Navigation – Plan du site

AccueilNuméros16-4Adapting school physical activity...

Adapting school physical activity and health surveys for children with disabilities

Adapter les enquêtes sur l’activité physique et la santé à l’école pour les enfants handicapés
Kwok Ng, Piritta Asunta, Eija Kärnä et Pauli Rintala
p. 73-93

Résumés

L’activité physique (AP) et les comportements de santé des élèves des classes et des écoles d’éducation spéciale (SECS) sont largement sous-étudiés. Le but de cette étude est de rendre compte du processus d’adaptation à ce public des enquêtes réalisées en population générale pour en améliorer la faisabilité et la comparabilité.Une série d’études a été réalisée. 1. Adaptation et test de l’enquête dans le SECS, 2. Recueil des données de l’étude pilote, 3. Tests supplémentaires pour une version simplifiée, 4. Recueil national des données auprès des élèves du SECS. Les items du Washington Group Child Functioning Module (CFM) ont été progressivement améliorés. Des échelles visuelles analogiques et des items simplifiés ont été ajoutés. Le temps passé à répondre et la facilité de compréhension des questions ont été retenus comme critères de faisabilité de l’enquête. Près de la moitié des élèves (n=396/889) ont terminé la version simplifiée et ce, sur un temps de classe. De plus, les enseignants ont fait un retour positif sur la passation de l’enquête. Dans les enquêtes représentatives nationales, les instructions données doivent être claires. Les élèves du SECS peuvent avoir besoin d’aide pour comprendre les questions posées et des investigations supplémentaires sont nécessaires pour étudier les effets de cette aide sur la réalisation des enquêtes.

Haut de page

Texte intégral

1. Background

1The health of adolescents is a top research priority because these individuals have their entire lives ahead of them. In addition, young adolescence is a time where there are many physical, mental and social changes that influence the social determinants of health (Sawyer et al., 2018). Moreover, physical activity (PA) patterns and health behaviours are established for future years (Hayes et al., 2019; Telama et al., 2014). Survey data can reveal much about the aspects of the lives of young adolescents, especially from the individual point of view (Bickenbach, 2011). The perceptions and reported behaviours of young adolescents are vital in understanding the mechanisms for improving the health behaviours and habits (Viner et al., 2012). Studies, such as the Health Behaviour in School-aged Children: WHO Collaborative Cross-National study (HBSC) has carried this type of research for over 30 years, with over 45 countries involved in producing nationally representative data. Outputs have included changes in national policy (Currie & Alemán-Díaz, 2015), involvement of youth leadership programs (Frasquilho et al., 2016), and reporting with UNICEF (Langevin-Falcon et al., 2012) to name a few. However, studies like the HBSC have its own limitations in that not all pupils are represented. Like many countries, HBSC Canada reports over 17,000 children in its data collection, but does not include pupils in special schools, incarcerated youth, or home schooled children (Freeman, King & Pickett, 2015), or in Wales, over 29,000 pupils only from mainstream schools were included (Hewitt et al., 2019) limiting the global interpretation of health of young adolescents. Some attempts have been made to collect data in special school settings, such as in France during the 2013/14 study (Godeau et al., 2015; Pacoricona Alfaro et al., 2017). Although, due to differences in education systems, the same practices may be difficult to replicate in other countries.

2Historically, when current Finnish Basic Education Act (628/1998) was enacted, it did not support the implementation of inclusion in Finnish comprehensive schools. Against the act, young adolescents with special needs were placed in special education. In 2006, the Ministry of Education and Culture appointed a steering group that created a proposal for a long-term strategy for the development of special needs and inclusive education. The strategy for special needs and inclusive education emphasized the importance of the right of every young adolescent to attend the nearest mainstream school, i.e. a school where the individual would normally be assigned. In this way, pupils with special needs could create and maintain their social relationships with other peers in their neighbourhood. The strategy in pre-primary and basic education was published in 2007 (Ministry of Education, 2007) and put into practice in autumn 2010 leading to amendments in the Finnish Education Act 2010 (642/2010). The supplemented act laid a basis for the new era in the implementation of inclusive policy in Finnish comprehensive schools, where in 2011 a new three-tiered support model was introduced and consisted of 1. general support, 2. intensified support, and 3. special support for children with special educational needs (Finland, 2010).

3If general support is not enough, the pupil’s need for support would be evaluated, and a pedagogical assessment follows to regulate the intensified support services. If intensified support is not enough, a new and more extensive evaluation of the pupil’s needs is conducted, and an individual education plan prepared. However, intensified support needs to be used as the primary form of support before a decision on special support is made. The level of support is based on the pupils’ special educational needs, not on diagnosis. This means that pupils who are entitled to intensified or special support have a variety of needs. Mainstream class is the first alternative for providing support to pupils who need intensified or special support. Only when this is not feasible, the provision of special needs education in a special group, class or school is considered (Finland, 2010). Thus, pupils with intensified or special support needs are placed in special classrooms or special schools if it is absolutely necessary and beneficial for them. The new support model shifted the focus of special education to the earliest possible support for individuals to prevent the emergence and growth of problems during later years and permanent placement in special education. Since then, there has been a linear increase in the proportion of pupils needing intensified and special support, from 8 % in 2010 to 16 % in 2016 (Statistics Finland, 2017). These changes to the Finnish education system have led to a demand for adapting surveys for data collection in both mainstream and special educational setting purposes.

4Under article 31 of the Convention of the Rights of Persons with Disabilities, population-based statistics should be disaggregated by disability status (UN Expert Group, 2014). Over 175 countries have ratified the convention since 2008, and Finland ratified it in 2016 (Formin.Finland.fi, 2016). To be compliant with this convention, surveys like the HBSC need to be adapted so that pupils in special education are also represented in these studies. The scope of the HBSC study is to get an understanding of young adolescents’ health in their social context such as at home, school, with friends and family (Currie et al., 2014). An extension to the HBSC study in Finland is the Finnish school-aged PA study (F-SPA) where comprehensive questions on PA behaviours and its correlates are designed for monitoring purposes (Kokko et al., 2019). Results from both studies are used to inform policy at national and international levels. These surveys are meant to be representative of Finnish young adolescents, and to directly transfer the same surveys to special education classes and schools (SECS) is not advisable. This is because often pupils in SECS have difficulties in reading (Mayes, Calhoun & Crowell, 2000), can experience difficulties in choosing the right options when responding to Likert scales, and may be unable to comprehend complex questions (Cohen, Mannarino & Deblinger, 2012). Although overcoming these obstacles may be to simplify the language, making fewer response options and reduce the number of questions in the survey, adaptations to surveys still require development and testing to see the credibility of the data. Further examples include the use of sans serif font, illustration response scales, colours to represent differences in Likert scales or figures to represent behaviours when data were collected in special education classes or units (Sentenac, Pacoricona & Godeau, 2016).

5According to survey methodologies, there are five cognitive processes involved when individuals respond to questionnaires. These include, 1) Question interpretation, 2) Information retrieval, 3) Judgement formation, 4) Response formatting, and potentially 5) Response editing (Price et al., 2017). At each of these stages, reporting errors may take place. Therefore, survey designers need to reduce the errors by stabilising the conditions of the first two stages. For example, according to Youngman (1984), the use of dichotomous questions with yes or no responses can create difficulties in interpretation of the question (stage 1), but the processes in the remaining stages are less complex. However, positive bias to “yes” responses are likely to be reported and children in the SECS environment may be more likely to be sensitive to negative stimuli (Reaven, 2009). As such, Osgood, Suci & Tannenbaum (1957) also suggested that Likert-scale items may make stages 3 and 4 more stable, but can demand more cognitive processes than questions with dichotomous responses. This is an area that needs to be taken into consideration when the respondents have cognitive difficulties. Another dimension to consider in the development of survey items is the inclusion of visual analogue scales (VAS). VAS has been useful in research to help respondents to identify feelings or opinions (Shields et al., 2003), and would be beneficial to alleviate some of the challenges for survey completion among pupils in SECS.

6Although some longitudinal studies have included pupils that could be identified to have special educational needs, such as the “Growing up in Ireland” (Healy et al., 2017), and the “National Educational Panel Study” (Nusser & Heydrich, 2016), most cross-sectional studies including people with disabilities have been based on a proxy reporting for the individual (Schutz et al., 2008). The direct involvement of pupils with SECS is a fundamental right of the child (UNICEF, 1989) and can be fulfilled through self-reporting surveys, yet few designs for survey collection have allowed for that (Cappa, Petrowski & Njelesani, 2015).

7Lack of understanding in survey instruments may lead to missing data (Biau, Kernéis & Porcher, 2008), raising concerns about the validity of the data (Nusser & Heydrich, 2016). Surveys may also take up too much time for the pupils in SECS to complete (Harris & Luff, 2017). These issues can result in low comparability within and between populations (Hee et al., 2017), fewer possibilities to make statistical inferences (Biau, Kernéis & Porcher, 2008), and difficulties to advance the scientific knowledge of PA and health behaviours of pupils in SECS. Therefore, in this paper, we use four studies to describe the process of adaptation from general school PA and health behaviour surveys for completion of all young adolescents including pupils in SECS.

2. Methods and results

8The main aims of the study were to plan and carry out data collection with the purpose to allow pupils in SECS to complete a self-report PA and health behaviour survey. We reviewed the existing available self-report surveys and the protocols to go with the data collection and then proceeded with a series of studies that led to the adaptation, creation and implementation of three types of surveys. Based on these findings, one-size fits all survey approach would not be appropriate for pupils in SECS. Thus, we identified the shortest, smallest and simple language survey as ‘S’, the longest, largest survey as ‘L’, and the survey type with easy-to-read language and of normal length was labelled ‘M’ for middle. We also made a distinction between the younger (Y) and older (O) version to allow for the inclusion of questions intended only for the older respondents, namely 15-year-olds.

9We conducted a series of studies and collected data from pupils in SECS, who with their best of their abilities, completed self-report surveys (Figure 1). In many SECS, teacher assistants or other support staff are available, although these surveys were designed for self-reporting purposes by the pupils rather than completion via a proxy. The aim of the first study was to create the survey and test its usability. This was the start of the process and later led to the M and L surveys. The second study was to carry out a pilot study to test the feasibility of carrying out the M and L surveys. From the pilot study, we further refined the survey (third study) so that more pupils in SECS would be able to participate. We identified the need for a shorter survey (S), and in the fourth study, we conducted a national data collection. These studies were guided by the areas highlighted for survey development by Coolican (2004). These areas were threefold: population sample, mode of collection, and designing questions. The scientific ethics committee of the University of Jyväskylä, Finland approved each stage of the studies.

Figure 1. Flowchart of questionnaire development for SECS at each stage of the study

Figure 1. Flowchart of questionnaire development for SECS at each stage of the study

2.1. Study 1 – Usability of younger and older survey items

2.1.1. Modification of survey items

10Most of the preparation work took place during this phase of the overall study. The questionnaire from the HSBC study was the starting point of the questionnaire focus. In response to the Global Matrix 2.0 (Tremblay et al., 2016), and the need for more comparative data on children with disabilities in national level monitoring of PA, we merged the questions from F-SPA with HBSC surveys. The HBSC survey had 210 items from 121 questions. The F-SPA study had 266 items from 60 questions. There were some items that appeared in both studies, although still too many distinct questions for a single survey for SECS. The first task was to identify the overlapping questions and remove items that we could use for formulating a national survey for monitoring and comparability between F-SPA and HBSC.

11The 2018 HBSC survey consisted of three types of questions, international mandatory, international optional and national (Currie et al., 2014). We gave priority in the selection of items to national and international mandatory items, and excluded items that were not in our current study interests, for example, we removed items on intimate relationships, or deemed too difficult to complete, such as health literacy.

12A group of experts (authors and see acknowledgements) examined the merged questionnaire and discussed the direction and themes to be covered in the questionnaire. The discussions were guided by the principles in survey design (Coolican, 2004). These principles included; 1) Only ask what is needed (low number of questions); 2) Ensure the questions can be answered (appropriate question language); 3) Enable truthful answering to questions (appropriate response scales); and, 4) Reduce the number of items that cannot be refused or are unanswered (avoid difficult items). We reviewed questions one by one, and consensus was made to decide the items that would be included in the usability study. This led to 71 questions deemed important by the researchers from both surveys. There were two versions of the survey, one was for the older (O) group with additional questions on risk behaviours and another for the younger (Y) group that included the core survey questions.

13Another process was to examine the response categories for each item and make few modifications to allow for as much comparability between the items in the adapted and the original survey items. For many of the original items with scales greater than a 4-point scale, the number of response options were reduced to either three- or four-point scales, depending on whether the original response categories had a mid-point. We also created visual analogue scales (VAS) at the anchors and central point. For example, we modified the child functioning model (Loeb et al., 2018) by including a separate visual representation for each level of the response category to indicate severity. The four-point scale consisted of the following response options, “no difficulties,” “some difficulties,” “a lot of difficulties” and “cannot do at all.” A temperature gauge placed in the response options as an illustration of severity of difficulties that is similar to temperature gauges used seen in Finnish saunas for the first three options and a big cross for the “cannot do” (Figure 2).

Figure . Exemplar visual analogue scale options for child functioning module questions

Figure . Exemplar visual analogue scale options for child functioning module questions

14There were concerns that pupils in SECS have low levels of concentration and experience fatigue when completing long surveys. We adressed this by including two extra activities the pupils could do. At question 34 (the 57th item, halfway of the questionnaire), we gave the respondents the option to take a mental break from completing the survey by looking at a short comic strip. For the online version, if they clicked yes, then a short cartoon strip from Calvin and Hobbs appeared. If the response was no, the respondent skipped to the next question. At question 35 (item 58), we asked the respondents to report their current mood in completing the survey.

2.1.2. First phase testing survey Y and O versions

15We wanted to test the usability of the survey by examining which questions could be answered and making sure that the pupils could complete the survey within a set time (class duration). Printed versions of the online survey were available for completion, where written feedback about items was possible, as well as an online survey to test responses through the computer. A convenience sample of SEC in two schools in Central Finland was selected. Parents were informed by the school about the study and asked for consent. The surveys were completed anonymously and voluntarily. Although teachers were aware of the pupils responding to the items, responses from the surveys were stored confidentially as required by institutional ethical board procedures. Pupils could stop at any time. To test the usability for both Y and O versions of the survey, the classes consisted of a mixture of 13- and 15-year-olds.

16Teachers were present at the time of data collection, although the survey was administered by the research team. The researchers handed out the survey and gave instructions encouraging full participation in the survey as well as informed teachers and teacher assistants of their role during survey completion. The teaching staff was informed to encourage the pupils to answer for themselves and avoid giving the answer for the pupil. After the completion of the survey, the teachers and teacher assistants provided oral feedback on their perceptions of how survey completion went with particular reference to questions they thought were challenging for the pupils. The researchers recorded notes on items that pupils had difficulties to respond to. The written feedback from the pupils, oral feedback and researcher notes were used to inform the next development of the survey and prepare the administration guide.

2.1.3. Results from Study 1

17The modified survey consisted of 71 questions (163 items). There were 12 pupils who tested the paper version and another 8 pupils who completed the online version. All pupils completed the survey within the duration of a class period (i.e., 45 min). Data from 5 of the pupils were in the database, and due to technical problems, the other 3 disappeared from the server. The quickest recorded time was 12 min and the longest was 36 min with a median duration of 25 min. A mental break from the survey to look at the comic was not selected by any respondent. The respondents felt either happy or neutral at the halfway stage of the survey.

18The researchers discussed how to adopt VAS in the survey, particularly for the functional difficulties’ items. With the help of a research assistant (see acknowledgements), the three-option temperature gauge and a cross for the last option (Figure 1) were considered acceptable. The last option of a cross was clearer than a temperature gauge going to the very end, because, in theory, the maximum temperature can go beyond the temperature gauge, whereas a stop sign is the ultimate signal for a limit of functions. The general feedback from the other VAS used in the study was positive, although there was uncertainty about the impact on responses. As such, in the next round of testing we organised some cognitive testing of the VAS. Moreover, we made sure that pupils would be familiar with the images and utilised a well-established special education teacher resource site called Papunet (https://papunet.net). The image bank has over 30,000 images that illustrate many daily activities, expressions, and symbols for communicating with people with special educational needs. The license used for papunet images was CC-BY-NC-SA.

2.2. Study 2 – Pilot study to carry out the M and L surveys

2.2.1. Modifications for online survey

19Following the experiments in Study 1, the researchers met to discuss the pilot phase of the survey development. The survey was transferred solely to an online platform called Webropol and further tests were based there. One of the main differences between paper and online surveys is the online design layout (Ruiz et al., 2019). We made adjustments when converting the paper version to the online version by ensuring pupils are able to see the entire question and response options without having to adjust the displays, through scrolling (Healey, 2007). In addition, the software had automatic responsive styling feature (automatic adjustments based on computers, tablets, and phones). Some schools had laptops and others had tablets available. The survey worked best when it was in landscape mode and instructions were created to communicate this in the data collection protocol. In addition to the VAS, we introduced graphics from Papunet to depict the main action of a question or main icon to depict the characteristics of the item. For example, we used separate graphics referring to taking part in recess activities by sitting, walking, or playing sports.

20We sent the surveys to the national centre for easy-to-read (ETR) language to convert and simplify the language. The ETR centre recommended converting matrix type of questions where the first line is connected with each item, to use the entire sentences for each line. For example, the beginning of the CFM items starts with, “When compared with other people of the same age, I have difficulties with…” and then each function was listed as an individual item (i.e., seeing, if you wear glasses or contact lens, evaluate your vision with them, etc.). The ETR version was “Compare yourself to other people of the same age. Which things are easy or difficult for you?” Then the entire description of functional difficulties was written (i.e., I have difficulties in seeing, if you wear glasses, evaluate your vision with them, etc.). Details of the full conversion of the CFM can be found in Appendix Table 1. The consultation with the ETR centre led to the M-version survey and we had four different surveys; L-Y, L-O, M-Y, and M-O.

2.2.2. Second phase testing of M and L surveys

21A list of schools with special educational classes was obtained from the Finnish National Agency for Education and a convenience sample of schools in the south of Finland were invited to take part in the pilot study. In addition, an announcement was made on the nationwide special school Facebook group. The sample was collected based on the snowball effect that the Facebook group offered. Five schools responded and provided consent from the students’ parents to participate in the study. The school was offered incentives for carrying out the research by receiving free sports equipment. The inclusion criteria of selected classes were that students needed to be between the ages of 11- and 15-years old. The pupils completed the surveys voluntarily, whereby they could stop or withdraw at any point. The time of completion was made available from the online survey platform.

22Teachers provided informal feedback to the researchers about the teacher instruction sheet and the questions in the survey. Where possible, focus groups of pupils were set up to explore the face validity of the items in the survey. The notes from the focus group were generated with particular attention to some items previously identified from study 1 that had low face validity.

2.2.3. Results from Study 2

23A total of 70 pupils (age mean = 13.7y, SD = 1.8, boys = 64 %) from four schools completed the L-Y, M-Y, L-O and M-O surveys. The majority of pupils completed the Y versions (86 %). The median completion time was 16 min and a range between 5 min and 56 min. The lower quartile time was 7 min and upper quartile time was 33min. The M versions were completed by 12 pupils (age mean = 15.2y, SD = 1.2, boys = 75 %) and took more time to complete (median = 30min, range 19-44 min) than the L versions. There were slightly more completers of the M-Y (58 %) version than the M-O. The median completion time of the pupil surveys was 10min and a range of 5 min to 45 min. The lower quartile time was 8 min and upper quartile time was 15 min.

24Unfortunately, the teachers’ survey could only be linked back to less than a third of the pupils. Teachers experienced problems with the survey platform. At the time of data collection, there was an excessive lag time, and some data came back that it took over 10 hours to complete the survey, and others were missing. Despite contacting technical support, the server problems were so large that the technicians who host the survey platform were unable to fix it in time during the data collection period.

25Although the pupils completed all the questions in the designed time, some modifications were made to improve the survey. For example, some of the battery questions were very detailed and included many items to cover a single question topic, such as the sport enjoyment scale (Garn & Cothran, 2006). That scale alone has 21 items and we decided to remove it completely.

26We also reduced the number of items in certain areas of interest. For example, in the versions used for studies 1 and 2, there were questions about the type of activities the individuals do during recess time. Originally, there were two contexts, indoors and outdoors, with four types of activities, 1) sitting or standing, 2) walking, 3) taking part in sports, play or ball games, 4) taking part in organised activities with a supervisor, making eight items in two questions. Based on the feedback, the two contexts of indoors and outdoors were too demanding on the pupils to differentiate. As such, we decided to focus solely on recess time in general in a single question without reference to indoors or outdoors.

2.3. Study 3 – Further modifications and the S version

2.3.1. Preparation for S version

27Based on the feedback from study 2, it became apparent that there was a need to create a further adaptation to the survey prior to national data collection. Pupils with more challenging behaviours and intellectual impairments had difficulties to complete the survey and therefore the survey would work best with fewer items, and simplification of questions and response options. For example, all text was put into block capitals and the vision functioning item of the CFM was modified with a visual graphic of an eye to highlight the part of the body and the question modified to “DO YOU SEE OK?” with dichotomous response option of “YES” and “NO.” This version became the Short (S) version survey.

2.3.2. Testing phase for S survey

28The purpose of study 3 was to test the usability of the S-version of the survey among pupils with challenging behaviours and intellectual impairments with intensified and special support levels. The time it took to complete the survey were recorded through the online survey platform. In addition, we showed teachers a guide to be used to allocate the appropriate survey for their pupils, and we asked the teachers to give feedback about the guide. A convenience sample included three groups of pupils with intellectual impairments from the Central Finland area. Parents were informed of the study and gave permission for their child to complete survey within school hours. Pupils completed the surveys anonymously and voluntarily.

29Feedback from teachers of these pupils were also noted by the researchers. Informal discussions also took place with teachers to gauge the appropriateness of the questions. This was an essential step because it is likely that the completers of the S-version of the survey would need the most amount of support in completing the survey. All surveys were completed anonymously, but the involvement of teachers and teacher assistants in facilitating the completion of the survey may compromise the anonymous nature of the survey. This is particularly a sensitive aspect for items such as risk behaviours, bullying and other mental health related items.

2.3.3. Results from Study 3

30A total of 11 pupils from three groups with intellectual impairments completed the S-survey. According to the three-tier special education system, they were considered under the special support pillar and therefore be deemed suitable to complete the S-survey. The teachers gave instructions to the participants on how to write in the web address of the survey into a web browser and then informed the participants to complete the survey. The teachers and researchers were available to provide support for the participants during the completion of the survey through either reading out the item to the individual or, if necessary, clarify the question and response categories. The median completion time for the S version of the survey (including the time for teacher or researcher support) was 21 min with a range between 11 min and 41 min, and the interquartile range between 15 min and 25 min.

31During data collection, the researchers noticed teachers helped to explain the seven-day recall physical activity item by pointing to the weekly daily activity calendar and then asking the pupil to input their own response. A common practice in special education is to use a daily activity calendar on the board to inform the pupils of what the schedule looks like for the day and the days of the week. Even with this aide, the response scale was difficult for the pupils to differentiate the sensitivity of the categories. The teachers reported some of the participants were guessing rather than stating their own preference. Therefore, the researchers replaced the PA items for being physically active in three contexts; 1) being physically active during recess time, 2) out of school, and 3) on weekends. In addition, items on eating habits were split into two questions so that there were only two items per screen, rather than four. This led to a slight increase in the number of questions, although the number of items in the survey did not change between the pilot and the national data collection (study 4).

32Teachers reported the support given to the pupils was labour-intensive and suggested audio recordings of the survey questions may be a way to overcome low levels of literacy. Unfortunately, the survey platform did not support such innovated adaptation, thus it could not be tested nor adopted. Some other pupil feedback led to an increased size of response buttons on the online survey. After taking these considerations into the final version of the S-survey, there were 30 questions.

33Teachers gave their feedback about the usefulness of the teacher’s survey allocation guide. The teachers felt the information presented by medical diagnosis was not helpful. They explained that it was the typology of support level that makes a difference in comprehension and they could not base the decision solely on diagnosis. Based on this feedback, we refined the teacher’s guide to reflect the contemporary approaches used by teachers to identify the level of support the pupils required by illustrating the three level support pillars.

2.4. Study 4 - National data collection

34Study 4 was to administer the surveys through national data collection. To accommodate the different level of support needs of the pupils, there were five different versions of the SECS survey. For the M- and L-versions, there was the Y and O versions, and one S-version. Details of the domains covered in the different versions can be found in Table 1.

Table 1. Physical activity and health domains by each survey type

Table 1. Physical activity and health domains by each survey type

S – Short, M-Y – Medium Young, M-O – Medium Old, L-Y – Long Young, L-O – Long Old

2.4.1. Sampling of the national data collection

35There were two target groups, special education classes (SEC) and special education schools (SES). Schools were first recruited through the same sampling protocols used in the F-SPA (Kokko et al., 2019) and Finnish data collection of HBSC (Villberg & Tynjälä, 2006) studies. The F-SPA and HBSC samples are based on national representative school-aged children through two level cluster probability proportion to size. During recruitment of the F-SPA and HBSC studies, the school principals were asked to respond to the invitation with a choice to take part in either the F-SPA or HBSC study (both studies are coordinated at the University of Jyvaskyla). In the same invitation note, the school principals were asked to inform the F-SPA or HBSC study coordinator if the school had SEC. Once the coordinator received their acceptance and confirmed the school had SEC, further instructions were sent out to the school principals concerning the requirement for a randomly selected class for F-SPA or HBSC and SEC from each year group.

36The second target group were special education schools (SES). Initial contact was made with a list of schools of local and national (in Finnish these are called “Valteri”) SES and hospital schools (n=82, at the time of the study). There were 31 SES (38 % response rate at school level) and 37 SEC, although not all invited schools had SEC settings (Pikkupeura et al., 2020).

2.4.2. Contents of the teacher survey items

37Teachers were involved to give evidence of the feasibility to collect PA and health data through self-report surveys among pupils in SECS. Teachers from the SECS completed an online survey with topics such as, opinions about the teachers’ guide for survey allocation, students use of visual images, listing the difficulties the teachers thought the pupils had, and whether pupils followed up with the teachers to discuss any of the topics in the survey.

2.4.3. Feasibility analysis of Study 4

38Although data collected from study 4 were intended for national reporting, in this paper, we report only the feasibility data from the teachers and the time for survey completion by the pupils. The teachers’ feedback is reported descriptively. There are different contexts between SEC and SES therefore, it was important to test differences in time for completion. All versions of the surveys were completed online, and the platform stored the time the survey began and ended. We tested 95 % of the responses to examine the differences in time completion between the SEC and SES for each survey through Student t-tests. A range between 2.5 and 97.5 percentile for each survey was used so that outliers (n=19) were removed from this analysis. Average time and standard deviations were calculated and then Cohen’s d effect sizes (Cohen, 1988) were used to report the effect of the differences between SEC and SES.

2.4.4. Results from Study 4

39The majority of the respondents (n=889) completed the S-versions (n=396) followed by the M-version (n=345) and the least completed the L-version (n=148) (Table 2). Over two thirds of the respondents were males (69.0 %).

Table 2. Distribution of surveys across the education sector

Table 2. Distribution of surveys across the education sector

SEC – Special Educational Classes, SES – Special Educational Schools, S – Short, M-Y – Medium Young, M-O – Medium Old, L-Y – Long Young, L-O – Long Old.

40The median time to complete the survey ranged from 10 min (S-survey) to 21 min (L-survey). However, three pupils in SES took over an hour to complete the S-surveys (although removed from analysis). The time to complete the surveys were similar between the SEC and SES for all surveys except for the L-O version, and the effect size was large (p=0.03, d=0.53). The differences in mean time completion between the SEC and SES are presented in Table 3.

Table 3. Mean time of survey completion by setting with Cohen’s d effect sizes

Table 3. Mean time of survey completion by setting with Cohen’s d effect sizes

SEC – Special Educational Classes, SES – Special Educational Schools, SD – Standard Deviation, p – T-test significance p-value, d – Cohen’s d, S – Short, M-Y – Medium Young, M-O – Medium Old, L-Y – Long Young, L-O – Long Old.

2.4.5. Teacher results

41There were 40 teacher surveys completed from the 67 SECS. Two thirds (68 %) of these teachers reported the instructions for allocation of surveys were clear and easy. The remaining teachers (32 %) stated that allocation was mixed as it was easy for some pupils and difficult for other pupils. None reported the information was insufficient. A few teachers (n=7) reported none of the three surveys were suitable for some of the pupils. Another teacher reported difficulties to allocate the correct survey, because that a pupil belongs across the spectrum between L, M, and S.

42The majority of the teachers (53 %, n=21) reported pupils generally responded well to the surveys, and 40 % of teachers (n=16) felt the pupils were neutral to the survey. Only one teacher reported the pupils did not easily understand the content of the questions, with over half (53 %, n=21) reported the pupils partially understood, and the remaining (45 %, n=18) stated “yes” that the pupils easily understood the content. Almost all the teachers (95 %) felt that the visual images in the survey made it easier for the pupils to understand the items. The remaining 5 % could not comment on the visual images, and none reported the images were not helpful. Not many teachers (13 %, n=5) reported pupils followed up with the teachers by discussing about certain PA and health behaviours appearing on the survey, for example bullying.

3. Discussion

43The culmination of four studies to provide national PA and health data among adolescents in the SECS is the first step of the inclusive data disaggregation strategies in Finland. We started by identifying which areas of interest we could use through combining other national surveys such as the F-SPA (for PA behaviours) and HBSC (for health and health behaviours) so that comparisons could be made between the school contexts for pupils with and without special education support needs. However, prior to carrying out such analyses, preceding steps were identified as critical to report in this paper through pilot and feasibility studies.

44The reduction in the number of items from the F-SPA and HBSC studies led the creation of five different surveys that could be aligned with the three-tier support system in special education (Finland, 2010). Modifications to the text in the questions, the range of response options and use of VAS were the key adaptation principles we used after following the guidelines from Coolican (2004). Face validity is an important process for survey development during the creation of young adolescent self-report surveys (Stanton, Willis & Balanda, 2000) and we made sure that each phase was tested appropriately with pupils in SECS. This included the use of the National Easy-to-Read Language service, whereby their experience to simplify the language for all people to comprehend was tested and checked to keep the internal validity of the previous tested items. The multi-stakeholder approach is a common approach when collecting data in the SECS settings (Godeau et al., 2015). As a result of these procedures, the fundamental rights of the pupils in SECS on data disaggregation are one step closer to reality. It has been reported that it is preferable to use, as much as possible, existing instruments from other monitoring studies (Coster & Khetani, 2008), such as F-SPA and HBSC. In our example, we have reported the appropriateness and feasibility of the adapted survey through rigorous scientific methods.

45Most of the pupils were able to complete a long survey within a 45-minute class and the time varied between the individual abilities and the survey version. The only time difference we found between educational settings were for completers of the L-O version, whereby more time was spent by pupils in the SEC than SES. The anonymous nature of the data analysis made it difficult to investigate the reasons for these differences. One possible explanation is the differences between co-teachers’ roles in the SEC (more helping child) and SES (more helping teacher) as noted in earlier studies (Takala, Pirttimaa & Törmänen, 2009). Moreover, teachers in SES have more experiences of co-teaching than the SEC (Takala & Uusitalo-Malmivaara, 2012). The changes in the education system for the SECS and the response to interventions may be more intense at SES than the SEC levels (Björn et al., 2016). As such, it would be logical that pupils in the SEC require more time to answer questions than in SES. National intervention programmes to train teachers and professionals in the SEC setting (Äikäs & Kovanen, 2020) may lead to more time efficient work within the learning environment and this may lead to equal response times in future data collection rounds.

46Through studies 2, 3 and 4, we used visual analogue scales (VAS). The feedback from the respondents and the teachers gave the impression that VAS was an acceptable modification. The set of standardised images used in SECS from the Papunet resource site aided the comprehension of the questions. This was because the images from Papunet are regularly used to enable pupils in SECS to communicate with people on a daily basis. Shields and colleagues (2003) suggested the impact of VAS on the response options are generally positive and this may be something to consider in future surveys, especially when Likert type scales are in the question. As such, the VAS with visual images to support the questions is a positive enabler of understanding the everyday lives pupils in SECS (Reaven, 2009). However, further studies and different data collection methods are needed to find out how pupils understood the items and scales. Methodological considerations are particularly crucial when dealing with children with special needs to avoid the risk of exclusion from research (Dindar, Lindblom & Kärnä, 2017; Tager-Flusberg & Kasari, 2013). Both UN’s CRPD and the Convention on the Rights of the Child demand children and youth with disabilities as equal as everybody else in services provided by society (UNICEF, 1989). Moreover, the goal of the Non-Discrimination Act of 2015 in Finland was to prevent exclusion and expand the obligation to promote equality, including the education providers and scientific institutes responsible for research.

47The health and overall well-being of Finnish young adolescents has positively developed according to many indicators during the last decades (Inchley et al., 2020; Luopa et al., 2014). Good examples of these developments include decreased smoking and alcohol use, and also increased physical activity (Kalman et al., 2015; Luopa et al., 2014). Moreover, the increase of obesity seems to be stabilized (Inchley et al., 2020). However, health disparities still exist among Finnish children, and few studies have included young adolescents with disabilities to date. Since inequality begins early in life, prevention of risks should be emphasized during adolescence (Luopa et al., 2014), particularly at a time when the majority of life habits are being adopted (Hanson & Chen, 2007). Moreover, the knowledge base of PA behaviours of young adolescents with disabilities is scanty. Few studies about their PA levels and sport club participation (Ng et al., 2016; Tammelin et al., 2018) are available, although knowledge of the determinants of PA is lacking (Tremblay et al., 2016). Therefore, the survey adaptation process was necessary, not just for the sake of knowledge base advancement, but for the equality of young adolescents.

3.1. Study limitations

48There are some limitations to the study to note and could be areas to consider for future implementation of the study. Some population bias may exist throughout the testing as convenience samples were used for the first three pilot studies. Moreover, some pupils were unable to complete the S-version of the survey as it was still too difficult to complete. The context was from a Finnish education system and processes may be limited to Finland. In the fourth study, teachers in the schools administered the surveys and fidelity information on how well teachers and assistants followed the instructions as intended were lacking. Despite our efforts to make the survey as universally available as possible, not all survey instruments were completely accessible. For example, the survey was not converted to a platform whereby students with severe visual impairments could complete it unaided, as we believe this would have led to a separate protocol needed for a teacher assisted survey. The study was also limited to the handful of students who gave their opinions on the appropriateness of the VAS, and more testing on the effect of VAS on survey responses is needed.

4. Conclusions

49The inclusion of young adolescents with disabilities for the large-scale surveys of the whole age group such as F-SPA and HBSC studies must be guaranteed in the future. Through the four studies in this paper, we have demonstrated the processes involved in adapting PA and health behaviour surveys for pupils in SECS. Modification to surveys include the inclusion of visual representations of items and response scales (VAS), simplified language and the creation of different versions of the survey that fit within the special education system in Finland. Teachers play a crucial role in the administration of surveys and would require training and clear instructions for the implementation of data collection. At the national data collection, pupils in SECS completed L, M, and S versions of PA and health behaviours surveys within a standard lesson time. The adapted physical activity and health behaviour surveys developed in this project are exemplary and could be recommended to be implemented in other countries as well.

Haut de page

Bibliographie

Äikäs Aino & Riina Kovanen. 2020. Tuvet/#paraskoulu -osahankkeen loppuraportti moniammatillisen oppilashuoltotyön toimintamallin kehittämisestä ja käytöstä. [Final report: TUVET#bestschool project on the development and use of an operating model for multi-professional student care work]. University of Eastern Finland. Retrieved from: www.tuvet.fi/wp-content/uploads/sites/23/2020/12/3_TUVET_Toimintamalli_Raportti_julkinen.pdf.

Biau David Jean, Kernéis Solen & Raphaël Porcher. 2008. Statistics in brief: The importance of sample size in the planning and interpretation of medical research. Clinical Orthopaedics and Related Research, 466(9): 2282-8. doi:10.1007/s11999-008-0346-9.

Bickenbach Jerome E. 2011. Monitoring the united nation’s convention on the rights of persons with disabilities: Data and the international classification of functioning, disability and health. BMC Public Health, 11(S4): S8. doi:10.1186/1471-2458-11-S4-S8.

Björn Pia M., Aro Mikko T., Koponen Tuire K., Fuchs Lynn S. & Douglas H. Fuchs. 2016. The many faces of special education within RTI frameworks in the United States and Finland. Learning Disability Quarterly, 39(1): 58-66. doi:10.1177/0731948715594787.

Cappa Claudia, Petrowski Nicole & Janet Njelesani. 2015. Navigating the landscape of child disability measurement: A review of available data collection instruments. ALTER. European Journal of Disability Research/Revue européenne de recherche sur le handicap, 9(4): 317-30. doi:10.1016/j.alter.2015.08.001.

Cohen Jacob. 1988. Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Earlbaum Associates.

Cohen Judith A., Mannarino Anthony P. & Esther Deblinger. 2012. Trauma-focused CBT for children and adolescents: Treatment applications. New York, NY: Guilford Press.

Coolican Hugh. 2004. Research methods and statistics in psychology (4th ed.). London: Hodder & Stoughton.

Coster Wendy & Mary A. Khetani. 2008. Measuring participation of children with disabilities: Issues and challenges. Disability & Rehabilitation, 30(8): 639-48. doi:10.1080/09638280701400375.

Currie Candace & Aixa Y. Alemán-Díaz. 2015. Building knowledge on adolescent health: Reflections on the contribution of the health behaviour in school-aged children (HBSC) study. European Journal of Public Health, 25(Suppl. 2): 4-6. doi:10.1093/eurpub/ckv017.

Currie Candace, Inchley Jo C., Molcho Michal, Lenzi Michaela, Veselska Zuzana & Felicity Wild. 2014. Health behaviour in school-aged children (HBSC) study protocol: Background, methodology and mandatory items for the 2013/14 survey. Child and Adolescent Health Research Unit (CAHRU).

Dindar Katja, Lindblom Anne & Eija Kärnä. 2017. The construction of communicative (in)competence in autism: A focus on methodological decisions. Disability & Society, 32(6): 868-91. doi:10.1080/09687599.2017.1329709.

Finnish Basic education act, 628/1998. Amendments up to 1136/2010, FIN-1998-L-73915Cong. (2010). www.finlex.fi/en/laki/kaannokset/1998/en19980628.pdf.

Finnish Basic Education Act. 2010. Laki perusopetuslain muuttamisesta [Law on amending the Basic Education Act] (642/2010). www.finlex.fi/fi/laki/alkup/2010/20100642.

Formin.Finland.fi. 2016. Finland ratifies the convention on the rights of persons with disabilities and its optional protocol. Retrieved from: um.fi/press-releases/-/asset_publisher/ued5t2wDmr1C/content/suomi-sitoutui-vammaisten-henkiloiden-oikeuksista-tehtyyn-yleissopimukseen-ja-sen-valitusmenettelyyn/35732.

Frasquilho Diana, Ozer Emily J., Ozer Elizabeth M., Branquinho Cátia, Camacho Inês, Reis Marta et al. 2016. Dream teens: Adolescents-led participatory project in Portugal in the context of the economic recession. Health Promotion Practice, 19(1): 51-9. doi:10.1177/1524839916660679.

Freeman John G., King Matthew & William Pickett. 2015. Health behaviour in school-aged children (HBSC) in Canada: Focus on relationships. Ottawa, CA: Public Health Agency of Canada. Retrieved from: healthycanadians.gc.ca/publications/science-research-sciences-recherches/health-behaviour-children-canada-2015-comportements-sante-jeunes/index-eng.php.

Garn Alex C. & Donetta J. Cothran. 2006. The fun factor in physical education. Journal of Teaching in Physical Education, 25(3): 281-97. doi:10.1123/jtpe.25.3.281.

Godeau Emmanuelle, Sentenac Marianne, Parcoricona Alfaro Dibia Liz & Virginie Ehlinger. 2015. Élèves handicapés ou porteurs de maladies chroniques. Perception de leur vie et de leur bien-être au collège [Children with disabilities or chronic diseases. life and well-being perception in secondary schools]. Éducation & Formations, 88-89: 145-61. Retrieved from: www.education.gouv.fr/media/19715/download#:~:text=Le%20ressenti%20des%20%C3%A9l%C3%A8ves%20en,plus%20n%C3%A9gative%2C%20plus%20de%20redoublements.

Hanson Margaret D. & Edith Chen. 2007. Socioeconomic status and health behaviors in adolescence: A review of the literature. Journal of Behavioral Medicine, 30(3): 263. doi:10.1007/s10865-007-9098-3.

Harris Richard & Ian Luff. 2017. Addressing special educational needs and disability in the curriculum: History (2nd ed.). Abingdon, Oxon: Routledge.

Hayes Gráinne, Dowd Kieran P., MacDonncha Ciarán & Alan E. Donnelly. 2019. Tracking of physical activity and sedentary behavior from adolescence to young adulthood: A systematic literature review. Journal of Adolescent Health, 65(4): 446-54. doi:10.1016/j.jadohealth.2019.03.013.

Healey Benjamin. 2007. Drop downs and scroll mice: The effect of response option format and input mechanism employed on data quality in web surveys. Social Science Computer Review, 25(1): 111-28. doi:10.1177/0894439306293888.

Healy Sean, Haegele Justin A., Grenier Michelle & Jeanette M. Garcia. 2017. Physical activity, screen-time behavior, and obesity among 13-year olds in Ireland with and without autism spectrum disorder. Journal of Autism and Developmental Disorders, 47(1): 49-57. doi:10.1007/s10803-016-2920-4.

Hee Siew Wan, Willis Adrian, Tudur Smith Catrin, Day Simon, Miller Franck, Madan Jason et al. 2017. Does the low prevalence affect the sample size of interventional clinical trials of rare diseases? An analysis of data from the aggregate analysis of clinicaltrials.gov. Orphanet Journal of Rare Diseases, 12(1): 44. doi:10.1186/s13023-017-0597-1.

Hewitt Gillian, Anthony Rebecca, Moore Graham, Melendez-Torres G. J. & Simon Murphy. 2019. Student health and wellbeing in wales: Report of the 2017/18 health behaviour in school-aged children survey and school health research network student health and wellbeing survey. Cardiff, UK: Cardiff University. Retrieved from: gov.wales/student-health-and-well-being-survey-september-december-2017.

Inchley Jo, Currie Dorothy, Budisavlijevic Sanja, Torsheim Torbjørn, Jåstad Atle, Cosma Alina et al. 2020. Spotlight on adolescent health and well-being. findings from the 2017/2018 health behaviour in school-aged children (HBSC) survey in Europe and Canada. International report. Volume 2. Key data. Denmark. WHO Europe. Retrieved from: www.who.int/europe/publications/i/item/WHO-EURO-2020-5747-45512-65149.

Inchley Joanna C., Stevens Gonneke W. J. M., Samdal Oddrun & Dorothy B. Currie. 2020. Enhancing understanding of adolescent health and well-being: The health behaviour in school-aged children study. Journal of Adolescent Health, 66(6, Supplement): S3-S5. doi:10.1016/j.jadohealth.2020.03.014.

Kalman Michal, Inchley Jo, Sigmundová Dagmar, Iannotti Ronald J., Tynjälä Jorma A., Hamrik Zdenek et al. 2015. Secular trends in moderate-to-vigorous physical activity in 32 countries from 2002 to 2010: A cross-national perspective. European Journal of Public Health, 25(Suppl. 2): 37-40. doi:10.1093/eurpub/ckv024.

Kokko Sami, Martin Leena, Villberg Jari, Ng Kwok W. & Anette Mehtälä. 2019. Itsearvioitu liikunta-aktiivisuus, ruutuaika ja sosiaalinen media sekä liikkumisen seurantalaiteet ja -sovellukset [Self-reported physical activity, screen-time, social media and physical activity tracking devices]. In S. Kokko & L. Martin (eds). Lasten ja nuorten liikuntakäyttäytyminen suomessa: LIITU-tutkimuksen tuloksia 2018 [Finnish children and adolescents physical activity behaviours: Results of the F-SPA study 2018]: 15-26). Helsinki: Valtion Liikuntaneuvosto [Finnish Sports Council] 2019:1. Retrieved from: www.liikuntaneuvosto.fi/files/634/VLN_LIITU-raportti_web_final_30.1.2019.pdf.

Langevin-Falcon Catherine, Gebre-Egziabher Hirut, Groject Anna, Holmes Carol, Kenney Lisa, Koster Antonius et al. 2012. Progress for children: A report card for adolescents. New York: UNICEF. Retrieved from: data.unicef.org/resources/progress-for-children-a-report-card-on-adolescents/.

Loeb Mitchell, Mont Daniel, Cappa Claudia, De Palma Elena, Madans Jennifer & Roberta Crialesi. 2018. The development and testing of a module on child functioning for identifying children with disabilities on surveys. I. Background. Disability and Health Journal, 11(4): 495-501. doi:10.1016/j.dhjo.2018.06.005.

Luopa Paulina, Kivimäki Hanne, Matikka Anni, Vilkki Suvi, Jokela Jukka, Laukkarinen Essi & Reija Paananen. 2014. Nuorten hyvinvointi suomessa 2000-2013. Kouluterveyskyselyn tulokset. [Wellbeing of adolescents in Finland 2000-2013. The results of the school health promotion study]. ( N.25/2014). Helsinki: National Institute for Health and Welfare.

Mayes Susan D., Calhoun Susan L. & Errin W. Crowell. 2000. Learning disabilities and ADHD: Overlapping spectrum disorders. Journal of Learning Disabilities, 33(5): 417-24. doi:10.1177/002221940003300502.

Ministry of Education. 2007. Ministry of education (2007). Erityisopetuksen strategia [special education strategy]. Reports of the ministry of education, Finland 2007:47 Helsinki: Ministry of Education. (N.47). Helsinki: Ministry of Education. Retrieved from: julkaisut.valtioneuvosto.fi/bitstream/handle/10024/79498/tr47.pdf.

Ng Kwok W., Rintala Pauli, Tynjälä Jorma, Välimaa Raili, Villberg Jari, Kokko Sami & Lasse Kannas. 2016. Physical activity trends of Finnish adolescents with long-term illnesses or disabilities from 2002 to 2014. Journal of Physical Activity & Health, 13(8): 816-21. doi:10.1123/jpah.2015-0539.

Nusser Lena & Jana Heydrich. 2016. Validity of survey data of students with special educational needs: Results from the national educational panel study. In H. Blossfeld, J. von Maurice, M. Bayer & J. Skopek (eds). Methodological issues of longitudinal surveys: The example of the national educational panel study: 251-66. Wiesbaden: Springer Fachmedien Wiesbaden. doi:10.1007/978-3-658-11994-2_15.

Osgood Charles E., Suci George J. & Percy H. Tannenbaum. 1957. The measurement of meaning. Urbana: University of Illinois Press.

Pacoricona Alfaro Dibia L., Ehlinger Virginie, Spilka Stanislas, Ross Jim, Sentenac Mariane & Emmanuelle Godeau. 2017. Alcohol, tobacco and cannabis use: Do students with mild-intellectual disability mimic students in the general population? Research in Developmental Disabilities, 63: 118-31. doi.org/10.1016/j.ridd.2016.10.009.

Pikkupeura Vilma, Asunta Piritta, Villberg Jari & Pauli Rintala. 2020. Tukea tarvitsevien lasten vapaa-ajan liikunta-aktiivisuus, ohjattu liikunnan harrastaminen ja liikunnan esteet. [Children with support needs’ leisure time physical activity, organised sport practices and barriers]. Liikunta & Tiede, 57(1): 62-9.

Price Paul C., Jhangiani Rajiv S., Chiang I-Chant A., Leighton Dana C. & Carrie Cuttler. 2017. Research methods in psychology (3rd ed.). opentext.wsu.edu/carriecuttler/: Pressbooks.

Reaven Judith A. 2009. Children with high-functioning autism spectrum disorders and co-occurring anxiety symptoms: Implications for assessment and treatment. Journal for Specialists in Pediatric Nursing, 14(3): 192-9. doi:10.1111/j.1744-6155.2009.00197.x.

Ruiz Montze C., Watt Anthony P., Palacios Samper Natalia & Tony Morris. 2019. Cross validation of hard-copy and web-based formats of the sport imagery ability measure. International Journal of Sport and Exercise Psychology, 17(6): 647-58. doi:10.1080/1612197X.2018.1428209.

Sawyer Susan M., Azzopardi Peter S., Wickremarathne Dakshitha & George C. Patton. 2018. The age of adolescence. The Lancet Child & Adolescent Health, 2(3): 223-8. doi:10.1016/S2352-4642(18)30022-1.

Schutz Mary Ellen, Durkin Maureen S., Gottlieb Carissa, Maenner Matthew, Cappa Claudia & Edilberto Loaiza. 2008. Monitoring child disability in developing countries. Results from the multiple indicator cluster surveys. New York: UNICEF Division of Policy and Practice.

Sentenac Marianne, Pacoricona Dibia & Emmanuelle Godeau. 2016. Comment les élèves handicapés perçoivent-ils le collège? [How Do Disabled Students Perceive High School?]. Agora débats/jeunesses, 4(hors-série): 79-94. doi:10.3917/agora.hs01.0079.

Shields B. J., Palermo T. M., Powers J. D., Grewe S. D. & G. A. Smith. 2003. Predictors of a child’s ability to use a visual analogue scale. Child Care Health and Development, 29(4): 281-90. doi:10.1046/j.1365-2214.2003.00343.x.

Stanton Warren R., Willis Michelle & Kevin P. Balanda. 2000. Development of an instrument for monitoring adolescent health issues. Health Education Research, 15(2): 181-90. doi:10.1093/her/15.2.181

Statistics Finland. 2017. Special education 2016. Statistics Finland, Education, 11.

Tager-Flusberg Helen & Connie Kasari. 2013. Minimally verbal school-aged children with autism spectrum disorder: The neglected end of the spectrum. Autism Research, 6(6): 468-78. doi:10.1002/aur.1329.

Takala Marjatta, Pirttimaa Raija & Minna R. K. Törmänen. 2009. Inclusive special education: The role of special education teachers in Finland. British Journal of Special Education, 36(3): 162-72.

Takala Marjatta & Lotta Uusitalo-Malmivaara. 2012. A one-year study of the development of co-teaching in four Finnish schools. European Journal of Special Needs Education, 27(3): 373-90. doi:10.1080/08856257.2012.691233.

Tammelin Tuija, Kämppi Katariina, Aira Annaleena, Halme Nina, Husu Pauliina, Inkinen Virpi et al. 2018. Finland’s report card 2018: Physical activity for children and youth. Jyväskylä: LIKES Research Reports on Physical Activity and Health 350. Retrieved from: www.likes.fi/filebank/2800-Finland-reportcard2018-final-150.pdf.

Telama Risto, Yang Xiaolin, Leskinen Esko, Kankaanpää Anna, Hirvensalo Mirja, Tammelin Tuija et al. 2014. Tracking of physical activity from early children through youth into adulthood. Medicine & Science in Sports & Exercise, 46(5): 955-62. doi:10.1249/MSS.0000000000000181.

Tremblay Mark S., Barnes Joel D., González Silvia A., Katzmarzyk Peter T., Onywera Vincent O., Reilly John J. & Grant R. Tomkinson. 2016. Global Matrix 2.0: Report card grades on the physical activity of children and youth comparing 38 countries. Journal of Physical Activity and Health, 13(11): S343-S366. doi:10.1123/jpah.2016-0594.

UN Expert Group. 2014. Disability data and statistics, monitoring and evaluation: The way forward- a disability- inclusive agenda towards 2015 and beyond. New York: United Nations. Retrieved from: www.un.org/disabilities/documents/egm2014/EGM_FINAL_08102014.pdf.

UNICEF. 1989. Convention on the rights of the Child

Villberg Jari & Jorma Tynjälä. 2006. Documentation of the sampling process in Finland 2006. Jyväskylä: University of Jyväskylä.

Viner Russell M., Ozer Elizabeth M., Denny Simon, Marmot Michael, Resnick Michael, Fatusi Adesegun O. & Candace Currie. 2012. Adolescence and the social determinants of health. The Lancet, 379(9826): 1641-52. doi:10.1016/S0140-6736(12)60149-4.

Youngman M. B. 1984. Designing questionnaires. In J. Bell, T. Bush, A. Fox, J. Goodey & S. Goulding (eds), Conducting small scale investigations in education management: 156-76. London: Harper and Row.

Haut de page

Annexe

List of abbreviations

S – Short survey

M-Y – Medium young survey

M-O – Medium older survey

L-Y – Long young survey

L-O – Long older survey

CFM – Child Functioning Module

ETR – Easy-to-Read

F-SPA – Finnish School-aged Physical Activity study

HBSC – Health Behaviour in School-aged Children study

PA – Physical Activity

SECS – special education classes and schools

SEC – special educational classes

SES – special educational schools

VAS – Visual Analogue Scales

* * *

Table 4. Conversion of the child functioning module for the special education classes or schools survey and easy-to-read versions

Haut de page

Table des illustrations

Titre Figure 1. Flowchart of questionnaire development for SECS at each stage of the study
URL http://journals.openedition.org/alterjdr/docannexe/image/1594/img-1.png
Fichier image/png, 251k
Titre Figure . Exemplar visual analogue scale options for child functioning module questions
URL http://journals.openedition.org/alterjdr/docannexe/image/1594/img-2.png
Fichier image/png, 157k
Titre Table 1. Physical activity and health domains by each survey type
Légende S – Short, M-Y – Medium Young, M-O – Medium Old, L-Y – Long Young, L-O – Long Old
URL http://journals.openedition.org/alterjdr/docannexe/image/1594/img-3.png
Fichier image/png, 580k
Titre Table 2. Distribution of surveys across the education sector
Légende SEC – Special Educational Classes, SES – Special Educational Schools, S – Short, M-Y – Medium Young, M-O – Medium Old, L-Y – Long Young, L-O – Long Old.
URL http://journals.openedition.org/alterjdr/docannexe/image/1594/img-4.png
Fichier image/png, 110k
Titre Table 3. Mean time of survey completion by setting with Cohen’s d effect sizes
Légende SEC – Special Educational Classes, SES – Special Educational Schools, SD – Standard Deviation, p – T-test significance p-value, d – Cohen’s d, S – Short, M-Y – Medium Young, M-O – Medium Old, L-Y – Long Young, L-O – Long Old.
URL http://journals.openedition.org/alterjdr/docannexe/image/1594/img-5.png
Fichier image/png, 168k
URL http://journals.openedition.org/alterjdr/docannexe/image/1594/img-6.png
Fichier image/png, 1,2M
Haut de page

Pour citer cet article

Référence papier

Kwok Ng, Piritta Asunta, Eija Kärnä et Pauli Rintala, « Adapting school physical activity and health surveys for children with disabilities »Alter, 16-4 | 2022, 73-93.

Référence électronique

Kwok Ng, Piritta Asunta, Eija Kärnä et Pauli Rintala, « Adapting school physical activity and health surveys for children with disabilities »Alter [En ligne], 16-4 | 2022, mis en ligne le 23 décembre 2022, consulté le 22 avril 2025. URL : http://journals.openedition.org/alterjdr/1594 ; DOI : https://doi.org/10.4000/9ifh

Haut de page

Auteurs

Kwok Ng

School of Educational Sciences and Psychology, University of Eastern Finland, Joensuu, Finland/Department of Physical Education and Sport Sciences, University of Limerick, Limerick, Ireland
kwok.ng[at]uef.fi

Piritta Asunta

Jamk University of Applied Sciences, Likes, Jyväskylä, Finland
piritta.asunta[at]jamk.fi

Eija Kärnä

School of Educational Sciences and Psychology, University of Eastern Finland, Joensuu, Finland
eija.karna[at]uef.fi

Pauli Rintala

Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
pauli.rintala[at]jyu.fi

Haut de page

Droits d’auteur

CC-BY-NC-ND-4.0

Le texte seul est utilisable sous licence CC BY-NC-ND 4.0. Les autres éléments (illustrations, fichiers annexes importés) sont « Tous droits réservés », sauf mention contraire.

Haut de page
Rechercher dans OpenEdition Search

Vous allez être redirigé vers OpenEdition Search