Interval training program optimization in highly trained endurance cyclists

Purpose: The purpose of this study was to examine the influence of three different high-intensity interval training (HIT) regimens on endurance performance in highly trained endurance athletes. Methods: Before, and after 2 and 4 wk of training, 38 cyclists and triathletes (mean +/- SD; age = 25 +/- 6 yr; mass = 75 +/- 7 kg; (V)over dot O-2peak = 64.5 +/- 5.2 mL.kg(-1).min(-1)) performed: 1) a progressive cycle test to measure peak oxygen consumption ((V)over dotO(2peak)) and peak aerobic power output (PPO), 2) a time to exhaustion test (T-max) at their (V)over dotO(2peak) power output (P-max), as well as 3) a 40-kin time-trial (TT40). Subjects were matched and assigned to one of four training groups (G(1), N = 8, 8 X 60% T-max P-max, 1:2 work:recovery ratio; G(2), N = 9, 8 X 60% T-max at P-max, recovery at 65% HRmax; G(3), N = 10, 12 X 30 s at 175% PPO, 4.5-min recovery; G(CON), N = 11). In addition to G(1) G(2), and G(3) performing HIT twice per week, all athletes maintained their regular low-intensity training throughout the experimental period. Results: All HIT groups improved TT40 performance (+4.4 to +5.8%) and PPO (+3.0 to +6.2%) significantly more than G(CON) (-0.9 to + 1.1 %; P < 0.05). Furthermore, G(1) (+5.4%) and G(2) (+8.1%) improved their (V)over dot O-2peak significantly more than G(CON) (+ 1.0%; P < 0.05). Conclusion: The present study has shown that when HIT incorporates P-max as the interval intensity and 60% of T-max as the interval duration, already highly trained cyclists can significantly improve their 40-km time trial performance. Moreover, the present data confirm prior research, in that repeated supramaximal HIT can significantly improve 40-km time trial performance.

Evaluating Australia's National Medicines Policy using geographical mapping

Background: There has been a proliferation of quality use of medicines activities in Australia since the 1990s. However, knowledge of the nature and extent of these activities was lacking. A mechanism was required to map the activities to enable their coordination. Aims: To develop a geographical mapping facility as an evaluative tool to assist the planning and implementation of Australia's policy on the quality use of medicines. Methods: A web-based database incorporating geographical mapping software was developed. Quality use of medicines projects implemented across the country was identified from project listings funded by the Quality Use of Medicines Evaluation Program, the National Health and Medical Research Council, Mental Health Strategy, Rural Health Support, Education and Training Program, the Healthy Seniors Initiative, the General Practice Evaluation Program and the Drug Utilisation Evaluation Network. In addition, projects were identified through direct mail to persons working in the field. Results: The Quality Use of Medicines Mapping Project (QUMMP) was developed, providing a Web-based database that can be continuously updated. This database showed the distribution of quality use of medicines activities by: (i) geographical region, (ii) project type, (iii) target group, (iv) stakeholder involvement, (v) funding body and (vi) evaluation method. At September 2001, the database included 901 projects. Sixty-two per cent of projects had been conducted in Australian capital cities, where approximately 63% of the population reside. Distribution of projects varied between States. In Western Australia and Queensland, 36 and 73 projects had been conducted, respectively, representing approximately two projects per 100 000 people. By comparison, in South Australia and Tasmania approximately seven projects per 100 000 people were recorded, with six per 100 000 people in Victoria and three per 100 000 people in New South Wales. Rural and remote areas of the country had more limited project activity. Conclusions: The mapping of projects by geographical location enabled easy identification of high and low activity areas. Analysis of the types of projects undertaken in each region enabled identification of target groups that had not been involved or services that had not yet been developed. This served as a powerful tool for policy planning and implementation and will be used to support the continued implementation of Australia's policy on the quality use of medicines.

Toward a better understanding of the influences on physical activity: The role of determinants, correlates, causal variables, mediators, moderators, and confounders

Background: For research on physical activity interventions to progress systematically, the mechanisms of action must be studied. In doing so, the research methods and their associated concepts and terminology become more complex. It is particularly important to clearly distinguish among determinants, correlates, mediators, moderators, and confounder variables used in physical activity research. This article examines the factors that are correlated with and that may have a causal relationship to physical activity. Methods and Results: We propose that the term correlate be used, instead of determinant, to describe statistical associations or correlations between measured variables and physical activity. Studies of the correlates of physical activity are reviewed. The findings of these studies can help to critique existing theories of health behavior change and can provide hypotheses to be tested in intervention studies from which it is possible to draw causal inferences. Mediator, moderator, and confounder variables can act to influence measured changes in physical activity. Intervening causal variables that are necessary to complete a cause-effect pathway between an intervention and physical activity are termed mediators. The relationship between an intervention and physical activity behaviors may vary for different groups; the strata by which they vary are levels of moderators of the relationship. Other factors may distort or affect the observed relationships between program exposure and physical activity, and are known as confounders. Conclusions: Consistent use of terms and additional research on mediators and moderators of intervention effects will improve our ability to understand and influence physical activity.