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These measures also require specialized training and the physical proximity of the participant for data collection. In addition, direct measures each possess their own limitations and no single "gold standard" exists for measuring physical activity or assessing validity [ 3 ].
The appropriate method for measuring physical activity at various levels depends on factors such as the number of individuals to be monitored, the time period of measurements and available finances [ 5 ]. Many previous studies have examined the reliability and validity of various self-report and direct methods for assessing physical activity. Results from these studies have been conflicting. To our knowledge no attempt has been made to synthesize the literature to determine the validity of physical activity measures in adult populations.
The primary objective of this study was to perform a systematic review to compare self-report versus direct measures for assessing physical activity in observational and experimental studies of adult populations.
The results from this systematic review provide a comprehensive summary of past research and a comparison between physical activity levels based on direct versus self-report measures in adult populations. The review sought to identify all studies observational or experimental that presented a comparison of self-report and direct measurement results to reveal differences in physical activity levels based on measurement in adult populations 18 years and over.
Studies which examined only a self-report or direct measure, but not both were not included in the review. All study designs were eligible e. Only studies involving adult populations with a mean age of 18 years and older were considered. A separate pediatric review was carried out as a result of differences in measurement methodologies and hypothesized cognitive and recall abilities between adults and children [ 6 ].
The eligible self-report measures of physical activity included: diaries or logs; questionnaires; surveys; and recall interviews. Proxy-reports were excluded because they present issues of reliability due to the potential heterogeneity of reporters e. The eligible direct measures of physical activity included: doubly-labeled water DLWindirect or direct calorimetry, accelerometry, pedometry, heart rate monitoring HRMglobal positioning Rev - Various - Local101V.2 (CD), and direct observation.
Although no language restrictions were imposed in the search, only English language articles were included in the review. Abstracts were included if they provided sufficient details to meet inclusion criteria. The search strategy is illustrated using the MEDLINE search as an example Table 1 and was modified according to the indexing systems of the other databases. Grey literature non-peer reviewed works included published abstracts and conference proceedings, published lists of theses and dissertations, and government reports.
Knowledgeable researchers in the field were solicited for key studies of interest. The bibliographies of key studies selected for the review were examined to identify further studies. Two independent reviewers screened the titles and abstracts of all studies to identify potentially-relevant articles. Duplicates were manually removed. The full texts of all studies that met the inclusion criteria were then obtained and reviewed.
Standardized data abstraction forms were completed by one reviewer and verified by two others. Information was extracted on the type of study design, participant characteristics, sample size, and methods of physical activity measurement self-report and direct measures employed, units of measurement, duration of direct measure, length of recall, and length of time between the self-report and directly measured estimates.
Reviewers were not blinded to the authors or journals when extracting data. The Downs and Black [ 7 ] checklist was used to assess the risk of bias. The Downs and Black instrument was recommended for assessing risk of bias in observational studies in a recent systematic review [ 8 ] and other assessments [ 9 ] and was employed in this review to assess study quality including reporting, external validity, and internal validity bias.
The Downs and Black checklist consists of 27 items with a maximum count of 32 points. A modified version of the checklist was employed with items that were not relevant to the objectives of this review removed. The adapted checklist consisted of 15 items, including items 1—4, 6, 7, 9—13, 16—18, and 20 from the original list, with a maximum possible count of 15 points higher scores indicate superior quality.
The risk of bias assessment was carried out by two independent assessors and when disagreements between assessors occurred, consensus was achieved through discussion. Only studies with units of measurement that were the same for both the self-report and direct measures were used to calculate percent mean differences. Units were converted where possible.
These studies were included in the direct comparison analyses. Forest plots graphical displays of the percent mean differences across the individual studies were constructed to present overall trends in agreement of physical activity by direct measure and gender.
As most studies did not employ the same units of measurement e. The preliminary search of electronic bibliographic databases, reference lists and grey literature identified 4, citations see Figure 1. After a preliminary title and abstract review, full text articles were retrieved for a detailed assessment. Of these, met the criteria for study inclusion. One hundred and forty-eight of these studies reported correlation statistics [ 10 — ].
Seventy-four studies contained comparable data meaning the self-report and direct measurements were reported using the same units [ 111517192023323344485356 — Rev - Various - Local101V.2 (CD)6573 — 778088909294,,—,—,, — ]. These studies were included in the direct comparison analyses and their characteristics are described in Table 2. Common reasons for excluding studies included: populations with mean ages less than 18 years, the absence of directly measured and self-report data on the same population, non-English language, duplicate reporting of data, and the absence of comparable units between measures or the absence of a direct comparison.
Data abstraction identified three articles and two dissertations that analyzed and reported duplicate data in multiple papers [ — ]. Studies were retained based on the most pertinent and most recent data, as well as the largest sample size. Studies included were published over a year period from to All studies were written in English. Nineteen of the studies used randomized controlled trial designs [ 22242628305053618491,,] and all others used observational designs e.
All included studies were published as journal articles except for 19 dissertations [ 162430343845496164697173747899, ]. Participants in the studies ranged from 10 to years of age.
Although the focus of the review was on those aged 18 and over, studies that had a range of ages less than 18 years were not excluded as long as the mean age of the sample was over 18 years. Sample sizes ranged from a low of six [ 21 ] to a high of 2, in Craig et al. There were a greater number of studies reporting on female-only data than studies reporting on male-only data.
A total of five direct measures were used in the assessment of physical activity and included: accelerometers, DLW, indirect calorimetry, HRM, and pedometers. Of the studies included in the synthesis of directly comparable data Table 2accelerometers were the most frequently used direct measure and indirect calorimetry was the least used.
A variety of self-report measures were employed, but the seven-day physical activity recall 7-day PAR [ ] was the most cited. Over half of the studies reported that the self-report and directly assessed physical activity levels were measured over the same length of time e. There were also a considerable number who reported measurements over the same period of time, but that did not measure the same length of time e.
Eleven of the studies in Table 2 lacked any mention of time [ 59,,, ], Rev - Various - Local101V.2 (CD). The range of items met on the modified Downs and Black tool was 8 to 15 maximum possible count was 15 with a mean of All studies were given maximum points for describing study objectives. All but one study scored maximum points for describing the main outcomes to be measured and the interventions used including comparison methods between measures.
Although most studies carried out some sort of significance testing on results, most did not report the actual probability values associated with the estimates or their associated measures of random variability e. Most studies obtained a high number of items on the reporting section maximum count of 8 with a mean of 6. The external validity section of the risk of bias assessment had a maximum count of three and consisted of reporting on the representativenessof the subjects and the testing conditions.
As a result, the external validity ratings of most studies were poor with a mean of 1. In order to obtain the maximum number of items four in the internal validity section, studies must have reported whether any of the results of the study were based on "data dredging", whether the analyses adjusted for any time lag between the two measurements or different lengths of follow-up, whether the statistical tests used to assess the main outcomes were appropriate, and whether the main outcome measures were accurate valid and reliable.
Internal validity item counts were generally high with the majority of studies having obtained a four. A qualitative analysis was conducted on the top seven scores of 14 and 15 out of 15 and lowest seven studies 8 and 9 out of 15 based on scores from the risk of bias assessment.
No conclusive patterns were identified from this analysis. The results from the accelerometer studies were further examined, as this was the only group of studies with a good distribution of low and high quality studies based on the accelerometer median split of bias scores.
Findings from this analysis did not identify any clear patterns in the differences in agreement between physical activity measured by self-report compared to accelerometer when grouped by low and high quality. One hundred and forty-eight studies [ 101113 —] reported correlation statistics between self-report and direct measurements of physical activity. Figure 2 is a plot of all extracted correlations and shows that overall, there is no clear trend in the degree of correlation between self-reported and directly measured physical activity, regardless of the direct method employed.
Overall, correlations were low-to-moderate with a mean of 0. Scatter plot of all correlation coefficients between direct measures and self-report measures. Seventy-four studies contained Rev - Various - Local101V.2 (CD) data on the measurement of physical activity based on self-report and directly measured values.
Table 2 describes these studies and their subcomponents. Percent mean differences were calculated for all of these studies and are presented as forest plots in Figures 3 to 8. Negative values indicate that self-report estimates were lower than the amount of physical activity assessed by direct methods while positive values indicate values that are higher. Sixty percent of the percent mean differences indicated that self-reported physical activity estimates were higher than those measured by direct methods.
All outlying data were from studies where physical activity was categorized by level of exertion e. Percent mean differences were examined separately for the five different direct measures. Accelerometers were the most used direct measure. Self-report measures of physical activity were generally higher than those directly measured by accelerometers Figures 3 to 5. The second-most common direct measure employed was DLW and comparable data with self-report measures are presented in Figures 6 to 8.
Pedometers and indirect calorimetry were the least commonly used direct measures for studies with comparable data. There were a total of eight comparisons from four studies for pedometers and 15 from two studies for indirect calorimetry Figures 6 to 8 making it difficult to draw conclusions with regard to patterns of agreement between the self-report and direct measures. However, seven [ 197576] of the eight pedometer comparisons reported higher levels of physical activity by self-report when compared to the pedometer results.
The eighth comparison [ 19 ] which involved female-only data saw no difference between the two measures. The indirect calorimetry results were less straightforward and presented no obvious patterns in agreement. Subgroups were qualitatively examined to assess whether any differences existed in the degree of agreement between self-reported and directly measured physical activity.
Meta-analyses were not possible due to the substantial heterogeneity in units of reporting for physical activity measured by the various self-report and direct methods across the studies, and the significant lack of data with comparable units across measures. As a result, we were unable to determine the sensitivity of the values and the associated measures of error for the studies. Overall effect sizes to summarize the magnitude of discrepancy across the various measures of physical activity could therefore not be calculated.
To the authors' knowledge this review represents the most comprehensive attempt to examine the relationship between self-report and directly measured estimates of adult physical activity in the international literature. Risk of bias was assessed and identified that just over one third of the studies had lower quality based on their description of the methods and external and internal validity.
Overall, no clear trends emerged in the over- or underreporting of physical activity by self-report compared to direct methods. However, some results suggest that patterns in the agreement between self-report and direct measures of physical activity may exist, but they are likely to differ depending on the direct methods used for comparison and the sex of the population sampled.
Interestingly, findings also identified that studies which categorized physical activity by level of exertion e.
These larger differences may reflect a problem with self-report measures attempting to capture higher levels of physical activity, or problems with participant interpretation and recall. Many of the studies tested the relationship between self-report and direct measures by using a correlation coefficient, but this is limited as correlation is only able to measure the strength of the relationship between two variables and cannot assess the level of agreement between them, as well as ignoring any bias in the data [ ].
A more useful approach, the Bland-Altman method, provides a means for assessing the level of agreement between self-report and direct measures by deriving the mean difference between the two measures and the limits of agreement. If the two measures possess good agreement and measure the same parameter of physical activity, then the cheaper and less invasive self-report methods may be valid substitutes for direct methods.
A meta-analysis would have allowed us to estimate the overall effect sizes for each of the direct measures and undertake a sensitivity analysis to further understand the degree of bias in the studies. Unfortunately, inconsistent methods and reporting among the studies included made such an analysis methodologically inappropriate. Further research in this area would benefit from greater consistency in the units of reporting and the methods used to facilitate comparisons.
For instance, many studies did not report results using the same units, so estimates of agreement between the self-report and direct measures could not be computed. There was also an inconsistency in the number of days measured and the time lag between the self-report and direct measures. It is recommended that authors present their results using the same units for both measures e. Adhering to consistent reporting criteria would increase the comparability of results across studies and enable the calculation of overall effect sizes.
Frustrated, I took apart the computer again and this time returned the original fireball drive, made sure all the connections were secure, and that there was no bent pins or crossed wires. I think you can guess that it still didn't work for some reason. Can anyone tell me where I might have went wrong? I only damaged two pins on the CD-ROM reader that I straightened with some needle nose plyers, and the video screw witch I tried to get out with a small flat head screwdriver from a glasses kit to no avail.
I think I've just about run out of ideas. I plan on replacing the PRAM battery tomorrow, so other than that, is there any suggestions on what might have happened or how to fix this? Just to be clear I have no fire wire drives of any kind, and this is the only mac I own currently. G'day and welcome to the forums. I am stunned you actually purchased a MHz original iMac. If you are talking about the original install CD from the MHz model it will not install.
Those original system discs are extremely model specific. They came with operating system 8. Also the slot loading optical drive may well be dead after all this time. Hmmm… are we getting spoofed here with comments such as "fireball drive" and "Rev A Bondi Blue mhz iMac G3" in the same paragraphs, and various other seemingly unrelated Mac and OS X comments…???
I'd question if any PRAM battery is going to help at this point, unless I missed something… and why even bother??? Tray loading Bondi Blue drive to be clear, and no this was the Non machine specific 8. I replaced the PRAM battery and logic board and it still occurred. I've come to the conclusion the video pin maaaay have more serious data interfacing issues. Ill keep you all updated with my progress since I am going to have to head in deeper.
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It can be very frustrating Also trying to use the circular function to fit on the label accurately. The posting of advertisements, profanity, or personal attacks is prohibited.
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