Tag: Smoking

A Summary of the E-cigarettes Summit 2016

Posted on by rebeccalawn

by Jasmine Khouja @jasmine_khouja

On the 17th November I attended the E-cigarette Summit 2016 at the Royal Society in London. The summit brought together researchers, policy-makers, smoking cessation services and industry members to hear about the latest research, developments and challenges in the e-cigarette domain.

The summit was a one-day event packed full of information with 20 fast-paced (10-20 minutes) talks and 4 panel discussions. My five take home points from the summit were:

  1. Communication

One point which was raised on multiple occasions was that good communication of the research into e-cigarettes is key to the public understanding the risks and benefits of e-cigarette use. Unfortunately, the consensus was that the communication of e-cigarette research to the public is poor. Astonishingly, one speaker commented that someone had asked their daughter: “Is your dad still selling e-cigarettes and killing people?” This demonstrates how badly e-cigarettes have been portrayed, despite general consensus that they are much less harmful than cigarettes. Researchers are trying to communicate their research but face hurdles; some journals may be less likely to publish articles that are positive about vaping, meaning that it is harder to publish evidence that vaping is not as bad for you as cigarettes. The media are also hampering researchers’ efforts as they prefer stories which are anti-vaping and sometimes draw inaccurate conclusions from the evidence, which makes for more interesting stories. However, effective communication of the research is possible: Professor Peter Hajek and Dr Alex Freeman provided some useful advice to researchers which included not inferring human risks from animal studies, ensuring risks are directly compared to those of smoking, being a trustworthy source by being competent, honest and reliable, and providing neutral information without recommendations allowing the public to make their own informed decisions.

  1. The British Medical Association’s Guidelines

Communication of the benefits and risks of e-cigarettes isn’t limited to publications and the media; doctors are being asked about e-cigarettes by patients. Despite the evidence that the research community has provided that e-cigarettes are less harmful than cigarettes, the British Medical Association are yet to update their guidelines to encourage smokers to switch to e-cigarettes. There seemed to be apprehension stemming from the lack of known long-term effects, despite the fact that we know there are vastly fewer and reduced amounts of toxicants in e-cigarettes compared to cigarettes meaning the likelihood of long-term effects as bad as or worse than smoking are extremely unlikely.

  1. Recent Research

Many new studies were presented but the study that really caught my attention was discussed by Dr Lynne Dawkins. Lynne provided evidence for increased puffing behavior when participants are given lower doses of nicotine in their e-cigarettes [1]. She concluded that inhaling more vapour to receive the same amount of nicotine exposes vapers to unnecessary amounts of toxicants. This is very topical as the regulations set out by the Tobacco Products Directive (TPD) which will be fully implemented by May 2017 limit doses to 20 mg/mL meaning that some higher dosage (36 mg/mL) users may expose themselves to extra toxicants to receive the levels of nicotine they need when the higher dosage product become unavailable in the next six months.

  1. The Tobacco Products Directive

The TPD provides some form of regulation for e-cigarette manufacturers and distributors. The inclusion of e-cigarettes in the TPD was controversial due to e-cigarettes not containing tobacco and the restrictive nature of the regulations which were seen as unnecessary by some users and industry members. Part of the regulations included the thorough testing of e-cigarette products to ensure they were safe and the publication of the contents (including toxicants) so that the public could make informed decisions. To my dismay, I was informed that the information submitted by the e-cigarette companies so far will not be made publically accessible for roughly six months due to a system error. I was also informed that compliance with the regulations was low and that age of sale restrictions in particular did not seem to be being enforced. The system and enforcement of the TPD in relation to e-cigarettes needs improving so that consumers can access the information which the TPD states they should have access to and to protect young people whose brain development may be adversely affected by consuming nicotine.

  1. New Systems

As restrictive as the TPD is, new products are still being developed. A new type of e-cigarette is emerging onto the market called pods. These devices are small and similar in size to older less effective designs of e-cigarettes (cigalikes) but have the power and nicotine delivery of the newer more effective tank systems. The sleek, compact designs combined with the improved nicotine delivery systems which prevent overheating (which is associated with harmful byproducts such as formaldehyde) are likely to be very popular. These systems can also record information on how the devices are used (how long individuals puff for and how many puffs they take etc.) which could provide essential information to researchers on how e-cigarettes are used in real life situations.

The day culminated in a key note speech by the Attorney General for Iowa, Tom Miller. He commended the UK’s focus on e-cigarette research and the general positive stance our public health officials have taken in terms of e-cigarettes. He concluded his speech by asking for help from the UK to bring the US up to the same standards.

References

  1. PMID: 27650300

Institutional smoking bans reduce secondhand smoke exposure and harms, but more research is needed

Posted on by rebeccalawn
by Olivia Maynard @OliviaMaynard17
This blog originally appeared on the Mental Elf site on 12th July 2016.

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It’s been almost 9 years since the introduction of SmokeFree legislation in the UK (although we elves still return from a night out smelling of campfire smoke). However, secondhand smoke is still accountable for 600,000 deaths annually.

Smoke free policies can be implemented at the micro-level (i.e. the individual level or in homes), the meso-level (i.e. in organisations, such as public healthcare facilities, higher education centres and prisons) or the macro-level (i.e. in an entire country). In many countries, smokefree legislation is at the macro-level, although exemptions exist at the meso-level. For example, in the UK, specific rooms in prisons and care homes are exempt from this legislation.

In their Cochrane review, Frazer and colleagues review the evidence for meso-level smoking bans (in venues not typically included in smokefree legislation) on 1) passive smoke exposure, 2) other health-related outcomes and 3) active smoking, including tobacco consumption and smoking prevalence.

Worldwide, secondhand smoke is still accountable for 600,000 deaths annually.

Worldwide, secondhand smoke is still accountable for 600,000 deaths annually.

Methods

Identification of included studies

The authors searched online databases of clinical trials, reference lists of identified studies and contacted authors to identify ongoing studies. Studies were included if they:

The introduction of smoking bans in psychiatric hospitals and prisons is extremely controversial.

The introduction of smoking bans in psychiatric hospitals and prisons is extremely controversial.

Results

Characteristics of included studies

No randomised controlled trials (RCTs) were found. 17 observational studies were identified (three using a controlled before-and-after design with another site for comparison and 14 using an uncontrolled before-and-after design). Of these 17 studies:

  • 12 were based in hospitals;
  • 3 in prisons;
  • 2 in universities.

Five studies investigated the impact of smoking bans on two participant groups (i.e. staff and either patients or prisoners).

The 17 studies were conducted in 8 countries: the USA (6 studies), Spain (3 studies), Switzerland (3 studies), Australia, Canada, Croatia, Ireland and Japan (all 1 study). Eight of these were conducted in US states or countries with macro-level (i.e. national) smoke-free legislation, eight with no legislative bans and one which compared all 50 US states (some with national bans and others without).

Main findings

There was considerable heterogeneity between the 17 studies and so a meta-analysis of all studies was not conducted. Instead studies were analysed using aqualitative narrative synthesis according to each of the outcome measures:

Reducing secondhand smoke exposure

Four studies assessed secondhand smoke exposure, finding that a reduction in exposure was observed in all three settings after smoking bans. However, none of the studies in the review used a biochemically validated measure of smoke exposure such as cotinine or carbon monoxide levels.

Other health outcomes

Four studies examined the impact of partial or complete smoking bans on health outcomes including smoking-related mortality. Two were conducted in prisons, one in a hospital and one in a secure mental hospital (Etter et al, 2007). All of these studies observed improvements in smoking-related morbidity and mortality after smoking bans. One of these assessed the impact of smoking bans in prisons in all 50 US states and found that smoking-related mortality was reduced in those prisons that had a smoking ban for more than 9 years.

Tobacco consumption and smoking prevalence

Thirteen studies reported data on the effect of smoking bans on smoking prevalence and five of these reported data on two populations within settings (i.e. prisoners and prison staff).

Eleven of these studies were included in a meta-analysis (using the Mantel-Haenszel fixed-effect method) and the data from the 12,485 participants in these studies was pooled. Although there was considerable heterogeneity between these studies (I2 = 72%; where a higher I2 value is evidence of higher levels of heterogeneity), this heterogeneity was lower within subgroups (e.g. in prisoners or hospital staff).

Ten studies conducted in hospital settings found mixed evidence for the impact of smoking bans on smoking prevalence. Eight of these studies were included in the meta-analysis and there was evidence that smoking bans reduced active smoking rates among hospital staff (risk ratio (RR) 0.71, 95% confidence interval (CI) 0.64 to 0.78, n = 4,544, I2 = 76%) and patients (RR 0.84, CI 0.76 to 0.98, n = 1442, I2 = 20%).

The one study in a prison setting found no evidence of a change in smoking prevalence among staff or prisoners after a smoking ban (RR 0.99, CI 0.84 to 1.16, n = 130).

Two studies in university settings observed reductions in smoking prevalence after smoking bans (RR 0.72, CI 0.64 to 0.80, n = 6,369, I2 = 59%), although one study only observed this among male ‘frequent’ smokers.

Quality of the evidence

The evidence was judged to be of low quality as all of the studies wereobservational (none used a RCT design) and the risk of bias was rated as high.

Banning smoking in hospitals and universities increased the number of smoking quit attempts and reduced the number of people smoking.

Banning smoking in hospitals and universities increased the number of smoking quit attempts and reduced the number of people smoking.

Conclusion

Overall, this review finds evidence of smoking bans on:

  • reducing smoking prevalence in hospitals and universities, with the greatest reductions among hospital staff;
  • reduced mortality and exposure to secondhand smoke in hospitals, universities and prisons.

Limitations

The quality of the evidence was low and the authors conclude that ‘we therefore need more robust studies assessing evidence for smoking bans and policies in these important specialist settings’. Limitations with the studies included in the review include: small sample sizes in some studies, a lack of a control location for comparison in all but three studies and a high level of heterogeneity between and within the different settings (e.g. the hospital settings included a cancer hospital, psychiatric hospitals and general hospitals).

We need more robust studies assessing the evidence for smoking bans and policies in specialist settings.

We need more robust studies assessing the evidence for smoking bans and policies in specialist settings.

Discussion

The authors report that given this evidence, smoking bans at the meso-level should be considered as part of multifactorial tobacco control activities to reduce secondhand smoke exposure and smoking prevalence.

Given that the introduction of these bans particularly in psychiatric hospitals and prisons is controversial, the introduction of these bans should be sensitive to the needs of populations. For example, bans in psychiatric hospitals should be implemented in consultation with psychiatrists to ensure that the improved health outcomes of patients is considered first and foremost. As the evidence is currently weak, with a high risk of bias, any interventions should be closely monitored.

More robust studies are needed, using a control group for comparison, assessing smoke exposure using biochemically validated measures, using long-term follow-ups of at least 6 months and reporting smoking prevalence both before and after the introduction of the ban.

It is not possible to draw firm conclusions about institutional smoking bans from the current evidence.

It is not possible to draw firm conclusions about institutional smoking bans from the current evidence.

Links

Primary paper

Frazer K, McHugh J, Callinan JE, Kelleher C. (2016) Impact of institutional smoking bans on reducing harms and secondhand smoke exposure. Cochrane Database of Systematic Reviews 2016, Issue 5. Art. No.: CD011856. DOI: 10.1002/14651858.CD011856.pub2.

Other references

Etter M, Etter JF. (2007) Acceptability and impact of a partial smoking ban in a psychiatric hospital.. Preventive Medicine 2007;44(1):64–9. [PubMed abstract]

Photo credits

Rates of restarting smoking after giving birth

Posted on by rebeccalawn

by Olivia Maynard @OliviaMaynard17

This blog originally appeared on the Mental Elf site on 25th April 2016.

Although many women spontaneously quit smoking when they find out they’re pregnant, approximately 11% of women in the UK continue to smoke during their pregnancy. The health implications of this are estimated to amount to an annual economic burden of approximately £23.5 million.

The NHS Stop Smoking Service provides support for pregnant women to quit smoking during their pregnancy at an annual cost of over £5 million (or £235 per successful quitter). However, despite successful smoking abstinence during pregnancy using this service, many women restart smoking after giving birth (i.e. postpartum), increasing their risk of smoking related diseases and their offspring’s risk of passive smoking and becoming smokers themselves.

Jones and colleagues conducted a systematic review and meta-analysis to investigate just how high the rates of restarting smoking postpartum are among those women who have received support to quit smoking during their pregnancy.

The NHS Stop Smoking Service costs over £5 million every year, but 11% of women in the UK continue to smoke during their pregnancy.

The NHS Stop Smoking Service costs over £5 million every year, but 11% of women in the UK continue to smoke during their pregnancy.

Methods 

Selection of included studies

Studies were included if:

  • Participants were pregnant smokers who were motivated to quit smoking (to ensure that participants were similar to those women who actively seek out Stop Smoking Services during their pregnancy)
  • Interventions aimed to encourage smoking cessation during pregnancy, with control group participants receiving placebo, another cessation intervention or no intervention
  • Outcome measures were continuous abstinence from the end of pregnancy to at least one postpartum follow-up, or 7-day point prevalence abstinence (i.e. not smoking for the past 7 days) at both the end of pregnancy and at least one postpartum follow-up. Where biochemically validated abstinence was not available, self-reported abstinence was accepted. 

Primary outcome measure

  • Longitudinally collected continuous abstinence data, among those women who reported abstinence at the end of their pregnancy and were in the intervention condition (i.e. had received Stop Smoking Service support).

Secondary outcome measure

  • The overall rates of smoking prevalence (using point-prevalence data) following childbirth across all women.

Results

Study characteristics

27 studies were included in the review. Of these:

  • 4 reported continuous abstinence only (i.e. can be used for the primary outcome measure only);
  • 7 reported both continuous abstinence and point-prevalence (i.e. can be used for both the primary and secondary outcome measures);
  • 16 reported point-prevalence only (i.e. can be used for the secondary outcome measure only);

20 studies were randomised controlled trials (RCTs) with individual randomisation, 5 were cluster randomised and 2 were quasi-randomised.

To minimise differences between the included studies, only data from similar time-points were synthesised. Postpartum follow-up time-points were as follows:

  • 6 weeks (including data from 10 days and 4, 6 and 8 weeks postpartum);
  • 3 months (data from 3 and 4 months);
  • 6 months (data from 6 and 8 months);
  • 12 months;
  • 18 months;
  • 24 months.

Risk of bias assessment  

  • Studies were screened and data extracted by two reviewers;
  • The quality of included studies was generally judged to be poor;
  • Only 8 (of 27) studies included an intention to treat analysis;
  • Only 18 studies used biochemically validated abstinence;
  • There was evidence of publication bias.

Primary analysis: proportion re-starting smoking

The primary analysis only included those 11 studies reporting continuous abstinence, including a total of 571 women who reported being abstinent at the end of their pregnancy.

By 6 months postpartum, 43% (95% CI = 16 to 72%, I2 = 96.7%) of these women had restarted smoking.

The subgroup analysis of those studies using biochemically validated abstinence measures included only 6 studies and found that by 6 months 74% of women (95% CI = 64 to 82%) had restarted smoking.

Secondary analysis: proportion smoking

The secondary analysis only included those 23 studies reporting point-prevalence abstinence, including a total of 9,262 women.

At the end of pregnancy, 87% (95% CI = 84 to 90%, I2 = 93.2%) of women were smoking and at 6 months this was 94% (95% CI = 92 to 96%, I2 = 88.0%).

The 17 studies using biochemically validated abstinence observed rates of smoking at the end of pregnancy of 89% (95% CI = 86 to 91%, I2 = 91.2%) and 96% at 6 months postpartum (95% CI = 92 to 99%, I2 = 70.7%).

Using these cross-sectional point-prevalence data, it is also possible to estimate the proportion of women restarting smoking postpartum. These data suggest that 13% of women were abstinent at the end of their pregnancy, but only 6% were abstinent at 6 months, which is equivalent to 54% restarting smoking postpartum.

In clinical trials of smoking cessation interventions during pregnancy, only 13% of female smokers are abstinent at term.

In clinical trials of smoking cessation interventions during pregnancy, only 13% of female smokers are abstinent at term.

Conclusion

The authors conclude that:

Most pregnant smokers do not achieve abstinence from smoking while they are pregnant, and among those that do, most will re-start smoking within 6 months of childbirth.

They also note that this means that the considerable expenditure by NHS Stop Smoking Services to help pregnant women quit smoking is not having as big an impact on improving the health of women and their offspring as it might.

Limitations  

  • There was considerable variability between the included studies (i.e. the I2 statistic was high). The authors attempted to minimise this variability by aggregating data at similar time-points and only including those studies where women consented to join (i.e. were motivated to quit smoking)
  • Only a few studies reported longitudinal continuous abstinence data, restricting the amount of data which could be included in the primary analysis.

Discussion  

This is the first study to systematically investigate the rate of restarting smoking postpartum and provide data on the effectiveness of the Stop Smoking Services provided to pregnant women.

Using continuous postpartum abstinence rates, 43% of women who had received a smoking cessation intervention and were abstinent at the end of their pregnancy had restarted smoking after 6 months. Using data from the cross-sectional point-prevalence data, a similar rate of restarting was observed.

These results are generalisable to those pregnant women who seek support from Stop Smoking Services. Although no reviews have investigated the rates of restarting smoking among those women who spontaneously quit smoking during their pregnancy, individual studies suggest that the rates are broadly similar at between 46 and 76%.

Nearly half (43%) of the women who do stop smoking during their pregnancy, re-start smoking within 6 months of childbirth.

Nearly half (43%) of the women who do stop smoking during their pregnancy, re-start smoking within 6 months of childbirth.

Links

Primary paper

Jones M, Lewis S, Parrott S, Wormall S, Coleman T. (2016) Re-starting smoking in the postpartum period after receiving a smoking cessation intervention: a systematic review. Addiction, doi: 10.1111/add.13309.

Photo credits

– See more at: http://www.nationalelfservice.net/populations-and-settings/pregnancy/rates-of-restarting-smoking-after-giving-birth/#sthash.iSRFc5w5.dpuf

Smoking and chronic mental illness: what’s the best way to quit or cut down?

Posted on by meryemgrabski

by Meg Fluharty @MegEliz_

This blog originally appeared on the Mental Elf site on 11th December 2015.

Smoking rates in the US and UK are 2-4 times higher in people with mental illnesses compared to those without (Lasser at al., 2000; Lawerence et al., 2009).

What’s more, smokers suffering from mental illness have higher nicotine dependence and lower quit rates (Smith et al.,2014; Weinberger et al., 2012; Cook et al 2014).

About half of deaths in people with chronic mental illness are due to tobacco related conditions (Callaghan et al., 2014; Kelly et al 2011).

A new ‘state of the art’ review in the BMJ by Tidey and Miller (2015) is therefore much needed, focusing as it does on the treatments currently available for smoking and chronic mental illness, such as schizophrenia, unipolar depression, bipolar depression, anxiety disorders and post-traumatic stress disorder (PTSD).

42% of all cigarettes smoked in England are consumed by people with mental health problems.

42% of all cigarettes smoked in England are consumed by people with mental health problems.

Methods

Tidey and Miller (2015) identified studies by searching keywords in PubMed and Science Direct, using relevant guidelines, reviews and meta-analyses, and data from the authors’ own files. Two authors reviewed the references and relevant studies were chosen and summarised. Only peer-reviewed articles published in English were reviewed.

It’s important to stress that this was not a systematic review, so the included studies were not graded, but simply summarised with a particular focus on outcomes.

BMJ State of the Art reviews are not systematic reviews, so are susceptible to the same biases as other literature reviews or expert opinion pieces.  

BMJ State of the Art reviews are not systematic reviews, so are susceptible to the same biases as other literature reviews or expert opinion pieces.

Results

Schizophrenia

Nicotine replacement therapy (NRT) plus psychosocial

Overall, in studies of NRT with psychosocial treatment (such as CBT) 13% of smokers with schizophrenia averaged 6 to 12 month quit rates. Additionally, those continuing to receive NRT had reduced relapse rates.

Bupropion

Studies investigating bupropion in smokers with schizophrenia found initial abstinence, but were followed by high relapse rates with treatment discontinuation, suggesting the need for longer treatment duration. One study found bupropion coupled with NRT and CBT reduced relapse rates. 

Varenicline

Studies investigating varenicline in smokers with schizophrenia achieved abstinence at the end of the trial (compared to placebo), but not at 12-month follow up. One study found varenicline and CBT had higher abstinence rates at 52 weeks (compared to controls). Psychiatric side effects reported did not differ between groups, suggesting varenicline is well tolerated in schizophrenia.

Psychosocial

Studies investigating psychosocial treatments in smokers with schizophrenia were varied. Studies implementing CBT displayed high continuous abstinence, and those receiving motivational interviewing were more likely to seek treatment. However, in contingency management trials (receiving monetary reward for abstinence) it appeared individuals might only be staying abstinent long enough for their reward, therefore longer trials are needed.

E-cigarettes

One (uncontrolled) study provided e-cigarettes for 52 weeks to smokers with schizophrenia, finding half reduced their smoking by 50% and 14% quit. None of the participants were seeking treatment for cessation at the start of the trial, suggesting a need for further RCTs of e-cigarettes in smokers with schizophrenia.

The Mental Elf looks forward to reporting on RCTs of e-cigarettes in smokers with schizophrenia.

The Mental Elf looks forward to reporting on RCTs of e-cigarettes in smokers with schizophrenia.

Unipolar depression

A review of the cessation treatments available to smokers with unipolar depression found little differences in outcomes between individuals with and without depression. However, women with depression were associated with poorer outcomes. Previous studies indicate bupropion, nortriptyline, and NTR with mood management all effective in smokers with depression. Additionally, a long-term study of varenicline displayed continuous abstinence up to 52 weeks without any additional psychiatric side effects.

Bipolar depression

Few studies investigated cessation treatments in smokers with bipolar depression; two small-scale studies of bupropion and varenicline indicated positive results. However a long-term varenicline study found increased abstinence rates at the end of the trial, but not at 6 month follow-up. Some individuals taking varenicline reported suicidal ideation, but this did not differ from the control group.

Anxiety disorders

An analysis investigating both monotherapy and combination psychotherapies found anxiety disorders to predict poor outcomes at follow-up. Despite combination psychotherapy doubling the likelihood of abstinence in non-anxious smokers, neither monotherapy or combination therapy were more effective than placebo in smokers with a lifetime anxiety disorder. However, unipolar and bipolar only touched on pharmaceutical treatments.

PTSD (Post Traumatic Stress Disorder)

Studies investigating cessation in PTSD sufferers found higher abstinence rates in integrative care treatment, in which cessation treatment is integrated into pre-existing mental healthcare where therapeutic relationships and a set schedule already exist. A pilot study investigating integrative care with bupropion found increased abstinence at 6 months. However, a contingency management trial found no differences between controls, although it’s possible this was due to small numbers.

Standard treatments to help people quit smoking are safe and effective for those of us with mental illness.

Standard treatments to help people quit smoking are safe and effective for those of us with mental illness.

Discussion

Clinical practice should prioritise cessation treatments for individuals suffering mental illnesses, in order to protect against the high rates of tobacco related death and disease in this population.

This review shows that smokers with mental illness are able to make successful quit attempts using standard cessation approaches, with little adverse effects.

Several studies suggested bupropion and varenicline effective in schizophrenia, and varenicline in unipolar and bipolar depression. However, it should be noted, these studies only investigated long-term depression, not situational depression.

Furthermore, all the participants in the studies reviewed were in stable condition, therefore it’s possible outcomes may be different when patients are not as stable. Individuals whom are not stable will have additional psychiatric challenges, may less likely to stick with their treatment regime, and may be more sensitive to relapse.

It should be noted that this was a ‘state of the art’ review, rather than a systematic review or meta-analysis. Therefore- as all literary reviews-it’s subject to bias and limitations, with possible exclusion of evidence, inclusion of unreliable evidence, or not being as comprehensive as if this were a meta analysed. For example, some of the author’s own files are used along side the literary search, but (presumably unpublished) data from other researchers are not sought out or included. Many of the studies included differed in design (some placebo controlled, some compared against a different active treatment ect.) therefore caution should be taken when drawing comparisons across studies.

Additionally, some sections appeared to be much more thorough than others. For example, schizophrenia is covered extensively, including NTR, psychosocial, and pharmaceutical approaches. While all anxiety disorders appeared to be gaped together as one (as opposed to looking at social anxiety, GAD, or panic disorder) and were not explored in detail, drawing little possible treatment conclusions. Finally, this was great literary review, which provided much information, but at times it did feel a bit overwhelming to read and difficult to identify the key information from each sections.

Service users who smoke are being increasingly marginalised, so practical evidence-based information to support quit attempts at the right time is urgently needed.

Service users who smoke are being increasingly marginalised, so practical evidence-based information to support quit attempts at the right time is urgently needed.

Links

Primary paper

Tidey JW and Miller ME. Smoking cessation and reduction in people with chronic mental illness. BMJ 2015;351:h4065

Other references

Lasser K, Boyd JW, Woolhandler S, et al. Smoking and mental illness: a population-based prevalence study.JAMA 2000;284:2606-10 [PubMed abstract]

Lawrence D, Mitrou F, Zubrick SR. Smoking and mental illness: results from population surveys in Australia and the United States. BMC Public Health 2009;9:285

Smith PH, Mazure CM, McKee SA. Smoking and mental illness in the US population. Tob Control 2014;23:e147-53.[Abstract]

Weinberger AH, Pilver CE, Desai RA, et al. The relationship of major depressive disorder and gender to changes in smoking for current and former smokers: longitudinal evaluation in the US population. Addiction 2012;107:1847-56. [PubMed abstract]

Cook BL, Wayne GF, Kafali EN, et al. Trends in smoking among adults with mental illness and association between mental health treatment and smoking cessation. JAMA 2014;311:172-82 [PubMed abstract]

Callaghan RC, Veldhuizen S, Jeysingh T, et al. Patterns of tobacco-related mortality among individuals diagnosed with schizophrenia, bipolar disorder, or depression. J Psychiatr Res 2014;48:102-10 [PubMed abstract]

Kelly DL, McMahon RP, Wehring HJ, et al. Cigarette smoking and mortality risk in people with schizophrenia. Schizophr Bull 2011;37:832-8 [Abstract]

Photo credits

– See more at: http://www.nationalelfservice.net/mental-health/substance-misuse/smoking-and-chronic-mental-illness-whats-the-best-way-to-quit-or-cut-down/#sthash.NvTaK7E6.dpuf

SMS texting to quit smoking: a meta-analysis of text messaging interventions for smoking cessation

Posted on by meryemgrabski

by Olivia Maynard @OliviaMaynard17

This blog originally appeared on the Mental Elf site on 26th August 2015.

The efficacy of different smoking cessation interventions is always a hot topic around our woodland campfire. We’ve blogged previously about the effectiveness of both pharmacological and psychological treatments for smoking cessation, as well as their effectiveness among different populations of smokers.

A recent systematic review and meta-analysis investigated the efficacy of SMS text message interventions for smoking cessation. Unlike the majority of other smoking cessation interventions, using mobile phones to deliver health information allows for direct interaction between clients and practitioners without face-to-face interaction and permits the collection of large amounts of data. It is therefore cost-effective and easily scalable to large populations.

Previous meta-analyses have looked at the effectiveness of text messaging interventions for smoking cessation, but the review recently published by Spohr and colleagues is the first to investigate which elements or moderators of text message interventions are the most effective in supporting smoking cessation.

This review

Methods

The authors searched for randomised controlled trials which investigated the efficacy of text messaging interventions for smoking cessation. Only studies which included a follow-up measure of smoking abstinence were included. 13 articles met all of these inclusion criteria.

The authors also extracted information on the use of each of the moderators described below:

  • Intervention type:
    • SMS only;
    • ‘SMS plus’ (where SMS support is combined with either face-to-face or web-based support).
  • Message frequency:
    • Fixed message schedule (a consistent number of messages throughout the intervention);
    • Decreasing schedule (most messages at quit attempts, followed by a gradual reduction);
    • Dynamic schedule (depends on the stage of cessation the client is at).
  • Message track:
    • Fixed message track (users cannot influence the course of the intervention);
    • Dynamic message track (user quit status and stage of change can influence intervention messages).
  • Message tailoring:
    • Tailored messages (customised message content to a specific individual);
    • Targeted messages (customised messages to a population subgroup).
  • On-demand messaging:
    • On-demand messaging (allow users to text a keyword in emergency situations to receive additional support. Some interventions allow users to connect with other users for support and encouragement).
  • Message direction:
    • Unidirectional messaging (by the researcher);
    • Bidirectional messaging (to obtain data from the client).
  • Message interaction:
    • Researcher-initiated (containing intervention messages and assessment questions);
    • User-initiated (containing requests for additional support).

Intervention success was assessed using seven-day point prevalence as the primary outcome measure, as 11/13 of the studies reported these results. Two other studies only reported 6 month continuous abstinence.

The researchers used an intention to treat analysis.

Perhaps surprisingly (given the ubiquitous nature of smartphones) the reviewers only found 13 trials to include in their analysis.

Results

The 13 articles resulted in a cumulative sample size of n = 13,626. Participants were primarily adult smokers (six studies), but four studies recruited participants aged 15 or over and three targeted adolescents and young adults (ages 16-25).

Smoking quit rates for the text messaging intervention groups were 35% higher as compared to control groups (OR = 1.35, 95% CI = 1.23 to 1.49).

Overall, the analysis of the intervention moderators did not find strong evidence that any particular moderator was more effective than any other:

  • Intervention type:
    • There were no differences (QB = 0.56, df = 1, p = 0.46) in intervention efficacy between those which provided text-only support (k = 6) as compared with text messaging plus additional support (k = 7).
    • However, text-only interventions had a slightly larger effect size than those with text messaging plus additional support.
    • There were no differences (QB = 0.89, df = 1, p = 0.35) in intervention efficacy between those which promoted the use of nicotine replacement therapy (NRT) (k = 7) as compared with those which did not (k = 6).
  • Message frequency:
    • There were no differences (QB = 0.96, df = 2, p = 0.62) in intervention efficacy between those which provided decreasing schedule (k = 8) as compared with fixed schedule (k = 3) or variable schedule (k = 2) support.
    • However, those which had a fixed schedule had larger effect sizes than either of the other types of schedules.
  • Message track:
    • There were no differences (QB = 0.38, df = 1, p = 0.54) in intervention efficacy between those which used a fixed message track (k = 5) as compared with a dynamic message track (k = 8).
  • Message tailoring:
    • There were no differences (QB = 1.54, df = 2 p = 0.46) in intervention efficacy between those which used message tailoring (k = 8) as compared message targeting (k = 1) or a combination of both (k = 4).
    • All studies included some form of message content tailoring.
  • On-demand messaging:
    • There were no differences (QB = 0.15, df = 1, p = 0.70) in intervention efficacy between those which used on-demand messaging (k = 11) as compared with those which did not (k = 2).
    • There were no differences (QB = 0.02, df = 1, p = 0.88) in intervention efficacy between those which provided peer-to-peer support (k = 5) as compared with those which did not (k = 8).
  • Message direction:
    • All of the studies used bidirectional messaging so the effectiveness of this moderator to unidirectional messaging could not be assessed.
  • Message interaction:
    • There were no differences (QB = 0.17, df = 1, p = 0.68) in intervention efficacy between those which included assessment messages (k = 7) as compared with those which did not (k = 6).

Text messaging does not compare well to many other more effective methods of smoking cessation.

Conclusions

This meta-analysis found that smoking cessation interventions which used text-messaging increased the odds of successfully quitting smoking by 35%.

To put this in perspective, other reviews have found that telephone quit lines increase smoking cessation success by 60%, social support increases success by 30% and practical counselling by 50%. NRT and other medications have been shown to increase cessation success by between 50% and 310% (Fiore et al., 2000).

None of the moderators investigated here were found to be more effective than any other. There was some evidence that interventions which used fixed schedules were more effective than those which used either decreasing or variable schedules. Similarly, there was some evidence that text-only support programs were more effective than those which provided a ‘text-plus’ service. However, there was no robust statistical evidence for these differences.

Overall, these results provide no evidence that text-messaging interventions, which are more complex and time-demanding (i.e. text-plus, on-demand messaging, variable schedules, social support communication), are any more effective than the simplest interventions.

However, given the cost-effectiveness, relative ease of delivery and promise of efficacy of these interventions, future research should continue to determine what moderators make an effective text-based intervention.

Limitations and future directions

These results should be treated with caution however, for a number of reasons:

  • The authors relied on data obtained from the original articles to compile this meta-analysis, rather than contacting the researchers themselves. As data regarding the actual use by users of some of the moderators such as social support and on-demand messaging was not reported in articles, we cannot be certain whether the failure of these moderators to increase quit success is because they are simply not more effective, or because users didn’t actually use these services.
  • The number of studies included in this meta-analysis was small (only 13 studies). This is even more the case for the moderator analyses. Drawing firm conclusions from the statistical evidence is therefore difficult.

shutterstock_117926893

Links

Primary paper

Spohr SA, Nandy R, Gandhiraj D, Vemulapalli A, Anne S, Walters ST. (2015) Efficacy of SMS Text Message Interventions for Smoking Cessation: A Meta-Analysis. Journal of Substance Abuse Treatment, 56, 1-10. doi: http://dx.doi.org/10.1016/j.jsat.2015.01.011

Other references

Fiore MC, Bailey WC, Cohen SJ, Dorfman SF, Goldstein MG, Gritz ER, … Lando HA. (2000) Treating tobacco use and dependence: a clinical practice guideline: Publications Clearinghouse.

– See more at: http://www.nationalelfservice.net/mental-health/substance-misuse/sms-texting-to-quit-smoking-a-meta-analysis-of-text-messaging-interventions-for-smoking-cessation/#sthash.hjMwMixu.dpuf

Does tobacco cause psychosis?

Posted on by meryemgrabski

by Marcus Munafo @MarcusMunafo

This blog originally appeared on the Mental Elf site on 30th July 2015.

Hot on the heels of a recent study suggesting a dose-response relationship between tobacco smoking and subsequent risk of psychosis, a systematic review and meta-analysis (including the data from that prospective study) has now been published, again suggesting that we should be considering the possibility that smoking is a causal risk factor for schizophrenia.

As I outlined in my earlier post, smoking and psychotic illness (e.g., schizophrenia) are highly comorbid, and smoking accounts for much of the reduced life expectancy of people with a diagnosis of schizophrenia. For the most part, it has been assumed that smoking is a form of self-medication, to either alleviate symptoms or help with the side effects of antipsychotic medication.

It's widely thought that people with psychosis or schizophrenia use smoking as a way to self-medicate and relieve their symptoms.

Methods

This new study reports the results of a systematic review and meta-analysis of prospective, case-control and cross-sectional studies. The authors hoped to test four hypotheses:

  1. That an excess of tobacco use is already present in people presenting with their first episode of psychosis
  1. That daily tobacco use is associated with an increased risk of subsequent psychotic disorder
  1. That daily tobacco use is associated with an earlier age at onset of psychotic illness
  1. That an earlier age at initiation of smoking is associated with an increased risk of psychotic disorder

The authors followed MOOSE and PRISMA guidelines for the conduct and reporting of systematic reviews and meta-analyses, and searched Embase, Medline and PsycINFO for relevant studies. They included studies that used ICD or DSM criteria for psychotic disorders (including schizophrenia, schizophreniform disorder, schizoaffective disorder, delusional disorder, non-affective psychotic disorder, atypical psychosis, psychotic depression, and bipolar mania with psychotic features).

To test the first hypothesis, studies with a control group were used to calculate an odds ratio. To test the second, prospective studies in which rates of smoking were reported for patients who developed psychotic disorders compared to controls were included, so risk ratios could be calculated. To test the third and fourth, prospective and case-control studies were included, and for the onset of psychosis, cross-sectional studies were also included.

Effect size estimates (weighted mean difference for continuous data, and odds ratios for cross-sectional data or relative risks for prospective data) were combined in a random-effects meta-analysis.

Results

A total of 61 studies comprising 72 independent samples were analysed. The overall sample included 14,555 tobacco users and 273,162 non-users.

  1. The overall prevalence of smoking in people presenting with their first episode of psychosis was higher than controls (12 case-control samples, odds ratio 3.22, 95% CI 1.63 to 6.33, P = 0.001). This supports hypothesis 1.
  2. Compared with non-smokers, the incidence of new psychotic disorders was higher overall (6 longitudinal prospective samples, risk ratio 2.18, 95% CI 1.23 to 3.85, P = 0.007). This supports hypothesis 2.
  3. Daily smokers developed psychotic illness at an earlier age compared with non-smokers (26 samples, weighted mean difference -1.04 years, 95% CI -1.82 to -0.26, P = 0.009). This supports hypothesis 3.
  4. Age at initiation of smoking cigarettes did not differ between patients with psychosis and controls (15 samples, weighted mean difference -0.44 years, 95% CI 1-.21 to 0.34, P = 0.270). This does not support hypothesis 4.

Daily tobacco use is associated with an increased risk of psychosis and an earlier age at onset of psychotic illness.

Conclusion

The authors conclude that the results of their systematic review and meta-analysis show that daily tobacco use is associated with an increased risk of psychotic disorder and an earlier age at onset of psychotic illness, although the magnitude of the association is relatively small.

Interestingly, the authors interpret their results in the context of the Bradford Hill criteria for inferring causality (which consider the strength, consistency, specificity, temporality, biological gradient, plausibility, coherence, experiment, and analogy of an association). They argue that, where these criteria can be applied (the specificity criterion cannot be applied because smoking affects so many disease processes, while the experiment criterion is not met because animal models of psychotic illness that capture important features such as delusions are impossible), they do appear to be met by the evidence available.

Limitations

There are a number of important limitations to this study, which the authors themselves acknowledge:

  • The first is that all analyses relied on observational data, which makes strong causal inference impossible. Longitudinal prospective studies help somewhat in this respect, but only a small number were available for inclusion in the analysis of risk of developing psychosis between smokers and non-smokers. Moreover, even these studies cannot exclude the possibility that symptoms present before a first full episode of psychosis may have led to smoking initiation (i.e., self medication).
  • Another important limitation is that very few studies measured or adjusted for use of other substances (most importantly, perhaps, cannabis, which has been widely discussed as a potential risk factor for schizophrenia). This is a potentially very important source of bias.

Nevertheless, this is a well-conducted systematic review and meta-analysis that brings together a reasonably large literature. The results appear robust, although given the observational nature of the data, and the fact that only data that were comparable across studies could be meta-analysed, any conclusions regarding causality need to be very tentative.

Very few studies in this review, measured or adjusted for use of other substances such as cannabis.

Summary

It seems that we should seriously consider the possibility that smoking is a causal risk factor for schizophrenia. Of course, the data available to date aren’t definitive, and we need to be very cautious about inferring causality from observational data, but this does feel like an area where there is growing, converging evidence from multiple studies using multiple methods.

It’s also worth bearing in mind that even if smoking is a causal risk factor, this does not preclude the possibility that smoking is also used as a form of self-medication. There are several thousand constituents of tobacco smoke; it is possible that some of these alleviate symptoms, while others exacerbate them. For this reason, we shouldn’t assume that nicotine is necessarily the culprit if smoking is indeed a causal risk factor; it may be (and Gurillo and colleagues discuss the biological plausibility of nicotine in this context), but that will need to be tested.

This last point is particularly important in the content of ongoing debate regarding the potential harms and benefits of electronic cigarettes. If smoking does turn out to be a causal risk factor for schizophrenia, then whether nicotine or something else in tobacco smoke is identified as the culprit will have an important bearing on this debate, and attitudes towards these products.

There are several thousands constituents of tobacco smoke; it is possible that some of these alleviate symptoms, while others exacerbate them

Links

Primary paper

Gurillo P, Jauhar S, Murray RM, MacCabe J. (2015) Does tobacco use cause psychosis? Systematic review and meta-analysis. Lancet Psychiatry 2015. doi: 10.1016/S2215-0366(15)00152-2 (Open access paper: features audio interview with authors)

Munafo M. Smoking and risk of schizophrenia: new study finds a dose-response relationship. The Mental Elf, 1 Jul 2015.

– See more at: http://www.nationalelfservice.net/mental-health/psychosis/does-tobacco-use-cause-psychosis/#sthash.sxUwJPIF.dpuf

Smoking and risk of schizophrenia: new study finds a dose-response relationship

Posted on by meryemgrabski

by Marcus Munafo @MarcusMunafo

This blog originally appeared on the Mental Elf site on 1st July 2015.

Almost exactly a year ago, a landmark study identified 108 genetic loci associated with schizophrenia (Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014). In a Mental Elf post on that study I wrote: “Genetic studies also don’t rule out an important role for the environment – [genome-wide association studies] might even help identify other causes of disease, by identifying loci associated with, for example, tobacco use.”

I mentioned this because one of the loci identified is strongly associated with heaviness of smoking. There are two possible explanations for this: either this locus influences both smoking and schizophrenia, or smoking causes schizophrenia.

Smoking and schizophrenia are highly co-morbid; the prevalence of smoking among people with a diagnosis of schizophrenia is much higher than in the general population. It is widely believed that this is because smoking helps to alleviate some of the symptoms of schizophrenia, or the side-effects of antipsychotic medication.

The possibility that smoking itself may be a risk factor for schizophrenia has generally not been widely considered. Now, however, intriguing evidence has emerged that it may be, from a large study of data from Swedish birth and conscript registries (Kendler et al, 2015).

The leading causes of premature mortality in people with schizophrenia are ischaemic heart disease and cancer, both heavily related to smoking.

Methods

The authors linked nationwide Swedish registers via the unique 10-digit identification number assigned at birth or immigration to all Swedish residents. Data on smoking habits were collected from the Swedish Birth Register (for women) and the Military Conscription Register (for men). The date of onset of illness was defined as the first hospital discharge diagnosis for schizophrenia or non-affective psychosis.

Cox proportional hazard regressions were used to investigate the associations between smoking and time to schizophrenia diagnosis. To evaluate the possibility that smoking began during a prodromal period (where symptoms of schizophrenia may emerge prior to a full diagnosis), buffer periods of 1, 3 and 5 years were included in the models. In the female sample, data from relatives (siblings and cousins) were also used to control for familial confounding (genetic and environmental).

Results

Smoking status information was available for 1,413,849 women, and 233,879 men.

There was an association between smoking at baseline and a subsequent diagnosis of schizophrenia for:

  • Women
    • Light smoking: hazard ratio 2.21, (95% CI 1.90 to 2.56)
    • Heavy smoking: hazard ratio 3.45 (95% CI 2.95 to 4.03)
  • Men
    • Light smoking: hazard ratio 2.15 (95% CI 1.25 to 3.44)
    • Heavy smoking: hazard ratio 3.80 (95% CI 1.19 to 6.60)

Adjustment for socioeconomic status and prior drug abuse (i.e., confounding) weakened these associations slightly.

Taking into account the possibility of smoking onset during a prodromal period also did not weaken these associations substantially, irrespective of whether the buffer period (from smoking assessment to the date at which a first schizophrenia diagnosis would be counted) was 1-, 3- or 5-years. Theoretically, if prodromal symptoms of schizophrenia lead to smoking onset (i.e., reverse causality) the smoking-schizophrenia association should weaken with longer buffer periods.

Finally, the co-relative analyses compared the association between smoking and schizophrenia in the female sample, within pairs of relatives of increasing genetic relatedness who had been selected on the basis of discordance for smoking (i.e., one smoked and one did not). If the smoking-schizophrenia association arises from shared familiar risk factors (genetic or environmental) the association should weaken with increasing familial relatedness. Instead, only modest decreases were observed.

As a validation check on the accuracy of their measure of smoking behaviour, the authors confirmed that heavy smoking was more strongly associated with both lung cancer and chronic obstructive pulmonary disease, two diseases known to be caused by smoking.

These results show a dose-response relationship between smoking and risk of schizophrenia, i.e. the more you smoke, the stronger the association. 

Conclusion

This study provides clear evidence of a prospective association between cigarette smoking and a subsequent diagnosis of schizophrenia. However, observational associations are notoriously problematic, because these associations may arise because of confounding (measured and unmeasured), or reverse causality. Since these analyses were conducted on observational data, these limitations should be borne in mind and we cannot say with certainty that smoking is a causal risk factor for schizophrenia.

Nevertheless, the authors conducted a number of analyses to attempt to rule out different possibilities. First, the associations were weakened only slightly when adjusted for socioeconomic status and prior drug abuse, so the impact of measured confounders appears to be modest (although other confounding could still be occurring). Second, the inclusion of a buffer period to account for smoking onset during a prodromal period also weakened the associations only slightly, which is not consistent with a reverse causality interpretation. Finally, the co-relative analysis did not indicate that the association differed strongly across levels of familial relatedness, suggesting that the impact of unmeasured familial confounders (both genetic and environmental) is relatively modest.

This study provides clear evidence of a prospective association between cigarette smoking and a subsequent diagnosis of schizophrenia.

Limitations

There are some limitations to the study that are worth bearing in mind:

  1. First, there were no data on lifetime smoking, although the authors validated their measure of smoking against outcomes known to be caused by smoking.
  2. Second, the authors used clinical diagnoses, and included both schizophrenia and non-affective psychosis, so the specificity of the findings to these outcomes is uncertain.
  3. Third, because of the small number of schizophrenia diagnoses the co-relative analyses used non-affective psychosis only.

This study is not enough to say with certainty that smoking is a causal risk factor for schizophrenia.

Summary

There are three main ways in which the association between smoking and schizophrenia might arise:

  1. Schizophrenia causes smoking,
  2. Smoking causes schizophrenia, and
  3. The association arises from risk factors common to both.

This study suggests that the first mechanism cannot fully account for the association; if anything there was more support for the third mechanism, including stronger evidence for a role for familial factors than for socioeconomic status and drug abuse. However, critically, this study also finds support for the second mechanism, including a dose-response relationship between smoking and risk of schizophrenia.

Despite this study’s strengths, and the care taken by the authors to explore the three possible mechanisms that could account for the association between smoking and schizophrenia, no single study is definitive. However, evidence is emerging from other studies that support the possibility that smoking may be a causal risk factor for schizophrenia.

Recently, McGrath and colleagues have reported that earlier age of onset of smoking is prospectively associated with increased risk of non-affective psychosis (McGrath et al, 2015).

In addition, Wium-Andersen and colleagues report that tobacco smoking is causally associated with antipsychotic medication use (but not antidepressant use), in a Mendelian randomisation analysis that uses genetic variants as unconfounded proxies for heaviness of smoking (Wium-Andersen et al, 2015).

Identifying potentially modifiable causes of diseases such as schizophrenia is a crucial part of public health efforts. There is also often reluctance among health care professionals to encourage patients with mental health problems (including schizophrenia) to attempt to stop smoking. If smoking is shown to play a causal role in the development of schizophrenia, there may be more willingness to encourage cessation. Since the majority of the mortality associated with schizophrenia is due to tobacco use (Brown et al, 2000), helping people with schizophrenia to stop is vital to their long-term health.

There is now mounting evidence that supports the possibility that smoking may be a causal risk factor for schizophrenia.

Links

Primary paper

Kendler, K.S., Lonn, S.L., Sundquist, J & Sundquist, K. (2015). Smoking and schizophrenia in population cohorts of Swedish women and men: a prospective co-relative control study. American Journal of Psychiatry. doi: 10.1176/appi.ajp.2015.15010126 [Abstract]

Other references

Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014). Biological insights from 108 schizophrenia-associated genetic loci. Nature, 511, 421-427. doi: 10.1038/nature13595

McGrath, J.J., Alati, R., Clavarino, A., Williams, G.M., Bor, W., Najman, J.M., Connell, M. & Scott, J.G. (2015). Age at first tobacco use and risk of subsequent psychosis-related outcomes: a birth cohort study. Australian and New Zealand Journal of Psychiatry. [PubMed abstract]

Wium-Andersen, M.K., Orsted, D.D. & Nordestgaard, B.G. (2015). Tobacco smoking is causally associated with antipsychotic medication use and schizophrenia, but not with antidepressant medication use or depression. International Journal of Epidemiology, 44, 566-577. [Abstract]

Brown S, Inskip H, Barraclough B. (2000) Causes of the excess mortality of schizophrenia. Br J Psychiatry. 2000 Sep;177:212-7.

– See more at: http://www.nationalelfservice.net/mental-health/schizophrenia/smoking-and-risk-of-schizophrenia-new-study-finds-a-dose-response-relationship/#sthash.u3UiDOlG.dpuf

The effect of smoking-free psychiatric hospitals on smoking behaviour: more evidence needed

Posted on by meryemgrabski

By Olivia Maynard @OliviaMaynard17 

This blog originally appeared on the Mental Elf site on 18th May 2015.

One in three people with mental health illnesses in the UK smoke, as compared with one in five of the general population. In addition, smokers with mental illnesses smoke more heavily, are more dependent on nicotine and are less likely to be given help to quit smoking. As a result, they are more likely to suffer from smoking-related diseases, and on average die 12-15 years earlier than the general population.

Since July 2008, mental health facilities in England have had indoor smoking bans. However, NICE guidelines recommend that all NHS sites, including psychiatric hospitals become completely smoke-free, a recommendation previously examined by the Mental Elf.

This NICE recommendation has been criticised by those who argue that:

  1. Tobacco provides necessary self-medication for the mentally ill;
  2. Smoking cessation interferes with recovery from mental illness;
  3. Smoking cessation is the lowest priority for those with mental illnesses;
  4. People with mental illnesses are not interested in quitting;
  5. People with mental illness cannot quit smoking.

Many people argue that forcing people to quit smoking when they are having an acute mental health episode is tantamount to abuse.

Judith Prochaska, a researcher at Stanford University, has previously addressed each of these arguments (she calls them ‘myths’) (Prochaska, 2011). The abridged summary of the evidence surrounding myths 1, 2 and 3 is that:

  1. Smoking actually worsens mental health outcomes; in fact, the argument that nicotine provides self-medication is one which has been promoted by the tobacco industry itself;
  2. Smoking cessation does not exacerbate mental health outcomes;
  3. Smoking cessation should be a high priority, given that mental health patients are much more likely to die from tobacco-related disease than mental illness.

These are interesting and important arguments and more evidence surrounding them is also available here (Prochaska, 2010).

However, in this blog post I focus on ‘myths’ 4 and 5, drawing on a recent systematic review investigating the impact of a smoke-free psychiatric hospitalisation on patients’ motivations to quit (myth 4) and smoking behavior (myth 5) (Stockings et al., 2014).

This systematic review brings together mostly cross-sectional studies that look at the impact that smoke-free hospitals have on psychiatric inpatients who smoke.

Methods and results

Stockings and colleagues searched for studies examining changes in patients’ smoking-related behaviours, motivation and beliefs either during or following an admission to an adult inpatient psychiatric facility.

Study characteristics

Fourteen studies matched these inclusion criteria, two of which were conducted in the UK. The majority of the studies used a cross-sectional design and none were randomised controlled trials. The studies were all quite different, with the number of participants ranging from 15-467 and the length of admission ranging from 1-990 days. Crucially, the type of smoking ban varied considerably between the studies, so I’ll consider these separately.

Facilities with complete smoking bans

Six studies were conducted in facilities with complete bans. All of these offered nicotine dependence treatment, including nicotine replacement therapy (NRT) or brief advice.

  • Only one of these statistically assessed smoking behaviour, finding that cigarette consumption was lower during admission compared with prior to admission.
  • Three studies assessed smoking behaviour after discharge, finding that the majority of patients resumed smoking within five days. However, there was some evidence from the two larger studies that smoking prevalence was still lower at two weeks and three months post-discharge compared with prior to admission.
  • The one study to statistically assess smoking-related beliefs and motivations found that patients expected to be more successful at quitting following discharge compared with at admission. Higher doses of NRT were related to higher expectations of success.

Facilities with incomplete bans

Eight studies were conducted in facilities with incomplete bans. 

  • Four banned smoking indoors and all of these offered nicotine dependence treatment:
    • Only one of these statistically assessed smoking behaviour, finding that quit attempts increased from 2.2% when smoking was permitted in specific rooms, to 18.4% after the ban.
    • One study that assessed smoking prevalence post-discharge found that all participants (n = 15) resumed smoking.
    • One study found that participants expected to be more successful in smoking cessation post-discharge as compared with at admission.
  • Three allowed smoking in designated rooms, with no nicotine dependence treatment:
    • There were mixed results among the two studies which assessed smoking prevalence during admission.
    • Compared with at admission, there was some evidence of increased motivation to quit smoking.
  • One restricted smoking to five pre-determined intervals per day, with no nicotine dependence treatment:
    • Motivation to quit was lower at discharge compared with at admission.

This review suggests that complete bans are the most effective at encouraging smoking cessation and that NRT or brief advice are crucial.

Conclusions

The authors concluded that:

Smoke-free psychiatric hospitalisation may have the potential to impact positively on patients’ smoking behaviours and on smoking-related motivation and beliefs.

Strengths and limitations

The fourteen studies included in this review were all quite different from each other and had a number of limitations including:

  • Small sample sizes;
  • Incomplete reporting of key outcomes;
  • Failure to use controlled, experimental research designs;
  • Differences in the types of smoking bans in place;
  • Inconsistent provision of nicotine dependence treatment.

These key differences and limitations prevented statistical examination of the results as a whole. This means that making firm conclusions is difficult. There is clearly a need for more research in this area.

This area of research is far from complete, so we cannot make any firm conclusions about smoke-free psychiatric hospitals at this stage.

Summary

There is evidence that people with mental illnesses are interested in quitting smoking (myth 4) and that they are able to (myth 5). However, we still need more studies to examine these questions with well-powered (i.e. large sample sizes), high-quality (i.e., experimental) research designs.

The evidence presented in this systematic review suggests that complete bans are the most effective at encouraging smoking cessation and that the provision of nicotine dependence treatment, such as NRT or brief advice, is also crucial.

Although a handful of the studies assessed smoking behaviour after discharge, none of the facilities viewed this as an important outcome. Given the high level of smoking-related disease among those with mental health illnesses, ensuring that individuals remain abstinent from smoking after discharge is important for the continuing good health of these individuals.

Importantly, none of the studies in this review explored the impact of smoke-free legislation on mental health outcomes. Although the evidence suggests that smoking cessation actually improves mental health outcomes, future research should continue to examine this relationship.

Over to you

Do you have a mental health illness yourself, or support someone who does? Do you work with people with mental health illnesses? Should psychiatric hospitals become smoke-free?

We'd love to hear your views about this systematic review and more generally on this often emotive topic. Please use the comment box below to share your knowledge and experience.

Links

Primary paper

Stockings EA. et al (2014) The impact of a smoke-free psychiatric hospitalization on patient smoking outcomes: a systematic review. Aust NZ J Psychiatry 2014 May 12;48(7):617-633. [PubMed abstract]

Other references

Prochaska, J. J. (2010). Failure to treat tobacco use in mental health and addiction treatment settings: A form of harm reduction? Drug and Alcohol Dependence, 110(3), 177-182. doi: http://dx.doi.org/10.1016/j.drugalcdep.2010.03.002

Prochaska, J. J. (2011). Smoking and Mental Illness — Breaking the Link. New England Journal of Medicine, 365(3), 196-198. doi: doi:10.1056/NEJMp1105248

 

Promoting smoking cessation in people with schizophrenia

Posted on by meryemgrabski

by Meg Fluharty @MegEliz_

This blog originally appeared on the Mental Elf site on 14th May 2015.

shutterstock_276469196People with schizophrenia have a considerable reduction in life expectancy compared to the general population (Osborn et al 2007; Lawrence et al 2013). A number of factors lead to cardiovascular disease (Osborn et al 2007; Lawrence et al 2013; Nielsen et al, 2010) one of which is smoking.People with schizophrenia smoke at much higher rates and more heavily than the general population (Ruther et al 2014, Hartz et al 2014).Stubbs et al (2015) carried out a review to assess the current cessation interventions available for individuals with serious mental illnesses and establish if any disparities currently lie in the delivery of these interventions.60% of premature deaths in people with schizophrenia are due to medical conditions including heart and lung disease and infectious illness caused by modifiable risk factors such as smoking, alcohol consumption and intravenous drug use.

Methods

The authors searched several electronic databases (Embase, PubMed, and CINAHL) using the following keywords: “smoking cessation”, “smoking”, “mental illness”, “serious mental illness” and “schizophrenia.”

Studies were eligible if they included individuals with a DSM or ICD-10 diagnosis of schizophrenia and reported a cessation intervention.

The authors included both observational and intervention studies as well as systematic-reviews and meta-analyses.

This paper is a clinical overview (not a systematic review) of a wide range of different studies relevant to smoking cessation in schizophrenia and other severe mental illnesses.

Results

Pharmacological interventions

 Non-pharmacological interventions

  • The evidence for E-cigarettes was inconsistent, with the authors concluding more evidence was needed before clinicians consider e-cigarettes within mental health settings. Additionally, e-cigarette use in people with schizophrenia should have side effects monitored closely.
  • There was little research on exercise in schizophrenia, but one study found a reduction in tobacco consumption.

Behavioural approaches

  • Behavioural approaches such as offering smoking cessation advice alongside pharmacotherapy have been found successful with no harmful side effects.

Disparities in smoking cessation interventions

  • An investigation of GP practices found individuals with schizophrenia did not receive smoking cessation interventions proportional to their needs.

Support while quitting

  • People with serious mental illnesses experience more severe withdrawal symptoms compared to the general population, and therefore should be given extra support during cessation attempts (Ruther et al 2014).
  • Psychiatrists should re-evaluate choice and the dose of antipsychotic medicine being given after abstinence from smoking is achieved. This is because of nicotine’s metabolic influence on antipsychotic medicine.
  • Alongside smoking cessation, exercise should be promoted among people with schizophrenia to combat weight gain and the increased metabolic risk.

People with serious mental illness are likely to need more support when quitting smoking, because they generally suffer more severe withdrawal symptoms.

Discussion

In light of the findings, the authors suggest several steps for clinicians to help people with schizophrenia quit smoking:

  • Patients’ current smoking status, nicotine dependency, and previous quit attempts should be assessed. Assessing nicotine dependency will help predict the level of withdrawal symptoms the patient is likely to experience upon quitting.
  • Cessation attempts are best timed when the patient is stable. Patients should be thoroughly advised on the process needed to give them the best chance of quitting smoking, Thus, allowing the patient to formulate their quit plan and take ownership of their own quit attempt.
  • Cessation counselling should be provided, particularly what to expect with withdrawal symptoms (e.g. depression and restlessness) and how to cope.
  • Pharmacological support should be provided (Bupropion recommended) when there is even mild tobacco dependence.
  • Clinicians should carefully monitor patients’ medication and fluxions in weight for a minimum of 6 months after quitting smoking, and when needed recommended exercise to combat weight gain.

The authors provide a well laid out summary of their findings, alongside some excellent suggestions for clinicians to consider on how to best promote cessation in practice.

However, it should be stressed that Stubbs et al (2015) only searched for high qualities studies and provided an overview of them –  this is not a systematic review or meta-analysis. They included several types of studies, set little inclusion criteria and listed no exclusion criteria. This is quite different from a systematic review with a meta-analysis, which would set stricter predefined search and eligibility criteria, which identify a set of studies all tackling the same question, thus allowing for the statistical pooling and comparison of these studies.

This is not a systematic review, but it does offer some very useful practical advice for clinicians who are trying to promote smoking cessation.

Links

Primary paper

Stubbs B, Vancampfort D, Bobes J, De Hert M, Mitchell AJ. How can we promote smoking cessation in people with schizophrenia in practice? A clinical overview. Acta Psychiatrica Scandinavica. 2015: 1-9. 
[PubMed abstract]

Other references

Osborn DPJ, Levy G, Nazareth I, Petersen I, Islam A, King MB. Relative risk of cardiovascular and cancer mortality in people with severe mental illness from the United Kingdom’s General Practice Research Database. Arch Gen Psychiatry 2007;64:242–249.

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Motivational interviewing may help people quit smoking, but more research is needed

Posted on by meryemgrabski

by Olivia Maynard @OliviaMaynard17

This blog originally appeared on the Mental Elf site on 30th April 2015.

Both pharmacological (i.e. bupropion and varenicline) and non-pharmacological (i.e. brief advice from physicians) interventions have been shown to be effective in assisting people to stop smoking. Evidence also suggests that combining both these types of interventions can help people to stop smoking and both are considered equally important in quitting success.

Motivational interviewing (MI) is a counselling-based intervention which focusses on encouraging behaviour change by helping people to explore and resolve their uncertainties about changing their behaviour. MI avoids an aggressive or confrontational approach and aims to increase the self-belief of the individual. MI was initially developed to treat alcohol abuse, but may be helpful in encouraging smoking cessation.

In a recent Cochrane systematic review, Lindson-Hawley and colleagues from the Cochrane Tobacco Addiction Group aimed to determine whether or not MI is an effective method of smoking cessation (Lindson-Hawley et al, 2015).

Motivational interviewing focusses on encouraging behaviour change by helping people to explore and resolve their uncertainties about changing their behaviour.

Methods

The authors searched online databases and studies were included if:

  • Participants were tobacco users and were not pregnant or adolescents;
  • The intervention was based on MI techniques;
  • The control group received brief advice or usual care;
  • Some monitoring of the quality of the MI intervention was included;
  • Smoking abstinence was reported at least 6 months after the start of the programme.

The main outcome measure was smoking abstinence, using the most rigorous definition of abstinence for each study. Biochemically-validated measures of abstinence (i.e., carbon monoxide breath testing or saliva cotinine samples) were also used where available. Those participants lost to follow-up were considered to be continuing to smoke.

Results across studies were combined in a meta-analysis.

Results

Twenty eight studies published between 1997 and 2014 were found to match the strict inclusion criteria.

The total dataset included over 16,000 participants and studies varied in:

  • The length of the MI sessions (ranging from 10 to 60 minutes)
  • The number of sessions (one to six sessions)
  • Who the sessions were delivered by (primary care physicians, hospital clinicians, nurses or counsellors)

Some of the main findings included:

  • A modest (26%) increase in quitting among those receiving MI as compared with control (although the true value is likely to lie between 16-36%).
  • Sub-group analyses found that:
    • MI delivered by primary care physicians increased the likelihood of successful quitting by 349% (53-794%) as compared with control
    • When it was delivered by counsellors, quit rates increased by only 25% as compared with control
    • MI delivered by nurses was not found to be more effective than control
  • Shorter sessions (less than 20 minutes) increased the chances of quitting relative to control by 69%, as compared with longer sessions, which only increased the chances of quitting by 20%.
  • There was little difference in the likelihood of quitting between single MI sessions (26%) and multiple sessions (20%) as compared with control.
  • There was little difference between MI delivered face-to-face as compared with via the telephone only.
  • There was no evidence for a difference for MI delivered to smokers who were motivated to quit as compared with those with low levels of motivation.

Compared with brief advice or usual care, motivational interviewing yielded a significant increase in quitting. However, study quality means that these results should be interpreted with caution.

Strengths

This review adds 14 additional studies to a previous review conducted in 2010. The addition of these new studies altered the results of the original review very little, providing strong support for the validity of these findings.

Two previous systematic reviews have also examined the effectiveness of MI for smoking cessation, observing modest positive effects of MI (Heckman et al., 2010, Hettema and Hendricks, 2010), although these studies used a broader inclusion criteria than used here and therefore may have underestimated the effects of MI.

The majority of studies included in this review adequately reported their design and methods. Some studies did not report information about blinding of the outcome assessment or how participants were allocated to conditions. However, sensitivity analyses indicated that these factors did not influence the findings of the review.

Limitations

The authors report some evidence for publication bias, such that studies reporting a positive effect of MI were more likely to be published, potentially compromising the results of this systematic review.

Eight of the 24 studies did not use biochemically-validated measures of abstinence. When analyses excluded these studies, the size of the beneficial effect of MI increased. Future research should use the biochemically-validated abstinence measures so as to ensure that smoking cessation is reliably reported.

Conclusions

These results indicate that MI is more effective at promoting smoking cessation than usual care or brief advice, although the effect is modest.

Some components of MI counselling appear to increase the effectiveness of MI for smoking cessation, including delivery by a primary care physician. The reviewers suggest that physicians may be better placed to use the MI approach given their established rapport with the patient. However, this effect is based on only two studies and therefore the importance of physician delivery should not be overstated.

Shorter sessions and fewer follow-ups were also found to be more effective than longer sessions with more follow-up sessions. One explanation given by the authors is that a single session is enough to motivate someone to quit smoking. Prolonging the time before the quit date may mean participants lose focus on their goal to stop smoking.

While MI seems to be effective in promoting smoking cessation, future research should continue to explore the components of MI which optimise the success of this intervention. The relationship between non-pharmacological interventions such as MI and pharmacological interventions should also be considered.

This review confirms that motivational interviewing for smoking cessation is supported by moderate level evidence.

Links

Primary paper

Lindson-Hawley N, Thompson TP, Begh R. Motivational interviewing for smoking cessation. Cochrane Database of Systematic Reviews 2015, Issue 3. Art. No.: CD006936. DOI: 10.1002/14651858.CD006936.pub3.

Other references

Heckman, C. J., Egleston, B. L. & Hofman, M. T. (2010). Efficacy of motivational interviewing for smoking cessation: a systematic review and meta-analysis. Tobacco Control, 19, 410-416.

Hettema, J. E. & Hendricks, P. S. (2010). Motivational interviewing for smoking cessation: A meta-analytic review. Journal of Consulting and Clinical Psychology, 78, 868-884. [DARE summary]