Purpose: The purpose of this study was to understand how implementing EIM influenced provider behaviors in a university-based healthcare system, using a process evaluation.
Methods: A multiple baseline, time series design was used. Providers were allocated to three groups. Group 1 (n=11) was exposed to an electronic medical record (EMR) systems change, EIM-related resources, and EIM training session. Group 2 (n=5) received the EMR change and resources but no training. Group 3 (n=6) was only exposed to the systems change. The study was conducted across three phases. Outcomes included asking about patient physical activity (PA) as a vital sign (PAVS), prescribing PA (ExRx), and providing PA resources or referrals. Patient surveys and EMR data were examined. Time series analysis, chi-square, and logistic regression were used.
Results: Patient survey data revealed the systems change increased patient reports of being asked about PA, χ2(4) = 95.47, p < .001 for all groups. There was a significant effect of training and resource dissemination on patients receiving PA advice, χ2(4) = 36.25, p < .001. Patients receiving PA advice was greater during phase 2 (OR = 4.7, 95% CI = 2.0-11.0) and phase 3 (OR = 2.9, 95% CI = 1.2-7.4). Increases were also observed in EMR data for PAVS, χ2(2) = 29.27, p <. 001 during implementation for all groups. Increases in PA advice χ2(2) = 140.90, p < .001 occurred among trained providers only. No statistically significant change was observed for ExRx, PA resources or PA referrals. However, visual analysis showed an upwards trend among trained providers.
Conclusions: An EMR systems change is effective for increasing the collection of the PAVS. Training and resources may influence provider behavior but training alone increased provider documentation. The low levels of documented outcomes for PA advice, ExRx, resources, or referrals may be due to the limitations of the EMR system. This approach was effective for examining the EIM Solution and scaled-up, longer trials may yield more robust results.
This study aimed to investigate the effects of specific macronutrient feedings on competitive golf performance and perceived levels of fatigue and alertness. Participants played three, nine hole rounds of golf, consuming an isocaloric beverage as a control (CON), with the addition of carbohydrate (CHO), or combination of protein and carbohydrate (COM). Physiological and performance measurements were taken before, during, and following each nine hole round. Performance measurements include driving accuracy (DA), driving distance (DD), iron accuracy (IA), chipping accuracy (CA), and putting accuracy (PA). Pre-golf hydration status (urine specific gravity [USG]) and Sweat Rate during golf performance showed no significant differences between trials. All nine hole rounds were performed in ~2 hours. Environmental conditions were similar for all three testing days (mean WBGT=10.946). No significant differences were seen in Driving Distance, Driving Accuracy, and Iron Accuracy for all nine holes between groups receiving different macronutrient feedings. Chipping Accuracy was significantly better in CON trial compared to CHO (p=0.004) and COM (p=0.019). No significant differences were seen in putting make percentages. COM trial significantly lowered Perceived Levels of Fatigue (p=0.019) compared to CON. The CHO trial showed significant improvements in DA compared to CON (13.7 vs. 44.1, p=0.012) and COM (13.7 vs. 33.6, p=0.004) in the first four holes. In the last five holes, the COM trial showed significant improvements in DA compared to CHO (17.5 vs. 29.7, p=0.007). Low Handicap golfers (3 +/- 3) performed significantly better than High Handicap golfers (14 +/- 3.6) in DD (265 vs. 241, p<0.001), DA (15.0 vs. 29.3, p=0.004), IA (15.2 vs. 25.2, p<0.001), CA (52.0 vs. 61.5, p=0.027), and PA 5ft (64% vs. 40%, p=0.003). High Handicap players showed no significant differences between the three trials for any golf performance measurements. Low Handicap players showed significant improvements in DA for COM trial compared to CON trial (13.6 vs. 27.6, p=0.003). The results suggest that carbohydrates at the start and a combination of carbohydrate and protein is beneficial at the second part of 9 holes to improve golf performance and maintain levels of fatigue, however, it needs to be investigated how this knowledge will relate to playing more holes.
The study used a cross-sectional design and participants consisted of 180 undergraduate university students (aged 18 to 24 years). Participants completed a one-time survey that assessed demographic characteristics, trait mindfulness, behavioral regulation toward exercise, exercise intention, perceived stress and PA. Bivariate associations between the variables were assessed with Pearson or Spearman correlations. A logistic regression analysis was conducted to determine which variables were independently associated with meeting weekly, leisure-time MVPA guidelines. Results of this study found weak positive associations between the mindfulness domain of acceptance and leisure time MVPA ( = .168, p < .05), no associations between mindfulness and transportation PA, and negative associations between mindfulness (MAAS, = –.238, p < .01; acceptance, = –.175, p < .05) and sitting time. Results of logistic regression found that only relative autonomy (OR = 1.085, 95% CI [1.008, 1.168], p = .030) and intention (OR = 2.193, 95% CI [1.533, 3.138], p < .0001) were independently associated with meeting weekly, leisure- time MVPA recommendations. The results of this study show that while there is only a weak direct relationship between trait mindfulness and PA, mindfulness may be related with other factors associated with PA. More research is needed in order to better understand the potential mechanisms behind the results found in this, and past, studies.