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.

Is moderate alcohol consumption good for you?

By Marcus Munafo @MarcusMunafo 

This blog originally appeared on the Mental Elf site on 13th March 2015

wine

This is something many of us would like to be true – the idea that the occasional glass of wine has health benefits is compelling in a society like the UK where alcohol consumption is widespread.

Certainly the observational data indicate a J-shaped associationbetween alcohol consumption and mortality (O’Keefe et al, 2007), with the lowest mortality observed at low to moderate levels of alcohol consumption (equivalent to perhaps a pint of beer a day for men, and about half that for women).

However, observational studies like this are fraught with difficulties.

  1. First, people may not report their alcohol consumption reliably.
  2. Second, and more importantly, alcohol consumption is associated with a range of other lifestyle behaviours, such as diet and smoking, which will themselves influence mortality, so that isolating any specific association of alcohol is extremely difficult.
  3. Third, how non-drinkers are defined may be important – lifetime abstainers may be different from former drinkers (who could have stopped drinking because of health problems).

The last point illustrates the problem of reverse causality; alcohol consumption may be causally associated with a range of health outcomes, but some of those health outcomes may also be causally associated with alcohol consumption.

In a recent study in the BMJ, the authors argue that the problems associated with the choice of an appropriate referent group of non-drinkers are often overlooked in research into alcohol-related mortality.

They also argue that age is not adequately considered, which may be relevant because of physiological changes to the ageing body that influence elimination of blood alcohol. Knott and colleagues explored the association between alcohol consumption and all cause mortality for people aged less than 65 years and aged 65 or more, and separated never and former drinkers.

The lowest mortality observed is at low to moderate levels of alcohol consumption (equivalent to perhaps a pint of beer a day for men, and about half that for women).

Methods

The authors used data from the Health Survey for England, an annual, nationally-representative cross sectional survey of the general population, linked to national mortality registration data.

The analysis focused on adults aged 50 years or older, and investigated two measures of alcohol consumption: self-reported average weekly consumption over the past year, and self-reported consumption on the heaviest day in the past week. The outcome was all cause mortality (i.e., any death recorded during the period of data collection).

The primary statistical analyses were proportional hazards analyses for each of the two age groups of interest (less than 65 years and 65 years or more). They tested for whether any associations observed differed between males and females and, given strong evidence of a sex-dose interaction, reported sex-specific models for each age group of interest.

Statistical adjustment was made for a comprehensive list of potential confounders, such as geographical location, ethnicity, cigarette smoking, obesity and a range of socio-demographic variables.

Results

Protective associations were only observed with statistical significance (a point I’ll return to below) among younger men (aged 50 to 64 years) and older women (65 years or older), using a never drinker referent category after full adjustment.

Among younger men a protective relationship between alcohol consumption and all cause mortality was observed among those who reported consuming 15.1 to 20 units per week (hazard ratio 0.49, 95% confidence interval 0.26 to 0.91).

Among older women, the range of protective use was broader but lower, with reductions in hazards of all cause mortality observed at all consumption levels up to 10 units per week of less.

The study supports a moderate protective effect of alcohol.

Conclusions

The authors conclude that observed associations between low levels of alcohol consumption and reduced all cause mortality may in part be due to inappropriate selection of a referent group (all non-drinkers, rather than never drinkers) and inadequate statistical adjustment for potential confounders.

They also conclude that beneficial dose response relationships between alcohol consumption and all cause mortality may be specific to women aged 65 years or older.

There is a relative lack of data on older populations in relation to the association between alcohol consumption and all cause mortality, which this study addresses. The consideration of different definitions of the referent category is also valuable – the authors are correct that conventional definitions of “non-drinker” may be problematic.

However, to what extent should we believe the conclusion that beneficial dose response relationships may be age- and sex-specific?

As David Spiegelhalter has pointed out, the authors base their conclusion on which associations achieved statistical significance and which did not. However, the hazard ratios for all cause mortality are consistently lower for alcohol consumers than non-consumers in this study. Although the confidence intervals are wider for some consumption levels and in some sub-groups (males vs females, or younger vs older), the individual hazard ratios are all consistent with each other.

The wide confidence intervals reflect a lack of statistical power, principally due to the small number of never drinkers, and the small number of deaths. Although the data set is relatively large, by carving it up into a number of sub-groups, the statistical power for the individual comparisons is reduced. Spiegelhalter points out that the entire comparison for participants in the younger age group is based on 17 deaths in the male baseline group and 19 deaths in the female group.

As Andrew Gelman and Hal Stern have said, the difference between “significant” and “non-significant” is not (necessarily) itself significant. Indeed, focusing on statistical significance (rather than effect size and precision) can lead to exactly the problems encountered here. Low statistical power is also a problem, reducing the likelihood that a statistically significant finding is true, and (perhaps more importantly) dramatically reducing the precision of our effect size estimates.

Should we believe that beneficial dose response relationships are age- and sex-specific?

Strengths and limitations

There are some strengths to this study, notably the use of a more considered referent category of never drinkers, and the statistical adjustment for a broad range of potential confounders.

However, the primary conclusion of the authors does not seem to be borne out by their own data – hazard ratios for all cause mortality are lower for alcohol consumers than non-consumers at all levels of consumption, for both men and women, and for both the younger and older age groups.

Is moderate alcohol consumption good for us then? The observational data, including that from this study, continues to suggest so.

However we should also remain wary of evidence from observational studies, which can be notoriously unreliable, and cannot confirm that an association is causal. Ultimately, we may need to use novel methods to answer this question, such as Mendelian randomization which utilized the properties of genetic variants to enable stronger causal inference.

We should be wary of evidence from observational studies, which can be notoriously unreliable, especially in underpowered studies like this one.

Link

Knott CS, Coombs N, Stamatakis E, Biddulph JP. (2015) All cause mortality and the case for age specific alcohol consumption guidelines: pooled analyses of up to 10 population based cohorts (PDF). British Medical Journal, 350, h384. doi: 10.1136/bmj.h384

O’Keefe HF, Bybee KA, Lavie CJ. (2007) Alcohol and cardiovascular health: the razor-sharp double-edged sword. J Am Coll Cardiol. 2007;50(11)

Spiegelhalter D. (2015) Misleading conclusions from alcohol protection study. Understanding Uncertainty website, last accessed 11 Mar 2015.

Research doesn’t just happen in the lab anymore: Mechanical Turk, Prolific Academic, and online testing.

By Michael Dalili @michaeldalili

Over the years, from assessment to analysis, research has steadily shifted from paper to PC. The modern researcher has an ever-growing array of computer-based and online tools at their disposal for everything from data collection to live-streaming presentations of their work. While shifting to computer- or web-based platforms is easier for some areas of research than others, this has proven to work especially well in psychology. These platforms can be used for anything from simply hosting an online version of a questionnaire, to recruiting and testing participants on cognitive tasks. Throughout the course of my PhD, I have increasingly used online platforms for multiple purposes, ranging from participants completing questionnaires online on Bristol Online Survey, to recruiting participants using Amazon Mechanical Turk and completing a task hosted on the Xperiment platform. And I’m not alone! While it’s impossible to estimate just how many researchers are using computer- and web-based platforms to conduct their experiments, we have a better idea of how many researchers are using online crowdsourcing platforms such as Mechanical Turk and Prolific Academic for study recruitment. Spoiler alert: It’s A LOT! In this blog post I will describe these two platforms and give an account of my experiences using them for online testing.

amazon

Amazon Mechanical Turk, or MTurk for short, is the leading online crowdsourcing platform. Described as an Internet marketplace for work that requires human intelligence, MTurk was publicly launched in 2005, having previously been used internally to find duplicates among Amazon’s product webpages.  It works as follows: workers (more commonly known as “Turkers”), who are individuals who have registered on the service, complete Human Intelligence Tasks (known as HITs) created by Requestors, who approve the completed HIT and compensate the Workers. Prior to accepting HITs, Workers are presented with information about the task, the duration of the task, and the amount of compensation they will be awarded upon successfully completing the task. Right now there are over 280,000 HITs available, ranging widely in terms of the type and duration of task as well as compensation. Amazon claims its Workers number over 500,000 ranging from 190 countries. They can be further sub-divided into “Master Categories”, who are described by Amazon as being “an elite group of Workers who have demonstrated superior performance while completing thousands of HITs across the Marketplace”. At time of writing, there are close to 22,000 Master Workers, with about 3,800 Categorization Masters and over 4,500 Photo Moderation Masters. As you might imagine, some Requestors can limit who can complete their HITs by assigning “Qualifications” that Workers must attain before participating in their tasks. Qualifications can range from requiring Master status to having approved completion of a specific number of HITs. While most Workers are based in the US, the service does boast an impressive gender balance,  with about 47% of its users being women.  Furthermore, Turkers are generally considered to be younger and have a lower income compared to the general US internet population, but possess a similar race composition. Additionally, many Workers worldwide cite Mechanical Turk as their main or secondary sources of income.

Since its launch, MTurk has been very popular, including among researchers. The number of articles on Web of Science with the search term “Mechanical Turk” has gone from just over 20 in 2012 to close to 100 in 2014 (see Figure 1). A similar search on PubMed produces 15 publications since the beginning of 2015.

graph
Figure 1. The number of articles found on the Web of Science prior to 2015 with the search term ‘Mechanical Turk’ within the ‘psychology’ research area. Used with permission fromWoods, Velasco, Levitan, Wan, & Spence (in preparation).

However, the popularity of MTurk has not come without controversy. Upon completing a HIT, Workers are not compensated until their task has been “approved” by the Requestor. Should the Requestor reject the HIT, the Worker receives no compensation and their reputation (% approval ratings) decreases. Many Turkers have complained about having had their HITs unfairly rejected, claiming Requestors keep their task data while withholding payment. Amazon has refused to accept responsibility for Requestors’ actions, claiming it merely creates a marketplace for Requesters and Turkers to contract freely and does not become involved in resolving disputes. Additionally, Amazon does not require Requestors to pay Workers according to any minimum wage, and a quick search of available HITs reveals many tasks requiring workers to devote a considerable amount of time for very little compensation. However, MTurk is only one of several crowdsourcing platforms, including CloudCrowd, CrowdFlower, and Prolific Academic.

poracad

Launched in 2014, Prolific Academic describes itself as “a crowdsourcing platform for academics around the globe”. Founded by collaborating academics from Oxford and Sheffield, Prolific Academic markets itself specifically as a platform for academic researchers. In fact, until August 2014, registration to the site was limited to UK-based individuals with academic emails (*.ac.uk) until it was opened up to everyone with a Facebook account (for user authentication purposes). Going a step further than its competition in appealing to academic researchers, Prolific Academic offers an extensive list of pre-screening questions (including questions about sociodemographic characteristics, levels of education or certifications, and more) that researchers can use to determine if someone is eligible to complete their study. Therefore, before someone can access and complete their study, they have to answer screening questions selected by the researcher. Individuals who have already completed screening questionnaires (available immediately upon signing up) will only be shown studies they are eligible for under the study page. At the time of writing this blog, according to the site’s homepage there are 5,081 individuals signed up to the site, with over 26,000 data submissions to date. Additionally, the site reports that participants have earned over £26,000 overall thus far. According to the site’s own demographics report from November 2014, 62% of users are male and the average age of users is about 24. Users are predominantly based in the US or UK. However, 1,500 users have joined since this report alone! Unlike MTurk and most other crowdsourcing platforms, Prolific Academic stipulates that researchers must compensate participants appropriately, which they term “Ethical Rewards”, requiring that participants be paid a minimum of £5 an hour.#

lab

I have had experience using both MTurk and Prolific Academic in conducting and participating in research. With the assistance of Dr Andy Woods and his Xperiment platform, where my experimental task is hosted online, I was able to get an emotion recognition task up and running online. This opened up the possibility of studies on larger and more diverse samples, as well as studies being completed in MUCH shorter time frames. With Andy’s help in setting up studies on MTurk, I have run three studies on the platform since July 2014, ranging in sample size from 100 to 243 participants. Most impressively, each study was completed in a matter of hours; conducting the same study in the lab would have taken months! Similarly, given the short duration of these tasks, and the speed and ease of completing and accessing study documents on a computer, these studies cost less than they would have had they been conducted in the lab.

My experience with Prolific Academic has only been as a participant thus far but has been very positive. All the studies I completed have adhered to the “Ethical Rewards” requirement, and all researchers have been prompt in compensating me following study completion. Study duration estimates have been accurate (if anything generous) and compensation is only withheld in the case of failed catch trials (more on that below). The site is very easy to use with a user-friendly interface. It is easy to contact researchers as well, which is helpful for any queries or concerns. I know several colleagues as well who have had similar experiences and I hope to run a study on the platform in the near future.

While there have been several criticisms of conducting research on these crowd-sourcing platforms, the most common one amongst researchers is that data acquired this way will be of lesser quality than data from lab studies. Critics argue that the lack of a controlled testing environment, possible distractions during testing, and participants completing studies for compensation as quick as possible without attending to instructions are all reasons against conducting experiments on these platforms. Given the fact that research using catch trials (trials included in experiments to assess whether participants are paying attention or not) has shown failure rates ranging from 14% to 46% in a lab setting, surely participants completing tasks from their own homes would do just as badly, if not worse? We decided to investigate for ourselves. In two of our online studies, we added a catch trial as the study’s last trial, shown below.

glitch

Out of the 343 people who completed the two studies, only 3 participants failed the catch trial. That is less than 1% of participants! And we are not the only ones who have found promising results from studies using crowdsourcing platforms. Studies have shown that Turkers perform better on online attention checks than traditional subject pool participants and that MTurk Workers with high reputations can ensure high-quality data, even without the use of catch trials. Therefore, the quality of data from crowdsourcing platforms does not appear to be problematic. However, using catch trials is still a very popular and useful way of identifying participants who may not have completed tasks with enough care or attention.

Since the launch of MTurk, many similar platforms have appeared and advances have been made. MTurk has been used for everything from getting Turkers to write movie reviews to helping with missing persons searches. It’s safe to say that crowdsourcing is here to stay and has changed the way we conduct research online, with many of these sites’ tasks working on mobile and tablet platforms as well. While people have been using computers and web platforms in testing for a long time now, using crowdsourcing platforms for participant recruitment is still in its infancy. Since the launch of MTurk, many similar platforms have appeared and advances have been made. With many new possibilties emerging with the use of these platforms, it is an exciting time to be a researcher.

Reducing alcohol consumption in illicit drug users: new Cochrane review on psychotherapies

By Olivia Maynard @OliviaMaynard17

This blog originally appeared on the Mental Elf site on 28th January 2015

shutterstock_3084226

Whilst we all know that excessive alcohol consumption is bad for our health, illicit drug users are one group for whom problem alcohol use can be especially harmful, causing serious health consequences.

The prevalence of the hepatitis C virus is high among illicit drug users and problem alcohol use contributes to a poorer prognosis of this disease by increasing its progression to other diseases. In addition, rates of anxiety, mood and personality disorders are higher among illicit drug users, each of which is exacerbated by problem alcohol use.

Despite these health consequences, the prevalence of problem alcohol use is high among illicit drug users, with around 38% of opiate- and 45% of stimulant-using treatment-seeking individuals having co-occurring alcohol use disorders (Hartzler 2010; Hartzler 2011).

Previous Cochrane reviews have investigated the effectiveness of psychosocial interventions (or ‘talking therapies’) for either problem alcohol use, or illicit drug use alone. However, none have investigated the effectiveness of these therapies for individuals with concurrent problem alcohol and illicit drug use. Given the significant health risk and the high prevalence of concurrent problem alcohol and illicit drug use, a Cochrane review of this kind is long over-due.

Luckily, Kilmas and colleagues have done the hard work for us and their comprehensive Cochrane review of the literature evaluates the evidence for talking therapies for alcohol reduction among illicit drug users (Klimas et al, 2014).

This updated Cochrane review looks at psychotherapy for concurrent problem alcohol and illicit drug use.

The talking therapies we’re concerned with here are psychologically based interventions, which aim to reduce alcohol consumption without using any pharmacological (i.e. drug-based) treatments. Although there’s a wide range of different talking therapies currently used in practice, the ones which are discussed in this Cochrane review are:

  • Motivational interviewing (MI): this uses a client-centered approach, where the client’s readiness to change and their motivation, is a key component of the therapy.
  • Cognitive-behavioural therapy (CBT): this focuses on changing the way a client thinks and behaves. To address problem alcohol use, CBT approaches identify the triggers associated with drug use and use behavioural techniques to prevent relapse.
  • Brief interventions (BI): often BIs are based on the principles of MI and include giving advice and information. However, as implied by the name, BIs tend to be shorter and so are more suitable for non-specialist facilities.
  • The 12-step model: this is the approach used by Alcoholics Anonymous and operates by emphasising the powerlessness of the individual over their addiction. It then uses well-established therapeutic approaches, such as group cohesiveness and peer pressure to overcome this addiction.

Methods

  • The Cochrane review included all randomised controlled trials which compared psychosocial interventions with another therapy (whether that be other psychosocial therapies (to allow for comparison between therapies), pharmacological therapies, or placebo). Participants were adult illicit drug users with concurrent problem alcohol use
  • Four studies were included, involving 594 participants in total
  • The effectiveness of these interventions were assessed and the authors were most interested in the impact of these therapies on alcohol use, but were also interested in their impact on illicit drug use, participants’ engagement in further treatment and differences in alcohol related harms
  • The quality of the studies was also assessed

The quality of trials included in this review could certainly have been a lot better.

Results

The four studies were very different, each comparing different therapies:

  • Study 1: cognitive-behavioural therapy versus the 12-step model (Carroll et al, 1998)
  • Study 2: brief intervention versus treatment as usual (Feldman et al 2013)
  • Study 3: group or individual motivational interviewing versus hepatitis health promotion (Nyamathi et al, 2010)
  • Study 4: brief motivational intervention versus assessment only (Stein et al, 2002)

Due to this heterogeneity, the results could not be combined and so each study was considered separately. Of the four studies, only Study 4 found any meaningful differences between the therapies compared. Here, participants in the brief motivational intervention condition had reduced alcohol use (by seven or more days in the past month at 6-month follow up) as compared with the control group (Risk Ratio 1.67; 95% Confidence Interval 1.08 to 2.60; P value = 0.02). However, no other differences were observed for other outcome measures.

Overall, the review found little evidence that there are differences in the effectiveness of talking therapies in reducing alcohol consumption among concurrent alcohol and illicit drug users.

The authors of this review also bemoan the quality of the evidence provided by the four studies and judged them to be of either low or moderate quality, failing to account for all potential sources of bias.

The review found no evidence that any of the four therapies was a winner when it came to reducing alcohol consumption in illicit drug users.

Conclusions

So, what does this all mean for practice?

In a rather non-committal statement, which reflects the paucity of evidence available, the authors report that:

based on the low-quality evidence identified in this review, we cannot recommend using or ceasing psychosocial interventions for problem alcohol use in illicit drug users.

However, the authors suggest that similar to other conditions, early intervention for alcohol problems in primary care should be a priority. They also argue that given the high rates of co-occurrence of alcohol and drug problems, the integration of therapy for these two should be common practice, although as shown here, the evidence base to support this is currently lacking.

And what about the comparison between the different talking therapies?

Again, rather disappointingly, the authors report that:

no reliable conclusions can be drawn from these data regarding the effectiveness of different types of psychosocial interventions for the target condition.

How about the implications for research? What do we still need to find out?

This review really highlights the scarcity of well-reported, methodologically sound research investigating the effectiveness of psychosocial interventions for alcohol and illicit drug use and the authors call for trials using robust methodologies to further investigate this.

Choosing a therapy for this group of patients is difficult with insufficient evidence to support our decision.

Links

Klimas J, Tobin H, Field CA, O’Gorman CSM, Glynn LG, Keenan E, Saunders J, Bury G, Dunne C, Cullen W. Psychosocial interventions to reduce alcohol consumption in concurrent problem alcohol and illicit drug users. Cochrane Database of Systematic Reviews 2014, Issue 12. Art. No.: CD009269. DOI: 10.1002/14651858.CD009269.pub3.

Hartzler B, Donovan DM, Huang Z. Comparison of opiate-primary treatment seekers with and without alcohol use disorderJournal of Substance Abuse Treatment 2010;39 (2):114–23.

Hartzler B, DonovanDM,Huang Z. Rates and influences of alcohol use disorder comorbidity among primary stimulant misusing treatment-seekers: meta-analytic findings across eight NIDA CTN trialsThe American Journal of Drug and Alcohol Abuse 2011;37(5):460–71.

Carroll, K.M., Nich, C. Ball, S.A, McCance, E., Rounsavile, B.J. Treatment of cocaine and alcohol dependence with psychotherapy and dislfram. Addiction 1998; 93(5):713-27. [PubMed abstract]

Feldman N, Chatton A, Khan R, Khazaal Y, Zullino D. Alcohol-related brief intervention in patients treated for opiate or cocaine dependence: a randomized controlled studySubstance Abuse Treatment, Prevention, and Policy 2011;6(22):1–8.

Nyamathi A, Shoptaw S,Cohen A,Greengold B,Nyamathi K, Marfisee M, et al. Effect of motivational interviewing on reduction of alcohol useDrug Alcohol Dependence 2010;107(1):23–30. [1879–0046: (Electronic)]

Stein MD, Charuvastra A, Makstad J, Anderson BJ. A randomized trial of a brief alcohol intervention for needle exchanges (BRAINE). Addiction 2002;97(6):691. [:09652140] [PubMed abstract]

Mikhail Pogosov / Shutterstock.com

– See more at: http://www.thementalelf.net/mental-health-conditions/substance-misuse/reducing-alcohol-consumption-in-illicit-drug-users-new-cochrane-review-on-psychotherapies/#sthash.DgftSUSM.dpuf

Helping people with depression return to work

By Meg Fluharty, @MegEliz_

This blog originally appeared on the Mental Elf blog on 27th January 2015.

shutterstock_213396637

Depression is a major public health concern, with a wide range of symptoms, including hopelessness, fatigue, impaired concentration, feelings of inadequacy, as well as slowed thought and movement processing (APA 2013).

These symptoms not only impact upon an individuals’ personal life, but can impair social functioning and the ability to work (Hirschfeld 2000, Lerner 2008).

Within the US, depression was related to 27.2 lost workdays per ill worker per year, and a total of $36.6 billion capital lost in the US labour force (Kessler, 2006).

A new Cochrane systematic review and meta-analysis aims to evaluate the effectiveness of the current interventions available for reducing workplace disability in depressive disorder (Nieuwenhuijsen et al, 2014).

A US study from 2006 found that depression was related to 27.2 lost workdays per ill worker per year.

Methods

The authors searched the following databases between January 2006 and January 2014: CENTRAL, MEDLINE, psychINFO, EMBASE, and CINAHL. Studies were included if they were:

  • Randomised controlled trials (RCT) or cluster RCTs
  • Participants were adults (17+)
  • Participants were from occupational health, primary care, or outpatient care settings
  • Depressive criteria met diagnostic criteria, was assessed by a self-reported symptom scale, or by a clinical rated instrument.

Studies were excluded if participants had a primary diagnosis of a psychiatric disorder other than depressive disorder including bipolar depression and depression with psychotic tendencies.

The authors included both workplace (modify the task or hours) and clinical (antidepressant, psychological, or exercise) interventions, and the primary outcome examined was the number of illness-related absences from work during follow up (Nieuwenhuijsen et al, 2014).

Workplace adjustments

Results

The original search yielded a total of 11,776 studies, and resulted in a full text assessment of 73 studies. 50 studies were excluded at the full-text stage- resulting in 1 study included in qualitative synthesis only, and 22 studies included within the meta-analysis.

Overall there were 20 RCTs and 3 Cluster RCTs, totalling 6,278 participants ranging from 20-200 participants between studies. 7 studies recruited from primary care settings, 10 from outpatient, 2 from occupational health, 1 from a managed care setting, and 1 was conducted in a community mental health centre (Nieuwenhuijsen et al, 2014).

Work directed interventions

5 work-directed interventions were identified:

  • There was moderate evidence that a work-directed intervention plus a clinical intervention reduced sick days when compared to clinical intervention alone or a work intervention alone
  • There was low evidence that an occupational therapy and return to work program was beneficial over occupational care as usual

The review found evidence to support a combination of work-directed interventions and clinical interventions.

Antidepressants

6 studies investigated and compared the effectiveness of different antidepressant use, including SSRI, SNRI, TCA, MAO, and placebo:

  • There was no difference between SSRIs and TCAs in reducing sickness absence, while another study found low quality evidence that either TCAs or MAOs reduced absences over placebo
  • Overall, the results of this category were inconsistent

Psychological therapies

  • There was moderate evidence of online or telephone CBT against occupational care as usual for reduction of absences
  • Two studies displayed no evidence that community health nurse interventions helped any more than care-as-usual

Psychological therapies combined with antidepressants

  • Two studies found that enhanced primary care did not decrease sick days over 4-12 months, and another longer term study found similar results
  • However, there was high quality evidence that a telephone outreach management program can be effective in reducing sick leave compared to care-as-usual

Exercise

  • There was low quality evidence that exercise was more effective than relaxing in sickness absence reduction
  • However, there was moderate evidence that aerobic exercise was not more effective than relation or stretching

The review found evidence to support the use of telephone outreach management programs (stern Matron optional).

Discussion

This review evaluated a number of RCTs investigating work or clinical interventions. However, in each category, there was a large amount of variation between the studies and very few studies per category making comparisons difficult.

There was moderate evidence that work-directed interventions combined with a clinical intervention reduced sick leave, and that primary or occupational care combined with CBT also reduced absences. Additionally, there was evidence that a telephone outreach management program with medication reduced absences from work compared to care as usual.

This suggests the need for more research on work-directed interventions to be paired with clinical care, as they have the potential to reduce illness-related absences, but there are currently limited studies evaluating these interventions (Nieuwenhuijsen et al, 2014).

primary or occupational care combined with CBT also reduced absences.

Links

Nieuwenhuijsen K, Faber B, Verbeek JH, Neumeyer-Gromen A, Hees HL, Verhoeven AC, van der Feltz-Cornelis CM, Bültmann U. Interventions to improve return to work in depressed people. Cochrane Database of Systematic Reviews 2014, Issue 12. Art. No.: CD006237. DOI: 10.1002/14651858.CD006237.pub3.

American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Arlington, VA: American Psychiatric Association, 2013.

Hirschfeld RM, Montgomery SA, Keller MB, Kasper S, Schatzberg AF, Moller HJ, et al. Social functioning in depression: a review. Journal of Clinical Psychiatry 2000; 61 (4):268–75. [PubMed abstract]

Lerner D, Henke RM. What does research tell us about depression, job performance, and work productivity? (PDF) Journal of Occupational and Environmental Medicine 2008; 50(4):401–10.

Kessler RC, Akiskal HS, Ames M, Birnbaum H, Greenberg P, Hirschfeld RM, et al. Prevalence and effects of mood disorders on work performance in a nationally representative sample of U.S. workers. American Journal of Psychiatry 2006; 163(9):1561–8.

Department of Health (2012). Advice for employers on workplace adjustments for mental health conditions (PDF). Department of Health, May 2012.

– See more at: http://www.thementalelf.net/mental-health-conditions/depression/helping-people-with-depression-return-to-work/#sthash.7fnmUfRX.dpuf