Recruitment and retention
shows participant flow through the trial. From an initial pool of potential participants (N = 461), a total of 177 were ineligible due to (i) excluded by GP (ii) moved away or (iii) deceased. We note in the reasons why individuals were screened out by the GP. The main three contraindications to PA were severe arthritis (n = 34), being house bound, general frailty or poor mobility (n = 26), and chronic mental health problems (n = 24).
Recruitment and participant flow through the trial
A final sample of eligible participants (n = 284) was invited to join the study. The invitation to participate in the walking project resulted in a 65.8% response rate (187/284). Of the eligible participants, 32.4% (n = 92) responded positively and 33.4% (n = 95) declined to take part. The remaining 34.2% (n = 97) did not respond. Of the 92 participants who responded positively, 44.6% (n = 41) participated in study visits. The Scottish Index of Multiple Deprivation (SIMD) was used to allocate each participant by their postcode to a category of socioeconomic status. Of those who participated in the study, 46% (19/41) were in the least deprived SIMD category and 59% (24/41) were in the youngest age category of 65–69 years. However, no significant differences were found between those who responded positively and those who responded negatively to the study invite in the distributions of SIMD (P = 0.91) or gender (P = 0.15). Baseline characteristics of study participants are shown in . There were no significant differences in demographic variables between study groups. The predominance of women in the trial (68%) is reflective of the study population. The retention rate (number of participants completing the study, as a proportion of those randomized) was 90% (37/41).
Baseline characteristics of study participants by group (Observations made [OBS] Missing data [MISS])
also summarizes the reasons that negative responders gave for declining participation. The most common (51%; 48/95) was that the individual self-assessed as already physically active. Of the positive responders, 54% (50/92) attended the first study visit and 45% (41/92) were randomized into the study. The most common reason for positive responders not being randomized was that they were already active (baseline step count >70 000 steps/week). No participants objected to randomization.
Appropriateness of the intervention for this target group and for the primary care setting
Nine participants from the intervention group and seven from the control group attended focus group discussions. The findings from these suggest that the pedometer was easy to use and was an important motivational tool for many. For example, one participant said ‘I think when you’ve got your meter on, you try to get a wee bit better … I feel it’s like a challenge’ (P107, control when receiving intervention). Using the pedometer for feedback in conjunction with goal setting and recording via the booklet appeared helpful. For instance, one participant noted: ‘When you’re out you’re so aware “I’ve got to get this steps going,” … walk round a longer route or do something … I found writing it down, it made me, do more. I did say 7000 today; tomorrow I’ll do 8’ (P123, intervention). However, some participants spoke of not always wearing the pedometer: ‘I probably could have accomplished the steps much more easily if I’d just worn it all the time as suggested. I didn’t, I tended to wait until I was actually going to do something’ (P125, intervention). The nurse-led consultation did not raise any concerns from participants and can therefore be seen as a feasible mechanism for delivering a walking intervention in primary care. Participants noted that it was helpful to have a person to phone if needed (the nurse)—‘You can lift the phone … you’re at the end of a phone I can ask something’ (P107, control).
Six adverse events were noted through the trial. Three were attributable to the intervention or research monitoring: one participant withdrew because of knee pain brought on by walking, one participant experienced temporary low back pain and one participant reported skin irritation due to activPAL wear. The latter two participants continued walking. Walking therefore appears to be a safe mode of activity to promote to older adults. However, the walking group was poorly attended (only nine participants attended but not regularly).
Project team members with an academic background were positive about rolling this intervention out in primary care as they saw it as a good way to access and recruit older adults. However, those from a primary care background were less certain; their main concerns were about time and routine care rather than research. For example, they said that screening for PA contraindications for this age group was time consuming: ‘This is a particular issue about physical activity. You’re not screening to see if the person’s alive or you’re not screening to see if they’re on a particular drug, you’re screening their whole life circumstances to see if physical activity is going to be okay and not contraindicated for them’ (101). Those from primary care acknowledged that a research project is different from routine practice. One said: ‘The project needs to be moved out of [the] research umbrella, it needs to be part of the primary care prevention and it needs to become embedded in the fabric of the way the primary care functions’ (104).
Step count data collected by pedometer and activ
PAL are shown in . At least some pedometer step count data were available for all participants at each time point. The activ
PAL did not return any data on only five occasions (four at baseline), due to technical failures. Nevertheless, the activ
PAL appears to have been used more consistently than the pedometer during the assessment periods. There were 52 days of recorded step counts with <1000 steps from the pedometers, compared with only 2 from the activ
PAL monitors. These values were not considered feasible, possibly due to the monitors not being worn at all times, and were excluded from calculations of the average daily step count. In addition, further analysis of these data has shown that pedometers underreport the values obtained from the continuously used activ
PAL monitor by around 2000 steps per day.
Step counts, recorded using pedometer and activPAL
There was no evidence of changes in pedometer step counts in either group during the first 12 weeks of the study, and no difference between groups over this period. Between weeks 12 and 24, the control group increased their average daily walking by 1672 pedometer steps.
There was strong evidence of an intervention effect with activPAL step counts, based on the between-group comparison of changes over the first 12 weeks of the study (2119 steps/day, P = 0.001). During the walking intervention, both study groups showed similar step count increases (1907 for intervention and 1908 for control when they received the intervention; standardized effect = 0.78). The increase in steps observed from baseline appears to have been maintained in the intervention group (mean step count week 12: 9351, week 24: 9161, P = 0.65). These results are illustrated in .
shows changes over time and between-group differences for selected secondary outcomes. Both groups showed increases in objectively measured walking time and decreases in objectively measured sedentary time during the periods when they received the walking intervention. While a pattern of improvement was seen across all subscales of the SF-36, the physical health dimension score was most sensitive to change during the intervention. Neither PANAS (both positive and negative) scores, the UCLA Loneliness Scale nor PMES-OA scores showed any evidence of within- or between-group effects during the study (full data available on request). A cost-utility analysis suggested that the intervention would cost around 100 pounds sterling per patient (full report available on request).
Selected secondary outcomesa