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Introduction: Despite the fact that hotels provide a venue for sleeping, there is surprisingly little research that has explored sleep among hotel guests. The aim of this study is to identify the relationship between hotel attributes (e.g., light in the guestroom, bed linens), guest sleep, and overall guest satisfaction. Methods: Cross-sectional survey data were obtained from frequent business and leisure travelers (N = 609). Guest sleep satisfaction and overall guest satisfaction were measured on 5-point Likert scales. Participants were asked to report the extent to which hotel attributes (e.g., "Room too light or too dark") related to their sleep on a scale from 1 (not at all) to 5 (very much). We used ordinal logistic regression to predict guest sleep and hotel satisfaction using hotel attributes as predictors while controlling for age, sex, and relationship status. Results: Hotel guest sleep did not differ between business and leisure travelers. Hotel guest sleep was inversely associated with "uncomfortable bed linen," "uncomfortable pillows," and "sound from the air conditioning unit or heater." Regression revealed that sleep satisfaction was a strong predictor of overall hotel satisfaction. Conclusions: Our study suggests that guest sleep is be a critical component of the guest satisfaction equation. Importantly, our study illuminated the hotel attributes that offer the biggest contribution to hotel guest sleep and the specific steps for improving guest sleep.
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OBJECTIVE: To explore predictors of intention of college students to use calorie labels on fast-food menus and differences in calories ordered after viewing calorie information. DESIGN: Quasi-experimental design. Participants selected a meal from a menu without calorie labels, selected a meal from the same menu with calorie labels, and completed a survey that assessed demographics, dietary habits, Theory of Planned Behavior constructs, and potential barriers to use of calorie labeling. SETTING: A southern university. PARTICIPANTS: Undergraduate university students (n = 97). MAIN OUTCOME MEASURES: Predictors of intention to use calorie labels and whether calories selected from the nonlabeled menu differed from the labeled menu. ANALYSIS: Confirmatory factor analysis, exploratory factor analysis, multiple regression, and paired t tests. RESULTS: Participants ordered significantly fewer calories (P = .02) when selecting from the labeled menu vs the menu without labels. Attitudes (P = .006), subjective norms (P < .001), and perceived behavioral control (P = .01) predicted intention to use calorie information but did not predict a difference in the calories ordered. Hunger (P = .03) and cost (P = .04) were barriers to using the calorie information. CONCLUSIONS AND IMPLICATIONS: If students can overcome barriers, calorie labeling could provide information that college students need to select lower-calorie items at fast-food restaurants.