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Development and validation of the Global Adolescent and Child Physical Activity Questionnaire (GAC-PAQ) in 14 countries: study protocol
  1. Richard Larouche1,
  2. Mahdi Rostami Haji Abadi1,
  3. Salomé Aubert2,
  4. Jasmin Bhawra3,
  5. Javier Brazo-Sayavera4,
  6. Valerie Carson5,
  7. Rachel C Colley6,
  8. Christine Delisle Nyström7,
  9. Dale W Esliger8,
  10. Ryan Harper-Brown9,
  11. Silvia Alejandra Gonzalez Cifuentes10,
  12. Alejandra Jáuregui11,
  13. Piyawat Katewongsa12,
  14. Anuradha Khadilkar13,
  15. Geoff Kira14,
  16. Nicholas Kuzik15,
  17. Yang Liu16,
  18. Marie Lof7,
  19. Tom Loney17,
  20. Taru Manyanga18,
  21. Tawonga W Mwase-Vuma19,20,
  22. Adewale L Oyeyemi21,22,
  23. John J Reilly20,
  24. Justin Richards14,
  25. Karen Roberts23,
  26. Olga Lucia Sarmiento10,
  27. Diego Augusto Santos Silva24,
  28. Melody Smith25,
  29. Narayan Subedi26,
  30. Leigh M Vanderloo27,28,
  31. Dyah Anantalia Widyastari12,
  32. Oliver W A Wilson14,
  33. S H Wong29,
  34. Mark S Tremblay2,15
  1. 1 Faculty of Health Sciences, University of Lethbridge, Lethbridge, Alberta, Canada
  2. 2 Active Healthy Kids Global Alliance, Ottawa, Ontario, Canada
  3. 3 School of Occupational and Public Health, Toronto Metropolitan University, Toronto, Ontario, Canada
  4. 4 Department of Sports and Computer Science, Universidad Pablo de Olavide, Sevilla, Spain
  5. 5 University of Alberta, Edmonton, Alberta, Canada
  6. 6 Health Analysis Division, Statistics Canada, Ottawa, Ontario, Canada
  7. 7 Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden
  8. 8 School of Sport, Exercise, and Health Sciences, Loughborough University, Loughborough, UK
  9. 9 Department of New Media, University of Lethbridge, Lethbridge, Alberta, Canada
  10. 10 School of Medicine, Universidad de los Andes, Bogotá, Colombia
  11. 11 Department of Physical Activity and Healthy Lifestyles, National Institute of Public Health, Cuernavaca, Mexico
  12. 12 Institute for Population and Social Research, Mahidol University, Salaya, Thailand
  13. 13 Hirabai Cowasji Jehangir Medical Research Institute, Jehangir Hospital, Pune, India
  14. 14 Te Hau Kori, Faculty of Health, Victoria University of Wellington, Wellington, Wellington, New Zealand
  15. 15 Healthy Active Living and Obesity Research Group, CHEO Research Institute, Ottawa, Ontario, Canada
  16. 16 School of Physical Education, Shanghai University of Sport, Shanghai, China
  17. 17 College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE
  18. 18 Division of Medical Sciences, University of Northern British Columbia, Prince George, British Columbia, Canada
  19. 19 Centre for Social Research, University of Malawi, Zomba, Malawi
  20. 20 Department of Psychological Sciences and Health, University of Strathclyde, Glasgow, UK
  21. 21 College of Health Solutions, Arizona State University, Tempe, Arizona, USA
  22. 22 Department of Physiotherapy, Redeemer’s University, Ede, Nigeria
  23. 23 Centre for Surveillance and Applied Research, Public Health Agency of Canada, Ottawa, Ontario, Canada
  24. 24 Federal University of Santa Catarina, Florianopolis, Brazil
  25. 25 The University of Auckland, Auckland, New Zealand
  26. 26 Nepal Development Society, Chitwan, Nepal
  27. 27 School of Occupational Therapy, University of Western Ontario, London, Ontario, Canada
  28. 28 ParticipACTION, Toronto, Ontario, Canada
  29. 29 Chinese University of Hong Kong, Hong Kong, China
  1. Correspondence to Dr Richard Larouche; richard.larouche{at}uleth.ca

Abstract

Introduction Global surveillance of physical activity (PA) of children and adolescents with questionnaires is limited by the use of instruments developed in high-income countries (HICs) lacking sociocultural adaptation, especially in low- and middle-income countries (LMICs); under-representation of some PA domains; and omission of active play, an important source of PA. Addressing these limitations would help improve international comparisons, and facilitate the cross-fertilisation of ideas to promote PA. We aim to develop and assess the reliability and validity of the app-based Global Adolescent and Child Physical Activity Questionnaire (GAC-PAQ) among 8–17 years old in 14 LMICs and HICs representing all continents; and generate the ‘first available data’ on active play in most participating countries.

Methods and analysis Our study involves eight stages: (1) systematic review of psychometric properties of existing PA questionnaires for children and adolescents; (2) development of the GAC-PAQ (first version); (3) content validity assessment with global experts; (4) cognitive interviews with children/adolescents and parents in all 14 countries; (5) development of a revised GAC-PAQ; (6) development and adaptation of the questionnaire app (application); (7) pilot-test of the app-based GAC-PAQ; and, (8) main study with a stratified, sex-balanced and urban/rural-balanced sample of 500 children/adolescents and one of their parents/guardians per country. Participants will complete the GAC-PAQ twice to assess 1-week test–retest reliability and wear an ActiGraph wGT3X-BT accelerometer for 9 days to test concurrent validity. To assess convergent validity, subsamples (50 adolescents/country) will simultaneously complete the PA module from existing international surveys.

Ethics and dissemination Approvals from research ethics boards and relevant organisations will be obtained in all participating countries. We anticipate that the GAC-PAQ will facilitate global surveillance of PA in children/adolescents. Our project includes a robust knowledge translation strategy sensitive to social determinants of health to inform inclusive surveillance and PA interventions globally.

  • Surveys and Questionnaires
  • Health Surveys
  • PUBLIC HEALTH
  • Psychometrics
http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/bmjopen-2023-082275

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    Strengths and limitations of this study

    • This will be the first physical activity (PA) questionnaire to be culturally adapted and validated for use among 8–17 years old across all inhabited continents and income levels.

    • The target sample of 7000 children and adolescents stratified by sex and urbanisation (eg, urban, rural) represents the most diverse ever used for the validation of a PA questionnaire for children and adolescents.

    • The use of an app with adaptable content should enhance data collection efficiency for younger children (eg, 8–10 years old) and respondents with limited reading ability, while minimising data entry errors.

    • Our questionnaire will be validated against ActiGraph accelerometers that have established reliability and validity, but underestimate PA during certain activities which may bias validity estimates towards the null hypothesis.

    • Self-reported measures of PA are at risk of recall and social desirability biases, but they provide important contextual information and are cheaper and generally easier to implement than accelerometers.

    Introduction

    Most children and adolescents worldwide do not meet current physical activity (PA) guidelines, which recommend an average of ≥60 min per day of moderate- to vigorous-intensity physical activity (MVPA).1–5 This raises concern because insufficient physical inactivity is a major risk factor for non-communicable diseases, and is associated with lower academic achievement and higher risk of mental health conditions.6–9 Many interventions have been developed to promote PA, but multiple reviews have highlighted a lack of tangible progress in addressing the global physical inactivity crisis.4 10 Moreover, evidence consistently indicates that girls are less active than boys1 3 11 12 and PA declines with age,1 13–15 underscoring a need to promote PA early in life and address known disparities. Such disparities have also been reported based on characteristics such as socioeconomic status (SES), ethnicity and disability.2 16 17

    In its Global Action Plan on Physical Activity 2018–2030, the WHO targeted a 15% reduction in the prevalence of insufficient PA among adolescents and adults by 2030.7 Monitoring progress towards this goal is challenging due to significant gaps and disparities in current national and international surveillance initiatives.1 18 19 Enhanced surveillance systems would allow for more precise cross-country comparisons of PA indicators, aligning with the missions of entities like the WHO and the Active Healthy Kids Global Alliance (AHKGA)2 to encourage PA.

    Presently, intercontinental PA surveillance initiatives for children and adolescents are limited by numerous issues.1 2 18 20 21 First, public health surveillance of PA is underfunded globally as evidenced by the lack of data on children’s PA in many countries across all levels of economic development.18 Second, there are many inconsistencies in measures (eg, devices vs self-report; variation in self-report and proxy-report instruments) and definitions of achieving sufficient PA (eg, achieving ≥60 min/day of MVPA every day vs on average) that make it hard to compare data across countries.1 Third, most PA questionnaires have been developed from predominantly urban samples from high-income countries (HICs), with insufficient efforts to adapt them to the cultural and socio-economic contexts of low- and middle-income countries (LMICs) and minority groups in HICs.1 Sound sociocultural adaptation is crucial to ensure comparability of PA estimates between countries while being attentive to issues of equity, diversity, inclusion, literacy levels and accessibility. Fourth, questionnaires used in large international studies tend to overlook active play, sport and work-related PA,2 which may be substantial sources of PA. The need for an instrument that captures all domains of PA has been repeatedly identified.1 2 18 22 23

    Among the domains that are overlooked, active play—‘voluntary engagement in activity that is fun and/or rewarding, usually driven by intrinsic motivation, and involving PA of any intensity’24—is essential for children’s physical, social and cognitive development.25 26 It is considered a human right,27 and it may be a more accessible and routine source of PA than organised activities, especially in low-income communities. However, a reliable and valid instrument to measure active play is lacking. Active play can occur indoors and outdoors,24 though outdoor play is typically associated with higher PA levels and may provide additional benefits in terms of psychosocial health.26 28 29

    Therefore, our primary objectives are to develop the Global Adolescent and Child Physical Activity Questionnaire (GAC-PAQ) and assess its reliability and validity based on child/adolescent and parent/guardian report across 14 countries providing large variability in climate, level of urbanisation, SES, ethnicity, languages spoken and Human Development Index. Our second objective is to generate the ‘first available data’ on active play and outdoor play in many of the participating countries and investigate how it varies by social determinants of health (eg, age, gender, education, ethnicity, (dis)ability) and across countries.

    Methods and analysis

    Project leadership and management

    Our project is guided by a 13-member Steering Committee including researchers and knowledge users (online supplemental file 1). The Steering Committee selected participating countries to maximise variability in characteristics such as geographical location, languages spoken, country income, population density and Human Development Index. Next, they identified investigators who have demonstrated the capacity to conduct large-scale PA data collection. Participating countries include Brazil, Canada, China, Colombia, India, Malawi, Mexico, Nepal, New Zealand, Nigeria, Spain, Sweden, Thailand and the United Arab Emirates (figure 1). Table 1 provides country-level indicators for participating countries and a more detailed version of the table is available in online supplemental file 2. The country Lead Investigators, also listed in online supplemental file 1, are responsible for all aspects of study implementation in their country. The Coordinating Centre, based at the University of Lethbridge (Canada), is responsible for developing questionnaire drafts and the app (discussed below), producing training materials and manuals, organising regular team meetings, planning analysis methods, completing data transfer and funding agreements with each site and maintaining the knowledge translation plan. The study team also includes subcommittees that advise on matters related to accelerometry, knowledge translation and justice, equity, diversity and inclusion.

    Supplemental material

    Supplemental material

    Figure 1
    Figure 1

    Countries involved in the Global Adolescent and Children Physical Activity Questionnaire project. Note: Created with mapchart.net under a Creative Commons Attribution-ShareAlike 4.0 International License.

    View this table:
    Table 1

    Characteristics of included countries

    Study design

    The development, adaptation and validation of the GAC-PAQ involves eight stages described below, some of which are occurring concurrently given our 3-year funding timeline. Table 2 summarises each stage and progress to date. Because stages involving data collection will use a cross-sectional design, we used the Strengthening the Reporting of Observational Studies in Epidemiology checklist30 to prepare the study protocol.

    View this table:
    Table 2

    Stages of the Global Adolescent and Child Physical Activity Questionnaire (GAC-PAQ) development and validation process and summary of progress to date

    Supplemental material

    Stage 1: systematic review of the psychometric properties of PA questionnaires

    This stage began with an environmental scan of instruments used in multicountry studies including the Global School-based Student Health Survey (GSHS)12 and Health Behaviour in School-aged Children Survey (HBSC)31 to help inform the first draft of the GAC-PAQ. The scan revealed important gaps in coverage of PA domains (eg, active play, work) and under-representation of LMICs as reported previously.1 Our full systematic review summarised the psychometric properties of existing PA questionnaires for preschoolers, children and adolescents, updating a previous review.32 We registered the protocol in the Open Science Framework registry (https://doi.org/10.17605/OSF.IO/9KN73) and used the Consensus-based Standards for the selection of health status Measurement Instruments (COSMIN) guidelines for systematic reviews of Patient‐Reported Outcome Measures33 to minimise bias and ensure consistent reporting. Many of the included questionnaires whose psychometric properties were assessed in LMICs were developed in HICs, often with limited cultural adaptation, so results of the systematic review (submitted for publication) support the need for developing a new PA questionnaire.

    Stage 2: development of the GAC-PAQ

    First, Steering Committee members and country Lead Investigators were surveyed about their preferences regarding questionnaire format, reference period (eg, past week, past month, typical week), and how PA duration and intensity should be assessed. RL, MST and MRHA reviewed survey responses, developed a first draft in English and requested further feedback from the Steering Committee and Lead Investigators. When indicating their preferences, members were asked to think about the extant evidence, to consider the trade-off between usability and accuracy in data collected as well as how to minimise recall bias.

    Stage 3: assessment of content validity

    Once consensus was reached on the modifications, the revised draft was sent to global PA measurement/surveillance experts for content validation (Stage 3). These experts were identified in consultation with all country Lead Investigators. Experts completed an online survey assessing their agreement with four statements adapted from the COSMIN checklist33 34 for each domain of the GAC-PAQ. Items were presented on a 5-point Likert scale from strongly disagree to strongly agree. The statements included: (1) ‘Items refer to relevant aspects of the domain’ (eg, the school domain); (2) ‘Items are relevant for the target population (ie, 8- to 17-year-olds)’; (3) ‘Items are relevant for the purpose of the measurement instrument’; and (4) ‘Collectively, the items adequately reflect the domain’. Respondents were invited to provide qualitative feedback following each domain and at the end of the survey. We collected socio-demographic information from respondents (age, gender, country and work sector) for descriptive purposes, and used their feedback to prepare a revised version of the GAC-PAQ.

    Stage 4: cognitive interviews in 14 countries

    We conducted cognitive interviews (10–20 per country) with a convenience sample of children/adolescents and their parents/guardians that aims to provide diversity in sociodemographic characteristics. Before beginning these interviews, the questionnaire was translated into the languages of participating countries and back-translated to English for verification. Any discrepancies between the original and back-translated versions were resolved by the country Lead Investigators in consultation with their study staff, translators and, as needed, the study co-principal investigators (PIs) (RL and MST). The English version of the GAC-PAQ initially used for cognitive interviews with children/adolescents is provided in online supplemental file 3. This version included still images representing different intensities of PA to exemplify how questions would appear in the app as described under Stage 5. Interviewees in Stage 4 were asked to identify any words or items in the questionnaire that they find unclear and provide suggestions for improvement. Participants were encouraged to think aloud while responding and to ask any questions for clarification.35 36 All interviews were audio-recorded and transcribed verbatim. The framework analysis method developed by Ritchie and Spencer,37 was used to analyse interview data. This pragmatic approach allows both inductive and deductive issues to be considered and is well-suited to applied projects where a qualitative component is embedded in a larger quantitative study.37 Two researchers with knowledge of the local context analysed the data for their country and compiled an Excel spreadsheet that includes challenges perceived by participants, suggestions for improvement, relevant quotes and participant sociodemographic characteristics. The spreadsheets from Stage 4 were merged and reviewed by the coordinating centre which proposed changes to the Steering Committee members and Lead Investigators. The revised version produced after this stage will be used to develop the app.

    We made some modifications to the questionnaire based on feedback from the first eight interviews in Canada and mock interviews in Thailand. First, the order of the work and chores domains was reversed. With the initial version, some participants reported chores as work, so we expect that this revision will minimise double counting. Second, the questions about travel mode from school to home were eliminated because many participants indicated that they do not go directly from school to home (eg, they may go to a park or an after-school programme) and given evidence from a recent national longitudinal study in Canada where the difference in the prevalence of active transportation between the trips to and from school was less than 1% (Larouche et al, unpublished observations). Third, for similar reasons, we removed the question about travel mode from work to home. These modifications allowed us to shorten the questionnaire, which may be desirable from a surveillance perspective.

    Stage 5: development of the app-based questionnaire

    We believe that an app-based questionnaire provides many advantages over traditional paper-and-pencil questionnaires including: (1) a streamlined data collection process, facilitating surveillance and preventing data entry errors; (2) using familiar and ubiquitous devices (eg, tablets and smartphones) to facilitate completion of the questionnaire; and, (3) the ability to use both text-based and audio/video descriptions for users with disabilities or limited reading ability. Furthermore, Tremblay and colleagues38 found that Canadian children as young as 7.7±0.5 years could recall their previous day’s PA reasonably accurately when facilitative video cues were provided. Video and images can help clarify nuances between different types and intensities of PA while ensuring consistency in directions provided to participants. The inclusion of narration and images also aims to facilitate the use of the GAC-PAQ as a self-administered survey in future research. The app will be designed to work on smartphones and tablets (with and without internet access to accommodate sites where such access can be limited); hence it will be a ‘native’ app rather than a web-based app. We intend to make the app freely available, so that it can be used at scale and tailored to different contexts. The app will be developed to comply with the European General Data Protection Regulation.

    Stage 6: production of the app in multiple languages

    This will involve the adaptation of the app to participating countries and the translation of app content following the approach described in Stage 3. We will use artificial intelligence (AI; specifically, MidJourney, ElevenLabs and Adobe Photoshop) to generate images illustrating the different types of activities and representing diversity in characteristics such as age, ability, ethnicity, size, sex and gender diversity. AI-generated images are realistic and do not require subjects’ consent. Lead Investigators will have access to an image bank from which they can select culturally-relevant examples. Although questionnaire items will be the same, examples (written and visual) provided will be customised to each country. To illustrate different activity intensities (light, moderate and vigorous), country Lead Investigators and their teams will select appropriate examples from the Youth Compendium of Physical Activities39 40 and may include other culturally-relevant activities. The app will be organised by the PA domains indicated in figure 2. At the beginning of each domain, there will be a screening question to determine if other questions in the domain apply. For example, in the school domain, children will be asked if they attended school in the past week. If they respond ‘no’, then subsequent questions about school will be deemed not applicable and thus skipped. This approach aims to enhance data quality by reducing completion time and the perceived irrelevance of questions.

    Figure 2
    Figure 2

    Sampling variables, instruments used in the main study and domains assessed by the Global Adolescent and Children Physical Activity Questionnaire (GAC-PAQ) project. Notes: Numbers in parentheses represent the number of participants in each stratum across 14 participating countries. The analytical sample size for ActiGraph data will depend on adherence to the protocol described in Stage 8. The right column indicates the psychometric properties that will be assessed in the study. GSHS: Global School-Based Student Health Survey; HBSC: Health Behaviour in School-Aged Children Survey.

    Stage 7: pilot study of the app

    Prior to deploying the main study, we will pilot test the app-based GAC-PAQ with a convenience, but sex-stratified and urban-/rural-stratified sample of 30 child–parent dyads per country. We will use country-specific definitions of urban and rural areas to ensure the relevance of our findings for knowledge users. Because peri-urban/suburban areas are near the centre of the continuum between rural and urban areas and more difficult to operationalise consistently between countries, we will recruit schools in urban and rural areas only. For Stages 7 and 8, children and adolescents will complete the questionnaire on tablets provided by the study team. Country investigators will be asked to consider the best way for the parents to complete the questionnaire (eg, on their own time on their phone or tablet vs in-person on tablets purchased for the study) based on considerations such as access to mobile devices. Following completion of the GAC-PAQ, we will ask participants to rate their satisfaction with the questionnaire on a 5-point Likert scale from poor to excellent that will include emojis to facilitate comprehension for younger participants. We will also provide an opportunity for participants to type comments about their experience in the app at the end of the survey. Their feedback will be considered by the Steering Committee and Lead Investigators when preparing the final version of the app. All study staff will be trained to use the same protocol to administer the questionnaire, which will be translated as needed to ensure compliance. We will create standard operating procedures (SOPs) for the administration of the GAC-PAQ and other questionnaires (ie, HBSC, GSHS) and for collecting accelerometry data. We will discuss the SOPs at a monthly team meeting, then investigators will be asked to train their staff.

    Stage 8: main study

    Each country will recruit a sex-balanced and urban-/rural-stratified sample of 500 children/adolescents and one of their parents/guardians. Table 3 summarises the country-specific adaptations of the sampling strategy and highlights planned efforts to ensure the diversity of the sample in terms of age, SES, climate, geography, ethnicity/nationality, etc. In some participating countries, a substantial proportion of children and adolescents do not attend school (eg, India, Malawi, Nepal). They are routinely excluded from international PA surveys like the GSHS and the HBSC,12 31 thus reducing their external validity. To minimise potential bias, we will also recruit children through community-based and faith-based groups in such countries. Our sampling strategy is tailored to each participating country (eg, different school systems), using a similar approach to the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE)41 and the International Study of Movement Behaviours in the Early Years.42 Data collection will be staggered, with each site completing data collection over a full calendar year to capture seasonal variations in weather and circannual behaviours. We aim to achieve reasonable heterogeneity to challenge the robustness of the GAC-PAQ across diverse socio-demographic and cultural circumstances.

    View this table:
    Table 3

    Sampling methods for each participating country

    We will ask participants to complete the GAC-PAQ twice, 8 days apart. We will also collect data on variables including child/adolescent gender (where culturally acceptable), sex, age, ethnicity/country of birth, urban/rural living location, whether the child/adolescent has a disability or chronic condition and SES indicators. These variables may contribute to differences in reliability/validity (objective 1) and/or predict engagement in active play (objective 2). To compare the GAC-PAQ with questionnaires employed in previous international studies examining the prevalence of PA (convergent validity), we will ask a random subsample of 50 adolescents per country to complete the PA modules from the GSHS12 and HBSC.31 Figure 2 summarises data collection plans for Stage 8.

    We will examine the concurrent validity of the questionnaires (GAC-PAQ, HBSC and GSHS) against PA estimates from hip-worn ActiGraph wGT3X-BT (Pensacola, Florida) accelerometers collected over seven consecutive days. The ActiGraph has good to excellent validity for measuring PA,43 including among children with physical disabilities.44 Accelerometers are increasingly used in population-based studies,13 45 46 making them an appropriate comparison measure of free-living PA. The ISCOLE 24-hour accelerometry protocol will be adopted, which resulted in much higher wear time than protocols wherein participants are asked to wear the device during waking hours only.47 48 Accelerometry data will be processed to estimate non-wear time, sleep time, sedentary time, light-intensity, moderate-intensity and vigorous-intensity PA, MVPA, total counts/min and total steps/day. The last two measures represent total PA and will be compared with the reported time spent in PA across all domains from the GAC-PAQ. Cut-points to determine the non-wear time and different PA intensities will be selected based on the best available evidence at the time of analyses. When research staff distribute accelerometers to participants, children/adolescents and parents/guardians will be asked to complete the GAC-PAQ for the previous week. Accelerometry data collection will begin in the late afternoon of the first day to capture sleep on the first night. On day 9, research staff will pick up accelerometers and ask children/adolescents and parents/guardians to complete the GAC-PAQ a second time, for the week corresponding to accelerometer wear. This will minimise the temporal mismatch between the questionnaire and accelerometer data. The deployment of accelerometers for 9 days will ensure that we get one full week of data.

    Patient and public involvement

    Given the importance of ensuring that questionnaire items are relevant and comprehensible, cognitive interviews are being conducted with children/adolescents and parents/guardians in Stage 4. Similarly, participants’ experience with the app-based version of the questionnaire will be assessed in Stage 7. Participants’ feedback will be synthesised by the Steering Committee and Country Lead Investigators to help simplify questions and improve the experience of app users. Furthermore, three knowledge users on our Steering Committee (RCC, LMV and KR) were intentionally selected based on their expertise in PA epidemiology, measurement and surveillance methods. They work in national governmental agencies responsible for surveillance (Statistics Canada, Public Health Agency of Canada) or in a national non-profit organisation that promotes PA (ParticipACTION). They are well-positioned to provide input on the feasibility of the GAC-PAQ for use in population monitoring and help mobilise findings. Several students in New Media and Computer Science from the University of Lethbridge are also contributing to the development of the app under the supervision of RH-B.

    Training and capacity building

    Capacity building has been included from the project inception, beginning with the inclusion of country Lead Investigators as co-applicants on the main grant application, and the inclusion of LMIC priorities in the study design. Lead Investigators are also responsible for providing feedback on different versions of the GAC-PAQ, recruiting staff and trainees, and they share the responsibility of training with the Principal Investigators and Project Manager. Across participating countries, we expect that ≥40 students, trainees and early-career researchers will be involved in the project. A 2-day in-person meeting was held before the International Society for Behavioural Nutrition and Physical Activity conference (Uppsala, Sweden; June 2023) where the project was first introduced to the broader scientific community through a symposium. Investigators from 12 participating countries attended the in-person meeting and two Investigators attended online. The meeting covered all phases that will be overseen by the Lead Investigators. It was at that meeting that the revisions to the draft questionnaire used for the cognitive interviews were decided. It included an accelerometer training session led by Dr Esliger and a presentation of the initial app design led by RH-B. Lead Investigators are required to submit monthly progress reports including details about recruitment progress and challenges and to participate in monthly Zoom meetings. This enables the Principal Investigators and Project Manager to monitor progress and intervene as needed.

    Sample size justification

    In the multicountry reliability studies for the widely used adult-focused Global Physical Activity Questionnaire49 and International Physical Activity Questionnaire,50 correlations between repeated measures for total PA ranged from r=0.67–0.73 and r=0.46–0.96, respectively. Craig et al 50 also reported that, in most study sites, correlation coefficients exceeded r=0.80. Based on the formula proposed by Walter et al,51 205 participants per country would be needed to achieve a power of 0.8 at an alpha of 0.05, assuming an expected intra-class correlation coefficient (ICC) of 0.70 (p 1) and a minimally acceptable level of reliability of 0.6 (p 0). Based on this calculation, a sample of ~500 parent–child dyads per country should provide sufficient power for sex-stratified and/or gender-stratified within-country analyses, allowing for 20–25% missing data. Within-country analyses will also be separately stratified by age (8–11 vs 12–17 years) and urbanisation (urban vs rural). Our target sample size per country is higher than psychometric studies for adult questionnaires49 50 and should provide adequate power to examine the concurrent validity between the GAC-PAQ and accelerometry-measured PA.

    Statistical analyses

    Objective 1

    In Stage 3, we will assess content validity based on the proportion of experts who agree or strongly agree with the statements for each domain. If agreement is <75% for any domain, we will revise the questionnaire items based on experts’ feedback and repeat the assessment of content validity. While there is no universal threshold for determining expert agreement, Delphi studies and psychometric studies often use thresholds ranging from 70% to 80%.32 52 In Stage 8, we will derive estimates of PA from the GAC-PAQ. To do this, we plan to use midpoints for the response options that are provided as ranges. Next, we will give weight to these midpoints to account for the fact that, for example, children and youth are not engaging in MVPA for the entire duration of their physical education period.53 54 Then, we will calibrate the GAC-PAQ against accelerometry data following a process similar to Saint-Maurice et al 55 to improve our estimates of PA.

    We will assess test–retest reliability and convergent validity with ICCs for continuous variables and kappa coefficients and percent agreement for categorical variables.30 We will use Cicchetti’s56 descriptors to qualify ICCs and kappa values as ‘excellent’ (≥0.75), ‘good’ (0.60–0.74), ‘fair’ (0.40–0.59) and ‘poor’ (<0.40). To verify the stability of the measures, we will use repeated measures analysis of variances (or Kruskal-Wallis tests if data are not normally distributed) to compare item and scale means between the test and retest. We will use Pearson correlations to assess the concurrent validity of the questionnaires against accelerometer data and compare the GAC-PAQ with measures of the corresponding constructs from the HBSC and the GSHS. We will use Bland-Altman57 plots to represent the limits of agreement between questionnaire estimates and accelerometry-measured total PA and MVPA. We will also assess the convergent validity of the GAC-PAQ by comparing scores from children/adolescents and parents/guardians. Our main analyses of reliability and validity will be stratified by country, sex and gender. We will only ask children/adolescents to report their gender in countries where it is deemed culturally appropriate (ie, by investigators and research ethics boards). Adopting such an approach will allow us to examine both biological (sex) and socio-cultural (gender) differences when possible. For comparison purposes, we will perform secondary analyses to examine how psychometric properties differ by social determinants of health, including age, disability, ethnicity (where acceptable), parent education, etc.

    Objective 2

    We will use descriptive analyses to summarise active play and outdoor time. Next, we will use sex-stratified generalised linear mixed models to investigate the correlates of these activities while accounting for the nesting of children within schools/organisations and countries as random effects.58 We will first run bivariate models and retain variables associated with active (or outdoor) play at a liberal threshold of p<0.20 as candidates for inclusion in multivariable models.59 Then, we will use a backward selection process to obtain parsimonious multivariable models by removing non-significant variables (p>0.05). In general, we will use a similar approach to investigate the correlates of overall PA and domain-specific PA. Based on an intersectionality perspective, we will also explore interactions between sex, gender and multiple social determinants of health given the emerging evidence showing that membership of multiple under-privileged groups (eg, women from visible minorities with low income) increases the risk of physical inactivity in Canadian and Brazilian adults.60 61

    Ethics and dissemination

    Ethical approval has been obtained for Stages 3 and 4 from institutional review boards of all institutions with researchers involved in data collection. The names of the institutional review boards and protocol number for these stages are reported in online supplemental file 4. In some countries, investigators have obtained ethical approval for Stages 7 and 8, while in other countries, ethical approval is pending. Participants in the content validation survey were invited by email, and received an information letter indicating that, by proceeding to the survey, they were providing implied consent. For Stages 4, 7 and 8, written informed consent and assent will be required from parents/guardians and children/adolescents, respectively (except for some countries where adolescents can provide consent). Approval will also be requested from school boards and/or other organisations participating in the study.

    Supplemental material

    A data-sharing agreement will be implemented between participating institutions and the Coordinating Centre (Canada) before sharing de-identified data. The agreement will be signed by parties at the Coordinating Centre and collaborating institutions. Collaborating institutions will retain ownership of their data. Data sets will be password-protected and encrypted prior to transfer, and only research team members will have access to data. Secure server space will be provided at the Coordinating Centre to store data collected through the app. Researchers not involved in the study can request data access, and if approved, they would need to sign a data-sharing agreement with the Coordinating Centre. Efforts will be made to integrate the de-identified accelerometry data set with the International Children Accelerometry Database.13 Publication policies will follow principles of justice, equity, diversity and inclusion. We developed a publications policy and a publications committee to ensure the representation of graduate students, trainees and early career investigators as lead authors of presentations and articles.

    Knowledge translation plan

    We will work with ParticipACTION whose mailing list includes >46 300 subscribers to ensure that findings are communicated in an appealing format for diverse target audiences, thus maximising reach and optimising uptake. Similar dissemination will be orchestrated through the Steering Committee and Lead Investigators’ networks. Study objective #2 focuses on improving the measurement of active play, addressing a gap that has been repeatedly identified by the AHKGA and ParticipACTION among others.2 62–64 Our study will substantially reduce the number of country report cards assigning ‘incomplete’ grades to the active play indicator in the Global Matrix initiative due to a lack of available data.2 62 65 66 The Report Card on Physical Activity for Children and Youth is a widely used and successful knowledge translation tool developed by MST and adopted by researchers and practitioners in>70 countries that synthesises the best-available data on children and adolescents PA.2 62 65–67

    We also plan several end-of-grant knowledge translation activities. We will develop a user manual to assist users in appropriately administering the GAC-PAQ as intended. The GAC-PAQ will be made freely available via the AHKGA website and promoted through team members’ networks. Moreover, the Co-PIs are founding members of Outdoor Play Canada and the Play, Learn, and Teach Outdoors Network (PLaTO-Net) which collectively have >700 members. These organisations will help disseminate results to practitioners, policymakers, researchers and advocates. We will host workshops/events in many participating countries and submit lay articles to The Conversation and other platforms to summarise, among others: (1) the development and psychometric properties of the GAC-PAQ; (2) the main findings for the comparison of PA and active play between countries; and (3) where to access the GAC-PAQ. We will submit abstract/symposia proposals for presentation at international PA conferences. Likewise, we plan to submit ≥20 manuscripts to leading PA/public health journals. Finally, team members will communicate findings via their websites, newsletters and social media channels, using relevant, handles, tags, and mentions.

    Ethics statements

    Patient consent for publication

    Acknowledgments

    The authors acknowledge the contribution of Mr Ogochukwu Onyeso who provided feedback on grant applications and helped format co-applicants’ CVs. Dr Farzana Sadia also assisted with the preparation of CVs. We also recognise the contribution of Ms Jackie Eshriew, Ms Moni Omubor and Mr Don Castillo in the design and development of the app. This protocol was presented at the 2023 International Society for Behavioral Nutrition and Physical Activity conference in Uppsala, Sweden; the abstract is available on p. 881 of this document: https://annualmeeting.isbnpa.org/wpcontent/uploads/2023/07/ISBNPA-2023-Abstract-Book-web-final.pdf

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    Supplementary materials

    Footnotes

    • X @valLCarson, @MelOliverSmith, @nsubedi_np

    • Contributors RL and MST conceived and designed the study and led grant applications. JR, GK, OWAW, and MS obtained funding for data collection in New Zealand. MRHA is the project manager for the study and led the systematic review. RL prepared the analysis plan, drafted the manuscript and appendices, and integrated feedback from all co-authors. MRHA, SA, JB, JB-S, VC, RCC, CN, DWE, RH-B, SAGC, AJ, PK, AK, GK, NK, YL, ML, TL, TM, TWM-V, ALO, JJR, JR, KR, MS, OLS, DASS, NS, LMV, DAW, OWAW, SHW, and MST critically reviewed the manuscript and approved the final version for submission.

    • Funding This work is supported by a Project Grant (grant # PJT 183705) and an Early Career Investigator Prize (grant # ECP 184184) from the Canadian Institutes of Health Research, a Prentice Institute Research Affiliate Fund Grant from the Prentice Institute for Global Population and Economy (grant # G00004116) and a Te Herenga Waka Victoria University of Wellington Division of Science Health Engineering Architecture and Design Innovation Faculty Strategic Research Grant (grant # FSRG-SHEADI-10724). The Thailand Physical Activity Knowledge Development Centre (TPAK)/Thai Health Promotion Foundation provided funding for the cognitive interviews and pilot study in Thailand (grant number 66-P1-0473). In Mexico, data collection for Stage 7 will be partially supported by Fundación Gonzalo Río Arronte (grant # S680), and the Consejo Nacional de Ciencia y Tecnología (grant # FOSISS-CONACYT 290382). The University Pablo de OIavide provided a scholarship for an undergraduate student working on the project (code PPI2207). OWAW was supported by the Division of Intramural Research at the National Institute on Minority Health and Health Disparities of the National Institutes of Health (Grant #: N/A). Opinions and comments expressed in this paper belong to the authors and do not necessarily reflect those of the US government, Department of Health and Human Services, National Institutes of Health or the National Institute on Minority Health and Health Disparities; they should not be construed to represent the views of the National Institutes of Health. The study sponsors have no role in study design, data collection, analysis and publication of the findings.

    • Map disclaimer The inclusion of any map (including the depiction of any boundaries therein), or of any geographical or locational reference, does not imply the expression of any opinion whatsoever on the part of BMJ concerning the legal status of any country, territory, jurisdiction or area or of its authorities. Any such expression remains solely that of the relevant source and is not endorsed by BMJ. Maps are provided without any warranty of any kind, either express or implied.

    • Competing interests None declared.

    • Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.

    • Provenance and peer review Not commissioned; externally peer reviewed.

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