The experience of smoking in recovery settings: an ecological momentary assessment pilot study

ABSTRACT

Smoking continues to be the leading cause of preventable death in the United States, and people with substance use disorders (SUD) smoke at higher rates compared to their non-using counterparts. Individuals with SUDs may have different emotional experiences and expectancies than those without. The current study explored the relationship between smoking and emotional experiences among residents in recovery homes, a population that little is known about regarding their tobacco addiction. Using ecological momentary assessment (EMA), significant emotional differences were found between nicotine users and nonusers. Implications of these findings could help in the development of interventions directed toward reducing smoking cessation.     

The Emergence of Flood Insurance in Canada: Navigating Institutional Uncertainty

Flood insurance has remained unavailable in Canada based on an assessment that it lacks economic viability. In response to Canada's costliest flood event to date in 2013, the Canadian insurance industry has started to develop a framework to expand existing property insurance to cover flood damage. Research on flood insurance has overlooked why and how insurance systems transition to expand insurance coverage without evidence of economic viability. This article will address this gap through a case study on the emergence of flood insurance in Canada, and the approach to its expansion. Between 2013 and 2016, insurance industry officials representing over 60% of premiums collected in Canada were interviewed. These interviews revealed that flood insurance is being expanded in response to institutional pressure, specifically external stakeholder expectations that the insurance industry will adopt a stronger role in managing flood risk through coverage of flood damage. Further evidence of this finding is explored by assessing the emergence of a unique flood insurance model that involves a risk‐adjusted and optional product along with an expansion of government policy supporting flood risk mitigation. This approach attempts to balance industry concerns about economic viability with institutional pressure to reduce flood risk through insurance. This analysis builds on existing research by providing the first scholarly analysis of flood insurance in Canada, important “empirical” teeth to existing conceptual analysis on the availability of flood insurance, and the influence of institutional factors on risk analysis within the insurance sector.     

Norm-preserving constraint in the Fisher–Rao registration and its application in signal estimation

Registration of temporal observations is a fundamental problem in functional data analysis. Various frameworks have been developed over the past two decades where registrations are conducted based on optimal time warping between functions. Comparison of functions solely based on time warping, however, may have limited application, in particular when certain constraints are desired in the registration. In this paper, we study registration with norm-preserving constraint. A closely related problem is on signal estimation, where the goal is to estimate the ground-truth template given random observations with both compositional and additive noises. We propose to adopt the Fisher–Rao framework to compute the underlying template, and mathematically prove that such framework leads to a consistent estimator. We then illustrate the constrained Fisher–Rao registration using simulations as well as two real data sets. It is found that the constrained method is robust with respect to additive noise and has superior alignment and classification performance to conventional, unconstrained registration methods.     

A latent class analysis of young adult gamblers from the Manitoba Longitudinal Survey of Young Adults

Informed by the Pathways Model, the current study utilized latent class analysis (LCA) to empirically derive subtypes of gamblers based on measures of impulsivity, anxiety, depression, drug use and alcohol dependence. The sample in this study (N = 566) was comprised of young adult gamblers (18–22 years of age) who participated in the Manitoba Longitudinal Survey of Young Adults (MLSYA). Multinomial regression was utilized to examine how demographic variables and participant scores on the Problem Gambling Severity Index (PGSI) predicted membership in gambler classes from the LCA. Results of the LCA revealed three classes of gamblers: emotionally vulnerable, non-problem and impulsive. Multinomial regression showed that older age (i.e. 20–22 years of age), lower income (< $20,000 per year), living independently and PGSI scores were associated with increased odds of being classified as an impulsive gambler. Identifying as European, living independently and PGSI scores were associated with increased odds of being grouped in the emotionally vulnerable class of gambler. These results suggest that young adult gamblers are not a homogeneous group but instead are best understood as falling into different subtypes based on shared characteristics outlined in the Pathways Model.     

Re-approaching interview data through qualitative secondary analysis: interviews with internet gamblers

ABSTRACT

This paper addresses two interrelated questions concerning what interview data are and how researchers might use them. The first considers the value of a shift from a predominant or exclusive focus upon how data are constructed and produced at interview, and towards how such data might be apprehended through different forms of engagement. The second question relates to how and what qualitative secondary analysis (QSA) might be used to tell about the social world. In exploring this, we advance a critique of the divide between primary and secondary analysis, recasting the debate in terms of different degrees and qualities of ‘proximity’ and ‘distance’ from the formative contexts of data generation, and the distinctive analytical affordances that relate to these. Using QSA of interview data from a study of problem internet gambling as an empirical crucible, we consider the kinds of participation that interviewees develop through reciprocal engagement with interviewers. We illustrate how participants reflexively negotiate the affordances and limits to the narratives through which they frame and recount their experiences. Finally, we show how interview data can be used both to speak of the temporal, relational, spatial, epistemic contexts of their production, and also to contexts and questions beyond these.     

“Beating the Bad Rap:” A Qualitative Study of Social Studies Educators Using Film

Abstract

The film-based practices of four social studies teachers were examined using a qualitative methodology. The research interviewed teachers twice over a 2-month period, collected handouts, and collected audio-recorded teacher logs. Three of the teachers taught social studies primarily, while a fourth teacher was responsible for both English and social studies content. The findings indicate that teachers used film in addition to a wide range of other visual practices. Teachers used film actively rather than passively to facilitate dialogic connections, as well as elicit thinking about their content areas.     

A flexible parametric survival model for fitting time to event data in clinical trials

Time‐to‐event data are common in clinical trials to evaluate survival benefit of a new drug, biological product, or device. The commonly used parametric models including exponential, Weibull, Gompertz, log‐logistic, log‐normal, are simply not flexible enough to capture complex survival curves observed in clinical and medical research studies. On the other hand, the nonparametric Kaplan Meier (KM) method is very flexible and successful on catching the various shapes in the survival curves but lacks ability in predicting the future events such as the time for certain number of events and the number of events at certain time and predicting the risk of events (eg, death) over time beyond the span of the available data from clinical trials. It is obvious that neither the nonparametric KM method nor the current parametric distributions can fulfill the needs in fitting survival curves with the useful characteristics for predicting. In this paper, a full parametric distribution constructed as a mixture of three components of Weibull distribution is explored and recommended to fit the survival data, which is as flexible as KM for the observed data but have the nice features beyond the trial time, such as predicting future events, survival probability, and hazard function.     

Timing and Sequence of Events: HIV Status Disclosure,Condomless Anal Sex,and Sexual Agreement Formation Among Same-Sex Male Couples

Despite the implications for human immunodeficiency virus (HIV) prevention and sexual health, little is known about the timing and chronological order of when same-sex male couples disclose their HIV serostatus, establish a sexual agreement, and first engage in condomless anal sex (CAS) in their relationships. Dyadic data from 357 dyads were used to describe when these respective events occurred; whether members of a couple concurred about when the events happened; and the chronological order of these events. For many, disclosure and CAS happened within the first month, whereas an agreement tended to occur much later (if at all). Couples’ concordance of when disclosure and agreement formation happened differed by their serostatus, whereas there was little difference by serostatus for CAS. The chronological order of these events revealed interesting patterns and varied substantially. Although two-thirds of partners reported disclosure had occurred first, some reported events happening on the same day. These findings reveal that the first few months in a same-sex male couple’s relationship is a critical time period for when information and decisions about sexual health occur. Suggestions are provided for how current and future HIV prevention efforts could assist couples with their sexual health needs.     

1998 Annual Meeting Plenary Session: Assessing and Managing Risks in a Democratic Society

The theme of one of the plenary sessions held at the 1998 annual meeting of the Society for Risk Analysis, 'Assessing and Managing Risks in a Democratic Society,' was chosen to reflect the current debate about the best ways to integrate social, political, economic, and technical issues into fair risk management decisions. In the papers presented here, the three plenary speakers provide their perspectives on how environmental risk management decision making is—or should be—informed by democratic processes.
John D. Graham Making Sense of Risk
Robert F. Kennedy, Jr. Risk, Democracy, and the Environment
Jason Shogren Markets to Master Health and Environmental Risk
Audience Questions and Answers     

IT security planning under uncertainty for high-impact events

While many IT security incidents result in relatively minor operational disruptions or minimal recovery costs, occasionally high-impact security breaches can have catastrophic effects on the firm. Unfortunately, measuring security risk and planning for countermeasures or mitigation is a difficult task. Past research has suggested risk metrics which may be beneficial in understanding and planning for security incidents, but most of these metrics are aimed at identifying expected overall loss and do not directly address the identification of, or planning for, sparse events which might result in high-impact loss. The use of an upper percentile value or some other worst-case measure has been widely discussed in the literature as a means of stochastic optimization, but has not been applied to this decision domain. A key requirement in security planning for any threat scenario, expected or otherwise, is the ability to choose countermeasures optimally with regard to tradeoffs between countermeasure cost and remaining risk. Most of the planning models in the literature are qualitative, and none that we are aware of allow for the optimal determination of these tradeoffs. Therefore, we develop a model for optimally choosing countermeasures to block or mitigate security attacks in the presence of a given threat level profile. We utilize this model to examine scenarios under both expected threat levels and worst-case levels, and develop budget-dependent risk curves. These curves demonstrate the tradeoffs which occur if decision makers divert budgets away from planning for ordinary risk in an effort to mitigate the effects of potential high-impact outcomes.