13 research outputs found
Factors predicting smoking in a laboratory-based smoking-choice task
No full textThis study aimed to expand the current understanding of smoking maintenance mechanisms by examining how putative risk factors of relapse relate to a single behavioral smoking choice using a novel laboratory smoking-choice task. After 12 hours of nicotine deprivation, participants were exposed to smoking cues and given the choice between smoking up to two cigarettes in a 15-minute window or waiting and receiving four cigarettes after a delay of 45 minutes. This single behavioral choice was meant to model real-world choices to forgo the immediate gratification of smoking to achieve delayed benefits associated with abstinence. Greater nicotine dependence, higher impulsivity, and lower distress tolerance were hypothesized to predict earlier and more intensive smoking. Out of 35 participants, 26 chose to smoke with a median time to a first puff of 1.22 minutes (standard deviation=2.62 min, range=0.03-10.62 min). Survival analyses examined latency to first puff, and results indicated that greater pre-task craving and smoking more cigarettes per day were significantly related to smoking sooner in the task. Greater behavioral disinhibition was a significant risk factor predicting shorter smoking latency in the first two minutes of the task, but not at a delay of more than two minutes. Lower distress tolerance (reporting greater regulation efforts to alleviate distress) was related to more puffs smoked during the task. This novel laboratory smoking-choice paradigm may be a useful laboratory analog for the choices smokers make during cessation attempts and may help identify factors that influence smoking lapses.M.S.Includes bibliographical referencesby Krysten Williams Bol
Independent and interactive effects of real-time risk factors on later temptations and lapses among smokers trying to quit
No full textResearch on the proximal influences on smoking relapse has focused primarily on the independent effects of risk factors, yet relapse may also be governed by complex, interactive processes. The current study sought to expand our understanding of relapse mechanisms by identifying the independent and interactive effects of real-time risk factors on temptations and the ability to resist temptations in smokers during a quit attempt. This study was a secondary analysis of ecological momentary assessment data collected from 109 treatment-seeking smokers 4 times a day for 21 days following a quit attempt. All smokers received nicotine replacement therapy and smoking cessation counseling. Multinomial hierarchical linear models were used to evaluate ways momentary impulsiveness, affect, urge, cigarette exposure, alcohol use and their interactions predicted temptations and smoking up to 8 hours later. Level-one data comprised report-level predictors and outcomes nested within individuals at level-two. Results suggested temptations were predicted by higher momentary agitation, distress, and urge; and lower positive affect. The inability to resist temptations was predicted by prior smoking, higher distress, and recent alcohol use. There were significant interactions between level-one predictors that influenced the risk of temptations (positive affect x impulsiveness, urge x agitation, agitation x cigarette exposure, urge x cigarette exposure) and the odds of resisting a temptation (alcohol x impulsiveness). These results suggest studies of complex relationships between proximal risk factors may provide new information about relapse processes and inform smoking cessation interventions.Ph.D.Includes bibliographical referencesby Krysten Williams Bol
Exploring the Relation between Confidence and Accuracy in Recognition Memory
No full textabstract: Recognition memory is examined by exposing a person to a stimulus and later prompting them with the same stimulus to examine their ability to accurately acknowledge that the stimulus was previously encountered (Kahana, 2012). In recognition memory, confidence ratings are taken during the testing phase to assess how confident the participant is that the old-new judgment that they just made is accurate (Busey et al., 2000). Confidence is a metacognitive assessment about the accuracy of perception of decision making based on the amount, speed, and clarity of thoughts that come to mind (Dunlosky and Metcalfe, 2008). The goal of the current study is to better understand how assessing recognition memory using a variety of test procedures influences memory accuracy using the signal detection theory and adding multiple confidence scales that vary in granularity. Based on the previous literature, it is hypothesized that; 1) tasks ordered sequentially will produce greater recognition accuracy (d') than the simultaneous (dual task) condition; 2) confidence scale of 3 points will produce a larger d' than the 7 point scale, and the 7 point scale will produce a larger d' than the 100 point scale; and 3) task mode (ordered vs. sequenced) will interact with confidence scale granularity to predict memory accuracy, such that sequential judgments lessen demands on working memory that come from maintaining an increasing number of decision criteria in comparison to the dual task. Results indicated all hypotheses were not upheld. The findings suggest that taxing working memory may not affect decisional accuracy on a recognition task incorporating confidence judgments
Supplemental Tables and References for, “The Royal Canadian Mounted Police (RCMP) Study: Protocol for a Prospective Investigation of Mental Health Risk and Resilience Factors”
No full textThe current link provides access to the supplemental materials described in the publication.The Royal Canadian Mounted Police (RCMP), like all public safety personnel (PSP), are frequently exposed to potentially psychologically traumatic events that contribute to posttraumatic stress injuries (PTSIs). Addressing PTSI is impeded by the limited available research. In this protocol paper, we describe the RCMP Study, part of the concerted efforts by the RCMP to reduce PTSI by improving access to evidence-based assessments, treatments and training, as well as participant recruitment and RCMP Study developments to date.
The RCMP Study has been designed to (1) develop, deploy and assess the impact of a system for ongoing annual, monthly and daily evidence-based assessments; (2) evaluate associations between demographic variables and PTSI; (3) longitudinally assess individual differences associated with PTSI; (4) augment the RCMP Cadet Training Program with skills to proactively mitigate PTSI; and (5) assess the impact of the augmented training condition (ATC) versus the standard training condition (STC). Participants in the STC (n = 480) and ATC (n = 480) are assessed before and after training and annually for 5 years on their deployment date; they also complete brief monthly and daily surveys.
The RCMP Study results are expected to benefit the mental health of all participants, RCMP and PSP by reducing PTSI among all who serve.The current study was supported by the RCMP, the Government of Canada, and the Ministry of Public Safety and Emergency Preparedness. Special thanks to the following people (alphabetically by last name) who have provided tremendous support for the current study in several different ways since inception: RCMP and Government Leaders - William Sterling Blair, Jasmin Breton, Sylvie Châteauvert, Daniel Dubeau, Ralph Edward Goodale, Louise Lafrance, Brenda Lucki, Sylvie Bourassa Muise, Robert Paulson, Stephen White; Academics - Kelly J. Abrams, Billea Ahlgrim, Katie Andrews, Myles Ferguson, Jennifer Gordon, Chet Hembroff, Bridget Klest, Jolan Nisbet, Laurie Sykes-Tottenham, Kristi Wright; University of Regina executive, administrative, and technical team members - Olabisi Adesina, Seerat Bassi, Chris Beckett, Brad Berezowski, Jonathan Burry, Murray Daku, Krysten Forbes, Jolene Goulden, Sally Gray, Kadie Hozempa, Xiaoqian Huang, Maria Kamil, Anita Kohl, Donna King, Jordan MacNeil, David Malloy, Akiff Maredia, Kathy McNutt, Megan Milani, Sara Moradizadeh, Sajid Naseem, Obimma Onuegbu, Abimbola Ogunkoyode, Steve Palmer, Cynthia Sanders, Mikhail Shchukin, Shubham Sharma, Vianne Timmons, Preeti Tyagi, Abinyah Walker, Keyur Variya, Christopher Yost, Zhe Zhang; Clinical staff and supervised clinicians - Andreanne Angehrn, Michael Edmunds, Amelie Fournier, Lis Hansen, Stephanie Korol, Caeleigh Landry, Katherine Mazenc, Michelle Paluszek, Vanessa Peynenburg, Lloyd Robertson, Robyn Shields, Joelle Soucy, Emilie Thomas, Vivian Tran.
Author Funding Declaration(s). L. M. Lix is supported by a Tier I Canada Research Chair in Methods for Electronic Health Data Quality. T. O. Afifi is supported by a Tier I Canada Research Chair in Childhood Adversity and Resilience. S. H. Stewart’s is supported by a Tier 1 Canada Research Chair in Addictions and Mental Health. Facultyye
Efficient Sample Size Calculator
No full textThis software is shared under a MIT License:
Copyright 2025
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.Natural grouping behavior of hosts can reduce sample size requirements to estimate disease prevalence at a population scale. The Efficient Sample Size Calculator allows users to consider grouping tendencies of the host species to compute sample sizes needed to have 95% probability that disease prevalence in the population is at or below 1% or 2%. Allowable sampling schemes include simple random sampling, high-harvest sampling and two-stage cluster sampling. Examples cover a wide range of host species, diseases, and sampling schemes, and reveal that a well-designed sampling strategy may dramatically improve scientific efficiency over traditional sample size calculators without jeopardizing scientific rigor. Alternatively, an ill-designed sampling strategy may hamstring the ability for information from samples to reach the population scale. Novel statistical theory in Booth et al. (2024) and Booth et al. (2025).This publication was supported by an agreement with Cornell University, under Federal Award Number AP24WSNWRC00C030 from United States Department of Agriculture, Animal and Plant Health Inspection Service. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of Cornell University nor those of Sponsor
Sample size calculator for declaring a population free of infectious disease (Version 1)
No full textThis software is shared under a MIT license:
Copyright 2024
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.Scientists can leverage natural biological groupings of free-ranging wildlife to measure the prevalence of an infectious pathogen or disease. Specifically, correlation in disease status among individuals within natural groupings may be leveraged to conduct more efficient disease investigations. Unlike traditional sample size calculators, this calculator considers the natural grouping behavior of wild animals on the landscape and its effects on infectious disease transmission. Side-by-side output plots show potential sample savings afforded when correlation is considered relative to the same population where correlation is ignored. The statistical theory is depicted in Booth et al. (2023). This software contains only simple random sampling (SRS) although Booth et al. (2023) shows additional sampling schemes and remarks that scheme matters in sample size computations. We provide tutorials that show a variety of ways that this software can be used within a simple random sampling paradigm to plan real life wildlife health investigations. Tutorials include various diseases and pathogens in cervid species, mammals, herpetofauna, avians, and aquatic species. Later versions of this software will contain additional sampling schemes.The work was funded by the US Fish and Wildlife Service and the Association for Fish and Wildlife Agencies through Multistate Grant #F23AP00488-00.
This publication was supported by an agreement with Cornell University, under Federal Award Number AP24WSNWRC00C030 from United States Department of Agriculture, Animal and Plant Health Inspection Service. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of Cornell University nor those of Sponsor
Examination of psychological risk factors for chronic pain following cardiac surgery: protocol for a prospective observational study
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Examination of psychological risk factors for chronic pain following cardiac surgery: protocol for a prospective observational study
No full textINTRODUCTION:Approximately 400 000 Americans and 36 000 Canadians undergo cardiac surgery annually, and up to 56% will develop chronic postsurgical pain (CPSP). The primary aim of this study is to explore the association of pain-related beliefs and gender-based pain expectations on the development of CPSP. Secondary goals are to: (A) explore risk factors for poor functional status and patient-level cost of illness from a societal perspective up to 12 months following cardiac surgery; and (B) determine the impact of CPSP on quality-adjusted life years (QALYs) borne by cardiac surgery, in addition to the incremental cost for one additional QALY gained, among those who develop CPSP compared with those who do not. METHODS AND ANALYSES:In this prospective cohort study, 1250 adults undergoing cardiac surgery, including coronary artery bypass grafting and open-heart procedures, will be recruited over a 3-year period. Putative risk factors for CPSP will be captured prior to surgery, at postoperative day 3 (in hospital) and day 30 (at home). Outcome data will be collected via telephone interview at 6-month and 12-month follow-up. We will employ generalised estimating equations to model the primary (CPSP) and secondary outcomes (function and cost) while adjusting for prespecified model covariates. QALYs will be estimated by converting data from the Short Form-12 (version 2) to a utility score. ETHICS AND DISSEMINATION:This protocol has been approved by the responsible bodies at each of the hospital sites, and study enrolment began May 2015. We will disseminate our results through CardiacPain.Net, a web-based knowledge dissemination platform, presentation at international conferences and publications in scientific journals. TRIAL REGISTRATION NUMBER:NCT01842568
One-year outcomes after discharge from noncardiac surgery and association between pre-discharge complications and death after discharge: analysis of the VISION prospective cohort study.
No full textEffect of colchicine on perioperative atrial fibrillation and myocardial injury after non-cardiac surgery in patients undergoing major thoracic surgery (COP-AF): an international randomised trial
No full textBackground: Higher levels of inflammatory biomarkers are associated with an increased risk of perioperative atrial fibrillation and myocardial injury after non-cardiac surgery (MINS). Colchicine is an anti-inflammatory drug that might reduce the incidence of these complications. Methods: COP-AF was a randomised trial conducted at 45 sites in 11 countries. Patients aged 55 years or older and undergoing major non-cardiac thoracic surgery were randomly assigned (1:1) to receive oral colchicine 0·5 mg twice daily or matching placebo, starting within 4 h before surgery and continuing for 10 days. Randomisation was done with use of a computerised, web-based system, and was stratified by centre. Health-care providers, patients, data collectors, and adjudicators were masked to treatment assignment. The coprimary outcomes were clinically important perioperative atrial fibrillation and MINS during 14 days of follow-up. The main safety outcomes were a composite of sepsis or infection, and non-infectious diarrhoea. The intention-to-treat principle was used for all analyses. This trial is registered with ClinicalTrials.gov, NCT03310125. Findings: Between Feb 14, 2018, and June 27, 2023, we enrolled 3209 patients (mean age 68 years [SD 7], 1656 [51·6%] male). Clinically important atrial fibrillation occurred in 103 (6·4%) of 1608 patients assigned to colchicine, and 120 (7·5%) of 1601 patients assigned to placebo (hazard ratio [HR] 0·85, 95% CI 0·65 to 1·10; absolute risk reduction [ARR] 1·1%, 95% CI –0·7 to 2·8; p=0·22). MINS occurred in 295 (18·3%) patients assigned to colchicine and 325 (20·3%) patients assigned to placebo (HR 0·89, 0·76 to 1·05; ARR 2·0%, –0·8 to 4·7; p=0·16). The composite outcome of sepsis or infection occurred in 103 (6·4%) patients in the colchicine group and 83 (5·2%) patients in the placebo group (HR 1·24, 0·93–1·66). Non-infectious diarrhoea was more common in the colchicine group (134 [8·3%] events) than the placebo group (38 [2·4%]; HR 3·64, 2·54–5·22). Interpretation: In patients undergoing major non-cardiac thoracic surgery, administration of colchicine did not significantly reduce the incidence of clinically important atrial fibrillation or MINS but increased the risk of mostly benign non-infectious diarrhoea. Funding: Canadian Institutes of Health Research, Accelerating Clinical Trials Consortium, Innovation Fund of the Alternative Funding Plan for the Academic Health Sciences Centres of Ontario, Population Health Research Institute, Hamilton Health Sciences, Division of Cardiology at McMaster University, Canada; Hanela Foundation, Switzerland; and General Research Fund, Research Grants Council, Hong Kong
