A pragmatic randomised controlled trial to evaluate the cost-effectiveness of a physical activity intervention as a treatment for depression: the treating depression with physical activity (TREAD) trial

Current treatment/management options in primary care

Although antidepressants are an effective treatment for the more severe depressions, there is some clinical uncertainly about their use, particularly in those patients with mild/moderate depression. Adherence to antidepressant treatment is often poor, and only about 20% of patients are understood to take their medication according to guidelines. 2,3 There is also widespread scepticism about the effectiveness of antidepressants among the general population, and this may contribute to an overall reluctance to consult a GP for depression. 4 Hence, there is a need to identify effective non-pharmacological interventions for the management of the common, less severe, forms of depression.

The main alternative to antidepressant medication is psychotherapy, particularly cognitive behavioural therapy (CBT). The availability of psychotherapies is improving thanks to the Improving Access to Psychological Therapies (IAPT) programme (www.iaptmds.co.uk/). However, the more intensive psychotherapies require professionals with high levels of training and frequent supervision. CBT can also be quite demanding of patients, requiring weekly hour-long appointments that can interfere with work and family commitments.

It is difficult to define ‘usual care’ of depression in the primary care setting. Some people with depression are managed without antidepressant medication, although often this group have a milder illness and could, in theory, be prescribed antidepressants if their symptoms persisted or worsened over time. Similarly, counselling and other psychotherapies can be used in primary care as an element of ‘usual care’, although often there is a delay to accessing such services because of the level of demand and the time needed for referral and assessment.

Possible health benefits of physical activity for depression

There has recently been an increased interest in the potential health benefits of physical activity in treating depression, following on from the well-documented success in managing heart disease, obesity and diabetes using similar methods. 5 ‘Exercise on prescription’ schemes have flourished within primary care in the UK, with over 800 such programmes being implemented in the past decade, designed primarily to improve physical health. The most recent guidance available to health-care providers on the treatment of depression within general practice is embodied in the National Institute for Health and Clinical Excellence (NICE) guidelines,6 which recommend a ‘structured’ physical activity programme for depression.

Possible mechanisms for how exercise might influence depression

Little is known about the possible mechanisms that might mediate any therapeutic effects of physical activity on depression. Suggested biological mechanisms include changes in neuroendocrine function, neurotransmission, core temperature, cerebral blood flow or muscular tension. Psychosocial mechanisms such as improvements in physical self-perception and self-confidence have been observed,7 and increased social interaction and perceived support from an exercise specialist or exercise group have also been suggested as possible therapeutic mechanisms.

Similarly, there is little evidence to indicate the type, intensity and duration of physical activity that might be most effective in reducing depression. The recent report5 by the Chief Medical Officer (CMO) concluded, on the basis of rather limited evidence, that aerobic exercise lasting between 20 and 60 minutes which involved large muscle groups, such as brisk walking, cycling and swimming, was likely to be most effective. A recent systematic review8 of physical activity and depression concluded that it was impossible to determine which types of activity provided the most benefit.

A physical activity intervention, if effective, is likely to improve depressive symptoms through some or all of the above pathways and it could be that the overall effectiveness of physical activity relies upon such multiple mechanisms. For this reason we think that the main question is whether or not physical activity, of whatever intensity, might improve outcomes for people with depression. We have chosen the term ‘physical activity’ to reflect this broad notion of what we wish to investigate. The term ‘exercise’ can, at least for some people, indicate vigorous and aerobic activity, which we suppose might exclude gentler activities, such as walking, that might still have psychological benefits.

Lack of evidence in clinical populations

Twenty-one trials were conducted in non-clinical populations, the majority among community volunteers who responded to advertisements for an exercise in depression trial. In some studies there were financial or other incentives to participate. Volunteers are likely to have an extra degree of motivation compared with patients who present to primary care and so results might be difficult to apply to NHS settings. A recent systematic review10 of randomised trials in participants who had received a diagnosis of depression identified 13 such trials. The pooled SMD for these was –0.40 (95% CI –0.66 to –0.14) with evidence of heterogeneity between trials (I² = 57.2%, p = 0.003). There was an inverse association between duration of intervention and magnitude of effect, with trials in which the intervention lasted for ≥ 10 weeks showing little evidence of a beneficial effect.

Short duration of follow-up

Only five of the trials studied whether or not any benefits of an exercise intervention outlasted the duration of the intervention. On average, the effect size was reduced at longer-term follow-up (between 4 and 26 months), with a SMD of 0.44 (95% CI 0.18 to 0.71) in the meta-analysis of the five studies. In the context of a chronic relapsing and remitting disease, it is important to estimate any long-term as well as short-term effects, although even a short-term benefit may still prove worthwhile and be cost-effective. In the subset of trials with participants with a clinical diagnosis of depression there was no evidence of a long-term benefit of physical activity. 10

Quality of trials

The majority of trials to date have used randomisation procedures that were inadequately concealed or failed to undertake intention-to-treat (ITT) analyses. In general, not reporting methodological characteristics of trials will tend to exaggerate the impact of an intervention. 11 There was also evidence of heterogeneity between trials, which suggests that results were not consistent across studies.

Small size of trials

The trials undertaken to date have all been far too small and underpowered to find anything other than a massive treatment effect. The largest of the trials12 included just 51 participants in the treatment arm and 49 in the control arm. Only six trials had > 50 participants.

Nature of the intervention

Only one trial12 described unsupervised physical activity as an intervention. In the remaining studies the nature of the intervention was either supervised or not described or reported. Blumenthal et al. 12 compared home-based unsupervised physical activity with supervised gym-based activity. Providing supervised physical activity seems costly and unrealistic as a health service intervention, unless offered in a group setting. None of the trials used an intervention that could be used in the NHS or other health service setting.

Two of the more recent trials are worthy of more detailed description. The DOSE study,13 based in the USA, reported a treatment response for the more intensive ‘dose’ of exercise. The intervention involved the participants attending a gym and carrying out supervised aerobic activity on an exercise bike. The more vigorous (17.5 kcal/kg/week) and more frequent (5 days) intervention appeared to have a benefit compared with the control group. However, the study was small and only 16 subjects were randomised to the most intensive group (80 in total to five groups with a Latin square design). The participants had very mild depression, with a mean Hamilton14 score of 16.2, although all met Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition (DSM-IV)15 criteria.

Another US study, by Blumenthal et al. ,12 carried out a comparison between two different exercise interventions and antidepressant and placebo treatments. They found a 9% difference in remission from depression in favour of home-based exercise when comparing home-based exercise and usual care at 16 weeks. This difference is slightly less than the difference we have used for the power calculations in the present study. However, we would expect a placebo effect in such trials and so we think that the plausible treatment difference between intervention and usual care would be greater than that reported in this trial. In addition, this was a relatively small trial with just over 40 participants in each group and so estimated these treatment differences with limited precision.

Another US trial, coincidentally also called TREAD, has begun and has published its protocol, but as far as we are aware it has not published any findings. 16 The intervention in this case is somewhat more pragmatic as it allows home-based as well as gym-based activity, modelled upon the more intensive intervention from the DOSE study. 13 The participants are sedentary at baseline and will be recruited by a combination of adverts and physician referral.

Intensity of the intervention

Previous reviews have concluded that there is little evidence to suggest that interventions designed to increase physical activity have led to long-term change. However, it is possible that this may have been because the interventions were not sufficiently intensive in terms of the amount of supervision and support provided to participants. Very few of the interventions would meet the NHS National Quality Assurance Framework (NQAF) guidelines for exercise referral schemes. 22,23 Many of the studies had only one contact with the patient and it is difficult to generalise from some of the US studies.

In a UK study, Harland et al. 24 concluded that progressively more intensive interventions, involving up to 6 counselling sessions and 30 free leisure centre vouchers, produced greater changes in physical activity up to 12 weeks; however, the effects were not sustained at 12 months. Taylor et al. ’s RCT in the UK7,25 reported increased activity and fitness at 26 weeks in response to a 10-week exercise referral scheme in a local leisure centre and improved physical self-perceptions at 9 months. However, in a recent systematic review26 of eight RCTs that evaluated exercise referral schemes there were no long-term differences in physical activity compared with usual care.

Most of the literature concerns interventions designed for patients with cardiovascular disease rather than depression. Depression is characterised by low motivation, fatigue and reduced self-esteem, and these symptoms are likely to make it difficult to increase physical activity levels. Almost all of the RCTs that have investigated the effects of physical activity on depression have used supervised physical activity sessions rather than advice. 8 This most likely reflects the understanding by those undertaking such studies that a less intensive intervention is unlikely to alter behaviour in those with depression. An intervention that has been relatively successful in changing behaviour in a cardiovascular disease group may not be intensive enough to produce an effect in a trial of people with depression.

Physical activity is still regarded with some scepticism as an effective treatment for depression and, at this stage of knowledge, it is important to ensure that any intervention has the best chance of changing behaviour. We want to avoid what Tones27 has called a ‘type 3’ error, in which lifestyle interventions have (correctly) failed to show an effect on outcome because the intervention itself was too weak to change behaviour. This suggests the need to lean towards greater intensity, such as offering more frequent contact over a longer period. On the other hand, if the intervention is too intensive, this will increase cost and reduce its cost-effectiveness and eventual adoption. It would be important to make an intervention for physical activity much less intensive, for example, than psychotherapies such as CBT.

Theoretical model underpinning intervention

Some of the reported trials have described an intervention based upon a theoretical framework. The most popular frameworks used were designed to influence exercise cognitions and behaviour based on stage of readiness to become more active (transtheoretical model). 28,29 A recent systematic review21 concluded that ‘stage of readiness’-based interventions have not, on the whole, been effective in increasing patients’ physical activity in primary care but, as mentioned above, many of these interventions were probably not sufficiently intensive. Little et al. 30 devised an intervention based upon the theory of planned behaviour (TPB) and reported a trend towards greater change in physical activity, but only at the 1-month follow-up and in patients without depression recruited through a postal request.

The existing research has not provided sufficient encouragement for the adoption of one approach over another. We chose to use self-determination theory,31 which proposes that real shifts in behaviour arise through heightened autonomy or personal ownership of behavioural success. Self-determination theory suggests that, in order to stimulate motivation, the psychological needs for competence, autonomy and relatedness must be met. Encouraging participants to take charge of their physical activity decisions and choices is therefore very important. This approach fits well with the principles of motivational interviewing,32 which is designed to lead to better adherence and better motivation. 33 It also supports the view that choice of physical activity option, as described later, should improve adherence, especially over longer time periods. 29,34,35 In practical terms, the key elements are likely to be an intervention that (1) assesses current attitudes to physical activity, perceived barriers and the readiness to change, (2) utilises motivational interviewing techniques32 to engage the patient’s own motivation rather than providing simple advice, (3) offers choice of physical activity and rate of improvement and (4) uses appropriate behavioural strategies that can increase self-efficacy and self-determination.

Who delivers the intervention

Evidence from primary care suggests that existing health professionals are very inconsistent at providing advice about physical activity. 36 For example, McKenna et al. 37 found that GPs and practice nurses typically did little to promote physical activity and that those who did were more likely to be active themselves. It appears that only health professionals with a commitment to physical activity tend to encourage an increase in activity in their patients. The intensity and nature of a physical activity intervention for depression suggests that individuals with both a commitment to the concept and a readiness to develop expertise are needed. If each general practice were to devote a health professional to promoting physical activity for people with depression the training would have to be less intensive and, as each professional would be seeing only a handful of patients, it might be difficult to develop expertise and commitment. Practice nurses already undertake a multiplicity of tasks and there are likely to be future shortages of health professionals, who are also expensive to employ. For these reasons many people have argued for a new type of health professional who has expertise in behavioural change, which we have described as a physical activity facilitator (PAF). If this model were to be adopted more widely, it would also be easier to implement, because it is much simpler to train one person who might cover 10 practices than to train a health professional from each of those practices.

Reducing barriers to physical activity

Many people are reluctant to engage in physical activity, not only because of financial barriers, but also because of their own perceptions about physical activity and preference for different forms of physical activity. The more traditional ‘exercise on prescription’ schemes in UK primary care have been termed ‘structured’ or ‘centre-based’ activity in which the patient attends formal group sessions at a leisure or community centre. In contrast, ‘lifestyle’ or ‘home-based’ activity allows individuals to develop their own physical activity programme from home, which often consists of walking or cycling. One issue facing ‘centre-based’ exercise is that many people find that initial visits to leisure centres and joining unfamiliar groups of exercisers are anxiety provoking. This may particularly be the case for those suffering from depression, who often have accompanying anxiety symptoms. In a recent Department of Health-commissioned review, Fox et al. 38 found no difference in adherence to these two programmes when patients were randomised. The critical issue is to maximise choice in order to increase chances of adherence. In some of the more progressive exercise schemes, such as those being delivered in Somerset, participants are referred to a trained exercise facilitator, who will establish exercise preferences.

As mentioned previously, we have chosen to use the term ‘physical activity’ to emphasise the broad range of activities that might be beneficial in depression and to try to prevent the idea that we wish only to encourage vigorous aerobic activities. This should help to reduce the perceived barriers to exercise. Related to this is the idea that if physical activity is to be sustained it has to be incorporated into a ‘routine’, for example by walking or cycling to work rather than using public transport or driving a car. This also has the effect of reducing the perceived barriers to physical activity.

Inclusion criteria

Patients were considered for inclusion if they:

• were aged 18–69 years at the time of assessment

• had a diagnosis of depression (F32, F33) according to the International Statistical Classification of Diseases and Related Health Problems, 10th Edition (ICD-10)41 using the revised Clinical Interview Schedule (CIS-R)42

• scored ≥ 14 on the Beck Depression Inventory (BDI)43

• were not taking antidepressants at the time of assessment or had been prescribed antidepressants within 4 weeks of assessment but had had an antidepressant-free period of 4 weeks prior to that.

Exclusion criteria

The study design excluded anyone:

• unable to complete self-administered questionnaires in English

• with medical contraindications to physical activity

• being treated for psychosis or bipolar disorder

• with a serious substance abuse problem

• who was pregnant or breastfeeding at the time of assessment.

Women who became pregnant in the course of study participation were encouraged to continue their involvement under their GP’s supervision.

Usual care

Individuals allocated to the usual care arm of the trial were advised to follow the current advice of their GP regarding their depression and its treatment. This might have included antidepressant medication, counselling or referral to secondary mental health services.

Intervention

In addition to usual care from their GP, those allocated to the intervention arm were encouraged to work with their TREAD PAF.

Primary outcome

The BDI was used as a self-report measure of depression at the 4-month follow-up point. The 4-month follow-up was used as the measurement point for the primary outcome because it reflected the stage of the intervention at which the largest effect was expected. The BDI is a 21-item scale that has been widely used to measure depression outcome in randomised trials, particularly trials of cognitive psychotherapy, with higher scores indicating more severe depression. The score was treated as both a continuous (range 0–63) and a binary (where < 10 indicates recovery) outcome within the analysis, providing a quantitative measure of improvement and an estimate of the proportion of patients reaching symptomatic recovery.

Secondary outcomes

Accelerometry

A subsample of the trial participants wore an accelerometer to provide an objective measure of the amount of physical activity undertaken and to validate the self-reported physical activity data elicited in the trial. Accelerometers record movement in such a way that it can be translated into a number of different outcomes, for example total step count, bouts of physical activity at specified intensities or energy expenditure. Every participant who completed the 4-month follow-up was offered an accelerometer to wear during waking hours for the next week, the aim being to gather data from 100 trial participants overall, taking into account their group allocation. At the end of the 7-day period, participants returned the monitor to the research team and completed the trial’s physical activity recall diary once more.

Accelerometry data were collected using Actigraph GT1Ms (Actigraph GT1M, Penascola, FL, USA) programmed to record using 10-second epochs. Data were reduced using MAH/UFFE Analyser v. 1.9.0.3 (MRC Epidemiology Unit, Cambridge, UK) set to ignore runs of 60 minutes of zeros. Days of data were matched with self-reported physical activity data, and cases with < 10 hours of Actigraph monitoring per day were also excluded from the analysis. Data were categorised as being of one of the following intensities:

• minutes of sedentary [0–99 counts per minute (CPM)]

• minutes of light inactive (100–499 CPM)

• minutes of light active (500–1951 CPM)

• minutes of moderate (1952–5723 CPM)

• minutes of vigorous (> 5723 CPM).

Minutes spent at light and moderate intensities were multiplied by the median values (2 and 4.5 METs respectively) for the accepted MET ranges for these intensities (light > 1–3, moderate 3–5.99 METs). A value of 7.5 METs was used for minutes spent at vigorous intensity, for which the intensity classification is ≥ 6 METs, and was considered to be representative of vigorous activities likely to be performed by participants. 44 This calculation provided a number of MET minutes per day, which was then summed over the entire week. We calculated two summary measures: light, moderate and vigorous MET minutes of physical activity per week (LMVPA) and moderate and vigorous MET minutes of physical activity per week (MVPA).

Original sample size justification

The original calculation for the research proposal estimated that 60% of participants in the usual care group and 73% in the intervention group would have recovered by the 4-month follow-up, that is, would score < 10 on the BDI. This difference of 13% in the proportion ‘recovered’ [equivalent to an odds ratio (OR) of 1.8] would be considered clinically worthwhile, being consistent with the lower end of treatment effects observed following treatment with antidepressants.

Assuming that 10% of the participants would not be taking antidepressants at the time of recruitment and so would be omitted from the originally planned primary analysis, 291 patients need to be recruited for each treatment group, with 90% power and 5% two-sided alpha. Previous studies using the BDI as a continuous outcome estimated a standard deviation of about 9 points and suggested a worthwhile target difference of 3–4 points. Thus, allowing for non-collection of primary outcome data of up to 15% at the 4-month follow-up point, the number required to be randomised was 762.

Revised sample size justification

After recruitment of 90 participants, we checked our assumptions in the original sample size calculation and found that the percentage of participants not on antidepressant treatment was closer to 50%, rather than the 10% originally anticipated. It was therefore proposed that all randomised participants should be included in the primary analysis rather than simply those on medication, with stratification by baseline antidepressant use to maximise balance between the trial arms. In addition, although the recovery rate of the participants in the usual care group was initially assumed to be around 60%, a recently concluded study conducted using similar methods47 found that the proportion of participants recovering in the equivalent group was nearer to 20% (95% CI 12.9% to 30.3%). Thus, the original power calculations were revised to reflect both the inclusion of all those randomised, irrespective of antidepressant use, and the change in proportion we expected to recover. The revised calculations – shown in Table 2 – indicate that, with 360 randomised participants, we would have adequate power to detect a 3-point difference in BDI total score and 80% power to detect a 15% difference in recovery between groups using the BDI as a binary variable.

Preliminary analyses

Descriptive statistics of the key clinical and sociodemographic variables were used to assess the baseline comparability of the two randomised groups and to enable additional adjustment of the primary and secondary analyses as appropriate.

Primary analyses

The primary outcome measure (BDI score at the 4-month follow-up point) was considered in both a binary and a continuous form. The continuous outcome was analysed in a linear regression model and presented as the adjusted difference in mean score between the intervention group and the usual care group with adjustment for baseline BDI score. The binary outcome was analysed in a logistic regression model and presented as an adjusted OR of recovery in the intervention group (with recovery denoted by a BDI score of < 10) compared with recovery in the usual care group. We calculated 95% CIs as well as p-values in interpreting both forms of the outcome measure. To account for the variables used for stratification and minimisation (the ‘design variables’) we also adjusted the primary analysis for antidepressant use, CIS-R score at baseline, recruiting centre and baseline level of physical activity.

Secondary analyses

The BDI score was also considered as a secondary outcome measure (in both binary and continuous forms) employing data from the 4-, 8- and 12-month follow-up points in a repeated measures analysis, using linear and logistic models as appropriate. This enabled investigation of whether or not between-group differences changed over time and estimated an average effect size over all three follow-up assessments in the absence of any time effect.

The other secondary outcome measures considered were SF-12 physical and mental health status, expectations of physical activity, physical activity levels and antidepressant use at the 4-month follow-up. All were analysed using the appropriate linear and/or logistic regression models with adjustment for the baseline value of that outcome as well as the design variables. The secondary outcomes were also subject to a repeated measures analysis using data from all three follow-up points. Finally, antidepressant prescription was analysed as a binary variable (0 = no prescription, 1 = at least one prescription issued) using all data available from the 12-month follow-up point in a logistic regression model. Accelerometer data were analysed in Stata using methods to allow clustering of observations in individuals. Means and CIs were calculated using the ‘svy’ commands.

Influence of practice

It is possible that participants attending the same general practice might have similarities in trial outcome and that, if this did occur, it could influence the variance estimates, showing a clustering effect. We therefore accounted for this possibility by using the robust variance techniques that are available for linear and logistic regression in Stata; however, Stata does not provide robust variance estimates for repeated measures logistic regression.

Influence of physical activity facilitator

Similarly, there may be variation in outcome dependent on the allocated PAF. Roberts and Roberts50 have suggested a method of accounting for this possibility using generalised linear and latent mixed regression to obtain a fully heteroscedastic model. Thus, it would be possible to determine whether or not the primary analyses at 4 months post randomisation were affected by incorporating any clustering effects according to PAF.

Depression symptoms

Depression symptoms

Physical activity undertaken

Outcome expectations of physical activity

Antidepressant use

Antidepressant prescription

Quality of life

Accelerometry

Data were available on 99 trial participants from both randomised groups who had at least 1 day with > 10 hours of usable accelerometer data, together with a recall diary entry completed for that same day. There were 84 participants with ≥ 5 days of paired data. The distribution of usable days for the respondents is given in Table 31.

Table 32 gives details of the mean MET minutes for light, moderate and vigorous activity as recorded in participants’ recall diaries and the accelerometers. The CIs have taken account of any clustering in the data within individuals. This illustrates that the accelerometer was recording markedly more MET minutes than the recall diary, especially for light activity. The difference probably reflects the instruction for those completing the recall diary to record ‘bouts’ of activity lasting 15 minutes, whereas the accelerometer registered much shorter time periods of activity. The differences in the moderate and vigorous categories of activity were less marked.

The association between the two measures was estimated using a random effects regression to take account of the clustering of the data within individuals. With the sum of light, moderate and vigorous activity on the accelerometer as the outcome, for each increase of 1 MET minute in the recall diary, there was an increase of 0.26 points (95% CI 0.13 to 0.40, p < 0.0001) in the accelerometer outcome. With the sum of moderate and vigorous MET minutes recorded by the accelerometer as the outcome, there was an increase of 0.12 points (95% CI 0.06 to 0.18, p < 0.0001) for each increase of 1 MET minute in the recall diary.

We also examined the agreement between the two types of physical activity measurement using the approach described by Bland and Altman,52 which takes account of any clustering by individual. Figure 3 gives the resultant plot and indicates that the difference between the two assessments increases as the participants become more active.

FIGURE 3.

Plot of the difference (accelerometer minus recall diary) between moderate and vigorous physical activity as recorded by accelerometer and moderate and vigorous physical activity as recorded by recall diary against the mean of both measures.

Health and social care resource use

Data on resource use came from two main sources. GP records were interrogated at the end of the 12-month follow-up period in order to collect information on all consultations in, by and through primary care; these were categorised according to who the consultation was with (GP, nurse, counsellor, etc.) and where the consultation took place (in the surgery, by telephone, etc.). Data on all medication prescribed to trial participants during the12 months were also extracted in this way.

A self-completion questionnaire was issued to participants as part of the follow-up assessments at 4, 8 and 12 months, which provided information about resource use not available from GP records. Included were questions about the use of secondary care services for a mental health problem, use of walk-in centres, NHS Direct and social and community services and any time off work because of mental health problems. The questionnaire was devised to be as user-friendly as possible. The main questionnaire asked a series of ‘filter’ questions that required a simple ‘yes’ or ‘no’ response according to whether or not a particular service was used. If a participant replied ‘yes’ to any service they were contacted by a researcher and asked for detailed information, for example which outpatient clinic or service was used, to help with the costing. This two-stage method of questionnaire delivery was designed to make data collection as efficient as possible and to reduce the ambiguity of participants either failing to respond to a question because they had not used a particular service or just failing to answer a question.

Valuing the resource use

The unit costs and their sources which were used to estimate total cost per participant are given in Table 33. For the most part primary and community service costs were based on those provided by Lesley Curtis. 53 We used the Department of Health reference costs54 for secondary care, and the British National Formulary (BNF)55 for prescribed medication. Published research was used to estimate the cost of an out-of-hours contact,56,57 a call to NHS Direct58 and a visit to a walk-in centre. 59 All resources were valued in pounds sterling at 2009 prices, adjusting for inflation where necessary using the Hospital and Community Health Services Pay and Price Index. 53 Time off work was valued using the human capital approach; we used the median gross weekly earnings by age and sex. 60

The intervention

Resource use associated with the intervention was recorded by the PAFs. They noted details of all contacts with participants, face to face and by telephone; they also recorded time spent travelling to sessions, the number of non-contact phone calls, and letters, e-mails and text messages sent.

The principal cost of the intervention was the cost of the PAFs’ time spent directly with the participants and travelling to the sessions. In addition to this there were training sessions, ongoing supervision and some non-contact time. All time spent was valued according to salaries paid during the trial, except in the case of supervision. This was carried out by members of the trial team, but in the analysis it was costed at the rate of a senior nurse (Band 8) to reflect the likely situation if the intervention was widely adopted. Some participants received subsidies towards the cost of exercise; the PAFs noted these, the amount of the subsidy and the amount of administrative time spent dealing with them.

Quality-adjusted life-years

Data to estimate quality-adjusted life-year (QALY) gain were collected through the participant questionnaire, as described above. We used the European Quality of Life-5 Dimensions (EQ-5D),61 which was administered at baseline and at the 4, 8 and 12-month follow-ups. The EQ-5D is a generic measure of health-related quality of life, designed and widely used to estimate QALYs. The five domains of mobility, self-care, usual activities, pain/discomfort and anxiety/depression each have three possible levels of response relating to no problems, some problems and extreme problems. A subset of the 243 possible health states have been valued directly by a sample of the UK general population62 and these valuations have been used to derive a tariff of valuations for all possible health states. This tariff was used to estimate health-related quality of life for each participant at baseline and 4, 8 and 12 months and these were used to estimate QALY gain over the 12-month period.

Data analysis

The number of each item of resource used by participants in each group was investigated using descriptive statistics.

The total cost per participant was estimated by combining the number of each item of resource used with the unit cost of that item. This provided an estimate of mean cost per participant by group. The incremental cost of caring for participants in the intervention group compared with those in the control group is the difference in these mean costs and the CI indicates the level of uncertainty around this difference.

Quality-adjusted life-years were computed using the area under the curve approach, weighting the 12-month period by quality of life measured on a scale from 0 to 1. 63

Cost and QALY estimates were combined to provide an incremental cost-effectiveness ratio (ICER), showing the value of money spent on this intervention. We used the ‘bootstrapping’ technique to indicate the level of uncertainty around the ICER estimate. 64 A total of 5000 replicates of the ICER were generated and used to construct a cost-effectiveness plane and a cost-effectiveness acceptability curve. These indicate the probability that the intervention is cost-effective at any given level of willingness to pay for a QALY.

Base-case results used data with complete information, the ‘complete cases’. Missing cost and QALY data were imputed to allow comparison and to test the robustness of the base-case results. The multiple imputation by chained equation procedure was used. 65 The regression analyses used to impute missing cost data included age, gender, randomisation group, GP costs, secondary care costs and cost of the intervention as these were associated with missing outcome data. For the QALY regression, in addition to age, gender, randomisation group and EQ-5D scores, we also used the variables identified as being associated with missing data and included in the imputation of the clinical outcomes, namely baseline values for receipt of counselling, educational level, homeownership, weekly alcohol use, smoking and SF-12 physical component score (see Table 6).

Data completeness

Data were missing either because permission to interrogate GP records was not given or because questionnaires were not fully completed at all time points. The most complete data were those obtained from GP records (86% complete) and data for the cost of the intervention, where data were recorded by the PAFs. Complete cost data were available for 156 (43%) participants – 72 from the usual care group and 84 from the intervention group. Complete EQ-5D data to estimate QALYs were available for 195 (54%) participants, 92 usual care and 103 intervention. Complete cost and QALY data were available for 152 (42%) participants, 71 usual care and 81 intervention. The base-case cost-effectiveness results use complete cases (n = 152) but we also include results for all available data where possible to maximise transparency and aid interpretation of results.

Resource use

The mean number of NHS contacts by participant is shown in Table 34. Results in this table are based on all available information for each participant, giving a variable number of observations in each category. Data on GP and nurse consultations were available for over 86% of participants; of these, 98% had some contact with a GP during the year and 64% had some contact with a nurse. The median number of each type of consultation was 8 for GPs and 1 for nurses. In total, 95% of participants were issued with at least one prescription, with a mean number of 8.2 and a median of 6. Participants accessed a wide range of services through primary care. Secondary care encounters were less common: 56 outpatient visits were reported during the year by 13 participants, and 2 participants visited an A&E department. There was no evidence of a difference between the usual care group and the intervention group in any category of resource use.

Data on the use of social and community services revealed very low use. Eight participants recorded contacts with a community support worker, a mental health nurse or a social worker; nine recorded having been to a day centre or being part of a self-help group; and nine recorded contact with ‘other services’, which included voluntary sector groups such as Lifecycle (cycling support group). As the reported use of these services was so low, they were excluded from the cost analysis to prevent a small number of observations having a disproportionate effect on the results.

Table 35a gives data on time off work by participants and their carers. Of those who provided data (n = 178, 41%), 65% reported no time off due to their illness, and for those who did take time away from work the median length of time away was 40 days. The mean amount of time off work by those in the intervention group was twice that of those in the usual care group (Table 35b).

Cost of health-care services

Tables 36 and 37 provide information about the mean cost per participant by category of resource use. Table 36 is based on all available data and Table 37 is based on participants for whom we had complete cost data at all time points. Consultations by a GP accounted for > 60% of total health-care costs, excluding the cost of the intervention, and prescribed medication for > 20%. Comparing the two groups, the cost of primary care for those in the intervention group was greater than the cost for those in the usual care group, although these costs were very variable and there is no evidence of a statistical difference between the two groups. The cost of prescribed medication was also greater for those in the intervention group, giving a total difference in mean cost per participant of £39 (95% CI –£53 to £131).

Cost of intervention

Table 38 gives the breakdown of time spent by the PAFs dealing with participants. Time spent on face-to-face sessions was slightly longer than that spent on phone contacts, but nearly as much time was spent on travel associated with face-to-face sessions as on the sessions themselves.

The mean total cost of the intervention, allowing for training and supervision, and subsidies given to some participants, was £220 per participant for all 182 participants (Table 39) and £252 for those in the complete cost and QALY set, which includes 81(45%) of those in the intervention group.

Value of lost productivity

The value of lost productivity due to time off work is given in Table 35b. The participants in the intervention group reported considerably more time off work than those in the usual care group, resulting in a difference in mean cost per participant between the two groups of £1517.

Quality-adjusted life-years

The EQ-5D scores for each measurement period are shown in Figure 4, for three levels of data completeness. The general pattern is that participants for whom we had the most complete data scored more highly than those with missing data, and those in the intervention group had a higher score at 12 months post randomisation than those in the usual care group. The slight imbalance across the groups at baseline for the set with complete QALY data is reflected in the QALYs shown in Table 40; the effect of the higher scores is mitigated by lower baseline scores.

FIGURE 4.

European Quality of Life-5 Dimensions (EQ-5D) scores by group.

Cost-effectiveness

The point estimate of the incremental cost per QALY gain is £20,834 (Table 41) and the uncertainty around this estimate is illustrated in Figures 5 and 6. The probability that the intervention is cost-effective is 0.49 at a willingness to pay of £20,000 per QALY and 0.57 if the willingness to pay is £30,000 per QALY.

FIGURE 5.

Cost-effectiveness plane showing bootstrapped replicates of the ICER.

FIGURE 6.

Cost-effectiveness acceptability curve showing the probability that the intervention is cost-effective at different willingness-to-pay thresholds.

Sensitivity analysis: missing data

The results of imputing missing cost and QALY data are shown in Table 42. Compared with the complete case analysis, costs in the intervention group were lower because the participants for whom we did not have complete data (because of dropout, failure to complete questionnaires or withholding permission to interrogate GP records) were lower users of the intervention than those who provided complete data. QALY gain is lower in both groups although the difference between the two groups is unchanged.

The ICER for the intervention using the imputed data is £19,394, slightly lower than the complete case analysis (£20,834). The probabilities of a positive net monetary benefit are correspondingly slightly higher at 0.50 for the £20,000 threshold (compared with 0.49) and 0.60 for the £30,000 threshold (compared with 0.57) (see Table 42 and Figures 7 and 8).

FIGURE 7.

Cost-effectiveness plane showing bootstrapped replicates of the ICER – imputed data.

FIGURE 8.

Cost-effectiveness acceptability curve showing the probability that the intervention is cost-effectiveness at different willingness-to-pay thresholds – imputed data.

Methods

Participants’ views of physical activity as a treatment for depression

Physical activity undertaken by participants during the trial

During the 4- and 12-month interviews, participants in both arms of the trial were asked about any current physical activity they were doing, the type of activity and if they attributed any change in activity levels to trial participation. There did not appear to be clear differences between the levels and types of activity undertaken by participants in each arm of the trial. Participants in both arms of the trial described being more aware of the need to be more physically active and having made an effort to be so. In addition, the intervention and usual care participants who were engaging in physical activity tended to describe undertaking low-intensity activities, such as walking.

Many participants in both arms of the trial detailed how, through their participation in TREAD, they had developed an increased awareness of their activity levels. There was some evidence to suggest that this was an artefact of completing activity logs at baseline and for follow-up for the main study.

I think if anything it [the trial] has made me more encouraged to do more, even though I am not on that side of the study, it’s sort of still made me think, well I’ve taken a good look at how much activity I do, and I know I won’t do enough so it’s made me feel I want to push that little bit further to get myself fit and active again and feel a whole person instead of the half a person I feel at times.

(Female, 38 years, usual care, moderate depression, low active, urban, 4 months)

I think it [the trial] focused my mind a little bit in terms of thinking about exercise. What it really did, and what I found very interesting, was particularly recording. When we were looking at recording how much exercise you’re doing in a week on that chart, [I realised] how little I was doing [laughs].

(Male, 35 years, usual care, mild depression, low active, urban, 4 months)

A few participants had been regular exercisers before their episode of depression and were motivated to get back into a regular pattern of activity.

At the start of the TREAD study it was nothing, and it gradually picked up. So, it’s gradually becoming more and more frequent now. So I am trying to get back to where I was before but it’s a big gap to go from almost 4 months of non-participating to try and get it all back.

(Male, 21 years, usual care, moderate depression, medium active, urban, 4 months)

There were also a few intervention participants who had a strong history of engagement in physical activity who had returned to more specialised or higher-intensity activities after receiving facilitation.

The karate has become the main thing and it’s you know, it’s part of the routine now, so it happens. As I say, it has returned, so at least I’m getting kind of, you know, 2, 2.5 hours training a week, um which has to be beneficial. Um so yeah, I think it [PAF intervention] has been a significant factor without a doubt.

(Male, 43 years, intervention, moderate depression, medium active, rural, 12 months)

One participant in the usual care arm had started engaging in activity and attributed her engagement with activity to factors outside the trial, such as making a new year’s resolution to be more active and noting that a friend with depression always seemed better having been for a run or to the gym. Another usual care participant partly attributed his engagement in activity as a response to the boredom experienced from being signed off work as a result of having depression.

It was a knock-on effect. I had to do something, because I couldn’t sit at home and just fester away like I was. So, just going for walks, you know, if I wanted something from down-town I’d walk instead of jumping in the car, and things like that. And it just sort of morphed into bigger walks.

(Male, 46 years, usual care, mild depression, medium active, urban, 4 months)

Participants who received the intervention reported at both time points making efforts to be more physically active mainly as a result of their contact with the PAF, and how the input they had received had provided a ‘way in’ to making changes in physical activity.

I think that simply having the oversight of the facilitator has encouraged me to keep going with things.

(Male, 55 years, intervention, moderate depression, low active, rural, 4 months)

It had come to a stop really, apart from the odd walk. But what I did was to make a conscious effort to do something every day, or every other day, which is the promise I made [to the PAF]. And I more or less kept to that.

(Female, 66 years, intervention, moderate depression, low active, suburban, 4 months)

The PAF has been really good, and really helped a lot with the way I see things and do things although I have not been able to do a lot – but it has changed, it has actually changed what I do and made me question what I do. And part of me is thinking if I can start feeling a bit better within myself I might be more likely to do exercise or find the time to do exercise.

(Female, 45 years, intervention, moderate depression, medium active, suburban, 12 months)

Participants in the intervention arm, particularly women with children, detailed how they had incorporated activity into family life.

I’m trying to get out with the dog for nearly an hour every day. I have also been going out for run/walks with the kids – because the kids aren’t averse – they like to come out as well because I used to run and they would cycle and so I’ve been trying to build it around the children’s activities.

(Female, 40 years, intervention, mild depression, medium active, suburban, 4 months)

However, there were also a few male participants in the intervention group who reported that they did not make an effort to be more physically active as they were in manual occupations such as the construction industry and were often too tired to contemplate any additional activity and considered their daily tasks as adequate activity:

I am obviously quite active in work, lifting and walking all day. I’m usually too tired – by the time I get home from work I’m too knackered to do anything.

(Male, 38 years, intervention, mild depression, low active, suburban, 4 months)

I’m doing everyday tasks like gardening, walking, washing the car and I’ve also got work to keep me occupied.

(Male, 40 years, intervention, severe depression, low active, rural, 12 months)

Although many participants in both arms of the trial reported an intention to do more physical activity when interviewed at 4 months, there was little evidence during the 12-month interviews to suggest that levels of activity had increased over the intervening 8 months. Many participants in both arms reported that their activity level had remained at a similar level to that reported in the initial interview. Participants reported barriers such as time, work and family commitments as reasons for not engaging in activity.

Participants’ experiences of the facilitated physical activity intervention

Participants’ views and experiences of the usual care arm

Reasons for participation in TREAD

Participants reported many reasons for taking part in TREAD. The most common reason reported by participants in both trial arms was altruism – participating for the greater good and the sense of contributing to research that may help not only them but also others with depression. No participants mentioned that their involvement in the study was influenced by the possibility of superior clinical care or additional attention. However, some did say that they felt that the study would offer an alternative to the prescription of antidepressants. These participants were usually from the intervention arm.

I’m a great believer that if people with problems don’t volunteer for research, how are you ever going to solve the problems? I kind of looked at it and thought, well, I don’t know whether it’s likely to be effective and I don’t have an inkling as to what research has currently been done, but it was clearly written, you know all the information was well presented, and I followed it through. I think you get to a point where, from my perspective, all I ever get from the doctor is a pack of pills.

(Male, 44 years, intervention, moderate depression, low active, urban, 4 months)

I thought exercise would help – I was looking for ways to manage my depression without pills, to have things I could do when I came off pills again. I hate suffering with depression and I wouldn’t wish it on anybody, and if I can help to develop things that will help other people then that is a good thing as well.

(Female, 36 years, intervention, moderate depression, medium active, urban, 4 months)

Others simply wanted to cooperate with the recommendations of their GP or were demonstrating a high degree of trust in their relationship with their GP.

I was looking for anything that might help really, and my doctor said ‘give it a go’ – that’s all you have to go by really. If your doctor thinks it’s a good idea, then she’s probably right, you know. So, yeah, I thought, I’ll give it a go.

(Male, 35 years, usual care, moderate depression, low active, urban, 4 months)

A few participants participated because they were glad to have someone independent to talk to. There were also a few participants who had been active in the past and saw an opportunity to re-engage with activities that they had previously enjoyed which had diminished as a consequence of their depression.

There’s a factor there that made me think, yeah, this is probably the right kind of study for me because I used to enjoy this and would like to get back to enjoying it and whether that made it easier for me or not, I don’t know.

(Male, 43 years, intervention, severe depression, medium active, urban, 4 months)

Finally, there were some participants who detailed how they saw the study as a potential means of gaining general health benefits, such as weight loss, from being encouraged to become more physically active.

Strengths and limitations of the qualitative study

Interviewing participants in a trial of physical activity may have meant we interviewed a select group of participants who held particularly positive views about physical activity as a treatment for depression. The content of the patient information sheets may have had a priming effect for participants by introducing thoughts about physical activity that had not previously existed. However, such priming may not necessarily influence their ability to undertake activity and its acceptability among other treatments offered for depression in primary care. It is possible that some participants may have found physical activity more accessible when interviewed for the study at 4 months compared with 12 months because, for example, they had been signed off work by their GPs and thus had more time in which to engage in physical activity. Additionally, as intervention participants were followed up 4 months after receiving the last meeting or telephone call from the facilitator, the accuracy of memories of activity level and impact of facilitation may have diminished. Subsequently, this may have led to a misattribution with regard to engagement with physical activity or what they felt they had gained from the facilitation in terms of increases in activity and improvements in mood.

The 4-month interviews were largely conducted in participants’ homes with a researcher who was independent of the trial in which they participated. This may have helped to elicit a high degree of candour and openness from participants. The 12-month interviews were conducted by telephone. Participants appeared to remember the researcher when being contacted about the second interview, and we are aware that well-planned telephone interviews can gather the same material as those conducted face to face. 68 Although data collection was undertaken by one individual, several team members were involved in development of the coding frame and analysis of the data. By employing a purposeful sampling approach, we ensured that interviews were held with men and women in both trial arms who varied in terms of age and socioeconomic background. The generalisability of our findings, however, may be limited as participants were primarily white British, and depression is known to affect individuals of all ethnic backgrounds, who may have different views.

Summary of findings and implications

Participants in both arms of the trial perceived physical activity as an acceptable treatment that could enhance mood for a wide range of individuals with depression. The mechanisms by which participants believed that physical activity could enhance mood included biochemical pathways, distraction from negative thoughts and providing a sense of structure to daily life. Participants also reported other benefits of engaging in activity, such as facilitating social interaction, weight loss and regulation of sleep or eating patterns, which could lead to a holistic sense of well-being, which in turn increased self-esteem. However, the perceived cause of depression had a bearing on the extent to which participants thought that activity might be helpful, with it being suggested that it was less beneficial if depression was believed to be a function of situational factors as opposed to being of biochemical origin. In addition, participants who thought that depression was due to a biochemical imbalance rather than to situational factors tended to state that physical activity had to be aerobic in nature in order to be effective, whereas those believing that their depression was related to situational or adverse life events tended to report the benefits of less intense aerobic activities, such as walking.

There was some evidence that participants may prefer the ‘self-help’ aspect of engaging in physical activity as opposed to the passive nature of taking antidepressant medication, despite the fact that many were currently being treated with antidepressant medication. Previous work has shown that physical activity is primarily seen by patients as an alternative coping mechanism – a credible next step after prior stabilisation with medication. 69 In addition, physical activity may be viewed in a ‘self-regulatory’ way as a means of providing temporary relief from symptoms rather than as a cure for depression. 70 However, some participants suggested that prescribed medication had enabled them to initiate and maintain physical activity. It had helped them to overcome barriers to activity such as low levels of motivation and confidence, which may be a particular problem in patients with depression. It was with reference to these barriers that participants felt that it would be easier to take a pill than participate in regular activity, implying a recognition of problems overcoming the initiation and maintenance of physical activity as a treatment.

Most participants receiving the facilitated physical activity intervention stated that they were making a conscious effort to do more activity at both time points. However, it was also apparent that some participants in the usual care arm had made efforts to be more active in the trial period, suggesting that participation in the trial and exposure to information sheets and activity logs could have influenced behaviour in the usual care arm.

For many participants, motivation was an issue and there was a reliance on other parties for engaging in physical activity. Indeed, support for physical activity was often found in the sense of companionship experienced in attending classes or other activities with friends or relatives. Even if activity was being undertaken, access was an overarching barrier to physical activity for participants in both the usual care and intervention arms and was primarily related to cost and time. In fact, for many participants there was an assumption that to undertake physical activity there would be a need for gym membership or to sign up for structured classes held at sports centres.

The experience of the majority of patients receiving the intervention was very positive. For many the facilitation was considered to be tailored to the individual and gave participants someone who would listen objectively and in a non-judgemental manner. Most participants stated that both modes of delivery of the intervention (face to face and telephone calls) were of equal importance to them, but often for different reasons. The face-to-face sessions were important for putting a name to a face, building trust and developing a rapport with the PAF and could also be a reaffirming experience in a time of emotional distress and were therefore appropriate in this study involving participants with depression. With regard to the telephone calls over the 8-month programme it was clear that this method of delivery served to help the continuity of the relationship with the PAF. The telephone calls were for the most part seen as ‘friendly reminders’ that enabled participants to focus on their endeavours to be physically active and to discuss ways of overcoming barriers to activity. The telephone contacts also provided the participants with the opportunity for a more informal discussion of their emotional well-being in relation to receiving the intervention.

Finally, with regard to the paperwork elements of the intervention, the worksheets enabled participants to evaluate their work/life or family balance and the development of life skills. The physical activity logs also served a useful role in delineating the extent of physical activity undertaken and setting future goals. During the 12-month interviews participants did not talk of using the worksheets and logs during the later stages of the intervention. This was the case even for those who found them useful at 4 months, suggesting that such tools had served their purpose in the early stages of the intervention and their use by participants was not sustained throughout the intervention period.

Facilitated physical activity for managing depression

Participants in the intervention arm described how their PAF had provided emotional support and encouragement, given guidance, been sympathetic to their situation and listened carefully and objectively to what they had to say. Participants reported emotional benefits from the contact with the PAF. In addition, participants described how contact with their PAF had encouraged them to be more physically active. Physical activity was reported as leading to improvements in mood, and it was apparent that participants could experience these benefits both during and after an activity. Some participants even described feeling more mentally positive when simply planning to be active. However, participants who described improvements in mood usually attributed this to situational factors, such as changes in employment circumstances, or use of medication and the passing of time. Thus, physical activity was only one of various factors described as influencing mood and was not usually reported as the key factor. Yet participants who had received the intervention felt that they had gained a greater awareness of depression and had learned to reframe negative thoughts or behaviours in a more positive way. For some, such insight had assisted in the development of coping strategies that they could utilise in the future once the input from the PAF had ended.

Methods

Results

Views expressed by GPs were classified within four principal domains during the analyses. These were:

• practitioners’ views of physical activity as a treatment for depression

• promotion of physical activity in the consultation

• practitioners’ experiences of referring patients’ to TREAD and patient feedback

• impact of facilitated physical activity on general practice.

Summary and discussion

The majority of GPs felt that although physical activity could be helpful in treating depression it was best utilised as an adjunct treatment with antidepressant medication. Many GPs reported that they felt that the benefits of engaging in physical activity with respect to improving symptoms of depression would be through several mechanisms acting together. These included biochemical pathways, distraction, social interaction and providing structure to the day. Physical activity could be of low intensity such as walking and that could be a sufficient means of distraction from more ruminative forms of depression. GPs were aware of many barriers associated with recommending physical activity to depressed patients. There were practical barriers such as time and access to facilities and the burden of comorbid conditions. In addition, GPs described issues relating to patients’ levels of motivation, confidence and self-efficacy such that a recommendation to be active may exacerbate feelings of low self-esteem if a patient was not successful in initiating or maintaining an activity.

There was also awareness among GPs that many patients were looking for alternative approaches to treating depression, or at least would like to be more autonomous in their care and less reliant on medication. Such views are also in alignment with patients’ views of physical activity for depression. 67 Previous work has shown that physical activity is primarily seen by patients as an alternative coping mechanism – a credible next step after prior stabilisation with medication. 69 In addition, physical activity may be viewed in a ‘self-regulatory’ way as a means of providing temporary relief from symptoms rather than as a cure for depression. 70 Thus, together, these studies demonstrate some acceptability of promoting physical activity as a treatment in primary care for mild depression from the perspective of both doctors and patients. With regard to the utility of facilitated activity, some GPs cited a lack of alternative and effective strategies for dealing with mild to moderate depression, suggesting that facilitated activity might fill the gap.

Finally, the extent of positive views of physical activity for managing depression, particularly when combined with the fact that few cited any scientific evidence for its effectiveness, would suggest that bias may be present in the sample. Although all GPs were from practices participating in the trial, not all had referred patients to the study. This could indicate variation in commitment to physical activity as a treatment for depression. However, it could also reflect variation between the GPs in their attitudes towards recruiting participants for trials, how frequently they saw depressed patients meeting the criteria for our trial or how busy they were.

1a) Research objectives

The primary research question is ‘Does physical activity, in addition to usual care in primary health care, change the outcome in depression and alter the subsequent use of antidepressant medication?’

1b) Existing research

Depression is one of the leading reasons for disability in the UK, as elsewhere, and is the third most common reason for consulting a general practitioner. There are now over 25m prescriptions of antidepressants each year in primary care in England that cost £80m (www.ppa.org.uk). Antidepressants are an effective treatment for the more severe depressions but there is uncertainty and concern about the use of antidepressants, especially in those with mild depression. Adherence to antidepressant treatment is often poor and only about 20% of patients will take medication according to guidelines. 1,2 There is widespread scepticism about the effectiveness of antidepressants amongst the general population and this may contribute to a reluctance to consult general practitioners for depression. 3 Hence, there is a need to identify effective non-pharmacological interventions for the management of the common, less severe forms of depression and as a potential means of reducing the length of treatment with pharmacological agents.

2a) Study design

We are proposing a two-arm, multi-centre, pragmatic, randomised controlled trial with randomisation at the level of the individual participant.

2b) Recruitment

Recruitment will take place over a 27-month period, predominantly in general practices that are currently part of the well established primary care R & D networks in Bristol (Avon Consortium – 20 practices) and Exeter (PenRen – 40 practices). We will ask GPs to refer patients whom they have just started on antidepressant medication for depression and also depressed patients who are not currently on antidepressant medication but who wish to pursue further treatment for their condition. We will use a variety of means to encourage referral to the trial. These will include stickers, posters, newsletters and other publicity. We will also screen practice computer systems for people who have recently been diagnosed as depressed or given an antidepressant, in order to recruit additional participants who have not been referred by their GP to the trial via consultation.

The two GP research networks we plan to use have a strong track record in carrying out research and both have experience and commitment to mental health trials. We will be providing a well thought out package as the intervention and this will help to gain the confidence of the GPs and encourage recruitment. The GP will ask patients diagnosed with depression if they are interested in taking part in the trial and suggest that they release their personal details to the research team for further contact. Once given permission to contact the patient, a Research Assistant will perform the baseline assessment, confirm eligibility and obtain informed consent. For participants randomised to the intervention arm, an appointment will be made to meet the Physical Activity Facilitator in the general practice, at the research office, or in the patient’s home. For those randomised to the control arm, the participant will be asked to continue with their usual GP care.

2c) Planned interventions

The principles behind the intervention have been described already in Section 1b. We propose to develop an intervention manual, based on the NHS National Quality Assurance Framework for Exercise Referral Schemes (NQAF) and the existing referral scheme in Somerset (in operation for over 10 years) which involves a trained exercise facilitator. The patients in receipt of the intervention will be given a list of local physical activity options, in addition to support from the Physical Activity Facilitator.

2d) Planned inclusion/exclusion criteria

We seek to recruit people with mild and moderate depression who are beginning a new episode of depression. We will, therefore, include people aged 18–69 who have either recently started antidepressants (within 4 weeks of their assessment and following an antidepressant free period of at least 1 month) or who are not currently on antidepressants but have recently consulted their GP for depression. The baseline assessment will use the revised Clinical Interview Schedule (CIS-R)36 administered by computer in order to make an ICD-10 diagnosis of depression (F32), a criteria for inclusion in the trial. The participants will also have to score 14 or more on the Beck Depression Inventory37 (BDI), in order to ensure that there is room for improvement in our primary outcome. Other exclusions will cover any medical contraindications to physical activity,38 inability to complete self-administered questionnaires in English, psychosis, bipolar disorder and any serious drug or alcohol abuse. Women who are pregnant at the time of recruitment will automatically be excluded from the trial but those who become pregnant during the trial may continue, providing they have approval and permission to do so from their GP. We will request consent from patients referred by the GP to use basic demographic information as a means of describing those who are excluded from the trial in comparison with those who do take part

2e) Ethical issues

We do not think this trial will raise any particular ethical issues. We are not interfering with the usual clinical care of participants. The physical activity intervention is an extra intervention in addition to GP usual care. We are obtaining valid informed consent from the subjects. The lack of a clear effect of physical activity in the treatment of depression from the most up-to-date systematic review5 shows that there is clinical equipoise. Finally, participants can still receive antidepressants, counselling or psychotherapy during the course of the trial, if this proves necessary or desirable.

2f) Proposed baseline and outcome measures

2g) Economic data & analysis

The aim of the economic evaluation is to compare the costs and benefits of physical activity in addition to usual care with usual care alone for primary care patients with depression. These two proposed methods of patient care will be compared from the viewpoint of: (i) the National Health Service (NHS) and personal social services (PSS), (ii) patients and carers, and (iii) society. 48 The analysis will be based on the costs incurred over the 12 months following randomisation, measured at baseline, 4, 8 and 12 months.

Resources used by all patients will be identified, measured and valued. The principal costs to the health care provider will relate to the cost of the intervention, primary and secondary health care contacts, and medication. Patients and carers are likely to incur travel costs, use of alternative therapies, loss of income, and home support costs such as childcare. Societal costs will relate to lost production due to time off work. We will collect patient level data from routine sources such as practice records, as well as a patient questionnaire based on the Client Service Receipt Inventory,49 which has been used elsewhere to assess the costs of treating mental illness. This will be adapted to suit this study, this patient group and for postal administration.

Health care resources will be valued using published national sources, for example, Unit Costs of Health and Social Care and the British National Formulary. The cost of the intervention will be based on the cost of its provision in the trial, but any protocol-driven research costs will be excluded. Informal care giving will be valued using the principle of opportunity cost, so the shadow price of informal care will be estimated as the unit cost of a home care worker. In valuing lost production, we will follow the recommendations of Drummond. 50 Productivity losses will be reported separately and measured in terms of days lost. We will estimate the value of lost production using the ‘friction’ approach, a variation of the ‘human capital’ approach, which includes only the resources required to replace the employee. Costs and outcomes at 12 months will be discounted at the recommended rate of 3.5%. 50 Costs will be related to the primary clinical outcome of the trial (BDI) and quality of life as measured by the EQ-5D. 40

It is our intention that incremental cost-effectiveness ratios will be formed comparing (i) the cost per extra patient recovering; (ii) the cost per depression free days; and (ii) the cost per QALY gain, for each of the proposed treatments. Sensitivity analyses will be conducted in those areas where there is uncertainty around assumptions about resource use measurement and/or valuation. Patient variation in resource use and the effectiveness of the intervention will be captured using ‘bootstrapping’ to construct a cost effectiveness acceptability curve. 51

2h) Feasibility Phase

2i) Sample size justification

Our original power calculation anticipated that about 60% of participants in the usual care group and 73% in the intervention group would have recovered by 4-month follow-up – scoring < 10 on the BDI. This difference of 13% in the proportion ‘recovered’, equivalent to an odds ratio of 1.8, is consistent with the lower end of treatment effects observed with antidepressant medication, but is still substantial and worth detecting for a common condition such as depression and for an intervention with other possible health benefits such as physical activity. With 90% power and 5% two-sided alpha, this would require 291 patients per group.

When using the BDI as a continuous outcome, previous studies have estimated a standard deviation of about 9 points,52 and have suggested that a worthwhile and feasible target difference is about 3–4 points. With 5% two-sided alpha, a sample size of 291 per group will afford 98 to > 99% power to detect a difference of 0.33 to 0.44 standard deviations. Furthermore, it will yield a derived margin of error for the difference between the randomised groups of approximately 0.16 standard deviations, equivalent to 95% CIs on the BDI scale of approximately 1.5 to 4.5 and 2.5 to 5.5 for estimated differences of 3 and 4 respectively.

The table below presents original estimates for numbers required to be recruited for different powers and proportions of patients not on antidepressants at baseline, allowing for an attrition rate of 15%, and based on detecting an odds ratio of 1.8 with 5% two-sided alpha.

Assuming that 10% of the sample would not be on antidepressant treatment when recruited, and that, overall, there would be a 10–15% attrition rate, the sample size specification above required 291 per group to be available for analysis. In order to achieve this, the total number that will need to be recruited, depending on the attrition rate, would be between 720 and 762 [(291*2)/(0.9*0.9) to (291*2)/(0.9*0.85)]. We, therefore, proposed to recruit 762 participants at the outset.

However, our initial calculation made a number of assumptions about:

• recruitment rate

• antidepressant use

• recovery rate at 4-month follow-up

• follow-up rate

2j) Statistical analysis

The analysis and presentation of this pragmatic randomised trial data will be in accordance with CONSORT guidelines,53 with the primary comparative analyses being conducted on an intention-to-treat basis and due emphasis placed on confidence intervals for the between-arm comparisons. Descriptive statistics of socio-demographic and clinical measures will be used to detect any marked imbalance between the arms at baseline. As described previously, we intend to make full use of BDI as both a binary and continuous outcome measure in the interpretation of the results of this trial. Although unusual we, therefore, specify two primary analyses. These primary comparative analyses will employ multivariable logistic or linear regression, as appropriate, to investigate differences between the groups, adjusting for minimisation variables and baseline BDI amongst those medicating at baseline. For the binary outcome, the comparison will be presented as an odds ratio of recovery (scoring < 10 on the BDI) in the intervention group compared with the control group. For BDI as a continuous measure, the comparison will be presented as a difference in group mean scores. For both outcomes we will also present 95% confidence intervals and p-values.

Sensitivity analyses, making different assumptions such as ‘best’ and ‘worst’ case scenarios as well as imputation models of ‘missingness’, will be conducted to investigate the potential impact of missing data. We will also investigate the extent and impact on the results of clustering by general practice and possibly Physical Activity Facilitator; although the small number of facilitators will mean that investigation of such effects will be limited. In the absence of adequate power to formally test for differential effects according to antidepressant therapy at baseline, we will investigate the patterns of confidence intervals for both subsets of patients separately and combined.

In addition to carrying out the same analyses for the secondary outcomes (where p-values will be adjusted to account for multiple testing), and to repeating any such primary analyses adjusted also for any variables exhibiting marked imbalance at baseline, the secondary analyses for this trial will take three general forms:

1. investigation of process measures such as adherence to the physical activity programme, use of antidepressants, counselling and social support. Mostly these will be descriptive analyses, but this information will be used to investigate whether adherence to the physical activity programme is associated with ‘recovery’, and will also be employed within the economic evaluation.

2. some of this process data will also be employed in secondary, explanatory analyses that attempt to explain the comparisons between the two treatment arms from the intention-to-treat analyses. This will be investigated by adjusting for factors such as adherence to the physical activity programme in the intervention group, but also reported activity levels in both groups. The models employed will be essentially the same as those for the primary analyses. In addition, we will investigate the patterns of BDI scores (as a continuous measure) between the groups at the 4, 8 and 12- month follow-up using repeated measures (random effects) linear regression, adjusting for baseline BDI, minimisation factors, and any other variables displaying imbalances at baseline. Divergence or convergence between the two groups over time will also be investigated using appropriate interaction terms.

3. thirdly, appropriate interaction terms will be entered into the primary regression analyses for BDI as both a binary and continuous outcome. in order to conduct pre-specified subgroup analyses according to baseline severity of depression (CIS-R score of ≤ 25, 26–33, 34+ at baseline) and baseline physical activity level (≤ 1, 2–3, 4+ days per week where at least 30 minutes of moderate intensity physical activity is undertaken). Since the trial is powered to detect overall differences between the groups rather than any interactions terms, the results of these exploratory analyses will be presented using confidence intervals as well as p-values, and interpreted with due caution.

2k) Qualitative Study

Qualitative methods can be an essential part of a trial’s evaluation and can provide another perspective on a trial’s results from those provided by the quantitative analysis. Within TREAD, results from a qualitative study could help us understand why the physical activity intervention, in addition to usual GP care, was or was not effective in changing the outcome of depression and/or altering subsequent use of antidepressants. We, therefore, suggest that the qualitative work is not restricted to the feasibility phase of the trial but also extends into the main trial.

The main aim of the qualitative study will be to explore patients’, health professionals’ and Physical Activity Facilitators’ views and experiences of the physical activity intervention, in order to assess its acceptability and to illuminate possible reasons for the quantitative results. Study objectives are to:

• assess patients’ views and experiences of the physical activity intervention

• identify patients’ reasons for accepting, declining, adhering to or withdrawing from the intervention

• explore health professionals’ views of the intervention and its impact on general practice

• assess the Physical Activity Facilitators’ views and experiences of providing the intervention

2l) Management and supervision of trial

Many of the Bristol Co-applicants are based in the Department of Community based Medicine at Bristol University (GL, DS, TP, NW, AM, SH) whilst the Department of Exercise, Nutrition and Health Science (KF, AH) is on the same University precinct, as is the Department of Social Medicine (MCal, DL). Exeter (JC, AT) is 75 minutes drive from Bristol, with regular train services between the two cities. We will have a full-time Trial Co-ordinator based in Bristol who has overall responsibility for the trial. The Trial Co-ordinator will develop the detailed protocol, finalise baseline and follow-up assessments, manage the Research Assistants, maintain the central database and coordinate meetings of the management group and Trial Steering Committee. They will also take the lead in the data analysis and preparation of final reports with the assistance of the Co-applicants when needed. A number of Research Assistants will be based in both Bristol and Exeter. Their primary role will be to conduct baseline assessments, obtain consent and activate the randomisation procedure. The administrators will arrange appointments and send out the mailings for follow-up assessments, working alongside the Research Assistants, for the Trial Co-ordinator. A research management group comprising GL, NW, JC, AM, SH, the Trial Co-ordinator, Research Assistants and administrators will meet monthly. KF, AH, AT, DL will attend regular meetings, when required, to supervise the physical activity element of the trial. A Trial Steering Committee (TSC) and Data Monitoring and Ethics Committee (DMEC) will be appointed based upon MRC guidelines and after approval from the HTA.

The Co-applicants are all in WestHub, part of the Mental Health Research Network (MHRN). The study will be adopted by both the MHRN and PCRN and this will give us access to the infrastructure to help with ethics applications, research governance and recruitment. The study will also benefit from the experience gained from existing HTA and MRC treatment trials of depression in Bristol.

Prioritisation Group

1. Director, NIHR HTA programme, Professor of Clinical Pharmacology, University of Liverpool

2. Professor Imti Choonara, Professor in Child Health, Academic Division of Child Health, University of Nottingham

   Chair – Pharmaceuticals Panel

3. Dr Bob Coates, Consultant Advisor – Disease Prevention Panel

4. Dr Andrew Cook, Consultant Advisor – Intervention Procedures Panel

5. Dr Peter Davidson, Director of NETSCC, Health Technology Assessment

6. Dr Nick Hicks, Consultant Adviser – Diagnostic Technologies and Screening Panel, Consultant Advisor–Psychological and Community Therapies Panel

7. Ms Susan Hird, Consultant Advisor, External Devices and Physical Therapies Panel

8. Professor Sallie Lamb, Director, Warwick Clinical Trials Unit, Warwick Medical School, University of Warwick

   Chair – HTA Clinical Evaluation and Trials Board

9. Professor Jonathan Michaels, Professor of Vascular Surgery, Sheffield Vascular Institute, University of Sheffield

   Chair – Interventional Procedures Panel

10. Professor Ruairidh Milne, Director – External Relations

11. Dr John Pounsford, Consultant Physician, Directorate of Medical Services, North Bristol NHS Trust

    Chair – External Devices and Physical Therapies Panel

12. Dr Vaughan Thomas, Consultant Advisor – Pharmaceuticals Panel, Clinical

    Lead – Clinical Evaluation Trials Prioritisation Group

13. Professor Margaret Thorogood, Professor of Epidemiology, Health Sciences Research Institute, University of Warwick

    Chair – Disease Prevention Panel

14. Professor Lindsay Turnbull, Professor of Radiology, Centre for the MR Investigations, University of Hull

    Chair – Diagnostic Technologies and Screening Panel

15. Professor Scott Weich, Professor of Psychiatry, Health Sciences Research Institute, University of Warwick

    Chair – Psychological and Community Therapies Panel

16. Professor Hywel Williams, Director of Nottingham Clinical Trials Unit, Centre of Evidence-Based Dermatology, University of Nottingham

    Chair – HTA Commissioning Board

    Deputy HTA Programme Director

HTA Commissioning Board

1. Professor of Dermato-Epidemiology, Centre of Evidence-Based Dermatology, University of Nottingham

2. Department of Public Health and Epidemiology, University of Birmingham

3. Professor of Clinical Pharmacology, Director, NIHR HTA programme, University of Liverpool

1. Professor Ann Ashburn, Professor of Rehabilitation and Head of Research, Southampton General Hospital

2. Professor Judith Bliss, Director of ICR-Clinical Trials and Statistics Unit, The Institute of Cancer Research

3. Professor Peter Brocklehurst, Professor of Women’s Health, Institute for Women’s Health, University College London

4. Professor David Fitzmaurice, Professor of Primary Care Research, Department of Primary Care Clinical Sciences, University of Birmingham

5. Professor John W Gregory, Professor in Paediatric Endocrinology, Department of Child Health, Wales School of Medicine, Cardiff University

6. Professor Steve Halligan, Professor of Gastrointestinal Radiology, University College Hospital, London

7. Professor Angela Harden, Professor of Community and Family Health, Institute for Health and Human Development, University of East London

8. Dr Martin J Landray, Reader in Epidemiology, Honorary Consultant Physician, Clinical Trial Service Unit, University of Oxford

9. Dr Joanne Lord, Reader, Health Economics Research Group, Brunel University

10. Professor Stephen Morris, Professor of Health Economics, University College London, Research Department of Epidemiology and Public Health, University College London

11. Professor Dion Morton, Professor of Surgery, Academic Department of Surgery, University of Birmingham

12. Professor Gail Mountain, Professor of Health Services Research, Rehabilitation and Assistive Technologies Group, University of Sheffield

13. Professor Irwin Nazareth, Professor of Primary Care and Head of Department, Department of Primary Care and Population Sciences, University College London

14. Professor E Andrea Nelson, Professor of Wound Healing and Director of Research, School of Healthcare, University of Leeds

15. Professor John David Norrie, Chair in Clinical Trials and Biostatistics, Robertson Centre for Biostatistics, University of Glasgow

16. Dr Rafael Perera, Lecturer in Medical Statisitics, Department of Primary Health Care, University of Oxford

17. Professor Barney Reeves, Professorial Research Fellow in Health Services Research, Department of Clinical Science, University of Bristol

18. Professor Peter Tyrer, Professor of Community Psychiatry, Centre for Mental Health, Imperial College London

19. Professor Martin Underwood, Professor of Primary Care Research, Warwick Medical School, University of Warwick

20. Professor Caroline Watkins, Professor of Stroke and Older People’s Care, Chair of UK Forum for Stroke Training, Stroke Practice Research Unit, University of Central Lancashire

21. Dr Duncan Young, Senior Clinical Lecturer and Consultant, Nuffield Department of Anaesthetics, University of Oxford

1. Dr Tom Foulks, Medical Research Council

2. Dr Kay Pattison, Senior NIHR Programme Manager, Department of Health

HTA Clinical Evaluation and Trials Board

1. Director, Warwick Clinical Trials Unit, Warwick Medical School, University of Warwick and Professor of Rehabilitation, Nuffield Department of Orthopaedic, Rheumatology and Musculoskeletal Sciences, University of Oxford

2. Professor of the Psychology of Health Care, Leeds Institute of Health Sciences, University of Leeds

3. Director, NIHR HTA programme, Professor of Clinical Pharmacology, University of Liverpool

1. Professor Keith Abrams, Professor of Medical Statistics, Department of Health Sciences, University of Leicester

2. Professor Martin Bland, Professor of Health Statistics, Department of Health Sciences, University of York

3. Professor Jane Blazeby, Professor of Surgery and Consultant Upper GI Surgeon, Department of Social Medicine, University of Bristol

4. Professor Julia M Brown, Director, Clinical Trials Research Unit, University of Leeds

5. Professor Alistair Burns, Professor of Old Age Psychiatry, Psychiatry Research Group, School of Community-Based Medicine, The University of Manchester & National Clinical Director for Dementia, Department of Health

6. Dr Jennifer Burr, Director, Centre for Healthcare Randomised trials (CHART), University of Aberdeen

7. Professor Linda Davies, Professor of Health Economics, Health Sciences Research Group, University of Manchester

8. Professor Simon Gilbody, Prof of Psych Medicine and Health Services Research, Department of Health Sciences, University of York

9. Professor Steven Goodacre, Professor and Consultant in Emergency Medicine, School of Health and Related Research, University of Sheffield

10. Professor Dyfrig Hughes, Professor of Pharmacoeconomics, Centre for Economics and Policy in Health, Institute of Medical and Social Care Research, Bangor University

11. Professor Paul Jones, Professor of Respiratory Medicine, Department of Cardiac and Vascular Science, St George‘s Hospital Medical School, University of London

12. Professor Khalid Khan, Professor of Women’s Health and Clinical Epidemiology, Barts and the London School of Medicine, Queen Mary, University of London

13. Professor Richard J McManus, Professor of Primary Care Cardiovascular Research, Primary Care Clinical Sciences Building, University of Birmingham

14. Professor Helen Rodgers, Professor of Stroke Care, Institute for Ageing and Health, Newcastle University

15. Professor Ken Stein, Professor of Public Health, Peninsula Technology Assessment Group, Peninsula College of Medicine and Dentistry, Universities of Exeter and Plymouth

16. Professor Jonathan Sterne, Professor of Medical Statistics and Epidemiology, Department of Social Medicine, University of Bristol

17. Mr Andy Vail, Senior Lecturer, Health Sciences Research Group, University of Manchester

18. Professor Clare Wilkinson, Professor of General Practice and Director of Research North Wales Clinical School, Department of Primary Care and Public Health, Cardiff University

19. Dr Ian B Wilkinson, Senior Lecturer and Honorary Consultant, Clinical Pharmacology Unit, Department of Medicine, University of Cambridge

1. Ms Kate Law, Director of Clinical Trials, Cancer Research UK

2. Dr Morven Roberts, Clinical Trials Manager, Health Services and Public Health Services Board, Medical Research Council

Diagnostic Technologies and Screening Panel

1. Scientific Director of the Centre for Magnetic Resonance Investigations and YCR Professor of Radiology, Hull Royal Infirmary

2. Professor Judith E Adams, Consultant Radiologist, Manchester Royal Infirmary, Central Manchester & Manchester Children’s University Hospitals NHS Trust, and Professor of Diagnostic Radiology, University of Manchester

3. Mr Angus S Arunkalaivanan, Honorary Senior Lecturer, University of Birmingham and Consultant Urogynaecologist and Obstetrician, City Hospital, Birmingham

4. Dr Diana Baralle, Consultant and Senior Lecturer in Clinical Genetics, University of Southampton

5. Dr Stephanie Dancer, Consultant Microbiologist, Hairmyres Hospital, East Kilbride

6. Dr Diane Eccles, Professor of Cancer Genetics, Wessex Clinical Genetics Service, Princess Anne Hospital

7. Dr Trevor Friedman, Consultant Liason Psychiatrist, Brandon Unit, Leicester General Hospital

8. Dr Ron Gray, Consultant, National Perinatal Epidemiology Unit, Institute of Health Sciences, University of Oxford

9. Professor Paul D Griffiths, Professor of Radiology, Academic Unit of Radiology, University of Sheffield

10. Mr Martin Hooper, Public contributor

11. Professor Anthony Robert Kendrick, Associate Dean for Clinical Research and Professor of Primary Medical Care, University of Southampton

12. Dr Nicola Lennard, Senior Medical Officer, MHRA

13. Dr Anne Mackie, Director of Programmes, UK National Screening Committee, London

14. Mr David Mathew, Public contributor

15. Dr Michael Millar, Consultant Senior Lecturer in Microbiology, Department of Pathology & Microbiology, Barts and The London NHS Trust, Royal London Hospital

16. Mrs Una Rennard, Public contributor

17. Dr Stuart Smellie, Consultant in Clinical Pathology, Bishop Auckland General Hospital

18. Ms Jane Smith, Consultant Ultrasound Practitioner, Leeds Teaching Hospital NHS Trust, Leeds

19. Dr Allison Streetly, Programme Director, NHS Sickle Cell and Thalassaemia Screening Programme, King’s College School of Medicine

20. Dr Matthew Thompson, Senior Clinical Scientist and GP, Department of Primary Health Care, University of Oxford

21. Dr Alan J Williams, Consultant Physician, General and Respiratory Medicine, The Royal Bournemouth Hospital

1. Dr Tim Elliott, Team Leader, Cancer Screening, Department of Health

2. Dr Joanna Jenkinson, Board Secretary, Neurosciences and Mental Health Board (NMHB), Medical Research Council

3. Professor Julietta Patrick, Director, NHS Cancer Screening Programme, Sheffield

4. Dr Kay Pattison, Senior NIHR Programme Manager, Department of Health

5. Professor Tom Walley, CBE, Director, NIHR HTA programme, Professor of Clinical Pharmacology, University of Liverpool

6. Dr Ursula Wells, Principal Research Officer, Policy Research Programme, Department of Health

Disease Prevention Panel

1. Professor of Epidemiology, University of Warwick Medical School, Coventry

2. Dr Robert Cook, Clinical Programmes Director, Bazian Ltd, London

3. Dr Colin Greaves, Senior Research Fellow, Peninsula Medical School (Primary Care)

4. Mr Michael Head, Public contributor

5. Professor Cathy Jackson, Professor of Primary Care Medicine, Bute Medical School, University of St Andrews

6. Dr Russell Jago, Senior Lecturer in Exercise, Nutrition and Health, Centre for Sport, Exercise and Health, University of Bristol

7. Dr Julie Mytton, Consultant in Child Public Health, NHS Bristol

8. Professor Irwin Nazareth, Professor of Primary Care and Director, Department of Primary Care and Population Sciences, University College London

9. Dr Richard Richards, Assistant Director of Public Health, Derbyshire County Primary Care Trust

10. Professor Ian Roberts, Professor of Epidemiology and Public Health, London School of Hygiene & Tropical Medicine

11. Dr Kenneth Robertson, Consultant Paediatrician, Royal Hospital for Sick Children, Glasgow

12. Dr Catherine Swann, Associate Director, Centre for Public Health Excellence, NICE

13. Mrs Jean Thurston, Public contributor

14. Professor David Weller, Head, School of Clinical Science and Community Health, University of Edinburgh

1. Ms Christine McGuire, Research & Development, Department of Health

2. Dr Kay Pattison, Senior NIHR Programme Manager, Department of Health

3. Professor Tom Walley, CBE, Director, NIHR HTA programme, Professor of Clinical Pharmacology, University of Liverpool

External Devices and Physical Therapies Panel

1. Consultant Physician North Bristol NHS Trust

2. Reader in Wound Healing and Director of Research, University of Leeds

3. Professor Bipin Bhakta, Charterhouse Professor in Rehabilitation Medicine, University of Leeds

4. Mrs Penny Calder, Public contributor

5. Dr Dawn Carnes, Senior Research Fellow, Barts and the London School of Medicine and Dentistry

6. Dr Emma Clark, Clinician Scientist Fellow & Cons. Rheumatologist, University of Bristol

7. Mrs Anthea De Barton-Watson, Public contributor

8. Professor Nadine Foster, Professor of Musculoskeletal Health in Primary Care Arthritis Research, Keele University

9. Dr Shaheen Hamdy, Clinical Senior Lecturer and Consultant Physician, University of Manchester

10. Professor Christine Norton, Professor of Clinical Nursing Innovation, Bucks New University and Imperial College Healthcare NHS Trust

11. Dr Lorraine Pinnigton, Associate Professor in Rehabilitation, University of Nottingham

12. Dr Kate Radford, Senior Lecturer (Research), University of Central Lancashire

13. Mr Jim Reece, Public contributor

14. Professor Maria Stokes, Professor of Neuromusculoskeletal Rehabilitation, University of Southampton

15. Dr Pippa Tyrrell, Senior Lecturer/Consultant, Salford Royal Foundation Hospitals’ Trust and University of Manchester

16. Dr Nefyn Williams, Clinical Senior Lecturer, Cardiff University

1. Dr Kay Pattison, Senior NIHR Programme Manager, Department of Health

2. Dr Morven Roberts, Clinical Trials Manager, Health Services and Public Health Services Board, Medical Research Council

3. Professor Tom Walley, CBE, Director, NIHR HTA programme, Professor of Clinical Pharmacology, University of Liverpool

4. Dr Ursula Wells, Principal Research Officer, Policy Research Programme, Department of Health

Interventional Procedures Panel

1. Professor of Vascular Surgery, University of Sheffield

2. Consultant Colorectal Surgeon, Bristol Royal Infirmary

3. Mrs Isabel Boyer, Public contributor

4. Mr Sankaran Chandra Sekharan, Consultant Surgeon, Breast Surgery, Colchester Hospital University NHS Foundation Trust

5. Professor Nicholas Clarke, Consultant Orthopaedic Surgeon, Southampton University Hospitals NHS Trust

6. Ms Leonie Cooke, Public contributor

7. Mr Seumas Eckford, Consultant in Obstetrics & Gynaecology, North Devon District Hospital

8. Professor Sam Eljamel, Consultant Neurosurgeon, Ninewells Hospital and Medical School, Dundee

9. Dr Adele Fielding, Senior Lecturer and Honorary Consultant in Haematology, University College London Medical School

10. Dr Matthew Hatton, Consultant in Clinical Oncology, Sheffield Teaching Hospital Foundation Trust

11. Dr John Holden, General Practitioner, Garswood Surgery, Wigan

12. Dr Fiona Lecky, Senior Lecturer/Honorary Consultant in Emergency Medicine, University of Manchester/Salford Royal Hospitals NHS Foundation Trust

13. Dr Nadim Malik, Consultant Cardiologist/Honorary Lecturer, University of Manchester

14. Mr Hisham Mehanna, Consultant & Honorary Associate Professor, University Hospitals Coventry & Warwickshire NHS Trust

15. Dr Jane Montgomery, Consultant in Anaesthetics and Critical Care, South Devon Healthcare NHS Foundation Trust

16. Professor Jon Moss, Consultant Interventional Radiologist, North Glasgow Hospitals University NHS Trust

17. Dr Simon Padley, Consultant Radiologist, Chelsea & Westminster Hospital

18. Dr Ashish Paul, Medical Director, Bedfordshire PCT

19. Dr Sarah Purdy, Consultant Senior Lecturer, University of Bristol

20. Dr Matthew Wilson, Consultant Anaesthetist, Sheffield Teaching Hospitals NHS Foundation Trust

21. Professor Yit Chiun Yang, Consultant Ophthalmologist, Royal Wolverhampton Hospitals NHS Trust

1. Dr Kay Pattison, Senior NIHR Programme Manager, Department of Health

2. Dr Morven Roberts, Clinical Trials Manager, Health Services and Public Health Services Board, Medical Research Council

3. Professor Tom Walley, CBE, Director, NIHR HTA programme, Professor of Clinical Pharmacology, University of Liverpool

4. Dr Ursula Wells, Principal Research Officer, Policy Research Programme, Department of Health

Pharmaceuticals Panel

1. Professor in Child Health, University of Nottingham

2. Senior Lecturer in Clinical Pharmacology, University of East Anglia

3. Dr Martin Ashton-Key, Medical Advisor, National Commissioning Group, NHS London

4. Dr Peter Elton, Director of Public Health, Bury Primary Care Trust

5. Dr Ben Goldacre, Research Fellow, Division of Psychological Medicine and Psychiatry, King’s College London

6. Dr James Gray, Consultant Microbiologist, Department of Microbiology, Birmingham Children’s Hospital NHS Foundation Trust

7. Dr Jurjees Hasan, Consultant in Medical Oncology, The Christie, Manchester

8. Dr Carl Heneghan, Deputy Director Centre for Evidence-Based Medicine and Clinical Lecturer, Department of Primary Health Care, University of Oxford

9. Dr Dyfrig Hughes, Reader in Pharmacoeconomics and Deputy Director, Centre for Economics and Policy in Health, IMSCaR, Bangor University

10. Dr Maria Kouimtzi, Pharmacy and Informatics Director, Global Clinical Solutions, Wiley-Blackwell

11. Professor Femi Oyebode, Consultant Psychiatrist and Head of Department, University of Birmingham

12. Dr Andrew Prentice, Senior Lecturer and Consultant Obstetrician and Gynaecologist, The Rosie Hospital, University of Cambridge

13. Ms Amanda Roberts, Public contributor

14. Dr Gillian Shepherd, Director, Health and Clinical Excellence, Merck Serono Ltd

15. Mrs Katrina Simister, Assistant Director New Medicines, National Prescribing Centre, Liverpool

16. Professor Donald Singer, Professor of Clinical Pharmacology and Therapeutics, Clinical Sciences Research Institute, CSB, University of Warwick Medical School

17. Mr David Symes, Public contributor

18. Dr Arnold Zermansky, General Practitioner, Senior Research Fellow, Pharmacy Practice and Medicines Management Group, Leeds University

1. Dr Kay Pattison, Senior NIHR Programme Manager, Department of Health

2. Mr Simon Reeve, Head of Clinical and Cost-Effectiveness, Medicines, Pharmacy and Industry Group, Department of Health

3. Dr Heike Weber, Programme Manager, Medical Research Council

4. Professor Tom Walley, CBE, Director, NIHR HTA programme, Professor of Clinical Pharmacology, University of Liverpool

5. Dr Ursula Wells, Principal Research Officer, Policy Research Programme, Department of Health

Psychological and Community Therapies Panel

1. Professor of Psychiatry, University of Warwick, Coventry

2. Consultant & University Lecturer in Psychiatry, University of Cambridge

3. Professor Jane Barlow, Professor of Public Health in the Early Years, Health Sciences Research Institute, Warwick Medical School

4. Dr Sabyasachi Bhaumik, Consultant Psychiatrist, Leicestershire Partnership NHS Trust

5. Mrs Val Carlill, Public contributor

6. Dr Steve Cunningham, Consultant Respiratory Paediatrician, Lothian Health Board

7. Dr Anne Hesketh, Senior Clinical Lecturer in Speech and Language Therapy, University of Manchester

8. Dr Peter Langdon, Senior Clinical Lecturer, School of Medicine, Health Policy and Practice, University of East Anglia

9. Dr Yann Lefeuvre, GP Partner, Burrage Road Surgery, London

10. Dr Jeremy J Murphy, Consultant Physician and Cardiologist, County Durham and Darlington Foundation Trust

11. Dr Richard Neal, Clinical Senior Lecturer in General Practice, Cardiff University

12. Mr John Needham, Public contributor

13. Ms Mary Nettle, Mental Health User Consultant

14. Professor John Potter, Professor of Ageing and Stroke Medicine, University of East Anglia

15. Dr Greta Rait, Senior Clinical Lecturer and General Practitioner, University College London

16. Dr Paul Ramchandani, Senior Research Fellow/Cons. Child Psychiatrist, University of Oxford

17. Dr Karen Roberts, Nurse/Consultant, Dunston Hill Hospital, Tyne and Wear

18. Dr Karim Saad, Consultant in Old Age Psychiatry, Coventry and Warwickshire Partnership Trust

19. Dr Lesley Stockton, Lecturer, School of Health Sciences, University of Liverpool

20. Dr Simon Wright, GP Partner, Walkden Medical Centre, Manchester

1. Dr Kay Pattison, Senior NIHR Programme Manager, Department of Health

2. Dr Morven Roberts, Clinical Trials Manager, Health Services and Public Health Services Board, Medical Research Council

3. Professor Tom Walley, CBE, Director, NIHR HTA programme, Professor of Clinical Pharmacology, University of Liverpool

4. Dr Ursula Wells, Principal Research Officer, Policy Research Programme, Department of Health

Expert Advisory Network

1. Professor Douglas Altman, Professor of Statistics in Medicine, Centre for Statistics in Medicine, University of Oxford

2. Professor John Bond, Professor of Social Gerontology & Health Services Research, University of Newcastle upon Tyne

3. Professor Andrew Bradbury, Professor of Vascular Surgery, Solihull Hospital, Birmingham

4. Mr Shaun Brogan, Chief Executive, Ridgeway Primary Care Group, Aylesbury

5. Mrs Stella Burnside OBE, Chief Executive, Regulation and Improvement Authority, Belfast

6. Ms Tracy Bury, Project Manager, World Confederation of Physical Therapy, London

7. Professor Iain T Cameron, Professor of Obstetrics and Gynaecology and Head of the School of Medicine, University of Southampton

8. Professor Bruce Campbell, Consultant Vascular & General Surgeon, Royal Devon & Exeter Hospital, Wonford

9. Dr Christine Clark, Medical Writer and Consultant Pharmacist, Rossendale

10. Professor Collette Clifford, Professor of Nursing and Head of Research, The Medical School, University of Birmingham

11. Professor Barry Cookson, Director, Laboratory of Hospital Infection, Public Health Laboratory Service, London

12. Dr Carl Counsell, Clinical Senior Lecturer in Neurology, University of Aberdeen

13. Professor Howard Cuckle, Professor of Reproductive Epidemiology, Department of Paediatrics, Obstetrics & Gynaecology, University of Leeds

14. Professor Carol Dezateux, Professor of Paediatric Epidemiology, Institute of Child Health, London

15. Mr John Dunning, Consultant Cardiothoracic Surgeon, Papworth Hospital NHS Trust, Cambridge

16. Mr Jonothan Earnshaw, Consultant Vascular Surgeon, Gloucestershire Royal Hospital, Gloucester

17. Professor Martin Eccles, Professor of Clinical Effectiveness, Centre for Health Services Research, University of Newcastle upon Tyne

18. Professor Pam Enderby, Dean of Faculty of Medicine, Institute of General Practice and Primary Care, University of Sheffield

19. Professor Gene Feder, Professor of Primary Care Research & Development, Centre for Health Sciences, Barts and The London School of Medicine and Dentistry

20. Mr Leonard R Fenwick, Chief Executive, Freeman Hospital, Newcastle upon Tyne

21. Mrs Gillian Fletcher, Antenatal Teacher and Tutor and President, National Childbirth Trust, Henfield

22. Professor Jayne Franklyn, Professor of Medicine, University of Birmingham

23. Mr Tam Fry, Honorary Chairman, Child Growth Foundation, London

24. Professor Fiona Gilbert, Consultant Radiologist and NCRN Member, University of Aberdeen

25. Professor Paul Gregg, Professor of Orthopaedic Surgical Science, South Tees Hospital NHS Trust

26. Bec Hanley, Co-director, TwoCan Associates, West Sussex

27. Dr Maryann L Hardy, Senior Lecturer, University of Bradford

28. Mrs Sharon Hart, Healthcare Management Consultant, Reading

29. Professor Robert E Hawkins, CRC Professor and Director of Medical Oncology, Christie CRC Research Centre, Christie Hospital NHS Trust, Manchester

30. Professor Richard Hobbs, Head of Department of Primary Care & General Practice, University of Birmingham

31. Professor Alan Horwich, Dean and Section Chairman, The Institute of Cancer Research, London

32. Professor Allen Hutchinson, Director of Public Health and Deputy Dean of ScHARR, University of Sheffield

33. Professor Peter Jones, Professor of Psychiatry, University of Cambridge, Cambridge

34. Professor Stan Kaye, Cancer Research UK Professor of Medical Oncology, Royal Marsden Hospital and Institute of Cancer Research, Surrey

35. Dr Duncan Keeley, General Practitioner (Dr Burch & Ptnrs), The Health Centre, Thame

36. Dr Donna Lamping, Research Degrees Programme Director and Reader in Psychology, Health Services Research Unit, London School of Hygiene and Tropical Medicine, London

37. Professor James Lindesay, Professor of Psychiatry for the Elderly, University of Leicester

38. Professor Julian Little, Professor of Human Genome Epidemiology, University of Ottawa

39. Professor Alistaire McGuire, Professor of Health Economics, London School of Economics

40. Professor Neill McIntosh, Edward Clark Professor of Child Life and Health, University of Edinburgh

41. Professor Rajan Madhok, Consultant in Public Health, South Manchester Primary Care Trust

42. Professor Sir Alexander Markham, Director, Molecular Medicine Unit, St James’s University Hospital, Leeds

43. Dr Peter Moore, Freelance Science Writer, Ashtead

44. Dr Andrew Mortimore, Public Health Director, Southampton City Primary Care Trust

45. Dr Sue Moss, Associate Director, Cancer Screening Evaluation Unit, Institute of Cancer Research, Sutton

46. Professor Miranda Mugford, Professor of Health Economics and Group Co-ordinator, University of East Anglia

47. Professor Jim Neilson, Head of School of Reproductive & Developmental Medicine and Professor of Obstetrics and Gynaecology, University of Liverpool

48. Mrs Julietta Patnick, Director, NHS Cancer Screening Programmes, Sheffield

49. Professor Robert Peveler, Professor of Liaison Psychiatry, Royal South Hants Hospital, Southampton

50. Professor Chris Price, Director of Clinical Research, Bayer Diagnostics Europe, Stoke Poges

51. Professor William Rosenberg, Professor of Hepatology and Consultant Physician, University of Southampton

52. Professor Peter Sandercock, Professor of Medical Neurology, Department of Clinical Neurosciences, University of Edinburgh

53. Dr Philip Shackley, Senior Lecturer in Health Economics, Sheffield Vascular Institute, University of Sheffield

54. Dr Eamonn Sheridan, Consultant in Clinical Genetics, St James’s University Hospital, Leeds

55. Dr Margaret Somerville, Director of Public Health Learning, Peninsula Medical School, University of Plymouth

56. Professor Sarah Stewart-Brown, Professor of Public Health, Division of Health in the Community, University of Warwick, Coventry

57. Dr Nick Summerton, GP Appraiser and Codirector, Research Network, Yorkshire Clinical Consultant, Primary Care and Public Health, University of Oxford

58. Professor Ala Szczepura, Professor of Health Service Research, Centre for Health Services Studies, University of Warwick, Coventry

59. Dr Ross Taylor, Senior Lecturer, University of Aberdeen

60. Dr Richard Tiner, Medical Director, Medical Department, Association of the British Pharmaceutical Industry

61. Mrs Joan Webster, Consumer Member, Southern Derbyshire Community Health Council

62. Professor Martin Whittle, Clinical Co-director, National Co-ordinating Centre for Women’s and Children’s Health, Lymington