Study design
The Finnish Late Adolescents Physical Activity (LAPA) study is a national monitoring physical activity study of late teenagers. It is the extension to the Finnish School-age Physical Activity (F-SPA) study that included 7-, 9-, 11-, 13-, and 15-year olds to late adolescents aged between 16 and 19 years old. The design of the sampling and administration of F-SPA and LAPA were similar. In short, the sampling strategy was based on national representative sample of general upper secondary school and vocational colleges through probability proportion to size, where clusters were set at macro regions of Finland, notably Metropolitan, South, Central and North. A complex sample design included the allocation of survey responses from general upper secondary schools as well as vocational colleges. For the 2019–2020 academic year, there were a total of 105,200 students attended upper general school and 168,000 students attended initial vocational education [15]. The planned data collection phase in spring 2020 commenced on the 9th March. As the emergency powers act came into force on the 17th March 2020, with schools closed on the 18th March, the research team rapidly updated the items in the LAPA study and included items that focused on relationships between PA behaviour and COVID-19 in the LAPA-C19 study. Data from the LAPA-C19 study were collected between 6th April – 5th June 2020. The LAPA study has a split sample design, so that traditional monitoring would continue with the original LAPA study in both Finnish (LAPA) and Swedish (LAPA-S) speaking schools including the collection of week-long accelerometer data. Data from late adolescents in general upper secondary school who completed LAPA-C19, LAPA, and LAPA-S were combined for the purpose of this study (Fig. 1). Contact with late adolescents in vocational colleges were an administrative challenge and for that reason, data from vocational colleagues were removed from the data analyses to avoid biasing the representativeness of the sample. Furthermore, accelerometer data was removed from the data set due to complications to collect representative sample that followed from the COVID-19 restrictions, leaving representative general upper secondary school self-report data in this study.
All surveys were completed anonymously and voluntarily through an online survey. In Finland, late adolescents over the age of 16 have the legal right to consent for themselves to take part in the study. Permission was obtained by all participants in this study. LAPA study was approved by the University of Jyväskylä research ethics committee.
Survey items
Background variables
Age was calculated from respondents input of their day, month and year of birth in relation to the date of survey completion. Age categories were created based on the nearest whole year for 16y, 17y, 18y olds. Disabilities were calculated through the self-reported version of the child functioning module of the Washington group on disability studies [23]. There are 11 items with a four-point scale on core functions for adolescents namely, seeing, hearing, speaking, walking, concentrating, learning, self-care, remembering, change of routines, getting friends, controlling own behaviour. A first past the post system for difficulties at the level of ‘a lot of difficulty’ was used to determine estimates for people with disabilities [24]. Items in relation to social economic status (SES) were determined by two items on parent’s highest level of education and the family finance level. Place of residence was a single item, those who live in a city was coded as urban, and those who live outside of the city were coded as rural.
Physical activity variables
A definition of physical activity intensity was included at the beginning of the survey, followed by a single item measure the number of days in the past week where the individual had participated in at least 60 min of moderate to vigorous physical activity (MVPA). This item has been used extensively for national monitoring purposes [25] with good validity against accelerometers [26] and acceptable test-retest reliability [27]. The days were grouped into 0–2 days, 3–4 days, 5–6 days, and 7 days, as 4 categories have meaningful interpretations [28] as well as providing more insight into the ‘every move counts’ connection from the updated WHO PA guidelines [29]. An additional definition of vigorous intensity PA (VPA) followed and a single question on the number days in a usual week the individual does VPA. This variable dichotomised into less than 3 days and more than 3 days as part of the PA guidelines for strengthen exercises [29].
Frequency of 21 physical activities carried out during a week was based on a frequency scale from Never to daily. Items were selected from Finnish expert group and included; muscular fitness training, body care (i.e. stretching/yoga), indoor aerobic, dance, gymnastics, hula hoops, cycling, skating or scootering, jogging, walking or Nordic walking, hiking, orienteering, geocatching, frisbee golf, stair running, walking the dog, skiing or ice skating, nature-based exercises, indoor e-games, outdoor e-games, and other. Respondents who reported ‘other’, wrote in an open-ended response box to describe what was the activity they did during lockdown. These items were cross-checked with the 21 items to identify extra activities that were not on the 21 activities already listed. This resulted in four more activities, ball sports, martial arts, horse riding and golf. Recoding of responses values were never, less than weekly or weekly as 0, and more frequently or daily as 1. The activities were then grouped into no PA, indoor only, outdoor only, and both indoor and outdoor PA.
A separate item was used to measure the extent of change in PA as a result of the emergency measures. The response option was a five-point scale from Much less to Much more with the midpoint [3] as the same. There has not been time to validate the measure, although similarly worded items have been used in a variety of published COVID-19 related papers [30].
Physical education
Students were asked if they received PE instruction during lockdown through remote methods. If they reported yes, the respondents were asked their level of agreement (1 completely agree – 4 completely disagree) on whether they completed all the PE tasks during the day. Students who reported ‘completely agree’ were grouped as ‘high task’, all others were grouped as ‘low task’, and students without any remote PE were coded as ‘no remote PE’ as the reference category.
Sport clubs
Three groups were created based on the combination of two items, 1. Membership of sport clubs before lockdown, and 2) Level of competitive aspiration. Aspirations for competitive sports for youth and adults were combined into a group called competitive member. Responses of membership but no competitive aspiration were grouped into recreational member and the final and reference group were the responses of no sport club member.
Statistical analyses
Chi-square test of independence on the proportions for the background variables were carried out to confirm analyses for pooled data from the survey types (LAPA-C19, LAPA, LAPA-S) as well as segmentation analysis (SES and PE) that could be generalised for the rest of the sample. When proportions of MVPA did not differ between the extra responses from LAPA-C19 with the rest of the sample (p > .05), the combined data were consisted sufficiently general for the items on PE and SES. Multinominal logistic analyses of the background variables and correlates were performed to identify the associations with different proportions of MVPA categories (3–4 days, 5–6 days and 7 days) to the reference category of 0–2 days.
A decision tree analyses approach through Chi-square Automatic Interaction Detector (CHAID) analysis was used for testing the probability of 0–2 days, 3–4 days, 5–6 days or 7 days of MVPA based on involvement in sport clubs, competitive aspiration and perceptions of change to MVPA. CHAID analysis can determine the probability of each possible node for different frequencies of MVPA.
To estimate the correlates of change in PA, univariate analysis of variance was conducted where change of MVPA was the independent variable and gender, age, disability, place of living, SES, PE, types of activity, frequency of MVPA, VPA and sport club aspirations as dependent variables. IBM SPSS 27.0 with 2-tailed tests and 95% confidence intervals was used for all analyses.