Lei Hum Wee

Stop smoking clinics in Malaysia: characteristics of attendees and predictors of success

INTRODUCTION As Stop Smoking Clinics (SSCs) become more common across the globe, it is important to know how far one can make broad generalisations concerning characteristics of smokers who attend these clinics and factors that predict their success. This involves accumulation of data from different countries. OBJECTIVE The aim of this study was to identify characteristics of smokers and factors leading up to quitting with clinics in Malaysia. METHOD Records from 629 smokers who had sought help from five selected SSCs in Malaysia from January 2006 to June 2007 were analysed. RESULTS The characteristics of smokers attending Malaysian smoking clinics were broadly similar to those in Western countries. Consistent with the findings from other countries, older age and longest duration of previous quit attempts were associated with successful smoking cessation. Greater baseline carbon-monoxide readings (OR 0.96, 95% CI 0.93-0.99; p=0.013), but not Fagerstrom Test for Nicotine Dependence (FTND), predicted failure to quit at six-month in multivariate analysis. Success rates varied greatly between clinics even after adjusting for all other predictors. CONCLUSION In these rare data from a non-Western culture some predictors of successful smoking cessation appeared to generalise from Western smokers but the universal validity of the FTND in particular needs to be examined further.

Predictors of 3-Month Abstinence in Smokers Attending Stop-Smoking Clinics in Malaysia

INTRODUCTION Much is known about the predictors of success in quitting smoking. In particular, nicotine dependence, but not strength of motivation to stop, appears to predict abstinence. However, to date, studies have come almost exclusively from Western countries. More data are needed on the cross-cultural generalizability of these findings. METHODS One hundred and ninety-eight smokers attending 5 stop-smoking clinics in Malaysia completed a questionnaire prior to their target quit date and were followed up 3 months after this date. Predictors included sociodemographic variables, smoking patterns, past history of quitting, characteristics of current quit attempt, and smoking motives as well as nicotine dependence (Fagerström Test for Nicotine Dependence [FTND]) and self-rated strength of motivation of stop. RESULTS At 3-month follow-up, 35.4% (95% CI: 28.7-42.0) of participants reported being abstinent. A backward elimination multiple logistic regression identified a number of significant predictors of success, including strength of motivation to stop (adjusted odds ratio [OR]: 3.05, 95% CI: 1.28-7.25). FTND did not predict success. CONCLUSIONS Motivation and nicotine dependence may play different roles in explaining variation in ability to stop smoking in different cultures.

Course and predictors of post‐traumatic stress disorder in a cohort of psychologically distressed patients with cancer: A 4‐year follow‐up study

Scant evidence exists on the long‐term course of cancer‐related post‐traumatic stress disorder (PTSD). This is among the few studies worldwide, and the first in the South‐East Asian region, to prospectively evaluate PTSD in patients with cancer using gold‐standard clinical interviews. The objective of the study was to assess the course and predictors of PTSD in adult patients with cancer in a South‐East Asian population.

Reply to Do 1 in 5 cancer patients develop post-traumatic stress disorder?: Correspondence

We recently read a BBC News article in the United Kingdom claiming that “a fifth of cancer patients experience PTSD [post-traumatic stress disorder], a Malaysian study has found.” On reviewing the full study, “Course and Predictors of Post-Traumatic Stress Disorder in a Cohort of Psychologically Distressed Patients With Cancer: A 4-Year Follow-Up Study” by Chan et al, we are concerned about the way in which the results are represented in the study and, subsequently, in the article. The study covered 469 eligible patients who had completed the Hospital and Anxiety Depression Scale at the baseline and at 4 to 6 weeks. For anyone scoring higher than 8 on either the anxiety or depression subscale or higher than 16 overall on this questionnaire, a full Structured Clinical Interview for DSM-IV Axis I Disorders (SCID) was performed by a clinical psychologist. After dropouts, 204 patients were grouped into categories according to the results of the SCID (no PTSD, subsyndromal PTSD, or full PTSD) in addition to 236 patients with nonprobable PTSD who did not undergo the SCID. In the Results section, it states that “at the 6-month follow-up, 27 of 203 patients (13.3%) met the full criteria for PTSD, and another 17 patients (8.4%) had subsyndromal PTSD symptoms. This yielded a 21.7% PTSD incidence when patients with both full and subsyndromal PTSD were aggregated.” However, because there were 439 patients, of whom 236 had nonprobable PTSD, we calculated an incidence of 6.2% for full PTSD (27 of 439 patients) and an incidence of 3.87% for subsyndromal PTSD (17 of 439). The study’s Discussion section states that “approximately 1 in 5 patients (21.7%) with cancer at the 6-month follow-up had PTSD”; this is significantly higher than prevalence estimates. However, we do not believe that this is correct. This 1-in-5 figure was derived only from the patients who had an elevated Hospital and Anxiety Depression Scale score. With the whole population, the value drops to 6.1% (or 10% if subsyndromal PTSD is included). We are concerned that this idea of 1 in 5 patients with cancer having PTSD is misleading and has been published within mainstream media across the world, including BBC News, the Huffington Post, and Times Now, and it has the potential to cause alarm in cancer sufferers and their relatives. We look forward to receiving a response from the authors.

Reply to Course and predictors of posttraumatic stress disorder in a cohort of psychologically distressed patients with cancer: A 4-year follow-up study-methodological and statistical issues: Correspondence

I read the article by Chan et al that was published in January 2018 with great interest. The study was conducted to examine the course and predictors of posttraumatic stress disorder (PTSD) in adult patients with cancer in a SouthEast Asian population. Although the valuable longitudinal study has been conducted by the authors, some important statistical issues need to be noted. The authors applied repeated-measures analysis of variance as a classic statistical test to assess the effect of psychological distress (measured at baseline and at 4-6 weeks, 1 year, and 4 years) on PTSD (measured at the 6month and 4-year follow-ups). They then applied 2 binary logistic regression models to their study’s data to determine the predictors of PTSD, which is problematic and does not consider the correlated structure of the exposure and outcome variables and may lead to biased results. To address the aforementioned limitation, parametric Gformula and G-estimation were suggested by Mansournia et al in 2017 to address the correlated structure of outcome and exposure variables simultaneously. In addition, the authors used only a crude logistic regression model to determine the predictors of PTSD in their study, but I wonder why the multivariable model was not constructed and no confounder was controlled. The parametric G-formula and G-estimation not only address the correlated structure of the exposure and outcome variables, but also can adjust the resulting effect size estimates for fixed or time-varying confounders. I believe the take-home message from the study by Chan et al is that the longitudinal data need to be analyzed through advanced statistical methods to address the correlated structure of the outcome and exposure variables, adjusting for fixed or time-varying confounding variables.

Rationalizations and identity conflict following smoking relapse: a thematic analysis

Abstract Introduction: Little is known about how smokers respond cognitively and emotionally to the experience of “late” relapse after the acute withdrawal phase. This study assessed the kinds of thoughts and feelings that emerge in order to provide a basis for quantitative research assessing prevalence of different types of response and implications for future quit attempts. Methods: Face-to-face in-depth interviews were conducted among 14 people attending a quit smoking clinic in Malaysia who had relapsed after at least 6 weeks of abstinence. Transcripts were analyzed using thematic analysis to enable emergence of important aspects of the experience. Results: Following relapse, smokers often engaged in rationalizations and activities to minimize worry about the harmful effects of smoking by switching to a lower-tar cigarette, reducing the number of cigarette smoked, attempting to reduce cigarette smoke inhalation, comparing themselves with other smokers, and minimizing the health risks associated with smoking. In some cases, smokers retained a “non-smoker” identity despite having relapsed. Conclusion: Smoking relapsers rationalize their failure to quit and minimize their health risk in order to protect their image as non-smokers while it remains a source of identity conflict.