Interpreting population reach of a large, successful physical activity trial delivered through primary care

The PACE-UP trial [15] recruited inactive 45-75 year olds registered at seven south-west London general practices and randomised 1023 people to one of three arms: an intervention arm designed to increase walking using pedometers, personalised walking plans and nurse consultations; a postal intervention arm (without nurse consultations); and a standard practice arm. Participants in the trial had to be able to walk outside and have no contraindications to increasing their PA levels.

Potentially eligible patients were identified using Read codes for medical conditions and local knowledge about care homes to exclude ineligible patients. The trial randomised households (one person living alone or two people with an age difference of less than 15 years if more than one eligible person in the household). Batches of approximately 400 potentially eligible individuals from randomly selected households were screened for exclusion criteria by general practitioners or practice nurses to avoid inviting patients with conditions that would exclude them from being offered the intervention in routine care, but which are not well recorded on Read codes (e.g., acute systemic illness such as pneumonia, unstable heart failure, unable to move about independently, psychotic illness). Some individuals will have already been screened out through READ codes. The remainder were invited to participate in the trial by letter, which included the trial information leaflet, a reply slip and stamped addressed envelope. Those willing to participate but who reported that they achieved, or were not sure if they achieved, recommended levels of at least 150 min weekly of at least moderate intensity physical activity [17], were telephoned to check their eligibility. If confirmed to be active they were excluded. One reminder letter was sent to those who did not reply. All trial information was written in English. For further details see the trial protocol [15].

The gender, age and Index of Multiple Deprivation (IMD) of all those invited were collected from GP records. IMD is an anonymised post-code deprivation measure [18]. To avoid the possibility of individuals being identified, aggregated practice-recorded ethnicity was exported in 10 year age-bands for all batches where everyone was mailed, less exclusions. We classified the practice recorded ethnicity into 4 categories, White (including ‘British or Mixed British’), Asian (including ‘Asian British’), Black (including ‘Carribbean’, ‘African’ and ‘Black British’) and Other.

Those not wanting to participate in the trial were asked if they would complete a shortened trial baseline questionnaire, including demographics, health, a primary care PA questionnaire (General Practice Physical Activity Questionnaire GPPAQ [19]), EQ-5D [20] and a question on reasons for not participating.

Individuals whose invitation letters were ‘returned-to-sender’ were excluded from analyses before calculating response rates. ‘Responders’ are defined as those who replied to the invitation letter, regardless of whether they wanted to take part or not. Individuals could respond by post, email or phone.

‘Participants’ are those who completed baseline assessment, although not all were randomised as some provided inadequate objectively measured physical activity data. ‘Non- participants’ are those who completed a questionnaire but did not wish to participate in the trial (Fig. 1).

Since PACE-UP targeted inactive adults, participants who attended a baseline appointment were selected on the basis of their low PA levels. Non-participants were not selected in this way. In order to minimise selection bias, analysis of participants and non-participants was therefore restricted to those categorized as ‘not active’ according to GPPAQ, which was the only physical activity measure available on both groups.

Age and gender standardised rates were used to compare IMD quintiles for responders. Similarly, gender standardised rates were used to compare age groups and age standardised rates to compare genders. The full population of invitees was used as a standard population throughout. No further analysis on non-responders was possible because they did not provide any questionnaire data on ethnicity or other factors.

Practice ethnicity data were extracted in 10-year age bands for 10,155 invitees from batches where everyone was mailed, effectively a random sample of the 11,015 invited. The proportion of patients belonging to each ethnicity category within age band and within practice was calculated and the number of invitees in each ethnicity in each practice and age-band was estimated. Overall, 1903 invitees had ethnicity recorded as ‘unknown’. These are assumed to be missing at random in the main results but sensitivity analyses were performed, assuming these were all white or all non-white. Age standardised participation rates for not active participants and non-participants completing questionnaires were calculated assuming that invitees gave the same ethnicity on the questionnaire as was recorded in their practice records. Participation rates by age, gender and IMD were calculated for not active participants versus not active non participants completing questionnaires, as in the analysis of responders.

Not active participants and non-participants completing the questionnaire were compared for additional demographic and social characteristics and health and lifestyle factors using logistic regression. All data came from questionnaires. Models were adjusted for clustering by practice and household by including fixed effects for practice and using robust standard errors for household.

The PACE-UP trial recruited 11% of patients aged 45 to 75 invited by post by their practice. Those replying were older, more likely to be female and from less deprived postcodes. Participants in the trial who completed a baseline assessment and were not classified as active by questionnaire, were also more likely to be older, female, and from less deprived postcodes compared with non-active non-participants. Asian patients were less likely to participate. Participation was associated with having some comorbidity or some degree of health impairment, and having had recent primary care contact. Insufficient time and perceiving themselves as being already physically active were common reasons for non-participation, even though we only included those who were classified by GPPAQ as not active.

A systematic review of 47 walking intervention studies [3] showed recruitment methods and participation rates were poorly reported. Participation rates could only be calculated for 5/25 randomised controlled trials. We recruited by post to reduce practice staff burden and to obtain response rate data. Primary care uses postal invitations for other preventive activities, making this a pragmatic approach [21]. Other primary care walking interventions using postal invitations [8, 22‐24] had similar response rates of 10 to 20%. Dubbert [4, 5] had higher rates (37% and 39%) but recruited additionally through routine primary care visits and patients were over 60 with on average 3.8 co-morbidities. We have shown that older age, having some comorbidity and recent health professional contact were associated with increased trial participation. Our previous trial [7] used similar recruitment strategies to PACE-UP and had a 30% recruitment rate, but was limited to over 60 year olds, was conducted in an affluent setting with few non-white residents and did not exclude those reporting they were active.

Non-responders were followed up with one reminder letter, but due to data protection constraints we could not telephone non-responders. Although only 1% of invitation letters were returned to sender, this may underestimate those not receiving the letter, as we did not used registered post. A previous London study using registered post found 26% of letters were not delivered [25]. Warner [24] found active refusal rates to be low but about 30% of eligible patients could not be contacted.

Most recruitment studies focus on recruitment methods [9, 26, 27]. In this study we compared participation rates for different groups within one primary care study using postal invitations. We have previously explored this in the PACE-Lift trial [28] setting, but PACE-UP is larger, with greater diversity, allowing ethnicity and deprivation effects to be explored comprehensively. We have already published findings from interviews to explore reasons for non-participation [29] in PACE-UP.

Our finding of greater participation in women, older people and those in affluent areas are supported by other studies [28, 29]. Although Attwood [30] found no association with deprivation or ethnicity this was in a highly deprived area with few non-white patients.

Among Asian patients, our response rate was similar to postal invitations in the PODOSA trial (5.2%) where community based approaches [31], through partnership with local South Asian groups were found to be more effective. Wilbur found social networking the most effective method for recruiting African American women from low income areas [27].

PACE-UP is a large trial recruiting from a clearly defined invited population, based on GP lists, enabling us to assess the potential reach of the intervention in terms of age, gender and deprivation. Our estimate of 11% participation may be an underestimate of the true rate, particularly in areas of high mobility.

Although based on limited data, the PACE-UP trial offers a rare opportunity to examine demographic differences between participants and non-participants. We were able to estimate participation within different ethnicities using pooled data from the practices. However, we were not able to match at an individual level and some participants may have categorised themselves in a different ethnic group to that on the GP register. Ethnicity was also poorly recorded in some practices and we needed to make assumptions about whether those with ‘unknown’ ethnicity were similar to those with recorded ethnicity. In a sensitivity analysis, even under extreme assumptions, the same ethnic variations persisted. It is possible we have underestimated the response rates in White people compared to other groups because in our estimation of the number of white invitees we classified as ‘White’ those classified as ‘British or Mixed British’; the practice data did not distinguish between ‘British’ and ‘Mixed British’. However comparing with the area census data (Wandsworth in 2011) [32] we believe any effect would be small.

The trial excluded individuals who self-reported being active, but the non-participants were not selected in this way. Our analysis attempted to mitigate this difference by restricting analysis to all those who self-reported as not being active using the same question. However, some residual bias may remain.

One possible limitation is that we did not attempt to compare different recruitment methods. Our main focus was to reach our recruitment target of 993 randomised patients in 1 year and we had insufficient resources to design a study within a trial [33] to compare different recruitment strategies. We chose to use postal recruitment which had been successful in our previous trial and we planned conservatively so that we had a large enough pool of invitees to achieve our target even with a low response rate. Copeland et al. [9] tried a number of strategies to boost recruitment in addition to postal invitation. These included asking GPs to recruit during consultations, and asking community leaders, health trainers and champions to distribute recruitment packs but these were all unsuccessful and all participants were recruited postally. Recruitment strategies based on advertising or community groups could be compared in terms of research effort required but would not allow characteristics of participants and non-participants to be compared; one of the key strengths of this study.

NICE guidelines [34] conclude that more research is needed to determine which interventions are effective and cost-effective in increasing activity levels among lower socio-economic and high risk groups, and that there is little evidence on differential effects of interventions. In our trial those groups for which more evidence is required tended to be those with the lowest recruitment rates, such as Asians and those in more deprived areas [2]. It has been suggested [35] that specific cultural groups may respond better to interventions directly targeted at their needs, rather than to universal interventions. Reasons for non-participation often related to individuals not wanting to increase activity or feeling that they were sufficiently active. It is likely such resistance will similarly apply to any intervention roll out and may apply more widely to other public health interventions. Low participation rates mean policy makers should be cautious about the intervention’s potential reach and the possibility that it could increase activity inequalities, but is not a reason not to implement an intervention shown to be effective in 11% [16] of the population. We were successful in recruiting older people, women and those with co-morbidities or some degree of health limitation. These groups have lower PA levels and are likely to benefit more from increased physical activity. However, those with more severe disability, fallers, and those with a fear of falling were not over-represented, indicating a rational choice by individuals.

Only 12% of non-participants cited randomisation as a factor for not participating, while 45% cited time constraints. The nurse intervention required three additional visits to the practice on top of the three data collection visits, which may deter working people or those with childcare and other commitments. However, PACE-UP showed that both the nurse and postal groups performed similarly at the main 12 month outcome [16]. An intervention offering pedometers with brief advice, without the need to provide research data, may be more acceptable.

Both PACE-Lift and PACE-UP recruited to target, achieved follow up rates of over 90% and demonstrated the interventions were effective in increasing physical activity [16, 24]. However, considerably more research effort was required per randomised participant in PACE-UP compared with PACE-Lift, due to lower uptake. In spite of the effort, we still had limited power to investigate ethnic and socio-economic subgroups.