)CHFT	PAQ-C: vs. accumulated counts r 0.39; vs. PAR r 0.46; vs. PAR h r 0.43; vs. activity rating r 0.57; vs. Godin 1 r 0.41; vs. Godin 2 r − 0.57; vs. CHFT r 0.283 of 6 hypotheses correct	Fair (all comparison measures)	Level 1: –
Previous Day Physical Activity Recall (PDPAR) [30]	n = 37Age: 10.8 ± 0.1 years (in total sample n = 38)Sex: 51% girls	Acc. (CSA activity monitor)(cut-point not reported)	Mean METs: vs. total counts SROC 0.39; vs. MVPA min SROC 0.43PA ≥ 3 METs: vs. total counts SROC 0.23; vs. MVPA min SROC 0.19PA ≥ 6 METs: vs. total counts SROC 0.35; vs. MVPA min SROC 0.38	Fair	Level 2: –Level 1: –
Physical Activity Questionnaire for older Children (PAQ-C) (Spanish version) [52]	n = 78Age: 11.0 ± 1.2 years (in total sample n = 83)Sex: 45% girls (in total sample n = 83)	Acc. (Actigraph)(cut-points: SB 0–100 cpm; LPA 101–2295 cpm; MPA 2296–4011 cpm; VPA ≥ 4012 cpm)	Total score vs. total PA: SROC 0.28, MD z value 0.10, LoA z values [–1.82; 2.02]kActivity checklist: vs. total PA SROC 0.08, vs. MVPA SROC 0.04PE vs. MVPA: SROC 0.04Recess: vs. total PA SROC 0.14, vs. MVPA SROC 0.19Lunch: vs. total PA SROC 0.07, vs. MVPA SROC 0.00After school: vs. total PA SROC 0.15, vs. MVPA SROC 0.15Afternoon: vs. total PA SROC 0.29, vs. MVPA SROC 0.28Weekend: vs. total PA SROC 0.12, vs. MVPA SROC 0.08Intensity last week: vs. total PA SROC 0.24, vs. MVPA SROC 0.21Week summary: vs. total PA SROC 0.30, vs. MVPA SROC 0.31	Fair	Level 1: –Level 2: –
Godin Leisure-Time Exercise Questionnaire [63]	n = 31Age: 10.6 ± 0.2 yearsSex: 45% girls	Acc. (Caltrac)(no cut-points used)	Average total leisure activity score: PCC 0.50 (0.86 when two outliers were removed)	Fair	Level 2: +
Multimedia Activity Recall for Children and Adolescents (MARCA) [64] f	n = 66Age: 11.6 ± 0.8 yearsSex: 50% girls	Acc. (Actigraph)(no cut-points used)	PAL vs. cpm: r 0.45MVPA vs. total counts: r 0.35Min. locomotion vs. total counts: r 0.375 of 5 hypotheses correct	Fair	Level 2: –
Chinese version of the Physical Activity Questionnaire for Older Children (PAQ-C) [43]	n = 358Age: 10.5 ± 1.1 years [8–13] (in total sample n = 742)Sex: 46% girls	Acc. (Actigraph)(cut-points: MPA 2296–4011 cpm; VPA ≥ 4012 cpm)	PAQ-C: vs. MPA min/day SCC 0.24; vs. VPA min/day SCC 0.36; vs. MVPA min/day SCC 0.33	Fair	Level 2: –
Youth Activity Profile (YAP) [38]	n = 291Age: 9.7 ± 1.0 years (n = 135), 11.7 ± 0.8 years (n = 67), 15.7 ± 1.2 years (n = 89)Sex: 56% girls	Sense Wear Armband (SWA)(cut-point not reported)	School activity vs. MVPA min/week.: MD − 15.6 ± 6.2 min, LoA [− 25.8; − 5.3], r 0.58Out-of-school activity weekday vs. MVPA min/week: MD 3.4 ± 16.6 min, LoA [− 24.2; 31.0], r 0.19Out-of-school activity weekend vs. MVPA min/weekend: MD − 21.7 ± 13.2 min, LoA [− 43.7; 0.3], r 0.22	Fair	Level 2: –
Food, Health, and Choices questionnaire (FHC-Q) [37]	n = 66Age: < 9 to > 12 yearsSex: 50% girls	PAQ-C	Frequency of both medium and heavy activity vs. PAQ-C: PCC 0.52Frequency of medium activity vs. PAQ-C medium activity: PCC 0.42Frequency of heavy activity vs. PAQ-C heavy activity: PCC 0.46	Fair	Level 3: –
Self-administered questionnaire to assess physical activity and sedentary behaviors [65]	n = 86Age: 10.2 ± 1.1 yearsSex: 54% girls	Acc. (Actigraph)(cut-points not reported)	MVPA vs. MVPA acc.: ICC 0.06, MD − 117.6 min. LoA [− 864.3; 629.0]g,l	Poor	Level 1: –
The South American Youth/Child Cardiovascular and Environment Study (SAYCARE) Physical Activity (PA) questionnaire (proxy) [66]	n = 82Age: 3–10 yearsSex: 54% girls	Acc. (Actigraph)(cut-points: LPA 26–573 cpm; MPA 574–1002 cpm; VPA ≥ 1003 cpm)	MPA vs. acc. MPA: SCC 0.61, bias − 13.6 min/day, LoA − [–15.2; 41.4]VPA vs. acc. VPA: SCC 0.27, bias − 35.3 min/day, LoA [− 36.8; 56.1]Weekly total MVPA vs. acc. total MVPA: 0.44, bias − 22.9 min/day, LoA [− 24.6; 19.9] % of agreement with PA guidelines ≥ 60 min/day: κ − 0.40	Poor	Level 1: –
Canadian Health Measures Survey (CHMS) [67]	n = 878Age: 8.7 years (95% CI 8.5–8.9) [6–11]Sex: 49% girls	Acc. (Actical)(cut-point: MVPA ≥ 1500 cpm)	MVPA vs. MVPA min/day: PCC 0.29	Poor	Level 1: –
Many Rivers Physical Activity Recall Questionnaire (MRPARQ) (modified version of the APARQ) [68]	n = 86Age: 11.1 ± 0.7 yearsSex: 59% girls	Acc. (Actigraph)(cut-point not reported)	MVPA vs. mean weekday MVPA min/day: PCC 0.37, ICC 0.25Bland–Altman plot depicts a positive magnitude biasm	Poor	Level 1: –
Patient Assessment and Council for Exercise (PACE) [69]	n = 18Age: 11.9 ± 2.0 yearsSex: 59% girls(Age and sex total sample n = 22)	Acc. (sensewear SP3 PRO)Acc. (Actigraph)(cut-points not reported)Diary (SRI and SRA)	Active days/week: vs. Actigraph (≥ 60 MVPA min/day) PCC 0.27; vs. SP3 (≥ 60 MVPA min/day) PCC 0.17; vs. SRI PCC 0.25; vs. SRA PCC 0.34Meeting guideline (1 h MVPA/day): vs. Actigraph PoA 56%, sens 28%, spec 100%, kappa 0.22; vs. SP3 PoA 33%, sens 20%, spec 100%, kappa 0.07	Poor (all comparison measures)	Level 1: –
Self-Administered Physical Activity Checklist (SAPAC) (Greek version) [49]	n = 90Age: 11.4 ± 0.6 years (boys), 11.3 ± 0.6 years (girls)Sex: 57% girls	Acc. (RT3 Research Tracker)(cut-points not reported)	Total-MET vs. total METs: Kendall’s tau-b r 0.31, MD − 600, LoA [− 1800; 400]nMET-LPA vs. LPA METs: Kendall’s tau-b r 0.03, MD − 750, LoA [− 1250; − 200]nBland–Altman plot depicts a negative magnitude biasoMET-MVPA vs. MVPA METs: Kendall’s tau-b r 0.37, MD 0, LoA [− 900; 900]n	Poor	Level 1: –
Assessment of Young Children’s Activity using Video Technology (ACTIVITY) [70] f	n = 47Age: 7.7 ± 0.5 yearsSex: 40% girls	Acc. (Caltrac)(no cut-points used)HR monitor (Polar)	ACTIVITY total score: vs. cpm r 0.40; vs. HR average activity 0.17, vs. 50% HR reserve 0.51	Poor (all comparison measures)	Level 1: –
Synchronised Nutrition and Activity Program (SNAP) [71] f	n = 121Age: 10.7 ± 2.2 years [7–15]Sex: 60% girls	Acc. (Actigraph)(cut-point not reported)	MVPA vs. total MVPA min.: MD − 9 min (90% CI − 23 to 5)Proportion complying to MVPA guideline: MD 0.02 (90% CI − 0.08 to 0.12)	Poor	Level 1:?
PA questionnaire for parents and teachers [72] f	n = 62Age: 7.0 ± 0.7 years [4–8]Sex: 52% girls	Acc. (Caltrac)(no cut-points used)HR monitor (Polar)	MVPA vs. total Caltrac score: r 0.53; vs. HR: ≥ 140 and ≥ 150 bpm r 0.40	Poor (all comparison measures)	Level 2: +
Physical Activity Questionnaire for older Children (PAQ-C) [51]	n = 58Age: 7–9 yearsSex: 48% girls	Pedometer (Omron)	PAQ-C score: vs. average steps/day SROC 0.49; vs. total no. of steps weekdays SROC 0.53	Poor	Level 2: +
The Modified Godin Leisure-Time Exercise Questionnaire [45]	n = 139Age: 11.1 ± 0.4 yearsSex: 52% girls	Acc. (Actigraph)(cut-points not reported)	Godin-Child Questionnaire total no. of min of activity/week. vs. acc. MVPA: r 0.22 (fall/autumn), r 0.24 (spring)	Poor	Level 2: –
Parent proxy-report of physical activity and sedentary activities (proxy) [73]	n = 167 (validity vs. acc.), n = 125 (validity vs. diary)Age: 6–10 years, 13–14 yearsSex: 51% girls (in total sample n = 189)	Acc. (Actigraph)(cut-points not reported)Time activity diary (PA record)	vs. acc. (adjusted for school grade, age, sex, and maternal education):Active behavior score vs. MVPA min/day: SCC 0.21Time spent outdoors vs. MVPA min/day: SCC 0.10Playing vigorously active indoors vs. MVPA min/day: SCC 0.08Playing vigorously active outdoors vs. MVPA min/day: SCC 0.19Cycling vs. MVPA min/day: SCC 0.11Time spent breathing hard and sweating vs. MVPA min/day: SCC 0.07Attending sports training (outside school) vs. MVPA min/day: SCC 0.11vs. diary:Tended to overestimate actively playing indoors and cycling, active play outside was comparable across both measures	Poor (all comparison measures)	Level 2: –
Diet and lifestyle questionnaire [74]	n = 446Age: 9.0–11.9 years (in total sample n = 563)Sex: 53% girls (in total sample n = 563)	Acc. (ActiGraph)(cut-point: MVPA ≥ 3000 cpm)	No./days child was active > 60 min: vs. mean MVPA min/day SCC 0.04; vs.  % that MET MVPA guidelines SCC 0.07	Poor	Level 2: –
Active Transportation to school and work in Norway (ATN) questionnaire [75]	n = 58Age: 11.4 ± 0.5 yearsSex: 54% girls	Cycle computerAcc.(Actigraph)(no cut-points used)	No. of trips walking vs. total cpm: SROC 0.12No. of trips cycling vs. cycling km/week: SROC 0.60	Poor (all comparison measures)	Level 2: –Level 3: –
The ENERGY-child questionnaire [48]	n = 96Age: [11.4 ± 0.6 to 12.0 ± 0.6 years]Sex: [31–67% girls]	Cognitive interview	Walking to school (no./days): ICC 0.84, PoA 75%, (amount of time), ICC 0.59, PoA 74%Transport today to school: ICC 0.67, PoA 74%Activity during breaks: ICC 0.65, PoA 81%Sport (h): (first sport) ICC 0.61, PoA 50%, (second sport) ICC 1.00, PoA 36%, (yesterday) ICC 0.22, PoA 50%Bike to school (no./days): ICC 0.81, PoA 73%, (amount of time), ICC 0.66, PoA 75%	Poor	Level 3: –
A physical activity questionnaire [76]	n = 4254Age: 11.3 yearsSex: 51% girls (in total sample n = 4452)	Reported PA level of the adolescent by the mother and the adolescent	PA: vs. mothers perception kappa 0.13, PoA 64.7%; vs. adolescents perception kappa 0.11, PoA 64.8%	Poor	Level 3: –
Instrument to assess children’s outdoor active play in various locations (proxy) [77]	n = 46Age: 9.2 years [7.9–11.7]Sex: 50% girls	Diary (parent-report)	Weekday: yard at home kappa 0.48, PoA 63.0% friend’s/neighbor’s yard kappa 0.40, PoA 65.2%, own street/court/footpath kappa 0.51, PoA 67.4%, nearby streets/court/footpath kappa 0.60, PoA 80.4%, park/playground kappa 0.39, PoA 73.9%, facilities or sport ovals kappa 0.35, PoA 67.4%, school grounds for free play outside school hours PoA 67.4%, other places PoA 86.9%Weekend day: yard at home kappa 0.44, PoA 71.7%, friend’s/neighbor’s yard kappa 0.50, PoA 76.1%, own street/court/footpath kappa 0.43, PoA 67.4%, nearby streets/court/footpath kappa 0.44, PoA 78.3%, park/playground kappa 0.37, PoA 71.7%, facilities or sport ovals kappa 0.37, PoA 71.7%, school grounds for free play outside school hours PoA 100.0%, other places kappa 0.22, PoA 76.1%	Poor	Level 3: –
Questions from the National Longitudinal Survey of Children and Youth [78]	n = 3940 (organized sports question)n = 3958 (leisure sports question)Age: 5th gradersSex: percentage girls unknown	Parent-reported questions from the National Longitudinal Survey of Children and Youth	Organized sports: kappa 0.41 (95% CI 0.39–0.44)Leisure sports: kappa 0.11 (95% CI 0.08–0.14)	Poor	Level 3: –
Physical Activity Questionnaire for Older Children (PAQ-C) (minor modifications) [44]	n = 132Age: 10.3 ± 0.6 years [9–11]Sex: 48% girls	Cardiovascular fitness (½ mile walk run test)	PAQ-C summary score: PCC − 0.38In-school factor: PCC − 0.27Outside-of-school: PCC − 0.37	Poor	Level 3: –
Older children and adolescents (mean age ≥ 12 years)
A physical activity questionnaire of the Estonian Children Personality Behavior and Health Study (ECPBHS) [79]	n = 224Age: 12.2 ± 0.8 yearsSex: 0% girls	Acc. (Actigraph)(cut-point: MVPA ≥ 2000 cpm)Parent-reported child PA (same questionnaire)	Child MVPA index: vs. acc. MVPA min/day r 0.28 (95% CI 0.16–0.40); vs. parent r 0.54 (95% CI 0.44–0.62), MD 0.33 min, LoA [–14.8; 15.4]	Good (all comparison measures)	Level 1: –
A physical activity questionnaire of the Estonian Children Personality Behavior and Health Study (ECPBHS) (proxy) [79]	n = 224Age: 12.2 ± 0.8 yearsSex: 0% girls	Acc. (Actigraph)(cut-point: MVPA ≥ 2000 cpm)Child-reported child PA (same questionnaire)	Parent MVPA index: vs. acc. MVPA min/day r 0.30 (95% CI 0.18–0.42); vs. child r 0.54 (95% CI 0.44–0.62), MDp 0.33 min, LoA [–14.8; 15.4]	Good (all comparison measures)	Level 1: –
3-Day Physical Activity Record (3DPARecord) (Greek version) [33]	n = 33Age: 13.7 ± 0.8 yearsSex: 43% girls (age and sex total sample n = 40)	Acc. (MTI/CSA)(no cut-points used)	3DPAR average scores vs. cpm: PCC 0.63	Fair	Level 1: +
Seven-Day Physical Activity Recall (7 Day-PAR) (Spanish version) [80]	n = 123Age: 14.9 ± 0.9 years [13–17]Sex: 59% girls	Acc. (Actigraph)(cut-points: SB 0–100 cpm; LPA 101–2295 cpm; MPA 2296–4011 cpm; VPA ≥ 4012 cpm)Aerobic fitness (20 m shuttle run)	LPA vs. LPA acc.: r − 0.22MPA: vs. MPA acc. r 0.25, vs. fitness r − 0.17Hard PA: vs. VPA acc. r 0.18, fitness r 0.07Very hard: PA vs. VPA acc. r 0.38, fitness r 0.42	Fair (all comparison measures)	Level 1: –
Youth Physical Activity Questionnaire (YPAQ) [81]	n = 44Age: 12.7 years [12–13]Sex: 61% girls	Acc. (Actigraph)(cut-points: MVPA ≥ 2295 cpm)	MVPA vs. acc. MVPA: PCC 0.47, SROC 0.39, MD 25.7 min, LoA [− 72.7; 124.0]q	Fair	Level 1: –
International Physical Activity Questionnaire – Short Form (IPAQ-SF) [82]	n = 191Age: 14.0 ± 0.7 yearsSex: 0% girls	Acc. (Actigraph)(cut-points: SB < 100 cpm; LPA > 100 cpm; MPA > 2000 cpm; VPA > 4000 cpm)	MPA min/day vs. acc. MPA min/day: PCC 0.11VPA min/day vs. acc. VPA min/day: PCC 0.24MVPA min/day vs. acc. MVPA min/day: PCC 0.31, MD 13.4 min/day, LoA [− 54.2; 80.8]g,rWalking min/day: vs. acc. steps PCC 0.32, vs. acc. LPA min/day PCC 0.07, MD − 146.1 min/day	Fair	Level 1: –
Tartu Physical Activity Questionnaire (TPAQ) [82]	n = 191Age: 14.0 ± 0.7 yearsSex: 0% girls	Acc. (Actigraph)(cut-points: SB < 100 cpm; LPA > 100 cpm; MPA > 2000 cpm; VPA > 4000 cpm)	MVPA min/day vs. acc. MVPA min/day: PCC 0.35, MD − 3.40 min/day, LoA [–49.6; 42.8]g,sWalking/cycling min/day: vs. acc. steps PCC 0.19, vs. MVPA PCC 0.21, vs. LPA PCC − 0.02, MD − 125.1 min/day	Fair	Level 1: –
Physical Activity and Lifestyle Questionnaire (PALQ) (Greek version) [33]	n = 33Age: 13.7 ± 0.8 yearsSex: 43% girls (age and sex total sample n = 40)	Acc. (MTI/CSA)(no cut-points used)	PALQ average scores vs. cpm: PCC 0.53	Fair	Level 1: –
Moderate and vigorous physical activity items of the Youth Risk Behavior Survey (YRBS) [83]	n = 125Age: 12.2 ± 0.6 yearsSex: 53% girls (age and sex total sample n = 139)	Acc. (Actigraph)(age-specific cut-points used [Freedson])	Meeting MPA recommendations (≥ 30 min/day for ≥ 5 days/week) vs. accumulated MPA min.: ≥ 5 days PoA 20.8%, < 5 days PoA 8.8%, sens 0.23, spec 0.92, kappa across four acc. measures ranged from − 0.05 to 0.03Meeting VPA recommendations (≥ 20 min/day for ≥ 3 days/week) vs. accumulated VPA min: ≥ 3 days PoA 19.2, < 3 days PoA 20.0, sens 0.86, spec 0.26; kappa across four acc. measures ranged from − 0.002 to 0.06	Fair	Level 1: –
3-Day Physical Activity Recall (3DPARecall) instrument [20]	n = 70Age: 14.0 ± 0.9 years [13–16]Sex: 100% girls	Acc. (CSA activity monitor)(cut-points not reported)	Total METs/day: vs. 7 days counts/day PCC 0.51; vs. 3 days counts/day PCC 0.46MVPA blocks/day: vs. 7 days MVPA min/day PCC 0.35; vs. 3 days MVPA min/day PCC 0.27VPA blocks/day: vs. 7 days VPA min/day PCC 0.45; vs. 3 days VPA min/day PCC 0.41	Fair	Level 1: –
International Physical Activity Questionnaire - Short Form (IPAQ - SF) [84]	n = 1021Age: 14.3 ± 1.6 years [12–18]Sex: 47% girls	Acc. (ActiGraph)(cut-points: LPA 101–2799 cpm; MPA 2800–3999 cpm; VPA ≥ 4000 cpm)	Total activities vs. cpm: SCC 0.31MPA and walking vs. MPA min/day: SCC 0.20VPA vs. VPA min/day: SCC 0.22MVPA and walking vs. MVPA min/day: SCC 0.22	Fair	Level 1: –
PACE + questionnaire [85]	n = 235Age: 14.7 ± 3.1 yearsSex: 59% girls	Acc. (Actigraph)(cut-point not reported)	PA (days/week ≥ 60 min MVPA): vs. MVPA min/day ≥ 5 valid days SCC 0.34; vs. MVPA min/day 7 valid SCC 0.27; vs. cpm ≥ 5 valid days SCC 0.33; vs. cpm 7 valid SCC 0.30Agreement meeting PA guideline, average method: ≥ 5 valid days PoA 78.7%, 7 valid days PoA 77.9%Agreement meeting PA guideline, all day method: ≥ 5 valid days PoA 90.2%, 7 valid days PoA 90.2%	Fair	Level 1: –
3-Day Physical Activity Recall (3DPARecall) (modified for Australian youth) [86]	n = 155Age: 12.3 ± 0.9 yearsSex: 50% girls	Activity monitor (CSA)(cut-points not reported)	MPA: vs. 3 days counts/day SCC 0.16; vs. 6 days counts/day SCC 0.15; vs. 3 days MPA min/day SCC 0.15; vs. 6 days MPA min/day SCC 0.14; vs. 3 days MVPA min/day SCC 0.14; vs. 6 days MVPA min/day SCC 0.12MET: vs. 3 days counts/day SCC 0.31; vs. 6 days counts/day SCC 0.31; vs. 3 days MPA min/day SCC 0.28; vs. 6 days MPA min/day SCC 0.26; vs. 3 days MVPA min/day SCC 0.29; vs. 6 days MVPA min/day SCC 0.27MVPA: vs. 3 days counts/day SCC 0.27; vs. 6 days counts/day SCC 0.26; vs. 3 days MPA min/day SCC 0.24; vs. 6 days MPA min/day SCC 0.24; vs. 3 days MVPA min/day SCC 0.23; vs. 6 days MVPA min/day SCC 0.25VPA: vs. 3 days VPA min/day males SCC 0.19, females SCC 0.33; vs. 6 days VPA min/day males SCC 0.16, females SCC 0.30	Fair	Level 1: –
Single-item activity measure [23]	n = 96 (acc. wear time 480 min/day)Age: 14.7 ± 0.5 yearsSex: 38% girls (total sample)(Age and sex total sample n = 123)n = 72 (acc. wear time 600 min/day)Age: 14.7 ± 0.5 yearsSex: 38% girls(Age and sex total sample n = 123)	Acc. (Actigraph)(cut-point not reported)	No. of days being physically active ≥ 60 min: vs. time spent in MVPA (480 min/day wear time) PCC 0.46 (95% CI 0.24–0.63); vs. time spent in MVPA (600 min/day wear time) PCC 0.44 (95% CI 0.24–0.63)	Fair	Level 1: –
Oxford Physical Activity Questionnaire (OPAQ) [23]	n = 96 (acc. wear time 480 min/day)Age: 14.7 ± 0.5 yearsSex: 38% girls (total sample)(Age and sex total sample n = 123)n = 72 (acc. wear time 600 min/day)Age: 14.7 ± 0.5 yearsSex: 38% girls(Age and sex total sample n = 123)	Acc. (Actigraph)(cut-point not reported)	MVPA: vs. time spent in MVPA (480 min/day wear time) PCC 0.43 (95% CI 0.23–0.62); vs. time spent in MVPA (600 min/day wear time) PCC 0.50 (95% CI 0.30–0.65)	Fair	Level 1: –
MVPA self-report questionnaire [87]	n = 203 (5 valid acc. days)Age: 15.8 ± 0.7 yearsSex: 61% girlsn = 103 (7 valid acc. days)Age: 15.8 ± 0.7 (total sample n = 203)Sex: 67% girls	Acc. (Actigraph)(cut-points not reported)	MVPA: vs. MVPA min/day (5 valid days) SROC 0.40 (95% CI 0.28–0.51); vs. MVPA min/day (7 valid days) SROC 0.49 (95% CI 0.32–0.62); vs. total cpm/day (5 valid days) SROC 0.42 (95% CI 0.30–0.5); vs. total cpm/day (7 valid days) SROC 0.49 (95% CI 0.33–0.63)Meeting PA recommendations (≥ 60 MVPA min/day): vs. average method (average of 60 MVPA min/valid day) (5 valid days) PoA 71.9%, sens 45.5%, spec 73.4%; vs. average method (7 valid days) PoA 88.2%, sens 16.7%, spec 92.7%; vs. all-day method (60 MVPA min on ≥ 5 days) (5 valid days) PoA 71.9%, sens 0%, spec 72.3%; vs. all-day method (60 MVPA min on ≥ 7 days) (7 valid days) PoA 69.6%, spec 69.6%	Fair	Level 1: –
Activity Questionnaire for Adults and Adolescents (AQuAA) [21]	n = 42Age: 13.4 ± 1.0 yearsSex: 50% girls	Acc. (Actigraph)(cut-points: LPA 700–4478 cpm; MPA 4479–8252 cpm; VPA; ≥ 8253 cpm)	Light activities vs. LPA min/week: SCC 0.11Moderate activities vs. MPA min/week: SCC − 0.21Vigorous activities vs. VPA min/week: SCC 0.21Moderate to vigorous activities vs. MVPA min/week: SCC − 0.23AQuAA score vs. PA cpm: SCC 0.13	Fair	Level 1: –
Physical Activity Questionnaire for Adolescents (PAQ-A) [88] f	n = ranging from 48 (Caltrac) to 85 (Activity rating, Godin 1 and 2)Age: 16.3 ± 1.5 yearsSex: 52% girls	Acc. (Caltrac)(cut-points not reported)7-day recall interview (PAR)Activity ratingGodin 1 and 2 (leisure time exercise questionnaires)	PAQ-A: vs. acc. activity counts/day r 0.33; vs. PAR 0.59; vs. PAR hours r 0.51; vs. activity rating r 0.73; vs. Godin 1 r 0.57; vs. Godin 2 r − 0.623 of 5 hypotheses correct	Fair (all comparison measures)	Level 1: –
Modified Physical Activity Questionnaire for Adolescents (PAQ-A) [34]	n = 88Age: 14.5 ± 1.7 yearsSex: 42% girls(Age and sex total sample n = 169)	Acc. (Actigraph)(cut-points not reported)IFIS (Fitness)	PAQ-A total score: vs. daily MVPA min/day SCC 0.39; vs. daily PA min/day SCC 0.42Sport and activity list: vs. daily MVPA min/day SCC 0.12; vs. daily PA min/day SCC 0.21Before school activity: vs. daily MVPA min/day SCC 0.02; vs. daily PA min/day SCC 0.14To school active travel: vs. daily MVPA min/day SCC 0.32; vs. daily PA min/day SCC 0.33PE: vs. daily MVPA min/day SCC 0.25; vs. daily PA min/day SCC 0.12After-school activity: vs. daily MVPA min/day SCC 0.26; vs. daily PA min/day SCC 0.26From school active travel: vs. daily MVPA min/day SCC 0.30; daily PA min/day SCC 0.22Evening activity: vs. daily MVPA min/day SCC 0.23; vs. daily PA min/day SCC 0.23Weekend activity: vs. daily MVPA min/day SCC 0.10; vs. daily PA min/day SCC 0.28Statement: vs. daily MVPA min/day SCC 0.38; vs. daily PA min/day SCC 0.33Weekly activity: vs. daily MVPA min/day SCC 0.34; vs. daily PA min/day SCC 0.29PAQ-A total score: vs. IFIS scores SCC 0.35	Fair (all comparison measures)	Level 1: –Level 2: –
An adapted version of the Assessment of Physical Activity Levels Questionnaire (APALQ) [53]	n = 77Age: 13.6 ± 1.1 yearsSex: 35% girls	Acc. (CSA)(cut-points: MPA 3000–5399 cpm; VPA > 5400 cpm)	PA index: vs. acc. MVPA min/day PCC 0.53, vs. steps/day PCC 0.47	Fair	Level 2: +
3-Day Physical Activity Recall (3DPARecall) instrument (Singaporean version) [42]	n = 219Age: 14.5 ± 1.1 years [13–16]Sex: 53% girls (age and sex total sample n = 221)	Pedometer (Digiwalker)	3-day average mean METs vs. step counts: SCC 0.403-day average VPA blocks vs. step counts: SCC 0.343-day average MVPA blocks vs. step counts: SCC 0.32	Fair	Level 2: –
Web-based physical Activity Questionnaire for Older Children (PAQ-C) [28]	n = 342 (pedometer), 391 (shuttlerun)Age: 12.8 yearsSex: 51% girls(Age and sex total sample n = 459)	Pedometer (Digiwalker)20mSRT	PAQ-C: vs. 3 days pedometer record PCC 0.28, vs. 20mSRT PCC 0.28	Fair (all comparison measures)	Level 2: –
Physical activity questionnaire of the Arab Teen Lifestyle Study [89]	n = 75Age: 16.1 ± 1.1 yearsSex: 48% girls	Pedometer (Digi-walker SW 701)	All activities vs. step counts/day: PCC 0.37MPA vs. step counts/day: PCC 0.27VPA vs. step counts/day: PCC 0.34Specific activities vs. step counts/day: walking PCC 0.35, jogging PCC 0.38, swimming PCC 0.14, household activities PCC 0.14, bicycling PCC 0.12, martial arts PCC 0.10, weight training PCC 0.04	Fair	Level 2: –
Previous Day Physical Activity Recall (PDPAR) [31]	ACTIVITYGRAMn = 147Age:12.4 ± 0.4 yearsSex: 44% girlsBiotrainer (first sample)n = 28 [25–28]Age: 12.4 ± 0.5 yearsSex: 50% girlsBiotrainer (second sample)n = 128Age: unknownSex: 36% girls	Activity monitor (Biotrainer Pro)(no cut-points used)ACTIVITYGRAM self-report assessment	PDPAR1 (compute no. of time intervals > 4 METs): vs. Biotrainer activity counts afternoon/evening r 0.65 (95% CI 0.36–0.94) (first sample), r 0.50 (second sample); vs. ACTIVITYGRAM r 0.40 (95% CI 0.25–0.55)PDPAR2 (SRI level was used instead of METs) vs. Biotrainer activity counts afternoon/evening r 0.56 (95% CI 0.24–0.88) (first sample), r 0.52 (second sample); vs. ACTIVITYGRAM r 0.50 (95% CI 0.36–0.64)	Poor vs. BiotrainerFair vs. questionnaire	Level 1: ± (PDPAR1)Level 1: – (PDPAR2)
Activitygram self-report assessment [31]	PDPARn = 147Age:12.4 ± 0.4 yearsSex: 44% girlsBiotrainern = 28 [25–28]Age: 12.4 ± 0.5 yearsSex: 50% girls	Activity monitor (Biotrainer Pro)(no cut-points used)PDPAR	ACTIVITYGRAM: vs. PDPAR 1 (compute no. of time intervals > 4 METs) r 0.40 (95% CI 0.25–0.55); vs. PDPAR 2 (SRI level scoring was used instead of METs) r 0.50 (95% CI 0.36–0.64); vs. Biotrainer activity counts r 0.50 (95% CI 0.17–0.83)	Poor vs. BiotrainerFair vs. questionnaire	Level 1: –
MVPA scores of the International Physical Activity Questionnaire Short form (IPAQ-SF) [90]	n = 76 (vs. acc.)Age: 12.7 ± 1.4 years (total sample n = 998)Sex: 53% girlsn = 998 (vs. questionnaire)Age: 12.7 ± 1.4 yearsSex: 50% girls	Acc. (Actigraph)(cut-point MVPA ≥ 3581 cpm), MVPA scores of the HBSC Research Protocol	MVPA IPAQ-SF T0: vs. MVPA acc. T0 girls r 0.08, boys r 0.10; vs. MVPA HBSC T0 girls r 0.55, boys r 0.62MVPA IPAQ-SF T1: vs. MVPA acc. T1 girls r 0.38, boys r − 0.05; vs. MVPA HBSC T1 girls r 0.76, boys r 0.70	Fair vs. acc.Poor vs. questionnaire	Level 1: –
MVPA scores of the Health Behavior in School-aged Children (HBSC) Research Protocol [90]	n = 76 (vs. acc.)Age: 12.7 ± 1.4 years (total sample n = 998)Sex: 53% girlsn = 998 (vs. questionnaire)Age: 12.7 ± 1.4 yearsSex: 50% girls	Acc. (Actigraph)(cut-point MVPA ≥ 3581 cpm), MVPA scores of the IPAQ-SF	MVPA HBSC T0: vs. MVPA acc. T0 girls r 0.10, boys r 0.35; vs. MVPA IPAQ-SF T0 girls r 0.55, boys r 0.62MVPA HBSC T1: vs. MVPA acc. T1 girls r 0.37, boys r 0.04; vs. MVPA IPAQ-SF T1 girls r 0.76, boys r 0.70	Fair vs. acc.Poor vs. questionnaire	Level 1: –
The South American Youth/Child Cardiovascular and Environment Study (SAYCARE) Physical Activity (PA) questionnaire [66]	n = 60Age: 11–18 yearsSex: 56% girls	Acc. (Actigraph)(cut-points: LPA 101–1999 cpm; MPA 2000–4999 cpm; VPA ≥ 4000 cpm)	MPA vs. acc. MPA: SCC 0.11, bias − 19.5 min/day, LoA [–41.6; 58.9]VPA vs. acc. VPA: SCC 0.65, bias 18.3 min/day, LoA [–92.6; 56.0]Weekly total MVPA vs. acc. total MVPA: 0.88, bias 16.0 min/day, LoA [–14.2; 17.4] % of agreement with PA guidelines ≥ 60 min/day: κ0.51	Poor	Level 1: ±
Pelotas Birth cohort physical activity questionnaire [91]	n = 25Age: 13.0 ± 0.3 yearsSex: 64% girls	DLW	PA: vs. total energy expenditure SROC 0.41; vs. PAEE SROC 0.30	Poor	Level 1: –
3-Day Physical Activity Recall (3DPARecall) questionnaire (modified) [92]	n = 20Age: 13.3 ± 0.9 yearsSex: 100% girls	Acc. (CSA)(cut-points not reported)	Total METs/day: vs. 7 days counts/day PCC 0.36; vs. 3 days counts/day PCC 0.63MPA blocks/day: vs. 7 days MPA min/day PCC 0.25; vs. 3 days MPA min/day PCC 0.29VPA blocks/day: vs. 7 days VPA min/day PCC 0.57; vs. 3 days VPA min/day PCC 0.49	Poor	Level 1: –
Short Questionnaire to ASsess Health-enhancing (SQUASH) physical activity in adolescents [93]	n = 17Age: 17.5 ± 0.6 yearsSex: 53% girls	DLW	PAEE: MDt 126 kcal/day, 95% LoA [–1207; 1459], SROC 0.50	Poor	Level 1: –
International Physical Activity Questionnaire for Adolescents (adapted version of the IPAQ) [94]	n = 2018Age: [12.5–17.5 years]Sex: 54% girls	Acc. (Actigraph)(cut-points: MPA 2000–3999 cpm; VPA ≥ 4000 cpm)VO2max	MPA: vs. MPA acc. min/day SROC 0.15, MD 31.6 min/day LoA [− 74.0; 137.2]; vs. VO2max SROC 0.08MVPA: vs. acc. MVPA min/day SROC 0.21; vs. VO2max SROC 0.21VPA: vs. acc. VPA min/day SROC 0.25, MD 13.2 min/day LoA [–65.0; 91.4]; vs. VO2max SROC 0.35Bland–Altman plots depict a positive magnitude biasu	Poor (all comparison measures)	Level 1: –
Recess Physical Activity Recall (RPAR) [95]	n = 49 (pedometer)Age: 13.3 ± 0.5 yearsSex: 65% girlsn = 32 (Biotrainer)Age: 12.9 ± 0.8 yearsSex: 31% girlsn = 32 (Actigraph)Age: 12.7 ± 0.8 yearsSex: 38% girls	Acc. (Actigraph)(cut-points not reported)Acc. (Biotrainer)(cut-points not reported)Pedometer (Yamax digiwalker)	Total PA: vs. pedometer steps PCC 0.35; vs. Biotrainer total counts PCC 0.40, counts adjusted for movement time PCC 0.54; vs. Actigraph total counts PCC 0.42MPA vs. MPA min: PCC 0.47VPA vs. VPA min: PCC 0.31MVPA vs. MVPA min: PCC 0.52, MDg 2.15 ± 3.67 min, LoA [–5.04; 9.34], syst. bias r = − 0.51Bland–Altman plot depicts a positive magnitude biasvTotal PA tertiles classification agreement (low, medium, high): vs. pedometer steps PoA 46.9% kappa 0.21; vs. Biotrainer total PA counts PoA 59.3% kappa 0.39, counts adjusted for movement time PoA 43.8% kappa 0.16; vs. Actigraph total counts 43.8%, kappa 0.16MVPA tertiles classification agreement (low, medium, high) vs. Actigraph MVPA min: PoA 62.5%, kappa 0.44	Poor (all comparison measures)	Level 1: –
Swedish Adolescent Physical Activity Questionnaire (SAPAQ) [96] f	n = 50Age: 16.9 ± 0.4 yearsSex: 62% girls	Acc. (MTI)(cut-points: LPA 500–1999 cpm; MPA 2000–5500 cpm; VPA ≥ 5500)	Total PA: vs. time spent in PA r 0.51; vs. counts/day r 0.49; vs. cpm r 0.45	Poor	Level 1: –
Activity Questionnaire for Adults and Adolescents (AQuAA) [22]	n = 236Age: 15.0 ± 1.0 yearsSex: 60% girls	Acc. (PAM)(cut-points not reported)	MPA vs. MPA min/week: MD 600 min/week, LoA [− 600; 1800]nVPA vs. VPA min/week: MD 200 min/week, LoA [− 500; 900]nMVPA vs. MVPA min/week: MD 800 min/week, LoA [− 700; 2100]nMVPA (-cycling) vs. MVPA min/week: MD 500 min/week, LoA [− 800; 1800]nAgreement between self-report and acc. differed by genderBland–Altman plots depict a positive magnitude biasw	Poor	Level 1:?
Computer assisted interview based on National Health and Nutrition Examination Survey (NHANES) survey [97]	n = 2761Age: 12–19 yearsSex: 48% girls	Acc. (Actigraph)(cut-point: MVPA ≥ 3000 cpm)	MVPA vs. MVPA min/day: median difference 27.4 min/dayBland–Altman plot depicts a negative magnitude biasx	Poor	Level 1:?
Previous Day Physical Activity Recall (PDPAR-24) self-report instrument [32]	n = 122Age: 13.8 ± 1.2 yearsSex: 53% girls	Pedometer (Digiwalker)	Mean METs vs. step counts: SCC 0.3430 min blocks VPA vs. step counts: SCC 0.3030 min blocks MVPA vs. step counts: SCC 0.29	Poor	Level 2: –
Dutch Physical Activity Checklist for Adolescents (PAQ-A) [35]	n = 44Age: 14.2 ± 1.8 yearsSex: 41% girls	Cardiopulmonary exercise test (CPET)	Spare-time activity—sports: SCC − 0.01Activity during PE: SCC 0.44Lunchtime activity: SCC 0.01After-school activity: SCC 0.05Evening activity: SCC 0.55Weekend activity: SCC 0.61Activity frequency during last 7 days: SCC 0.43Activity frequency during each day last week: SCC 0.41Total PA: SCC 0.52	Poor	Level 3: ±
Godin-Shephard Survey [98]	n = 102Age: 11.2 ± 0.7 years (n = 36), 13.6 ± 0.5 years (n = 36), 16.4 ± 0.8 years (n = 30)Sex: 51% girls	Activity ratingSeven-day Physical Activity Recall (PAR)	Godin-Shephard survey: vs. PAR total kcal of expenditure and kcal per kg body weight (KKD) r 0.39; vs. activity rating r 0.32	Poor	Level 3: –
Children’s Leisure Activities Study Survey (CLASS) questionnaire (modified version) [99]	n = 108Age: 12 yearsSex: 58.3% girls	Eurofit test battery: aerobic fitness	Total PA: SROC 0.43MPA: SROC 0.13VPA: SROC 0.20	Poor	Level 3: –

20mSRT 20 m shuttle run test, acc. accelerometer, bpm beats per min, CHFT Canadian Home Fitness Test, CI confidence interval, COSMIN COnsensus-based Standards for the selection of health Measurement Instruments, cpm counts per min, DLW doubly labeled water, HR heart rate, ICC intraclass correlation coefficient, LMVPA light, moderate, and vigorous physical activity, LoA limits of agreement, LPA light physical activity, MD mean difference, MET metabolic equivalent, MPA moderate physical activity, MVPA moderate to vigorous physical activity, PA physical activity, PAEE physical activity energy expenditure, PCC Pearson correlation coefficient, PE physical education, PoA percentage of agreement, r correlation coefficient without specific information on the kind of correlation, SCC Spearman correlation coefficient, SD standard deviation, sens sensitivity, spec specificity, SRA self-reported activity, SRI self-reported intensity, SROC Spearman rank order correlation, VO maximal oxygen uptake, VPA vigorous physical activity

aAge presented as mean age ± SD [range]

bMD represents mean questionnaire value – mean comparison measure value, unless stated otherwise

cData are presented in the following order: (i) construct measured by questionnaire; (ii) versus construct measured by comparison measure; and (iii) statistical method(s) and outcome(s). Terms used in the original papers to clarify the cutpoints used are provided in parentheses

dBased on the COSMIN checklist

eBased on Table 1 and best available comparison measure: + indicates ≥ 80% acceptable correlations; ± indicates ≥ 50% to < 80% acceptable correlations; – indicates < 50% acceptable correlations

fStudy from previous review

gMean accelerometer value − mean questionnaire value

hLoA extracted from figure in article

iBland–Altman plot indicates larger overestimation by questionnaire with increasing mean VPA time (no statistical analysis applied)

jBland–Altman plot indicates larger overestimation by questionnaire with increasing mean MVPA time (no statistical analysis applied)

kBland–Altman plot indicates underestimation by questionnaire with decreasing mean MVPA time and overestimation with increasing mean MVPA time (no statistical analysis applied)

lBland–Altman plot indicates underestimation by questionnaire with decreasing mean MVPA time and overestimation with increasing mean MVPA time (no statistical analysis applied)

mBland–Altman plot indicates underestimation by questionnaire with decreasing mean MVPA time and overestimation with increasing mean MVPA time (no statistical analysis applied)

nLoA and MD extracted from figure in article

oBland–Altman plot indicates larger underestimation by questionnaire with increasing mean LPA time (no statistical analysis applied)

pChild report mean value − parent report mean value

qBland–Altman plot indicates underestimation by questionnaire with decreasing mean MVPA time and overestimation with increasing mean MVPA time (no statistical analysis applied)

rBland–Altman plot indicates smaller underestimation by questionnaire with increasing mean MVPA time (r = 0.14, p < 0.05)

sBland–Altman plot indicates overestimation by questionnaire with decreasing mean MVPA time and underestimation with increasing mean MVPA time (r = 0.78, p < 0.0001)

tDLW mean value − questionnaire mean value

uFor both MPA and VPA the Bland–Altman plot indicates overestimation by questionnaire with increasing mean MPA and VPA time (no statistical analysis applied)

vBland–Altman plot indicates underestimation by questionnaire with decreasing time spent in PA and overestimation with increasing time spent in PA (no statistical analysis applied)

wFor MPA, MVPA, MVPA (-cycling) and VPA the Bland–Altman plot indicates larger overestimation by questionnaire with increasing mean activity min/week (no statistical analysis applied)

xBland–Altman plot indicates overestimation by questionnaire with decreasing mean MVPA time and underestimation with increasing mean MVPA time (no statistical analysis applied)

Table 3

Reliability of physical activity questionnaires for youth sorted by age category, methodological quality, and evidence rating

Questionnaire	Study populationa	Time interval	Results	Methodological qualityb	Evidence rating
Preschoolers (mean age < 6 years)
Preschool-age Children’s Physical Activity Questionnaire (Pre-PAQ) [58]	n = 103Age: 3.8 ± 0.74 yearsSex: 48% girls	2 weeks	Pre-PAQ level 3: ICC 0.53Pre-PAQ level 4: ICC 0.44Pre-PAQ level 5: ICC 0.64Time spent in fast-paced activities: ICC 0.64Time spent in organized activities: ICC ranged from 0.96 to 0.99	Good	–
Energy Balance Related Behaviors (ERBs) self-administered primary caregivers questionnaire (PCQ), from the ToyBox-study (proxy) [46]	n = 93 preschoolers	2 weeks	Sports: time per week ICC 0.93 (95% CI 0.85–0.97), type of sport 0.71 (95% CI 0.46–0.86)Active/passive transport: travel forth ICC 0.91 (95% CI 0.87–0.94), time 0.82 (95% CI 0.73–0.88), travel home 0.88 (95% CI 0.82–0.92), time 0.89 (95% CI 0.83–0.93)	Fair	+
Children’s Leisure Activities Study Survey (CLASS) (proxy) [100] c	n = 58Age: 5.3 ± 0.5 years [5–6]Sex: 37% girls	At least 14 days	MPA: ICC frequency 0.74, duration 0.49VPA: ICC frequency 0.87, duration 0.81Total PA: ICC frequency 0.83, duration 0.76List of activities: ICC frequency ranging from − 0.03 to 0.94, duration ranging from − 0.04 to 0.91	Fair	–
Physical activity questionnaire for parents of preschoolers in Mexico [40]	n = 21Age: 3–5 yearsSex: percentage girls unknown	1 week	Duration moderate activity: r 0.79Duration vigorous activity: r 0.94Overall activity: r 0.97	Poor	±
Kid Active Q (Web-based)(proxy) [101]	n = 20Age: 4.2 ± 1.3 years [2–6]Sex: 50% girls	3 weeks	Overall PA level: ICC 0.66 (95% CI 0.41–0.91)Time spent outdoors: ICC 0.60 (95% CI 0.31–0.88)	Poor	–
Children (mean age ≥ 6 to < 12 years)
Chinese version of the Physical Activity Questionnaire for Older Children (PAQ-C) [43]	n = 92Age: 8–13 yearsSex: 45% girls	7–10 days	PAQ-C: ICC 0.82	Good	+
Active Transportation to school and work in Norway (ATN) questionnaire [41]	n = 87Age: 11–12 yearsSex: percentage girls unknown	2 weeks	Walking: SROC 0.92Cycling: SROC 0.92Classification in major mode of commuting: kappa 0.93	Good	+
Children’s Leisure Activities Study Survey Chinese-version questionnaire (CLASS-C)[50]	n = 214Age: 10.9 ± 0.9 years [9–12] Sex: 62% girls	Approx. 1 week	Weekly MPA (min): ICC 0.61 (95% CI 0.49–0.70)Weekly VPA (min): ICC 0.73 (95% CI 0.64–0.79)Weekly MVPA (min): ICC 0.71 (95% CI 0.61–0.77)	Good	±
Out-of-school Physical Activity questionnaire [62]	n = 151Age: 11 yearsSex: 60% girls (in total sample n = 155)	Approx. 30 days	MVPA duration: ICC 0.65MVPA frequency: ICC 0.64	Good	–
The Energy-child questionnaire [48]	n = 730Age: [11.3 ± 0.5 to 12.5 ± 0.6 years]Sex: [47–58% girls]	1 week	Walking to school: (no./days) ICC 0.91; (amount of time) ICC 0.70Transport today to school: ICC 0.79Activity during breaks: ICC 0.80Sport hours: (first sport) ICC 0.74, (second sport) ICC 1.00, (yesterday) ICC 0.22Bike to school: (no./days) ICC 0.94, (amount of time) ICC 0.81	Fair	+
Self-Administered Physical Activity Checklist (SAPAC) (Greek version) [49]	n = 72Age: 11.5 ± 0.5 yearsSex: 49% girls	2 weeks	Total-MET: ICC 0.87 (95% CI 0.85–0.88)MET-LPA: ICC 0.85 (95% CI 0.82–0.88)MET-MVPA: ICC 0.88 (95% CI 0.86–0.90)	Fair	+
Physical Activity Questionnaire for Older Children (PAQ-C) [29] c	n = 84Age: 9–14 yearsSex: 49% girls	1 week	ICC boys 0.75, girls 0.82	Fair	+
Girls health Enrichment Multisite Study Activity Questionnaire (GAQ) [102] c	n = 68Age: 9.0 ± 0.6 yearsSex: 100% girls	4 days	28 activities: yesterday ICC 0.78, usual 0.8218 activities: yesterday ICC 0.70, usual 0.79	Fair	+
Food, Health, and Choices questionnaire (FHC-Q) [37]	n = 82 (digital vs. paper)Age: < 9 to > 12 yearsSex: 51% girlsn = 73 (digital vs. digital)Age: < 9 to > 12 yearsSex: 45% girls	2 weeks	PA digital vs. paper: ICC 0.73PA digital vs. digital: ICC 0.66	Fair (both groups)	±
The South American Youth/Child Cardiovascular and Environment Study (SAYCARE) Physical Activity (PA) questionnaire (proxy) [66]	n = 161Age: 3–10 yearsSex: 50% girls	15 days	Active commuting: SCC 0.28PA at school: SCC 0.31PA at leisure time: SCC 0.33MPA: SCC 0.37VPA: SCC 0.89Weekly total MVPA: SCC 0.56 % of agreement with current PA guidelines ≥ 60 min/day: κ 0.32	Fair	–
Dutch Physical Activity Checklist for Children (PAQ-C) [35]	n = 192Age: 8.9 ± 1.7 years [5–12]Sex: 53% girls	NA: inter-rater (parent vs. child)	Spare-time activity—sports: kappa 0.50 (95% CI 0.41–0.60)Activity during PE classes: 0.48 (95% CI 0.37–0.59)Break-time activity: 0.64 (95% CI 0.55–0.73)Lunchtime activity: 0.68 (95% CI 0.60–0.77)After-school activity: 0.63 (95% CI 0.54–0.71)Evening activity: 0.69 (95% CI 0.62–0.77)Weekend activity: 0.56 (95% CI 0.46–0.67)Activity frequency last 7 days: 0.65 (95% CI 0.56–0.74)Activity frequency during each day: 0.64 (95% CI 0.55–0.72)Total PA: 0.60 (95% CI 0.52–0.67)	Fair	–
Instrument to assess children’s outdoor active play in various locations (proxy) [77]	n = 53Age: 9.5 ± 0.7 years [8.3–12.3]Sex: 42% girls	2 weeks	Weekday ICC: yard at home 0.80, friend’s/neighbor’s yard 0.70, own street/court/footpath 0.82, nearby streets/court/footpath 0.40, park/playground 0.63, facilities or sport ovals 0.48, school grounds for free play outside school hours 0.51, other places 0.47Weekend day ICC: yard at home 0.58, friend’s/neighbor’s yard 0.77, own street/court/footpath 0.76, nearby streets/court/footpath 0.33, park/playground 0.64, facilities or sport ovals 0.63, school grounds for free play outside school hours 0.18, other places 0.62	Fair	–
Parent proxy-report of physical activity and sedentary activities (proxy) [73]	n = 147Age: 6–10 years, 13–14 yearsSex: 51% girls (in total sample n = 189)	2 months6 months	After 2 months:Playing vigorously indoors: ICC 0.41, MD − 8.7 (min/day) (− 17.6 to 0.1)Playing vigorously outdoors: ICC 0.43, MD − 10.0 (− 19.2 to − 0.8)Cycling: ICC 0.64 MD − 1.4 (− 7.2 to 4.5)After 6 months:Playing vigorously indoors: ICC 0.67, MD − 8.3 (− 14.2 to − 2.4)Playing vigorously outdoors: ICC 0.60, MD − 3.1 (− 11.3 to 5.1)Cycling: ICC 0.45, MD 2.6 (− 4.4 to 9.7)	2 months’ time interval: fair6 months’ time interval: poor	–
Physical Activity Questionnaire for older Children (PAQ-C) (Spanish version) [52]	n = 83Age: 11.0 ± 1.2 yearsSex: 45% girls	6 h	Total score: ICC 0.96Activity checklist: ICC 0.96PE: ICC 0.95Recess: ICC 0.79Lunch: ICC 0.87After school: ICC 0.82Afternoon: ICC 0.77Weekend: ICC 0.63Intensity last week: ICC 0.90Week summary: ICC 0.95	Poor	+
Godin Leisure-Time Exercise Questionnaire [63]	n = 31Age: 10.6 ± 0.2 yearsSex: 45% girls	Same day (beginning and end of the school day)	Mild exercise: PCC 0.25Moderate exercise: PCC 0.38Strenuous exercise: PCC 0.69Total leisure activity score: PCC 0.62, MD − 33.4, LoA [− 239; 172.2]	Poor	–
The Modified Godin Leisure-Time Exercise Questionnaire [45]	n = 139Age: 11.1 ± 0.4 yearsSex: 52% girls	Fall (autumn) and spring (6 months)	Total min of exercise: PCC 0.68	Poor	–
Older children and adolescents (mean age ≥ 12 years)
Single-item activity measure [23]	n = 107Age: 14.7 ± 0.5 yearsSex: 38% girls(Age and sex total sample n = 123)	2 weeks	ICC 0.75 (95% CI 0.64–0.83), MD 0.08 (95% CI − 0.12 to 0.26)	Good	+
Web-based and paper-based Physical Activity Questionnaire for Older Children (PAQ-C) [28]	n = 323Age 12.8 yearsSex: 51% girls(Age and sex total sample n = 459)	Approx. 8 days	Web-based vs. web-based: ICC 0.79 (95% CI 0.74–0.82), PCC 0.79, MD 0.11 (95% CI 0.06–0.15)Web-based vs. paper-based: ICC 0.70 (95% CI 0.65–0.75), PCC 0.70, MD − 0.02 (95% CI − 0.06 to 0.03)	Good	+
An adapted version of the Assessment of Physical Activity Levels Questionnaire (APALQ) [53]	n = 150Age: 13.6 ± 1.1 yearsSex: 52% girls	7 days	PA index: ICC 0.76Organized sport participation outside school: ICC 0.86Non-organized sport participation outside school: ICC 0.58PE: ICC 0.61Hours per week out of school PA intensity: ICC 0.82Participation in competitive sport: ICC 0.93	Good	±
International Physical Activity Questionnaire - Short Form (IPAQ-SF) [84]	n = 92Age: 15.9 ± 1.4 years [12–18]Sex: 53% girls	1 week	VPA: ICC 0.79 (95% CI 0.70–0.86)MPA: ICC 0.53 (95% CI 0.36–0.66)Walking: ICC 0.66 (95% CI 0.53–0.76)Total PA: ICC 0.74 (95% CI 0.63–0.82)	Good	±
Child and Adolescent Physical Activity and Nutrition survey (CAPANS-PA) recall questionnaire [103]	n = 77Age: 12 ± 0.8 years [11–14]Sex: 51% girls	1 week	Frequency MVPA: ICC Monday–Friday 0.77 (95% CI 0.67–0.85), Saturday 0.73 (95% CI 0.57–0.84), Sunday 0.19 (95% CI − 0.16 to 0.50), Monday–Sunday 0.86 (95% CI 0.79–0.91)Duration MVPA: ICC Monday–Friday 0.74 (95% CI 0.62–0.83), Saturday 0.70 (95% CI 0.51–0.82), Sunday 0.36 (95% CI 0.01–0.63), Monday–Sunday 0.78 (95% CI 0.66–0.85)Frequency active in PE: kappa 0.51 (95% CI 0.34–0.67)Frequency PA right after school: 0.48 (95% CI 0.37–0.66)Frequency PA evenings: 0.50 (95% CI 0.37–0.66)Frequency PA last weekend: 0.49 (95% CI 0.34–0.64)Participation in 32 PAs: kappa ranging from − 0.04 to 0.82	Good	–
Activity Questionnaire for Adults and Adolescents (AQuAA) [21]	n = 53Age: 14.1 ± 1.4 yearsSex: 43% girls	2 weeks	AQuAA score (MET × min/week): ICC 0.44 (95% CI 0.16–0.65)Light activities (min/week): ICC 0.30 (95% CI 0.04–0.52)Moderate activities (min/week): ICC 0.50 (95% CI 0.27–0.68)Moderate to vigorous activities: ICC 0.54 (95% CI 0.32–0.70)Vigorous activities (min/week): ICC 0.59 (95% CI 0.38–0.75)	Good	–
Godin-Shephard Survey [98]	n = 102Age: 11.2 ± 0.7 years (n = 36), 13.6 ± 0.5 years (n = 36), 16.4 ± 0.8 years (n = 30)Sex: 51% girls	2 weeks	Godin-Shephard Survey: r 0.81	Fair	+
VISA-TEEN questionnaire [104]	n = 228Age: 15.4 ± 1.6 yearsSex: 46% girls(Age and sex total sample n = 396)	15 days	MVPA: (days/week) ICC 0.77 (95% CI 0.71–0.82), (h/week) 0.86 (95% CI 0.81–0.89)VPA: (h/week) ICC 0.80 (95% CI 0.75–0.85)	Fair	+
Children’s Leisure Activities Study Survey (CLASS) questionnaire (modified version) [99]	n = 108Age: 12 yearsSex: 58.3% girls	3 weeks	MPA: ICC 0.95VPA: ICC 0.83Total PA: ICC 0.93	Fair	+
Oxford Physical Activity Questionnaire (OPAQ) [23]	n = 104Age: 14.7 ± 0.5 yearsSex: 38% girls(Age and sex total sample n = 123)	2 weeks	ICC 0.79 (95% CI 0.69–0.86), MD − 0.17 (95% CI − 0.43 to 0.10)	Fair	+
Quantification de l’activité physique en altitude chez les enfants (QAPACE) [105] c	n = 121Age: 8–16 yearsSex: 54% girls	90 days	Toilet: ICC 0.90 (95% CI 0.87–0.93)Transportation: ICC 0.84 (95% CI 0.78–0.89)Mandatory PE: ICC 0.95 (95% CI 0.93–0.97)Other activities in school: ICC 0.94 (95% CI 0.92–0.96)Personal artistic activities: ICC 0.98 (95% CI 0.97–0.99)Sport competition: ICC 0.98 (95% CI 0.97–0.99)Home activities: ICC 0.89 (95% CI 0.85–0.92)Daily EE: LoA [–515.5; 532.5 kJ/d]	Fair	+
Oxford Physical Activity Questionnaire (OPAQ) [24] c	n = 87Age: 13.1 ± 0.9 yearsSex: 45% girls	1 week	MPA: ICC 0.76 (95% CI 0.63–0.84)VPA: ICC 0.80 (95% CI 0.70–0.87)MVPA: ICC 0.91 (95% CI 0.87–0.95)	Fair	+
World Health Organization Health Behavior in Schoolchildren questionnaire (WHO HBSC) [106] c	n = 71Age: 14.9 ± 1.6 years [13–18]Sex: 56% girls	8–12 days	Frequency: ICC 0.73 (95% CI 0.60–0.82)Duration: ICC 0.71 (95% CI 0.57–0.81)	Fair	+
Selected indicators from the Health Behaviour in School-aged Children (HBSC) questionnaire (Chinese version) [107]	n = 95 (11 years [n = 44], 15 years [n = 51])Age: [11.7 ± 0.4 to 15.8 ± 0.3 years]Sex: 46% girls	3 weeks	MVPA: last 7 days ICC 0.82 (95% CI 0.74–0.88), usual week 0.74 (95% CI 0.64–0.82)VPA: frequency 0.68 (95% CI 0.55–0.77), times per week 0.57 (95% CI 0.42–0.66)	Fair	±
Selected physical activity items of the international Health Behavior in School-aged Children (HBSC) questionnaire (Czech version) [108]	n = 693Age: 11.1 ± 0.5 and 15.1 ± 0.5 yearsSex: 49.1% girls	4 weeks (n = 580)1 week (n = 113)	4-week time interval:MVPA: ICC 0.52 (95% CI 0.46–0.58), kappa 0.44VPA: ICC 0.55 (95% CI 0.49–0.61), kappa 0.411-week time interval:MVPA: ICC 0.98 (95% CI 0.97–0.99)VPA: ICC 0.90 (95% CI 0.86–0.93)	Fair	±
Measures of in-school and out-of-school physical activity, and travel behaviors of the international Healthy Environments and active living in teenagers – Hong Kong [iHealt(H)] study [47]	n = 68Age: 15.4 yearsSex: 47% girls	13 days (range: 8–16 days)	PE min/class: ICC 0.89, min/week 0.84No. of sport teams or after school PA in school: ICC 0.74No. of sport teams or after school PA out-of-school: ICC 0.89Leisure time PA: past 7 days ICC 0.70, usual week ICC 0.79, average ICC 0.76Walking or cycling to/from destinations: Indoor or exercise facility 0.61, friend’s or relative’s house 0.48, outdoor recreation place 0.47, food store or restaurant/cafe 0.82, other retail stores 0.51, non-school social or educational activities 0.51, public transportation stop 0.71, total score walking or cycling times/week 0.59Walk to school: ICC 0.89Walk from school: ICC 0.76	Fair	±
Physical Activity and Lifestyle Questionnaire (PALQ) (Greek version) [33]	n = 21Age: 13.7 ± 0.8 yearsSex: 43% girls (age and sex total sample n = 40)	2 weeks	PALQ: ICC 0.52, typical error 2.39, MD (LoA) − 1.88 ± 6.82	Fair	–
The South American Youth/Child Cardiovascular and Environment Study (SAYCARE) Physical Activity (PA) questionnaire [66]	n = 177Age: 11–18 yearsSex: 58% girls	15 days	Active commuting: SCC 0.51PA at school: SCC 0.63PA at leisure time: SCC 0.68MPA: SCC 0.36VPA: SCC 0.93Weekly total MVPA: SCC 0.60 % of agreement with current PA guidelines ≥ 60 min/day: κ 0.56	Fair	–
Self-administered questionnaire on children’s travel to school [39]	n = 61 (study 1), n = 68 (study 2)Age: 11–14 yearsSex: percentage of girls unknown	1 week	After school exercise no. of days: study 1, kappa 0.07; study 2, kappa 0.01After school exercise no. of hours: study 1, kappa NA; study 2, kappa 0.01Physical training: study 1, kappa 0.07; study 2, kappa − 0.01	Fair	–
Dutch Physical Activity Checklist for Adolescents (PAQ-A)[35]	n = 94Age: 13.6 ± 1.4 years [12–17]Sex: 55% girls	NA: inter-rater (parent vs. child)	Spare-time activity—sports: kappa 0.67 (95% CI 0.54–0.81)Activity during PE classes: 0.53 (95% CI 0.33–0.72)Lunchtime activity: 0.60 (95% CI 0.46–0.73)After-school activity: 0.61 (95% CI 0.47–0.76)Evening activity: 0.68 (95% CI 0.53–0.79)Weekend activity: 0.51 (95% CI 0.38–0.65)Activity frequency last 7 days: 0.63 (95% CI 0.51–0.76)Activity frequency during each day: 0.51 (95% CI 0.38–0.64)Total PA: 0.64 (95% CI 0.51–0.77)	Fair	–
3-Day Physical Activity Recall (3DPARecall) instrument (Singaporean version) [42]	n = 106Age: 14.5 ± 1.1 years [13–16]Sex: 53% girls(Age and sex total sample n = 221)	6–8 h	3-day average MET level: ICC 0.88 (95% CI 0.83–0.92)	Poor	+
3-Day Physical Activity Record (3DPARecord) (Greek version) [33]	n = 21Age: 13.7 ± 0.8 yearsSex: 43% girls(Age and sex total sample n = 40)	2 weeks	All days: ICC 0.97, typical error 382.51, LoA [–375.3; 1092.7] Weekend: ICC 0.88, typical error 276.4, LoA [–230.6; 789.5]Weekdays: ICC 0.97, day 1 typical error 119.8, LoA [–66.12; 342.19], day 2 typical error 131.5, MD (LoA) − 78.6 ± 375.6	Poor	+
Recess Physical Activity Recall (RPAR) [95]	n = 113Age: 13.1 ± 0.7 yearsSex: 48% girls	1 h	Total PA: ICC 0.87MVPA: ICC 0.88	Poor	+
Refined 60-min MVPA screening measure [109] c	n = 138Age: 12.1 ± 0.9 yearsSex: 65% girls	Same day up to 1 month	ICC: total sample 0.77, same day 0.88 (n = 42), up to 1 month 0.53 (n = 31)Kappa: total sample 61%, same day 84%, up to 1 month 36%	Poor	+
MVPA scores of the Health Behavior in School-aged Children (HBSC) Research Protocol [90]	n = 998Age: 12.7 ± 1.4 yearsSex: 50% girls	1 year	MVPA girls r 0.43, boys r 0.50	Poor	–
MVPA scores of the International Physical Activity Questionnaire Short form (IPAQ-SF) [90]	n = 998Age: 12.7 ± 1.4 yearsSex: 50% girls	1 year	MVPA girls r 0.45, boys r 0.44	Poor	–
Moderate and vigorous physical activity items of the Youth Risk Behavior Survey (YRBS)[83]	n = 128Age: 12.2 ± 0.6 years (in total sample n = 139)Sex: 53% girls	Ranged from 1 to 40 days (n = 92 [≤ 15 days] and n = 36 [> 15 days])	MPA: ICC ≤ 15 days 0.57, > 15 days 0.35, total sample 0.51VPA: ICC ≤ 15 days 0.47, > 15 days 0.34, total sample 0.46	Poor	–

approx. approximately, CI confidence interval, COSMIN COnsensus-based Standards for the selection of health Measurement Instruments, ICC intraclass correlation coefficient, LoA limits of agreement, LPA light physical activity, MD mean difference, MET metabolic equivalent, MPA moderate physical activity, MVPA moderate to vigorous physical activity, NA not applicable, PA physical activity, PCC Pearson correlation coefficient, PE physical education, SD standard deviation, SROC Spearman rank order correlation, VPA vigorous physical activity; + indicates ≥ 80% acceptable correlations, ± indicates ≥ 50% to < 80% acceptable correlations, – indicates < 50% acceptable correlations

aAge presented as mean age ± SD [range]

bBased on the COSMIN checklist

cStudy from previous review

Table 4

Measurement error of physical activity questionnaires for youth sorted by age category and methodological quality

Questionnaire	Study populationa	Time interval	Results	Methodological qualityb
Preschoolers (mean age < 6 years)
Preschool-age Children’s Physical Activity Questionnaire (Pre-PAQ) [58]	n = 103Age: 3.8 ± 0.74 yearsSex: 48% girls	2 weeks	Time spent in organized activities: ME ranged from 1.0 to 1.1 min	Good
Children (mean age ≥ 6 to < 12 years)
The ENERGY-child questionnaire [48]	n = 730Age: [11.3 ± 0.5 to 12.5 ± 0.6 years]Sex: [47–58% girls]	1 week	Walking to school: (no./days) PoA 81%, (amount of time) 76%Transport today to school: PoA 83%Activity during breaks: PoA 86%Sport hours: (first sport) PoA 55%; (second sport) 43%; (yesterday) 28%Bike to school (no./days): PoA 88%, (amount of time) 85%	Fair
Dutch Physical Activity Checklist for Children (PAQ-C) [35]	n = 192Age: 8.9 ± 1.7 years [5–12]Sex: 53% girls	NA: inter-rater (parent vs. child)	Spare-time activity—sports: PoA 59.9%Activity during PE classes: 71.4%Break-time activity: 74.0%Lunchtime activity: 71.9%After-school activity: 67.7%Evening activity: 71.9%Weekend activity: 69.8%Activity frequency last 7 days: 72.4%Activity frequency during each day: 65.6%Total PA: 65.6%	Fair
Children’s Leisure Activities Study Survey (CLASS) [100] c	n = 109Age: 10.6 ± 0.8 years [10–12] (in total sample n = 111)Sex: 63% girls	NA: inter-rater (parent vs. child)	Total VPA: PoA 58.6%Total MPA: PoA 84.7%Total PA: PoA 89.2%Individual activities: PoA ranges from 8.0% to 97.8%	Fair
Older children and adolescents (mean age ≥ 12 years)
Active Transportation to school and work in Norway (ATN) questionnaire (days/week type of transportation) [41]	n = 87Age: 11–12 yearsSex: percentage girls unknown	2 weeks	Classification in major mode of commuting: PoA 97%	Good
3-Day Physical Activity Recall (3DPARecall) [19] c	n = 65Age: 12.5 ± 1.1 yearsSex: 64% girls(Age and sex in total sample n = 320)	1 day	List of activities: PoA boys ranges from 0% to 75%, mean (SD) 51% (29); girls from 18% to 75%, mean (SD) 47% (18)	Good
Self-Administered Physical Activity Checklist (SAPAC) (modified) [19] c	n = 84Age: 12.5 ± 1.1 yearsSex: 64% girls(Age and sex in total sample n = 320)	1 day	List of activities: PoA boys ranges from 7% to 70%, mean (SD) 34% (20); girls from 26% to 75%, mean (SD) 42% (15)	Good
Measures of in-school and out-of-school physical activity, and travel behaviors of the international Healthy Environments and active living in teenagers – Hong Kong [iHealt(H)] study [47]	n = 68Age: 15.4 yearsSex: 47% girls	13 days (range: 8–16 days)	PE days/week: PoA 98%No. of sport teams or after school PA in school: PoA 79%No. of sport teams or after school PA out-of-school: PoA 90%Leisure-time PA: past 7 days PoA 76%, usual week PoA 65%Walking or cycling to/from destinations: indoor or exercise facility 76%, friend’s or relative’s house 57%, outdoor recreation place 62%, food store or restaurant/cafe 80%, other retail stores 62%, non-school social or educational activities 68%, public transportation stop 69%, work 100%, other 100%Transportation to school: walk PoA 90%, bicycle 100%Transportation from school: walk PoA 79%, bicycle 100%	Fair
Dutch Physical Activity Checklist for Adolescents (PAQ-A) [35]	n = 94Age: 13.6 ± 1.4 years [12–17]Sex: 55% girls	NA: inter-rater (parent vs. child)	Spare-time activity—sports: PoA 77.7%Activity during PE classes: 73.4%Lunchtime activity: 64.9%After-school activity: 69.2%Evening activity: 71.0%Weekend activity: 57.5%Activity frequency last 7 days: 70.2%Activity frequency during each day: 51.0%Total PA: 70.2%	Fair

COSMIN COnsensus-based Standards for the selection of health Measurement Instruments, ME measurement error, MPA moderate physical activity, NA not applicable, PA physical activity, PE physical education, PoA percentage of agreement, SD standard deviation, VPA vigorous physical activity

aAge presented as mean age ± SD [range]

bBased on the COSMIN checklist

cStudy from previous review

Best Evidence

We chose to divide the included studies in three age categories, i.e., preschoolers, children, and adolescents, and draw conclusions on the best available questionnaire(s) for each age category. A questionnaire was considered of interest when at least a fair methodological quality and a positive evidence rating were achieved. Additionally, for construct validity, the level of evidence (see Table 1) was taken into account, so questionnaires with a higher level of evidence comparison measure were considered more valuable. Because no evidence ratings were available for measurement error, these measurement properties were not taken into account when drawing conclusions about the best available questionnaire.

Results

Systematic literature searches using the PubMed, EMBASE, and SPORTDiscus databases yielded 15,220 articles after removal of duplicates. After title and abstract screening, 110 eligible articles remained. Another 21 articles were found through cross-reference searches. Therefore, 131 full-text articles were screened, which resulted in the inclusion of 71 articles examining 76 (versions of) questionnaires. After additionally including 16 articles from the previous review, this resulted in 87 articles examining 89 (versions) of questionnaires. See Fig. 1 for the full selection process. Within the 87 articles, 162 studies were conducted, with 103 assessing construct validity, 50 test–retest reliability, and nine measurement error. Four of the included questionnaires were assessed by two of the included studies, i.e., the 3-Day Physical Activity Recall (3DPARecall) [19, 20], the Activity Questionnaire for Adults and Adolescents (AQuAA) [21, 22], the Oxford Physical Activity Questionnaire (OPAQ) [23, 24], and a physical activity, sedentary behavior, and strength questionnaire [25, 26]. Furthermore, two of the questionnaires were assessed by three of the included studies, i.e., the Physical Activity Questionnaire for Older Children (PAQ-C) [27-29], and the Previous Day Physical Activity Recall (PDPAR) [30-32]. In addition, various modified versions of questionnaires were assessed by the included studies.

Fig. 1

Preferred Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram of study inclusion

Construct Validity

The construct validity results are summarized in Table 2. Of the 72 questionnaires that were assessed on construct validity, eight were from the previous review. Fifteen of the questionnaires were assessed by two studies, two were assessed by three studies, one by four, one by five, and one by six studies. Six questionnaires were assessed in preschoolers, 29 in children, and 38 in adolescents (one questionnaire was assessed in both children and adolescents). The methodological quality rating of the construct validity studies ranged from poor to good: 49 studies received a poor, 49 a fair, and five a good rating. The low methodological scores were predominantly due to comparison measures with unacceptable or unknown measurement properties, and a lack of a priori formulated hypotheses. No definite conclusion could be drawn regarding the best available questionnaires for preschoolers, as studies on construct validity within this age category were of low methodological quality or received negative evidence ratings. For children, the best available questionnaire was found to be the Godin Leisure-Time Exercise Questionnaire [63] (fair methodological quality and positive level 2 evidence). Although the moderate level 2 evidence hampered our ability to draw conclusions on the validity, it is worthwhile to investigate further. We concluded that the most valid questionnaire in adolescents was the Greek version of the 3-Day Physical Activity Record (3DPARecord) [33] (fair methodological quality and positive level 1 evidence rating). Note that the 3DPARecord uses a different format (i.e., different time segments and categories) than the frequently used 3DPARecall.

Content Validity

Six of the included questionnaires were qualitatively assessed on content validity, one of which was assessed by two studies [25, 26, 34–37]. Studies used cognitive interviews, semi-structured interviews, and focus groups with children and adolescents and/or experts (e.g., researchers in the field of sports medicine, pediatrics, and measurement) to assess the comprehensibility, relevance of items, and comprehensiveness of the questionnaires. Due to a lack of details on the methods used regarding testing or developing these questionnaires, the methodological quality of these studies and the quality of the questionnaires could not be assessed. Ten of the included questionnaires were pilot-tested with children and/or parents on, for example, comprehensiveness and time to complete [33, 38–45]. However, again, the study quality could not be assessed due to the minimal amount of information provided. Lastly, 15 of the questionnaires were translated versions [33, 35, 39, 40, 43, 46–53]; the majority of these studies provided little information on the translation processes. These studies did not assess the cross-cultural validity, and thus no definite conclusion about the content validity of the translated questionnaires could be drawn.

Test–Retest Reliability

The test–retest reliability results are summarized in Table 3. Of the 46 questionnaires assessed on test–retest reliability, five were from the previous review. Four of the questionnaires were assessed by two studies. Five questionnaires were assessed in preschoolers, 16 in children, and 26 in adolescents (one questionnaire was assessed in both children and adolescents). The methodological quality of the studies was rated as follows: 13 scored poor, 26 fair, and 11 good. The majority of poor and fair scores were due to the lack of a description about how missing items were treated and inappropriate time intervals between test and retest. The most reliable questionnaire in preschoolers was the Energy Balance Related Behaviors (ERBs) self-administered primary caregivers questionnaire (PCQ) [46] (fair methodological quality and positive evidence rating). In children, the most reliable questionnaires were the Chinese version of the PAQ-C [43], and the Active Transportation to school and work in Norway (ATN) questionnaire [41] (both good methodological quality and positive evidence rating). The most reliable questionnaires in adolescents were a single-item activity measure [23], and the Web-based and paper-based PAQ-C [28] (both good methodological quality and positive evidence rating).

Measurement Error

Table 4 summarizes the measurement error outcomes. Of the nine questionnaires assessed on measurement error, two were from the previous review. One questionnaire was assessed in preschoolers, three in children, and five in adolescents. Four of the studies received a good methodological quality rating, and five received a fair one. Fair scores were predominantly due to the lack of a description about how missing items were treated.

Discussion

This review summarizes studies that assessed the measurement properties of physical activity questionnaires for children and adolescents under the age of 18 years. Questionnaires varied in (sub)constructs measured, recall periods, number of questions and format, and different measurement properties that were assessed, e.g., construct validity, test–retest reliability, or measurement error. Unfortunately, most studies had low methodological quality scores and low evidence ratings, especially for construct validity. Additionally, no questionnaire was identified with both high methodological quality and positive evidence ratings for reliability and validity. Furthermore, for the majority of questionnaires there was a lack of data on both reliability and validity. Consequently, no definite conclusion regarding the most promising questionnaire can be drawn.

For adolescents, one valid questionnaire was found, i.e., the Greek version of the 3DPARecord [33]. The 3DPARecord is a questionnaire using a segmented day structure that divides the previous 3 days (1 weekend day) into timeframes of 15 min each, with the adolescents reporting their activity using nine categories ranging from 1 (sleep) to 9 (vigorous physical activity and sport) for each of the timeframes [33].

Due to the predominantly low methodological study quality and negative evidence ratings for study results in children and preschoolers, no valid questionnaires were identified. The low methodological quality of the studies was predominantly due to a lack of a priori formulated hypotheses and the use of comparison measures with unknown or unacceptable measurement properties. Moreover, in some studies comparisons between non-corresponding constructs were made, e.g., moderate to vigorous physical activity (MVPA) measured by a questionnaire compared with total accelerometer counts.

Test–Retest Reliability and Measurement Error

For preschoolers, one reliable questionnaire was identified: the ERBs self-administered PCQ [46]; two reliable questionnaires were identified for children: the Chinese version of the PAQ-C [43] and the ATN questionnaire [41]; and two for adolescents: a single-item activity measure [23] and the web- and paper-based PAQ-C [28].

Many questionnaires received a positive evidence rating but due to the low methodological quality of the studies no definite conclusions regarding their reliability could be drawn. The low methodological quality was mainly due to inappropriate time intervals between test and retest, and the lack of a description about how missing items were handled. Unfortunately, no final evidence rating for measurement error could be computed as none of the studies provided information on the MIC.

Strengths and Limitations

A strength of this review is the separate assessment of the questionnaire quality (i.e., results for measurement properties) and the methodological quality of the study in which the questionnaire was assessed. This provides transparency in the conclusion regarding the best available questionnaires. Furthermore, data extraction and assessment of methodological quality were carried out by at least two independent researchers, minimizing the chance of bias. In addition, cross-reference searches were carried out, thereby increasing the likelihood of finding all relevant studies. However, we only included English-language studies, disregarding relevant studies published in other languages.

Recommendations for Future Research

Due to the methodological limitations of existing studies, we cannot draw definite conclusions on the measurement properties of physical activity questionnaires. This hampers the identification of the most suitable questionnaires for assessing physical activity in children. To improve future research we recommend the following:

Using standardized tools for the evaluation of measurement properties such as COSMIN, to improve the quality of studies examining measurement properties [11, 54];

Using appropriate translation methods [17];

Using the mode of administration in a validation study that is intended in the field;

Defining the context of use and the measurement model of the questionnaire to determine which measurement properties are relevant to examine;

Conducting more studies assessing content validity to ensure questionnaires are comprehensive and an adequate reflection of the construct to be measured [13, 55];

For construct validity, choosing a comparison measure that measures a similar construct and formulating hypotheses a priori;

For reliability studies, test and retest should concern the same day/week when recalling a previous day/week;

More research on the responsiveness of valid and reliable questionnaires;

Building on or improving the most promising existing questionnaires rather than developing new questionnaires;

Providing open access to the examined questionnaire; and

Editors of journals to request reviewers and authors to use a standardized tool such as COSMIN for studies on measurement properties.

Conclusions

Unfortunately, conclusive evidence for both validity and reliability was not found for any of the identified physical activity questionnaires. The lack of high-quality studies examining both the reliability and the validity of a questionnaire hampered the ability to draw definite conclusions about the best available physical activity questionnaire for children and adolescents. Thus, high-quality methodological studies examining all relevant measurement properties are highly warranted. We strongly recommend researchers adopt standardized tools, e.g., the COSMIN methodology [11, 56, 57], for the design and report of future studies. Current studies using physical activity questionnaires should keep in mind that their results may not adequately reflect children’s and adolescents’ physical activity levels, as most questionnaires lack appropriate validity and/or reliability.

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 51 kb)

Supplementary material 2 (PDF 178 kb)

No conclusive evidence was found for both the validity and reliability for any of the included physical activity questionnaires for youth.

High-quality studies on the measurement properties of the most promising physical activity questionnaires are urgently needed, e.g., by using the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist.

More attention on the content validity of physical activity questionnaires is needed to confirm that questionnaires measure what they intend to measure.