Journal of Adolescence 1991, 14, 305-321
Leisure activities of adolescent school students: predictors of participation and interest ALISON
F. GARTON*
AND CHRIS
PRATT-/-
Frequency of participation and levels of interest in more than 60 leisure pursuits were measured via a questionnaire administered to 1248 adolescent high school students. The relationship between participation and levels of interest was measured by correlation as well as by asking the students to nominate up to three activities they would like to participate in but cannot and to indicate the reason for their non-participation. Factor analyses reduced the Participation and Interest items to six factors each. Multiple regressions were then conducted on the derived factor-score variables. Sex was the major predictor of participation in sports and vocational activities and of interest in sporting and gregarious activities. Age, school location, ethnicity and SES were lesser predictors for groups of activities such as the social and outdoor pursuits. The results are discussed in terms of the theoretical and practical implications of the relationship between participation and interest as well as the prediction of participation and interest levels by developmental and social factors.
INTRODUCTION
An examination of leisure pursuits can provide an important key to an understanding of the composition and extent of a developing adolescent’s world. If we study what adolescents do in their spare time, we can gain a greater insight into the organization of their social world. Further, we can use the information to study if and how individual needs are being fulfilled by the available and accessible leisure activities. The active participation in worthwhile leisure pursuits has been proposed to be important for healthy psychological development (Hendry, 1983). Should the available leisure activities not fulfil the adolescent’s social and individual requirements either by external (accessibility) or internal (interest) constraints, then progress through adolescence may be unsatisfactory and unhealthy psychologically. “Reprints requests should be addressed Psychologist, Gascoyne House, Graylands Australia 6010, Australia. tliniversky of Western Australia. 0140-1971/91/030305+17
$03.00/0
0
to Dr Alison F. Garton, Senior Research Hospital, Private Bag 1, Claremont, Western
1991 The
Association
for the Psychiatric
Study
of Adolescents
306
A. F. GARTON AND C. PRATT
Although there is general concern over the increased leisure time available to various sections of society, for example, the retired, the unemployed and those working reduced or part-time hours, the focus of this study is on adolescents who are still at school. These adolescents form a homogeneous group who have a commitment to school during certain hours five days a week and have limited time and money available for leisure. Some previous research (e.g. Connell, Stroobant, Sinclair, Connell and Rogers, 1975) has compared adolescents at school with those in or out of work. However, with a heterogeneous group of adolescents, it is more difficult to make firm claims and generalizations (Garton and Cartmel, 1986). By restricting the study to only school students, it is hoped to capture more accurately the leisure pursuits and interests of a large group of adolescents who share a number of important characteristics and limitations. Further, it is directly comparable with earlier research which examined the leisure activities of adolescents, some descriptive and applied (e.g. Poole, 1983; Poole and Juchnowski, 1976; 1977), some more measurement-based and analytic (Garton and Pratt, 1987) and some cross-cultural (Garton, Takimoto, Pratt and Hayashi, 1990). Garton and Pratt (1987) noted that while participation and interest were indeed highly correlated and adolescents were interested in what they participated in and not interested in activities they did not participate in, it was not clear to what extent interest developed as a result of participation. Therefore, the adolescents in this present study were provided with the opportunity to stipulate activities in which they would like to participate but could not (as an indicator of “interest”) and to provide a reason why they were unable to participate. In this way, it would be possible to gauge whether activities were available but non-participation was due to lack of time or other commitments or whether facilities and/or opportunities for participation did not exist. Thus, the first aim of the study was to ascertain the relationship between participation in activities and interest and to determine to what extent interest (measured by a wish for participation) was related to external constraints or pressures. The second aim of the study was to examine some of the predictors of participation and interest in leisure activities. Five independent variables were chosen and these were sex, age, school location, ethnicity and socio-economic status. Regression analyses were conducted using all five variables to establish their relative influences on the selection of leisure activities. It was hypothesized that the sex of the respondent would be an important predictor of levels of participation and interest in different activities, with males being more participatory and interested in sporting pursuits (Garton and Cartmei, 1986; Garton and Pratt, 1987). With age, there should be shifts in the leisure activities of the adolescents,
ADOLESCENTS’
LEISURE ACTIVITIES
307
as according
to Coleman’s (1979) “focal theory”, with age there are shifts of attitudes to personal and social issues. These shifts may be reflected in the preferred pursuits and interests of different age groups (Hendry, 1983). The school attended was also used as a predictor variable. The schools selected represented the range of possible co-educational school types in Western Australia. The schools differ in their geographical locations and were categorized as either city high schools or country high schools. This distinction has important implications not only for the type of student attending (based on personal factors) but for the availability of certain facilities for activities. Thus, it is likely that students in country schools may not have as much access to a range of facilities for activities and hence may participate less. Such information is useful for planning for facilities both in the school and in the local community. Ethnicity was judged by the country of birth of the student respondent. It was hypothesized that participatory activities and preferred interests might differ according to ethnicity. The nature and magnitude of this influence is difficult to predict, except to point out that some sporting activities are clearly preferred by certain nationalities (e.g. golf by the Japanese-see Garton et aZ., 1990). Socio-economic status (SES) reflects a range of cultural and social aspects that impinge on adolescence, permitting and denying access to available leisure pursuits. SES factors play an important role, both direct and indirect, in predicting an adolescent’s leisure activities and interests. Socio-economic status may directly impact on leisure through the different lifestyles and opportunities, values and models, made available during childhood and adolescence. The indirect influences of socio-economic status are noted in such things as home suburb, school selection and the provision of equipment and resources for leisure activities. A broad indicator of SES is parental occupation and in this study, father’s occupation was used as a predictor of levels of participation and degrees of interest in leisure activities.
METHOD Subjects
A total of 1316 students participated in the study by completing a questionnaire during school time. Forty-two students were dropped from the analyses because their questionnaires were substantially incomplete, defaced or showed evidence of a marked response bias. Thus, 1274 (96.8 per cent) questionnaires were available for inclusion in the analysis.
308
A. F. GARTON
Table 1.
AND C. PRATT
Distribution of ages of students
Age
n
13-year-olds 14-year-olds 15-year-olds 16-year-olds 17-year-olds Total
358 381 294 1.59 56 1248
Age was established from stated date of birth. Selection was made of subjects aged between 13 and 17 years-old only, as these ages represent the median ages for the five school grades 8 to 12. This reduced the final sample size to 1248. The distribution of these students is shown in Table 1. Sex
Of the final sample, boys.
SO.9 per cent were girls and 49.1
per cent were
School
The students were drawn from 11 high schools in Western Australia, seven metropolitan and four country schools. The city schools were all Senior High Schools, providing the full five years of high school educaTable 2. Paternal 1.
2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. Total
Paternal
occupations and percentages Percentage
occupation
Professional Managerial and administrative Clerical Sales (retail and wholesale) Farmers, fishermen etc Miners Workers in transport and communication Trades Workers in service, sport and recreation Armed services Pensioner/student Unemployed Not stated
industries
19.9 11.6 4.6 4.1 10.8 0.6 8.9 18.4 3.8 1.1 1.4 7.2 7.6 100.0
(%)
ADOLESCENTS’
LEISURE
ACTIVITIES
309
tion (Grades 8 to 12) while in the country, three were District High Schools which provide education for Grades 8 to 10 only and one was a Senior High School, but only students in Grades 8 to 10 participated. The schools were classified as city or country for comparison purposes, with 75.4 per cent of the students attending city schools and 24.6 per cent attending country schools. Country
of birth
The majority of students were Australian born (76.6 per cent),which compares favourably with the 1986 census figure for Australian born young people (15 to 24-year-olds) in Western Australia of 76 per cent (Youth Affairs Bureau (WA)/ABS, 1988). For the purposes of analyses, the countries of birth were grouped as: Australia and New Zealand (79.3 per cent), Europe (9.4 per cent), Asia (7.9 per cent), America (l-2 per cent) and Africa (2.2 per cent), corresponding to the major continents. Father’s
occupation
The paternal jobs were grouped along the lines of the Australian with some alterations and additions. Bureau of Statistics groupings, These groupings are based on occupational classifications on a scale from professionals through farmers to trades and services. Unemployed fathers were categorized separately as were those on a pension or who were students. There was an over-representation of professionals and underrepresentation of administrators, clerks and trades people (Youth Affairs Bureau (WA)/ABS, 1988) in the occupational groupings, a result of two large schools being in older, well established and reasonably wealthy areas. The occupational groupings used, with the percentage of fathers in each category, are shown in Table 2. Questionnaire*
A 37-page questionnaire entitled Youth in Australia was completed by the students. The questionnaire predominantly seeks students’ attitudes to a range of contemporary issues and concerns, including participation and interest in leisure activities, attitudes to school and work and about health and fitness. This paper is concerned with students’ participation and interest in leisure pursuits and the activities in which they would like to participate but cannot, and why not. Basic demographic information was collected from each student on the *The questionnaire was adapted from “Young Scotland” courtesy of Professor Leo B. Hendry.
People’s Leisure and Lifestyle in Modern
310
A. F. GARTON AND C. PRATT
first two pages. Participation in leisure activities was measured by 63 items. The frequency of participation for each item was measured on a four-point scale, ranging from: two/three times a week (4); once/twice a fortnight (3); few times a year (2); to seldom or never (1). The internal reliability of the Participation items was analysed by calculating the reliability coefficient and Cronbach’s alpha was 0.79. The 63 Participation items were then repeated for students to indicate the degree of their interest in these same activities. The degree of interest was measured on a three-point scale, ranging from: a lot of interest (3); a little interest (2); and no interest (1). The calculation of Cronbach’s alpha revealed a high degree of internal reliability in the Interest items (alpha = 0.92). Finally, students were permitted to list up to three activities (indoor, outdoor or sporting) that they would like to participate in but were unable to. They were also asked to tick the main reason why they could not participate in each nominated activity from a list of six reasons or they could specify a reason themselves.
RESULTS
Relationship
between participation
and interest
Correlation
The first analysis examined the relationship between levels of participation and interest through an inspection of the product-moment correlation coefficients calculated for each of the 63 Participation-Interest pairs. All correlations were significant at the 0.001 level. The mean correlation was 0.54, with a range of between 0.21 and 0.79. The item with the lowest correlation was “Go out for a meal” where there was little participation (mean of 2.34 with a maximum of 4) but a great deal of interest (mean of 2.47 with a maximum of 3). The highest correlation was noted for the item “Read books for pleasure” with moderate participation (2.98) and a similar level of interest (2.25). Another correlation of 0.78 was found for the item “Play a musical instrument” where there was little participation (1.96) and little interest (1.26). These same calculations were then performed for males and females separately, since previous research has shown that while boys and girls have similar preferred leisure activities and interests, their least preferred activities and interests vary (Garton and Cartmel, 1986; Garton and Pratt, 1987). A very similar pattern emerged, with the mean correlation for boys being 0.52, and for girls 0.51. The lowest correlation was recorded for “Going out for meal” for boys and girls (~~0.24 and rz0.19, respectively).
ADOLESCENTS’
311
LEISURE ACTIVITIES
The highest correlation for boys was noted for “Read books for pleasure” (~0.79) while for girls, a similar high correlation was recorded for “Play a musical instrument”. Activities
would like to participate
students
in but cannot, and why not
Correlation indicates that participation and interest levels are positively related, and that discrepancies between participation and interest are shown by low or modest correlations. However, it tells us nothing about the prediction of participation or interest. One assumption that can be made is that interest is reflected in a wish to participate but external constraints operate to prevent participation. As an exploratory hypothesis this was examined in the present study by asking students to nominate up to three activities they would like to participate in but cannot and to say why not. Table 3 lists the ten most frequently mentioned activities by boys and girls separately. The list of activities contains few unusual activities and all are sports. There were few similarities in the top ten activities for boys and girls. Squash, basketball and tennis were mentioned by both sexes, but their relative ranking varied. Otherwise, the activities in which boys and girls were interested were different. Boys provided a greater variety of activities in general than girls. The most frequently cited reasons for non-participation (or why the interest could not be fulfilled) are shown in Table 4. The most frequently mentioned reason was the lack of facilities for the particular activity, regardless of the actual activity, followed by specification of a particular reason. Some of those mentioned by the students are interesting. Lack of Table 3.
Ten most frequently
mentioned
activities
Boys Activities Squash Basketball Cricket Martial arts Motocross Soccer Football Rugby Tennis Skateboarding
Girls n 66 64 56 55 46 43 42 41 41 40
Activities Horseriding Tennis Netball Dancing Ice skating Gymnastics Basketball Swimming Water skiing Squash
n 127 87 72 68 67 63 59 59 59 54
312
A. F. CARTON
Table 4.
AND C. PRATT
Factor analysis for participation
items (after varimax rotation)
Reasons
n
693 584
No facilities “Other”
including : No time
250 42 35 31 30 25 25 24 20 14
No opportunities for girls Inconvenient time Not old enough Injury/illness No teams/clubs Don’t know how to get involved No talent No-one to play with Not tall/fit/flexible enough Too expensive Cannot get to facilities Do not have necessary special gear Parents won’t let me People would laugh at me
539 414 301 197 97
time was clearly an important issue as was the lack of provision for girls to participate in team games. Expense was also perceived to be a barrier to some activities, mainly the water sports which involve expensive equipment. However, it appears that the interest precedes participation, assuming that should resources (including facilities and time) permit, then adolescents would engage in the nominated pursuits.
Predictors Factor
of participation
and interest
analysis
Rather than using the lists of items to explore the relationships between certain independent variables and levels of participation and interest, the items were subjected to factor analysis in an attempt to discover underlying commonalities. Previous research (Garton and Pratt, 1987) found that factor analysis was a suitable way to examine Participation and Interest items, in that case in relation to differences between males and females. This study extends this by using different items and including other important independent variables in the analysis. The Participation and Interest items were factor analysed separately. For each, a principal components analysis was undertaken with a varimax
ADOLESCENTS’
Table 5. Factor
Fahor
name
LEISURE
ACTIVITIES
analysis for participation
items (after
Variance
1.
Sport
43.2
2.
Social
3.
Gregarious
10.4
4.
Vocational
9.1
5.
Water
6.2
6.
Outdoor
entertainment
sports
16-5
5.8
(%)
Items
loading
313 varimax
rotation)
(>+/-0.30)
Play cricket Watch outdoor sport Play Aus rules football Go to sports club Watch indoor sport Play baseball Circuit/weight training Play badminton Play rugby Play golf Play soccer Play tennis Athletics Go to Timezone Go to pop concerts Go to the cinema Go to parties Go out for a meal Go to the bowling alley Go to disco Go ice/roller skating Go to the pub Go to pool hall Visit friends Have friends to visit Listen to music Listen to radio Hang around and talk Sit around and talk Read papers/magazines Go to library Read books Go to museum/art gallery Play musical instrument Cooking Gardening Knitting/sewing Windsurfing Sailing Surfing Water skiing Rowing/canoeing Swimming Hillwalking Camping Fishing Voluntarvlsocial work
0.68 0.65 0.65 0.53 0.47 0.40 0.40 0.39 0.39 0.38 0.37 0.35 0.33 0.63 0.55 0.53 0.51 0.40 0.40 0.34 0.32 0.30 0.30 0.62 0.57 0.44 0.44 0.43 0.41 0.41 0.64 0.57 0.52 0.41 0.39 0.35 0.33 0.65 0.62 0.58 0.54 0.54 0.30 0.51 050 0.41 0.36
A. F. CARTON
314
Table 6. Factor 1.
name
Factor analysis of interest items (after varimax Variance 45.1
Sport
2. Gregarious
19.6
3. Water
10.1
4.
Serious
5.
Indoor
sports
8.8
games
AND C. PRATT
5.4
(%)
Items
loading
rotation)
(>+/-0.30)
Play cricket Play Aus rules football Watch outdoor sport Watch indoor sport Play rugby Play soccer Go to sports club Play baseball Play golf Play hockey Circuit/weight training Play tennis Athletics Play badminton Martial arts Listen to music Go to parties Listen to radio Go to pop concerts Hang around and talk Sit around and talk Visit friends Go to disco Have friends to visit Read papers/magazines Go shopping Go to the cinema Watch TV/video Windsurfing Surfing Water skiing Sailing Rowing/canoeing Skateboarding Swimming Go to the library Read books Go to museum/art gallery Play musical instrument Gardening Go to Timezone Play video games Play on home computer Go to the bowling alley Go to pool hall
0.69 0.67 0.65 0.59 0.59 0.54 0.52 0.51 0.49 0.46 0.46 o-43 0.43 0.39 0.31 0.61 0.58 0.57 0.56 0.53 0.52 0.47 0.46 0.44 0.39 0.37 0.36 0.30 0.80 0.78 0.75 0.70 0.54 0.34 0.34 0.69 0.63 0.55 0.40 0.31 0.66 0.63 0.54 0.49 0.39
ADOLESCENTS’
Table 6. Factor 6.
Other
Factor
LEISURE
analysis of interest items (after Variance
name
(%)
varimax
Items
4.2
activities
315
ACTIVITIES rotation)-continued
(>+/-0.30)
loading
Dancing Aerobics Knitting/sewing Voluntary/social work Cooking Go horse riding Go to evening classes Go ice/roller skating
0.60 0.55 0.44 0.40 0.38 0.38 0.33 0.31
rotation of the first eight factors. These factors accounted for 39 per cent and 46 per cent of the variance, respectively, in the principal components analysis and covered 52 and 60 Participation and Interest items, respectively. In each case, after rotation, six of the eight factors had eigenvalues greater than 1, were interpretable and so were used in subsequent analyses. These two sets of six factors covered 47 and 53 items, respectively so the two factors that were eliminated had few items loading on them. The six Participation factors are shown in Table 5 together with the variables that load on them with a weighting of > +/- 0.30. Similarly, Table 6 shows the Interest factors with the items that load on them. The groupings of items that loaded on each of the six Participation and Interest factors have been given broad descriptive labels. Further analyses were then undertaken using the factor-score variables calculated using the regression method for each factor, in order to establish which, if any, of the students’ personal and social factors were predictive of their participation and interest in these groups of leisure activities.
Table 7.
Zero-order Sex -0.02
Age
Country
Country
of birth
Father’s
occupation
between predictor
of birth 0.10**
-0.02
Sex
* p
Leisure activities of adolescent school students: predictors of participation and interest ALISON
F. GARTON*
AND CHRIS
PRATT-/-
Frequency of participation and levels of interest in more than 60 leisure pursuits were measured via a questionnaire administered to 1248 adolescent high school students. The relationship between participation and levels of interest was measured by correlation as well as by asking the students to nominate up to three activities they would like to participate in but cannot and to indicate the reason for their non-participation. Factor analyses reduced the Participation and Interest items to six factors each. Multiple regressions were then conducted on the derived factor-score variables. Sex was the major predictor of participation in sports and vocational activities and of interest in sporting and gregarious activities. Age, school location, ethnicity and SES were lesser predictors for groups of activities such as the social and outdoor pursuits. The results are discussed in terms of the theoretical and practical implications of the relationship between participation and interest as well as the prediction of participation and interest levels by developmental and social factors.
INTRODUCTION
An examination of leisure pursuits can provide an important key to an understanding of the composition and extent of a developing adolescent’s world. If we study what adolescents do in their spare time, we can gain a greater insight into the organization of their social world. Further, we can use the information to study if and how individual needs are being fulfilled by the available and accessible leisure activities. The active participation in worthwhile leisure pursuits has been proposed to be important for healthy psychological development (Hendry, 1983). Should the available leisure activities not fulfil the adolescent’s social and individual requirements either by external (accessibility) or internal (interest) constraints, then progress through adolescence may be unsatisfactory and unhealthy psychologically. “Reprints requests should be addressed Psychologist, Gascoyne House, Graylands Australia 6010, Australia. tliniversky of Western Australia. 0140-1971/91/030305+17
$03.00/0
0
to Dr Alison F. Garton, Senior Research Hospital, Private Bag 1, Claremont, Western
1991 The
Association
for the Psychiatric
Study
of Adolescents
306
A. F. GARTON AND C. PRATT
Although there is general concern over the increased leisure time available to various sections of society, for example, the retired, the unemployed and those working reduced or part-time hours, the focus of this study is on adolescents who are still at school. These adolescents form a homogeneous group who have a commitment to school during certain hours five days a week and have limited time and money available for leisure. Some previous research (e.g. Connell, Stroobant, Sinclair, Connell and Rogers, 1975) has compared adolescents at school with those in or out of work. However, with a heterogeneous group of adolescents, it is more difficult to make firm claims and generalizations (Garton and Cartmel, 1986). By restricting the study to only school students, it is hoped to capture more accurately the leisure pursuits and interests of a large group of adolescents who share a number of important characteristics and limitations. Further, it is directly comparable with earlier research which examined the leisure activities of adolescents, some descriptive and applied (e.g. Poole, 1983; Poole and Juchnowski, 1976; 1977), some more measurement-based and analytic (Garton and Pratt, 1987) and some cross-cultural (Garton, Takimoto, Pratt and Hayashi, 1990). Garton and Pratt (1987) noted that while participation and interest were indeed highly correlated and adolescents were interested in what they participated in and not interested in activities they did not participate in, it was not clear to what extent interest developed as a result of participation. Therefore, the adolescents in this present study were provided with the opportunity to stipulate activities in which they would like to participate but could not (as an indicator of “interest”) and to provide a reason why they were unable to participate. In this way, it would be possible to gauge whether activities were available but non-participation was due to lack of time or other commitments or whether facilities and/or opportunities for participation did not exist. Thus, the first aim of the study was to ascertain the relationship between participation in activities and interest and to determine to what extent interest (measured by a wish for participation) was related to external constraints or pressures. The second aim of the study was to examine some of the predictors of participation and interest in leisure activities. Five independent variables were chosen and these were sex, age, school location, ethnicity and socio-economic status. Regression analyses were conducted using all five variables to establish their relative influences on the selection of leisure activities. It was hypothesized that the sex of the respondent would be an important predictor of levels of participation and interest in different activities, with males being more participatory and interested in sporting pursuits (Garton and Cartmei, 1986; Garton and Pratt, 1987). With age, there should be shifts in the leisure activities of the adolescents,
ADOLESCENTS’
LEISURE ACTIVITIES
307
as according
to Coleman’s (1979) “focal theory”, with age there are shifts of attitudes to personal and social issues. These shifts may be reflected in the preferred pursuits and interests of different age groups (Hendry, 1983). The school attended was also used as a predictor variable. The schools selected represented the range of possible co-educational school types in Western Australia. The schools differ in their geographical locations and were categorized as either city high schools or country high schools. This distinction has important implications not only for the type of student attending (based on personal factors) but for the availability of certain facilities for activities. Thus, it is likely that students in country schools may not have as much access to a range of facilities for activities and hence may participate less. Such information is useful for planning for facilities both in the school and in the local community. Ethnicity was judged by the country of birth of the student respondent. It was hypothesized that participatory activities and preferred interests might differ according to ethnicity. The nature and magnitude of this influence is difficult to predict, except to point out that some sporting activities are clearly preferred by certain nationalities (e.g. golf by the Japanese-see Garton et aZ., 1990). Socio-economic status (SES) reflects a range of cultural and social aspects that impinge on adolescence, permitting and denying access to available leisure pursuits. SES factors play an important role, both direct and indirect, in predicting an adolescent’s leisure activities and interests. Socio-economic status may directly impact on leisure through the different lifestyles and opportunities, values and models, made available during childhood and adolescence. The indirect influences of socio-economic status are noted in such things as home suburb, school selection and the provision of equipment and resources for leisure activities. A broad indicator of SES is parental occupation and in this study, father’s occupation was used as a predictor of levels of participation and degrees of interest in leisure activities.
METHOD Subjects
A total of 1316 students participated in the study by completing a questionnaire during school time. Forty-two students were dropped from the analyses because their questionnaires were substantially incomplete, defaced or showed evidence of a marked response bias. Thus, 1274 (96.8 per cent) questionnaires were available for inclusion in the analysis.
308
A. F. GARTON
Table 1.
AND C. PRATT
Distribution of ages of students
Age
n
13-year-olds 14-year-olds 15-year-olds 16-year-olds 17-year-olds Total
358 381 294 1.59 56 1248
Age was established from stated date of birth. Selection was made of subjects aged between 13 and 17 years-old only, as these ages represent the median ages for the five school grades 8 to 12. This reduced the final sample size to 1248. The distribution of these students is shown in Table 1. Sex
Of the final sample, boys.
SO.9 per cent were girls and 49.1
per cent were
School
The students were drawn from 11 high schools in Western Australia, seven metropolitan and four country schools. The city schools were all Senior High Schools, providing the full five years of high school educaTable 2. Paternal 1.
2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. Total
Paternal
occupations and percentages Percentage
occupation
Professional Managerial and administrative Clerical Sales (retail and wholesale) Farmers, fishermen etc Miners Workers in transport and communication Trades Workers in service, sport and recreation Armed services Pensioner/student Unemployed Not stated
industries
19.9 11.6 4.6 4.1 10.8 0.6 8.9 18.4 3.8 1.1 1.4 7.2 7.6 100.0
(%)
ADOLESCENTS’
LEISURE
ACTIVITIES
309
tion (Grades 8 to 12) while in the country, three were District High Schools which provide education for Grades 8 to 10 only and one was a Senior High School, but only students in Grades 8 to 10 participated. The schools were classified as city or country for comparison purposes, with 75.4 per cent of the students attending city schools and 24.6 per cent attending country schools. Country
of birth
The majority of students were Australian born (76.6 per cent),which compares favourably with the 1986 census figure for Australian born young people (15 to 24-year-olds) in Western Australia of 76 per cent (Youth Affairs Bureau (WA)/ABS, 1988). For the purposes of analyses, the countries of birth were grouped as: Australia and New Zealand (79.3 per cent), Europe (9.4 per cent), Asia (7.9 per cent), America (l-2 per cent) and Africa (2.2 per cent), corresponding to the major continents. Father’s
occupation
The paternal jobs were grouped along the lines of the Australian with some alterations and additions. Bureau of Statistics groupings, These groupings are based on occupational classifications on a scale from professionals through farmers to trades and services. Unemployed fathers were categorized separately as were those on a pension or who were students. There was an over-representation of professionals and underrepresentation of administrators, clerks and trades people (Youth Affairs Bureau (WA)/ABS, 1988) in the occupational groupings, a result of two large schools being in older, well established and reasonably wealthy areas. The occupational groupings used, with the percentage of fathers in each category, are shown in Table 2. Questionnaire*
A 37-page questionnaire entitled Youth in Australia was completed by the students. The questionnaire predominantly seeks students’ attitudes to a range of contemporary issues and concerns, including participation and interest in leisure activities, attitudes to school and work and about health and fitness. This paper is concerned with students’ participation and interest in leisure pursuits and the activities in which they would like to participate but cannot, and why not. Basic demographic information was collected from each student on the *The questionnaire was adapted from “Young Scotland” courtesy of Professor Leo B. Hendry.
People’s Leisure and Lifestyle in Modern
310
A. F. GARTON AND C. PRATT
first two pages. Participation in leisure activities was measured by 63 items. The frequency of participation for each item was measured on a four-point scale, ranging from: two/three times a week (4); once/twice a fortnight (3); few times a year (2); to seldom or never (1). The internal reliability of the Participation items was analysed by calculating the reliability coefficient and Cronbach’s alpha was 0.79. The 63 Participation items were then repeated for students to indicate the degree of their interest in these same activities. The degree of interest was measured on a three-point scale, ranging from: a lot of interest (3); a little interest (2); and no interest (1). The calculation of Cronbach’s alpha revealed a high degree of internal reliability in the Interest items (alpha = 0.92). Finally, students were permitted to list up to three activities (indoor, outdoor or sporting) that they would like to participate in but were unable to. They were also asked to tick the main reason why they could not participate in each nominated activity from a list of six reasons or they could specify a reason themselves.
RESULTS
Relationship
between participation
and interest
Correlation
The first analysis examined the relationship between levels of participation and interest through an inspection of the product-moment correlation coefficients calculated for each of the 63 Participation-Interest pairs. All correlations were significant at the 0.001 level. The mean correlation was 0.54, with a range of between 0.21 and 0.79. The item with the lowest correlation was “Go out for a meal” where there was little participation (mean of 2.34 with a maximum of 4) but a great deal of interest (mean of 2.47 with a maximum of 3). The highest correlation was noted for the item “Read books for pleasure” with moderate participation (2.98) and a similar level of interest (2.25). Another correlation of 0.78 was found for the item “Play a musical instrument” where there was little participation (1.96) and little interest (1.26). These same calculations were then performed for males and females separately, since previous research has shown that while boys and girls have similar preferred leisure activities and interests, their least preferred activities and interests vary (Garton and Cartmel, 1986; Garton and Pratt, 1987). A very similar pattern emerged, with the mean correlation for boys being 0.52, and for girls 0.51. The lowest correlation was recorded for “Going out for meal” for boys and girls (~~0.24 and rz0.19, respectively).
ADOLESCENTS’
311
LEISURE ACTIVITIES
The highest correlation for boys was noted for “Read books for pleasure” (~0.79) while for girls, a similar high correlation was recorded for “Play a musical instrument”. Activities
would like to participate
students
in but cannot, and why not
Correlation indicates that participation and interest levels are positively related, and that discrepancies between participation and interest are shown by low or modest correlations. However, it tells us nothing about the prediction of participation or interest. One assumption that can be made is that interest is reflected in a wish to participate but external constraints operate to prevent participation. As an exploratory hypothesis this was examined in the present study by asking students to nominate up to three activities they would like to participate in but cannot and to say why not. Table 3 lists the ten most frequently mentioned activities by boys and girls separately. The list of activities contains few unusual activities and all are sports. There were few similarities in the top ten activities for boys and girls. Squash, basketball and tennis were mentioned by both sexes, but their relative ranking varied. Otherwise, the activities in which boys and girls were interested were different. Boys provided a greater variety of activities in general than girls. The most frequently cited reasons for non-participation (or why the interest could not be fulfilled) are shown in Table 4. The most frequently mentioned reason was the lack of facilities for the particular activity, regardless of the actual activity, followed by specification of a particular reason. Some of those mentioned by the students are interesting. Lack of Table 3.
Ten most frequently
mentioned
activities
Boys Activities Squash Basketball Cricket Martial arts Motocross Soccer Football Rugby Tennis Skateboarding
Girls n 66 64 56 55 46 43 42 41 41 40
Activities Horseriding Tennis Netball Dancing Ice skating Gymnastics Basketball Swimming Water skiing Squash
n 127 87 72 68 67 63 59 59 59 54
312
A. F. CARTON
Table 4.
AND C. PRATT
Factor analysis for participation
items (after varimax rotation)
Reasons
n
693 584
No facilities “Other”
including : No time
250 42 35 31 30 25 25 24 20 14
No opportunities for girls Inconvenient time Not old enough Injury/illness No teams/clubs Don’t know how to get involved No talent No-one to play with Not tall/fit/flexible enough Too expensive Cannot get to facilities Do not have necessary special gear Parents won’t let me People would laugh at me
539 414 301 197 97
time was clearly an important issue as was the lack of provision for girls to participate in team games. Expense was also perceived to be a barrier to some activities, mainly the water sports which involve expensive equipment. However, it appears that the interest precedes participation, assuming that should resources (including facilities and time) permit, then adolescents would engage in the nominated pursuits.
Predictors Factor
of participation
and interest
analysis
Rather than using the lists of items to explore the relationships between certain independent variables and levels of participation and interest, the items were subjected to factor analysis in an attempt to discover underlying commonalities. Previous research (Garton and Pratt, 1987) found that factor analysis was a suitable way to examine Participation and Interest items, in that case in relation to differences between males and females. This study extends this by using different items and including other important independent variables in the analysis. The Participation and Interest items were factor analysed separately. For each, a principal components analysis was undertaken with a varimax
ADOLESCENTS’
Table 5. Factor
Fahor
name
LEISURE
ACTIVITIES
analysis for participation
items (after
Variance
1.
Sport
43.2
2.
Social
3.
Gregarious
10.4
4.
Vocational
9.1
5.
Water
6.2
6.
Outdoor
entertainment
sports
16-5
5.8
(%)
Items
loading
313 varimax
rotation)
(>+/-0.30)
Play cricket Watch outdoor sport Play Aus rules football Go to sports club Watch indoor sport Play baseball Circuit/weight training Play badminton Play rugby Play golf Play soccer Play tennis Athletics Go to Timezone Go to pop concerts Go to the cinema Go to parties Go out for a meal Go to the bowling alley Go to disco Go ice/roller skating Go to the pub Go to pool hall Visit friends Have friends to visit Listen to music Listen to radio Hang around and talk Sit around and talk Read papers/magazines Go to library Read books Go to museum/art gallery Play musical instrument Cooking Gardening Knitting/sewing Windsurfing Sailing Surfing Water skiing Rowing/canoeing Swimming Hillwalking Camping Fishing Voluntarvlsocial work
0.68 0.65 0.65 0.53 0.47 0.40 0.40 0.39 0.39 0.38 0.37 0.35 0.33 0.63 0.55 0.53 0.51 0.40 0.40 0.34 0.32 0.30 0.30 0.62 0.57 0.44 0.44 0.43 0.41 0.41 0.64 0.57 0.52 0.41 0.39 0.35 0.33 0.65 0.62 0.58 0.54 0.54 0.30 0.51 050 0.41 0.36
A. F. CARTON
314
Table 6. Factor 1.
name
Factor analysis of interest items (after varimax Variance 45.1
Sport
2. Gregarious
19.6
3. Water
10.1
4.
Serious
5.
Indoor
sports
8.8
games
AND C. PRATT
5.4
(%)
Items
loading
rotation)
(>+/-0.30)
Play cricket Play Aus rules football Watch outdoor sport Watch indoor sport Play rugby Play soccer Go to sports club Play baseball Play golf Play hockey Circuit/weight training Play tennis Athletics Play badminton Martial arts Listen to music Go to parties Listen to radio Go to pop concerts Hang around and talk Sit around and talk Visit friends Go to disco Have friends to visit Read papers/magazines Go shopping Go to the cinema Watch TV/video Windsurfing Surfing Water skiing Sailing Rowing/canoeing Skateboarding Swimming Go to the library Read books Go to museum/art gallery Play musical instrument Gardening Go to Timezone Play video games Play on home computer Go to the bowling alley Go to pool hall
0.69 0.67 0.65 0.59 0.59 0.54 0.52 0.51 0.49 0.46 0.46 o-43 0.43 0.39 0.31 0.61 0.58 0.57 0.56 0.53 0.52 0.47 0.46 0.44 0.39 0.37 0.36 0.30 0.80 0.78 0.75 0.70 0.54 0.34 0.34 0.69 0.63 0.55 0.40 0.31 0.66 0.63 0.54 0.49 0.39
ADOLESCENTS’
Table 6. Factor 6.
Other
Factor
LEISURE
analysis of interest items (after Variance
name
(%)
varimax
Items
4.2
activities
315
ACTIVITIES rotation)-continued
(>+/-0.30)
loading
Dancing Aerobics Knitting/sewing Voluntary/social work Cooking Go horse riding Go to evening classes Go ice/roller skating
0.60 0.55 0.44 0.40 0.38 0.38 0.33 0.31
rotation of the first eight factors. These factors accounted for 39 per cent and 46 per cent of the variance, respectively, in the principal components analysis and covered 52 and 60 Participation and Interest items, respectively. In each case, after rotation, six of the eight factors had eigenvalues greater than 1, were interpretable and so were used in subsequent analyses. These two sets of six factors covered 47 and 53 items, respectively so the two factors that were eliminated had few items loading on them. The six Participation factors are shown in Table 5 together with the variables that load on them with a weighting of > +/- 0.30. Similarly, Table 6 shows the Interest factors with the items that load on them. The groupings of items that loaded on each of the six Participation and Interest factors have been given broad descriptive labels. Further analyses were then undertaken using the factor-score variables calculated using the regression method for each factor, in order to establish which, if any, of the students’ personal and social factors were predictive of their participation and interest in these groups of leisure activities.
Table 7.
Zero-order Sex -0.02
Age
Country
Country
of birth
Father’s
occupation
between predictor
of birth 0.10**
-0.02
Sex
* p
