The feasibility of using pedometers and brief advice to increase activity in sedentary older women – a pilot study

Inclusion and exclusion criteria

Women aged over 70 years who were insufficiently active or sedentary, i.e. no participation in moderate-intensity physical activity of at least 30 minutes at least 5 days per week or at least 20 minutes of continuous vigorous-intensity activity three or more times a week [14] were included in the study. Women were asked about their participation in physical exercise and walking at a preliminary phone call before any visits took place. Women fulfilling physical activity recommendations, resident of institutional care, housebound (unable to increase outdoor walking), having moderate to severe cognitive impairment (MMSE score < 18) precluding informed consent, having significant visual impairment and so unable to read pedometer count screen, wheelchair bound or unwilling to participate were excluded from the study.

Recruitment and randomisation

Participants were recruited from a single GP practice (see figure 1) via the well established Scottish Primary Care Research Network (SPCRN). The GP principal provided a list of all women aged 70 years and over, excluding those who should not be approached because of terminal illness, recent bereavement, severe heart failure/COPD/dementia or nursing home dwellers. The GP wrote to the women inviting them to take part in the study, including a pre-paid reply envelope. Those accepting the invitation were telephoned and asked whether they were housebound, how much exercise they were taking, whether they were visually impaired or using a wheelchair. At the first face-to-face visit, a mini mental state examination was performed.

Randomisation was performed by an individual not otherwise involved in the study using a computer-based random number generator. The participants were allocated at random, in a 3:2 ratio, to one of two groups: pedometer plus self-regulation intervention ("pedometer group") or self-regulation intervention alone ("advice group"). The pedometer group were further randomised to one of three target groups: a 10%, 15% or 20% monthly increase in step count (steps taken per day). The average daily pedometer count over three consecutive days (at baseline before intervention) was taken and used to set a target of achieving a 10%, 15% or 20% increase in steps during the first month. If the participant met her target step count, it was increased again after the first and second months. If she had not met her target, 10%, 15% or 20% was added to the average number of steps they achieved over the three day period preceding the telephone call.

Development of the self-regulation intervention and protocol for delivery

Self-regulation theory emphasises the role of goal setting, planning and self-monitoring in behaviour change [14]. Theory-based advice was given to each participant in the form of individualised activity action plans and coping plans. Additional file 1 shows the protocol that was developed for the delivery of this advice. The protocol was developed using the Coding Manual to Identify Behaviour Change Techniques in Published Intervention Descriptions [15]. The intervention was delivered by a senior research nurse who had received training from two experienced health psychologists (authors DJ and FFS). First, each participant was given advice about the health benefits of increasing physical activity both verbally and in pamphlet form after collection of baseline data at the second visit. Then action plans and coping plans were discussed and written with each participant in her own home after the baseline data had been collected. The action plans were designed to increase participants' physical activity levels (mainly through walking) and the coping plans were to identify how to cope with possible barriers towards increasing their walking [16]. A graded approach to increasing walking was given with clear advice on when and where to walk and how to schedule time for physical activity. Each participant was given a daily activity diary to complete with logs of either pedometer count or time spent walking outdoors. These diaries were returned to the researcher, in a supplied stamped addressed envelope, to assess compliance with diary keeping. Each participant was contacted by telephone once a week for the first month and then fortnightly thereafter until the end of the study to provide motivation, encouragement and to troubleshoot any problems.

Validation of pedometers

Two different types of pedometer were used in this study in order to ascertain how accurate and user-friendly they were in our study population: the Omron HJ-005 spring levered and the Omron HJ-113 piezoelectric pedometers. The spring levered device is worn on the waistband; a horizontal lever-arm moves up and down in response to vertical movement and opens and closes an electrical circuit. This device must remain vertical to be effective [17]. In this study the piezoelectric device was worn around the neck although it can be worn on the waistband. It contains a horizontal cantilevered beam with a weight at the end that compresses a piezoelectric crystal when subjected to movement, it is less susceptible to tilt than the spring levered device [17]. At the randomisation visit (visit 2), each participant in the pedometer group was asked to read the count screen of each device and to walk 100 steps at their usual pace wearing both pedometers in the presence of the researcher. They were also asked which device they preferred. The more accurate device was given to the participant and they were asked to wear it to monitor their step count during waking hours.

Outcome measures

The outcome measures were assessed at baseline (before the intervention) and after 3 months. Outcome measures were collected on the same day on both occasions and baseline outcomes were assessed before implementation of the intervention. The primary outcome measure was change in daily activity levels which was measured by accelerometry (RT3 Tri-axial Research Tracker, Stay Healthy Inc., USA), a device the size of a pager worn on the waistband during waking hours for a 7-day period which has been validated for use in an elderly population [13]. Accelerometers were worn for 7 days by the participant, tri-axial data was collected in 1 minute epochs, counts < 250 or > 3000 were discarded as spurious [18]. Counts were totalled over each 24 hr period (midnight – midnight), the 1st set of 24 hour data was discarded (incomplete day) and missing days were excluded from analysis. Counts (per minute) per day for valid days were recorded.

Secondary outcome measures were: assessment of lower limb function using a validated performance score [19] consisting of three 0–4 point scales summarising performance on three tests of lower extremity function – usual walking speed over 3 meters, standing balance and repeated chair stands; health related quality of life was assessed using the EuroQuol questionnaire which provides a brief measure of health status with self ratings on mobility, self-care, anxiety and depression, usual activities and pain together with a global rating of health state which has been shown to be reliable at interview in an older population [20]; and depression and anxiety were assessed using the Hospital Anxiety and Depression Scale [21]. This pilot study was not powered to detect changes in outcome measures, but to demonstrate feasibility of data collection for a larger trial.

Statistical analysis

Descriptive information was generated for readability of the pedometer screen, accuracy of step counting for the two pedometer types, adherence with daily activity diaries and drop out rate. The correlation between pedometer counts and accelerometry at baseline was examined using Pearson's correlation (2 tailed), and the difference in change in accelerometer count and secondary outcomes from visit 1 to visit 3 between the two groups was analysed by t-test assuming that variances were not the same. Comparisons between target groups were carried out using analysis of variance followed by Bonferroni corrected pair-wise tests. In addition, a test for trend across target groups was carried out. Where variables were non-Normally distributed, non-parametric tests such as Mann-Whitney were utilised. All analyses were implemented in SPSS.

Feasibility of using pedometers and brief advice to increase activity in sedentary older women

There was 100% adherence with activity action plan and coping plan completion (nobody refused). Diary filling and measurement of all the outcome measures was acceptable to all participants. Compliance with diary completion was 96% in the pedometer plus advice group, with one diary that went missing and an average of 2 day's entries per participant missing over the whole 3 month study period. In the advice alone group, compliance with dairy completion was lower at 83% with 4 diaries that went missing and an average of 5 day's entries per participant missing.

9 participants dropped out of the study in total (17%). 5 participants dropped out from the pedometer group: 1 from the 10% target group (felt the study was "too much"), 1 from the 15% target group (study "too much"), and 3 from the 20% target group (1 gave no reason, 1 had depression, 1 felt study was "too much"). 4 participants dropped out from the advice group (1 felt study was "too much", 1 had memory problems, 1 had a transient ischaemic attack and 1 had on-going colds and flu), see figure 1.

Validation of pedometers for this study population

All participants in the pedometer group were able to read the count screens on both pedometers. The piezoelectric pedometer was generally preferred over the spring levered device by the participants because it recorded step counts more accurately in the target population; the spring levered pedometer counted an average of 62 steps per 100 steps taken (range 1–179), the piezoelectric pedometer counted an average of 73 steps per 100 steps taken (range 6–117). There were complaints of over-counting from several participants using spring levered device and we received no complaints from the participants using the piezoelectric device. The piezoelectric device has a 7-day inbuilt memory which allowed the researcher to confirm pedometer counts noted by the participants. The majority of participants preferred the piezoelectric device. 12 participants used the spring levered device and 20 participants used the piezoelectric. Daily step counts for all participants in the pedometer group were low at baseline, with an average of 2895 steps per day (range 185 to 8845).

Accelerometry and pedometer counts

There was a strong correlation of 0.78 (p = 0.01, Pearson's correlation) between accelerometry and pedometer step counts at baseline, i.e. time spent walking, for both pedometer types combined.

There was no difference in change in accelerometry count between the advice group and the pedometer group as a whole (t-test, p = 0.893, table 1 and figure 2), however, there was an increase in activity (accelerometry) amongst those in the 20% target pedometer group compared to the other target groups although not reaching statistical significance (p = 0.192). Looking at the daily diary entries, the advice group met the target 58% of days compared with 61% of days in the pedometer group (p < 0.001). In the pedometer group, the 10% target group met the target 55%, 15% target group 57% and 20% target group 74%. There was a higher rate of meeting the target in the highest target group.

Time	Intervention Group	N	Mean	Standard Deviation	Standard Error Mean	p-value*
Baseline	Advice group	18	116,378	47,952	11,302	0.816
	Pedometer group	26	112,984	46,887	9,195
12 weeks	Advice group	18	113,822	62,337	14,693	0.776
	Pedometer group	26	108,738	54,728	10,733
Change (12 weeks – baseline)	Advice group	18	-2,556	46,494	10,958	0.893
	Pedometer group	26	-4,245	36,355	7,129

† 1 missing accelerometry data

* t-test assuming variances not same

Secondary outcomes