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Objectives

To determine: (i) the behaviour change techniques used by a sample of Australian physiotherapists to promote non-treatment physical activity; and (ii) whether those behaviour change techniques are different to the techniques used to encourage adherence to rehabilitation exercises.

Design

Cross-sectional survey.

Method

An online self-report survey was advertised to private practice and outpatient physiotherapists treating patients with musculoskeletal conditions. The use of 50 behaviour change techniques were measured using five-point Likert-type scale questions.

Results

Four-hundred and eighty-six physiotherapists responded to the survey, with 216 surveys fully completed. Most respondents (85.1%) promoted non-treatment physical activity often or all of the time. Respondents frequently used 29 behaviour change techniques to promote non-treatment physical activity or encourage adherence to rehabilitation exercises. A similar number of behaviour change techniques was frequently used to encourage adherence to rehabilitation exercises (n = 28) and promote non-treatment physical activity (n = 26). Half of the behaviour change techniques included in the survey were frequently used for both promoting non-treatment physical activity and encouraging adherence to rehabilitation exercises (n = 25). Graded tasks was the most, and punishment was the least, frequently reported technique used to promote non-treatment physical activity and encourage adherence to rehabilitation exercises.

Conclusions

Respondents reported using similar behaviour change techniques to promote non-treatment physical activity and encourage adherence to rehabilitation exercises. The variability in behaviour change technique use suggests the behaviour the physiotherapist is promoting influences their behaviour change technique choice. Including the frequently-used behaviour change techniques in non-treatment physical activity promotion interventions might improve their efficacy.  相似文献   
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Background

Laparoscopic Roux-en-Y gastric bypass, laparoscopic sleeve gastrectomy, and laparoscopic adjustable gastric banding all lead to substantial weight loss in obese patients. Long-term weight loss can be highly variable beyond 1-year postsurgery. This study examines and compares the frequency distribution of weight loss and lack of treatment effect rates after laparoscopic Roux-en-Y gastric bypass, laparoscopic sleeve gastrectomy, and laparoscopic adjustable gastric banding.

Methods

A total of 1,331 consecutive patients at a single academic institution were reviewed from a prospectively collected database. Preoperative data collected included demographics, body mass index, and percent excess weight loss. Postoperative BMI and %EWL were collected at 12, 24, and 36 months. Percent excess weight loss was analyzed by the percentiles of excess weight lost, and the distribution of percent excess weight loss was evaluated in 10% increments. Lack of a successful treatment effect was defined as <25% excess weight loss.

Results

Of the 1,331 patients, 72.4% (963) underwent laparoscopic Roux-en-Y gastric bypass, 18.3% (243) laparoscopic sleeve gastrectomy, and 9.4%(125) laparoscopic adjustable gastric banding. Mean percent excess weight loss was greatest for laparoscopic Roux-en-Y gastric bypass, followed by laparoscopic sleeve gastrectomy, and then by laparoscopic adjustable gastric banding at every time point: at 2 years mean percent excess weight loss was 77.9± 24.4 for laparoscopic Roux-en-Y gastric bypass, 50.8 ± 25.8 for laparoscopic sleeve gastrectomy, and 40.8± 25.9 for laparoscopic adjustable gastric banding (P < .0001). The rates of a successful treatment effect s for laparoscopic Roux-en-Y gastric bypass, laparoscopic sleeve gastrectomy, and laparoscopic adjustable gastric banding were 0.9%, 5.2%, and 24.3% at 1 year; 0.3%, 11.1%, and 26.0% at 2 years; and 1.0%, 25.3%, and 30.2% at 3 years. At 1 year, the odds ratio of lack of a successful treatment effect of laparoscopic sleeve gastrectomy versus laparoscopic Roux-en-Y gastric bypass was 6.305 (2.125–19.08; P?=?.0004), the odds ratio for laparoscopic adjustable gastric banding versus laparoscopic Roux-en-Y gastric bypass was 36.552 (15.64–95.71; P < .0001), and the odds ratio for laparoscopic adjustable gastric banding versus laparoscopic sleeve gastrectomy was 5.791 (2.519–14.599; P < .0001). At 2 years, the odds ratio for laparoscopic sleeve gastrectomy versus laparoscopic Roux-en-Y gastric bypass increased to 70.7 (9.4–531.7; P < .0001), the odds ratio for laparoscopic adjustable gastric banding versus laparoscopic Roux-en-Y gastric bypass increased to 128.1 (16.8–974.3; P < .0001), and the odds ratio for laparoscopic adjustable gastric banding versus laparoscopic sleeve gastrectomy decreased to 1.8 (0.9–3.6; P?=?.09).

Conclusion

This study emphasizes the existing variability in weight loss across bariatric procedures as well as in the lack of a treatment effect for each procedure. Although laparoscopic adjustable gastric banding has the greatest rate of a lack of a successful treatment effect, the rate remained stable over 3 years postoperatively. Laparoscopic sleeve gastrectomy showed a doubling in the rate of a lack of a successful treatment effect every year reaching 25% at year 3. The rates for lack of a successful treatment effect for laparoscopic Roux-en-Y gastric bypass remained stable at about 1% for the first 3 years postoperatively.  相似文献   
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Theory: Immersive simulation is a common mode of education for medical students. Observation of clinical simulations prior to participation is believed to be beneficial, though this is often a passive process. Active observation may be more beneficial. Hypotheses: The hypothesis tested in this study was that the active use of a simple checklist during observation of an immersive simulation would result in better participant performance in a subsequent scenario compared with passive observation alone. Methods: Medical students were randomized to either passive or active (with checklist) observation of an immersive simulation involving cardiac arrest prior to participating in their own simulation. Performance measures included time to cardiopulmonary resuscitation (CPR) and time to defibrillation and were compared between first and second scenarios as well as between passive and active observers. Results: Seventy-nine simulations involving 232 students were conducted. Mean time to CPR was 18 seconds (SD = 11.6) for those using the checklist and 24 seconds (SD = 15.8) for those who observed passively (M difference = 6 seconds), t(35) = 1.46, p =.153. Time to defibrillation was 94 seconds (SD = 26.4) for those using the checklist and 92 seconds (SD = 23.8) for those who observed passively (M difference = –2 seconds), t(38) =.21, p =.837. Time to CPR was 24 seconds (SD = 15.8) for passive observers and 31 seconds (SD = 21.0; M difference = 7 seconds), t(35) = 1.13, p =.265, for their first scenario counterparts. Time to CPR was 18 seconds (SD = 11.6) for active observers and 36 seconds (SD = 26.2; M difference = 18 seconds), t(24) = 2.81, p =.010, for their first scenario counterparts. Time to defibrillation was 92 seconds (SD = 23.8) for passive observers and 125 seconds (SD = 32.2; M difference = 33 seconds), t(33) = 3.63, p =.001, for their first scenario counterparts. Time to defibrillation was 94 seconds (SD = 26.4) for the active observers and 132 seconds (SD = 52.9; M difference = 38 seconds), t(28) =.46, p =.008, for their first scenario counterparts. Conclusions: Observation alone leads to improved performance in the management of a simulated cardiac arrest. The active use of a simple skills-based checklist during observation did not appear to improve performance over passive observation alone.  相似文献   
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