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Abstract

Efforts to increase physical activity in youth need to consider which activities are most likely to be sustained over time in order to promote lifelong participation in physical activity. The Monitoring Activities of Teenagers to Comprehend their Habits (MATCH) study is a prospective cohort study that uses quantitative and qualitative methods to develop new knowledge on the sustainability of specific physical activities.Methods/design: Eight hundred and forty-three grade 5 and 6 students recruited from 17 elementary schools in New Brunswick, Canada, are followed-up three times per year. At each survey cycle, participants complete self-report questionnaires in their classroom under the supervision of trained data collectors. A sub-sample of 24 physically active students is interviewed annually using a semi-structured interview protocol. Parents (or guardians) complete telephone administered questionnaires every two years, and a health and wellness school audit is completed for each school. MATCH will provide a description of the patterns of participation in specific physical activities in youth, and enable identification of the determinants of maintenance, decline, and uptake of participation in each activity. These data will inform the development of interventions that take into account which activities are the most likely to be maintained and why activities are maintained or dropped.
ST U D Y P R O T O C O L Open Access
Monitoring activities of teenagers to comprehend
their habits: study protocol for a mixed-methods
cohort study
Mathieu Bélanger
1,2,3*
, Isabelle Caissie
1
, Jacinthe Beauchamp
1
, Jennifer OLoughlin
4,5,6
, Catherine Sabiston
7
and Michelina Mancuso
8
Abstract
Background: Efforts to increase physical activity in youth need to consider which activities are most likely to be
sustained over time in order to promote lifelong participation in physical activity. The Monitoring Activities of
Teenagers to Comprehend their Habits (MATCH) study is a prospective cohort study that uses quantitative and
qualitative methods to develop new knowledge on the sustainability of specific physical activities.
Methods/design: Eight hundred and forty-three grade 5 and 6 students recruited from 17 elementary schools in
New Brunswick, Canada, are followed-up three times per year. At each survey cycle, participants complete self-report
questionnaires in their classroom under the supervision of trained data collectors. A sub-sample of 24 physically active
students is interviewed annually using a semi-structured interview protocol. Parents (or guardians) complete telephone
administered questionnaires every two years, and a health and wellness school audit is completed for each school.
Discussion: MATCH will provide a description of the patterns of participation in specific physical activities in youth,
and enable identification of the determinants of maintenance, decline, and uptake of participation in each activity.
These data will inform the development of interventions that take into account which activities are the most likely to
be maintained and why activities are maintained or dropped.
Keywords: Physical activity, Sport, Youth, Behavior, Adolescents, Mixed methods, Cohort
Background
In Canada, physical inactivity is the most prevalent pre-
ventable risk factor for chronic disease and mortality in
youth and across the lifespan [1,2]. A recent objective
assessment of physical activity in a representative sample
of Canadians aged 6 to 19 years indicated that only 9%
of boys and 4% of girls engaged in the recommended
60 minutes of moderate-to-vigorous physical activity per
day [3]. The burden of chronic disease will likely increase
given that low levels of physical activity in youth is a
strong predictor of a sedentary lifestyle in adulthood [4].
Physical inactivity in youth increases the risk of cardio-
vascular disease [5,6], diabetes [7], low bone mineral
density [8,9], slower cognitive development [10-12], anx-
iety and depression [13], and obesity [14,15]. Physical ac-
tivity and sports provide opportunitie s for developing
competence, experiencing achievement, developing iden-
tities, forming positive relationships, learning to respect
others, and enhancing a sense of community, while phys-
ical inactivity may result in suboptimal psychological and
social growth [3]. Enrolment in physical activity programs
is associated with improved social and communication
skills, heighted motivation, lower rates of deviant behav-
iours, and better academic achievement [16].
Declines in physical activity during adolescence are
characterized by marked changes in the range of physical
activities in which youth engage [17]. The popularity of
nearly all types of physic al activity declines during ado-
lescence [18] and the number of different activities in
which adolescents engage also decreases with age [17,19].
With the possible exceptions of active transportation (i.e.,
* Correspondence: mathieu.f.belanger@usherbrooke.ca
1
Centre de formation médicale du Nouveau-Brunswick, Pavillon
J.-Raymond-Frenette, 15, rue des Aboiteaux, Moncton, NB, Canada E1A 3E9
2
Department of family medicine, Université de Sherbrooke, Sherbrooke,
Canada
Full list of author information is available at the end of the article
© 2013 Bélanger et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly cited.
Bélanger et al. BMC Public Health 2013, 13:649
http://www.biomedcentral.com/1471-2458/13/649
walking, bicycling to and from school) and household
chores, few young people maintain involvement in specific
types of physical activity during adolescence [20-26].
Other reports indicate that the relative contribution of
different types of physical activity changes with age. For
example, although participation in both organized and
non-organized physical activity decreases during adoles-
cence [27-29], there are steeper declines in organized
physical activity especially in girls [30]. Similarly, high
drop-out rates from sports are reported from childhood
to adolescence [18] and from adolescence to adulthood
[22,31,32]. Some activities are en gaged in almost exclu-
sively by some age groups [31].Skipping rope, playing
tag, and using playgrounds are popular among children
[24,25], whereas adults engage in physical conditioning
and occupational physical activity [31]. Participation in
specific physical activities in adulthood is nevertheless
more likely among individuals who engaged in the activ-
ity durin g adolescence [22].
Systematic reviews have identified factors that are ro-
bustly associated with physical activity [33-35]. However,
other than gender differences whereby boys prefer com-
petitive sports [20,21,36-38] and accumulate more vigor-
ous physical activity than girls (who accumulate more
moderate physical activity [20,21] and prefer non-
competitive individual sports [37]), little is known about
the determinants of participating in specific physical activ-
ities. Moreover, in-depth understanding of why adoles-
cents discontinue, maintain or initiate physical activity
participation is lacking.
Whereas qualitative studies provide rich descriptive in-
formation on how various factors influence behavioral
patterns, few qualitative studies explore reasons for par-
ticipation in physical activity during adolescence. Extant
qualitative studies show that common reasons for taking
part in physical activity include enjoyment, social inter-
action and weight management, whereas lacking confi-
dence and ability are barriers [39-42]. A qualitative study
that explored differences between phy sical activity main-
tainers and decliners [43] suggested that decliners
reported negative social interactions, unsupportive social
environments and feeling insufficiently competent as
factors related to declines in physical activity. In con-
trast, maintenance of physical activity was associated
with recognition of health benefits of physical activity,
relatedness to others, and perceiving the environment as
supportive of physical activity. Insights on factors ex-
plaining differences in patterns of physical activity par-
ticipation during adolescence from both prospective
qualitative and quantitative data are needed.
Monitoring Activities of Teenagers to Comprehend
their Habits (MATCH) is a prospective mixed-methods
study aimed at identifying and better understanding the
determinant s of discontinuing or sustaining participation
in specific physical activities during adolescence. The ob-
jectives are: 1) to better understand the physical activity-
related experiences of participants in various types of
physical activity, including individual activities, team-
based activities, organised activities, and non-organised
activities; 2) to develop better understanding of the
process of maintaining adequate physical activity levels
during the transition from childhood to adolescence; 3)
to develop better understanding of the process of de clin-
ing physical activity levels during the transit ion from
childhood to adolescence; 4) to identify determinants of
maintaining, discontinuing, or taking up participation in
different types of physical activity from childhood to
adolescence; and 5) to assess how changes in correlates
relate to changes in participation in different types of
physical activity.
Methods/design
Design and conceptual framework
MATCH is a prospe ctive cohort study that uses quanti-
tative and qualitative methods to develop new know-
ledge on the natural course and determinants of physical
activity in youth. The M ATCH study is grounded in the
Self-Determination Theory (SDT) which enables better
understanding of what motivates people to engage in,
and maintain, certain types of physical activity. This in
turn will help inform the design of intervent ions tailored
to individual needs. SDT is founded on the notion that
individuals behave according to interactions between ex-
trinsic forces, intrinsic motives and essential needs [44].
An integral component of SDT is the underlying theory
of Basic Psychological Needs, which assumes that a per-
son maintains optimal functioning in contexts that sup-
port three basic psychological needs: competence,
autonomy and relatedness [45,46]. Specifically, mainten-
ance of participation in a physical activity is achieved
when an individual feels that he or she masters the activ-
ity (competence), when the activity is undertaken by
choice (autonomy), and when a meaningful connection
is established with people through participation in the
activity (relatedness). Chaos Theory is also incorporated in
components of MATCH because random external events
(i.e., loss of a friend, a public announcement, a conversa-
tion) may trigger at least short-term behavior change [47].
Chaos Theory supports investigating the influence of un-
planned or uncontrolled factors that lead to sudden
changes in physical activity. MATCH received Ethics
Approval from the Comité dÉthique de la Recherche du
Centre Hospitalier de lUniversité de Sherbrooke.
Study population
Nineteen schools were initially recruited from across the
province of New Brunswick, Canada to participate in
MATCH. However two schools were subsequently
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excluded because of a low return rate of consent forms.
Schools recruited were selected to include a mix of
French and English language schools from high, mod er-
ate, and low socioeconomic neighbourhoods, situated in
rural and urban areas. Students were recruited within
the 17 study schools from September 2011 to January
2012. Information packages were sent to the parents of
all children in Grade 5 and 6 (10-12 years old), which
provided detailed information on the MATCH study ob-
jectives and methods, as well as a consent form for par-
ents and students to complete and return to the school.
A total of 802 eligible students were recruited in the first
year of data collection, for a response proportion of 51%.
Contact information for parents or guardians of 490 of
these 802 participants were obtained from schools. At
least three attempts to contact each parent were made
between August 2012 and February 2013. A total of 253
parents were contacted, of whom 246 (97%) agreed to
respond to a telephone-admi nistered questionnaire.
For the qualitative component of the study, a purposely-
selected sample of participants was selected from among
those categorized, after four survey cycles, as most physic-
ally active (we ascertained that four questionnaires were
needed to appropriately assess types of activities usually
practiced). Six participants were recruited to represent
each of the following categories of physical activity partici-
pation: involved primarily in a) team activities; b) individ-
ual activities; c) organised activities; and d) non-organised
activities, for a total of 12 boys and 12 girls. Although
overlap occurs among the types of physical activity prac-
ticed by different groups, the decision to recruit based on
this categorisation was motivated by the intention to in-
clude participants with a wide variety of behavioral pat-
terns and not to obtain four mutually exclusive groups.
This way, we maximize our ability to develop an under-
standing of experiences of participation in different types
of physical activities.
Quantitative data collection
Participants provide data three times each year until the
end of grade 12 when they graduate from high school,
for a total of up to 24 survey cycles per participant.
Three survey cycles per year permit investigation of sea-
sonal variation in activity levels and types of activity
practiced [48]. At each survey cycle, participants
complete self-report questionnaires in their classroom
under the supervision of trained data collectors. Class-
room visits in the first survey cycle took approximately
45-60 minutes and subsequent visits take approximately
20-30 minutes (stu dents need less instructions). All data
collection visits are scheduled at the convenience of
teachers.
Data are collected from parents (or guardians) every
two years a telephone-administered questionnaires.
During the first year that schools participate in the
study, a designated person within each scho ol completes
a questionnaire in consultation with other staff, which
collects data on the school environment. Responses are
verified on-site by a research assistant.
Student questionnaire
The student questionnaire uses a checklist of 36 activ-
ities to collect data on the types of physical activity in
which participants engaged over the past four months.
The checklist inc orporates all of the commonly prac-
ticed activities by youth in this region [49] and all activ-
ities included in other similar and validated physical
activity checklists [50-52]. Participants report the fre-
quency of participation in each activity, where the activ-
ity took place (school, home or neighborhood, indoor
arena or gym, outdoor field, other), and with whom (by
myself, organized group or team, siblings, friends, par-
ents) activities were engaged in [24]. Pilot-testing of the
questionnaire in English and French followe d by discus-
sions with 12 Grade 5 and 6 students indicated that chil-
dren have no difficulty understanding and answering the
questions.
Physical activity level is estimated using a simple 2-
item questionnaire developed for use among youth [53].
This questionnaire has demonstrated test-retest reliabil-
ity (r = 0.77) and it correlated significantly with acceler-
ometer data (r = 0.40; this criterion validity index is as
good as or better than other physical activity question-
naires) [53].
Basic Psychological Needs are measured in three ques-
tionnaires: (i) perceived competence is assessed with the
6-item subscale from the Intrinsic Motivation Inventory
[54], (ii) perceived autonomy is assessed in the seven
items from the autonomy subscale of the Basic Psycho-
logical Needs in Life Scale [55,56], an d (iii) perceived re-
latedness is assessed with the Relatedness to Others in
Physical Activity Scale [57]. Each of these scales has in-
ternal consistency reliability coefficients (Cronbachs
alpha) of 0.70 to 0.92 and is associated with physical ac-
tivity [54-57]. Motives for physical activity is measured
with the Motivations for Physical Activities Measure-
Revised, a 30-item questionnaire that reflects five gen-
eral motives for physical activity participation including
enjoyment, competence, appearance, fitness and social
interaction [58]. Enjoyme nt and competence are mea-
sures of intrinsic motives, whereas appearance, fitness
and social are indicators of extrinsic motives [58]. The
questionnaire has been used successfully to document a
relationship between different types of motives for phys-
ical activity and long-term adherence to two specific types
of physical activity (Tae Kwon Do and Aerobics) [58].
Active transportation is determined by asking youth
how they usually get to and from school (actively,
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inactively or mixed) [59]. The core questionnaire also
collects data on age, sex, school-based physical activities
[59], sedentary behaviors [60,61], perceived physical ac-
tivity of others, weight regulating behaviors [62], sleep
patterns [63], pubertal stage [64,65], and unplanned
events that may have influenced physical activity partici-
pation such as parental divorce, sickness in the family,
difficulties at school, etc. Data on dietary habits are col-
lected once a year, using items from the 2010 National
Youth Physical Activity and Nutrition survey [66].
Parent questionnaire
Parents provide data on their own level of participation
in physical activity in a telephone-administered ques-
tionnaire [67]. They also report on their participation in
specific phy sical activities [67], and they provide data on
family structure, socioeconomic level, and neighbour-
hood attributes [68].
Student and parent questionnaires were developed in
English and translated into French if validated transla-
tions were not already available. The translation was
undertaken by a bilingual kinesiologist whose mother
tongue is French, with emphasis on conceptual rather
than literal translations, and on clear and concise formu-
lation. Three bilingual research team members reviewed
and edited the translation for consistency with the English
version. The French items were then back-translated
by an independent individual whose mother tongue is
English. The initial and final English versions where
then compared to confirm consistency.
School questionnaire
The school questionnaire includes data on facilities
available for physical activity inside schools, school yards
and in the schoo l neighborhood. Data are also collected
on whether students have access to schools facilities dur-
ing non-instructional times throughout the school day, if
activities are offered to them when they remain indoors
due to inclement weather during non- instructional time,
and if students have access to school facilities outside
school hours. We also collect information on frequency
and duration of Physical Education classes, and school
policies related to physical activity and nutrition (adapted
from [69] and [70]). Data collected in this school question-
naire has a high level of validity (% agreement with
consensus-based opinion among school staff is perfect
for >75 of items), test-retest reliability (exact agreement
for 79.4% of items), and inter-judge reliability (77.3% of
items have shown exact agreement between raters) [71].
Qualitative data collection
The annual individual qua litative interviews with a sub-
sample of 24 participants take place in a private room
provided by schools. A phenomenological approach,
which is particularly useful for understanding experi-
ences of individuals and gaining insight into their moti-
vations and actions, is used in the qualitative component
of this study [72]. The phenomena under study include
participation in specific types of physical activity, main-
tenance of physical activity, and decline in level of phys-
ical activity. Consistent with standard phenomenological
methodology, our design involves multiple face-to-face
interviews [73,74]. Participants are interviewed individu-
ally on a yearly basis to describe the evolution of their
physical activity-related experiences as it relates to i) the
type of physical activity they take part into as well as ii)
maintenance or decline in participation in physical activ-
ity. The first interview serves as a baseline from which
individual profiles will thereafter be built using data
from follow up interviews. The interviews are audio-
recorded and transcribed verbatim.
Although phenomenological research often begins
from a perspective free from hypotheses or preconcep-
tions [75], mor e recent viewpoin ts suggest that it is im-
possible to begin withou t preconceptions or bias and
therefore emphasize that res earchers should state their
initial theoretical basis [76,77]. Therefore, the semi-
structured interview guide (used as a flexible template
rather than a rigid list of questions [78]) aims at gather-
ing data on part icipants general experience s with phys-
ical activity and physical activity-related feelings of
competence, relatedness with others, and autonomy
(Ba sic Psychological Needs component of the SDT). In-
terviewers are also trained to examine the occurrence of
random external triggers if marked changes in patterns
of physical activity are noted.
In addition to the 24 participants above, we will invite
participants with low physical activity in the first two
years of study who subsequently become physically ac-
tive for interviews that explore circumstances that led to
this (sudden) change. Participants in these interviews
will be met only once. These interviews could take place
in year 3-6, depending on when sudden increases
are noted. This will be of particular use to investigate
the extent to which chaotic events influence increases
in physical activi ty. Interviews will continue until data
saturation is reached. All interviews will be recorded and
transcribed.
Limitations
The study schools for MATCH represent a convenience
sample. However, the schools were selected specifically
to represent a mix of schools from low, middle, and
higher socioeconomic status in a variety of urban, subur-
ban, and rural settings in French and English regions of
New Brunswick. Further, it is unlikely that the determi-
nants of the maintenance or discontinuation of physical
activity differ markedly between youth populations in
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Canada. It is possible that repeated data collection using
the same questionnaire could sensitize participants to
motives for maintaining or not participating in physical
activity. This is partly why (in addition to cost, feasibility,
and seasonality) we limited data collection to every 4
th
month, rather than monthly or more frequently. Given
the young age of participants, it is also possible that they
experience difficulty expressing their feelings during
the qualitative interviews. Our team includes researchers
experienced in conducing in-depth interviews with this
age group and has developed strategies to ease this
process.
Discussion
The MATCH study provides the infrastructure for a re-
search program that will generate better understanding
of how physical activity participation evolves during
childhood and adolescence. Recruiting grade 5 and 6
students and following them throughout adolescence is
motivated by the finding that, for most people, peak
physical activity level occurs between grade 5-7 [79], and
then declines markedly from grade 8-11 [20,21,80-82].
The MATCH study will provide a detailed assessment of
the natural history of physical activity participation in a
period characterised by important changes in behaviour,
growth, and puberty. No study has yet provided such de-
tailed prospective data. Moreover, although the determi-
nants of youth engaging in specific types of physical
activities may vary, few investigations distinguish be-
tween types of physical activity. MATCH will enable in-
vestigating processes of sustaining, interrupting, or
initiating participation in a wide variety of different
physical activities. Particularly, although some studies
have shown strong relationships between different types
of physical activity motives and basic psychological
needs and physical activity, MATCH has the capacity to
tease out why such factors are important for some
people, and if this changes over time and for different
types of physical activities. In addition, the mixed
methods approach enables investigation according to
various theoretical frameworks. We will quantify the im-
portance of se veral potential determ inants of participa-
tion and develop in-depth understanding of how these
determinant s arise and co-occur. This combination of
approaches will allow gaining insight s into processes and
events that lead to behavioural changes while also enab-
ling unexpected questions to occur. All of this will guide
the development of better interventions aimed at in-
creasing and sustaining participation in physical activity
among youth.
Abbreviations
SDT: Self-Determination Theory; MATCH: Monitoring Activities of Teenagers
to Comprehend their Habits.
Competing interests
The authors declare that they have no competing interests.
Authors contributions
MB conceptualized the study and its design. JB, JOL, MM and CS contributed
to the conception of the study and study design. IC and MB organize and
coordinate the data collection process. MB and IC drafted the first version of
this manuscript. All authors reviewed the manuscript for intellectual content
and approved it for publication.
Acknowledgements
The MATCH project is supported by the New Brunswick Health Research
Foundation and by the Social Sciences and Humanities Research Council
and Sport Canada through the joint Sport Participation Research Initiative.
JOL holds a Canada Research Chair in the Early Determinants of Adult
Chronic Disease.
Author details
1
Centre de formation médicale du Nouveau-Brunswick, Pavillon
J.-Raymond-Frenette, 15, rue des Aboiteaux, Moncton, NB, Canada E1A 3E9.
2
Department of family medicine, Université de Sherbrooke, Sherbrooke,
Canada.
3
Research Centre, Vitalité Health Network, Moncton, Canada.
4
Department of social and preventive medicine, Université de Montréal,
Montreal, Canada.
5
Centre de recherche du Centre Hospitalier de lUniversité
de Montréal, Montreal, Canada.
6
Institut national de santé publique du
Québec, Montreal, Canada.
7
Faculty of Kinesiology and Physical Education,
University of Toronto, Toronto, Canada.
8
New Brunswick Health Council,
Moncton, Canada.
Received: 28 June 2013 Accepted: 8 July 2013
Published: 12 July 2013
References
1. Cameron C, Wolfe R, Craig C: Physical activity and sport: encouraging children
to be active. Physical Activity Monitor. Ottawa, Canada: Canadian Fitness and
Lifestyle Research Institute; 2005.
2. Canada S: Canadian Community Health Survey: A first look. Ottawa, Canada:
The Daily; 2002.
3. Colley RC, Garriguet D, Janssen I, Craig CL, Clarke J, Tremblay MS: Physical
activity of Canadian children and youth: accelerometer results from the
2007 to 2009 Canadian Health Measures Survey. Health reports / Statistics
Canada, Canadian Centre for Health Information 2011, 22:1523.
4. Paavola M, Vartiainen E, Haukkala A: Smoking, alcohol use, and physical
activity: a 13-year longitudinal study ranging from adolescence into
adulthood. J Adolesc Health: official publication of the Society for Adolescent
Medicine 2004, 35:238244.
5. Saakslahti A, Numminen P, Varstala V, Helenius H, Tammi A, Viikari J,
Valimaki I: Physical activity as a preventive measure for coronary heart
disease risk factors in early childhood. Scand J Med Sci Sports 2004,
14:143149.
6. Timmons BW, Naylor P-J, Pfeiffer KA: Physical activity for preschool
children - how much and how? Applied Physiology. Nutr Metab 2007,
32:S122S134.
7. Huang JS, Gottschalk M, Norman GJ, Calfas KJ, Sallis JF, Patrick K:
Compliance with behavioral guidelines for diet, physical activity and
sedentary behaviors is related to insulin resistance among overweight
and obese youth. BMC Res Notes 2011, 4:29.
8. Janz KF, Burns TL, Torner JC, Levy SM, Paulos R, Willing MC, Warren JJ:
Physical activity and bone measures in young children: the Iowa bone
development study. Pediatrics 2001, 107:13871393.
9. Specker B, Binkley T: Randomized trial of physical activity and calcium
supplementation on bone mineral content in 3- to 5-year-old children.
J Bone Miner Res: the official journal of the American Society for Bone and
Mineral Research 2003, 18:885892.
10. Son S-H, Meisels SJ: The relationship of young childrens motor skills to
later reading and math achievement. Merrill-Palmer Quarterly: Journal of
Developmental Psychology 2006, 52:755778.
11. Ginsburg KR, of Pediatrics Committee on Communications AA, of Pediatrics
Committee on Psychosocial Aspects of Child AA, Health F: The importance
of play in promoting healthy child development and maintaining strong
parent-child bonds. Pediatrics 2007, 119:182191.
Bélanger et al. BMC Public Health 2013, 13:649 Page 5 of 7
http://www.biomedcentral.com/1471-2458/13/649
12. Burdette HL, Whitaker RC: Resurrecting free play in young children:
looking beyond fitness and fatness to attention, affiliation, and affect.
Arch Pediatr Adolesc Med 2005, 159:4650.
13. Calfas KJ, Taylor WC: Effects of Physical Activity on Psychological Variables
in Adolescents. Pediatr Exerc S ci 1994, 6:406423.
14. Klesges RC, Klesges LM, Eck LH, Shelton ML: A longitudinal analysis of
accelerated weight gain in preschool children. Pediatrics 1995,
95:126130.
15. Moore LL, Nguyen US, Rothman KJ, Cupples LA, Ellison RC: Preschool
physical activity level and change in body fatness in young children. The
Framingham Childrens Study. Am J Epidemiol 1995, 142:982988.
16. Strong WB, Malina RM, Blimkie CJ, Daniels SR, Dishman RK, Gutin B,
Hergenroeder AC, Must A, Nixon PA, Pivarnik JM, Rowland T, Trost S,
Trudeau F: Evidence based physical activity for school-age youth.
J Pediatr 2005, 146:7327.
17. Aaron DJ, Storti KL, Robertson RJ, Kriska AM, Laporte RE: Longitudinal Study
of the Number and Choice of Leisure Time Physical Activities From Mid
to Late Adolescence. Arch Pediatr Adolesc Med 2002, 156:10751080.
18. Bélanger M, Gray-Donald K, OLoughlin J, Paradis G, Hanley J: When
Adolescents Drop the Ball: Sustainability of Physical Activity in Youth.
Am J Prev Med 2009, 37:4149.
19. Dovey SM, Reeder AI, Chalmers DJ: Continuity and change in sporting and
leisure time physical activities during adolescence. Br J Sports Med 1998,
32:5357.
20. Van Mechelen W, Twisk JWR, Post GB, Snel J, Kemper HCG: Physical Activity
of Young People: The Amsterdam Longitudinal Growth and Health
Study. Med Sci Sports Exerc 2000, 32:16101616.
21. Telama R, Yang X: Decline of Physical Activity from Youth to Young
Adulthood in Finland. Med Sci Spor ts Exerc 2000, 32:16171622.
22. Kjonniksen L, Torsheim T, Wold B: Tracking of leisure-time physical activity
during adolescence and young adulthood: a 10-year longitudinal study.
Int J Behav Nutr Phys Act 2008, 5:
69.
23. Stanley RM, Ridley K, Olds TS: The type and prevalence of activities
performed by Australian children during the lunchtime and after school
periods. J Sci Med Sport 2011, 14:227232.
24. Pate RR, Sallis JF, Ward DS, Stevens J, Dowda M, Welk GJ, Young DR, Jobe
JB, Strikmiller PK: Age-Related Changes in Types and Contexts of Physical
Activity in Middle School Girls. Am J Prev Med 2010, 39:433439.
25. Grieser M, Vu MB, Bedimo-Rung AL, Neumark-Sztainer D, Moody J, Young
DR, Moe SG: Physical Activity Attitudes, Preferences, and Practices in
African American, Hispanic, and Caucasian Girls. Health Educ Behav 2006,
33:4051.
26. Erwin HE: Middle School Students Leisure Activity Engagement:
Implications for Park and Recreation Administrators. J Park and Recreation
Adm 2008, 26:5974.
27. Wall MI, Carlson SA, Stein AD, Lee SM, Fulton JE: Trends by Age in Youth
Physical Activity: Youth Media Campaign Longitudinal Survey.
Med Sci Sports Exerc 2011, 43:21402147.
28. Duncan SC, Duncan TE, Strycker LA, Chaumeton NR: A Cohort-Sequential
Latent Growth Model of Physical Activity from Ages 12-17 Years.
Ann Behav Med 2007, 33:8089.
29. Bélanger M, Gray-Donald K, OLoughlin J, Paradis G, Hutcheon J, Maximova
K, Hanley J: Participation in organised sports does not slow declines in
physical activity during adolescence. Int J Behav Nutr Phys Act 2009, 6:22.
30. Findlay L, Garner R, Kohen D: Patterns of Childrens Participation in
Unorganized Physical Activity. Res Q Exerc Sport 2010, 81:133.
31. Bélanger M, Townsend N, Foster C: Age-related differences in physical
activity profiles of English adults. Prev Med 2011, 52:247249.
32. Lunn PD: The sports and exercise life-course: A survival analysis of recall
data from Ireland. Soc S ci Med 2010, 70:711719.
33. Sallis JF, Prochaska JJ, Taylor WC: A review of correlates of physical activity
of children and adolescents. Med Sci Sports Exerc 2000, 32:
96375.
34. Van Der HK, Paw MJ, Twisk JW, Van MW: A brief review on correlates of
physical activity and sedentariness in youth. Med Sci Sports Exerc 2007,
39:12411250.
35. Lubans DR, Foster C, Biddle SJ: A review of mediators of behavior in
interventions to promote physical activity among children and
adolescents. Prev Med 2008, 47:463470.
36. Vilhjalmsson R, Kristjansdottir G: Gender differences in physical activity in
older children and adolescents: the central role of organized sport.
Soc Sci Med 2003, 56:363374.
37. Bradley CB, McMurray RG, Harrell JS, Deng S: Changes in common
activities of 3rd through 10th graders: the CIHC study. Med Sci Sports
Exerc 2000, 32:19752153.
38. Nelson MC, Neumark-stzainer D, Hannan PJ, Sirard JR, Story M: Longitudinal
and Secular Trends in Physical Activity and Sedentary Behavior During
Adolescence. Pediatrics 2006, 118:16271634.
39. Allender S, Cowburn G, Foster C: Understanding participation in sport and
physical activity among children and adults: a review of qualitative
studies. Health Educ Res 2006, 21:826835.
40. Bray SR, Born HA: Transition to university and vigorous physical activity:
implications for health and psychological well-being. J Am College Health :
J of ACH 2004, 52:181188.
41. Eime RM, Payne WR, Casey MM, Harvey JT: Transition in participation in
sport and unstructured physical activity for rural living adolescent girls.
Health Educ Res 2010, 25:282293.
42. Coleman L, Cox L, Roker D: Girls and young womens participation in
physical activity: psychological and social influences. Health Educ Res
2008, 23:633647.
43. Bélanger M, Casey M, Cormier M, Filion AL, Martin G, Aubut S, Chouinard P,
Savoie S-P, Beauchamp J: Maintenance and decline of physical activity
during adolescence: insights from a qualitative study. Int J Behav Nutr
Phys Act 2011, 8:117.
44. Teixeira P, Carraca E, Markland D, Silva M, Ryan R: Exercise, physical activity,
and self-determination theory: a systematic review. Int J Behav Nutr Phys
Act 2012, 9:78.
45. Ryan R, Deci E: Self-determination theory and the facilitation of intrinsic
motivation, social development, and well-being. Am Psychol 2000,
55:6878.
46. Ryan R: Deci, E: Self-determination theory: A macrotheory of human
motivation, development, and health. Can Psychol 2008, 49:182185.
47. Resnicow K, Page SE: Embracing chaos and complexity: a quantum
change for public health. Am J Public Health 2008, 98:13829.
48. Belanger M, Gray-Donald K, OLoughlin J, Paradis G, Hanley J: Influence of
weather conditions and season on physical activity in adolescents.
Ann Epidemiol 2009, 19:180186.
49. Craig C, Cameron C, Russell S, Beaulieu A: Increasing Physical Activity
Participation: Supporting Childrens Participation. Ottawa, Ont: Canadian
Fitness and Lifestyle Research Institute; 2001.
50. Sallis JF, Condon SA, Goggin KJ, Roby JJ, Kolody B, Alcaraz JE: The
development of self-administered physical activity surveys for 4th grade
students. Res Q Exerc Sport 1993, 64:3238.
51. Crocker PRE, Bailey DA, Faulkner RA, Kowalski KC, McGrath R: Measuring
general levels of physical activity: preliminary evidence for the Physical
Activity Questionnaire for older children. Med Sci Sports Exerc 1997,
29:13441349.
52. Janz KF, Lutuchy EM, Wenthe P, Levy SM: Measuring Activity in Children
and Adolescents Using Self-Report: PAQ-C and PAQ-A. Med Sci Sports
Exerc 2008, 40:767772.
53. Prochaska JJ, Sallis JF, Long B: A physical activity screening measure for
use with adolescents in primary care. Arch Pediatr Adolesc Med 2001,
155:554559.
54. McAuley E, Duncan T, Tammen VV: Psychometric properties of the
Intrinsic Motivation Inventory in a competitive sport setting: a
confirmatory factor analysis. Res Q Exerc Sport 1989, 60:4858.
55. Gagné M: The role of autonomy support and autonomy orientation in
prosocial behavior engagement. Motivation and Emotion 2003,
27:199223.
56. Ntoumanis N: A Prospective Study of Participation in Optional School
Physical Education Using a Self-Determination Theory Framework.
J Educ Psychol 2005, 97:444453.
57. Wilson PM, Bengoechea EG: The Relatedness to Others in Physical Activity
Scale: Evidence for structural and criterion validity. J Appl Biobehav Res
2010, 15:6187.
58. Ryan RM, Frederick CM, Lepes D, Rubio N, Sheldon KM: Intrinsic Motivation
and Exercise Adherence. Int J Sport Psychol 1997, 28:335354.
59. Wong SL, Leatherdale ST, Manske SR: Reliability and Validity of a School-
Based Physical Activity Questionnaire. Med Sci Sports Exerc 2006,
38:15931600.
60. Schmitz KH, Harnack L, Jr DR J, Gao S, Lytle LA, Van Coevering P, Fulton JE:
Reliability and Validity of a Brief Questionnaire to Assess Television
Viewing and Computer Use. J Sch Health 2004, 74:370377.
Bélanger et al. BMC Public Health 2013, 13:649 Page 6 of 7
http://www.biomedcentral.com/1471-2458/13/649
61. Utter J, Neumark-Sztainer D, Jeffery R, Story M: Couch potatoes or french
fries: are sedentary behaviors associated with body mass index, physical
activity, and dietary behaviors among adolescents? J Am Diet Assoc 2003,
103:12981305.
62. Neumark-Sztainer D, Story M, Hannan PJ, Perry CL, Irving LM: Weight-related
concerns and behaviors among overweight and nonoverweight
adolescents: implications for preventing weight-related disorders.
Arch Pediatr Adolesc Med 2002, 156:171178.
63. Wolfson AR, Carskadon MA: Sleep schedules and daytime functioning in
adolescents. Child Dev 1998, 69:875887.
64. Petersen AC, Crockett L, Richards M, Boxer A: A self-report measure of
pubertal status: Reliability, validity, and initial norms. J Youth Adolesc
1988, 17:117133.
65. Carskadon MA, Acebo C: A self-administered rating scale for pubertal
development. J Adolesc Health: official publication of the Society for
Adolescent Medicine 1993, 14:190195.
66. Park S, Blanck H, Sherry B, Brener N, OToole T: Factors associated with
sugar-sweetened beverage intake among United States high school
students. J Nutr 2012, 142:306312.
67. Taylor H, Jacobs D, Schucker B, Knudsen J, Leon A, Debacker G: A
questionnaire for the assessment of leisure time physical activities.
J Chronic Dis 1978, 31:741755.
68. Rosenberg D, Ding D, Sallis JF, Kerr J, Norman GJ, Durant N, Harris SK,
Saelens BE: Neighborhood Environment Walkability Scale for Youth
(NEWS-Y): reliability and relationship with physical activity. Prev Med
2009, 49:213218.
69. Haug E, Torsheim T, Samdal O: Physical environmental characteristics and
individual interests as correlates of physical activity in Norwegian
secondary schools: the health behaviour in school-aged children study.
Int J Behav Nutr Phys Act 2008, 5:47.
70. Beyers J, Vaillancourt J, Murkin E, Etches V, Kroeker C, Manske S, Leatherdale
S, Sabiston C: In Development of the School Health Environment Survey
(SHES). Edited by Centre for Behavioral Research and Program Evaluation.
Waterloo, Ontario: University of Waterloo; 2006.
71. Manske S: In Pilot Phase of the 2007-2008 School Health Environment Survey:
Technical Report. Edited by Centre for Behavioral Research and Program
Evaluation. Waterloo, Ontario: University of Waterloo; 2008.
72. Smith DW: Phenomenology. Fall 2011. Stanford, CA: Stanford Encyclopedia of
Philosophy; 2011.
73. Benner P:
Quality of life: a phenomenological perspective on
explanation, prediction, and understanding in nursing science.
ANS Adv Nurs Sci 1985, 8:114.
74. Poifroni E, W M: Perspective on Philosophy of Science in Nursing: An Historical
and Contemporary Anthology. Washington: Lippincott.
75. Husserl E: Logical Investigations. New York: Humanities Press; 1970.
76. Plummer K: Documents of Life: An Introduction to the Problems and Literature
of a Humanistic Method. London: Unwin Hyman; 1983.
77. Stanley L, Wise S: Breaking Out Again : Feminist Ontology and Epistemology.
London: Routledge; 1993:264.
78. Charmaz K: Constructing Grounded Theory: A Practical Guide Through
Qualitative Analysis. Thousand Oaks, CA: Sage Publications; 2006.
79. Kahn JA, Huang B, Gillman MW, Field AE, Austin SB, Colditz GA, Frazier AL:
Patterns and determinants of physical activity in U.S. adolescents.
J Adolesc Health: official publication of the Society for Adolescent Medicine
2008, 42:369377.
80. Allison KR, Adlaf EM: Age and sex differences in physical inactivity among
Ontario teenagers. Canadian J Public Health 1997, 88:177180.
81. Allison KR, Adlaf EM, Dwyer JJ, Lysy DC, Irving HM: The decline in physical
activity among adolescent students: a cross-national comparison.
Canadian J Public health 2007, 98:97100.
82. Caspersen CJ, Pereira MA, Curran KM: Changes in physical activity patterns
in the United States, by sex and cross-sectional age. Med Sci Sports Exer
2000, 32:1601 1609.
doi:10.1186/1471-2458-13-649
Cite this article as: Bélanger et al.: Monitoring activities of teenagers to
comprehend their habits: study protocol for a mixed-methods cohort
study. BMC Public Health 2013 13:649.
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... However, for some behaviours, the relationship remains unclear. While one cross-sectional study among 15,283 Texan middle and high school students found that sugary beverages were associated with increased consumption of unhealthy foods (e.g., unhealthy meats, fried snacks, desserts), this study also found that soda intake was associated with lower consumption of vegetables and fruits, while flavoured and sports drinks were associated with a greater vegetable and fruit intake [11]. ...
... This study used data collected from 937 children (mean age 10.8 years old, in Grades 5 and 6 at study inception) recruited from 17 elementary schools in New Brunswick, Canada for the Monitoring Activities for Teenagers to Comprehend their Habits (MATCH) longitudinal study [15]. Detailed information on the MATCH study protocol has been published elsewhere [15], but briefly, students completed a self-reported questionnaire three times per academic year, over 8 years from 2011 to 2019. ...
... This study used data collected from 937 children (mean age 10.8 years old, in Grades 5 and 6 at study inception) recruited from 17 elementary schools in New Brunswick, Canada for the Monitoring Activities for Teenagers to Comprehend their Habits (MATCH) longitudinal study [15]. Detailed information on the MATCH study protocol has been published elsewhere [15], but briefly, students completed a self-reported questionnaire three times per academic year, over 8 years from 2011 to 2019. They came from schools selected to represent geographical (i.e., rural and urban), and cultural (i.e., French and English) diversity. ...
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Adolescence represents a critical transition phase during which individuals acquire eating behaviours that can track into adulthood. This study aims to characterise trends in eating behaviours throughout adolescence by investigating the presence of sub-groups of individuals presenting distinct trajectories of vegetable and fruit, sugary beverage, breakfast and fast-food consumption. Data from 744 MATCH study Canadian participants followed from 11 to 18 Years old (2013–2019) were included in the analyses. Participants reported how often they ate breakfast and consumed vegetables and fruits, sugary beverages and fast foods. Trajectories of eating behaviours over seven years were identified using group-based multi-trajectory modelling. For girls, three different groups were identified, namely ‘stable food intake with a decline in daily breakfast consumption’ (39.9%), ‘moderate food intake and worsening in overall eating behaviours’ (38.0%) and ‘stable high food intake’ (22.1%). For boys, five different groups were identified, namely ‘low food intake with stable daily breakfast consumption’ (27.3%), ‘breakfast-skippers and increasing fast food intake’ (27.1%), ‘low food intake with a decline in daily breakfast consumption’ (23.9%), ‘high food intake with worsening of eating behaviours’ (13.3%) and ‘average food intake with consistently high breakfast consumption’ (8.4%). Eating behaviours evolve through various distinct trajectories and sub-group-specific strategies may be required to promote healthy eating behaviours among adolescents.
... The MATCH study is an ongoing longitudinal prospective study in the province of New Brunswick, Canada. The complete study protocol is provided in Bélanger et al. [51]. Briefly, a convenience sample of 19 schools were recruited, and it included both French-and English-speaking students from a range of socioeconomic neighborhoods located in both rural and urban areas. ...
... The same respondents were asked to complete self-report questionnaires three times per year (fall, winter, and spring) at four-month intervals, which were combined to capture seasonal variations in one year of physical activity participation [6,51,53]. The first eight years of the MATCH study were used for the current analysis (n = 24 cycles). ...
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Despite their prevalence, the longitudinal impacts of relative age effects (RAEs) on sport and other forms of physical activity (PA) are understudied. This study examined longitudinal participation patterns in organized sport (team and individual), unorganized PA, and non-participation with respect to RAEs in a prospective cohort of adolescents. Data from the first 24 cycles of the MATCH study were used for analyses. Elementary students (n = 929) were recruited from 17 schools in Atlantic Canada. Respondents self-reported PA three times/year. Mixed multilevel logistic models compared the likelihood of participating in each context across birth quarter. Chronological age and gender were considered, along with the interaction between chronological and relative age. Individuals born in Quarter 1/Quarter 2 were more likely to report participation in organized team sport but not individual sports. Relatively older participants born in Quarter 2 were more likely to report participation in unorganized PA. Increasing chronological age was associated with decreased participation in organized sport (particularly team-based) and increased non-participation. Gender was not associated with organized sport participation, but girls were under-represented in unorganized PA and more likely to report non-participation. The interaction parameters suggested that RAEs were consistent throughout adolescence in each context. Longitudinal analyses suggest RAEs are context dependent.
... The Monitoring Activities for Teenagers to Comprehend their Habits (MATCH) longitudinal study involved 937 students (aged 10-11 years old at baseline) from 17 elementary schools in New Brunswick, Canada (Belanger et al., 2013). Detailed information on the MATCH study is available elsewhere (Belanger et al., 2013;Doggui et al., 2021) and is only briefly described herein. ...
... The Monitoring Activities for Teenagers to Comprehend their Habits (MATCH) longitudinal study involved 937 students (aged 10-11 years old at baseline) from 17 elementary schools in New Brunswick, Canada (Belanger et al., 2013). Detailed information on the MATCH study is available elsewhere (Belanger et al., 2013;Doggui et al., 2021) and is only briefly described herein. Schools were selected to represent geographical (i.e. ...
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Beverages contribute substantially to daily energy and nutrient intakes. However, little is known about the co-development of beverage consumption throughout adolescence. This study aimed to investigate the presence of naturally occurring sub-groups of girls and boys following distinct trajectories of various types of beverage consumption (i.e. sugary beverages, tea and coffee, water, and milk) throughout adolescence. During the Monitoring Activities for Teenagers to Comprehend their Habits study, data were collected from 744 Canadian youths followed for six years (2013–2019). The participants were asked yearly (start-age 10–11 years old) to report how many times they consumed sugary beverages, tea and coffee, water, and milk in a week. Trajectories of beverage consumption were identified from age 11 to 18 using a person-centred approach, namely group-based multi-trajectory modelling. For girls, three different groups were identified: ‘Water consumers’ (62.7%), ‘High beverage consumers’ (20.9%), and ‘Water and milk consumers’ (16.4%). For boys, four different groups were identified: ‘Water consumers’ (39.1%), ‘Water and milk consumers’ (30.5%), ‘Sugary drinks, coffee and tea consumers’ (20.1%), and ‘High beverage consumers’ (10.4%). This study illustrates the complexity of beverage consumption patterns in adolescence. Various types of public health messaging and interventions may be required to promote healthier beverage consumption patterns among all adolescents.
... Data were derived from the longitudinal "Monitoring Activities of Teenagers to Comprehend their Habits" (MATCH) study. (Bélanger et al., 2013) At study inception, English-and Frenchspeaking grade 5 and grade 6 students were recruited from a convenient sample of 17 schools in New Brunswick, Canada. Efforts were made to recruit schools that were situated in a mix of rural and urban areas representing diverse socio-economic backgrounds. ...
... (Brislin, 1970;Chapman & Carter, 1979) Specifically, items were translated from English to French, back-translated to English, and then pilot tested with 12 French and English grade 5 and 6 students, which served to confirm that the questionnaire was comprehensible in both languages. (Bélanger et al., 2013) Participants were asked to report the extent to which 30 items representing PA motives were true for them using a 7-point Likert-type scale, with 1 representing "not at all true for me" and 7 representing "very true for me." In theory, the MPAM-R includes 7 items assessing enjoyment motives (e.g., "because it makes me happy"), 7 items assessing competence motives (e.g., "because I want to improve existing skills"), 5 items assessing social motives (e.g., "because I want to be with friends"), 5 items assessing fitness motives (e.g., "because I want be physically fit"), and 6 items assessing appearance motives (e.g., "because I want to lose or maintain weight to look better"). ...
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This study examined the longitudinal associations between five physical activity (PA) motives and moderate-to-vigorous PA (MVPA) across a 5-year period spanning late childhood to middle adolescence. METHODS: Data (n = 937; 55% girls; mean age = 10.33 years) were drawn from the Monitoring Activities for Teenagers to Comprehend their Habits study. PA motives and MVPA were assessed 15 times over the course of 5 years. Measurement invariance for the Motives for Physical Activity Measure-Revised (MPAM-R) questionnaire was established, and sex-stratified mixed-effects regression models were analysed. MVPA increased until a mean age of 12.18 years for girls and 12.89 years for boys before decreasing through the final assessment. From late childhood to middle adolescence, for boys, enjoyment motives were positively (β(95% CI) = 6.14(3.86–8.43)), while fitness motives were negatively (β(95% CI) = −4.80(−8.0, −1.59)) associated with MVPA. Whereas, for girls, competence motives were positively β(95% CI) = 3.44(1.59–5.28)) associated with MVPA Boys may benefit from PA interventions, if these were primarily aimed at increasing ones’ enjoyment, whereas developing a girl’s competence may provide greater contributions to a girl’s future PA behaviours. PA interventions should avoid promoting the desire to be active to improve fitness, particularly among boys.
... The Monitoring Activities of Teenagers to Comprehend their Habits (MATCH) study [21], is an ongoing prospective study designed to describe the natural development of PA patterns of youth and identify their determinants. The MATCH study was designed to include a mix of students from schools from low, middle, and higher socioeconomic status in a variety of urban, suburban, and rural settings in French and English regions of New Brunswick. ...
... rural or urban) and cultural backgrounds (i.e. French or English language) [21]. ...
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... Comprehend their Habits (MATCH) study, an ongoing prospective longitudinal study designed J o u r n a l P r e -p r o o f to investigate patterns of participation in physical activity among youth in New Brunswick, Canada [36]. A total of 937 children (55.2% girls) were recruited over the first four years of the study and data were collected through self-report questionnaires every four months for eight years starting in Fall 2011. ...
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Body image is a commonly-reported factor perpetuating declines in physical activity levels during adolescence. However, the evidence is predominantly qualitative, cross-sectional, and focused on females. Furthermore, the affective dimension of body image has been overlooked compared to the perceptual (e.g., misrepresentations of body size) and cognitive (e.g., dissatisfaction) dimensions. Affective body image includes a range of self-conscious emotions including guilt, shame, envy, embarrassment, and authentic and hubristic pride. This study examined (i) body-related self-conscious emotions over time, and (ii) associations between body-related emotions and physical activity over five years during early-to-mid adolescence. Potential gender differences were also explored. Self-report data for this study were collected once a year over 5 years as part of the MATCH study. The main analyses involved mixed-effects modeling. Participants (n = 776, 55.8% female) initially aged 12.6 (SD = 0.6) years who provided data on at least one occasion were included in the analysis. Females reported higher body-related guilt, shame, envy, and embarrassment than males, and males reported higher hubristic pride than females. Over five years from early to mid-adolescence, body-related shame, guilt, envy, and embarrassment significantly increased for boys and girls, authentic pride did not change, and hubristic pride increased for girls only. Controlling for gender and puberty status, body-related guilt, shame, and embarrassment were negatively, and body-related authentic and hubristic pride were positively, associated with physical activity over time. Body-related envy was not significantly related to physical activity. These findings suggest that adolescents’ express greater negative body-related self-conscious emotions over time. Since these were negatively related to physical activity, interventions focused on reducing negative body-related emotions and enhancing positive body-related emotions may be valuable in adolescence to help curb declining physical activity.
... Participants' data were grouped by schoolgrade (e.g., grade 5, grade 6., etc.) to provide a comprehensive understanding of yearly sport involvement. Detailed methodology for the MATCH study is reported elsewhere (Bélanger et al., 2013). The MATCH study received ethical approval by the Université de Sherbrooke research ethics committee. ...
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Few studies describe sport participation profiles in the general population using multiple characteristics. Therefore, the objective of this study was to identify sport participation profiles during adolescence and to describe transitions across profiles from grades 5 to 12 (age 10 to 18 years). We used data from 916 participants (55% girls; age 10–12 years at inception) of the Monitoring Activities of Teenagers to Comprehend their Habits (MATCH) study. Participants self-reported involvement in 36 organized and unorganized physical activities three times/year from grades 5 to 12 (24 data collection cycles; 2011–2018). At each school grade, we derived four categorical variables of sport involvement: number of organized sports, number of unorganized activities, weekly sessions, and number of year-round activities. To identify sport participation profiles, we used latent class analysis at each grade. To characterize transitions between sport participation profiles across grades, we used latent transition analysis. Five distinct sport participation profiles emerged: “non-participants”, “unorganized activities only”, “single-sport low frequency”, “single sport high frequency”, and “multi-sport”. Only “multi-sport” participants were unlikely to be classified as “non-participants” over time. Encouraging multi-sport participation might help protect against later non-participation. This study helps identify important times to intervene for improving physical activity levels.
... MATCH methods are reported in more detail elsewhere. 30 Ethics approval was obtained from the Université de Sherbrooke ethics committee. All participants provided written informed assent and their parents provided written informed consent. ...
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The Pediatric Collections: Sports Medicine Playbook will increase pediatric providers’ understanding of the injuries that young athletes may incur – including their history, treatment, and prevention. Each section includes a unique expert introduction and they cover such topics as the benefits of physical activity, injuries, and concerns including concussions. Available for purchase at https://shop.aap.org/pediatric-collections-sports-medicine-playbook-paperback/
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Physical activity (PA) motives are associated with both moderate‐to‐vigorous intensity PA (MVPA) and mental health. Studies examining whether PA motives relate directly to mental health or indirectly through MVPA are lacking. This study examined the direct effect of five PA motives (i.e., enjoyment, competence, fitness, social, appearance) on mental health and their indirect effects through MVPA in adolescents. A total of 424 participants (57.1% females) ages 14‐15 years from the longitudinal MATCH study were included. Mediation analyses, based on the counterfactual framework, assessed the natural direct effect of PA motives on mental health, and the natural indirect effects through MVPA. Separate models were conducted for each PA motive. Natural direct effects were observed for enjoyment (β̂[95%CI] = 2.12 [0.34,3.90]), competence (β̂[95%CI] = 1.58[0.28, 2.88]), fitness (β̂[95%CI] = 1.42[0.04, 2.80]) and social (β̂[95%CI] = 2.32[1.03, 3.60]) motives. No natural direct effects were observed for appearance motives. A natural indirect effect through MVPA was observed for fitness motives, and no other natural indirect effects were found. Interventions and public health strategies in adolescents need to acknowledge the importance of enjoyment, competence social and fitness motives in PA to promote mental health, and integrate specific recommendations on the importance of the reasons why adolescents participate in PA.
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We examined whether changes in social context (i.e., frequency with which youth engage in physical activity [PA] alone, with teammates, with friends, with siblings, or with parents/grandparents) is associated with change in moderate-to-vigorous intensity PA (MVPA) across Grades 5–8 and Grades 8–11 (N = 938). Data were self-reported annually. Across Grades 5–8, the frequency of PA in all social contexts declined over time, and changes in the frequency of PA alone, with teammates, with siblings, and in diversity of PA companion types were positively associated with change in MVPA. Across Grades 8–11, the frequency of PA with siblings, friends, and parents/grandparents declined over time, and changes in the frequency of PA alone, with teammates, with friends, and with parents/grandparents, and in diversity of PA companion types were positively associated with change in MVPA. PA social contexts vary in how they associate with change in MVPA in youth over time.
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Background Physical activity is an important determinant of health and fi tness. This study provides contemporary estimates of the physical activity levels of Canadians aged 6 to 19 years. Data and methods Data are from the 2007 to 2009 Canadian Health Measures Survey. The physical activity of a nationally representative sample was measured using accelerometers. Data are presented as time spent in sedentary, light, moderate and vigorous intensity movement, and in steps accumulated per day. Results An estimated 9% of boys and 4% of girls accumulate 60 minutes of moderate-to-vigorous physical activity on at least 6 days a week. Regardless of age group, boys are more active than girls. Canadian children and youth spend 8.6 hours per day-62% of their waking hours-in sedentary pursuits. Daily step counts average 12,100 for boys and 10,300 for girls. Interpretation Based on objective and robust measures, physical activity levels of Canadian children and youth are low.
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Background Physical activity (PA) declines during adolescence. There has been little research describing this decline or examining participation and nonparticipation in specific activities.Objective To describe the pattern of change in the number of physical activities, the time spent on specific activities, and the stability of participation and nonparticipation in specific activities during adolescence.Design and Setting A population-based 4-year longitudinal study of adolescents recruited from a single suburban school district near Pittsburgh, Pa.Participants A total of 782 adolescents, aged 12 to 15 years at baseline.Main Outcome Measures Physical activity was measured annually via questionnaire. Outcome measures include hours per week of PA, number of reported activities, and participation (yes or no) in specific activities.Results Physical activity declined during the 4 years by 26%. The decline in PA was primarily due to a decrease in the number of reported activities. Adolescents who continued to report an activity during the 4 years of the study maintained or increased the time spent on that specific activity. Female adolescents were more likely to report individual activities, while male adolescents were more likely to report team activities. The probability of maintaining participation in a specific activity during the 4 years was low to moderate, 0.02 to 0.47 for female adolescents and 0.04 to 0.71 for male adolescents. The probability of not participating in a specific activity during the 4 years was extremely high and consistent for male and female adolescents, 0.70 to 1.00.Conclusions The decline in PA during adolescence is primarily due to a decrease in the number of activities in which the adolescent is participating, and there is only a moderate probability that an adolescent will continue to participate in an activity during the 4-year period from junior to senior high. Future efforts should be directed at identifying factors associated with initiating and maintaining participation in specific activities.
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Objectives To assess weight-related concerns and behaviors in a population-based sample of adolescents and to compare these concerns and behaviors across sex and weight status.Design The study population included 4746 adolescents from St Paul or Minneapolis, Minn, public schools who completed surveys and anthropometric measurements as part of Project EAT (Eating Among Teens), a population-based study focusing on eating patterns and weight concerns among teenagers.Main Outcome Measures Measured weight status, weight-related concerns (perceived weight status, weight disparity, body satisfaction, and care about controlling weight), and weight-related behaviors (general and specific weight control behaviors and binge eating).Results Weight-related concerns and behaviors were prevalent among the study population. Although adolescents were most likely to report healthy weight control behaviors (adolescent girls, 85%; and adolescent boys, 70%), also prevalent were weight control behaviors considered to be unhealthy (adolescent girls, 57%; and adolescent boys, 33%) or extreme (adolescent girls, 12%; and adolescent boys, 5%). Most overweight youth perceived themselves as overweight and reported the use of healthy weight control behaviors during the past year. However, the use of unhealthy and extreme weight control behaviors and binge eating were alarmingly high among overweight youth, particularly adolescent girls. Extreme weight control practices (taking diet pills, laxatives, or diuretics or vomiting) were reported by 18% of very overweight adolescent girls, compared with 6% of very overweight adolescent boys (body mass index, ≥95th percentile).Conclusion Prevention interventions that address the broad spectrum of weight-related disorders, enhance skill development for behavioral change, and provide support for dealing with potentially harmful social norms are warranted in light of the high prevalence and co-occurrence of obesity and unhealthy weight-related behaviors.
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To identify the most consistent relationships among psychological variables and physical activity in youth (ages 11-21 years), 20 articles on depression, anxiety, stress, self-esteem, self-concept, hostility, anger, intellectual functioning, and psychiatric disorders were reviewed. Physical activity was consistently related to improvements in self-esteem, self-concept, depressive symptoms, and anxiety/stress. The effect sizes were +.12, -.15, and -.38 for self-esteem/self-concept, stress/anxiety, and depression, respectively. The evidence for hostility/anger and academic achievement was inconclusive. No negative effects of physical activity were reported. The literature suggests that physical activity in youth is psychologically beneficial. More research is needed to confirm previous findings. Adolescents should engage in moderate or vigorous aerobic activity approximately three times per week for a total of at least 60 minutes per week.
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The grounded theory approach to doing qualitative research in nursing has become very popular in recent years. I confess to never really having understood Glaser and Strauss' original book: The Discovery of Grounded Theory. Since they wrote it, they have fallen out over what grounded theory might be and both produced their own versions of it. I welcomed, then, Kathy Charmaz's excellent and practical guide.
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Objective To describe the demographic characteristics of adolescent boys and girls who engage in three sedentary behaviors (television/video use, computer use, and reading/homework), and to explore how each sedentary activity is associated with body mass index (BMI), dietary behaviors, and leisure time physical activity. Design This study draws on data collected from Project EAT (Eating Among Teens), a school-based survey examining personal, behavioral, and socioenvironmental factors-that are associated with nutritional intake among adolescents. Subjects The study sample consists of 4,746 middle and high school students from 31 public schools in a metropolitan area of the upper Midwest. All students were invited to participate. The overall response rate for Project EAT was 81.5%. Data collection was completed during the 1998-1999 school year. Statistical analyses Multivariate linear regression was used for examining associations between independent and dependent variables, controlling for age, race/ethnicity, and socioeconomic status. All differences were considered statistically significant at P<.05. Results Among boys, television/video use and time spent reading/doing homework were positively associated with BMI (P-.<05), whereas for girls television/video and computer use were positively associated with BMI (P<.05). High television/ video use among boys and girls was associated with more unhealthful dietary behaviors (eg, increased consumption of soft drinks, fried foods, and snacks) (P<.05). In contrast, time spent reading/doing homework was associated with more healthful dietary behaviors (eg, increased consumption of fruits and vegetables) (P<.05). Leisure time physical activity was not associated with television/video use among boys or girls, but was positively associated with computer use and time spent reading/doing homework (P<.05). Applications/Conclusions Messages and advice aimed at reducing time spent in sedentary activities should be targeted at television/video use instead of time spent reading, doing homework, or using a computer. Nutrition education should incorporate messages about the influence of the media and advertising on dietary behaviors.
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Two prospective studies tested the hypothesis that intrinsic motives for physical activities facilitate long-term adherence. In Study 1, participants in two physical activity classes, Tae Kwon Do and Aerobics (N = 40), were compared in their motives for participating using the Motivation for Physical Activity Measure (MPAM; Frederick & Ryan, 1993). Participation motives were also used to predict adherence. Results showed that Tae Kwon Do participants were higher in enjoyment and competence motives and lower in body-related motives than those in aerobics. They also showed better adherence. Further analyses revealed that group differences in adherence were mediated by enjoyment motives. Body-focused motives were unrelated to adherence. In Study 2, subjects joining a nautilus center (N-155) rated their initial motives on a revised Motivation for Physical Activity Measure (MPAM-R). They also rated workout length, challenge, and enjoyment after each exercise session. Results revealed that adherence was associated with motives focused on enjoyment, competence, and social interaction, but not with motives focused on fitness or appearance. Post-workout ratings of enjoyment also predicted adherence. Discussion focuses on the importance of intrinsic motivation for exercise adherence.