Protocol: A randomised controlled trial evaluation of Cancer Focus NI’s ‘Dead Cool’ smoking prevention programme in post-primary schools

This paper presents a research protocol for a randomised controlled efficacy trial of the ‘Dead Cool’ smoking prevention programme. Dead Cool is a three to four-hour programme designed to be used by teachers with Year 9 students in Northern Ireland. The main outcome of the programme is to prevent students from starting to smoke. The protocol reports a research design intended to test the efficacy of the programme in 20 post-primary school settings. Selected schools included those from secondary /grammar/integrated/single sex/coeducational, rural and urban schools from both the maintained and controlled state sector and independent sector schools. Outcome measures include self-reported behaviours, monitoring of carbon monoxide (CO) in exhaled breath and focus groups designed to assess implementation fidelity and opinions on efficacy in intervention schools and explore the ‘counterfactual’ potential treatments in control schools.

Unsupervised Solution Post Identification from Discussion Forums

Discussion forums have evolved into a dependablesource of knowledge to solvecommon problems. However, only a minorityof the posts in discussion forumsare solution posts. Identifying solutionposts from discussion forums, hence, is animportant research problem. In this paper,we present a technique for unsupervisedsolution post identification leveraginga so far unexplored textual feature, thatof lexical correlations between problemsand solutions. We use translation modelsand language models to exploit lexicalcorrelations and solution post characterrespectively. Our technique is designedto not rely much on structural featuressuch as post metadata since suchfeatures are often not uniformly availableacross forums. Our clustering-based iterativesolution identification approach basedon the EM-formulation performs favorablyin an empirical evaluation, beatingthe only unsupervised solution identificationtechnique from literature by a verylarge margin. We also show that our unsupervisedtechnique is competitive againstmethods that require supervision, outperformingone such technique comfortably.