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Does schizophrenia influence cannabis use? How to report the influence of disease liability on outcomes in Mendelian randomization studies

The recent Nature Neuroscience paper by Pasman et al entitled “GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal influence of schizophrenia” (see below) provides important and novel insights into the aetiology of cannabis use and its relationship with mental health. However – in its title and elsewhere – it subtly misrepresents what the Mendelian randomization (MR) [1] analyses it presents actually show. MR analyses are increasingly being reported as demonstrating the effect of a disease (in this case schizophrenia) on the outcome, through using genome wide significant variants associated with risk of the disease on the outcome (which can be a behavior, such as cannabis smoking in the present paper, a measured trait or a second disease).

MR analyses are often carried out using summary data, where the exposure and outcome GWAS come from separate samples. In such analyses interpretation is not to apparent effects of the disease itself, but to the phenotypic effects of genetic liability to that disease. Typically, only a tiny proportion of participants in the outcome GWAS datasets will actually have experienced the disease – in this case particularly so given the low participation rate of people with schizophrenia in most studies in the general population. Indeed, MR studies can be carried out in datasets where there are no individuals with the outcome (e.g. datasets collected amongst an age group in whom the outcome will have occurred very rarely, if ever). Such analysis may reveal apparent, but impossible, effects of the disease on outcome phenotypes. To use MR analyses to investigate the causal effect of a disease on outcomes would require individual-level data with recorded disease events and subsequent follow-up. Analytical approaches to such data have, as yet, not been published.

The widespread misrepresentations of such MR studies have important implications, not just in terms of how the results are interpreted, but also how they are applied. One valuable contribution of MR studies is that they can identify modifiable exposures that can be the target of interventions. If it is recognized that what is being shown is an effect of liability to disease on an outcome, then interventions targeting the mechanisms of this liability would have benefits even in individuals who are unlikely to go on to develop the disease, including those at low risk of the disease for other reasons. For example, targeting breast cancer liability may have benefits in men if this liability influenced diseases that are common in men. If, however, it is the disease itself which has the effect, then the interventions would be targeted at those likely to develop disease: only women, in the case of breast cancer liability. It may be that schizophrenia does indeed lead to cannabis use, but the analyses reported by Pasman et al show only that liability to schizophrenia leads to cannabis use.

The point is a subtle one – we have both used similar language in the past in articles reporting MR analyses on which we are authors. Indeed, one of us (MM) was an author on the Pasman et al paper (and contributed principally to the MR analyses and their interpretation) but failed to suggest the correct phrasing.  Fortunately, the title and discussion will be changed to address this problem so that the enduring version of the paper captures this importance nuance (unfortunately, the original headline has already been repeated elsewhere [2]). However, it is a widespread and underappreciated point of interpretation in MR studies, and we feel that this presents a useful opportunity to highlight it. It also illustrates that methodologies, and the interpretation of the results they generate, continue to evolve, illustrating the need to interpret past work (including our own!) through the lens of current approaches.

[1] Davey Smith G, Ebrahim S. ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease?  Int J Epidemiology 2003;32:1-22.

[2] Andrae LC. Cannabis use and schizophrenia: Chicken or egg?  Sci Transl Med 2018;10:eaav0342.

The House of Commons Science and Technology Committee reports on e-cigarettes

Written by Jasmine Khouja, PhD Student, Tobacco and Alcohol Research Group

Today sees the publication of a report on electronic cigarettes (e-cigarettes) by the House of Commons Science and Technology Committee. This compiles evidence from over 100 pieces of written submissions and five oral sessions, and highlights key issues around reducing harm, promoting smoking cessation and effectively regulating e-cigarettes. Since the report is quite long, we’ve tried to extract the main messages.

The report takes a relatively positive stance on e-cigarettes, encouraging use for smoking cessation and suggesting a more accepting approach to e-cigarettes in public spaces. This is in contrast to other countries, such as Australia, where a ban is in place due to the lack of long-term research on the health impact of using e-cigarettes.

Reducing harm

The general consensus from a variety of sources is that e-cigarettes are less harmful than combustible cigarettes. However, a frequent theme is that this does not mean that e-cigarettes are ‘safe’, and the report is careful to emphasise that e-cigarettes are not completely harmless. The relative harm of heat-not-burn tobacco products compared to combustible cigarettes is less clear. There is a lack of independent evidence as the majority of data on the safety and emissions of these product has come from Philip Morris, a major tobacco company.

The long-term effects of using e-cigarettes are currently unknown. It is difficult to assess the comparative harm of e-cigarettes without also measuring the effects of prior smoking, since there are very few long-term e-cigarette users who have never smoked. Exposure to second-hand e-cigarette vapour has been similarly difficult to assess, but since potentially harmful compounds emitted are present only at very low levels second-hand vapour is unlikely to be harmful.

E-cigarettes have become a popular tool for quitting smoking and an estimated 16,000 to 22,000 people who would not have quit using alternative products or willpower alone have successfully quit each year by using e-cigarettes. Although these figures are promising, there is a lack of high-quality evidence from randomised control trials showing how effective e-cigarettes are when quitting smoking. Other evidence has been inconclusive due to the low quality of some studies.

Despite fears that e-cigarettes may act as a ‘gateway’ to smoking, current evidence does not show that using e-cigarettes causes people to start smoking. Although there is a link between e-cigarette use and subsequent smoking initiation, very few never smokers regularly use e-cigarettes, so any causal link would have a limited impact on smoking rates.

Smoking cessation

Providing e-cigarettes on prescription could encourage smokers to try e-cigarettes without barriers such as money as well as give them more confidence in the product being less harmful than cigarettes. The report concludes that e-cigarettes should be available to those in NHS mental health services given high rates of smoking in this group.

NHS England were unable to provide evidence for how they were addressing this issue. They were unable to provide a representative because there is no one individual responsible centrally with ‘oversight’ of e-cigarette policies across NHS mental health trusts. The report criticises this, stating it was concerning and that a position should be created as a matter of urgency.

E-cigarettes are generally prohibited in closed spaces such as workplaces, public transport and restaurants and vapers are usually encouraged to vape outside within designated ‘smoking’ areas. Since second-hand vapour is unlikely to be harmful, these policies may be more harmful than beneficial; frequently exposing vapers to cigarettes and cigarette smoke may increase the likelihood that they will relapse to smoking.


E-cigarettes are currently regulated under the Tobacco Products Directive (TPD; see our previous blog) if you want to learn more about these regulations). As part of this directive, the Medicines and Healthcare products Regulatory Agency must be notified before any e-cigarette or e-liquid can be sold in the UK.

Four key criticisms of the TPD were identified in the report: i) unnecessary limits on nicotine strength of refill liquids which may lead to failed quit attempts, ii) unnecessary tank size restrictions which may lead to failed quit attempts, iii) blocking advertising the relative harm-reduction of e-cigarettes which may discourage quit attempts, and iv) the ineffective notification scheme for e-cigarette ingredients which slows innovation.

Some TPD regulations are optional and give freedom to governments to be as restrictive as they feel necessary. Scotland has been more restrictive than England in their regulations by banning certain advertising of vapour products. Currently, health claims are banned from all media advertising of e-cigarettes without a medical license (of which none is currently available). The Advertising Standards Authority is currently reviewing the legislation on e-cigarette advertising and health claims and are considering allowing this in the future.

Unsurprisingly, there is uncertainty about the future regulation of e-cigarettes due to Brexit. Regulation of e-cigarettes may change after leaving the European Union and it is unclear what these changes may be or what potential impact increased flexibility in regulating e-cigarettes could have.


The report is comprehensive and raises some interesting questions particularly about the lack of NHS involvement in developing strategies for smoking cessation that utilise e-cigarettes. It will be interesting to see if the NHS responds to these criticisms by taking action. I am also interested to see what Brexit will mean for the regulation of e-cigarettes in the UK, given the criticisms of TPD regulations.

The full report can be accessed here: [The House of Commons Science and Technology Committee reports on e-cigarettes]


Can cognitive interventions change our perception from negative to positive, and might that be useful in treating depression?

By Sarah Peters

Have you ever walked away from a social interaction feeling uncomfortable or anxious? Maybe you felt the person you were talking to disliked you, or perhaps they said something negative and it was all you could remember about the interaction. We all occasionally focus on the negative rather than the positive, and sometimes ruminate over a negative event, but a consistent tendency to perceive even ambiguous or neutral words, faces, and interactions as negative (a negative bias), may play a causal role in the onset and rate of relapse in depression.

A growing field of psychological interventions known as cognitive bias modification (CBM) propose that by modifying these negative biases it may be possible to intervene prior to the onset of depression, or prevent the risk of subsequent depressive episodes for individuals in remission. Given that worldwide access to proven psychological and pharmacological treatments for mood disorders is limited, and that in countries like the UK public treatment for depression is plagued by long waiting lists, high costs, side effects, and low overall response rates, there is a need for effective treatments which are inexpensive, and both quick and easy to deliver. We thought that CBM might hold promise here, so we ran a proof of principle trial for a newly developed CBM intervention that shifts the interpretation of faces from negative to positive (a demonstration version of the training procedure can be seen here). Proof of principle trials test an intervention in a non-patient sample, which is important to help us understand a technique’s potential prior to testing it in a clinical population – we need to have a good idea that an intervention is going to work before we give it to people seeking treatment!

In this study, we had two specific aims. Firstly, we aimed to replicate previous findings to confirm that this task could indeed shift the emotional interpretation of faces. Secondly, we were interested in whether this shift in interpretation would impact on clinically-relevant outcomes: a) self-reported mood symptoms, and b) a battery of mood-relevant cognitive tasks. Among these were self-report questionnaires of depressive and anxious symptoms, the interpretation of ambiguous scenarios, and an inventory of daily stressful events (e.g., did you “wait too long in a queue,” and “how much stress did this cause you on a scale of 0 to 7”). The cognitive tasks included a dot probe task to measure selective attention towards negative (versus neutral) emotional words, a motivation for rewards task which has been shown to measure anhedonia (the loss of pleasure in previously enjoyed activities), and a measure of stress-reactivity (whereby individuals complete a simple task under two conditions: safe and under stress). This final task was included because it is thought that the negative biases we were interested in modifying are more pronounced when an individual is under stress.

We collected all of our self-report and cognitive measures at baseline (prior to CBM), after which participants underwent eight sessions (in one week) of either CBM or a control version of the task (which does not shift emotional interpretation). We then collected all of our measures again (after CBM). In order to be as sure of our results as possible, there were a number of critical study design features we used. Our design, hypotheses, and statistical analyses were pre-registered online prior to collecting data (this meant that we couldn’t fish around in our data until we found something promising, then re-write our hypotheses to make that result seem stronger). We also powered our study to be able to detect an effect of our CBM procedure. This meant running a statistical calculation to ensure we had enough participants to be convinced by any significant findings, and their potential to be clinically useful. This told us we needed 104 individuals split evenly between groups. Finally, our study was randomised (participants were randomly allocated to the intervention group or the control group), controlled (one group underwent an identical “placebo” procedure), and double-blind (only an individual who played no role in recruitment or participant contact knew which group any one participant was in).

So, what did we actually find? While the intervention successfully shifted the interpretation of facial expressions (from negative to positive), there was only inconclusive evidence of improved mood and the CBM procedure failed to impact most measures. There was some evidence in our predicted direction that daily stressful events were perceived as less stressful by those in the intervention group post-CBM, and weaker evidence for decreased anhedonia in the intervention group. In an exploratory analysis, we also found some evidence that results in the stress-reactivity task were moderated by baseline anxiety scores – for this task, the effects of CBM were only seen in individuals who had higher baseline anxiety scores. However, exploratory findings like this need to be treated with caution.

Therefore, as is often the case in scientific research, our results were not entirely clear. However, there are a few limitations and directions for future research that might explain and help us to interpret our findings. Our proof of principle study only considered effects in healthy individuals. Although these individuals were clearly amenable to training, and may indeed have symptoms of depression or anxiety without a clinical diagnosis, our observation that more anxious individuals appeared to be more affected by the intervention warrants research in clinical populations. In fact, a reasonable parallel to the effects observed in this study may be working memory training, which does not transfer well to other cognitive operations in healthy samples, but shows promise as a tool for general cognitive improvement in impaired populations.

Future research is also needed to disambiguate the tentative self-report stress and cognitive anhedonia effects observed here. One possibility, for example, is that the 104 participants we recruited were not enough to detect an effect of transference from CBM training to other measures (the size of which is unknown). Given the complexity of any mechanism through which a computerised task could shift the perception of faces and then influence behaviour, it is likely that a larger sample is necessary. While it could be argued that if such a large group of individuals is warranted to detect an effect, that effect is likely too small to be clinically useful, we would argue that even tiny effects can indeed be meaningful (e.g., cancer intervention studies often identify very small effects which can have a meaningful impact at a population level).

Another explanation for our small effects is that while one week was long enough to induce a change in bias, it may not have been long enough to observe corresponding changes in mood. For instance, positive interpretation alone may not be enough – it may be that individuals need to go out into the world and use this new framework to have personal, positive experiences that gradually improve mood, and this process may take longer than one week.

Overall, this CBM procedure may have limited impact on clinically-relevant symptoms. However, the small effects observed still warrant future study in larger and clinical samples. Given the large impact and cost of mood disorders on the one hand, and the relatively low cost of providing CBM training on the other, clarifying whether even small effects exist is likely worthwhile. Even if this procedure fails to result in clinical improvement, documenting and understanding the different steps in going from basic scientific experimentation to intervening in clinical samples is crucial for both the scientific field and the general public to know. The current study is part of a body of research which should encourage all individuals who are directly or indirectly impacted by depression or other mood disorders. Novel approaches towards understanding, preventing, and treating these disorders are constantly being investigated, meaning that we can be hopeful for a reduction in the devastating impact they currently have in the not so distant future.

Read the published study here

Sarah Peters can be contacted via email at: 

Supervised injectable heroin for refractory heroin addiction

by Eleanor Kennedy @Nelllor_

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

Opioid use is the number one reason for seeking substance misuse treatment across 30 European countries. Opioids are drugs derived from the opium poppy and these include the drug heroin (EMCDDA, 2015).

Heroin dependence has negative consequences for both the individual and society as persistent use of the drug is associated with poor health, criminal offences and damaged personal relationships (Ferri et al, 2011). Drug-free treatments and substitution treatments are the two interventions used to overcome heroin dependence.

Methadone is the most common substitution treatment in the EU, however, heroin prescribing is well established in Denmark, Germany and The Netherlands, an option in the UK and Spain, and currently under investigation in Belgium and Luxembourg (EMCDDA, 2015).

A recent systematic review and meta-analysis aims to compare supervised injectable heroin (SIH) as a treatment for heroin users who have not responded to more standard treatments such as methadone maintenance treatment (MMT) or residential rehabilitation (Strang et al, 2015).

NICE guidance recommends the use of methadone or buprenorphine as the first-line treatment in opioid detoxification.


Electronic databases (PubMed, Web of Science and Scopus) were searched for studies that reported on the effects of SIH treatment in participants with heroin-dependence unresponsive to standard treatments.

The studies had to have opiate use, retention in treatment, mortality and side-effects as outcome variables.

Studies were excluded if they were methodological papers, assessed unsupervised heroin treatment provision, focused on policy aspects, cost effectiveness, community perspectives or patient satisfaction.

The meta-analysis focussed on Mantel-Haenszel random effects pooled risk ratios for SIH treatment compared to the comparison groups.


There were a total of six papers included in the main review and meta-analysis. These studies were based in Switzerland, The Netherlands, Spain, Germany, Canada and England.

All studies explored SIH compared to MMT (oral methadone) in chronic heroin-dependent individuals who have repeatedly failed in orthodox treatment.

The results of rate of retention and the use of illicit heroin following treatment are shown in Table 1. The rates of retention varied across studies, with only one study reporting a lower rate of retention for the SIH group (Van den Brink et al, 2003). The statistical evidence indicated a lower rate of illicit heroin use in individuals receiving SIH treatment in all six studies.

Table 1: Retention in treatment and use of illicit heroin results

Study Retention in treatment Use of illicit heroin
Perneger et al, 1998 SIH 93% vs MMT 92% p = 0.002
Van den Brink et al, 2003 SIH 72% vs MMT 85% P = 0.002
March et al, 2006 SIH 74% vs MMT 68% P = 0.02
Haasen et al, 2007 SIH 67% vs MMT 40% P < 0.001
Oviedo-Joekes et al, 2009 SIH 88% vs MMT 54% P = 0.004
Strang et al, 2010 SIH 88% vs MMT 69% P < 0.0001


A meta-analysis was conducted to explore retention in treatment, mortality outcome and side-effects.

  • Retention in treatment was significantly better for the SIH than for the MMT treatment groups as demonstrated by four studies; RR = 1.37, 95% CI = 1.03 to 1.83
  • Mortality was lower in the SIH than in the MMT treatment groups but this was not significant; RR=0.65, 95% CI = 0.25 to 1.69
  • There was a higher risk of side effects in the SIH compared to the MMT treatment groups based on analysis of five studies; RR = 4.99, 95% CI = 1.66 to 14.99

This review provides good evidence that heroin-assisted treatment works for a small group of patients with refractory heroin dependence.

Strengths and limitations

All of the included studies were randomised controlled trials comparing traditional oral MMT to SIH in participants with chronic heroin-dependence who have not been successfully treated. The review followed PRISMA guidelines and was inclusive of all languages and publication dates, so the likelihood of important papers being excluded is minimal.

In this review the authors focussed on supervised administration of heroin only, which contrasts with a 2011 Cochrane Review that also included studies where heroin was prescribed for take-home administration (Ferri et al, 2011). By restricting the inclusion criteria, stronger conclusions can be made about the efficacy of this type of treatment which may guide the introduction of new interventions. Additionally the authors’ address several key misgivings about SIH, which further supports the argument that SIH is an effective treatment for treatment-resistant heroin dependence. For example, the concern that SIH may undermine other existing treatments is countered by the difficulty in recruitment experienced by many of the six trials under review.

There are some limitations, e.g. the safety of injectable diamorphine requires further research as the instances of sudden-onset respiratory depression is at a rate of about 1 in 6,000 injections.

The supervision and administration of SIH makes it more expensive than oral forms of opioid maintenance treatment.


The authors concluded that:

Based on the evidence that has been accumulated through these clinical trials, heroin-prescribing, as a part of highly regulated regimen, is a feasible and effective treatment for a particularly difficult-to-treat group of heroin dependent patients.

The importance of supervision during administration is emphasised throughout the review. As mentioned above, all of the participants engaged in SIH had previously repeatedly failed in orthodox treatment, however, the evidence supports SIH as a treatment option for these individuals.

Will this systematic review and meta-analysis be sufficient for policy makers to start recommending supervised injectable heroin for heroin users who have not responded to other standard treatments?


Primary paper

Strang J, Groshkova T, Uchtenhagen A. et al. (2015) Heroin on trial: systematic review and meta-analysis of randomised trials of diamorphine-prescribing as treatment for refractory heroin addictionBr. J. Psychiatry 2015;207:5-14. doi:10.1192/bjp.bp.114.149195.

Other references

EMCDDA (2015) European Monitoring Centre for Drugs and Drug Addiction. 2015. Available at:

Ferri M, Davoli M, Perucci CA. Heroin Maintenance for chronic heroin-dependent Individuals. Cochrane Database of Systematic Reviews 2011, Issue 12. Art. No .: CD003410. DOI: 10.1002 / 14651858.CD003410.pub4.

Van den Brink W, Hendriks VM, Blanken P, Koeter MWJ, van Zwieten BJ, van Ree JM. (2003) Medical prescription of heroin to treatment resistant heroin addicts: two randomised controlled trialsBMJ 2003;327(August):310. doi:10.1136/bmj.327.7410.310.

Perneger T V, Giner F, del Rio M, Mino A. (1998) Randomised trial of heroin maintenance programme for addicts who fail in conventional drug treatmentsBMJ 1998;317(July):13-18. doi:10.1136/bmj.317.7150.13.

March JC, Oviedo-Joekes E, Perea-Milla E, Carrasco F. (2006) Controlled trial of prescribed heroin in the treatment of opioid addiction. J. Subst. Abuse Treat. 2006;31:203-211. doi:10.1016/j.jsat.2006.04.007. [PubMed abstract]

Haasen C, Verthein U, Degkwitz P, Berger J, Krausz M, Naber D. (2007) Heroin-assisted treatment for opioid dependence: Randomised controlled  trialBr. J. Psychiatry 2007;191:55-62. doi:10.1192/bjp.bp.106.026112.

Oviedo-Joekes E, Brissette S, Marsh DC, et al. (2009) Diacetylmorphine versus methadone for the treatment of opioid addiction. N. Engl. J. Med. 2009;361:777-786. doi:10.1056/NEJMoa0810635. [Abstract]

Strang J, Metrebian N, Lintzeris N, et al. (2010) Supervised injectable heroin or injectable methadone versus optimised oral methadone as treatment for chronic heroin addicts in England after persistent failure in orthodox treatment (RIOTT): a randomised trial. Lancet 2010;375(9729):1885-1895. doi:10.1016/S0140-6736(10)60349-2. [Abstract] [Watch Prof John Strang talk about the RIOTT trial]

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Are changes in routine health behaviours the missing link between bereavement and poor physical and mental health?

by Olivia Maynard @OliviaMaynard17 

This blog originally appeared on the Mental Elf site on 6th July 2015.

While bereavement can occur at any point during the lifespan, it is much more common later in life and is a risk factor for both poor physical and mental health.

While the Mental Elf has blogged previously about the impact of childhood bereavement on mental health, the impact of bereavement on the health of older people can be even more severe, given the ongoing declines in health as a result of their age.

Due to the high prevalence of bereavement in this age group, understanding how bereavement leads to declines in health among older adults is important. Behavioural changes may partially account for these negative health outcomes.

To examine this, Stahl and Schulz (2014) conducted the first systematic review to examine the relationship between bereavement and five routine health behaviours:

  1. Physical activity
  2. Nutrition
  3. Sleep
  4. Alcohol use
  5. Tobacco use

As well as one modifiable risk factor associated with health:

  1. Body weight

This review


The authors searched databases to find 34 studies which met the following criteria:

  • Quantitative and qualitative studies with either observational or intervention-based designs;
  • Older adults (aged over 50 years) who had experienced the death of a spouse;
  • Health behaviours were assessed.


Physical activity

18 studies: 4 cross-sectional, 8 prospective longitudinal, 5 post-bereavement longitudinal

  • Physical activity was assessed using self-report in all studies and physical activity ranged from social activities such as visiting friends to sports activities.
  • As a result, the evidence was mixed, with bereavement increasing the prevalence of social activities, but decreasing the prevalence of sports. Furthermore, while this pattern applied to bereaved women, bereavement decreased all forms of physical activity among men.


12 studies: 5 cross-sectional, 5 prospective longitudinal, 3 post bereavement longitudinal

  • Nutrition was assessed using a range of self-report questionnaires.
  • There was consistent evidence for a strong relationship between bereavement and increased nutritional risk, including worse nutrient intake and poor dietary behaviours, particularly within the first year of bereavement.

Sleep quality

9 studies: 1 cross-sectional, 0 prospective longitudinal, 8 post-bereavement longitudinal

  • Sleep quality was assessed using both self-report and objective measures such as electroencephalography and actigraphy (measurement of movement using small body sensors).
  • While the self-report studies consistently showed strong support for a link between bereavement and poorer sleep quality, no relationship was observed when sleep disturbance was measured objectively.

Alcohol consumption

7 studies: 2 cross-sectional, 3 prospective longitudinal, 2 post-bereavement longitudinal

  • There was moderate evidence (from longitudinal studies only) that bereavement was associated with increased self-reported alcohol consumption, for both men and women.

Tobacco use

7 studies: 2 cross-sectional, 4 prospective longitudinal, 1 post-bereavement longitudinal

  • Smoking status and frequency of tobacco use was assessed using self-report.
  • There was inconsistent evidence for the impact of bereavement on smoking behaviour, with bereavement reducing smoking frequency among current smokers (particularly men) but increasing the likelihood of smoking initiation among female non-smokers.

Weight status

6 studies: 1 cross-sectional, 5 prospective longitudinal, 0 post-bereavement longitudinal

  • There was consistent evidence across the studies that bereavement led to unintentional weight loss among both men and women.

nutrition, sleep quality and weight status

Limitations and directions for future research

  • The studies were heterogeneous and many did not report effect sizes, meaning that quantitatively assessing them (i.e. using meta-analysis) was not possible.
  • The majority of studies used self-report which may be affected by recall bias. For studies exploring sleep quality, only those which used self-report, rather than objective measures observed a negative effect of bereavement.
  • Few of the longitudinal studies reported the length of the bereavement period or when assessments were taken. Precise information on measurement intervals is important in determining when behavioural changes are most likely to occur and would be important for treatment.



This systematic review observed:

  • Strong support for changes in nutrition, sleep quality and weight status after bereavement
  • Moderate evidence for an impact on alcohol consumption
  • Mixed evidence for effects on physical activity and tobacco use

Although this review did not explore why bereavement led to these changes in health behaviours, the authors provide a number of explanations, which should be examined in future studies:

  • Loss of social support and the onset of depression and grief. This may reduce motivation to engage in health-promoting behaviours such as physical activity and also exacerbate or trigger physical symptoms such as poor sleep and headaches.
  • Changes in daily routines. Previously shared activities, such as exercise, food preparation or sleeping, may be difficult to maintain following spousal loss.

Crucially, however, this review is only one part of the puzzle. While it shows us that bereavement is associated with changes in health behaviours, we don’t know whether these changes mediate the relationship between bereavement and physical and mental health, the key outcome we’re interested in.

Given the known health burden associated with bereavement, it is critical that we further investigate this link and if this link were observed, interventions could target health behaviours to reduce the impact of bereavement on physical and mental health.

Future studies should explore whether specific health behaviours can reduce the negative impact that bereavement has on our physical and mental health.


Primary paper

Stahl ST, Schulz R. (2014) Changes in routine health behaviors following late-life bereavement: A systematic reviewJournal of Behavioral Medicine, 37, 736-755.

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Financial incentives for smoking cessation in pregnancy

By Meg Fluharty @MegEliz_

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


Smoking during pregnancy is thought to cause approximately 25,000 miscarriages per year in the United Kingdom (Health and Social Care Information Centre, 2010).

Additionally, smoking while pregnant is attributable to 4-7% of stillbirths (Flenady et al., 2011), and 3-5% of infant deaths (Gray et al., 2009) with these rates even higher in deprived areas, where remaining a smoker during pregnancy is more common (Gray et al., 2009).

In 2009, 24% of women attending antenatal appointments in Scotland were smokers (NHS, 2009). However only 1 in 10 reported using cessation services, and 3% were abstaining by four weeks (Tappin et al., 2010).

A recent Cochrane systematic review suggested financial incentives may be beneficial in helping pregnant women stop smoking, although it concluded that further evidence was needed (Chamberlain et al., 2013). Tappin et al (2015) investigated the effectiveness of shopping vouchers in addition to NHS Stop Smoking Services to aid quit attempts in pregnant women.

Nearly 1 in 4 women attending antenatal appointments in Scotland were smokers (NHS, 2009).


The authors conducted a randomised controlled trial of 609 pregnant smokers recruited from NHS Greater Glasgow and Clyde. Women were randomly allocated to routine smoking cessation care (control group) or to routine care and up to £400 in shopping vouchers if they engaged with services and successfully quit smoking (incentives group).

Routine care

Routine specialist pregnancy care involved an initial meeting to discuss quitting smoking and set a quit date. This was followed by 4 weekly telephone calls, and free nicotine replacement therapy for 10 weeks.

Incentives group

The incentives group received £50 in shopping vouchers for attending the initial meeting to set a quit date. If participants were smoke-free 4 weeks later, they would receive another £50 voucher, and if smoke-free at 12 weeks, participants received £100 in gift vouchers. Between 34-38 weeks gestation, women were once again asked smoking status, and those who had quit received a final £200 voucher. In all instances, smoking status was verified by a carbon monoxide breath test. 

Women who successfully quit smoking in this study received up to £400 in shopping vouchers.


  • More women successfully quit smoking in the incentives group (22.5%) than the routine care group (8.6%).
  • There was a higher quit rate at 4 weeks in the incentives group compared to the routine care group.
  • 12 months after quit date, there was still large difference in self-reported quit rates (15% incentives, 4% control).
  • Women lost to follow-up were assumed to be smokers, which was validated by analysing residual routine blood samples for cotinine.



This study demonstrated that financial incentives with routine care could be beneficial in motivating quit attempts in pregnant smokers, as well as aiding them in continuing to abstain up to 12 months after their quit date. Furthermore, the quit rates reported in this trial were larger than many pharmaceutical (Coleman et al., 2012) or behavioural (Chamberlain et al., 2013) intervention trials in pregnant women. Although, it should be noted that women in the control group had higher nicotine addiction scores than those in the incentives group.

While the evidence from this study suggests using financial incentives may be beneficial in helping pregnant smokers to stop, there may be practical and ethical issues in implementing this as an intervention.

Additionally, other studies are needed to determine the generalizability and possible cost effectiveness of this intervention, as well as what cessation services are best suited to pair with financial incentives. However, it will be interesting to see how this study may be used to inform future policy.


Tappin D, Bauld L, Purves D, Boyd K, Sinclair L, MacAskill S et al. Financial incentives for smoking cessation in pregnancy: randomised controlled trial (pdf). BMJ 2015; 350:h134

Health and Social Care Information Centre, Infant feeding survey 2010 (pdf). HSCIC, 2012.

Flenady V, Koopmans L, Middleton P, Frøen JF, Smith GC, Gibbons K, et al. Major risk factors for stillbirth in high-income countries: a systematic review and meta-analysis. Lancet 2011;377:1331-40. [Abstract]

Gray R, Bonellie SR, Chalmers J, Greer I, Jarvis S, Kurinczuk J, et al. Contribution of smoking during pregnancy to inequalities in stillbirth and infant death in Scotland 1994-2003: retrospective population based study using hospital maternity records. BMJ 2009;339:b3754.

Information Services Division, NHS National Services Scotland. Births and babies: smoking and pregnancy, 2009.

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Welcome to the TARG blog

Hi there everyone!

I’m Suzi Gage, a PhD student in TARG, and an avid blogger. I have a science blog called Sifting the Evidence, which is on the Guardian website. I love writing about science, for a variety of reasons. I believe that since most research conducted in Universities is carried out using money which has ultimately come from the public, we as researchers have a duty to share any results we find. This can be hard due to journals sometimes having paywalls, meaning research isn’t freely available. Also, academic papers are often written in dry technical language which can be confusing or boring to read.

Blogging is a great way of sharing our findings with those people who are interested in what we get up to. We intend to use this TARG blog to do just this, as well as writing posts more generally about the type of research we do, or background summaries of areas of research we are interested in.

If there’s anything you’d like us to cover, do let us know.

A first post will be up soon. Enjoy!