This research has been conducted in compliance with all applicable Federal Regulations governing the protection of human subjects in research. No human subjects were directly involved in this research. ii SUMMARY BackgroundCardiorespiratory fitness is important for health, work, and athletic performance. Laboratory tests of maximal oxygen uptake (VO 2max ) are the gold standard for assessing this aspect of fitness. VO 2max protocols with small measurement errors will provide the best estimates of relationships between fitness and its antecedents and consequences. For example, tests with smaller errors will provide better indications of how well running tests function as substitutes for laboratory tests. ObjectivePublished studies of the reliability of VO 2max tests provide an empirical basis for estimating VO 2max test precision. This review employed meta-analysis procedures to model VO 2max test precision. ApproachStudies of the test-retest reliability of VO 2max protocols were identified from previous reviews and searches of computerized databases for biomedical, behavioral, and sports research. Of 51 studies identified, 12 were dropped because long test-retest intervals made it likely that true VO 2max values changed during the study. The reported means, standard deviations, and test-retest correlations were used to compute the standard error of measurement (SEM) for VO 2max for the remaining 39 studies. The age and gender composition of the sample were coded along with the exercise mode (treadmill, cycle ergometer, other) and the test-retest interval for the protocol. Meta-analysis produced a predictive model for SEM based on sample and protocol attributes. ResultsAverage SEM was 2.58 ml·kg -1 ·min -1. SEM was higher in samples with higher average VO 2max . Age, gender, test interval, and exercise mode were not related to SEM. After allowing for outliers, the final model to predict SEM was ln(SEM) = 0.661 + (.006 * VO 2max ). ConclusionsSEM increases as the average VO 2max of the sample increases. Other population and protocol attributes were not related to SEM. The potential applications of the model for SEM include evaluating new VO 2max protocols, evaluating field tests (e.g., run tests, walk tests), and making allowances for measurement error when investigating the relationships of VO 2max with other variables.

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Appropriate health behaviors are necessary to ensure health and well-being, thereby keeping military personnel ready to perform their jobs which may demand exceptional efforts at key times. An understanding of factors influencing health behaviors would be more readily achieved if general dimensions could be identified to delineate sets of health behaviors that consistently co-occur. 'Such dimensions may represent the effects of causal factors influencing multiple behaviors and may, thereby, provide an empirical basis for identifying causal factors that have widespread behavioral effects. Hodifying these causal factors may be an efficient way to improve health behavior. Well-defined health behavior dimensions are a requirement for these undertakings, but such dimensions have not been established.-Prior research has suffered from the use of only brief lists of health behaviors, failure to systematically select health behaviors to represent hypothesized health behavior dimensions, and failure to replicate findings across samples. The present study was designed to extend prior efforts by determining the number of dimensions of health behavior that could be reliably identified in two samples of Navy personnel. A set of 40 health behavior items was chosen to represent four major dimensions of health behavior that prior work suggested were present in groups representing a wide range of social and demographic backgrounds.-One sample of participants consisted of 812 men assigned to duty on U.S. Navy ships during 1984 who volunteered to participate in a survey study of general health habits conducted as part of program evaluation efforts for the Navy's Health and Physical Readiness Program. A second sample consisted of 605 recruits participating in a study of the effects of different interventions to stop smoking in Navy basic training. Data on the 40 health behaviors were collected by self-report questionnaires. Principle components analysis was conducted with 2, 3, 4, and 5 components extracted in each sample. The stability of the solutions across samples was determined by computing coefficients of congruence, by cross-validating regression weights for the factor scores, and by determining the number of items with component loadings greater than .30 in both samples. Different solutions also were compared in terms of the number of items that could be assigned to at least one component and how many of these were assigned to just a single component.

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