Six-month outcomes of a multi-campus smoking cessation contest

Background: Up to 40% of North American post-secondary students smoke at least occasionally, and most want to quit. Given students' preferences for free, easy-to-access, self-directed, convenient cessation methods, a motivational, incentive-based cessation contest may be an effective way to assist students to quit. The current study describes 3- and 6-month outcomes experienced by post-secondary student smokers who entered the 'Let's Make A Deal!' contest. Methodology: Contestants from five university campuses who chose to quit completely ('Quit For Good') or reduce their tobacco consumption by 50% ('Keep The Count') were invited to participate in a study of the contest. Three and six months after registration, participants were contacted by phone to assess their smoking and quitting behaviours. Qualitative and quantitative measures were collected, including weekly tobacco consumption, efficacy to resist temptations to smoke, use of quitting aids, and strategies to cope with withdrawal. Quitting was assessed using 7-day point prevalence and continuous abstinence. Results: Seventy-four (64.9%) of the 114 participants recruited for the study completed the follow-ups. Over 31 % of participants who entered Quit For Good and 23.5% of participants who entered Keep The Count were identified as quitters at the 6-month follow-up. Among the quitters, 45.5% experienced sustained abstinence from smoking for the 6-month duration of the study. Keep The Count contestants reduced their tobacco consumption by 57.2% at 3-month follow-up and sustained some of this reduction through to the 6-month follow-up. Qualitative data provides insights into how quitters coped with withdrawal and what hampered continuing smokers' efforts to quit. Significance: A motivational, incentive-based contest for post-secondary students can facilitate both smoking cessation and harm reduction. The contest environment, incentives, resources, and "buddies" provide positive structural and social supports to help smokers overcome potential barriers to quitting, successfully stop smoking, and manage potential triggers to relapse. The contest cessation rates are higher than the typical 5-7% associated with unassisted quitting.

What gets plans off the shelf? : a multi-site case study of the factors influencing municipal recreation plan implementation

Municipalities that engage in recreation planning have the potential to use their resources more effectively. However, successful planning means getting the plan off the shelf and implemented. This study investigated the factors that influenced municipal recreation plan implementation in three municipalities. Interviews were conducted with eleven key informants (recreation directors, planning consultants, a city councillor, and members of plan steering committees). The findings of this study suggested that because the implementation of recreation plans occurs in a highly political environment, recreation professionals will need effective strategies to get their plans implemented and that implementation can be facilitated by developing or expanding strategies that: (l) build the power of the recreation department within the municipal government structure; (2) build support for recreation within the local community; and (3) build the political and organizational capacity in the recreation department.

Generating Aesthetically Pleasing Images in a Virtual Environment using Particle Swarm Optimization

This research focuses on generating aesthetically pleasing images in virtual environments using the particle swarm optimization (PSO) algorithm. The PSO is a stochastic population based search algorithm that is inspired by the flocking behavior of birds. In this research, we implement swarms of cameras flying through a virtual world in search of an image that is aesthetically pleasing. Virtual world exploration using particle swarm optimization is considered to be a new research area and is of interest to both the scientific and artistic communities. Aesthetic rules such as rule of thirds, subject matter, colour similarity and horizon line are all analyzed together as a multi-objective problem to analyze and solve with rendered images. A new multi-objective PSO algorithm, the sum of ranks PSO, is introduced. It is empirically compared to other single-objective and multi-objective swarm algorithms. An advantage of the sum of ranks PSO is that it is useful for solving high-dimensional problems within the context of this research. Throughout many experiments, we show that our approach is capable of automatically producing images satisfying a variety of supplied aesthetic criteria.