Effect on smoking quit rate of telling smokers their health risk appraisal in terms of health age: a randomized control trial

Differentiated thyroid cancer: effect on quality of life, depression, and anxiety

CONTEXT

Thyroid cancer is the most common endocrine cancer, the lifelong risk for which is approximately 1%. Despite favorable prognosis and well-tolerated treatment modalities, numerous studies have shown that thyroid cancer survivors have impaired health-related quality of life (HRQoL). Patients are also more frequently affected by depression and anxiety.

OBJECTIVE

We aimed to evaluate HRQoL, depression, and anxiety status in female patients with DTC.

DESIGN, SUBJECTS, AND METHODS

We compared HRQoL, depression, and anxiety status in 114 female thyroid cancer survivors with 110 healthy subjects via a cross-sectional design. For this purpose, we utilized short-form 36 (SF-36), Beck Depression Inventory (BDI), and Beck Anxiety Inventory (BAI).

RESULTS

The majority of the patients (82%) were stage I. Fifty-seven patients (51%) received radioiodine treatment. Regarding HRQoL, depression, and anxiety between groups, thyroid cancer survivors did worse on every aspect of SF-36 than the control group (p < 0.05). Thyroid cancer survivors had higher BDI and BAI scores (p < 0.05). In those receiving RAI, the dose of RAI, lymph node dissection, and tumor stage did not affect SF-36, depression, and anxiety scores. Duration since diagnosis also did not affect results.

CONCLUSION

Our study further confirms the observation that survivors of DTC have impaired HRQoL. Furthermore, they are more likely to suffer from anxiety and depression.

How effective are 'age' tools at changing patient behaviour? A rapid review

BACKGROUND

A common form of risk communication is to relay the relative risk (%) of an adverse outcome based on surrogate markers associated with the outcome. A novel way of communicating risk is through 'effective age' of a person or specific organ. These tools can be used to change patient behaviour.

OBJECTIVE

To determine the effect of 'effective age' tools on patient behaviour as compared with more traditional methods of risk communication.

STUDY SELECTION

We performed a search of the PubMed database up to February 2019 for systematic reviews and randomised controlled trials (RCT) that answered our question. Interventions were 'effective age' tools, comparators were usual care or alternative risk communication tools. Primary outcomes were behavioural change measures.

FINDINGS

We included 1 overview of systematic reviews (level 1 evidence), 2 systematic reviews (level 1 evidence) and 13 RCTs (level 2 evidence). Both systematic reviews concluded the evidence base was not conclusive enough to make specific recommendations.Age tools assessed in the 13 RCTs were: 'lung age' (n=5), 'heart age' (n=3), 'health age' (n=2), 'cardiovascular age' (n=1), 'body age' (n=1) and 'net present value' (n=1). 7/13 (54%) RCTs demonstrated a clinical effect on behaviour change favouring the 'age' tool; 2/13 (15%) demonstrated a null effect; 4/13 (31%) favoured control.

CONCLUSIONS

Our findings indicate that systematic review evidence needs updating. The evidence from RCTs on the effect of using age metrics on patient behaviour is poor. There is a need for high-quality trials to decrease uncertainty in the available evidence.

Biomedical risk assessment as an aid for smoking cessation

BACKGROUND

A possible strategy for increasing smoking cessation rates could be to provide smokers with feedback on the current or potential future biomedical effects of smoking using, for example, measurement of exhaled carbon monoxide (CO), lung function, or genetic susceptibility to lung cancer or other diseases.

OBJECTIVES

The main objective was to determine the efficacy of providing smokers with feedback on their exhaled CO measurement, spirometry results, atherosclerotic plaque imaging, and genetic susceptibility to smoking-related diseases in helping them to quit smoking.

SEARCH METHODS

For the most recent update, we searched the Cochrane Tobacco Addiction Group Specialized Register in March 2018 and ClinicalTrials.gov and the WHO ICTRP in September 2018 for studies added since the last update in 2012.

SELECTION CRITERIA

Inclusion criteria for the review were: a randomised controlled trial design; participants being current smokers; interventions based on a biomedical test to increase smoking cessation rates; control groups receiving all other components of intervention; and an outcome of smoking cessation rate at least six months after the start of the intervention.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures expected by Cochrane. We expressed results as a risk ratio (RR) for smoking cessation with 95% confidence intervals (CI). Where appropriate, we pooled studies using a Mantel-Haenszel random-effects method.

MAIN RESULTS

We included 20 trials using a variety of biomedical tests interventions; one trial included two interventions, for a total of 21 interventions. We included a total of 9262 participants, all of whom were adult smokers. All studies included both men and women adult smokers at different stages of change and motivation for smoking cessation. We judged all but three studies to be at high or unclear risk of bias in at least one domain. We pooled trials in three categories according to the type of biofeedback provided: feedback on risk exposure (five studies); feedback on smoking-related disease risk (five studies); and feedback on smoking-related harm (11 studies). There was no evidence of increased cessation rates from feedback on risk exposure, consisting mainly of feedback on CO measurement, in five pooled trials (RR 1.00, 95% CI 0.83 to 1.21; I² = 0%; n = 2368). Feedback on smoking-related disease risk, including four studies testing feedback on genetic markers for cancer risk and one study with feedback on genetic markers for risk of Crohn's disease, did not show a benefit in smoking cessation (RR 0.80, 95% CI 0.63 to 1.01; I² = 0%; n = 2064). Feedback on smoking-related harm, including nine studies testing spirometry with or without feedback on lung age and two studies on feedback on carotid ultrasound, also did not show a benefit (RR 1.26, 95% CI 0.99 to 1.61; I² = 34%; n = 3314). Only one study directly compared multiple forms of measurement with a single form of measurement, and did not detect a significant difference in effect between measurement of CO plus genetic susceptibility to lung cancer and measurement of CO only (RR 0.82, 95% CI 0.43 to 1.56; n = 189).

AUTHORS' CONCLUSIONS

There is little evidence about the effects of biomedical risk assessment as an aid for smoking cessation. The most promising results relate to spirometry and carotid ultrasound, where moderate-certainty evidence, limited by imprecision and risk of bias, did not detect a statistically significant benefit, but confidence intervals very narrowly missed one, and the point estimate favoured the intervention. A sensitivity analysis removing those studies at high risk of bias did detect a benefit. Moderate-certainty evidence limited by risk of bias did not detect an effect of feedback on smoking exposure by CO monitoring. Low-certainty evidence, limited by risk of bias and imprecision, did not detect a benefit from feedback on smoking-related risk by genetic marker testing. There is insufficient evidence with which to evaluate the hypothesis that multiple types of assessment are more effective than single forms of assessment.

Intention to Quit Smoking among Intermediate and Secondary School Students in Saudi Arabia

BACKGROUND

Smoking is one of the most preventable causes of disease and death, including cancer, and quitting at an early age can reduce smoking-related morbidity and mortality. This study aimed to estimate the prevalence and to identify factors affecting the "intention to quit" among intermediate and secondary school current cigarette smoker students in Al Madinah city, Saudi Arabia.

MATERIALS AND METHODS

This study cohort included 307 current smoker students in a school-based survey. The intention to quit and its related determinants were assessed using a self-administered questionnaire.

RESULTS

More than half of the participants were ≥17 years, and of male gender (54.7%, 77.9% respectively). An intention to quit smoking was reported in 71.7% of participants, and was been significantly associated with: male gender (OR=3.25, 95% CI=1.65-6.41): age at 1st trial of smoking. 10-15 years (OR=2.11, 95% CI=1.03-4.32) along with age of ≥15 years (OR=3.10, 95% CI=1.20-7.88); days of smoking in the past 30 days (days<10 (OR=2.31, 95% CI=1.23-4.35) along with days ranging from 10-19 days (OR= 3.42, 95% CI=1.18-9.91); knowing that smoking is hazardous to health (OR=3.04, 95% CI=1.42-6.47); and finally, supporting smoking bans in public places (OR=1.89, 95% CI=1.11-3.25).

CONCLUSIONS

A substantial number of participants were willing to quit smoking. Effective interventions focusing on providing information about the hazards of smoking and prohibiting smoking in public places could help initiate the intention to quit among youth smokers.

Factors Affecting Korean Registered Nurses' Intention to Implement Smoking Cessation Intervention

Objectives

Nurses have been identified as an instrumental partner in tobacco reduction. This study aimed to examine factors affecting Korean nurses' intention to implement smoking cessation intervention in Busan, Korea.

Methods

The participants were a total of 215 Korean registered nurses. A self-administered questionnaire evaluated predisposing factors, motivational factors (attitude, social influence, and self-efficacy) and intention to implement smoking cessation intervention. Data were analyzed by t tests, Pearson's correlation, and hierarchical multiple regression.

Results

The mean age of the participants was 28.12 ± 5.72 years. The majority of the participants were staff nurses (85.6%), and 64.2% of the sample had < 5 years of work experience. Significant predictors of intention to implement smoking cessation intervention included perceived barrier of smoking cessation intervention (β = −0.128, p = 0.023), willingness to receive smoking cessation training (β = 0.123, p = 0.034), more positive attitude (β = 0.203, p = 0.002), higher social influence (β = 0.292, p < 0.001), and higher self-efficacy toward smoking cessation intervention (β = 0.151, p = 0.021), which explained 45% of the total variance of intention to implement smoking cessation intervention.

Conclusion

Attitude, social influence, and self-efficacy towards smoking cessation intervention had a significant positive influence in determining the intention to implement smoking cessation intervention. These findings can be used to develop evidence-based smoking cessation training programs for nurses in Korea. The programs should aim for positive attitude, higher social influence, and higher self-efficacy in hospital settings.

Self-rated Subjective Health Status Is Strongly Associated with Sociodemographic Factors, Lifestyle, Nutrient Intakes, and Biochemical Indices, but Not Smoking Status: KNHANES 2007-2012

Despite advertised health warnings regarding the deadly hazards of smoking, many people have not heeded recommendations to quit smoking. We examined factors that affect self-rated subjective health status (SRH) scores among lifestyle, nutrient intake and biochemical parameters, and the association of SRH scores and smoking status in a large Korean adult population. Adjusted odd ratios for SRH were calculated for smoking status, selected biochemical data, and food and nutrient intake obtained using the 24-hr recall method after covariate adjustment in the 2007-2012 Korean National Health and Nutrition Examination Survey (27,534 men and women aged ≥ 20 yr). Age, sex, income, education, drinking, exercise and stress levels were associated with SRH scores, regardless of smoking status (P < 0.001). Interestingly, people in any smoking status groups considered the well-known indicators for metabolic diseases (HDL cholesterol, glucose, aspartate aminotransferase, and alanine aminotransferase in the circulation), and the intake of fiber, total vitamins A, and vitamin C as indicators of SRH. Especially in current smokers, higher intake of nutritious food groups such as grains (OR = 1.227), vegetables (OR = 1.944), and milk (OR = 2.26) significantly increased the adjusted odds ratio of SRH. However, smoking status was not associated with SRH scores. In conclusion, SRH is affected by the indices related to health but not smoking status in Korean adults. The development of a new indicator of the direct adverse effects of smoking at regular health check-ups might be required to modulate the SRH in smokers and a nutritional education should not include the possible attenuation of adverse effects of smoking by good nutrition.

The effect of motivational lung age feedback on short-term quit rates in smokers seeking intensive group treatment: A randomized controlled pilot study

BACKGROUND

A brief "Lung Age" feedback intervention has shown promise for personalizing the health impact of smoking and promoting cessation in unselected smokers. Now that many healthcare organizations provide face-to-face cessation services, it is reasonable to ask whether such motivational feedback of lung function tests might improve treatment compliance and cessation rates in smokers wanting to quit. This study assessed effects of baseline motivational spirometry-based "Lung Age" feedback on treatment compliance and tobacco abstinence at 28-day follow-up.

METHODS

This randomized controlled pilot study took place in Penn State University-affiliated outpatient medical practices. Participants were 225 adult smokers (≥5 cigarettes/day) willing to attend tobacco dependence treatment. At assessment lung function (FEV-1) and exhaled carbon-monoxide (CO) were assessed. The Intervention group (n=120) were randomly allocated to receive motivational "Lung Age" feedback estimated by FEV-1 and on exhaled CO; Control group (n=105) received minimal feedback. Participants were offered 6 weekly group smoking cessation sessions and nicotine patches and followed-up 28 days after target quit date. The primary outcome measure was self-reported 7-day tobacco abstinence, confirmed by CO<10ppm at 28-day follow-up.

RESULTS

Quit rates were similar at follow-up (Intervention 50.8%; Control 52.4%; p=0.65) after controlling for abstinence predictors. Group attendance and patch use were similar. Among those attending follow-up (n=164, 73%), a greater proportion of the Intervention group had improved lung function (67% vs. 46%; p=0.0083).

CONCLUSIONS

Baseline Lung Age feedback did not improve quit rates or compliance at 28-day follow-up in smokers seeking intensive treatment.

Process evaluation of the first computer tailored program for smoking cessation among Romanian smokers

The objective of this paper is to present the implementation and process evaluation of the first computer tailored program for smoking cessation among Romanian smokers. The program targeted adult smokers who declared the intention to quit smoking in the next six months. The intervention consisted of a letter tailored to several respondent characteristics: gender, cognitive variables (attitude, social influence, and self-efficacy), intention to quit smoking, goal and relapse prevention strategies (action and coping plans), and smoking behaviour. The first 80 participants entered into the program filled in a process evaluation questionnaire one month after the intervention. The results of our study confirmed that the participants had read and remembered the letter. Moreover, new for Romania, this approach was positively appreciated by the participant and the score received for the tailored letter was high. The opinions of the participants confirmed that the tailored letter provided information that was useful, trustworthy and relevant for the individual. At the same time, the participants appreciated the polite, easy to understand content of the letter. These data underlined the premises for continuing the program and for using the information and communication technologies for healthy lifestyle promotion among Romanian population.