Category Archives: Research

Antidepressants during pregnancy and risk of persistent pulmonary hypertension of the newborn

by Meg Fluharty @MegEliz_

This blog originally appeared on the Mental Elf site on 2nd July 2015.

Persistent pulmonary hypertension of the newborn (PPHN) is associated with increased morbidity and mortality of infants and occurs in 10-20 per 10,000 births.

Those who survive face chronic lung disease, seizures, and neurodevelopmental problems as a result of hypoxemia and aggressive treatment (Walsh-Sukys et al 2000; Farrow et al 2005; Clark et al 2003; Glass et al 1995).

Based on a single study in 2006, the FDA issued a public health advisory that late pregnancy exposure to SSRIs may be associated with an increased risk of PPHN (FDA 2015; Chambers 2006). However, a review yielding conflicting findings led the FDA to conclude that they were premature in their conclusion.

This is the background to a new study by Huybrechts et al (2015), which sets out to investigate SRRI and non-SSRI antidepressants and the associated risk of PPHN in late stage pregnancy.

PPHN is a potentially fatal condition affecting mainly full-term babies, in which the blood flow to the lungs shuts down because the main arteries to the lungs constrict.

Methods

Cohort and data

Participants were drawn from the Medicaid Analytic eXtract (MAX) cohort, which holds the health records of medicate beneficiaries in the United States.

Antidepressants

If women filled 1 antidepressant prescription 90 days before delivery, they were considered ‘exposed.’ Antidepressant medications were classified as either SSRIs (Selective Serotonin Re-uptake Inhibitors) or non-SSRIs. Women exposed to both types of antidepressant were excluded from the analysis. A reference group of women was created, whom had not been exposed to either SSRI or non-SSRIs at any time during pregnancy.

Persistent Pulmonary Hypertension of the Newborn (PPHN)

PPHN was defined by the ICD-9 diagnostic criteria for persistent foetal circulation or primary pulmonary hypertension in the first 30 days following delivery.

Analysis

A sensitivity analysis was conducted to control for possible misclassification, with exposure status defined as filling 2 prescriptions during 90 days before delivery, and outcome redefined as only severe cases of PPHN (respiratory assistance, extracorporeal membrane oxygenation, or inhaled nitric oxide therapy).

This very large (3.8 million pregnant women) population-based study included mothers in the US on low income and with limited resources.

Results

Within 3,789,330 pregnancies, 3.4% of women used antidepressants in the 90 days before delivery, of which 2.7% were SSRIs and 0.7% were non-SSRI antidepressants.

Antidepressant versus non-use

  • 31.0 (95% CI, 28.1 to 34.2) per 10,000 infants exposed to antidepressant use had PPHN
  • 20.8 (95% CI, 20.4 to 21.3) per 10,000 infants not exposed to antidepressant use had PPHN

SSRI versus non-SSRI antidepressant use

  • 31.5 (95% CI 28.3 to 35.2) per 10,000 infants exposed to SSRIs had PPHN
  • 29.1 (95% CI 23.3 to 36.4) per 10,000 infants exposed to non-SSRIs had PPHN

Depression diagnosis

After restricting to a diagnosis of depression:

  • 33.8 (95% CI, 29.7 to 38.6) per 10,000 infants exposed to SSRIs had PPHN
  • 34.4 (95% CI, 26.5 to 44.7) per 10,000 infants exposed to non-SSRIs had PPHN
  • 14.9 (95% CI 23.7 to 26.1) per 10,000 infants not exposed to antidepressant use had PPHN

Sensitivity analysis

  • Women who filled 2 prescriptions in the 90 days before delivery did not have stronger associations
  • Changing the definition for PPHN did not alter associations in either SSRIs or non-SSRIs

The chances of a baby getting PPHN when its mother was not taking an SSRI are around 2 in 1,000, compared to around 3 in 1,000 when the mother had taken an SSRI in the last 90 days of pregnancy.

Discussion

Overall, the authors found evidence that SSRI exposure in the last 90 days of pregnancy may be associated with an increased risk of PPHN. However, the magnitude of risk observed is less than has previously been reported. Furthermore, sensitivity analyses did not amplify these risks.

The authors conclude by suggesting clinicians should take the increase of risk of PPHN into consideration when prescribing these drugs during pregnancy.

Limitations

There are a few limitations in this study to be noted:

  • Possible misclassification of the exposure or outcome, (e.g. filling a prescription does not guarantee it was taken as prescribed) which may bias the results. However, the authors did conduct a sensitivity analysis in order to control for this.
  • The baseline characteristics varied between women taking antidepressants and those who did not, with women prescribed antidepressants more likely to be older, white, taking other psychotropic medicines, be chronically ill, be obese, smoke, and have health care issues. While the SSRI and non-SSRI groups were more comparable, non-SSRI women had higher overall illness, more comorbidities, and co-medication use. Additionally, the participant population was drawn from a relatively low-income group, in which comorbid illness is likely to be higher than general populations, which may account for the difference in risk of previous studies.

This evidence would suggest that the benefits of antidepressants taken during pregnancy outweigh the risks of rare events such as PPHN.

Professor Andrew Whitelaw, Professor of Neonatal Medicine at the University of Bristol, said of the study:

Taking this study with the previous evidence, I conclude that there is a slightly increased risk of PPHN if a pregnant woman takes an SSRI but this only brings the risk up to 3 per 1000 births. I do not suggest that seriously depressed pregnant women should be denied SSRI treatment, but it would be wise for them to deliver in a hospital with a neonatal intensive care unit in case PPHN does occur.

Links

Primary paper

Huybrechts K, Bateman B, Palmsten K, Desai R, Patorno E, Gopalakrishnan C, Levin R, Mogun H, Hernandez-Diaz S. (2015) Antidepressant Use Late in Pregnancy and Risk of Persistent Pulmonary Hypertension of the Newborn. 2015: 313(21). [Abstract]

Other references

Walsh-Sukys MC, Tyson JE, Wright LL et al. (2000) Persistent pulmonary hypertension of the newborn in the era before nitric oxide: practice variation and outcomes. Pediatrics. 2000;105(1 pt 1):14-20. [PubMed abstract]

Farrow KN, Fliman P, Steinhorn RH. (2005) The diseases treated with ECMO: focus on PPHN. Semin Perinatol. 2005;29(1):8-14. [PubMed abstract]

Clark RH, Huckaby JL, Kueser TJ et al. (2003) Clinical Inhaled Nitric Oxide Research Group.  Low-dose nitric oxide therapy for persistent pulmonary hypertension: 1-year follow-up. J Perinatol. 2003;23(4):300-303. [PubMed abstract]

Glass P, Wagner AE, Papero PH et al. (1995) Neurodevelopmental status at age five years of neonates treated with extracorporeal membrane oxygenation. J Pediatr. 1995;127(3):447-457. [PubMed abstract]

US Food and Drug Administration. (2006) Public health advisory: treatment challenges of depression in pregnancy and the possibility of persistent pulmonary hypertension in newborns.

Chambers  CD, Hernández-Diaz  S, Van Marter  LJ,  et al.  Selective serotonin-reuptake inhibitors and risk of persistent pulmonary hypertension of the newborn. N Engl J Med. 2006;354(6):579-587. [PubMed abstract]

– See more at: http://www.nationalelfservice.net/treatment/antidepressants/antidepressants-during-pregnancy-and-risk-of-persistent-pulmonary-hypertension-of-the-newborn/#sthash.kEFM7Ik8.dpuf

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

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

CBT for substance misuse in young people

by Eleanor Kennedy @Nelllor_

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

According to 2011 figures for the UK, over 11% of people seeking treatment for substance use were aged between 15-19 years old (Emcdda.europa.eu, 2015).

Cognitive-Behavioural Therapy (CBT) is a treatment that uses cognitive and behavioural techniques to target drug-related beliefs and to alter how these beliefs impact on actions. The individualised nature of CBT may especially be beneficial for young people whose needs differ from those of an adult due to the developmental stage of adolescence.

The factors that moderate the success of CBT treatment among young people are not well-defined. The authors of the current review aimed “to assess the effectiveness of CBT for young people in outpatient non-opioid drug use and to explore any factors that may moderate outcomes” (Filges et al 2015). Non-opioid drugs refers to cannabis, cocaine, ecstasy and amphetamines.

The non-opioid drugs covered by this review were cannabis, cocaine, ecstasy and amphetamines.

Methods

Numerous online databases were searched and studies were included if:

  • The study design was either a randomised, quasi-randomised or non-randomised controlled trial (RCT, QRCT or NRCT)
  • Participants were aged 13-20 years old
  • Participants were enrolled in outpatient treatment for non-opioid drug treatment
  • CBT was the primary intervention, although CBT interventions with an add-on component, such as motivational interviewing, were included

The primary outcome measure was abstinence or reduction of drug use as measured by biochemical test, self-report estimates or psychometric scales. Secondary outcomes of interest were social and family functioning; education or vocational involvement; retention; risk behaviour such as crime rates.

Two separate meta-analyses were conducted.

Seven

Results

Study characteristics

Seven studies, reported in seventeen papers, were included in the review. All seven studies were RCTs; six were conducted in the US and one was carried out in The Netherlands. The seven studies were quite different; sample sizes ranged from 43 to 320 participants and the gender of participants enrolled ranged from 54% to 81% male.

CBT was compared to a range of interventions, namely adolescent community reinforcement approach; multidimensional family therapy; chestnut’s Bloomington outpatient program; interactional treatment; psychoeducational substance abuse treatment and functional family therapy. Three evaluated CBT only, while four studies looked at CBT with an add-on component including Assertive Continuing Care, Motivational Enhancement Intervention or Integrated Family therapy.

The studies also differed in terms of CBT delivery; one study provided individual CBT, two had group CBT session, one study included family sessions alongside peer-group therapy, another study had family sessions at the beginning and end of the treatment period, while another study provided a home-based continuing care approach.

Main findings

Separate meta-analyses were conducted on the four studies that looked at CBT with an add-on component and on the three studies that evaluated CBT without an add-on component. Analyses had differing numbers of included studies depending on the variable in question.

Outcome measures were evaluated in three different intervals: short term (beginning of treatment to < 6 months later); medium term (6 months to < 12 months after beginning treatment) and long term (12 months + after the beginning of treatment).

Drug use

  • Overall, studies that reported on the effects of CBT with an add-on component did not show a reduction of drug use relative to the comparison treatment in the:
    • Short term (SMD 0.14 95% CI -0.64 to 0.36);
    • Medium term (SMD -0.06 95% CI -0.44 to 0.32) or
    • Long term (SMD -0.15 95% CI -0.36 to 0.06)
  • The studies that evaluated CBT without an add-on component were not found to be significantly more effective than their respective comparison treatment in the
    • Short term (SMD -0.13 95% CI -0.68 to 0.42);
    • Medium term (SMD 0.08 95% CI -0.48 to 0.31) or
    • Long term (SMD 0.02 95% CI -0.48 to 0.52)

Recovery

  • Studies that reported on CBT with an add-on component showed a statistically significant relative effect on recovery status in the long term (OR = 0.63 (95% CI 0.39 to 1.00)
  • Only one study with CBT without an add-on component reported recovery status, this was not statistically significant (OR = 2.89 (95% CI 0.72 to 11.56)

Secondary outcomes

  • CBT with an add-on component was not found to have a significant relative effect on retention or risk behaviour
  • CBT without an add-on component also did not have a significant relative effect on psychological problems, family problems, school problems, retention or risk behaviour

Unfortunately, this review does not tell us whether CBT is more or less effective than other treatments for substance misuse in young people.

Strengths and limitations

The review had some strengths. A large number of databases were searched and there were no language restrictions on the literature included. Additionally, all included studies were RCTs with none of the studies classified as having a very high risk of bias.

The small number of studies included in this review is not problematic by itself, however, the choice to carry out separate meta-analyses based on the inclusion of an add-on component to the CBT, reduced the power of the analyses even further.

Additionally, caution must be taken when interpreting the findings of the meta-analyses as the studies were all very different. There was significant heterogeneity between the studies in all but one analysis and also many of the analyses were conducted on only two studies.

The qualitative review of the paper was weak, it was merely a description of the included studies without an evaluation of the differences between them.

Conclusions

The review is inconclusive in terms of CBT being more or less effective than other therapies, as the authors themselves note. No qualitative comparisons were drawn between the studies, this may have been more beneficial given the array of differences between all seven studies.

The review did not consider any factors that may moderate the efficacy of CBT as a treatment for non-opioid drug use and the authors suggest that future studies should include more information about the heterogeneity of treatment effects so that this can be explored.

Given the differences between the included studies, a meta-analysis was probably not appropriate and a good quality systematic review may have been more useful.

More qualitative analysis of the included studies may have shed more light on this discussion.

Links

Primary paper

Filges T, Knudsen ASD, Svendsen MM, Kowalski K, Benjaminsen L, Jørgensen AMK. Cognitive-Behavioural Therapies for Young People in Outpatient Treatment for Non-Opioid Drug Use: A Systematic Review. Campbell Systematic Reviews 2015:3 10.4073/csr.2015.3

Other references

Emcdda.europa.eu, (2015). EMCDDA | European Monitoring Centre for Drugs and Drug Addiction — information on drugs and drug addiction in Europe. [online] Available at: http://www.emcdda.europa.eu/ [Accessed 15 May 2015].

– See more at: http://www.nationalelfservice.net/mental-health/substance-misuse/cbt-for-substance-misuse-in-young-people/#sthash.xWsGpoWk.dpuf

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

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

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.

Lawrence D, Hancock KJ, Kisely S. The gap in life expectancy from preventable physical illness in psychi- atric patients in Western Australia: retrospective analysis of population based registers. BMJ 2013;346: f2539-f.

Nielsen RE, Uggerby AS, Jensen SOW, McGrath JJ. Increasing mortality gap for patients diagnosed with schizophrenia over the last three decades – a Danish nationwide study from 1980 to 2010. Schizophr Res 2013;146:22–27.  
[PubMed abstract]

Ruther T, Bobes J, de Hert M et al. EPA guidance on tobacco dependence and strategies for smoking cessation in people with mental illness. Eur Psychiatry 2014;29:65– 82. 
[PubMed abstract]

Hartz SM, Pato CN, Medeiros H et al. Comorbidity of severe psychotic disorders with measures of substance use. JAMA Psychiatry 2014;71:248–254.

 

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

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-analysisTobacco 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]

 

Researching abroad: Cannabis and decision making in the Big Apple

by Michelle Taylor @chelle_bluebird

Setting off for TARGs 2013 annual retreat to Cumberland Lodge in Great Windsor Park, I was looking forward to hearing a talk from an invited guest speaker. Gill had flown in from Columbia University to talk to the group about a recent drug administration study her lab group had completed. The research being conducted by their lab was very different to the epidemiological research that I am used to. Now don’t get me wrong, I thoroughly enjoy the research that I do, but these studies sounded new and exciting. After listening to the talk, the evening activities began with dinner and a quiz. Luckily, I ended up on the same quiz team as Gill, giving me the opportunity to ask more about her research. I decided to grab the bull by the horns and offer my help in one of her future studies, and so my trip to the Big Apple began…

central park 1Nine months later I was on my way to Heathrow for a two month stint collecting data on a cannabis administration study. I was both excited and apprehensive. I have never lived more than a 3 hour drive away from family, and have always been in a city where I have known people. I didn’t know whether I would get homesick, or whether I would make friends on my trip abroad. These feelings of apprehension soon disappeared in the first few hours of my first day at the New York Psychiatric Institute. Everyone I met was so friendly and welcoming, even the many morning commuters who stopped to help the lone Brit who was obviously puzzled by the subway map at 7.30am.

yankeesI was to spend the next six weeks collecting data for a study examining the neuro-behavioural mechanisms of decisions to smoke cannabis at the Substance Use Research Center in the New York Psychiatric Institute at Columbia University. This research centre is unique; it is one of the largest drug administration centre in the world and has licenses to administer a wide variety of drugs, including cannabis, cocaine and heroin. This means that much of the research conducted here is cutting edge. The aim of the study that I would be working on was to shed light on how and why drug abusers repeatedly make decisions to take drugs despite substantial negative consequences. The study used brain imaging (fMRI) to examine the neural and behavioural processes involved in decisions to self-administer cannabis, compared to decisions to eat food, in regular cannabis users. We also examined the influence of drug and food cues on the processes underlying these decisions. To do this, participants were recruited as inpatients and stayed with us in the lab for a week. Data collection for this study is still ongoing, but I will be sure to write another blog post with what we found when the results are available.

coney_2I found this research fascinating and it was a pleasure to be involved in the work carried out in this department. The experience was made even more enjoyable by the people I was working with. There were many office conversations about the British and American slang that was being used, many lunchtime trips to Chipotle (an American fast food restaurant that I am definitely missing since my return to the UK), and several Friday evening trips to the local Irish bar. One office memory that will always stick in my mind was meeting a very accomplished researcher in the field of my PhD, a researcher that was definitely someone I should be impressing. Upon entering this individuals office on an extreme
ly hot New York day, the fan was turned to the meeting area and the smell of cannabis filled the room as the flow of air reached me (I had been administered the drug to a participant earlier that afternoon). Probably not the best first impression I have ever made!

milkshakeI did, of course, take every opportunity to explore New York. I was lucky enough to get tickets to watch the New York Yankees beat the Boston Red Sox at the Yankee Stadium, which was also one of the last games played by baseball-legend Derek Jeter. I made several trips to the American Natural History Museum (my favourite type of museum, and this one cannot be done in a day), and while there saw a live spider show, a 3D film about Great White Sharks and a full T-Rex skeleton. The glorious weather allowed for several leisurely strolls around Central Park. And, of course, the American food definitely needs a mention. If anyone reading this takes a trip over the Atlantic, I would definitely recommend visiting Big Daddy’s Diner for what could be the best milkshake on the planet. And don’t be shy about trying a hotdog from one of the carts that can be found on nearly every street corner. The reason there are so many of them is that they’re delicious! I would also recommend a trip to the Russian Tea Rooms for caviar afternoon tea, an evening at the New York Metropolitan Opera (if that’s your cup of tea), and a trip to Coney Island.

t_rexAlthough it was daunting going abroad for that length of time to begin with, I don’t think I would be having those feelings again and I would definitely jump at any opportunity to work in a different environment in the future. I am very grateful that I am a PhD student in a large working group like TARG, as without this I probably would not have come across opportunities such as this one. This experience has taught me the importance of inter-disciplinary research, and the need for several fields contributing evidence to a much larger research question. Since this trip, I have been successful in a fellowship application allowing me 9 months in a different department at the University of Bristol, an application that I probably would not have made if it wasn’t for my experience at the Columbia University. I am an epidemiologist and do not have any plans to change that; however I do plan to conduct more interdisciplinary research in the future. I would like to that Gill (and everyone in her lab group) for welcoming me and making this trip possible. I look forward to hopefully working with you again in the future…

E-cigarettes and teenagers: cause for concern?

By Marcus Munafo @MarcusMunafo 

This blog originally appeared on the Mental Elf site on 20th April 2015

shutterstock_208797175

Electronic cigarettes (e-cigarettes) are a range of products that deliver vapour which typically contains nicotine (although zero-nicotine solutions are available). The name is misleading because some products are mechanical rather than electronic, and because they are not cigarettes. While first-generation products were designed to be visually similar to cigarettes, second- and third-generation products are visually distinctive and come in a variety of shapes and sizes. Critically, these products do not contain tobacco, and are therefore intended to deliver nicotine without the harmful constituents of tobacco smoke.

There has been rapid growth in the popularity and use of e-cigarettes in recent years, accompanied by growth in their marketing. At present they are relatively unregulated in many countries, although countries are introducing various restrictions on their availability and marketing. For example, a ban on sales to under-18s will be introduced in England and Wales in 2015.

These products have stimulated considerable (and often highly polarized) debate in the public health community. On the one hand, if they can support smokers in moving away from smoking they have enormous potential to reduce the harms associated with smoking. On the other hand, the quality and efficacy of these products remains largely unknown and is likely to be highly variable, and data on the long-term consequences of their use (e.g., the inhalation of propylene glycol vapour and flavourings) is lacking. There is also a concern that these products may re-normalise smoking, or act as a gateway into smoking.

E-cigarettes and teenagers: a gateway

Methods

This study reports the results of a survey conducted by Trading Standards in the North-West of England on 14 to 17 year-old students. The survey focuses on tobacco-related behaviours, and a question on access to e-cigarettes was introduced in 2013. This enabled identification of factors associated with e-cigarette use among people under 18 years old.

The study used data from the 5th Trading Standards North West Alcohol and Tobacco Survey among 14 to 17 year-olds in North-West England, conducted in 2013. The questionnaire was made available to secondary schools across the region through local authority Trading Standards departments, and delivered by teachers during normal school lessons. Compliance was not recorded, and the sample was not intended to be representative but to provide a sample from a range of communities.

The survey consisted of closed, self-completed questions covering sociodemographic variables, alcohol consumption and tobacco use. There were also questions on methods of access to alcohol and tobacco, as well as involvements in violence when drunk. E-cigarette access was assessed by the question “Have you ever tried or purchased e-cigarettes?”.

The study used data from the North West Alcohol and Tobacco Survey, which asked 14 to 17 year-olds lots of questions about their substance use behaviour.

Results

A total of 114 schools participated, and the total dataset included 18,233 participants, of which some were removed for missing data or spoiled questionnaires (e.g., unrealistic answers), so that the final sample for analysis was 16,193. Some of the main findings of the survey included:

  • In total, 19.2% of respondents reported having accessed e-cigarettes, with this being higher in males than females, and increasing with age and socioeconomic deprivation.
  • Level of e-cigarette access was higher among those who had smoked, ranging from 4.9% of never smokers, through 50.7% of ex-smokers, 67.2% of light smokers and 75.8% of heavy smokers.
  • E-cigarette use was associated with alcohol use, with those who drank alcohol more likely to have accessed e-cigarettes than non-drinkers, as well as with smoking by parents/guardians.

Nearly 1 in 5 of the young people surveyed

Conclusion

The authors conclude that their results raise concerns around the access to e-cigarettes by children, particularly among those who have never smoked cigarettes. They argue that their findings suggest that the children who access e-cigarettes are also those most vulnerable to other forms of substance use and risk-taking behavior, and conclude with a call for the “urgent need for controls on e-cigarette sales to children”. The study has some important strengths, most notably its relatively large size, and ability to determine which respondents were living in rich and poor areas.

Understanding the determinants of e-cigarette use, and patterns of use across different sections of society, is important to inform the ongoing debate around their potential benefits and harms. However, it is also not clear what this study tells us that was not already known. The results are consistent with previous, larger surveys, which show that young people (mostly smokers) are trying e-cigarettes. Critically, these previous surveys have shown that while some young non-smokers are experimenting with electronic cigarettes, progression to regular use among this group is rare. Product labels already indicate that electronic cigarettes are not for sale to under-18s, and in 2014 the UK government indicated that legislation will be brought forward to prohibit the sale of electronic cigarettes to under-18s in England and Wales (although at present no such commitment has been made in Scotland).

This study does not add anything significant to our knowledge about e-cigarettes.

Limitations

There are a number of important limitations to this study:

  • As the authors acknowledge, this was not meant to be a representative survey, and the results can therefore not be generalized to the rest of the north-west of England, let alone the wider UK.
  • As a cross-sectional survey it was not able to follow up individual respondents, for example to determine whether never smokers using e-cigarettes progress to smoking. This problem is common to most e-cigarette surveys to date.
  • The question asked does not tell us whether the participants actually used the e-cigarette they accessed, or what liquid was purchased with the e-cigarette (e.g., the concentration of nicotine). Zero-nicotine solutions are available, and there is evidence that these solutions are widely used by young people.
  • The results are presented confusingly, with numerous percentages (and percentages of percentages) reported. For example, 4.9% of never smokers reported having accessed e-cigarettes, but this is less than 3% of the overall sample (fewer than 500 out of 16,193 respondents). This is potentially an important number to know, but is not reported directly in the article.

Summary

This study does not add much to what is already known. Young people experiment with substances like tobacco and alcohol, and as e-cigarettes have become widely available they have begun to experiment with these too. However, to describe electronic cigarette use as “a new drug use option” and part of “at-risk teenagers’ substance using repertoires” is probably unnecessarily alarmist, given that:

  1. There is evidence that regular use of e-cigarettes among never smokers is negligible
  2. There is little evidence of e-cigarette use acting as a gateway to tobacco use
  3. The likelihood that e-cigarette use will be associated with very low levels of harm

It's alarmist to suggest

Links

Primary reference

Huges K, Bellis MA, Hardcastle KA, McHale P, Bennett A, Ireland R, Pike K. Associations between e-cigarette access and smoking and drinking behaviours in teenagers. BMC Public Health 2015; 15: 244. doi: 10.1186/s12889-015-1618-4

Other references

Young Persons Alcohol and Tobacco Survey 2013. Lancashire County Council’s Trading Standards.

New evidence on the effects of plain cigarette packaging in Australia

By Olivia Maynard @OliviaMaynard17 

This blog originally appeared on the Mental Elf site on 27th March 2015

Last week I was lucky enough to attend the 15th Annual World Conference on Tobacco or Health in Abu Dhabi. With both Ireland and the UK announcing in the weeks leading up to the conference that they would implement plain (or ‘standardised’) packaging of cigarettes, it wasn’t surprising that this was one of the conference’s hot topics.

One of the sessions that focused on plain packaging was organised by Professor Melanie Wakefield’s team at the Cancer Council Victoria in Australia. As the first country in the world to introduce plain packaging, Australian data on its real-world effectiveness is of keen interest to policy-makers worldwide.

These researchers published a supplement to the journal Tobacco Control last week, including 12 new studies on plain packaging in Australia (more details about each of the 12 studies and their methodologies are given at the end of this blog). The majority of these used a ‘pre-post’ methodology, which means that they assessed behaviours and attitudes to smoking before plain packaging was introduced and compared with these same attitudes and behaviours afterwards.

At their conference session, some of these studies were discussed in more detail, with one in particular (Durkin et al., 2015), which investigated the impact of plain packaging on quitting-related cognitions, catching my attention. This study seemed like the logical extension of my most recently published paper on plain packaging, which reports the results of randomising UK smokers to use either a branded or a plain pack of cigarettes for a day and measuring smoking behaviour and attitudes to smoking and quitting.

As I’ll discuss later on, it’s important that we use a range of methodologies, including laboratory based experiments (such as those I’ve conducted) and real-world investigations (such as those conducted by the Australian researchers) to investigate the possible impact of plain packaging.

Plain (or ‘standardised’) packaging would mean standardising the size, shape, colour and method of opening of all tobacco products.

Methods

Data for this study were obtained as part of a continuous cross-sectional telephone based survey. Participants were called twice, one month apart, first for a baseline survey and then for a follow-up. Participants were aged between 18 and 69 and all participants were required to be cigarette smokers at the baseline call.

All calls were made between April 2012 and March 2014 and participants were split into 4 groups according to when their two phone calls were made:

  1. Those who had both their baseline and follow-up phone calls before plain packaging was introduced
  2. Participants’ baseline call was made before plain packaging was introduced and their follow-up was during a transitional period where both plain and branded packs were available for purchase
  3. Baseline phone calls were made during the transitional period, whilst follow-up calls were made either during the transitional period or after plain packaging had been fully implemented (November 2012)
  4. Both baseline and follow-up calls were made within the first year of plain packaging being fully implemented

At both the baseline and follow-up stages, participants were asked about quitting related cognitions, micro-indicators of concern and quit attempts. Logistic regression was used to analyse the data and participants’ baseline scores were included as predictors for their follow-up scores (after accounting for potential confounders). Essentially, this means that follow-up scores between participants in the four groups could be directly compared, accounting for any differences at baseline. Responses from participants in Groups 2, 3 and 4 were compared with those of the participants in Group 1.

Results

In total, 5,137 participants completed both the baseline and follow-up calls. At follow-up, approximately 6% of participants across all groups had quit smoking. The following results were found for each of outcome measures:

Quitting related cognitions

  • No differences in thoughts about quitting, or plans to quit in the next month were observed between the groups. However, higher intentions to quit were observed among those in Group 3 as compared with those in Group 1

Micro-indicators of concern

  • Participants in Groups 3 and 4 were more likely to conceal their pack than those in Group 1
  • Those in Group 4 reported higher levels of stubbing out cigarettes early than those in Group 1
  • Higher rate of forgoing cigarettes were observed amongst participants in Group 2 than Group 1

Quit attempts

  • More quit attempts were reported among participants in Groups 2 and 4 as compared with those in Group 1

Given that results are likely to be closely scrutinised by researchers, policy makers and the tobacco industry, it is important to carefully consider their implications and not overstate the findings.

Conclusions

This study provides modest statistical evidence that plain packaging in Australia has increased micro-indicators of concern, increased quit attempts and increased some quitting related cognitions among smokers.

The authors describe the outcomes they measured in the current study as being ‘downstream’ from the more immediate effects of plain packaging, which they have found evidence for in their other studies. These include:

It is possible that more substantial changes in the downstream effects such as those measured in this study may take longer to emerge.

Plain packaging: putting these results in context

Investigating the impact of plain packaging in the ‘real-world’ using this pre-post technique has its limitations. Unlike the laboratory, the real-world isn’t tightly controlled and although the researchers tried to account for other factors which may have influenced the results, such as changes in the price of tobacco and other tobacco control measures such as mass media campaigns, it’s impossible to completely control for the effect of these, making causal interpretations difficult.

Obviously we cannot randomise whole countries to either introduce or not introduce plain packaging (which would address these limitations), and examine what happens to smoking prevalence in these countries. Studies like that by Durkin and colleagues are therefore probably the best that we can do in the real world. Moreover, no one piece of research will give us the full picture when it comes to the potential impact of plain packaging.

Although, on their own, these findings do not provide overwhelming support for a beneficial impact of plain packaging, when they are considered together with the other studies in theTobacco Control supplement, and with data from the Australian government (which this year reported record lows in tobacco sales and smoking prevalence) along with findings fromlaboratory-based experiments and surveys, the evidence looks more compelling.

Now that both the UK and Ireland have announced plans to introduce plain packaging in May 2016, with other countries likely to follow suit, it will be important to continue to monitor the longer-term impacts of this tobacco control measure, making use of the wide range of research tools and methodologies available to us.

Plain packaging will become

Links

Primary study

Durbin S, Brennan E, Coomber K, Zacher M, Scollo M, Wakefield M. Short-term changes in quitting-related cognitions and behaviours after the implementation of plain packaging with larger health warnings: findings from a national cohort study with Australian adult smokersTobacco Control 2015;24:Suppl 2 ii26ii32 doi:10.1136/tobaccocontrol-2014-052058

Other references

Research papers included in the Tobacco Control plain packaging Supplement:

Two paper-based surveys of adolescents:

Six telephone survey-based studies:

One in-depth interview:

One analysis of tobacco retailer journals:

Two observational studies:

High potency cannabis and the risk of psychosis

By Eleanor Kennedy @Nelllor_

This blog originally appeared on the Mental Elf site on 24th March 2015

shutterstock_27220114

Smoking higher-potency cannabis may be a considerable risk factor for psychosis according to research conducted in South London (Di Forti, et al., 2015).

Cannabis is the most widely used illicit drug in the UK and previous research has suggested an association between use of the drug and psychosis, however the causal direction and underlying mechanism of this association are still unclear.

This recent case-control study published in Lancet Psychiatry, aimed to explore the link between higher THC (tetrahydrocannabinol) content and first episode psychosis in the community.

To compare the impact of THC content on first episode psychosis, participants were asked whether they mainly consumed skunk or hash. Analysis of seized cannabis suggests that skunk has THC content of between 12-16%, while hash has a much lower THC content ranging from 3-5% (Potter, Clark, & Brown, 2008; King & Hardwick, 2008).

Cannabis hash and skunk have very different quantities of the active THC component.

Methods

The researchers used a cross-sectional case-control design. Patients presenting for first-episode psychosis were recruited from a clinic in the South London and Maudsley NHS Foundation Trust; patients who had an identifiable medical reason for the psychosis diagnosis were excluded. Control participants were recruited from the local area using leaflets, internet and newspaper adverts. There were 410 case-patients and 370 controls recruited.

Researchers gathered data on participants’ cannabis use in terms of lifetime history and frequency of use as well as type of cannabis used, i.e. skunk or hash. Participants were also asked about their use of other drugs including alcohol and tobacco, as well as providing demographic information.

Results

The case-patients and control participants were different in a couple of key areas (note: psychosis is more common in men and in ethnic minorities):

Case patients Control participants 
Male 66% 56%
Age 27.1 years 30.0 years
Caribbean or African ethnic origin 57% 30%
Completed high level of education 57% 90%
Ever been employed 88% 95%
Lifetime history of ever using cannabis 67% 63%

Participants with first episode psychosis were more likely to:

  • Use cannabis every day
  • Use high-potency cannabis
  • Have started using cannabis at 15 years or younger
  • Use skunk every day

A logistic regression adjusted for age, gender, ethnic origin, number of cigarettes smoked, alcohol units, and lifetime use of illicit drugs, education and employment history showed thatcompared to participants who had never used cannabis:

  • Participants who had ever used cannabis were not at increased risk of psychosis
  • Participants who had used cannabis at age 15 were at moderately increased risk of psychotic disorder
  • People who used cannabis or skunk everyday were roughly 3 times more likely to have diagnosis of psychotic disorder

A second logistic regression was carried out to explore the effects of a composite measure of cannabis exposure which combined data on the frequency of use and the type of cannabis used.Compared with participants who had never used cannabis:

  • Individuals who mostly used hash (occasionally, weekends or daily) did not have any increased risk of psychosis
  • Individuals who smoked skunk less than once a week were nearly twice as likely to be diagnosed with psychosis
  • Individuals who smoked skunk at weekends were nearly three times as likely to be diagnosed with psychosis
  • Individuals who smoked skunk daily were more than five times as likely to be diagnosed with psychosis

The population attributable factor (PAF) was calculated to estimate the proportion of disorder that would be prevented if the exposure were removed:

  • 19.3% of psychotic disorders attributable to daily cannabis use
  • 24.0% of psychotic disorders attributable to high potency cannabis use
  • 16.0% of psychotic disorders attributable to skunk use every day

These findings raising awareness among young people of the risks associated with the use of high-potency cannabis

Conclusions

The results of this study support the theory that higher THC content is linked with a greater risk of psychosis, with daily use of skunk conferring the highest risk. Recruiting control participants from the same area as the case participants meant that the two groups were more likely to be matched on not only demographic factors but also in terms of the actual cannabis that both groups were consuming.

The study has some limits, such as the cross-sectional design which cannot be used to establish causality. Also the authors have not included any comparison between those who smoke hash and those who consume skunk so no conclusions can be drawn about the relative harm of hash.

Media reports about the study have mainly focussed on the finding that ‘24% of psychotic disorders are attributable to high potency cannabis use’. This figure was derived from a PAF calculation which assumes causality and does not allow for the inclusion of multiple, potentially interacting, risk factors. Crucially the PAF depends on both the prevalence of the risk factor and the odds ratio for the exposure; the PAF can be incredibly high if the risk factor is common in a given population.

In this case, the prevalence rate of lifetime cannabis use was over 60% in both participant groups. According to EMCDDA, the lifetime prevalence of cannabis use in the UK is 30% among adults aged 15-64, so it is arguable that this study sample is not representative of the rest of the UK. The authors themselves note that “the ready availability of high potency cannabis in south London might have resulted in a greater proportion of first onset psychosis cases being attributed to cannabis use than in previous studies”, which is a more accurate interpretation than media reports claiming that “1 in 4 of all new serious mental disorders” is attributable to skunk use.

Future studies looking at the relationship between cannabis and psychosis should also aim to differentiate high and low potency cannabis. Longitudinal cohort studies are particularly useful as they have the same advantages as a case-control design but data about substance use could be more reliable as ‘lifetime use’ can be gathered from multiple measurements collected at a number of time points across the lifetime.

This innovative study is the first to distinguish between different strengths of cannabis in this way.

Links

Primary study

Di Forti M. et al (2015). Proportion of patients in south London with first-episode psychosis attributable to use of high potency cannabis: a case-control study (PDF). The Lancet Psychiatry, 2(3), 233-238.

Other references

King L, & Hardwick S. (2008). Home Office Cannabis Potency Study (PDF). Home Office Scientific Development Branch.

Potter DJ, Clark P, & Brown MB. (2008). Potency of Delta(9)-THC and other cannabinoids in cannabis in England in 2005: Implications for psychoactivity and pharmacology (PDF). Journal of Forensic Sciences, 53(1), 90-94.