Youth’s narratives about family members smoking: parenting the parent- it’s not fair!

<p>Abstract</p> <p>Background</p> <p>Successful cancer prevention policies and programming for youth must be based on a solid understanding of youth’s conceptualization of cancer and cancer prevention. Accordingly, a qualitative study examining youth’s perspectives of cancer and its prevention was undertaken. Not surprisingly, smoking (i.e., tobacco cigarette smoking) was one of the dominant lines of discourse in the youth’s narratives. This paper reports findings of how youth conceptualize smoking with attention to their perspectives on parental and family-related smoking issues and experiences.</p> <p>Methods</p> <p>Seventy-five Canadian youth ranging in age from 11–19 years participated in the study. Six of the 75 youth had a history of smoking and 29 had parents with a history of smoking. Youth were involved in traditional ethnographic methods of interviewing and photovoice. Data analysis involved multiple levels of analysis congruent with ethnography.</p> <p>Results</p> <p>Youth’s perspectives of parents and other family members’ cigarette smoking around them was salient as represented by the theme: <it>It’s not fair.</it> Youth struggled to make sense of why parents would smoke around their children and perceived their smoking as an unjust act. The theme was supported by four subthemes: <it>1) parenting the parent about the dangers of smoking; 2) the good/bad parent; 3) distancing family relationships; and 4) the prisoner</it>. Instead of being <it>talked to</it> about smoking it was more common for youth to share stories of <it>talking to</it> their parents about the dangers of smoking. Parents who did not smoke were seen by youth as the good parent, as opposed to the bad parent who smoked. Smoking was an agent that altered relationships with parents and other family members. Youth who lived in homes where they were exposed to cigarette smoke felt like a trapped prisoner.</p> <p>Conclusions</p> <p>Further research is needed to investigate youth’s perceptions about parental cigarette smoking as well as possible linkages between youth exposed to second hand smoke in their home environment and emotional and lifestyle-related health difficulties. Results emphasize the relational impact of smoking when developing anti-tobacco and cancer prevention campaigns. Recognizing the potential toll that second-hand smoke can have on youth’s emotional well-being, health care professionals are encouraged to give youth positive messages in coping with their parents’ smoking behaviour.</p

Distinguishing Asthma Phenotypes Using Machine Learning Approaches.

Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as asthma endotypes. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies

An Information Theory Approach to Hypothesis Testing in Criminological Research

Background: This research demonstrates how the Akaike information criterion (AIC) can be an alternative to null hypothesis significance testing in selecting best fitting models. It presents an example to illustrate how AIC can be used in this way. Methods: Using data from Milwaukee, Wisconsin, we test models of place-based predictor variables on street robbery and commercial robbery. We build models to balance explanatory power and parsimony. Measures include the presence of different kinds of businesses, together with selected age groups and social disadvantage. Results: Models including place-based measures of land use emerged as the best models among the set of tested models. These were superior to models that included measures of age and socioeconomic status. The best models for commercial and street robbery include three measures of ordinary businesses, liquor stores, and spatial lag. Conclusions: Models based on information theory offer a useful alternative to significance testing when a strong theoretical framework guides the selection of model sets. Theoretically relevant ‘ordinary businesses’ have a greater influence on robbery than socioeconomic variables and most measures of discretionary businesses

Dusty: an assistive mobile manipulator that retrieves dropped objects for people with motor impairments

People with physical disabilities have ranked object retrieval as a high priority task for assistive robots. We have developed Dusty, a teleoperated mobile manipulator that fetches objects from the floor and delivers them to users at a comfortable height. In this paper, we first demonstrate the robot's high success rate (98.4%) when autonomously grasping 25 objects considered important by people with amyotrophic lateral sclerosis (ALS). We tested the robot with each object in five different configurations on five types of flooring. We then present the results of an experiment in which 20 people with ALS operated Dusty. Participants teleoperated Dusty to move around an obstacle, pick up an object, and deliver the object to themselves. They successfully completed this task in 59 out of 60 trials (3 trials each) with a mean completion time of 61.4 seconds (SD=20.5 seconds), and reported high overall satisfaction using Dusty (7-point Likert scale; 6.8 SD=0.6). Participants rated Dusty to be significantly easier to use than their own hands, asking family members, and using mechanical reachers (p < 0.03, paired t-tests). 14 of the 20 participants reported that they would prefer using Dusty over their current methods