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Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES

Objective

To evaluate the correlation between the Yale Physical Activity Survey (YPAS) scores and objective accelerometer measures of time spent in light intensity physical activities, moderate to vigorous intensity physical activities, and moderate to vigorous activities in bouts lasting at least 10 minutes.

Methods

This study analyzed baseline data from 171 persons with rheumatoid arthritis (RA) and 139 persons with osteoarthritis (OA) in a randomized clinical trial (Increasing Motivation for Physical Activity in Arthritis Clinical Trial). Persons fulfilling the 1987 American College of Rheumatology criteria for RA and persons with symptomatic radiologic knee OA (Kellgren/Lawrence class ≥2) wore an accelerometer for 7 days, then responded to the YPAS questionnaire and questions regarding demographics (age, sex, and race) and health factors (body mass index, disease status [Health Assessment Questionnaire/Western Ontario and McMaster Universities Osteoarthritis Index], comorbidities, pain, and function). Spearman's correlation coefficients were estimated between each YPAS summary measure and accelerometer measures.

Results

In the RA participants, the strongest correlation was between the YPAS activity dimensions summary index (Y-ADSI) and average daily minutes of bouted moderate/vigorous activity (r = 0.51). Additionally, the Y-ADSI correlated significantly with both objectively measured average daily accelerometer counts (r = 0.45) and average daily minutes of moderate/vigorous activity (r = 0.43). For OA participants, a similar pattern emerged: the Y-ADSI had significant correlations with average daily minutes of bouted moderate/vigorous activity (r = 0.36), average daily minutes of moderate/vigorous activity (r = 0.31), and average daily counts (r = 0.24).

Conclusion

For both the RA and OA groups, the Y-ADSI had the strongest significant correlations with objectively measured physical activity, which supports Y-ADSI use as a tool for clinical applications and in rheumatology research.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES

In both population and clinical settings, physical activity promotion in persons with arthritis would be greatly enhanced by the availability of reliable, valid, and efficient self-report instruments that assess physical activity behavior of those with arthritis. Because persons with arthritis share the physical challenges that confront older populations and those with chronic conditions, focusing on lower intensity physical activities associated with functional independence (1) has been recommended. Self-report physical activity measures used with arthritis populations include the Physical Activity Scale for the Elderly (PASE) (2) and the Life Activity Record (ACTRE), which was formulated specifically for persons with musculoskeletal disorders (3, 4). While the PASE has moderate correlations with objective measures of physical activity (2), the ACTRE has not been validated with objective measures, and both require significant time and energy to collect, limiting their use in research and clinical settings. Objective assessment of physical activity using accelerometers provides reliable and accurate measurement, but can be expensive to implement in large-scale studies or in clinical practice. Therefore, a reliable and valid self-report measure of physical activity that has clinical applicability would be a valuable addition to providers' resources.

The Yale Physical Activity Survey (YPAS) was developed specifically for the measurement of physical activity in epidemiologic studies of older adults (5). The YPAS, like the PASE and ACTRE, includes questions about lower intensity functional activities, as well as the standard higher intensity sporting and leisure activities typically found in many physical activity surveys. However, an advantage of the YPAS for adults with rheumatic disease is its ease in data collection, which increases its potential for use in research and clinical settings.

The 2-part YPAS measures physical activity over a time period of a typical recent week (part 1) and from the past month (part 2). Previous studies demonstrated a good correlation of the YPAS scores with objectively measured accelerometer counts in normal healthy volunteers (6), but that relationship has not been examined in the context of either degenerative osteoarthritis (OA) or rheumatoid arthritis (RA), both of which threaten mobility. Therefore, the purpose of this study was to examine the performance of the YPAS as a measure of self-reported physical activity compared to objective accelerometer assessment in individuals with RA and OA.

Significance & Innovations

  • A reliable and valid self-report measure of physical activity that has clinical applicability would be a valuable addition to providers' resources.

  • This study evaluated the agreement of the Yale Physical Activity Scale (YPAS) questionnaire summary measures from adults with rheumatoid arthritis and osteoarthritis with objectively measured accelerometer measures of physical activity.

  • The YPAS activity dimensions summary index, which is fast to both administer and score, was moderately correlated with objective accelerometer measures, making it a feasible choice for clinical applications.

PATIENTS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES

Study population and sample.

This study analyzed baseline (preintervention) data from 171 persons with RA and 139 persons with OA who participated in the randomized clinical trial, Increasing Motivation for Physical Activity in Arthritis Clinical Trial (IMPAACT) of lifestyle physical activity promotion. This study received institutional review board approval, and written informed consent was obtained from each of the participating subjects. Eligible persons with RA were recruited for this study from 2 faculty rheumatology practices of a single academic medical center. Eligible persons with knee OA were recruited from rheumatology, general medicine, and orthopedic surgery practices at the same academic medical center, from 2 research registries, and through advertisements to the general public placed in buses and trains. RA participants fulfilling the 1987 American College of Rheumatology (ACR) criteria for RA (7) and persons with symptomatic radiologic knee OA (Kellgren/Lawrence class 2 or higher) were eligible if they met the following criteria: 1) age 18 years or greater, 2) no primary diagnosis of fibromyalgia, 3) no functionally limiting comorbidities such as spinal stenosis, peripheral vascular disease, or residual effects of stroke, 4) able to ambulate at least household distances (50 feet), 5) body mass index (BMI) <35 kg/m2, 6) cognitively intact and able to speak and understand English, 7) no contraindication to physical activity intervention due to comorbid conditions, 8) no total joint replacement surgery within the past 12 months and no plans for total joint replacement in the next 24 months, and 9) no plans to relocate from the metropolitan area in the next 24 months. Participants were instructed to “do what they would normally do in a typical week” before accelerometer measures were obtained in this preintervention assessment.

Physical activity measures.

YPAS. Briefly, YPAS part 1 requires approximately 15 minutes to assess 5 categories of activities performed during a typical week from the past month: housework activities, yard work, care giving of elders or children, purposeful exercise, and leisure (recreational) activities. The values from YPAS part 1 are used to calculate the YPAS total time index (Y-TTI) and the YPAS energy expenditure index (Y-EEI). For the purposes of this study, subjects were instructed to reflect on activities from the past week (during which the accelerometer was worn).

YPAS part 2 requires 5–7 minutes to assess 5 activity dimensions, i.e., vigorous activity, leisure walking, moving, standing, and sitting behaviors, performed over the past month. YPAS part 2 scores are used to calculate an activity dimensions summary index (Y-ADSI). The YPAS instrument has established reproducibility and validity (5).

Accelerometer measures and procedures.

Physical activity was monitored in all of the study participants using a GT1M ActiGraph accelerometer, a small uniaxial accelerometer that measures vertical acceleration and deceleration (8). Accelerometer output is an activity “count,” which is the weighted sum of the number of accelerations measured over a time period (e.g., in this case 1 minute), where the weights are proportional to the magnitude of measured acceleration. The validity and reliability of ActiGraph accelerometers under field conditions have been established in many populations, including RA (9–12) and knee OA (13, 14).

During the week prior to YPAS administration, the participants were instructed to don the accelerometer upon arising in the morning, and wear continuously (except for water activities) until going to bed at night for 7 consecutive days while going about their usual daily activities. The unit was worn on a belt at the natural waistline on the right hip in line with the right axilla. Participants also maintained a daily log (time sheet) to record when the accelerometer was put on in the morning and removed at night. At least 1 valid weekend day of data was present for 100% of the sample. Skipped days reported on the time sheets (2.4%) were just as likely to be weekdays as weekend days and were excluded from the analysis.

Descriptive measures.

Demographic factors, including age, sex, and race (white, African American, Asian, Hispanic, or other), were collected via telephone interview.

Health factors included BMI, disease status, comorbidities, pain, and function. BMI was calculated using height and weight measured at the time of the baseline visit (weight [kilograms]/height [m2]) (15). Disease status was defined as the duration of arthritis disease activity in years. Comorbidities were classified as either “mobility limiting” (e.g., chronic obstructive pulmonary disease, asthma) or “non–mobility limiting.” Pain and function were assessed in participants with RA using the Health Assessment Questionnaire (HAQ), which has demonstrated reliability and validity in RA (16). The HAQ pain scale measures arthritis pain severity on a scale between 0 (best) and 10 (worst), and function is based on the HAQ disability index scales (17), ranging between 0 (best) and 3 (worst). Pain and function were assessed in participants with knee OA using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) (18), which has demonstrated reliability and validity in OA (19). The Likert version of the WOMAC provides a pain score between 0 (best) and 20 (worst) and a physical function score between 0 (best) and 88 (worst).

Statistical analysis.

Accelerometer data from each participant were analytically filtered to identify nonwear periods (a period the monitor was potentially removed during a day) and days with sufficient wear time to be analyzed. Nonwear periods were defined as ≥90 minutes with zero activity counts (allowing for 2 interrupted minutes with counts <100) (20). A valid day of monitoring was defined as 10 or more wear hours in a 24-hour period, which was verified from accelerometer output (21). For this study, we included only participants who had 4 or more valid days of monitoring. These methods are consistent with accelerometer methodology used in the general population and have been validated in patients with rheumatic disease (18, 20).

Accelerometer data were scored for the purposes of standardization. First, an average daily count value was calculated for each subject. We then applied intensity thresholds used by the National Cancer Institute (NCI) (21) on a minute-by-minute basis to classify accelerometer counts into 3 intensity levels: light (100–2,019 counts), moderate (2,020–5,998 counts), and vigorous (≥5,999 counts). Total daily time (minutes) was summed for each intensity level. In addition, we calculated daily bouted minutes of moderate to vigorous physical activity (MVPA), a “bout” being defined as 10 or more consecutive minutes above the 2,020 count threshold, with allowance for interruptions of 1 or 2 minutes below the threshold, consistent with NCI methodology (21). Weekly totals were summed from the daily totals or estimated as 7 times the average daily total for persons with at least 4 valid days of monitoring.

Spearman's correlation coefficients were calculated to estimate the correlation between each of the YPAS physical activity summary measures (Y-TTI, Y-EEI, and Y-ADSI) and 4 accelerometer physical activity measures (average daily counts, mean light intensity activity minutes, mean MVPA minutes, and mean moderate to vigorous minutes occurring in bouts of 10 minutes).

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES

RA participants.

A total of 171 adults meeting the ACR criteria for RA participated in accelerometer monitoring. Demographic characteristics for both diagnostic groups can be found in Table 1. The age distribution of the sample was broad (range 23–86 years, mean age 55 years), but skewed to older ages. Participants were primarily women (82%) and white (76%). On average, participants had RA disease for mean ± SD 13.5 ± 10 years. Participants tended to be overweight (mean BMI 28 kg/m2). HAQ pain scores were relatively low at a mean score of 3.39 (of 10); HAQ function scores averaged 0.69 (of 3). Twenty-eight percent of participants (n = 48) reported taking a prescription medication for at least 1 comorbidity that may have affected their ability to be mobile: the most frequent were osteoporosis (n = 28), respiratory conditions (n = 13), and cardiovascular conditions (n = 7). In addition, several subjects reported a diagnosis of depression (n = 32), which may have also affected physical activity.

Table 1. Demographic and disease variables*
 RA (n = 171)Knee OA (n = 139)
  • *

    RA = rheumatoid arthritis; OA = osteoarthritis; BMI = body mass index.

Age, mean ± SD years55 ± 1463 ± 13
Female sex, %8258
Race, %  
 White7658
 African American1232
 Other1210
BMI, mean ± SD kg/m228 ± 631 ± 6
Mobility-limiting comorbidities, %2824
Depression, %199
Disease duration, mean ± SD years14 ± 1011 ± 11

OA participants.

A total of 139 adults meeting the study's criteria for knee OA participated in accelerometer monitoring. Participants were an average age of 63 years (range 34–91 years) and were primarily women (58%) and white (58%). On average, participants had OA disease for mean ± SD 11 ± 11 years, and tended to be overweight (33%) or obese (52%). WOMAC pain scores had a mean of 5.6 (of 20); WOMAC function scores averaged 17.5 (of 68). Twenty-four percent of the participants (n = 34) reported at least 1 comorbidity that may have affected their ability to be mobile. The reported mobility-limiting comorbidities (in descending order of frequency) were osteoporosis (n = 13), respiratory conditions (n = 12), and cardiovascular conditions (n = 9). Again, several subjects reported a diagnosis of depression (n = 12), which may have also have affected physical activity.

Measures of physical activity.

Table 2 shows the physical activity (both subjective and objective measures) of the study participants. The objective measures of physical activity supported findings from the self-report measures, with some differences in activity patterns. Participants with RA reported spending an average of 26 hours per week engaged in physical activity, which resulted in a mean Y-EEI of 5,577 kilocalories per week. The Y-ADSI mean for the RA participants was 48. Higher scores indicate more active lifestyles, with possible scores ranging from 0–133. Accelerometer measures indicated that the greatest amount of activity occurred within the context of light intensity physical activity (median 481 minutes/day), followed by moderate to vigorous minutes (median 14 minutes/day), and finally bouted MVPA (median 3 minutes/day). In fact, 94% of all activity time was spent engaged in light intensity activity.

Table 2. Physical activity characteristics of the sample*
 RA (n = 171)Knee OA (n = 139)
Median (IQR)Mean ± SDMedian (IQR)Mean ± SD
  • *

    RA = rheumatoid arthritis; OA = osteoarthritis; IQR = interquartile range; YPAS = Yale Physical Activity Survey; Y-TTI = YPAS total time index; Y-EEI = YPAS energy expenditure index; Y-ADSI = YPAS activity dimensions summary index; MVPA = moderate/vigorous physical activity.

YPAS subscales    
 Y-TTI, hours of activity/week21 (22)26 ± 1526 (22)32 ± 25
 Y-EEI, kilocalories/week4,830 (4,150)5,577 ± 3,4285,950 (4,470)7,435 ± 6,222
 Y-ADSI43 (26)48 ± 2148 (24)51 ± 20
Mean accelerometer    
 Counts per day208,566 (116,373)220,506 ± 106,022208,259 (139,809)220,915 ± 110,149
 Light intensity, minutes/day481 (163)477 ± 103459 (153)468 ± 100
 MVPA intensity, minutes/day14 (26)19 ± 1915 (25)20 ± 20
 Bouted MVPA, minutes/day3 (3)9 ± 133 (10)8 ± 14

Participants with OA reported spending an average of 32 hours per week engaged in physical activity, which resulted in a mean Y-EEI of 7,435 kilocalories per week. The Y-ADSI mean for the OA participants was 51. Accelerometer measures again indicated that the greatest amount of activity (again, 94%) occurred within the context of light intensity physical activity (median 459 minutes/day), followed by moderate to vigorous minutes (median 15 minutes/day), and finally bouted MVPA (median 3 minutes/day).

Correlations among the subjective and objective measures in the RA participants revealed modest but statistically significant positive associations between all YPAS summary measures (Table 3) and at least 1 accelerometer measure, the strongest being between the Y-ADSI and average daily minutes of bouted MVPA (r = 0.51). Additionally, the Y-ADSI demonstrated significant positive associations with both average daily accelerometer counts (r = 0.45) and average daily minutes of unbouted MVPA (r = 0.43). However, the Y-ADSI did not correlate with objectively measured light intensity activity, which had weaker but significant correlations with the other 2 YPAS summary measures, Y-TTI (r = 0.26) and Y-EEI (r = 0.27). Among participants with OA (Table 4), the Y-ADSI had modest but significant correlations with accelerometer measures of average daily minutes of bouted MVPA (r = 0.36), average daily minutes of unbouted MVPA (r = 0.31), and average daily accelerometer counts (r = 0.24). Additionally, the Y-EEI was significantly correlated with accelerometer measures of average daily minutes of bouted MVPA (r = 0.17). However, the Y-TTI was not significantly correlated with any accelerometer measures in the OA group.

Table 3. Spearman's correlations of objective and subjective physical activity measures for rheumatoid arthritis (n = 171)*
 Objective accelerometer measurements
Average daily countsAverage daily minutes of light activityAverage daily minutes of MVPAAverage daily minutes of bouted MVPA
  • *

    MVPA = moderate/vigorous physical activity; YPAS = Yale Physical Activity Survey; Y-TTI = YPAS total time index; Y-EEI = YPAS energy expenditure index; Y-ADSI = YPAS activity dimensions summary index.

  • P < 0.001.

  • P < 0.05.

YPAS subscales    
 Y-TTI, hours of activity/week0.190.260.04−0.00
 Y-EEI, kilocalories/week0.300.270.150.11
 Y-ADSI0.450.040.430.51
Table 4. Spearman's correlations of objective and subjective physical activity measures for knee osteoarthritis (n = 139)*
 Objective accelerometer measurements
Average daily countsAverage daily minutes of light activityAverage daily minutes of MVPAAverage daily minutes of bouted MVPA
  • *

    MVPA = moderate/vigorous physical activity; YPAS = Yale Physical Activity Survey; Y-TTI = YPAS total time index; Y-EEI = YPAS energy expenditure index; Y-ADSI = YPAS activity dimensions summary index.

  • P < 0.05.

  • P < 0.01.

  • §

    P < 0.001.

YPAS subscales    
 Y-TTI, hours of activity/week0.05−0.010.050.12
 Y-EEI, kilocalories/week0.12−0.000.130.17
 Y-ADSI0.24−0.080.31§0.36§

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES

The purpose of this study was to evaluate whether scores on YPAS summary measures from adults with RA and OA correlate with objectively measured time spent in light, MVPA, and bouted MVPA, as well as average daily accelerometer counts. In general, the Y-ADSI had the strongest association with objectively measured physical activity. Among all of the YPAS summary scores, it had the highest correlation with average daily accelerometer counts, with MVPA, and with bouted MVPA in both RA and knee OA participants. The Y-ADSI is a weighted summary measure (analogous to accelerometer counts) that gives higher scores to more intense physical activity behavior, which may account for a stronger correlation with higher intensity accelerometer measures. The Y-ADSI is also more sensitive than other YPAS summary measures to time spent in MVPA, which has relevance to federal guideline physical activity assessments. Because the Y-ADSI requires much less time to administer than the entire YPAS, it could easily be administered and scored in a clinical setting to gain perspective on the physical activity (or lack thereof) of persons with arthritis, making it an efficient summary measure for both diagnostic groups.

Objective accelerometer monitoring showed that the majority (94%) of physical activity time for these study participants was spent in light intensity activities (median 481 minutes/day for RA, median 459 minutes/day for OA), which is a noteworthy finding, as neither the general health benefits nor the arthritis-specific benefits of light intensity activity are known. Accelerometer-measured light intensity activity was significantly correlated with Y-TTI (r = 0.26) and the Y-EEI (r = 0.27), but only in persons with RA. As noted in Table 4, for persons with OA, correlations between the YPAS measures and accelerometer measures were lower in general, which may be related to measurement precision issues. Possible explanations for the lower correlations in the OA group include the potential for less precise accelerometer monitoring in the OA group. The higher BMI noted in the OA participants may have interfered with accurate accelerometer data collection, especially at slower walking speeds (22), as can be seen in older persons with knee symptoms (23, 24). In addition, the demand for more detailed memory regarding the week's activities in YPAS part 1 (the accelerometer reference week) may have diminished the reporting precision, especially in the older OA subjects, resulting in reduced correlation. The Y-TTI and Y-EEI values for the OA sample were less precise (larger variation) than those for the RA respondents. However, it is interesting and somewhat counterintuitive to note that the best correlations were found with the section of the YPAS (part 2) that inquires about the past month and not part 1, which asks for activity recall regarding the accelerometer reference week. Overall, this finding is not terribly surprising, because recall for constant low-level activity may not be as strong or accurate as it is for activities that cause more notable physiologic responses such as increased heart rate, breathing, and perspiration. In YPAS reliability testing, DiPietro et al also found that light intensity activities were not recalled as precisely as higher intensity activities (5). It may be that if light intensity activity is the activity of interest, objective measurement is required to adequately capture it.

The performance of the YPAS in the current study compared favorably with other self-report measures that have been compared with accelerometer data. For example, PASE scores were significantly correlated with average 3-day accelerometer readings in the total sample (r = 0.49) and in persons over age 70 years (r = 0.64) (2). In a New Zealand validation study (25) of the International Physical Activity Questionnaire (n = 70 adults ages 18–65 years), moderate correlations were seen with 7-day ActiGraph data for time spent in moderate intensity physical activity (r =0.30) and total physical activity (sum of moderate and vigorous intensity physical activity; r = 0.32). The 7-day physical activity recall was compared to data obtained from the same week using the RT3 triaxial accelerometer over 3 time points from 115 adults ages 33–85 years. There was significant moderate agreement between the 7-day physical activity recall and the accelerometer with longitudinal serial correlation coefficients of 0.54 at baseline, 0.24 at year 1, and 0.53 at year 2 (26). Finally, the self-report instrument used for the 2001 Behavioral Risk Factor Surveillance System (BRFSS) was compared to accelerometer data obtained from 60 subjects followed for 22 days in Columbia, South Carolina. Spearman's correlation coefficients ranged from 0.16 to 0.27 for moderate intensity activity, and from 0.52 to 0.63 for vigorous intensity activities (27). The BRFSS physical activity questions had been updated in 2001 to include domains of leisure time, household, and transportation-related activity of moderate and vigorous intensity and walking questions, so a strong correlation might have been expected.

There were some limitations to this study that must be considered. First, accelerometers are not entirely able to account for activity associated with cycling or water sports, which may have affected the outcome. We attempted to rectify this issue with a review of the YPAS items that asked for estimated time engaged in cycling and water activities. Very few participants reported water activities (4% of OA and 5% of RA). Although more participants reported cycling (20% of OA and 15% of RA), the actual amount of minutes spent cycling (median for OA was 70 minutes, in RA the median was 60 minutes) comprised a small percentage of the total activity time. It is likely that correlations would have been even stronger if these activities had been accurately reflected in the accelerometer counts; this suggests that our correlations represent a conservative estimate. The higher BMI in this sample may have interfered with accurate accelerometer data collection, especially at different walking speeds. It has been shown that abdominal adipose can cause inaccuracies in both the placement and sensory capacity of the equipment (22). Mobility-limiting comorbidities were inferred from medication logs, and therefore may underrepresent the actual number of such comorbidities.

One important question that will determine the external validity of the findings of this study is the similarity of the IMPAACT populations as compared with other RA and knee OA populations. The RA participants in IMPAACT were similar compared to participants in a clinical study of RA remissions (28) in age (mean age 55 versus 56 years), race/ethnicity (76% versus 67% white), and disease duration (13 versus 12 years). These findings support the generalizability of the IMPAACT RA cohort results to persons with RA in other clinical settings.

The knee OA participants in IMPAACT were similar to knee OA participants enrolled in a natural history study, the Mechanical Factors in Arthritis of the Knee (MAK) study (29), in mean age (63 versus 64 years) and mean BMI (31.4 versus 30.3 kg/m2), but had a slightly lower frequency of women (58% versus 75%). Like those in the MAK study, the OA sample examined in this study was comprised of nonclinical community members. These findings support the generalizability of IMPAACT's OA cohort results to other adults with knee OA recruited from the community.

The moderate correlations between accelerometer data and the Y-ADSI seen in this study add to the literature supporting the validity of the YPAS as a measure of self-reported (moderate to vigorous) physical activity in individuals with RA and OA. While the Y-EEI was moderately correlated with objective accelerometer measures, the Y-ADSI is faster to both administer and score, making it the more feasible choice for clinical applications. Finally, since the Y-ADSI is scored entirely from the shorter YPAS part 2, it does not appear to be especially important to administer the longer part 1 in a clinical setting, unless a rich description of the activities themselves is desired.

AUTHOR CONTRIBUTIONS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES

All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. Semanik had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study conception and design. Semanik, Chang.

Acquisition of data. Semanik, Chang.

Analysis and interpretation of data. Semanik, Lee, Manheim, DiPietro, Dunlop, Chang.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. REFERENCES
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