Category: Mental elf

Exercise for the prevention and treatment of antenatal depression

Posted on by oliviamaynard

By Meg Fluharty

This blog originally appeared on the Mental Elf blog on 19th September 2014

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Depression occurring during pregnancy, known as antenatal depression, is very common; affecting 10-13% of women (Gavin et al, 2005), which can result in premature labour, low birth weight, and a compromised mother-child relationship (Li et al, 2009; Mancuso et al 2004).

The current treatments include antidepressants and psychotherapy (Field et al, 2009; Rethorst et al 2009). However, antidepressant use may result in adverse effects during pregnancy and psychotherapy often has lengthy waiting lists (Einerson et al 2010, Parker et al; 2008).

Exercise is also recommended as a treatment option for mental and physical health during pregnancy, by NICE (NICE, 2006), the Royal College of Obstetricians and Gynaecologists (RCOG, 2006) and the American College of Obstetricians and Gynaecologists (Artal & O’Tool, 2006).

This study is the first systematic review and meta-analysis of randomised controlled trials (RCTs) investigating the effectiveness of exercise as a treatment option in antenatal depression (Daley et al, 2014).

Exercise balls are a popular training aid and also a soft place to grab a few minutes sneaky shut-eye.

“Balls to exercise” Insert exclamation mark or question mark as you see fit.

Methods

The authors conducted a literature search of multiple electronic databases, and studies were selected for inclusion if they were RCTs which compared exercise with usual care, a control group or another comparator. Studies were also included which recruited non-depressed, at risk, and depressed participants as the review focused on both prevention and treatment of antenatal depression. Studies were excluded if the intervention was less than 6 weeks (Daley et al, 2014).

The primary outcome was change in depression score between baseline and final antenatal follow-up. The means and standard deviations of the different depression scores were extracted, or calculated if necessary. The standardised mean different (SMD) was calculated in order to summarise the effects across the trials. For the meta-analysis, a random effects model was used, with subgroup analyses in depressed vs. non-depressed patients and aerobic vs. non-aerobic exercise conditions (Daley et al, 2014).

Results

Included studies

Six out of a total of 919 papers were chosen for inclusion in the review and analysis. Studies were primarily excluded if they were not RCTs, did not measure depression, or compared exercise interventions.

All six studies investigated exercise as an intervention versus a control:

  • 2 studies used standard prenatal care
  • 2 used a waiting list
  • 1 used social support
  • 1 used parent education sessions as the control groups

The interventions ranged from 8-12 weeks and were categorised as either aerobic exercise or non aerobic.

In total, there were 406 pregnant women, whose ages ranged from 14-38 and were recruited from 16 weeks gestation.

One study included non-depressed women, and 5 studies included either at risk or participants depressed at baseline (Daley et al, 2014).

Meta-analysis results

  • There was a reduction in depression scores in the exercise groups versus the comparator groups (SMD -0.46, 95%CI -0.87 to 0.05, p=0.03, I2= 68%)
  • There was no difference between women who were:
    • Non-depressed at baseline (SMD -0.74; 95% CI -1.22 to -0.27, p=0.002)
    • Depressed at baseline (SMD -0.41; 95% CI -0.88 to 0.07, p=0.09, I2=70%)
  • There was no difference between:
    • Aerobic exercise interventions (SMD -0.74: 95% CI -1.22 to -0.27 p=0.002)
    • Non-aerobic exercise interventions (SMD -0.41; 95% CI -0.88 to 0.07, p=0.09, I2 =70%)

Exercise during pregnancy may be effective at reducing depression, but bigger and better RCTs are needed before we can be sure of this finding.

Exercise during pregnancy may be effective at reducing depression, but bigger and better RCTs are needed before we can be sure of this finding.

Discussion

Daley et al (2014) present the first meta-analysis of trials investigating the effectiveness as a treatment for antenatal depression. NICE (NICE, 2006), Royal College of Obstetricians and Gynaecologists (RCOG, 2006), and the American College of Obstetricians and Gynaecologists (Artal & O’Tool, 2006) have all stated that women should consider exercise during pregnancy for mental health benefits, and this review provides evidence to support those guidelines.

However, there are a number of limitations that should be considered:

  • The results show a small to moderate effect size, based on a small number of low to moderate quality studies
  • The studies varied greatly and contained large confidence intervals, which may result in imprecise estimates
  • 5 of the 6 studies were based on women with depression, so the authors cannot conclude whether exercise can be used to prevent depression in pregnancy
  • Tests of subgroup differences in exercise category were based on a single trial, therefore future studies should examine a larger range of exercises (aerobic and non-aerobic)
  • No studies reported on adverse events
  • Publication bias was not investigated due to the small number of trials

Future research should be based on a larger sample, include a wider range of exercise categories, investigate possible adverse events, and include non-depressed women.

While we're waiting for the new research into antenatal depression, don't forget that exercise in pregnancy has all sorts of other important benefits.

While we’re waiting for new research to be published, don’t forget that exercise in pregnancy does of course have all kinds of other undeniable benefits.

Links

Daley AJ, Foser L, Long G, Paler C, Robinson O, Walmsley H, Ward R. The effectiveness of exercise for the prevention and treatment of antenatal depression: a systematic review with meta-analysis. BJOG 2014; DOI: 10.1111/1471-0528.12909 [PubMed abstract]

Gavin NI, Gaynes BN, Lohr KN, Meltzer-Brody S, Gartlehner G, Swinson T. Perinatal depression: a systematic review of prevalence and incidence. Obstet Gynecol 2005;106:1071–83. [PubMed abstract]

Li D, Liu L, Odouli R. Presence of depressive symptoms during early pregnancy and the risk of preterm delivery: a prospective cohort study. Hum Reprod 2009;24:146–53.

Mancuso RA, Schetter CD, Rini CM, Roesch SC, Hobel CJ. Maternal prenatal anxiety and corticotropin-releasing hormone associated with timing of delivery. Psychosom Med 2004;66:762–9. [PubMed abstract]

Field T, Deeds O, Diego M, Hernandez-Reif M, Gauler A, Sullivan S, et al. Benefits of combining massage therapy with group interpersonal psychotherapy in prenatally depressed women. J Body Mov Ther 2009;13:297–303. [PubMed abstract]

Rethorst CD, Wipfli BM, Landers DM. The antidepressive effects of exercise: a meta-analysis of randomized trials. Sports Med 2009;39:491–511. [PubMed abstract]

Einerson A, Choi J, Einerson TR, Koren G. Adverse effects of antidepressant use in pregnancy: an evaluation of fetal growth and preterm birth. Depress Anxiety 2010;27:35–8 [PubMed abstract]

Parker GB, Crawford J, Hadzi-Pavlovic D. Quantified superiority of cognitive behavioural therapy to antidepressant drugs: a challenge to an earlier meta-analysis. Acta Psychiatr Scand 2008;118:91–7 [PubMed abstract]

Royal College of Obstetricians and Gynaecologists. Exercise in Pregnancy. Statement No. 4. London: RCOG, 2006.

Antenatal and postnatal mental health: Clinical management and service guidance. NICE CG45, Feb 2007.

Artal R, O’Toole M. Guidelines of the American College of Obstetricians and Gynecologists for exercise during pregnancy and the postpartum period. Br J Sports Med 2003;37:6–12. [PubMed abstract]

– See more at: http://www.thementalelf.net/mental-health-conditions/depression/exercise-for-the-prevention-and-treatment-of-antenatal-depression/#sthash.oDvrzRsY.dpuf

Quitting smoking is associated with decreased anxiety, depression and stress, says new systematic review

Posted on by oliviamaynard

It is well known that tobacco is the leading cause of preventable death in the world (WHO, 2011). However, the associations between smoking and mental health are less well established.

Smokers often want to quit, but the belief that cigarettes can be used to regulate mood can often deter them, and this is especially true for individuals with mental health problems (Zhou et al, 2009; Thompson et al 2005). However, this is somewhat paradoxical because smoking is often associated with poor mental health (Coulthard et al, 2002). So it’s interesting to report on this new study by Taylor et al (2014) who reviewed the current literature evaluating changes in mental health in those who quit smoking compared with those who continued to smoke.

Methods

The authors conducted a systematic review by searching Web of Science, Cochrane, Medline, Embase & PsychINFO, as well as contacting authors for missing data, and translating non-English papers.

Eligibility was determined using the following criteria:

  • Studies took smokers from the general population or from populations with a defined clinical diagnosis
  • They were longitudinal studies collecting data on mental health prior to quit attempts and again 6 weeks after

A meta-analysis was performed using a random effects model to pool the standard mean difference (SMD) between the change in mental health in quitters and continued smokers from baseline to follow-up. The SMD was used, as different scoring systems couldn’t be standardised across studies.   The mental health outcomes they measured were anxiety, depression, mixed anxiety/depression, positive affect, psychological quality of life & stress.

Results of systematic review

After data extraction, 15 full text articles were included:

Study type

11 cohort studies, 14 secondary analyses of cessation interventions, and 1 randomised controlled trial.

Participant population

14 studies included the general population, 3 included patients living with chronic physical condition, 2 with pregnant patients, 1 included postoperative patients, 2 studies included either chronic physical or psychiatric conditions, and 4 studies included patients with psychiatric conditions.

48% of participants were male with a median age of 44, and on average smoked 20 cigarettes per day. The average participant scored as moderately dependent to nicotine on a dependence test.

Results of meta-analysis

Compared with continuing to smoke:

People who quit smoking were less anxious, depressed and stressed than those who continued to smoke

People who quit smoking were less anxious, depressed and stressed than those who continued to smoke

  • Quitting was associated with a decrease in anxiety (SMD -0.37, 95% CI  -0.70 to -0.03; P=0.03)
  • Quitting was associated with a decrease in depression (SMD -0.25, 95% CI -0.37 to -0.12; P<0.001)
  • Quitting was associated with a decrease in mixed anxiety and depression (SMD -0.31, 95% CI -0.47 to -0.14; P<0.001)
  • Quitting was associated with a decrease in stress (SMD -0.27, 95% CI -0.40 to -0.13; P<0.001)
  • Quitting was associated with an improved psychological quality of life (SMD 0.22, 95% CI 0.09 to 0.36; P<0.001)
  • Quitting was associated with increased positive affect (SMD 0.40, 95% CI 0.09 to 0.71; P=0.01)

Subgroup Analyses

  • Analyses for study quality did not change summary estimates
  • Studies which adjusted for covariates showed a larger difference between quitters and those who continued to smoke compared to studies which did not adjust

Additional Analyses

  • There was no evidence that effect size differed across different clinical populations
  • There was no evidence of subgroup differences between study designs
  • The studies were ordered according to length in a forest plot and no clear chronological pattern in effect estimates was found

Discussion

This review shows that quitting smoking is associated with reduced depression, anxiety and stress, and improved psychological quality of life and positive affect compared to continuing to smoke. The strength of the association was similar for all populations; both general and clinical. The authors suggest three possible interpretations of the data:

  1. Quitting smoking results in improved mental health
  2. Improved mental health causes an individual to quit smoking
  3. There is a common factor that explains both the improved mental health and smoking cessation

The authors hypothesise that quitting smoking improves mood is supposed by a biological mechanism caused by brain changes in the nicotinic pathways due to chronic smoking (Wang & Sun, 2005). These brain changes result in low mood (irritation, anxiety, and depressed mood) after smoking a cigarette. While an individual is actually feeling withdrawal symptoms, they are misattributed to low mood, and more cigarettes are smoked to alleviate their symptoms (Benowitz, 1995; Benowitz, 2010).

However, not all of the data supports this interpretation.  For example, a study using Mendelian randomisation- an instrumental variable approach that uses gene relating to smoking behaviour to examine health related outcomes, did not find a causal association between smoking and mental health (Bjorngaard et al 2013).

While this review displays that there are strong associations between quitting smoking and mental health, the authors recommend future studies examining this association to help strengthen causal inferences which come from observation research. The authors suggest further epidemiological studies using Mendelian randomisation, or using statistical analysis of observational data using propensity score matching to reduce the bias of confounding variables.

Conclusion

Many people believe that quitting smoking can have adverse psychiatric effects. This high quality research suggests the opposite

Many people believe that quitting smoking can have adverse psychiatric effects. This high quality research suggests the opposite

These are important findings as smokers can find reassurance in the fact that quitting is likely to result in improved mental wellbeing. Additionally, these findings are important as they show that quitting smoking is likely to improve your mental health if you are mentally ill or mentally well.

Hopefully these findings will help overcome some of the current barriers within the mental health field; for example the continued belief that quitting smoking or certain pharmacological treatments can have adverse psychiatric effects.  See our recent Lee Cook et al (2013) blog, which showed that individuals with mental illness treated as outpatients were more likely to decrease and quit smoking than those in inpatient facilities.

Furthermore, the NICE guidelines on smoking cessation, which we blogged about here, recommend that all NHS hospitals and clinics should become smoke-free, as well as identifying smokers and offering behavioural and pharmacotherapy onsite. Additionally, the guidelines suggest staff should be trained on stop-smoking services and should abstain from smoking on-site themselves (NICE, 2013).

Links

Taylor G et al. Change in mental health after smoking cessation: systematic review and meta-analysis. BMJ 2014;348:g1151 doi: 10.1136/bmj.g1151

Coulthard M, Farrell M, Singleton N, Meltzer H. Tobacco, alcohol and drug use and mental health (PDF). Office for National Statistics, 2002.

World Health Organization. WHO report on the global tobacco epidemic. WHO, 2011.

Zhou X, Nonnemaker J, Sherrill B, Gilsenan A, Coste F, West R. Attempts to quit smoking and relapse: factors associated with success or failure from the ATTEMP cohort study (PDF). Addict Behav 2009;34:365-73.

Thompson B, Thompson LA, Thompson J, Fredickson C, Bishop S. Heavy smokers: a qualitative analysis of attitudes and beliefs concerning cessation and continued smoking. Nicotine Tob Res 2003;5:923-33. [PubMed abstract]

Le Cook B, Wayne GF, Kafali EN, Lui Z, Shu C Flore M. Trends in Smoking Among Adults with Mental Illness and Association Between Mental Health Treatment and Smoking Cessation. JAMA. 2014; 311 (2): 172-182. [Abstract]

Smoking cessation: acute, maternity and mental health services: guidance (PDF). NICE, PH48, 27 Nov 2013.

Wang H, Sun X. Desensitized nicotinic receptors in brain. Brain Res Rev 2005;48:420-37. [Abstract]

Benowitz NL. Nicotine addiction. Prim Care 1999;26:611-31 [PubMed abstract]

Benowitz NL. Nicotine addiction. N Engl J Med 2010;362:2295 [Abstract]

Bjorngaard JH, Gunnell D, Elvestad MB, Davey-Smith G, Skorpen F, Krokan H, et al. The causal role of smoking in anxiety and depression: a Mendelian randomization analysis of the HUNT study. Psychol Med 2013;43:711-9 [PubMed abstract]

This article first appeared on the Mental Elf website on 13 March 2014 and is posted by Meg Fluharty. Follow Meg on Twitter @MegEliz_

– See more at: http://www.thementalelf.net/mental-health-conditions/anxiety-disorders/quitting-smoking-is-associated-with-decreased-anxiety-depression-and-stress-says-new-systematic-review/#sthash.z8TIWuMV.dpuf

Cochrane review says there’s insufficient evidence to tell whether fluoxetine is better or worse than other treatments for depression

Posted on by Marcus Munafo

Depression is common in primary care and associated with a substantial personal, social and societal burden. There is considerable ongoing controversy regarding whether antidepressant pharmacotherapy works and, in particular, for whom. One widely-prescribed antidepressant is fluoxetine (Prozac), an antidepressant of the selective serotonin reuptake inhibitors (SSRI) class. Although a number of more recent antidepressants are available, fluoxetine (which went off patent in 2001) remains highly popular and is commonly prescribed.

This systematic review and meta-analysis, published through the Cochrane Collaboration, compares the effects of fluoxetine for depression, compared with other SSRIs, tricyclic antidepressants (TCAs), selective noradrenaline reuptake inhibitors (SNRIs), monoamine oxidase inhibitors (MAOIs) and newer agents, as well as other conventional and unconventional agents. This is an important clinical question – different antidepressants have different efficacy and side effect profiles, but direct comparisons are relatively rare.

Methods

Thank goodness for systematic reviewers who read hundreds of papers and combine the results, so you don't have to

Thank goodness for systematic reviewers who read hundreds of papers and combine the results, so you don’t have to

The review focused on studies of adults with unipolar major depressive disorder (regardless of the specific diagnostic criteria used), searching major databases for studies published up to 11 May 2012.

All randomised controlled trials comparing fluoxetine with any other antidepressant (including non-conventional agents such as hypericum, also known as St John’s wort) were included. Both dichotomous (reduction of at least 50% on the Hamilton Depression Scale) and continuous (mean scores at the end of the trial or change score on depression measures) outcomes were considered.

Results

A total of 171 studies were included in the analysis, conducted between 1984 and 2012 and comprising data on 24,868 participants.

A number of differences in efficacy and tolerability between fluoxetine and certain antidepressants were observed. However, these differences were typically small, so that the clinical meaning of these differences is not clear.

Moreover, the majority of studies failed to report detail on methodological procedures, and most were sponsored by pharmaceutical companies.

Both factors increase the risk of bias and overestimation of treatment effects.

Conclusions

The review

The review found sertraline and venlafaxine (and possibly other antidepressants) had a better efficacy profile than fluoxetine

The authors conclude that: “No definitive implications can be drawn from the studies’ results”.

There was some evidence for greater efficacy of sertraline and venlafaxine over fluoxetine, which may be clinically meaningful, but other considerations such as side-effect profile, patient acceptability and cost will also have a bearing on treatment decisions.

In other words, despite considerable effort and pooling all of the available evidence, we still can’t be certain whether one antidepressant is superior to another.

What this review really highlights is the ongoing difficulty in establishing whether some drugs are genuinely effective (and safe), because of publication bias against null results (Turner, 2008).

This situation is made worse when there are financial vested interests involved. Recently, there has been active discussion about how this problem can be resolved, for example by requiring pharmaceutical companies to release all data from clinical trials they conduct, irrespective of the nature of the findings.

Despite the mountains of trials published in this field, we still cannot say for sure which treatments work best for depression

Despite the mountains of trials published in this field, we still cannot say for sure which treatments work best for depression

Clinical decision making regarding the most appropriate medication to prescribe are complex, and made harder by the lack of direct comparisons. Moreover, the apparent efficacy of individual treatments may be inflated by publication bias. Direct comparisons between different treatments are therefore important, but remain relatively rare. This Cochrane Review provides very important information, even if only by highlighting how much we still don’t know about which treatments work best.

Links

Magni LR, Purgato M, Gastaldon C, Papola D, Furukawa TA, Cipriani A, Barbui C. Fluoxetine versus other types of pharmacotherapy for depression. Cochrane Database of Systematic Reviews 2013, Issue 7. Art. No.: CD004185. DOI: 10.1002/14651858.CD004185.pub3.

Etchells, P. We don’t know if antidepressants work, so stop bashing them. The Guardian website, 15 Aug 2013.

Turner EH, Matthews AM, Linardatos E, Tell RA, Rosenthal R. Selective publication of antidepressant trials and its influence on apparent efficacy. N Engl J Med. 2008 Jan 17;358(3):252-60. doi: 10.1056/NEJMsa065779. [PubMed abstract]

This article first appeared on the Mental Elf website on 1st October 2013 and is posted by Marcus Munafo

Health Technology Assessment report finds computer and other electronic aids can help people stop smoking

Posted on by Marcus Munafo
Smoking continues to be the greatest single preventable cause of premature illness and death in developed countries. Although rates of smoking have fallen, over 20% of the adult population in the UK continues to smoke. Anything which can be done to help people stop smoking will therefore have substantial public health benefits.

More and more people now have access to computers and other electronic devices (such as mobile ‘phones), and there is growing interest in whether these can be used to prompt or support attempts to stop smoking. This could be by providing a prompt to quit, reaching smokers who would otherwise use no support, and/or supporting the degree to which people use their smoking cessation medication (e.g., nicotine replacement therapy).

A recent Health Technology Assessment review assessed the effectiveness of internet sites, computer programs, mobile telephone text messages and other electronic aids for helping smokers to quit, and/or to reduce relapse to smoking among those who had quit.

Methods

The reviewers conducted a systematic review of the literature from 1980 to 2009 and found 60 randomised controlled trials (RCTs) and quasi-RCTs evaluating smoking cessation programmes that utilised computer, internet, mobile telephone or other electronic aids. The review was restricted to studies of adult smokers.

The primary outcomes were smoking abstinence, measured in two ways: Point prevalence abstinence and prolonged abstinence. The first is typically available in more studies (because it is easier to measure) but a rather liberal measure of abstinence (since the smoker need only be abstinent at the point the assessment is made to count as having quit). The latter is more conservative (since it requires the smoker to have been abstinent for an extended period to count as having quit), and is generally the preferred measure. Smoking abstinence at the longest follow-up available in each study was used, again because this is most conservative.

Results

Combining the data from the 60 trials indicated that, overall, the use of computer and other electronic aids increased quit rates for both prolonged (pooled RR = 1.32, 95% CI 1.21 to 1.45) and point prevalence (pooled RR = 1.14, 95% CI 1.07 to 1.22) abstinence at longest follow-up,  compared with no intervention or generic self-help materials.

The authors also looked at whether studies which aided cessation differed from those which prompted cessation, and found no evidence of any difference in the effect size between these. The effectiveness of the interventions also did not appear to vary with respect to mode of delivery or the concurrent use non-electronic co-interventions (e.g., nicotine replacement therapies).

Conclusions

Computer and other electronic aids do indeed increase the likelihood of cessation compared with no intervention or generic self-help materials, but the effect is small

The review concluded that computer and other electronic aids do indeed increase the likelihood of cessation compared with no intervention or generic self-help materials, but the effect is small. However, even a small effect is likely to have important public health benefits, given the large number of people who smoke and the impact of smoking on health. The authors also note that uncertainty remains around the comparative effectiveness of different types of electronic intervention, which will require further study.

The authors argue that further research is needed on the relative benefits of different forms of delivery for electronic aids, the content of delivery, and the acceptability of these technologies for smoking cessation with subpopulations of smokers, particularly disadvantaged groups. More evidence is also required on how electronic aids developed and tested in research settings are applied in routine practice and in the community.

Link

Chen YF, Madan J, Welton N, Yahaya I, Aveyard P, Bauld L, Wang D, Fry-Smith A, Munafò MR. Effectiveness and cost-effectiveness of computer and other electronic aids for smoking cessation: a systematic review and network meta-analysis (PDF). Health Technol Assess 2012; 16(38): 1-205, iii-v. doi: 10.3310/hta16380.

This article first appeared on the Mental Elf website on 11th March 2013 and is posted by Marcus Munafo