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.
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.
1 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.
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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.
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2 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).
2.1 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.
2.2 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.
2.3 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.
2.4 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.
2.5 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.
2.6 Questionnaire Quality Assessment
2.6.1 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.
2.6.2 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 ≥ 0.70
Accelerometer total or activity counts ≥ 0.60a
PAEE measured by doubly labeled water ≥ 0.60
Accelerometer vigorous counts, moderate counts, or moderate and vigorous counts ≥ 0.40
Pedometer counts ≥ 0.40
Questionnaire, diary, or interview; corresponding constructs ≥ 0.70
VO2max ≥ 0.40
Physical activity, not all constructs or timeframes (e.g., excluding time spent at school or chores)
Direct observation ≥ 0.70
Accelerometer total or activity counts; corresponding timeframe ≥ 0.60
Accelerometer total or activity counts; total daytime ≥ 0.40
Accelerometer moderate and vigorous counts ≥ 0.50
Questionnaire, diary, or interview; corresponding constructs ≥ 0.70
VO2max ≥ 0.40
Physical activity, single constructs (e.g., only unstructured free play, cycling, time spent outdoors)
Accelerometer total or activity counts ≥ 0.40
Accelerometer moderate and vigorous counts ≥ 0.50
Pedometer counts ≥ 0.40
Questionnaire, diary, or interview; corresponding constructs ≥ 0.70
VO2max ≥ 0.40
Cycle computer ≥ 0.70b
Physical activity energy expenditure
PAEE measured by doubly labeled water ≥ 0.70
Accelerometer total or activity counts ≥ 0.50
Pedometer counts ≥ 0.40
Questionnaire, diary, or interview; corresponding constructs ≥ 0.70
VO2max ≥ 0.40
Vigorous activity
Accelerometer vigorous counts ≥ 0.60
Accelerometer total or activity counts ≥ 0.40
Pedometer counts ≥ 0.40
Questionnaire, diary, or interview; corresponding constructs ≥ 0.70
VO2max ≥ 0.60
Moderate and vigorous activity
Accelerometer moderate and vigorous counts ≥ 0.60
Accelerometer total or activity counts ≥ 0.40
Pedometer counts ≥ 0.40
Questionnaire, diary, or interview; corresponding constructs ≥ 0.70
VO2max ≥ 0.60
Moderate activity
Accelerometer moderate counts ≥ 0.60
Accelerometer total or activity counts ≥ 0.40
Pedometer counts ≥ 0.40
Questionnaire, diary, or interview; corresponding constructs ≥ 0.70
VO2max ≥ 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, VO2max 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).
2.7 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
MVPA duration vs. MVPA min/day: SCC 0.25, MDg − 6.3 min
MVPA frequency vs. MVPA min/day: SCC 0.25
Fair
Level 1: –
Children’s Leisure Activities Study Survey Chinese-version questionnaire (CLASS-C) [50]
n = 139
Age: [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 biasi
MVPA 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 rating
Godin 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 0.28
3 of 6 hypotheses correct
Fair (all comparison measures)
Level 1: –
Previous Day Physical Activity Recall (PDPAR) [30]
n = 37
Age: 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 0.43
PA ≥ 3 METs: vs. total counts SROC 0.23; vs. MVPA min SROC 0.19
PA ≥ 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]
MVPA min/day vs. acc. MVPA min/day: PCC 0.35, MD − 3.40 min/day, LoA [–49.6; 42.8]g,s
Walking/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 = 33
Age: 13.7 ± 0.8 years
Sex: 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 = 125
Age: 12.2 ± 0.6 years
Sex: 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 0.03
Meeting 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
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 0.30
Agreement 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 = 155
Age: 12.3 ± 0.9 years
Sex: 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 0.12
MET: 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 0.27
MVPA: 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 0.25
VPA: 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
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)
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)
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]
3-day average VPA blocks vs. step counts: SCC 0.34
3-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 years
Sex: 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 = 75
Age: 16.1 ± 1.1 years
Sex: 48% girls
Pedometer (Digi-walker SW 701)
All activities vs. step counts/day: PCC 0.37
MPA vs. step counts/day: PCC 0.27
VPA vs. step counts/day: PCC 0.34
Specific 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]
ACTIVITYGRAM
n = 147
Age:12.4 ± 0.4 years
Sex: 44% girls
Biotrainer (first sample)
n = 28 [25–28]
Age: 12.4 ± 0.5 years
Sex: 50% girls
Biotrainer (second sample)
n = 128
Age: unknown
Sex: 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)
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. Biotrainer
Fair 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% girls
n = 998 (vs. questionnaire)
Age: 12.7 ± 1.4 years
Sex: 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 0.62
MVPA 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% girls
n = 998 (vs. questionnaire)
Age: 12.7 ± 1.4 years
Sex: 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 0.62
MVPA 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]
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 0.42
MPA vs. MPA min: PCC 0.47
VPA vs. VPA min: PCC 0.31
MVPA vs. MVPA min: PCC 0.52, MDg 2.15 ± 3.67 min, LoA [–5.04; 9.34], syst. bias r = − 0.51
Bland–Altman plot depicts a positive magnitude biasv
Total 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 0.16
Age: 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 rating
Seven-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 = 108
Age: 12 years
Sex: 58.3% girls
Eurofit test battery: aerobic fitness
Total PA: SROC 0.43
MPA: SROC 0.13
VPA: 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, VO2max 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
Time 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 = 58
Age: 5.3 ± 0.5 years [5–6]
Sex: 37% girls
At least 14 days
MPA: ICC frequency 0.74, duration 0.49
VPA: ICC frequency 0.87, duration 0.81
Total PA: ICC frequency 0.83, duration 0.76
List 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]
Physical Activity Questionnaire for Older Children (PAQ-C) [29] c
n = 84
Age: 9–14 years
Sex: 49% girls
1 week
ICC boys 0.75, girls 0.82
Fair
+
Girls health Enrichment Multisite Study Activity Questionnaire (GAQ) [102] c
n = 68
Age: 9.0 ± 0.6 years
Sex: 100% girls
4 days
28 activities: yesterday ICC 0.78, usual 0.82
18 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 years
Sex: 51% girls
n = 73 (digital vs. digital)
Age: < 9 to > 12 years
Sex: 45% girls
2 weeks
PA digital vs. paper: ICC 0.73
PA 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 = 161
Age: 3–10 years
Sex: 50% girls
15 days
Active commuting: SCC 0.28
PA at school: SCC 0.31
PA at leisure time: SCC 0.33
MPA: SCC 0.37
VPA: SCC 0.89
Weekly 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 = 192
Age: 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 = 53
Age: 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 0.47
Weekend 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 = 147
Age: 6–10 years, 13–14 years
Sex: 51% girls (in total sample n = 189)
2 months
6 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: fair
6 months’ time interval: poor
–
Physical Activity Questionnaire for older Children (PAQ-C) (Spanish version) [52]
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 = 323
Age 12.8 years
Sex: 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 = 150
Age: 13.6 ± 1.1 years
Sex: 52% girls
7 days
PA index: ICC 0.76
Organized sport participation outside school: ICC 0.86
Non-organized sport participation outside school: ICC 0.58
PE: ICC 0.61
Hours per week out of school PA intensity: ICC 0.82
Participation in competitive sport: ICC 0.93
Good
±
International Physical Activity Questionnaire - Short Form (IPAQ-SF) [84]
n = 92
Age: 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 = 77
Age: 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 = 53
Age: 14.1 ± 1.4 years
Sex: 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)
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 = 121
Age: 8–16 years
Sex: 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 = 87
Age: 13.1 ± 0.9 years
Sex: 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 = 71
Age: 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 = 693
Age: 11.1 ± 0.5 and 15.1 ± 0.5 years
Sex: 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 0.44
VPA: ICC 0.55 (95% CI 0.49–0.61), kappa 0.41
1-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 = 68
Age: 15.4 years
Sex: 47% girls
13 days (range: 8–16 days)
PE min/class: ICC 0.89, min/week 0.84
No. of sport teams or after school PA in school: ICC 0.74
No. of sport teams or after school PA out-of-school: ICC 0.89
Leisure time PA: past 7 days ICC 0.70, usual week ICC 0.79, average ICC 0.76
Walking 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 0.59
Walk to school: ICC 0.89
Walk from school: ICC 0.76
Fair
±
Physical Activity and Lifestyle Questionnaire (PALQ) (Greek version) [33]
Bike to school (no./days): PoA 88%, (amount of time) 85%
Fair
Dutch Physical Activity Checklist for Children (PAQ-C) [35]
n = 192
Age: 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 = 109
Age: 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 = 87
Age: 11–12 years
Sex: percentage girls unknown
2 weeks
Classification in major mode of commuting: PoA 97%
Good
3-Day Physical Activity Recall (3DPARecall) [19] c
n = 65
Age: 12.5 ± 1.1 years
Sex: 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 = 84
Age: 12.5 ± 1.1 years
Sex: 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 = 68
Age: 15.4 years
Sex: 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]
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
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2.8 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.
3 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
×
3.1 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.
3.2 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.
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3.3 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).
3.4 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.
4 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.
4.1 Construct Validity
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].
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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.
4.2 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.
4.3 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.
4.4 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 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.
5 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.
Compliance with Ethical Standards
Funding
The contribution of Lisan Hidding was funded by the municipality of Amsterdam, Amsterdam Healthy Weight Programme.
Conflict of interest
Lisan Hidding, Mai Chinapaw, Mireille van Poppel, and Teatske Altenburg declare that they have no conflicts of interest. The institute of which Lidwine Mokkink is a part receives royalties for one of the references cited in this review (de Vet HCW, Terwee CB, Mokkink LB, Knol DL. Measurement in medicine: a practical guide. 1st ed. Cambridge: Cambridge University Press; 2011).
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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