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Does calorie and unit information influence our drinking behaviour?

By Olivia Maynard

Over the past two years we’ve invited hundreds of people into the lab to drink beer. Unfortunately, we weren’t there to socialise; this was in the name of science. We wanted to know whether giving people information about the number of units and or calories in their beer influenced how much they drank and their perceptions of drinking.

There are strong arguments for including this information: providing unit information may increase knowledge about alcohol consumption and calorie information may help drinkers choose lower calorie (and as a result lower unit) beverages. However, we also wondered whether there might be some unintended consequences of providing this information, particularly for those who are highly motivated to drink. What if unit information simply allows these drinkers to choose higher strength drinks and calorie information only discourages them from eating more, not drinking less? What if discussion around mandatory unit and calorie labelling is distracting us from the bigger issues: health warnings, minimum unit pricing, improving treatment for alcohol dependence and stopping alcohol advertising to young people, to name a few?

So, with this healthy level of scepticism, we set about inviting 264 regular alcohol consumers (mostly undergraduate students) to attend a lab session where they were given some beer and completed some taste ratings. What participants didn’t know was that they had been randomly assigned to one of four conditions. One group had information about the calorie and unit content of the beers, one group just got calorie information, another had just unit information, and the final group got no information at all. As well as measuring how much beer they drank, we also asked participants to reflect on the likely impact of unit and calorie information on their drinking behaviour.

You can read all the results in our (open access) paper that was published this week in the journal Alcohol and Alcoholism. If you want the concise version: we found no evidence that either unit or calorie information influenced how much beer people consumed and we found a lot of variation in the amount people drank.

However, it was our analysis of participants’ thoughts on unit and calorie information that proved vital to understanding what was going on here. Our participants told us that their main motivation for drinking alcohol was usually to get drunk; where unit information was perceived as being helpful, this was to help them choose the highest strength drink. Unit and calorie information was seen as distracting from the social aspect of drinking, and although some participants felt that calorie information might reduce consumption, most thought it would affect others, not themselves. Some people thought that calorie information could be misused by encouraging people to eat less (to compensate), rather than drink less.

It’s interesting that even though the unit and calorie information was very visible in our study (on a piece of paper, presented for 10 minutes), those who had received this information were still very inaccurate when it came to reporting how many units and calories were in their drinks. They basically didn’t seem to have read or engaged with it. If they’re not reading it in this context, is it likely that drinkers will read this information when it’s printed in tiny font on the back of the bottle?

So, what does this all mean for any plans to introduce unit and calorie information? Our study only really tells us about the potential impact of unit and calorie information among young adults (many of whom were students) who tend to drink to get drunk. However, our findings do call into question whether mandatory unit and calorie labelling on its own would reduce how much people drink, and also highlights potential negative unintended consequences of providing this information.

Despite some of these potential unintended consequences, there are still reasons to include unit and calorie information, if only because it’s a consumer right (you know how many calories are in just about everything else you consume). However, perhaps more effort needs to be placed on making this information more engaging and embedding it into public understanding of recommended drinking levels. Coincidentally, an analysis of the public’s awareness of new national alcohol guidelines was also published yesterday. This report argues that although the public have a relatively high awareness of what the guidelines are, they should be put into context by increasing the public’s awareness of the links between alcohol and cancer. Perhaps using health messages such as ‘Drinking alcohol regularly is linked to long-term risks such as cancer’, alongside unit and calorie information, might result in more meaningful changes in attitudes and behaviours around drinking. I feel another study coming on….

Olivia Maynard can be found on Twitter at @OliviaMaynard17

Alcohol brief interventions: how can content, provider and setting reduce alcohol consumption?

screen-shot-2016-09-23-at-10-11-24 

Alcohol brief interventions (ABIs) provide structured advice on alcohol use. They involve an assessment of individual risk with feedback and advice, brief motivational interviewing, or a combination of these techniques.

While the Government’s Alcohol Strategy (HM Government, 2012) recommends that ABIs be implemented increasingly inprimary care settings and accident and emergency (A&E) departments, the National Institute for Health and Care Excellence (NICE) calls for alcohol brief interventions to be offered by a range of practitioners and in a range of different settings.

Given national-level support for increasing and wider use of ABIs, this systematic review and multi-level meta-regression by Platt and colleagues assessed the effectiveness of ABIs on alcohol consumption and how effectiveness of ABIs differs by:

  1. Content of intervention,
  2. Provider group and
  3. Setting.
Alcohol brief interventions usually involve a combination of risk assessment, feedback, advice and brief motivational interviewing.

Alcohol brief interventions usually involve a combination of risk assessment, feedback, advice and brief motivational interviewing.

Methods

Studies were peer-reviewed randomised controlled trials (RCTs) where participants were randomly allocated to a control group (such as treatment as usual) or a group which received an alcohol brief intervention.

Brief interventions were defined as person-to-person discussions on alcohol, with between 1 and 4 sessions and a total of 2 hours intervention time. ABIs which were delivered in groups or via a computer were excluded as were those which included participants with complex health problems where it is difficult to generalise findings to the general population.

The primary outcome measure was a quantitative continuous measure of total alcohol consumption, reported as the standardised mean difference between ABI group and control group measured at follow-up. The authors also examined how ABIs influenced the frequency of alcohol consumption.

Different types of setting, provider and content were examined and these are shown (along with the number of studies in each category) in the Results section below.

A multi-level meta-analysis method was used, which allowed the authors to include a number of different effect sizes from individual studies (i.e. amount of alcohol consumed per unit of time and/or amount of alcohol consumed per drinking occasion) rather than just trying to selecting one comparable effect size for each study).

Results

Study characteristics

50 studies were included in the analyses, with 29,891 individuals contributing data. 45% of studies were conducted in the USA and 22% in the UK.

The percentage of studies which examined alcohol brief interventions with different types of content, providers and settings are shown below:

Intervention content:

  1. Motivational interviewing (MI) (48%)
  2. Enhanced motivational interviewing (MI+) (40%)
  3. Brief advice approaches (24%)

Intervention providers:

  1. Counselors (44%)
  2. General practitioners (22%)
  3. Nurses (18%)
  4. Different providers (12%)
  5. Peer-delivered (4%)

Setting of intervention delivery:

  1. Primary or ambulatory care in clinical settings such as outpatient services (38%)
  2. A&E services (20%)
  3. University (20%)
  4. Community-based delivery (12%)
  5. Hospital inpatient services (10%)

Quality of the evidence

71% of studies were classified as having a low risk of bias regarding randomisation and allocation concealment strategies. However, the method of allocation concealment was unclear in most of the studies. An intention-to-treat analysis was conducted in 47% of the studies and loss to follow-up was assessed in 80% of studies.

The overall impact of ABIs as compared with control conditions

ABIs reduced alcohol consumption by -0.15 SDs (95% confidence interval (CI) = -0.20 to -0.10) a result the authors describe as a ‘small but statistically significant effect’. However, the extent to which this is clinically meaningful is less clear.

Note: The authors present the effect sizes as SDs because they have summarised their data as standardised mean differences. This method is used when included studies all assess the same outcome, but measure it in a variety of ways. Although this makes sense statistically, it does make understanding how important these effects are clinically a little more difficult.

The authors found that this effect persisted after controlling for covariates and when conducting sensitivity analyses. The studies included in this analysis were found to have a small to medium level of heterogeneity (I2 = 37%; this figure is the percentage of variation between trials which is due to actual variation between studies as opposed to variation due to chance. A small I2 value means that the majority of the differences observed between studies was due to chance).

ABIs reduced frequency of alcohol consumed by a similar amount (-0.15 SDs, 95% CI = -0.20 to -0.11).

Content

Splitting studies by ABI content didn’t reduce the heterogeneity between studies (I2 = 39%: no, or little change in this I2 value from when all studies are considered together (I2 = 37%) indicates that this categorisation by content does not adequately explain the heterogeneity between studies).

However, it did appear that all content types were effective at reducing amount of alcohol consumed, and there was some evidence that while brief advice is more effective than MI or MI+ for amount of alcohol consumed, brief advice did not appear to reduce the frequency of consumption while MI and MI+ did.

Providers

Splitting studies by ABI provider was not found to reduce the heterogeneity between studies (I2 = 34%).

ABIs delivered by a range of different providers or by peers were not found to be effective at reducing amount consumed or frequency of consumption (although it’s important to note that very few studies were included in these categories).

There was evidence that interventions delivered by counselors, physicians and nurses were effective, with those delivered by nurses the most effective (-0.23 SDs amount consumed, 95% CI = -0.33 to -0.13).

Setting

Splitting studies by ABI setting didn’t reduce the heterogeneity between studies (I2 = 34%).

There was no evidence that ABIs delivered in hospital inpatient services and in community settings were effective in reducing either amount or frequency of alcohol consumed.

Interventions delivered in A&E, ambulatory care settings and in universities were found to reduce alcohol both amount and frequency of alcohol consumed.

This review suggests that alcohol brief interventions have a ‘small but statistically significant effect’, but it's unclear whether or not this is clinically meaningful.

This review suggests that alcohol brief interventions have a ‘small but statistically significant effect’, but it’s unclear whether or not this is clinically meaningful.

Conclusions

The authors conclude that their study provides:

important new evidence on how the effectiveness of brief alcohol interventions differs by setting, provider and content.

While this analysis does show that ABIs reduce amount of alcohol consumed and frequency of consumption, the size of this effect is small. It will be important to determine to what extent this is a clinically meaningful effect.

Although the authors claim that their findings suggest that the “provider of interventions may matter” (with nurses providing the best results) there is only weak evidence for this. As the categorisation of studies by provider (and setting and content for that matter) didn’t really have any impact on the heterogeneity (as measured by I2) between studies, there is little evidence that the effectiveness of ABIs differed meaningfully across providers.

Interventions delivered by nurses appeared the most effective, although further work is needed to confirm this finding.

Interventions delivered by nurses appeared the most effective, although further work is needed to confirm this finding.

Strengths and limitations

Strengths

As the authors used a multi-level meta-analysis, they were able to include all relevant outcomes into their analysis, rather than just picking one outcome (and consequently having to exclude studies which did not assess this outcome). This is also likely to have reduced study level heterogeneity.

Limitations

As the authors were interested in the difference in effectiveness of a range of different ABI settings, providers and contents, the number of studies included within each of these categories was small. This makes drawing firm conclusions regarding the effectiveness of particular forms of ABIs difficult.

Implications

Given that there is little evidence to suggest that the effectiveness of alcohol brief interventions differs meaningfully according to setting, provider or content, the authors do note that this indicates that resources should be allocated to those settings, providers and contents where ABIs are likely to be most cost-effective and feasible.

For example, A&E may not be the best setting for ABIs given the lack of privacy, the brevity of the visit and the fact that the patient is likely to be suffering from a severe injury at the time.

Nurses are likely to be well placed to provide ABIs given their repeated contact with patients, although appropriate training should be provided to nurses so that they can embed these practices into their care.

Focusing on interventions that are feasible and cost-effective seems like the biggest practical advice from this evidence.

Focusing on interventions that are feasible and cost-effective seems like the biggest practical advice from this evidence.

Links

Primary paper

Platt L, Melendez-Torres GJ, O’Donnell A, Bradley J, Newbury-Birch D, Kaner E, et al. (2016) How effective are brief interventions in reducing alcohol consumption: do the setting, practitioner group and content matter? Findings from a systematic review and metaregression analysis. BMJ Open. 2016;6(8).

Other references

HM Government (2012) The Government’s Alcohol Strategy PDF. CM 8336, March 2012.

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

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

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

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

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

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

Methods

Identification of included studies

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

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

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

Results

Characteristics of included studies

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

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

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

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

Main findings

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

Reducing secondhand smoke exposure

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

Other health outcomes

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

Tobacco consumption and smoking prevalence

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

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

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

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

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

Quality of the evidence

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

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

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

Conclusion

Overall, this review finds evidence of smoking bans on:

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

Limitations

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

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

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

Discussion

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

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

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

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

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

Links

Primary paper

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

Other references

Etter M, Etter JF. (2007) Acceptability and impact of a partial smoking ban in a psychiatric hospital.. Preventive Medicine 2007;44(1):649. [PubMed abstract]

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Rates of restarting smoking after giving birth

by Olivia Maynard @OliviaMaynard17

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

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

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

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

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

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

Methods 

Selection of included studies

Studies were included if:

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

Primary outcome measure

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

Secondary outcome measure

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

Results

Study characteristics

27 studies were included in the review. Of these:

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

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

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

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

Risk of bias assessment  

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

Primary analysis: proportion re-starting smoking

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

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

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

Secondary analysis: proportion smoking

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

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

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

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

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

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

Conclusion

The authors conclude that:

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

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

Limitations  

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

Discussion  

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

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

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

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

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

Links

Primary paper

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

Photo credits

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

New alcohol guidelines: what you need to know

by Olivia Maynard @OliviaMaynard17

This blog originally appeared on the Mental Elf site on 9th Febraury 2016.

Last month the UK Chief Medical Officers (CMOs) published new guidelines for alcohol consumption. These are the first new guidelines since 1995 and are based on the latest evidence on the effects of alcohol consumption on health.

The guidelines provide recommendations for weekly drinking limits, single drinking episodes and recommendations for pregnant women, drawing heavily on the Sheffield Alcohol Policy Model, which uses the most up to date evidence on both the short- and long-term risks of alcohol.

What are the new guidelines?

Guidelines for weekly drinking

For the new weekly drinking guidelines, the CMOs recommend that:

  • It’s safest for both men and women to not regularly drink more than 14 units of alcohol per week;
  • It’s best to spread these units over 3 days or more;
  • Having several drink-free days each week is a good way of cutting down the amount you drink;
  • The risk of developing a range of illnesses increases with any amount you drink on a regular basis.

There are two key changes here from the guidelines we’ve been used to:

First, there’s no difference in recommendations for men and women. This is because there is increasing evidence that although women are more at risk from the long-term health effects of alcohol, men are more at risk from the short-term effects of drinking (they’re more likely to expose themselves to risky situations while drinking).

Second, there is an explicit statement that there is no ‘safe’ level of alcohol consumption. Over the past 21 years, the link between alcohol and cancer has become much clearer. For example, we now know that while the lifetime risk ofbreast cancer is 11% among female non-drinkers, the lifetime risk for a woman drinking within the new guidelines is 13%. A woman drinking over 35 units a week increases her risk of breast cancer to 21%.

In their report, the CMOs are also at pains to point out that the evidence supporting alcohol’s protective effects on ischaemic heart disease is now weaker than in 1995. Furthermore, any potential protective effect of alcohol is mainly observed among older women at very low levels of consumption. Previously some have used this to claim that drinking is better than abstinence – the new guidelines refute this.

The new guidance says it's safest for men and women to drink no more than 14 units each week.

The new guidance says it’s safest for men and women to drink no more than 14 units each week.

Guidelines for single drinking episodes

The new guidelines are the first to provide guidance on drinking on single occasions, recommending drinkers:

  • Limit the total amount consumed on any occasion;
  • Drink slowly, with food and alternating with water;
  • Avoid risky places and activities and ensure they have a safe method of getting home.

These new recommendations reflect the fact that many alcohol consumers may drink heavily on occasion and provide guidance to avoid the risk of injury and ischaemic heart disease which increase with heavy drinking.

Heavy drinking episodes are linked with a higher risk of injury.

Heavy drinking episodes are linked with a higher risk of injury.

Guidelines for drinking during pregnancy

The new guidelines suggest that:

  • The safest approach for pregnant women is not to drink alcohol at all, to keep risks to the baby to a minimum.
  • Drinking during pregnancy can lead to long-term harm to the baby, with the risk increasing with the more alcohol consumed;
  • The risk of harm to the baby is likely to be low if a woman has drunk only small amounts of alcohol before she knew she was pregnant or during pregnancy.

The CMOs report that while the evidence on the effects of low alcohol consumption during pregnancy remains ‘elusive’, taking a precautionary approach is most prudent when it comes to a baby’s long term health. However, given the elusive evidence, the guidance is also careful to note that mothers should not be too concerned if they have drunk early in their pregnancy, as this kind of stress may be even more harmful to the developing baby.

Pregnant women are advised not to drink alcohol at all.

Pregnant women are advised not to drink alcohol at all.

A note on risk

These recommendations are based on a level of alcohol consumption which confers a 1% lifetime risk of death from alcohol. Their purpose is therefore tominimise risk from alcohol, rather than eliminate it. Indeed, the guidelines explicitly state that there is no safe level of alcohol consumption. So what does a 1% lifetime risk mean and how does this compare to other health behaviours?

Lifetime mean risks

  • Being killed through BASE jumping (0.3%);
  • Being killed in a car accident (0.4%);
  • Being diagnosed with bowel cancer from eating three rashers of bacon every day (1%);
  • Dying from an alcohol related disease, if drinking within the new guidelines (1%);
  • Smokers dying from a smoking related disease (50%, although new estimates suggest that this may be as high as 67%).

Put in the context of smoking, the risk posed by drinking within the new guidelines seems tiny (although it’s still more risky than BASE jumping!) However, it’s important to note that alcohol consumption and smoking are quite different. Alcohol consumption is perceived as normal in our society and is much more prevalent than cigarette smoking. By contrast, the acceptability of smoking is reducing and unlike social alcohol consumers, smokers are constantly being told to quit smoking.

This 1% risk level is that which is deemed ‘acceptable’ by the CMO. However, everyone will have a different ‘acceptable’ level of risk, which depends in part on how much pleasure is obtained from drinking. While some will think that increasing their risk of death from alcohol to 5% is acceptable, others will not accept any risk and will use these guidelines to cut out alcohol completely.

Criticisms of the new guidelines

As expected, the ‘nanny state’ criticism has been bandied around in pubs, on message boards and on social media since the publication of these guidelines. Others claim that these new guidelines are simply scaremongering. However, it’s important to remember that these are recommendations, not rules.

The last word must go to CMO Professor Dame Sally Davies, who addressed this criticism by saying that:

What we are aiming to do with these guidelines is give the public the latest and most up- to-date scientific information so that they can make informed decisions about their own drinking and the level of risk they are prepared to take.

What do you think? Are these new guidelines useful? Will they help reduce alcohol related harm?

What do you think? Are these new guidelines useful? Will they help reduce alcohol related harm?

Links

Primary paper

Department of Health (2016) Health risks from alcohol: new guidelines. Open Consultation, 8 Jan 2016 (Consultation closes on 1 April 2016)

Department of Health (2016). Alcohol Guidelines Review – Report from the Guidelines development group to the UK Chief Medical Officers.

Other references

Centre for Public Health (2016). CMO Alcohol Guidelines Review – A summary of the evidence of the health and social impacts of alcohol consumption. Liverpool John Moores University.

Centre for Public Health (2016). CMO Alcohol Guidelines Review – Mapping systematic review level evidence. Liverpool John Moores University.

Department of Health (1995). Sensible drinking: Report of an inter-departmental working group.

Photo credits

 

SMS text messaging interventions for healthy behaviour change

by Olivia Maynard @OliviaMaynard17

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

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There’s a lot to like about text messaging (Short Message Service: SMS) interventions for behaviour change: they can deliver cost-effective, brief, real-time and tailored messages at moments when individuals need them most. They reduce time demands on both the individual and health care practitioners, maintain the privacy of the individual and what’s more, given that the majority of the world’s population own a mobile phone, text messaging interventions can be delivered at a global scale.

Given these advantages, there’s been a great deal of research on the effectiveness of SMS interventions for health behaviours, finding mixed results. Last month, I blogged about a meta-analysis which found weak evidence for the efficacy of SMS interventions for smoking cessation. However, smoking cessation is a complex health behaviour and recent reviews have found that SMS interventions are more effective for more simple health behaviours such as medicine adherence and attending medical appointments.

Another recent meta-analysis by Orr and King (2015) published in Health Psychology Review was the first to examine the overall effectiveness of SMS interventions to enhance healthy behaviour, rather than focus on any one health behaviour (i.e. smoking cessation). Similar to the meta-analysis I blogged about last month, the authors also aimed to identify which SMS features have the biggest impact on intervention effectiveness.

Mobile phones are now so ubiquitous that they are a great tool to deliver interventions globally.

Methods

The authors searched for randomised controlled trials (RCTs) which compared SMS interventions targeting health behaviour change to a non-SMS control, which did not attempt to change behaviour (i.e. RCTs which compared two active treatments were not included).

The authors examined the influence of six moderators on the effectiveness of SMS interventions:

  1. SMS dose (i.e. the frequency of the messages: multiple per day, weekly, once only etc);
  2. SMS message tailoring (i.e. standardised, tailored, personalised);
  3. SMS directionality between researcher and participant (i.e. one-way, two-way);
  4. Category of health behaviour targeted (i.e. unhealthy behaviour modification, chronic disease management, medication adherence, appointment attendance, disease or pregnancy preventive behaviours);
  5. Complexity of these behaviours (i.e. complex: chronic disease management, disease-related medication adherence, unhealthy behaviour modification; simple: appointment attendance, non-disease-related medication adherence, preventive behaviour);
  6. Participants’ mean age.

Results

Thirty eight studies met the criteria for inclusion in this meta-analysis.

The meta-analysis found that there was an overall (pooled) positive effect of SMS interventions on healthy behaviour (g = 0.291, 95% CI = 0.219 to 0.363, p < 0.001). The heterogeneity between studies was low (I2 = 38.619, p = 0.009­).

Planned sub-group analyses explored the impact of the six moderators on health behaviour change. There was little evidence that any of the six moderators impacted SMS intervention efficacy. However, when the authors regrouped the studies (i.e. unplanned analyses) for the tailoring, dose and complexity moderators, only SMS dose was found to impact SMS efficacy, with studies using multiple messages per day being more effective than those with reduced frequency.

The effect size for SMS interventions was small, but given that this is a cheap and simple intervention to deliver, it may be worthwhile.

Strengths

The quality of the evidence in the 38 studies was judged to be relatively high, with all but three of the studies assessed as having high to moderate methodological quality. However, the authors judged that the risk of incomplete data was high in 40% of studies, despite efforts to contact the authors of the original studies for further information.

Further analyses of the data found that publication bias was not a threat to the validity of the estimated effect of SMS interventions for healthy behaviour.

Weaknesses

The majority of included studies relied on self-report outcome measures, rather than actual behaviour, which is likely to have increased the observed effects of the studies. Future studies should use objective outcome measures.

The observation that more frequent text messages are more effective than less frequent messages was only found after regrouping the studies and running multiple unplanned comparisons between groups. This finding should therefore be treated with caution.

The authors only included studies which compared SMS intervention to no intervention at all. These findings therefore tell us nothing about how SMS interventions compare to other established interventions, such as verbal or other written reminders and messages.

Very few of the studies included in this meta-analysis were grounded in any health behaviour theory. The authors suggest that future research should examine the impact of established theoretical components on health behaviour change outcomes.

This study does not provide reliable evidence that more frequent text messages are more effective than less frequent messages.

Discussion

Using strict inclusion criteria for studies, this meta-analysis found that SMS interventions have a positive, albeit small, effect on healthy behaviour change. There was little evidence that moderators such as tailoring, directionality, health behaviour category or complexity or participant age influence efficacy. There was some evidence that higher SMS dose might increase efficacy.

These findings echo those in a recent meta-analysis of studies exploring the effectiveness of SMS interventions for smoking cessation where no moderator was found to be more effective than any other at increasing quit success and only a small positive effect of SMS intervention was observed.

Although this and previous meta-analyses have found only modest benefits of SMS interventions over control, given the low cost of delivery of SMS interventions and the potential to target large numbers of individuals, the public health benefits are still considerable and future research should continue to examine the efficacy of these interventions.

Despite the small effect sizes, SMS text messages remain a potentially effective intervention that can work on a truly global scale.

Links

Primary paper

Orr JA, King RJ. (2015) Mobile phone SMS messages can enhance healthy behaviour: a meta-analysis of randomised controlled trialsHealth psychology review (just-accepted), 1-36.

Other references

Maynard O. (2015) SMS texting to quit smoking: a meta-analysis of text messaging interventions for smoking cessation. The Mental Elf, 26 Aug 2015.

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

 

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]

 

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:

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

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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]

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