Development of the Physical Literacy Environmental Assessment (PLEA) tool

Hilary A T Caldwell; Alexandra Wilson; Drew Mitchell; Brian W Timmons

doi:10.1371/journal.pone.0230447

. 2020 Mar 17;15(3):e0230447. doi: 10.1371/journal.pone.0230447

Development of the Physical Literacy Environmental Assessment (PLEA) tool

Hilary A T Caldwell ^1,², Alexandra Wilson ³, Drew Mitchell ³, Brian W Timmons ^1,^2,^*

Editor: Catherine M Capio⁴

PMCID: PMC7077881 PMID: 32182272

Abstract

Physical literacy is becoming increasingly popular in sport, recreation, physical education and physical activity settings and programming. We developed an environmental assessment tool to evaluate the extent child and youth activity programs implement physical literacy across four domains: environment, programming, leaders and staff, and values and goals. The Physical Literacy Environmental Assessment (PLEA) tool was developed in 3 phases. First, the PLEA tool was created, content validity established, and physical literacy leaders were consulted. In the second phase, the PLEA tool was completed and tested by 83 child and youth programs and it was validated with individual physical literacy assessments completed on children in programs that scored in the top 10% and bottom 10% on the PLEA tool. Third, a National consultation was conducted, and program leaders provided feedback on the PLEA tool. In Phase 1, the PLEA tool was modified and shortened from 41 to 29 indicators, based on feedback from physical literacy content leaders. In Phase 2, participants in programs that scored in the top 10% had significantly higher scores on the upper body object control domain of PLAYfun (p = 0.018), and significantly higher PLAYself scores (p = 0.04) than participants in programs that scored in the bottom 10%. In Phase 3, over 80% of program leaders identified the PLEA tool was useful, and relevant to their areas of practice. The completed PLEA tool is a 20-item environmental assessment tool to evaluate to what degree child and youth programming implement physical literacy across four domains: environment, programming, leaders and staff, and values and goals. The application and validity of the PLEA tool beyond child and youth physical education, sport, dance and recreation sectors, such as in early years programs, should be investigated.

Introduction

Physical education, sports clubs, and recreation programming provide opportunities for children to engage in physical activity. According to Canadian parents and children, over 75% of 5- to 19-year-olds participate in organized physical activity or sports [1,2]. Almost 100% of Canadian elementary students take part in curricular physical education. In high school, 72% of students take part in physical education in Canada [2], as it becomes optional in all provinces except Manitoba [3]. Due to high exposure and participation rates in organized physical activity programs, it is important to consider the quality of this programming for children and youth. Physical education, sport, recreation and dance have become increasingly interested in the construct of physical literacy and how physical literacy can be embedded in their programming. In the Physical Literacy Consensus Statement, physical literacy is defined as “the motivation, confidence, physical competence, knowledge and understanding to value and take responsibility for engagement in physical activities for life”[4]. Physical literacy is more than physical activity participation. In most literature, physical literacy is conceptualized as motor competence, motivation to engage in physical activity, and valuing physical activity across the lifespan [5].

To date, research and practice about physical literacy assessment has focused on individual physical literacy assessments. Three Canadian physical literacy assessment instruments are available to assess an individual’s physical literacy [6–8]. Each of these assessment instruments vary in their target audiences, target scorers, assessment time, materials and assessment measures/ components [9]. While these assessment instruments focus on the individual, evaluation tools of how programs implement the principles of physical literacy are limited. Existing evaluation tools assess the programming, facilities and leaders of physical activity programs, but lack a specific focus on physical literacy and are applicable to one specific contexts, such as physical education [10–12]. These program evaluation tools were created by sector leaders in Canada [10–12], yet there is no published research about their development, validity or reliability. To our knowledge, a multi-sector program evaluation tool that assesses if programs support physical literacy in their environments, programming, leaders and staff, and values and goals does not exist.

A physical literacy program evaluation tool is needed to address this gap. It has been proposed that physical literacy can be a guiding framework for some interventions, and that these interventions incorporate activities scaled to a participant’s ability, provide mastery experiences for participants, provide opportunities for new activities, and that activities are enjoyable for participants [13]. Beyond this context, physical literacy is being applied and integrated into sport, physical education, dance, recreation and other physical activity programming. The PLEA Tool was developed for programs to assess how they incorporate physical literacy in their programming to address key elements of physical literacy, including motor competence, motivation and confidence to be active, and valuing lifelong physical activity [5]. The PLEA Tool assesses these elements across four domains of programs: environment, programming, leaders and staff, and values and goals.

The purpose of this study is to develop a physical literacy program evaluation tool using a physical literacy leader panel and consensus, local testing and construct validation, and a national consultation process. Across a range of sectors, the goal is to develop a tool that could assess how programs support and implement physical literacy, demonstrate accountability to stakeholders, and provide information for program leaders to adapt their programs.

Materials and methods

Overview

The Child Health & Exercise Medicine Program at McMaster University in Hamilton, ON, Canada partnered with the Partnership for Active Hamilton (formerly the Physical Literacy 4 All Committee), who proposed the idea for a physical literacy “friendliness” tool for a range of programs. The resultant Physical Literacy Environmental Assessment (PLEA) tool was developed from 2014–2018 in three phases. This study received ethics approval from the Hamilton Integrated Research Ethics Board, and local school boards, as necessary. Other participating organizations did not require additional ethics approval.

Phase 1: Content validation

The objective of Phase 1 was to establish content validity [14]. The Partnership for Active Hamilton local partners were asked to identify any existing tools related to physical literacy that could be used as a framework for the development of the PLEA tool. Partners included representation from recreation organizations, sport clubs, school boards, researchers and public health. Physical literacy leaders, including researchers and professionals as identified by the Partnership for Active Hamilton, were consulted to establish key concepts and indicators to be included. Partners were contacted by email and given this prompt to generate indicators:

“We would like your input as to what elements, information, or considerations of physical literacy do you feel are important and essential to sport- or physical activity-related programming for children and youth. In other words, what would a program have to include (that could be measured) to be considered physical literacy ‘friendly’?”

The first version of the PLEA tool was created and included the identified elements and information suggested.

Next, physical literacy content leaders were consulted regarding the content relevance of each indicator. Fifteen leaders, including physical literacy researchers and professionals, were contacted and asked to rate each indicator as extremely relevant, somewhat relevant, somewhat irrelevant, or totally irrelevant. They were also prompted for additional feedback: “you may also suggest we combine items or some other arrangement to result in the most logical checklist”. Lastly, the PLEA tool was distributed to 5 local program leaders, identified by convenience sampling with the assistance of the Partnership for Active Hamilton. The leaders were asked to complete the PLEA Tool about their child and youth physical activity programs and to provide general comments on the PLEA tool.

Phase 2: Construct validation

The objective of Phase 2 was to establish construct validity, which refers to whether or not a test legitimately describes what the test is intending to measure. One type of construct validity, convergent validity, assesses the degree that a measure is associated to another measure that assesses the same construct (e.g. physical literacy) [15]. The PLEA tool was further tested and validated in children’s physical activity, physical education, sport and recreation programs in Hamilton, ON.

Program recruitment

Local school boards, recreation departments, community organizations, sports clubs and camps were contacted by email or phone and invited to participate in the project. Once program leaders completed and returned a consent form, they were sent the PLEA tool to complete. Eligibility criteria included: 1) program operated within Hamilton; 2) program was physical activity, sport, physical education or movement based; 3) program was delivered to participants 7-to-18 years of age.

PLEA tool administration

Program leaders completed the PLEA tool and returned it to our research team by email, fax or it was collected by a member of our research team. Program leaders indicated if their programs met or did not meet each of the 29 indicators included in the PLEA Tool. In addition, program leaders were asked: “If checked, how can your program improve further in this indicator?” or “If not checked, what can your program do to meet this indicator? Comment on any barriers to meeting this indicator”. A PLEA tool score was generated for each program as the sum of indicators selected (maximum score = 29).

PLEA tool construct validation

Programs that scored in the highest 10% and lowest 10% on the PLEA tool were invited to participate in the construct validation phase. This phase included individual assessments of participant’s physical literacy. Research assistants visited each of these programs to distribute parent consent forms and a parent questionnaire. Research assistants returned to the programs 1–2 weeks later to conduct individual physical literacy assessments. Participants with parental consent were asked to complete an assent form.

Physical literacy assessments

Physical literacy was assessed with the Physical Literacy Assessment for Youth (PLAY) tools. The PLAY tools represent a series of workbooks designed to assess the multiple domains of physical literacy. The PLAY tools were designed for children 7 years and older. In combination, the PLAYfun, PLAYself and PLAYparent tools provide a multi-perspective assessment of a participant’s physical literacy [7].

PLAYfun has very good inter-rater reliability (0.87) and construct validity [16], examined by studying variations in scores due to age and sex. PLAYfun and an obstacle course of motor competence demonstrated moderate-to-large correlations, showing convergent validity [17]. Criterion validity has not been established for the PLAY tools because a gold standard for the measure of physical literacy has not been identified in the literature. PLAYfun is an assessment of 18 movement skills within five domains: running, locomotor, object control (upper body), object control (lower body) and balance, stability and body control and were administered with the same methods as Cairney et al. [16]. All PLAYfun assessments were administered and scored by the same investigator (HATC).

The participants then completed the PLAYself questionnaire, a 22-item, self-evaluation of a child’s perception of their own physical literacy [7]. The PLAYself questionnaire includes four subsections: environment, physical literacy self-description, relative rankings of literacies (literacy, numeracy, physical literacy) and fitness. The PLAYself score was calculated by adding up the totals of the subsections and dividing by 27, as outlined in the PLAYself workbook [7]. Parents completed the PLAYparent questionnaire to assess the parent’s perception of their child’s level of physical literacy, including questions about the child’s ability, confidence, and participation. PLAYparent provided researchers with an additional perspective from outside the child’s current activity program and identified positive and negative factors that affected the child’s ability to lead a healthy lifestyle. The PLAYparent is divided into five subsections: physical literacy visual analogue scale, cognitive domain, environment, motor competence (locomotor and object control) and fitness [7]. The PLAYparent questionnaire was scored by summing the parents responses and multiplying by 2.63 to give a total out of 150, as outlined in the PLAYparent workbook [7]. To date, no psychometric properties of the PLAYself or PLAYparent have been reported.

Statistical analyses

Statistical analyses were conducted using STATA Version 14SE for Mac (Statacorp, College Station, Texas). Significance was set at p<0.05 for all analyses. Descriptive summary statistics were computed, and continuous variables are expressed as means ± standard deviation. Normality of outcome variables (PLAYfun, PLAYself, and PLAYparent) was assessed with the Shaprio-Wilk Test and verified visually using histograms. Normality of the residuals of the models were assessed with the Shapiro-Wilk Test for Normality, Skewness/Kurtosis Test for Normality and visual inspection of P-P plots, Q-Q plots and histograms.

Mixed multi-level modelling was used to determine differences in PLAYfun, PLAYself and PLAYparent between programs that scored high versus low on the PLEA tool. Multi-level modeling was used to account for clustering of participants within the same programs. Models were adjusted for participant’s age and sex. High or low scores on the PLEA tool were treated as the fixed effects and program was treated as the random effect. An independent variance-covariance structure was used.

Effect sizes were also calculated using Cohen’s d for the PLAYfun, PLAYself and PLAYparent scores. Cohen’s d is calculated as the average of the programs that scored in the top 10% on the PLEA tool minus the average of the programs that scored in the bottom 10% on the PLEA tool divided by the standard deviation of the outcome variable for the sample. Cohen suggests d = 0.2 is a small effect size, d = 0.5 is a medium effective size and d = 0.8 is a large effect size [18].

Phase 3: National consultation phase

Administration of the PLEA tool

Phase 3 of PLEA tool development was an online National consultation, administered with Research Electronic Data Capture (REDCap). Participants read and completed an online consent form before viewing and completing the PLEA tool and then a feedback survey about the PLEA Tool.

Participants completed the updated 27-item PLEA tool by selecting if they met or did not meet each indicator. If they did not meet the indicator, the following follow-up questions were displayed: 1) what can your program do to meet this indicator?; and 2) What barriers prevent your program from meeting this indicator”. If they met the indicator, the following follow-up question was displayed: “how can your program improve further in this area?”. Participants then completed a short questionnaire about the usefulness and relevance of the PLEA tool (see Table 4 for questions).

Table 4. Summary of responses to PLEA Tool feedback questions.

	Response Options Responses, n (%)
Please indicate your overall level of satisfaction with the PLEA Tool as a way of helping you understand if and how your program is implementing the principles of physical literacy?	Not satisfied at all	Not satisfied	Satisfied	Very satisfied
	4 (1.9%)	34 (16.0%)	156 (73.2%)	19 (8.9%)
Is the PLEA Tool important to program planning and delivery?	Not important at all	Not important	Important	Very important
	6 (2.8%)	31 (14.6%)	147 (69.0%)	29 (13.6%)
Is the PLEA Tool important to program evaluation?	Not important at all	Not important	Important	Very important
	5 (2.3%)	32 (15.0%)	141 (66.2%)	35 (16.4%)
Is the PLEA Tool relevant to your area of practice?	Not relevant at all	Not relevant	Relevant	Very relevant
	5 (2.3%)	33 (15.5%)	126 (59.2%)	49 (23%)
How likely are you to use the PLEA Tool?	Very unlikely	Unlikely	Likely	Very Likely
	12 (5.5%)	47 (22.1%)	121 (56.8%)	33 (15.5%)

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Scores presented as n(%).

Participants and recruitment

The PLEA tool was distributed by email through relevant organizations (e.g., Sport for Life, national and provincial sport organizations, provincial physical education organizations, etc.). The goal was to reach coaches, teachers, public health professionals and physical activity leaders. Sport for Life assisted researchers with recruitment by contacting certain organizations. The researchers or Sport for Life personnel provided text and a survey link to organizations to include in their newsletter or email to members. The organizations then communicated their number of email list recipients or social media reach to researchers. The PLEA tool and questionnaire were communicated by email to approximately 45,055 recipients and shared on social media (Facebook and Twitter) with an estimated reach of 12,118 followers.

Thematic analysis

In Phase 3, responses to the follow-up questions (listed above) were coded and categorized by two independent reviewers (HC and SL). HC first reviewed all responses and developed categories for each question (e.g., program planning, leader training). SL was provided with the categories and asked to code all responses into one of the provided categories. The categories from both reviewers were reviewed. When both reviewers agreed on the same category/ categories for a response, no further discussion was needed. HC and SL discussed any conflicting categories and came to a consensus on the most appropriate category for each response. These responses were used to update the wording of relevant indictors.

Removal of indicators

To reduce redundancy in the PLEA tool, we a priori decided that if ≥90% of programs met an indicator, it was unlikely that the particular indicator was differentiating between programs. These indicators were removed from the PLEA tool.

Results

Phase 1

In Phase 1, the Partnership for Active Hamilton partners (listed above) and the authors of this research identified 12 related, existing tools, questionnaires and surveys (See S1 Appendix). The indicators proposed by physical literacy leaders were grouped into four themes to create the first version of the PLEA tool. The first version included 41 indicators. The environment theme had 13 indicators, the programming theme had 12 indicators, and the leaders and staff and values and goal themes each had 8 indicators. Three of the 15 (20%) invited content leaders responded.

The PLEA tool was modified based on the physical literacy content leader’s responses. In the environment domain, 2 indicators were removed as content leaders indicated they were both “somewhat irrelevant” to the questionnaire. The indicator “equipment is available for unstructured and structured play” was modified to be “space, facility and equipment are available for unstructured and structured play”. In the programming domain, 3 indicators were removed, 1 was added and one was modified. “Encourages participation in a wide variety of physical activities” was added based on content leader’s comments. In this domain, 2 indicators were removed as leaders indicated they were both “somewhat irrelevant” to the questionnaire. In the leaders and staff domain, 3 indicators were removed, 1 was added and 3 were modified. The indicator “program leaders are trained in effective teaching strategies” was replaced with “program leaders develop and execute plans for effective teaching strategies”. Three indicators were modified to be clearer to those using the PLEA tool. In the values and goals domain, 2 indicators were removed and 1 was modified. The indicator “emphasis is on learning and improvement” was modified to “emphasis is on learning and improvement and personal achievement”. Two indicators were removed in this domain as content leaders indicated they were both “somewhat irrelevant” to the questionnaire.

The five local program leaders that completed the updated PLEA tool did not suggest any further changes to the PLEA tool and this version was used in Phase 2.

Phase 2

In Phase 2, 135 organizations and programs in Hamilton were contacted to participate, 89 (66%) programs submitted consent forms and 83 (61%) programs completed the PLEA tool. Thirteen of these organizations completed the PLEA tool for multiple individual programs (e.g., different sites for an organization’s after-school programs). Programs that participated in Phase 2 included: 12 after-school programs, 2 dance programs, 3 fitness programs, 10 physical education curriculum delivery, 22 recreation programs, 6 school sport programs, and 28 sport programs. In total, 32 sports and physical activities participated in Phase 2. Summary scores for the PLEA Tool and each domain are included in Table 1. Fig 1 reports the frequency of PLEA scores.

Table 1. Summary of PLEA tool and PLAY tools scores from Phase 2.

	High Scoring Programs (n = 8)	Low Scoring Programs (n = 7)	All Programs (n = 83)
PLEA Tool Total Score	29.0 ± 0.0	17.7± 5.1 (7 to 23)	25.3 ± 3.9 (7 to 29)
Environment Domain	7.0 ± 0.0	5.1 ± 1.7 (3 to 7)	6.3 ± 1.1 (2 to 7)
Programming Domain	10.0 ± 0.0	6.3 ± 2.4 (2 to 10)	8.7 ± 1.6 (2 to 10)
Leaders and Staff Domain	6.0 ± 0.0	3.0 ± 2.2 (0 to 6)	5.3 ± 1.3 (0 to 6)
Values and Goals Domain	6.0 ± 0.0	3.3 ± 2.4 (0 to 6)	5.1 ± 1.4 (0 to 6)

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Scores are presented as mean ± SD (minimum to maximum score). All high scoring programs achieved a maximum score on the PLEA Tool (29 out of 29). High scoring programs represent programs that scored in the top 10% and low scoring programs represent programs that scored in the bottom 10% on the PLEA Tool.

Parents of 144 participants provided consent for participants to complete the construct validation phase. One of the high scoring programs was scheduled for assessments but due to changes in their facility availability, assessments with participants were not completed. As such, 8 high scoring programs and 7 low scoring programs participated in the validation phase. Seventy-two (70% female) participants were in the high scoring programs and 72 (60% female) in low scoring programs. The higher percentage of females is attributed to 2 female-only programs, and higher female enrollment in the remaining coeducational programs. Eight participants of the 144 who provided consent (5.5%) were absent for data collection and 136 participated in the PLAYfun assessment. Two participants did not complete all items on the PLAYfun assessment because they chose to terminate the assessment early or skip an item and 134 completed assessments were included in the analysis. One hundred and twenty-eight participants completed the PLAYself questionnaire and 97 parents completed the PLAYparent questionnaire. In the programs that scored in the top 10% of programs and the bottom 10% of programs on the PLEA tool, the ages of participants were 9.3 ± 1.5 years and 10.0 ± 1.6 years and, respectively.

The dependent variables were normally distributed: PLAYfun (p = 0.998), PLAYself (p = 0.128) and PLAYparent (p = 0.086). Based on inspection of a histogram, P-P plot and Q-Q plot, model residuals were normally distributed. Table 2 displays the outcomes between participants in programs that scored in the top 10% versus those in programs that scored in the 10% on the PLEA tool. The high scoring programs included: 4 after-school programs, 1 physical education class, 2 recreation programs and 2 sport programs while the low scoring programs included 1 physical education class, 3 recreation and 3 sport programs.

Table 2. Summary of individual physical literacy assessments from Phase 2.

Physical Literacy Measure	High Scoring Programs (n = 8)	Low Scoring Programs (n = 7)	95% confidence interval of the difference		p-value	Effect Size
Physical Literacy Measure	High Scoring Programs (n = 8)	Low Scoring Programs (n = 7)	Lower	Upper	p-value	Effect Size
PLAYfun Total	39.9 ± 9.1	40.0 ± 7.9	-0.1	4.4	0.064	0.02
PLAYfun Running	46.5 ± 9.4	46.1 ± 8.9	-1.3	4.6	0.261	-0.04
PLAYfun Locomotor	39.1 ± 11.5	40.4 ± 10.9	-2.7	6.3	0.434	0.12
PLAYfun Object Control (upper body)	47.9 ± 13.0	46.2 ± 11.8	0.8	8.2	0.018^*	0.20
PLAYfun Object Control (lower body)	36.7 ± 16.8	34.0 ± 17.2	-1.0	12.8	0.091	-0.16
PLAYfun Balance, Stability and Body Control	30.5 ± 14.6	32.8 ± 13.5	-4.6	4.5	0.983	0.16
PLAYself Total	76.2 ± 10.7	72.7 ± 12.3	0.2	8.1	0.04^*	-0.30
PLAYself Environment	71.6 ± 13.8	68.3 ± 14.3	-1.1	11.3	0.10	-0.23
PLAYself PL Self-Description	74.0 ± 14.6	70.2 ± 16.5	-0.8	10.2	0.10	-0.24
PLAYself Relative Ranking of Literacies	82.8 ± 11.5	77.7 ± 15.1	-1.1	12.0	0.10	-0.38
PLAYparent	127.2 ± 16.1	129.7 ± 17.0	-9.3	4.4	0.487	0.15

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All results were adjusted for age and sex. Physical literacy assessment results presented as raw scores. p-values represent the results of the mixed models conducted to assess differences in physical literacy measurements (PLAYfun, PLAYself and PLAYparent) between programs that scored in the top 10% and the bottom 10% on the PLEA Tool; PL: physical literacy

*p <0.05; Effect size is Cohen’s d.

Children in the programs that scored in the top 10% on the PLEA tool demonstrated significantly higher PLAYfun object control (upper body) skills and PLAYself scores than those in the programs that in the bottom 10% on the PLEA tool. There were no differences in the other outcome measures (PLAYparent, PLAYfun total and domain scores and other PLAYfun domain scores). The significant effect sizes were small to medium (Cohen’s d = 0.20 and -0.30).

Updates to PLEA tool following Phase 2

Based on feedback from participants in Phase 2, the PLEA tool was reviewed and updated. Following Phase 2, the question “How relevant is this indicator to your program?” was removed. One indicator was removed: “staff and leaders help motivate and encourage participants to try their best and achieve their goals” because 100% of participating programs responded “yes” for this indicator and it was determined that this indicator was not differentiating programs from one another. The language in several indicators was modified to ensure the indicator was as clear as possible. For example, “staff and leaders are trained in safety protocols” was modified to “staff and leaders are trained in safety protocols designed to minimize the risk of injury of participants”, to capture the importance of injury prevention and safety management. In addition, “program leaders develop and execute plans for effective teaching strategies” was changed to “program leaders are given time to develop and execute plans for effective teaching strategies” to capture that programs are providing time for leaders to develop plans, not only leaders who may use their own time to develop plans.

The first two indicators of the PLEA tool were combined into one indicator. The first indicator was “access to indoor opportunities for activity” and the second was “access to outdoor opportunities for activity”. This information was modified into one indicator: “access to more than one environment for activity”. After program leaders selected if they met or did not meet the indicator, they selected which environments were available for their program (ice/snow, land, water, air, indoors, outdoors). After all modifications at the end of Phase 2, the PLEA tool had 27 indicators.

Phase 3

Three hundred and thirty-three program leaders participated in Phase 3, including 213 leaders who completed the PLEA tool and all follow-up questions, and 120 program leaders who partially completed the PLEA tool and follow-up questions. Program leaders represented multiple sectors and multiple provinces and territories (see Table 3). The most common sectors represented were recreation, sports and education. Program leaders could indicate if they represented more than one sector. The greatest number of programs leaders were from Ontario, British Columbia and Alberta.

Table 3. Participant demographics.

What area (s) of practice do you represent? (can select more than one option)	N	%
Education	99	22.0
Recreation	115	25.6
Not-for-profit	91	20.3
Sports	105	23.4
Government Agency	17	3.8
Public Health	9	2.0
Research/ University	9	2.0
Other	4	0.9
Total	449	100
Where do you primarily live/ practice?	N	%
Alberta	39	18.3
British Columbia	41	19.7
Manitoba	7	3.3
New Brunswick	8	3.8
Newfoundland	2	0.9
Northwest Territories	1	0.5
Nova Scotia	19	8.9
Ontario	72	33.8
Prince Edward Island	6	2.8
Quebec	4	1.9
Saskatchewan	9	4.2
Yukon	2	0.9
International	2	0.9
Total	213	100

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For the thematic analysis, HC and SL were in agreement for 81.5% responses. Responses were categorized into 1–3 categories based on the comments provided. Seven (25.9%) indicators were removed from the PLEA tool because ≥90% of participants responded yes to those indicators. The seven indicators included: 1 environment domain indicator, 2 programming domain indicators, 1 leader and staff domain indicator and 3 values and goals indicators. Language changes were made to 14 indicators based on responses from participants. Details of these changes are included in S2 Appendix. The final PLEA tool now includes 20 indicators, including 5 environment domain indicators, 7 programming domain indicators, 5 leaders and staff indicators and 3 values and goals indicators.

Program leaders provided feedback on the PLEA tool (see Table 4). For example, 82% of program leaders were satisfied or very satisfied with the PLEA tool as a way of helping them understand if and how their programs implement the principles of physical literacy, and 72% of program leaders identified that they were likely or very likely to use the PLEA tool.

Discussion

Child and youth physical education, sport and recreation sectors are becoming increasingly interested in physical literacy and how it can be implemented in their programming. As a result, it is imperative that program leaders have the appropriate tools to evaluate how their programs support the development of physical literacy through people, programs, facilities and values. While some assessment tools are available to measure an individual’s physical literacy [6–8], no assessment tool existed that could evaluate how programs across multiple sectors implement elements of physical literacy. Therefore, we developed, validated, tested and evaluated the PLEA tool, an evaluation tool for child and youth physical education, sport, and physical activity programs to evaluate how programs support the development of physical literacy. The PLEA assessed programs across the 4 domains of environment, programming, leaders and staff, and values and goals. It includes indicators that reflect the elements most commonly identified in definitions of physical literacy: motor competence, motivation, confidence and knowledge to engage in lifelong physical activity [4,5].

The revised PLEA tool is a 20-item checklist of program indicators related to physical literacy within a program’s environment, programming, leaders and staff, and values and goals. For each indicator, a program leader indicates if their program currently meets or does not meet that indicator. Upon completion of the PLEA tool, program leaders are issued a score for each domain and for the overall PLEA tool. The PLEA tool was specifically designed for program evaluation; however, it would also be useful as a checklist when planning and delivering a physical activity-based program, including its environment, programming, leaders and staff, and values and goals.

Phase 1: PL content leaders consultation, pilot and content validation

In Phase 1, the PLEA Tool was created and modified based on physical literacy content leader’s opinions and piloted with local program leaders. The first version of the PLEA tool aimed to be as inclusive as possible to ensure important items were not excluded. The next step was to establish content validity of the indicators. It was necessary to determine the relevance of each item, and if items needed to be added, removed or modified. The physical literacy content leaders provided this critical feedback and these suggestions ensured the PLEA tool was asking about specific elements of physical literacy and that the indicators were relevant across multiple sectors. Content validity is based on judgement of experts and their view on the items included in the instrument. This method is common practice in developing or updating health measures [19]. The establishment of content validity gave us confidence that the PLEA tool was ready to move to Phase 2.

Phase 2: Construct validation

In Phase 2, construct validity was determined by assessing if the participants in programs that scored in the top 10% on the PLEA tool had higher individual physical literacy scores than participants in programs that scored in the bottom 10% on the PLEA tool. When developing the PLEA tool, a criterion, gold-standard measure did not previously exist. In the absence of a gold standard measure, construct validation can be carried out with two extreme groups [19], programs that scored in the top 10% versus bottom 10% on the PLEA tool. Our results showed that only one domain of PLAYfun (object control-upper body) and, PLAYself were higher in the participants in the programs who scored in the top 10% on the PLEA tool. The higher total PLAYself scores reported by participants in high scoring programs may be attributed to higher object control skills, which can influence perceived sport competence and lead to increased physical activity participation [20,21]. For PLAYself, the individual domain scores were all higher in participants who attended the high scoring programs, but the domain differences were not significant. There is evidence that children’s self-motivation, self-efficacy, perceived athletic/ sport competence and perceived self-worth are associated with their physical activity participation [21–24]. The PLAYparent scores did not differ between children attending high and low scoring programs, suggesting possible responder bias about parent’s perceptions of their children’s physical literacy or parent’s choice in selecting activity programs for their children. Phase 2 had limitations and challenges that help explain these results.

Eighty-three child and youth physical activity, sport, and physical education programs completed the PLEA tool, including 32 different activities and sports from multiple sectors. The range of participating programs and activities in Phase 2 of the development of the PLEA tool ensures the PLEA tool has external validity [25]. In this case, the programs that participated were similar to the target population of the PLEA tool, which includes child and youth sport, physical education and physical activity programs. All programs that scored in the top 10% on the PLEA tool identified that they met 100% of the indicators, suggesting possible responder bias and a ceiling effect. The scores were more variable for the bottom 10% of programs, and the scores ranged from 7 to 23 out of 29, with an average score of 17.7±5.1. The comparison of individual physical literacy between participants in the programs that scored in the top and bottom 10% on the PLEA Tool is a limitation as the physical literacy of participants in the middle is unknown. In addition, we had less than 10 programs in the high and scoring programs, limiting the generalizability of the results to all programs. Unfortunately, it was not feasible to complete additional assessments due to limitations in time and personnel.

There were also several challenges to the validation portion of Phase 2. For the validation phase, programs were invited if they scored in the top or bottom 10% on the PLEA Tool, and were not matched based on participant’s age or gender, or program’s sport or activity. Seven programs that scored in the bottom 10% on the PLEA tool that were invited to participate in the individual assessments were unable to participate. As such, a roll-down method was used, and the subsequent low scoring programs were invited to participate and do not represent the true lowest scores. It was not feasible for programs with short sessions to participate because the assessments could not be scheduled during the session. One program that scored in the top 10% on the PLEA tool agreed to take part in the individual assessments, but due to facility and scheduling changes, the assessments could not be completed. It was also not possible to complete the assessment at one water-based program that did not have adequate land space close by. Another limitation was the inability to control if children attended other physical activity programs, the quality of other programs or, how long and frequently they attended all physical activity programs.

Phase 3: National consultation

In Phase 3, 213 program leaders completed the PLEA tool and feedback questions, and 120 programs partially completed the PLEA tool and feedback questions. The partially completed questionnaires may be explained by the length of the PLEA tool in this phase. To collect qualitative data to potentially inform changes to the PLEA tool, each of the 27 indicators included follow-up questions, which would not be included in the final PLEA tool version. The added duration to complete that form of the PLEA tool may have deterred some program leaders. Over twenty participants commented that the PLEA tool was too long or suggested the follow-up questions be removed. These comments were considered, and the final version of the PLEA tool is now 20 indicators and there are no follow-up questions. The final version of the PLEA tool can now be completed in 10 to 15 minutes.

In Phase 3, program leaders almost equally represented education, recreation, not-for-profit organizations and sport. The PLEA tool is most relevant to program leaders to evaluate programs and make changes for future program sessions. The PLEA Tool may also be appropriate for public health professionals, government officials and researchers to evaluate and plan and evaluate physical activity programming and interventions. The question about where participants live and practice was at the end of the survey, so only the locations of participants who completed the entire PLEA Tool are known. Participation was limited in the territories. The largest representation of participants was from Ontario, Alberta and British Columbia. Only 4 participants from Quebec participated, and this may have been because the PLEA tool was not available in French. It was not feasible to translate the PLEA tool into French and then translate open-ended responses back to English for interpretation. Several national organizations were invited to circulate the PLEA tool to members (such as coaching groups). Many of these organization’s mandates outline that information circulated to members must be available in English and French. The final PLEA tool is translated into French. The broad representation of participants from multiple sectors is a strength of Phase 3.

In Phase 3, overall feedback was very positive. Over 80% of program leaders indicated that they were satisfied or very satisfied with the PLEA tool, that the PLEA tool was important or very important for program planning, program delivery, and program evaluation and, that it was relevant or very relevant to their areas of practice. Just over 70% of participants indicated they were likely to use the PLEA tool, and this may be based on the participant’s profession or role. For example, some participants may be interested in the PLEA Tool and it’s outcomes, but may not use the PLEA tool in their everyday work.

After Phase 2, only minor changes to the PLEA tool were made. Seven indicators (≥90% of programs met the indictor) were removed because they did not differentiate between high and low scoring programs. This change also supported the comments that the PLEA tool was too long. Additional feedback from participants was used to re-word several indicators to ensure they were clearer and that they captured the appropriate information about programs. The final PLEA tool is 20 indicators.

Conclusion

The PLEA tool assesses how programs across multiple sectors, such as physical education, recreation, and sport support the development of participant’s physical literacy across environment, programming, leaders and staff, and values and goals domains. The PLEA tool was designed, tested and modified through a rigorous, 3-phase development process with input from over 400 program leaders and stakeholders. Program leaders from across Canada confirmed the PLEA tool was relevant to their areas of practice and important for program planning, delivery and evaluation. In the future, translation into additional languages would be advantageous to increase the reach of the PLEA tool. Future studies should test the applicability and relevance of the PLEA tool programs that include participants of different age groups, such as early years (0- to 4-years old) or older adults. It would also be advantageous to assess the individual physical literacy of participants in programs that score across the entire spectrum of the PLEA Tool, not only the top and bottom 10%. Future work should also examine if the PLEA tool is sensitive enough to detect changes in a physical activity, physical education or sport program as a result of new or updated programming.

Supporting information

S1 Appendix. List of identified physical literacy related tools and questionnaires.

(DOCX)

Click here for additional data file.^{(23.1KB, docx)}

S2 Appendix. Changes to the PLEA tool following Phase 3.

(DOCX)

Click here for additional data file.^{(27.4KB, docx)}

S3 Appendix. PLEA national consultation feedback questions.

(DOCX)

Click here for additional data file.^{(24.2KB, docx)}

S4 Appendix. The PLEA tool.

(DOCX)

Click here for additional data file.^{(138.4KB, docx)}

Acknowledgments

The creation of the PLEA Tool would not have been possible without the ongoing support and collaborations with Sport for Life (Alex Wilson and Drew Mitchell), City of Hamilton Public Health Services (Alison Bochsler), the Partnership for Active Hamilton (formerly Hamilton Physical Literacy 4 All) and SportHamilton. Thank you to Logan Meyers, Bhanu Sharma, Alexis Bullock and Samantha Li from the Child Health & Exercise Medicine Program at McMaster University for their contributions to the project. Lastly, we would like to thank the many programs and their participants who contributed to the PLEA tool as participants in our research study.

Data Availability

All files are available from the McMaster University Dataverse database (https://doi.org/10.5683/SP2/ZFSSME.).

Funding Statement

Financial support from City of Hamilton Public Health Services, City of Hamilton Healthy Kids Community Challenge and RBC Learn to Play Grant. BWT is supported by a Tier II Canada Research Chair in Child Health and Exercise Medicine. HATC was supported by an Ontario Graduate Scholarship. Two of the authors, AW and DM, are employed by Sport for Life. Sport for Life provided support in the form of salaries for AW and DM, who contributed to the manuscript by assisting with data collection, decision to publish, and preparation and review of the manuscript. Sport for Life now hosts the PLEA Tool as a free, open access resource on their website with no intention of revenue generation.

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PLoS One. doi: 10.1371/journal.pone.0230447.r001

Decision Letter 0

Catherine M Capio

25 Sep 2019

PONE-D-19-20283

Development of the Physical Literacy Environmental Assessment (PLEA) Tool

PLOS ONE

Dear Dr. Timmons,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Both reviewers viewed the manuscript positively, and I also believe that the study presented here offers important contributions to physical literacy. There are major points raised by one reviewer, and I think that by addressing these, you could be improving the paper substantially.

We would appreciate receiving your revised manuscript by Nov 09 2019 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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We have obtained two reviews of your manuscript, and both were generally positive and that this work offers significant contributions to the field. There are a number of points raised by one reviewer, and I believe there is an opportunity to generate substantial improvements to the paper by addressing those issues.

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Reviewer #1: It was my pleasure to perform this review of Dr Timmons and colleagues work reporting on the development of the PLEA. This was an important piece of research which significantly adds to the growing literature base pertaining to Physical Literacy. The paper is well organised and written with a very transparent reporting of the findings and limitations of the research.

My recommendation is that the paper be published as is pending a couple of small clarifications and editorial corrections.

1. Phase 1 reads as almost a quasi Delphi process. Was a Delphi protocol followed in this expert consultation phases followed and if so, to what degree was fidelity of the Delphi maintained?

2. L628 & Table 2: I think you can safely reported this effect size as 'small to medium' but I also think you need to stipulate the ES measure being used in Table 2 (i.e. Cohen's d).

3. Given that Cohen's d is the ES statistic, please clarify why this was used ahead of other ES statistics (i.e. Hedge's g) given the relatively small sample.

Reviewer #2: Development of the physical literacy environmental assessment tool.

PONE-D-19-20283

Overall, I was impressed with the breadth of work completed to develop and characterize the measurement properties of a tool for environmental assessment of various contexts that can develop physical literacy in children and youth. I believe that this short form survey could provide useful into the future, by providing one of the first tools specific to physical literacy for the assessment of a facility and a program(s).

Major concerns

The rationale for illustrating the gradient of the PLAY tools measures to the PLEA tool based on top vs bottom 10% is weak. The sensitivity to other forms of categorizations (quintiles) is needed. Especially, if discrimative validity is to be established.

The lack of references to the definitional, theoretical and/or philosophical basis from which they undertook the development of the tool. The article identifies PL principles but no particular discussion of principles that were used to design the tool are mentioned.

There were some significant limitations that were not addressed, or were addressed inadequately.

It would appear to me, that all of these criticisms can be addressed through revision.

Competing interest

Depending upon the deployment of the tool, there could be a perceived competing interest in the support of an external organization that was involved in the RBC process (Sport for Life) – this should be disclosed whether it is real or “perceived” as indicated in the submission guidelines, especially since one of the authors represents that organization. Indeed line 639 indicates that this tool is provided by sportforlife.ca, and is copyright. As such, this agency can can accrue financial reward indirectly from this tool. This needs to be stated – even if the resource is free, the training now and in the future may not be and therefore be revenue generating – this is a competing interest or a commercial interest.

Ethical Issues

Was ethical approval of the youth programs outside of school (ie recreation) sought? Especially since school boards were?

Data availability

Authors specify there will be specific limitations on data access. What are the specific limitations requested? especially given the concerns related to competing interests above.

Abstract

1st line: The notion of PL being an “element” of programs as stipulated in the abstract is concerning. PL could be viewed and has been suggested to be both a transformative process, as a well as a state of a person. that can be utilized in the settings stipulated in first line of the abstract. I suggest that the authors consider revising the term element, or defend it’s use. Considerations made for PL? is this the intent? Certainly, the authors state later “in line with physical literacy principles”. What are these principles – you mean programs consistent with the definition of PL? as the authors stipulated in line 621. Consistency on this issue is important and the entire manuscript should be consistent (there are numerous occurrences).

2nd line: The authors state that the tool is to assess “programs” when in fact it assesses four domains (environment, program, people and values). I suggest that in order for clarity, they utilize the term “environmental assessment” (as in the title of the tool), to encompass both programs, places, people and values, perhaps by operationally defining in that way.

The middle section of the abstract describing the phases could have improved clarity with a substantial reduction in words, as there is repetition.

Last line: Application of the PLEA tool to other environments? This is not clear since the specific environments evaluated are not stated in the abstract. Revise. In fact, the authors conclude that there is broad generalizability. You can’t have it both ways. Please see my comments on generalizability.

Introduction

Line 35 – 75% participate – I would argue that is too strong – 75% have experienced – given how this number dramatically contrasts with objectively measured PA.

Line 36 – 100% enrolled in elementary with a “sharp decline” – the sharp decline is not necessarily due to enrolment but can also be due to access, and also provincial curriculum standards for provision. Please revise as the line implies it is student choice. And please support this statement with research citations specific to Canada and it’s provinces.

Line 38 – I think the authors are suggesting that - it is important to consider the quality of the programming since there is a high exposure to programming, but this conflicts with the dramatic reduction in participation (esp in sport) through adolescence, & this is consistent with measured PA reductions through these age groups. Is this the intention, as the wording does not convey this.

Line 40 - these sectors? Recreation has programs, schools offer curricula, and schools offer recess (not a program or curricular), and schools offer intramural sport and interscholastic sport opportunities, - the term program does not accurately describe these different contexts. I am not sure how to address this but educational settings do not use “programs” to describe curricular delivery.

Line 42 – this contrast between PA and PL is interesting, but the statement is pure conjecture of the authors and not written in a manner which befits existing definitions of PL. Specifically, the “ability to be active” is distinct from physical competence or movement competence of many definitions and the “willingness to engage in lifelong PA” is not specifically referring to motivation to move. Please revise. The authors use the IPLA definition in the PLEA tool appendix but don’t reference it here and should. And use words consistent with it.

43-45– “the tactics and strategies for movement”- is quite a stretch from contemporary definitions (IPLA, Canadian consensus statement (basically IPLA), SPORT AUS, etc) and very sport and PE specific. The article cited is not appropriate in this context, the authors should be referring to the four domains of PL (eg physical comp, affect, cognition.. ) consistent across major definitions. Revise. The PLEA tool appendix uses the IPLA definition (unreferenced) – you should be consistent.

Line 47 – not all tools are limited to children – as they can be used into adult hood – remove word “child”?

Line 49 – change to? – general evaluation tools assessing the programs, facilities and staff are limited ? But I agree they are limited, if not absent if you adopt a PL lens.

51 – “existing PL related program evaluation” suggest change to “existing context specific tools“. The basic High five (ref 10) was designed for the ECE space which is not necessarily limited to recreation! As a day care is not a recreation space. Revise.

Line 52 – endorsement – please cite the references which identify the endorsements or remove this statement. The second part is acceptable.

Line 54 – here the term “principles of PL” arises again. A consensus on principles is not published. Revise to state “consistent with” ? or reference the principles. I like the idea of principles but we would not necessarily agree on the list, so this statement adds confusion, and in the current wording implies there are accepted “principles”.

Line 56 – after school programs involve people to 20+, and this is beyond youth.

Line 56- Purpose – the purpose needs to be more succinct - develop tool using an expert panel and consensus, evaluate basic properties of the tools.

Line 56-58 The goal of “a tool to determine program effectiveness” is not addressed with the current methodology, nor the accountability portion. It is accepted that future uses could deploy the tool for such cases, but the ability of the tool to perform this task is not included. The COSMIN checklist is a tool for measurement properties that could be used to gauge how well the PLEA stands.

Line 62 – the use of the term “program leaders” is not inclusive of the groups and sectors that could use the tool and consistent with the sectors evaluated. Please revise.

Line 77 – please list the partners

Line 79 – please cite or list the experts by type (and how were they deemed experts?), as well as what process was used to secure them?

Line 81- the question shows a strong sport bias toward the questionnaire and this needs to be addressed in limitations and declared. The following terms were not used, explain why?

Recreation and PA

Performance arts and PA

Education and PA

ECE and PA

PE and PA

Parks and PA

This statement violates the inclusivity statement of the Canadian PL consensus statement as a result. Why were the other sectors (see below) not explicitly mentioned ? Line 98 provides a more comprehensive list compared to this statement. Please explain. Further these statements are inconsistent with lines line 103-104 (item 2) which also includes a new context “movement based” -please explain. These inconsistencies of sectors need to be sorted out.

Line 89-92 – The question didn’t permit the identification of items that were absent? The wording in the quotation reveals an implicit bias toward refinement only. Please explain.

Line 91 – was this a broad sampling (maximum variability sampling or convenient sampling or other? ) Please describe or list.

Line 88 – suggest that you list the experts by sector and title

Line 71- the role of RBC and Sport for Life needs to be stated here.

Line 75 – don’t need a definition of content validity. Remove. Throughout the document you define the basic statistical terms and this is not needed. Please revise.

Line 104 - aged 7 to 18 – it would be useful to report that although you were recruiting this range, the actual range of ages was? The mean SD values reported indicate a high proportion of children under 10.

114-115 – I get anxious when a comparison between bottom and top 10% are performed without a rationale for using this approach, and without a clear description of the data (histogram required for the scores). Why not tertiles, or quintiles? By choosing 10% this immediately limits the suitability of the tool to discern in the mid range. Please explain your rationale citing other works on measurement properties of a tool that used this approach. See further commentary below and above.

135-144 should be removed and refer to the construct validation paper of Cairney.

145 – 155 – good descriptions but would be handy to state what subscales you derived from the two tools. See comments below as well.

161 – remove “for normality”

161 – I would like to see a histogram for the PLEA scores.

167 – chronological age was used, so the developmental age was not – and therefore this would confound the results especially since a age spanned pubescent period- comment please.

Line 169 – “measure of the magnitude of the difference between the groups in standard deviation units” can be removed as cohens d is well known.

At Line 174 you could add the references indicating that a 0.4 to 0.6 is usually regarded a “clinically relevant” magnitude.

Lines 177-182 section requires substantial word reduction eg - a online survey (RedCap, manufacturer) was distributed nationally. Also it would be handy to have the survey in supplemental material.

Line 191 – this is not a national distribution methodology as stipulated by the examples in the list – how was a comprehensive distribution list created? This method could result in substantial responder biases. Please explain and defend.

How was the number of emails determined? Line 193? Was this predicted by membership or was this a known number? Normally ethical approval is required to obtain mailing lists.

Line 211- state number of partners and researchers, and list the number of each

Line 215 – why so low a response rate? Certainly, when one looks at 217 to 231 one sees a response bias that may have arisen from specific responders not being representative.

Line 238 – 240

What is a PE program? You mean the PE curricular delivery in school? Or do you mean all the movement possibilities at the school which are not limited to the “PE program”.

How did you derive 32 from the responses. Eg if PE was included it would have potentially included many sport components.

Were the dance programs the same form of dance? If not, then each type of dance is equivalent to a different sport. Did any of the after school programs involve dance? This section could be improved – I accept that there are a wide range of programs – but we would like to know – what is represented and what is missing? Further, what age ranges did these “programs” represent. Especially since the age range for the upper and lower were so low – relative to your recruitment strategy (7-18).

Table 1 –Since this was a ceiling effect for the high group – please comment on suitability of scale to differentiate good programs, and how to contend with the ceiling effect?

Also, responder bias is relevant here in that they are performing self assessment, so perhaps the high scoring respondents are biased in some way.

Line 242 _ I would like to see the histogram of the PLEA scores

Line 248 provide a list of the type of programs using the same headings as 238-240 for the low and high scorers. Provide a list of the targeted age ranges for these. Were they age biased?

Line 249

The recruitment method for PLAY tools needs to be clearly stated. Were all potential parents of participants in all the programs invited to participate? If so how many consents were sent out and how? Please estimate the number of participants in the 440+ programs.

Line 250 – does “high and low scoring programs” refer to the the top 10 and bottom ten?% If so did you only recruit in those two categories? So, to be clear, you did not have any PLAY data for the programs in the middle?

Like 251 – it looks like you have a sex biased sample. Please discuss.

Line 257 – it looks like you have a very narrow age range for the top ten and bottom ten %. Please discuss.

Line 264 – you didn’t state how you computed the play self scores – it appears you could have used the sum of the two first sections, or perhaps the first section and the second section separately? what did you use and why ? Further, the first section is enviormental the second PL self description, so did you check using the subscales in the analysis which appear to cover different aspects of PL? Specifically, It would be good to see if PLAY self environmental sub scale relates to the PLEA environments section.

Line 268 effect size was small to fair (0.36 isnt bad). Why report the NS cohens? Rather than the cohens for sig effects- this is odd?

Table 2 – it is consistent with other literature that the effects will be upper body control and perhaps lower body- so that data makes sense in relation to other work (you should cite referecnes that this is where we typically see effects in motor competence studies (Barnett reviews this). It is good to see that play self mirrors the upper body data (that is new!).

It is interesting that PLAY parent was inverted – perhaps showing a responder bias – parents that are sending kids to the low programs may be different in their assessment of their kids than parents sending kids to the high ones! This is plausible. Perceptual mismatch.

Table 2- of course using less than 10 subjects per group has major issues of both type 1 and 2 errors. Discuss. If you repeat the test using the bottom 25% versus top 25, or tertiles or qunitiles – same result?

Line 283 – this variation of text towards minimization of injury would reflect a potential “over” safety situation - comment

Table 3 – the list of areas of practice do not jive with the sectors stipulated in intro and methods – why not categorize using the same sector names identified in previous sections? Does it change interpretation? For instance, what is an eg of “not for profit” – big brothers and sisters ? And can you provide a breakdown of the sports please.

You should remove the two international respondents or change your methods accordingly.

You do comment on the low Quebec representation, but there are large numbers of English programs. This is also relevant since the consensus statement in French was not created until the next year after the English was released. The term was “savior faire physique” in Quebec prior, as well as in new Brunswick – this has relevance to how they answered item 1 in table 1 – which explicitly states PL. Also you had over 15 non-english responses – any indication of a language bias?

Line 302 – can you break down education into PE and other sub domains

Line 323 – development of PL through people, programs, facilities and values.

328 – the revised PLEA tool

328 – “ support development “ infers cause, you only have association so you need to state that a gradient was evident in PL measures with the PLEA tool

333 – you are limiting yourself to programming when it could also be used to modify facilities such as a play ground

335 – “modified based upon PL experts” – this is far too strong given three respondents and no means to assess PL expert status! I would suggest a change from the word expert throughout to another term.

At 338 – why was RASCH not employed?

352 – it is quite nice to see play self, a self perception, linked to this with a ok cohens for a small sample! I would emphasize the importance of this more

353 – it is not unsurprising that at this age the upper body were the differences this aligns well with intervention programs – please cite this literature (Barnett et al)

356 – you cant state “broad” here as you don’t have the denominator of programs available by environmental scan. Eg 32 sports of 58 olympic sports, and at least 35 other leisure time recreational sports means 32/93 is not overly representative! It certainly wasn’t narrow but broad I am not confident and is over-reaching with=out additional information – also the top 10 vs bottom ten was for a very narrow age range!!! comment

361 – contend with ceiling effect

365 – please explain how data was derived from assessments for the bottom ten given that you state that none of the 7 participated? How did you get 72 participants then?

369 – add the word NOT

370 – report how many places were not assessed that were water based? This would result in a bias – so discuss

391 – for the initial assessment it was performed only in English, future validation will be required to create a PLAY French tool. However 14 plus responded in French? From other provinces? Discuss if there responses showed language bias

Discussion – I have major issue with top 10 versus bottom 10 – normally in this field one would use tertiles or quintiles OR better yet show the gradient of scores over quintiles graphically! I require a strong rationale for this approach adopted – and a statement whether other means of categorization did or did not show the gradient

The references are rather thin. Particular the references to PL and the principles and how they informed the creation of the survey in the beginning. More references and discussion related to aspects/domains/definitions of PL and how the PLEA relates are necessary.

Biases based upon reviewers need to be addressed by pools of respondents. Did the education sector respond differently than sport.? The questions were modified in such a way that indicate that this bias may have existed (line 535).

Why not perform a CFA to see of the items load into the appropriate sections?

Line 629 to 630 – over 440

Line 629 to 630 – list all sectors not just selected sectors

Errors

Line 441 – institute - is spelled incorrectly

Line 496 and 453 – the quality sport tool is not named the same (revise) and is not attributed the same to the agencies.

Line 509 – missing )

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PLoS One. 2020 Mar 17;15(3):e0230447. doi: 10.1371/journal.pone.0230447.r002

Author response to Decision Letter 0

17 Jan 2020

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PLoS One. doi: 10.1371/journal.pone.0230447.r003

Decision Letter 1

Catherine M Capio

2 Mar 2020

Development of the Physical Literacy Environmental Assessment (PLEA) tool

PONE-D-19-20283R1

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Acceptance letter

Catherine M Capio

6 Mar 2020

PONE-D-19-20283R1

Development of the Physical Literacy Environmental Assessment (PLEA) tool

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Appendix. List of identified physical literacy related tools and questionnaires.

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S2 Appendix. Changes to the PLEA tool following Phase 3.

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S3 Appendix. PLEA national consultation feedback questions.

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S4 Appendix. The PLEA tool.

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Data Availability Statement

All files are available from the McMaster University Dataverse database (https://doi.org/10.5683/SP2/ZFSSME.).

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PERMALINK

Development of the Physical Literacy Environmental Assessment (PLEA) tool

Hilary A T Caldwell

Alexandra Wilson

Drew Mitchell

Brian W Timmons

Roles

Abstract

Introduction

Materials and methods

Overview

Phase 1: Content validation

Phase 2: Construct validation

Program recruitment

PLEA tool administration

PLEA tool construct validation

Physical literacy assessments

Statistical analyses

Phase 3: National consultation phase

Administration of the PLEA tool

Table 4. Summary of responses to PLEA Tool feedback questions.

Participants and recruitment

Thematic analysis

Removal of indicators

Results

Phase 1

Phase 2

Table 1. Summary of PLEA tool and PLAY tools scores from Phase 2.

Fig 1. Frequency distribution of PLEA scores from all programs.

Table 2. Summary of individual physical literacy assessments from Phase 2.

Updates to PLEA tool following Phase 2

Phase 3

Table 3. Participant demographics.

Discussion

Phase 1: PL content leaders consultation, pilot and content validation

Phase 2: Construct validation

Phase 3: National consultation

Conclusion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Catherine M Capio

Roles

Author response to Decision Letter 0

Decision Letter 1

Catherine M Capio

Roles

Acceptance letter

Catherine M Capio

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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