Observational Measures of Children’s Physical Activity Thomas L. McKenzie
D
irect observation in natural settings has had a long history. Various systems are available for studying children’s physical activity as it relates to health. Recent technological advances permitting complex observational codes to be entered, stored, and analyzed by portable computers makes this method appealing for assessing children’s physical activity.2 It is important to distinguish between physical activity and energy expenditure. Physical activity refers to body movement, while energy expenditure results from body movement. A lean child and an obese child may engage in the same physical activity, such as walking a mile, but experience different levels of energy expenditure from that activity. Systematic observation is a valid method for obtaining data from a physical activity from natural settings because it requires little inference. Observational procedures are flexible and permit researchers and practitioners to quantify diverse dimensions related to children’s physical activity. Children engage in activity relative to many different environmental factors such as location, presence of others, facilities, availability of toys and equipment, and whether the setting provides for free play or structured activity. Systematic observation allows the study of these contextual variables with limited response burden on participants. Systematic observation of children’s physical activity is an important method in health-related research, supervision, and curriculum development. Observation of children’s physical activity can be used as either a process or outcome measure. Information on both independent and dependent variables can be obtained through observation. Frequently, both researchers and practitioners can use the same instruments. Direct observation of children’s physical activity does have disadvantages. Events studied must be observable and codable, and are thereby limited to events seen or heard. Observers or video-recorders need to be in the environment where behaviors of interest occur, thereby limiting situations where data can be collected. Observers must be properly trained to be rigidly objective, and not to be evaluative or judgmental about what they see. Observers also must be trained to reduce subject reactivity caused by observers being present in the observational environment. Substantial time and effort are needed to develop the observational system, prepare coding conventions, and train observers. Substantial observation time in the natural setting also is needed to validate instruments and to obtain sufficient data to permit generalization of results to other settings and populations. The necessity of a human observer being present to code data means that relative to other methods of measurement, direct observation is costly. This article reviews systematic observation instruThomas L. McKenzie, PhD, Dept. of Physical Education, San Diego State University, San Diego, CA 92182. This work was supported, in part, by NIH grants HL3SlO9 and HL 44467.
224 * Journal of School Health
May 1991, Vol. 61.No. 5
ments designed to assess characteristics of children’s physical activity related to health. The instruments most relevant to health are identified, findings are discussed, and suggestions are made for improving the current observational technology.
LOCATION OF INSTRUMENTS A combination of computer and manual literature searches were used to locate instruments specifically designed for systematic observation of children’s physical activity. Instruments not thoroughly described and those focusing on variables other than physical activity as it relates directly to children’s health were excluded from review. For example, instruments designed to assess children’s skill engagement and social interaction opportunities were excluded’ as were systems designed mainly to examine psychological variables, such as hyperactivity, though they might relate indirectly to physical activity. Instruments selected for review are considered valid measures of physical activity. Validity refers to the degree to which an instrument measures what it is purported to measure. Associated with validity is the concept of interobserver reliability, or agreement on observed events by independent observers. A primary limitation on the validity of any instrument is the extent of interobserver agreement. For example, there is a limit on fine distinctions observers can be trained to make. When too many activity categories exist and distinctions between them are unclear, interobserver agreement are reduced. Only instruments that reported high interobserver agreement or reliability were reviewed. Because systematic observation is a direct measure of behavior that requires little inference or interpretation, it is sometimes used as a criterion method for validating other measurements of physical activity, such as self-report and mechanical and electronic monitoring. Because many health-related researchers are interested in energy expenditure, most instruments selected for review have been validated against measures of energy expenditure or heart rates. While physical activity can be assessed directly through observation methodology, energy expenditure can only be inferred. Table 1 compares eight instruments. Four instrumentd-’ were designed specifically to observe children’s physical activity in schools, and four‘-’Iwere designed to examine children’s physical activity in diverse settings. The categories presented in Table 1 are: Citation: Provides the reference used in the review. Name: Identifies the instrument. If the instrument had no name, one was provided. Location: Identifies settings where the instrument has been used. “Diverse” indicates the system may be used in any location. Observation strategy: Identifies the specific observation method the system uses. Momentary time-
r
sampling refers to coding events occurring at the end of the observation interval. Partial time-sampling refers to coding events that have occurred during a specific time interval, usually 5-20 seconds. Even though observers might watch a subject continuously, a partial or momentary time-sampling system could be used to record data.6-9 Activity categories: Specifies the number and briefly
identifies the activity categories coded. Validation: Identifies specific child variables correlated with the activity codes to permit energy expenditure to be estimated from observed data. Data summary: Identifies the primary summary variables. Additional summary variables may be calculated for some instruments. Associated variables: Identifies associated variables
Table 1 Characteristics of Selected Instruments Designed for Observing Children's Physical Activity Citation Name 4
Location
Observation Strategy
Activity Categories
momentary time-sampling; 5-second intervals
3 (no activity, none moderate; vigorous), each for upper and lower body
Validation
Data Summary
Associated Variables
Training Time
Test Side
%
none
low
recess
1-1 third-sixth grade students (88%-94%)
low
free play in gym
obese girls, ages five-eight
Subjects
Reliability
MAL (Movement of the Arms and Legs)
diverse
5
APEE (Activity Patterns and Energy Expenditure)
free play
momentary time-sampling; 15-second intervals
5 (sitting/lying heart rates mean quietly; standing activity quietly; sitting/ score; lying while Kcal/ kg/ active;standing min while active; very active/moving)
none
6
CPAF (Children's Physical Activity Form)
physical education classes
partial-time sampling; 1minute intervals
4 (stationary, heart rates activity no movement, points; stationary, limb Kcals movement; slow trunk movement; rapid trunk movement)
none
moderate
physical education classes
third-fifth 1-1 grade students (96%-98%)
7
SOFIT (System for Observing Fitness Instruction Time)
physical education classes
momentary time-sampling; 10-second obs/rec intervals
5 (lying; sitting; heart rates % standing; walkintervals/ ing; very active) time
lesson context; teacher behavior
low
physical education classes
1-1 third-fifth grade students (92%)
8
FATS (Fargo Activity Timesampling Survey)
home
partial interval recording; 10-second obs/rec intervals
8 (sleeping; lying down; sitting; crawling; climbing; standing; walking; running: each with 3 intensity levels minimal; moderate; extreme)
location; persons present; interactors; interactions; child remonse
high
home
children, ages 20-48 month
1-1 (91%-98%) Kappa (.go)
CARS (Children's Activity Rating Scale)
diverse
partial timesampling; 1-minute intervals
5 (stationary, heart no movement; rates; stationary, VO, movement; translocation, easy; translocation, moderate; translocation, strenuous)
location; others present ; television; eats; interactors, prompts; consequences
high
diverse
children, ages three-six
1-1 (84.1 % )
10
BEACHES (Behaviors of Eating and Physical Activity for Children's Health Evaluation System)
diverse
momentary time-sampling; I-minute intervals
5 (lying; sitting ; standing; walking; very active)
location; TV; interactors; eating; prompts; consequences; child response
high
diverse
children, ages four-nine
Kappa (.91)
11
SCAN CATS (Studies of Children's Activity and Nutrition Children's Activity Timesampiing Survey)
diverse
momentary time-sampling; 10-second obs/rec intervals
4 (stationary; none minimal activity; slow movement; rapid movement)
location, persons present; interactors; prompts
high
home
children, ages three-six
field scores, NA; videotape Kappa (.91)
9
none; correlated with LSI readings
intervals/ time; mean activity score
%
intervals
1-1
(86%-99%)
' %
intervals; Kcal/kg/ min
heart rates % intervals/ time; Kcal/kg/ min
%
intervals/ time
Journal of School Health
May 1991, Vol. 61,No. 5
225
coded simultaneously with the physical activity levels. Training time: Identifies the relative amount of time necessary for initially training observers to use the instruments reliably. Training time was reported for only a few instruments. Estimates of total hours, including classroom study and field practice, for initial training are: low, 10-15 hours, medium, 15-25, and high, 25-40. lest site: Identifies the setting where subjects were
observed during field tests of the instrument. Subjects: Identifies characteristics of subjects in the field test. Reliability: Identifies types and results of reliabilities reported in field tests. Reliability in systematic observation typically refers to the degree two or more persons simultaneously viewing an activity using the same behavior definitions and coding conventions record the same codes. When possible, interobserver agreement scores for the physical activity codes were isolated and are reported. 1-1 refers to interval-by-interval reliabilities. Kappa is a statistic that takes chance agreement into consideration. 1-1 scores typically are higher than Kappa scores.
REVIEW OF INSTRUMENTS Eight instruments4-11were selected for comparison. All eight have been carefully constructed, field tested with children, reported high reliabilities, and are generalizable for use in studying physical activity as it relates to health. Instruments validated for studying physical activity levels of adolescents were not located. The observation focus of all eight instruments was on an individual child. However, two systems designed for school envir~nments~.~ alternatively shift the focus to different children. All eight instruments used sampling procedures to estimate time children spent in various activity categories. Observers using two of the i n s t r ~ m e n t sfocused ~,~ continuously on the target child. However, the procedure of identifying whether or not the child engaged in specific categories during the oneminute intervals still provided only an estimate of how much time was spent in different activities. Instruments using duration recording, which would provide a more precise measure of the time a child spent in specific categories, were not located. Four instruments4-’ were designed specifically for researching children’s physical activity levels at school. These instruments are appropriate for studying behaviors during recess, free play, and physical education classes. None were designed specifically for entering, storing, and summarizing data by portable computer. Except for SOFIT,’ which provides for the simultaneous recording of lesson context and teacher behavior, these instruments focused solely on children’s activity levels. However, the other three instruments could be adapted to permit researchers to study school contextual variables. Four instruments8-” were designed to observe children’s physical activity in the home and can be used in other settings. These all permit simultaneous coding of many events associated with physical activity and are useful for comparing physical activity levels in different locations.
226 * Journal of School Health * May 1991. Vol. 61, No. 5
DISCUSSlON Children’s physical activity levels can be observed reliably, and observers can be quickly trained to generate accurate information, especially if physical activity is the only event coded. Complex systems that code variables in addition to physical activity demand more extensive training. Partial-interval recording systems, which typically produce lower interobserver agreement scores and demand more training time than momentary time-sampling systems, need to be used when transitory events such as prompts to be active or consequences are to be recorded. Many of the instruments had their physical activity categories validated against heart rates or estimates of children’s caloric e x p e n d i t ~ r e . ~ -This ~ * ~ Jvalidation ~ is particularly important for researchers interested in energy costs, but it may not be a priority for practitioners. The cost of validating activity level codes is sub~ t a n t i a l . * ~Most ~ . ~ ~ instruments ’~ reviewed can be modified to permit simultaneous recording of different variables while keeping the validated activity coding system intact. Investigators are encouraged to use the information in Table 1 to select the most appropriate measure for their purposes, rather than develop an untested instrument. These instruments reflect current interests of healthrelated researchers in primarily studying the activity engagement of young children. All eight instruments were designed for studying physical activity of the young, including one for children ages 20-48 months.$ None have been tested for use with students beyond the sixth grade. An instrument validated by observing young children may not necessarily be appropriate for use with others. Therefore, further validation may be needed before some instruments can be used with older populations, particularly if energy expenditure is to be estimated from coded behavior. Use of systematic observation to generate descriptive information and examine process and product variables, as well as validate other methods for recording children’s physical levels, is likely to continue. Future researchers should consider improving the observational m e t h ~ d o l o g y For .~~~ example, two instruments relied on observers to focus on a stopwatch then look up to locate the target child. Computer or audiocassette recorder pacing might improve accuracy with these instruments by reducing the need for observers to divert their focus to a stopwatch and away from the target child. Purchasing computers and training observers to use them to record data are more expensive initially, but reduced costs involved in recoding, reducing, and analyzing data favor using computers. Additional attention should be paid to training and supervising observer^.'.^ While reliabilities of reviewed instruments consistently were high, most studies were of brief duration and used few observers. In long-term studies, many different observers need to be trained and their skills need to be maintained over several years. While most studies report using videotape technology to train observers, only a few researchers reported using standardized videotapes to assess observer accuracy and to reduce observer drift and instrument decay. Follow-
up measures, particularly in extended studies, should include both reliability checks in the field and periodic calibrations against precoded “gold standard” videotapes. More care can be taken in training observers to be unobtrusive and to reduce subject reactivity. To reduce subject reactivity and eliminate potential observer bias in intervention studies, observers should not simultaneously participate as a member of the intervention team. Direct observation has several advantages over other field techniques and, with the advent of hand-held computers, will play an increased role in studying children’s physical activity as it relates to health. A number of systems have been published, and reported reliabilities generally are high. Several systems are substantially comprehensive and have been validated by comparing observations to measurements of children’s energy expenditure. Comparisons of different systems have not been conducted, thus insufficient information exists to indicate which systems are most accurate and which can be used most reliably. More effort needs to be expended to assess various categories for coding physical activity and to determine whether different results are produced when different observation tactics, such as duration recording, momentary time-sampling, and partial interval recording are used. Simultaneous coding of children’s physical activity from videotapes using H different observation systems is needed. References 1. Hartmann DP, ed. Using Observers to Study Behavior. San
Francisco, Calif: Jossey Bass; 1982. 2. McKenzie TL, Carlson BR. Systematic observation and computer technology. In: Darst P, Zakrajsek D, Mancini V, eds. Analyzing Physical Education and Sport Instruction. Champaign, Ill: Human Kinetics Press; 1989:81-89. 3. Darst P, Zakrajsek D, Mancini V, eds. Analyzing Physical Education and Sport Instruction. Champaign, Ill: Human Kinetics Press; 1989. 4. Hovel1 M, Bursick J, Sharkey R, McClure J. An evaluation of elementary students’ voluntary physical activity during recess. Res Q Exerc Sports. 1978;49(4):460-470. 5. Epstein L, McGowan C, Woodall K. A behavioral observation system for free play activity in young overweight female children. Res Q Exerc Sports. 1984;55(2):180-183. 6. O’Hara N, Baranowski T, Simons-Morton B, Wilson S, Parcel G. Validity of the observation of children’s physical activity. Res Q Exerc Sports. 1989;60(1):4247. 7 . McKenzie T, Sallis J, Nader P. SOFIT: System for Observing Fitness Instruction Time. J Teach Phys Ed. in press. 8 . Klesges R, Coates T, Moldenhauer-Klesges L, Holzer B, Gustavson J, Barnes J . The FATS: An observational system for assessing physical activity in children and associated parent behavior. Behav Assess. 1984;6:333-345. 9. Puhl J, Greaves K, Hoyt M, Baranowski T. Children’s activity rating scale (CARS): Description and evaluation. Res Q. Exerc Sports. 199O;61(1):26-36. 10. McKenzie T, Sallis J, Patterson T, Elder J, et al. BEACHES: An observational system for assessing children’s eating and physical activity behaviors and associated events. J Appl Behav Anal. 1991;24:1 . 11. Klesges R, Eck L, Hanson C, Haddock K, Klesges L. Effects of obesity, social interactions, and physical environmental on physical activity in preschoolers. Health Psychol. 1990;9(4):435-449.
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Journal of School Health
May 1991, Vol. 61. No. 5
227
D
irect observation in natural settings has had a long history. Various systems are available for studying children’s physical activity as it relates to health. Recent technological advances permitting complex observational codes to be entered, stored, and analyzed by portable computers makes this method appealing for assessing children’s physical activity.2 It is important to distinguish between physical activity and energy expenditure. Physical activity refers to body movement, while energy expenditure results from body movement. A lean child and an obese child may engage in the same physical activity, such as walking a mile, but experience different levels of energy expenditure from that activity. Systematic observation is a valid method for obtaining data from a physical activity from natural settings because it requires little inference. Observational procedures are flexible and permit researchers and practitioners to quantify diverse dimensions related to children’s physical activity. Children engage in activity relative to many different environmental factors such as location, presence of others, facilities, availability of toys and equipment, and whether the setting provides for free play or structured activity. Systematic observation allows the study of these contextual variables with limited response burden on participants. Systematic observation of children’s physical activity is an important method in health-related research, supervision, and curriculum development. Observation of children’s physical activity can be used as either a process or outcome measure. Information on both independent and dependent variables can be obtained through observation. Frequently, both researchers and practitioners can use the same instruments. Direct observation of children’s physical activity does have disadvantages. Events studied must be observable and codable, and are thereby limited to events seen or heard. Observers or video-recorders need to be in the environment where behaviors of interest occur, thereby limiting situations where data can be collected. Observers must be properly trained to be rigidly objective, and not to be evaluative or judgmental about what they see. Observers also must be trained to reduce subject reactivity caused by observers being present in the observational environment. Substantial time and effort are needed to develop the observational system, prepare coding conventions, and train observers. Substantial observation time in the natural setting also is needed to validate instruments and to obtain sufficient data to permit generalization of results to other settings and populations. The necessity of a human observer being present to code data means that relative to other methods of measurement, direct observation is costly. This article reviews systematic observation instruThomas L. McKenzie, PhD, Dept. of Physical Education, San Diego State University, San Diego, CA 92182. This work was supported, in part, by NIH grants HL3SlO9 and HL 44467.
224 * Journal of School Health
May 1991, Vol. 61.No. 5
ments designed to assess characteristics of children’s physical activity related to health. The instruments most relevant to health are identified, findings are discussed, and suggestions are made for improving the current observational technology.
LOCATION OF INSTRUMENTS A combination of computer and manual literature searches were used to locate instruments specifically designed for systematic observation of children’s physical activity. Instruments not thoroughly described and those focusing on variables other than physical activity as it relates directly to children’s health were excluded from review. For example, instruments designed to assess children’s skill engagement and social interaction opportunities were excluded’ as were systems designed mainly to examine psychological variables, such as hyperactivity, though they might relate indirectly to physical activity. Instruments selected for review are considered valid measures of physical activity. Validity refers to the degree to which an instrument measures what it is purported to measure. Associated with validity is the concept of interobserver reliability, or agreement on observed events by independent observers. A primary limitation on the validity of any instrument is the extent of interobserver agreement. For example, there is a limit on fine distinctions observers can be trained to make. When too many activity categories exist and distinctions between them are unclear, interobserver agreement are reduced. Only instruments that reported high interobserver agreement or reliability were reviewed. Because systematic observation is a direct measure of behavior that requires little inference or interpretation, it is sometimes used as a criterion method for validating other measurements of physical activity, such as self-report and mechanical and electronic monitoring. Because many health-related researchers are interested in energy expenditure, most instruments selected for review have been validated against measures of energy expenditure or heart rates. While physical activity can be assessed directly through observation methodology, energy expenditure can only be inferred. Table 1 compares eight instruments. Four instrumentd-’ were designed specifically to observe children’s physical activity in schools, and four‘-’Iwere designed to examine children’s physical activity in diverse settings. The categories presented in Table 1 are: Citation: Provides the reference used in the review. Name: Identifies the instrument. If the instrument had no name, one was provided. Location: Identifies settings where the instrument has been used. “Diverse” indicates the system may be used in any location. Observation strategy: Identifies the specific observation method the system uses. Momentary time-
r
sampling refers to coding events occurring at the end of the observation interval. Partial time-sampling refers to coding events that have occurred during a specific time interval, usually 5-20 seconds. Even though observers might watch a subject continuously, a partial or momentary time-sampling system could be used to record data.6-9 Activity categories: Specifies the number and briefly
identifies the activity categories coded. Validation: Identifies specific child variables correlated with the activity codes to permit energy expenditure to be estimated from observed data. Data summary: Identifies the primary summary variables. Additional summary variables may be calculated for some instruments. Associated variables: Identifies associated variables
Table 1 Characteristics of Selected Instruments Designed for Observing Children's Physical Activity Citation Name 4
Location
Observation Strategy
Activity Categories
momentary time-sampling; 5-second intervals
3 (no activity, none moderate; vigorous), each for upper and lower body
Validation
Data Summary
Associated Variables
Training Time
Test Side
%
none
low
recess
1-1 third-sixth grade students (88%-94%)
low
free play in gym
obese girls, ages five-eight
Subjects
Reliability
MAL (Movement of the Arms and Legs)
diverse
5
APEE (Activity Patterns and Energy Expenditure)
free play
momentary time-sampling; 15-second intervals
5 (sitting/lying heart rates mean quietly; standing activity quietly; sitting/ score; lying while Kcal/ kg/ active;standing min while active; very active/moving)
none
6
CPAF (Children's Physical Activity Form)
physical education classes
partial-time sampling; 1minute intervals
4 (stationary, heart rates activity no movement, points; stationary, limb Kcals movement; slow trunk movement; rapid trunk movement)
none
moderate
physical education classes
third-fifth 1-1 grade students (96%-98%)
7
SOFIT (System for Observing Fitness Instruction Time)
physical education classes
momentary time-sampling; 10-second obs/rec intervals
5 (lying; sitting; heart rates % standing; walkintervals/ ing; very active) time
lesson context; teacher behavior
low
physical education classes
1-1 third-fifth grade students (92%)
8
FATS (Fargo Activity Timesampling Survey)
home
partial interval recording; 10-second obs/rec intervals
8 (sleeping; lying down; sitting; crawling; climbing; standing; walking; running: each with 3 intensity levels minimal; moderate; extreme)
location; persons present; interactors; interactions; child remonse
high
home
children, ages 20-48 month
1-1 (91%-98%) Kappa (.go)
CARS (Children's Activity Rating Scale)
diverse
partial timesampling; 1-minute intervals
5 (stationary, heart no movement; rates; stationary, VO, movement; translocation, easy; translocation, moderate; translocation, strenuous)
location; others present ; television; eats; interactors, prompts; consequences
high
diverse
children, ages three-six
1-1 (84.1 % )
10
BEACHES (Behaviors of Eating and Physical Activity for Children's Health Evaluation System)
diverse
momentary time-sampling; I-minute intervals
5 (lying; sitting ; standing; walking; very active)
location; TV; interactors; eating; prompts; consequences; child response
high
diverse
children, ages four-nine
Kappa (.91)
11
SCAN CATS (Studies of Children's Activity and Nutrition Children's Activity Timesampiing Survey)
diverse
momentary time-sampling; 10-second obs/rec intervals
4 (stationary; none minimal activity; slow movement; rapid movement)
location, persons present; interactors; prompts
high
home
children, ages three-six
field scores, NA; videotape Kappa (.91)
9
none; correlated with LSI readings
intervals/ time; mean activity score
%
intervals
1-1
(86%-99%)
' %
intervals; Kcal/kg/ min
heart rates % intervals/ time; Kcal/kg/ min
%
intervals/ time
Journal of School Health
May 1991, Vol. 61,No. 5
225
coded simultaneously with the physical activity levels. Training time: Identifies the relative amount of time necessary for initially training observers to use the instruments reliably. Training time was reported for only a few instruments. Estimates of total hours, including classroom study and field practice, for initial training are: low, 10-15 hours, medium, 15-25, and high, 25-40. lest site: Identifies the setting where subjects were
observed during field tests of the instrument. Subjects: Identifies characteristics of subjects in the field test. Reliability: Identifies types and results of reliabilities reported in field tests. Reliability in systematic observation typically refers to the degree two or more persons simultaneously viewing an activity using the same behavior definitions and coding conventions record the same codes. When possible, interobserver agreement scores for the physical activity codes were isolated and are reported. 1-1 refers to interval-by-interval reliabilities. Kappa is a statistic that takes chance agreement into consideration. 1-1 scores typically are higher than Kappa scores.
REVIEW OF INSTRUMENTS Eight instruments4-11were selected for comparison. All eight have been carefully constructed, field tested with children, reported high reliabilities, and are generalizable for use in studying physical activity as it relates to health. Instruments validated for studying physical activity levels of adolescents were not located. The observation focus of all eight instruments was on an individual child. However, two systems designed for school envir~nments~.~ alternatively shift the focus to different children. All eight instruments used sampling procedures to estimate time children spent in various activity categories. Observers using two of the i n s t r ~ m e n t sfocused ~,~ continuously on the target child. However, the procedure of identifying whether or not the child engaged in specific categories during the oneminute intervals still provided only an estimate of how much time was spent in different activities. Instruments using duration recording, which would provide a more precise measure of the time a child spent in specific categories, were not located. Four instruments4-’ were designed specifically for researching children’s physical activity levels at school. These instruments are appropriate for studying behaviors during recess, free play, and physical education classes. None were designed specifically for entering, storing, and summarizing data by portable computer. Except for SOFIT,’ which provides for the simultaneous recording of lesson context and teacher behavior, these instruments focused solely on children’s activity levels. However, the other three instruments could be adapted to permit researchers to study school contextual variables. Four instruments8-” were designed to observe children’s physical activity in the home and can be used in other settings. These all permit simultaneous coding of many events associated with physical activity and are useful for comparing physical activity levels in different locations.
226 * Journal of School Health * May 1991. Vol. 61, No. 5
DISCUSSlON Children’s physical activity levels can be observed reliably, and observers can be quickly trained to generate accurate information, especially if physical activity is the only event coded. Complex systems that code variables in addition to physical activity demand more extensive training. Partial-interval recording systems, which typically produce lower interobserver agreement scores and demand more training time than momentary time-sampling systems, need to be used when transitory events such as prompts to be active or consequences are to be recorded. Many of the instruments had their physical activity categories validated against heart rates or estimates of children’s caloric e x p e n d i t ~ r e . ~ -This ~ * ~ Jvalidation ~ is particularly important for researchers interested in energy costs, but it may not be a priority for practitioners. The cost of validating activity level codes is sub~ t a n t i a l . * ~Most ~ . ~ ~ instruments ’~ reviewed can be modified to permit simultaneous recording of different variables while keeping the validated activity coding system intact. Investigators are encouraged to use the information in Table 1 to select the most appropriate measure for their purposes, rather than develop an untested instrument. These instruments reflect current interests of healthrelated researchers in primarily studying the activity engagement of young children. All eight instruments were designed for studying physical activity of the young, including one for children ages 20-48 months.$ None have been tested for use with students beyond the sixth grade. An instrument validated by observing young children may not necessarily be appropriate for use with others. Therefore, further validation may be needed before some instruments can be used with older populations, particularly if energy expenditure is to be estimated from coded behavior. Use of systematic observation to generate descriptive information and examine process and product variables, as well as validate other methods for recording children’s physical levels, is likely to continue. Future researchers should consider improving the observational m e t h ~ d o l o g y For .~~~ example, two instruments relied on observers to focus on a stopwatch then look up to locate the target child. Computer or audiocassette recorder pacing might improve accuracy with these instruments by reducing the need for observers to divert their focus to a stopwatch and away from the target child. Purchasing computers and training observers to use them to record data are more expensive initially, but reduced costs involved in recoding, reducing, and analyzing data favor using computers. Additional attention should be paid to training and supervising observer^.'.^ While reliabilities of reviewed instruments consistently were high, most studies were of brief duration and used few observers. In long-term studies, many different observers need to be trained and their skills need to be maintained over several years. While most studies report using videotape technology to train observers, only a few researchers reported using standardized videotapes to assess observer accuracy and to reduce observer drift and instrument decay. Follow-
up measures, particularly in extended studies, should include both reliability checks in the field and periodic calibrations against precoded “gold standard” videotapes. More care can be taken in training observers to be unobtrusive and to reduce subject reactivity. To reduce subject reactivity and eliminate potential observer bias in intervention studies, observers should not simultaneously participate as a member of the intervention team. Direct observation has several advantages over other field techniques and, with the advent of hand-held computers, will play an increased role in studying children’s physical activity as it relates to health. A number of systems have been published, and reported reliabilities generally are high. Several systems are substantially comprehensive and have been validated by comparing observations to measurements of children’s energy expenditure. Comparisons of different systems have not been conducted, thus insufficient information exists to indicate which systems are most accurate and which can be used most reliably. More effort needs to be expended to assess various categories for coding physical activity and to determine whether different results are produced when different observation tactics, such as duration recording, momentary time-sampling, and partial interval recording are used. Simultaneous coding of children’s physical activity from videotapes using H different observation systems is needed. References 1. Hartmann DP, ed. Using Observers to Study Behavior. San
Francisco, Calif: Jossey Bass; 1982. 2. McKenzie TL, Carlson BR. Systematic observation and computer technology. In: Darst P, Zakrajsek D, Mancini V, eds. Analyzing Physical Education and Sport Instruction. Champaign, Ill: Human Kinetics Press; 1989:81-89. 3. Darst P, Zakrajsek D, Mancini V, eds. Analyzing Physical Education and Sport Instruction. Champaign, Ill: Human Kinetics Press; 1989. 4. Hovel1 M, Bursick J, Sharkey R, McClure J. An evaluation of elementary students’ voluntary physical activity during recess. Res Q Exerc Sports. 1978;49(4):460-470. 5. Epstein L, McGowan C, Woodall K. A behavioral observation system for free play activity in young overweight female children. Res Q Exerc Sports. 1984;55(2):180-183. 6. O’Hara N, Baranowski T, Simons-Morton B, Wilson S, Parcel G. Validity of the observation of children’s physical activity. Res Q Exerc Sports. 1989;60(1):4247. 7 . McKenzie T, Sallis J, Nader P. SOFIT: System for Observing Fitness Instruction Time. J Teach Phys Ed. in press. 8 . Klesges R, Coates T, Moldenhauer-Klesges L, Holzer B, Gustavson J, Barnes J . The FATS: An observational system for assessing physical activity in children and associated parent behavior. Behav Assess. 1984;6:333-345. 9. Puhl J, Greaves K, Hoyt M, Baranowski T. Children’s activity rating scale (CARS): Description and evaluation. Res Q. Exerc Sports. 199O;61(1):26-36. 10. McKenzie T, Sallis J, Patterson T, Elder J, et al. BEACHES: An observational system for assessing children’s eating and physical activity behaviors and associated events. J Appl Behav Anal. 1991;24:1 . 11. Klesges R, Eck L, Hanson C, Haddock K, Klesges L. Effects of obesity, social interactions, and physical environmental on physical activity in preschoolers. Health Psychol. 1990;9(4):435-449.
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mARKANSAS The University of Arkansas Press Fayetteville 72 70 1 1-800-525-1823
Journal of School Health
May 1991, Vol. 61. No. 5
227
