33 resultados para Multi-attribute utility theory
Resumo:
Purpose: To assess the compliance of Daily Disposable Contact Lenses (DDCLs) wearers with replacing lenses at a manufacturer-recommended replacement frequency. To evaluate the ability of two different Health Behavioural Theories (HBT), The Health Belief Model (HBM) and The Theory of Planned Behaviour (TPB), in predicting compliance. Method: A multi-centre survey was conducted using a questionnaire completed anonymously by contact lens wearers during the purchase of DDCLs. Results: Three hundred and fifty-four questionnaires were returned. The survey comprised 58.5% females and 41.5% males (mean age 34. ±. 12. years). Twenty-three percent of respondents were non-compliant with manufacturer-recommended replacement frequency (re-using DDCLs at least once). The main reason for re-using DDCLs was "to save money" (35%). Predictions of compliance behaviour (past behaviour or future intentions) on the basis of the two HBT was investigated through logistic regression analysis: both TPB factors (subjective norms and perceived behavioural control) were significant (p. <. 0.01); HBM was less predictive with only the severity (past behaviour and future intentions) and perceived benefit (only for past behaviour) as significant factors (p. <. 0.05). Conclusions: Non-compliance with DDCLs replacement is widespread, affecting 1 out of 4 Italian wearers. Results from the TPB model show that the involvement of persons socially close to the wearers (subjective norms) and the improvement of the procedure of behavioural control of daily replacement (behavioural control) are of paramount importance in improving compliance. With reference to the HBM, it is important to warn DDCLs wearers of the severity of a contact-lens-related eye infection, and to underline the possibility of its prevention.
Resumo:
The frequency, time and places of charging have large impact on the Quality of Experience (QoE) of EV drivers. It is critical to design effective EV charging scheduling system to improve the QoE of EV drivers. In order to improve EV charging QoE and utilization of CSs, we develop an innovative travel plan aware charging scheduling scheme for moving EVs to be charged at Charging Stations (CS). In the design of the proposed charging scheduling scheme for moving EVs, the travel routes of EVs and the utility of CSs are taken into consideration. The assignment of EVs to CSs is modeled as a two-sided many-to-one matching game with the objective of maximizing the system utility which reflects the satisfactory degrees of EVs and the profits of CSs. A Stable Matching Algorithm (SMA) is proposed to seek stable matching between charging EVs and CSs. Furthermore, an improved Learning based On-LiNe scheduling Algorithm (LONA) is proposed to be executed by each CS in a distributed manner. The performance gain of the average system utility by the SMA is up to 38.2% comparing to the Random Charging Scheduling (RCS) algorithm, and 4.67% comparing to Only utility of Electric Vehicle Concerned (OEVC) scheme. The effectiveness of the proposed SMA and LONA is also demonstrated by simulations in terms of the satisfactory ratio of charging EVs and the the convergence speed of iteration.
Resumo:
Background: The present study tested the utility of the theory of planned behaviour (TPB), augmented with anticipated regret, as a model to predict binge-drinking intentions and episodes among female and male undergraduates and undergraduates in different years of study. Method: Undergraduate students (N = 180, 54 males, 126 females, 60 per year of study) completed baseline measures of demographic variables, binge-drinking episodes (BDE), TPB constructs and anticipated regret. BDE were assessed one-week later. Results: The TPB accounted for 60% of the variance in female undergraduates' intentions and 54% of the variance in male undergraduates' intentions. The TPB accounted for 57% of the variance in intentions in first-year undergraduates, 63% of the variance in intentions in second-year undergraduates and 68% of the variance in intentions in final-year undergraduates. Follow-up BDE was predicted by intentions and baseline BDE for female undergraduates as well as second- and final-year undergraduates. Baseline BDE predicted male undergraduates’ follow-up BDE and first-year undergraduates’ follow-up BDE. Conclusion: Results show that while the TPB constructs predict undergraduates’ binge-drinking intentions, intentions only predict BDE in female undergraduates, second- and final-year undergraduates. Implications of these findings for interventions to reduce binge drinking are outlined.