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Computer tailoring is a relatively innovative and promising physical activity intervention approach. However, few computer-tailored physical activity interventions in adults have provided feedback based on pedometer use.
To (1) describe the development of a Web-based, pedometer-based, computer-tailored step advice intervention, (2) report on the dissemination of this tool through general practice, (3) report on its perceived acceptability, and (4) evaluate the preliminary efficacy of this tool in comparison with a standard intervention.
We recruited 92 participants through general practitioners and randomly assigned them to a standard condition (receiving a pedometer-only intervention, n = 47) and a tailored condition (receiving a pedometer plus newly developed, automated, computer-tailored step advice intervention, n = 45). Step counts, self-reported data obtained via telephone interview on physical activity, time spent sitting, and body mass index were assessed at baseline and postintervention. The present sample was mostly female (54/92, 59%), highly educated (59/92, 64%), employed (65/92, 71%), and in good health (62/92, 67%).
Recruitment through general practitioners was poor (n = 107, initial response rate 107/1737, 6.2%); however, the majority of participants (50/69, 73%) believed it is useful that general practitioners help patients find ways to increase physical activity. In the tailored condition, 30/43 (70%) participants requested the computer-tailored step advice and the majority found it understandable (21/21, 100%), credible (17/18, 94%), relevant (15/18, 83%), not too long (13/18, 72%), instructive (13/18, 72%), and encouraging to increase steps (16/24, 67%). Daily step counts increased from baseline (mean 9237, SD 3749 steps/day) to postintervention (mean 11,876, SD 4574 steps/day) in the total sample (change of 2639, 95% confidence interval 105–5172;
The majority of participants in the tailored condition accepted the step advice and indicated it was useful. However, in this selected sample of adults, the tailored condition did not show superior effects compared with the standard condition.
There is ample evidence of the positive effects of regular physical activity on physical and mental health [
A relatively innovative and promising intervention approach in public health promotion is the use of computer tailoring via the Internet [
The major advantage of computer tailoring through the Internet is the ability to reach many people in a variety of settings at any time and location, and at a relatively low cost. Research revealed that promoting physical activity via the Internet is feasible and appealing to adults [
Existing computer-tailored physical activity programs might, however, also have weaknesses. As the diagnostic assessment is mostly done by questionnaires [
Another weakness of online physical activity programs is reaching the targeted population. Recruiting individuals to visit website programs on health behavior change appears to be rather difficult. For example, Australian research conducted in a worksite sample showed that only 46% of participants who agreed to take part in a website-delivered physical activity intervention actually visited the website [
The development of computer-tailored interventions requires (1) a data source, including the significant characteristics of the recipient derived from an individual diagnosis or assessment, (2) a message library that contains the intervention messages, (3) a set of decision rules that selects messages matched and tailored to the specific needs of the recipient, and (4) a channel that delivers the messages to the specific person, such as the Internet [
Prior to visiting the computer-tailored website, participants’ baseline step level had to be determined. Participants were instructed to wear a pedometer for 7 consecutive days without changing their usual lifestyle. To receive the computer-tailored step advice, participants had to log on to a website using a confidential username and password, and then complete a questionnaire (see
The tailored feedback was created from a database of messages that match any possible combination of answers and is based on the theory of planned behavior [
The feedback was organized so that participants first received a general introduction (see
Examples of introductions to the tips and suggestions of the advice intervention for the various stages of change.
Stage of change | Example of introduction to the tips and suggestions section of the pedometer-based, computer-tailored advice |
Precontemplation | It seems that you are not reaching the goal of 10,000 steps a day. That’s a pity because being active has several health advantages, in both the short and the long term. People can experience these benefits when they are being physically active on a regular basis. The following tips could help people who want to be more active... |
Contemplation | It seems that you are not reaching the goal of 10,000 steps a day, but are planning to become more active at some point in the future. That’s good because being active has several health advantages, in both the short and the long term. You could experience these benefits when you are being physically active on a regular basis. When you decide the time has come to take more steps, the following tips and suggestions will certainly be helpful... |
Preparation | You are intending to take more steps than you are taking now, and you want to reach this goal within 1 month. This is a good idea, as you are currently not reaching the goal of 10,000 steps a day which is needed to achieve health benefits. The following tips should help you to realize your good intentions... |
Action | Because you are already reaching the 10,000 steps goal, it doesn’t seem necessary to overload you with tips to take even more steps. After all, you are doing well! Still, we want to give you some tips, which may be helpful in times when it is hard to keep up your high level of physical activity... |
Maintenance | Because your step level is high and you have been able to maintain this for quite a while, it seems unnecessary to give you tips to step more. They would probably not be very helpful. However, we want to emphasize that you are among the few Flemish people who are very active, and that’s really good! Carry on being this active! |
Through contacts with GPs’ organizations, we found a convenience sample of 38 GPs willing to take part in this pretest study to evaluate the dissemination and test the acceptability of the computer-tailored step advice. We recruited participants through GPs, who were asked to personally hand out invitation letters to the 50 first counseling patients eligible for the study. Exclusion criteria were (1) being physically unable to engage in physical activity, (2) already being highly active or participating in sport activities, and (3) not being Dutch speaking. The letter briefly explained the purpose of the project, namely promoting physical activity in the general population through pedometer use and providing computer-tailored feedback; invited the patient to take part in the study; and presented the inclusion criteria: (1) being aged 18–65 years, (2) having Internet access at home or at work, and (3) having a personal email address. To participate, they were required to email us their full name, address, telephone number, date of birth, and name of GP.
On receiving this information from the participants, we sent them an envelope containing a pedometer, a step log for 7 days, information on how to use these instruments, and a stamped, self-addressed envelope for return mailing after 3 months. Participants were first asked to wear the pedometer for 7 consecutive days and to complete the step log in order to assess their baseline step level; they were asked not to increase their step or activity levels from what they would usually do in this period. Afterward, they had to email the step log to us. After receiving the step log, we contacted the participants by telephone to complete the baseline assessment.
After this interview, we randomly assigned participants to (1) the pedometer intervention only (standard condition) or (2) the pedometer intervention supplemented with computer-tailored step advice (tailored condition). Participants in both conditions were mailed generic paper booklets with information on how to increase their steps [
Participants completed informed consent forms, and the study protocols were approved by the Ethics Committee of the Ghent University, Belgium. The study was conducted between January and August 2010.
We used the Yamax Digiwalker SW-200 (Yamax, Tokyo, Japan) in this study, as it is known to be a valid, accurate, and reliable instrument for counting steps in adults [
Participants were requested to record the date, the daily steps taken, and the type and duration of nonambulatory activities (eg, biking and swimming) in an activity log. Following established guidelines [
During a telephone interview at baseline and postintervention, we asked participants their gender, age, height, and weight. The interviewers also obtained information on participants’ perceived health (very good, good, moderate, poor, or very poor), education (primary education, vocational secondary education,; technical secondary education, general secondary education, and college or university), employment status (yes or no), computer and Internet use (daily, weekly, monthly, a couple of times a year, or never), and Internet access at home or at work (yes or no). Furthermore, participants were asked who gave them the invitation letter (GP or other; in the case of answering other, participants were asked to specify). Finally, we assessed their intention to participate in physical activity by asking whether participants planned to increase their steps (yes, within 1 month; yes, within 6 months; or no intention).
To assess physical activity and time spent sitting, we used the long interview form of the International Physical Activity Questionnaire (IPAQ) at baseline and postintervention. Physical activity in a usual week in four different domains was measured: at work, during transport, at home, and during leisure time. The IPAQ has been shown to be a valid and reliable instrument at the population level in Europe [
At postintervention, we assessed the feasibility of disseminating the intervention through GPs. We asked all participants about the usefulness of GPs emphasizing the importance of sufficient physical activity, helping to find ways to increase steps, and providing pedometers to their patients, using 5-point Likert scales (ranging from totally not useful to very useful).
At postintervention, we asked participants in the tailored condition about the understandability, logic, practical use, and length of the questionnaire prior to receiving the advice. Four questions assessed what participants did with the advice (read it, discussed it with others, saved it, or reread it later). The interviewer also asked what the advice indicated about the step level of participants (insufficient, just enough, or sufficient) and whether participants were aware of this. Further, participants were asked about the relevance, credibility, understandability, and length of the advice; whether the advice helped them to gain insight into their physical activity pattern; and whether the advice was an encouragement to increase steps. If participants requested the advice more than once, they were asked about the usefulness of receiving the advice twice or more.
We analyzed all data using SPSS 17.0 for Windows (IBM Corporation, Somers, NY, USA). The level of statistical significance was set at .05. Participant characteristics were described using descriptive statistics. Self-reported physical activity was expressed in minutes/day for total time spent walking and total physical activity, and in hours/day for sitting time (based on guidelines at www.ipaq.ki.se). Walking and total physical activity scores were log transformed to obtain normal distributions. However, for clarity, the numbers in the tables are the means and standard deviations of the nontransformed data. Average daily step counts were calculated, and values over 20,000 steps/day were truncated as 20,000 to limit unrealistically high averages and to ensure normal distributions [
We compared participant characteristics at baseline between the two conditions using independent-samples
The time and intervention effects on body mass index (BMI), self-reported and pedometer-based physical activity, and sitting time were examined using repeated measures analyses of variance with condition as the between-participants factor and time as the within-participants factor. We conducted these analyses using both a retained-sample analysis (only participants who completed postintervention assessments) and an intent-to-treat analysis (assuming baseline values at postintervention for dropout participants). As we found no differences between these two types of analyses, we report only the results of the retained-sample analysis.
Most of the sample were female (54/92, 59%), were highly educated (59/92, 64%), were employed (65/92, 71%), were in good health (62/92, 67%), used the computer (75/91, 82%) and the Internet (69/92, 75%) daily, and did not reach 10,000 steps/day (65/87, 75%) at baseline.
Participant characteristics at baseline.
Characteristic | Tailored |
Standard |
Group |
|
|
|
|||||
Age (years), mean (SD) | 46.6 (10.9) | 47.7 (11.4) |
|
.63 | |
Male, n (%) | 17/45 (38%) | 21/47 (45%) | χ2 1 = 0.5 | .50 | |
BMIa (kg/m2), mean (SD) | 25.8 (4.3) | 26.3 (4.6) |
|
.64 | |
Higher education, n (%) | 30/45 (67%) | 29/47 (62%) | χ2 1 = 0.2 | .62 | |
Employed, n (%) | 35/45 (78%) | 30/47 (64%) | χ2 1 = 2.2 | .14 | |
Good to very good health, n (%) | 26/45 (58%) | 36/47 (77%) | χ2 1 = 3.7 | .06 | |
|
|||||
Daily computer use | 36/45 (80%) | 39/46 (85%) | χ2 1 = 0.4 | .55 | |
Daily Internet use | 30/45 (67%) | 39/47 (83%) | χ2 1 = 3.3 | .07 | |
Internet access at home | 44/45 (98%) | 46/46 (100%) | χ2 1 = 1.0 | .31 | |
Internet access at work | 28/35 (80%) | 22/30 (73%) | χ2 1 = 3.4 | .19 | |
|
χ2 2 = 2.3 | .31 | |||
Within 1 month | 23/43 (54%) | 19/42 (45%) | |||
Within 6 months | 11/43 (26%) | 8/42 (19%) | |||
No intention | 9/43 (21%) | 15/42 (36%) | |||
|
|||||
Walking | 33.2 (60.3) | 44.9 (57.4) |
|
.43 | |
Total physical activity | 142.7 (123.8) | 163.6 (120.8) |
|
.10 | |
Pedometer-based physical activity (steps/day), mean (SD) | 8609 (3370) | 8933 (3367) |
|
.66 | |
Sitting time (hours/day), mean (SD) | 7.0 (3.1) | 7.0 (3.4) |
|
.97 |
a Body mass index.
In total, 23 participants dropped out: 7 had health problems, 3 lacked the time, and 1 went abroad. The other 12 dropout participants could not be reached at postintervention, so the reason for dropout is unknown. Dropout analyses revealed no significant differences between those who dropped out (n = 13 in the tailored condition; n = 10 in the standard condition) and those who did not (data not shown).
From the 1900 available invitation letters (50 per GP, 38 GPs), 1737 letters were handed out to patients. A total of 107 individuals expressed an interest in participating (response rate 6.2%); however, 1 participant did not meet the inclusion criteria and 7 eventually withdrew for family- or work-related reasons, leaving 99 participants at baseline (see
Flow of participants through the study. GP = general practitioner.
Of the 43 participants who received the tailored intervention, 32 completed the postintervention telephone interview (74%). Of this group, 7 did not request the computer-tailored step advice (22%), 18 requested it once (56%), 6 twice (19%) and 1 person three times (3%). The most frequently mentioned reason for not requesting the advice was lack of time; 1 person had computer problems; and 1 believed that he didn’t need the advice. Of those who did request the advice, all found the questions prior to receiving the advice understandable (21/21, 100%), and most had no problems answering them (24/25, 96%), found the questions logically built up (19/20, 95%), and didn’t find the questionnaire too long (14/19, 74%).
After receiving the advice, almost everyone read it (20/21, 95%) and the majority saved it (12/20, 60%). Fewer participants discussed it with others (8/19, 42%), printed it (8/21, 38%), or reread it later (7/20, 35%). Of those who could remember the feedback on their step level, almost half (9/19, 47%) got the advice that they were insufficiently active. The majority (13/19, 68%) had expected the feedback they got. Of those requesting the advice more than once (n = 7), all found it useful to be able to receive the advice several times.
Everyone found the advice understandable (100%), and the majority found the advice credible (17/18, 94%), relevant (15/18, 83%), and not too long (13/18, 72%). The majority also reported that the advice helped them to gain insight into their physical activity pattern (13/18, 72%), and two-thirds found that the advice encouraged them to increase their number of steps (16/24, 67%).
Baseline characteristics of the participants in the tailored condition who requested the computer-tailored step advice at least once and those who did not request the computer-tailored step advice.
Characteristic | At least one |
No request |
Group |
|
|
|
|||||
Age (years), mean (SD) | 47.2 (11.2) | 43.5 (9.9) |
|
.31 | |
Male, n (%) | 11/30 (37%) | 4/13 (31%) | χ2 1 = 0.1 | .76 | |
BMIa (kg/m2), mean (SD) | 26.1 (4.7) | 24.4 (2.7) |
|
.32 | |
Higher education, n (%) | 19/30 (63%) | 9/13 (69%) | χ2 1 = 0.1 | .71 | |
Employed, n (%) | 25/30 (83%) | 10/13 (77%) | χ2 1 = 0.2 | .62 | |
Good to very good health, n (%) | 16/30 (53%) | 9/13 (69%) | χ2 1 = 0.9 | .33 | |
|
χ2 2 = 2.2 | .34 | |||
Within 1 month | 13/29 (45%) | 9/13 (69%) | |||
Within 6 months | 9/29 (31%) | 2/13 (15%) | |||
No intention | 7/29 (24%) | 2/13 (15%) | |||
|
|||||
Daily computer use | 22/30 (73%) | 13/13 (100%) | χ2 1 = 4.3 | .04b | |
Daily Internet use | 18/30 (60%) | 11/13 (85%) | χ2 1 = 2.5 | .11 | |
Internet access at home | 30/30 (100%) | 12/13 (92%) | χ2 1 = 2.4 | .12 | |
Internet access at work | 19/25 (76%) | 9/10 (90%) | χ2 1 = 1.0 | .61 | |
|
|||||
Walking | 30.1 (43.4) | 41.0 (66.2) |
|
.99 | |
Total physical activity | 142.7 (128.0) | 153.9 (124.9) |
|
.28 | |
Pedometer-based physical activity (steps/day), mean (SD) | 7690 (2416) | 10,730 (4319) |
|
.03b | |
Sitting time (hours/day), mean (SD) | 7.0 (3.2) | 7.3 (2.9) |
|
.77 |
a Body mass index.
b .01 <
Effects on body mass index, physical activity, and time spent sitting in both conditions.
Variable/condition | n | Baseline | Postintervention | Change (95% CIa) |
|
|
|
|
||
|
0.7 | .40 | 3.5 | .07 | ||||||
Tailored condition | 27 | 26.3 (4.7) | 26.0 (4.5) | –0.3 (–0.6 to 0.0) | ||||||
Standard condition | 33 | 26.2 (4.6) | 26.0 (4.6) | –0.2 (–0.5 to 0.3) | ||||||
|
||||||||||
Walking | 0.1 | .82 | 0.1 | .71 | ||||||
Tailored condition | 21 | 17.8 (21.8) | 26.4 (34.6) | 8.6 (–6.6 to 23.9) | ||||||
Standard condition | 22 | 46.2 (59.7) | 38.9 (44.8) | –7.3 (–40.8 to 26.1) | ||||||
Total physical activity | 2.0 | .16 | 0.5 | .47 | ||||||
Tailored condition | 32 | 131.0 (121.1) | 142.0 (108.9) | 11.0 (–25.5 to 47.5) | ||||||
Standard condition | 36 | 165.9 (125.7) | 138.2 (98.5) | –27.8 (–72.5 to 16.9) | ||||||
|
1.1 | .31 | 5.0 | .04b | ||||||
Tailored condition | 10 | 9162 (2542) | 10,668 (3826) | 1505 (–1850 to 4861) | ||||||
Standard condition | 10 | 9549 (4903) | 13,690 (4743) | 4141 (462 to 8744) | ||||||
|
0.0 | .85 | 2.4 | .12 | ||||||
Tailored condition | 28 | 7.1 (3.0) | 6.6 (3.1) | –0.5 (–1.5 to 0.4) | ||||||
Standard condition | 35 | 7.1 (3.6) | 6.4 (3.2) | –0.7 (–1.9 to 0.5) |
a Confidence interval.
b
We developed a new pedometer-based, computer-tailored step advice intervention and examined the feasibility of disseminating this tool through general practice, and its acceptability and preliminary efficacy in adults. Overall, participants accepted the computer-tailored step advice well. Results are comparable with the previous computer-tailored advice intervention [
Despite this positive evaluation of the computer-tailored step advice, the tool did not result in significant effects on behavior or BMI, compared with participants who did not receive the advice. The evidence on this matter is inconsistent: while some physical activity programs did find good outcomes [
The fact that the standard condition in the present study was not a true nonintervention may partially explain the lack of interaction effects. Participants in our standard condition used a pedometer and received standard 10,000 steps intervention materials, two strategies that have been shown to be effective in increasing physical activity in adults [
The initial response rate to the invitation letter spread by GPs was very poor. Only 6% signed up for the project after receiving an invitation letter from their GP; we did, however, expect that more participants would respond, as previous research showed that face-to-face contact significantly increased recruitment for an online tailored intervention (46%) compared with recruitment via a flyer only (6%) [
The number of participants actually visiting the website and requesting the computer-tailored step advice was reasonably high (nearly 70%) when compared with other studies. Mailing participants a personal login and password seems an effective strategy to invite them to visit the website. Figures were lower in previous Belgian [
Some limitations need to be mentioned. First, as mentioned above, the small sample, which was mainly female, highly educated, employed, and in good health, is the main weakness of the present study. As such, the generalizability of the present findings is limited. Second, the lack of information on how GPs spread the invitation letters confines our understanding of the low initial response rate. In addition, we do not know what the dissemination strategy of the GPs was: did they hand out the invitation letters to their first 50 patients or only to those who were most in need of a physical activity intervention? We also do not know how motivating GPs were during recruitment. The fact that we collected no data on the recruitment process from GPs is a limitation in terms of understanding the poor retention rates. A final weakness is the use of self-reports, which may be subject to recall [
Existing interventions promoting step count increases could benefit from an additional computer-tailored component. For example, community-based interventions guided by socioecological models of health behavior, such as 10,000 Steps Rockhampton, Canada on the Move, and 10,000 Steps Ghent, focus primarily on social systems, policy, and organizations [
To conclude, we describe the development of a new pedometer-based, computer-tailored step advice intervention, which was disseminated through GPs. Despite the poor results of the recruitment method, participants evaluated the dissemination through general practice positively and found it useful for GPs to promote physical activity. A substantial number of participants requested the computer-tailored step advice and rated the acceptability of the tool very well. However, the tailored condition showed no superior effects on self-reported and pedometer-based physical activity, BMI, or time spent sitting, compared with the standard condition. More research is needed to enhance our knowledge of the best dissemination channel and the effectiveness of this tool in larger trials.
Examples of screenshots of the web-based computer-tailored and pedometer-based physical activity advice.
CONSORT-EHealth V1.6 Checklist [
body mass index
general practitioner
International Physical Activity Questionnaire
K De Cocker was supported by the Research Foundation Flanders (FWO) (postdoctoral research fellowship: FWO11/PDO/097). C Vandelanotte was supported by National Health and Medical Research Council of Australia (#519778) and National Heart Foundation of Australia (#PH 07B 3303) postdoctoral research fellowships.
The authors are the developers of the intervention. No other conflicts have been declared.