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					Paper presented at Walk21-VI “Everyday Walking Culture”, The 6th International Conference
on Walking in the 21st Century, September 22-23 2005, Zurich, Switzerland
www.walk21.ch www.walk21.com


Are pedometers useful motivational tools for increasing walking in
sedentary adults?
Graham Baker, BSc (Hons): University of Strathclyde
Professor Nanette Mutrie, DPE, M.Ed, PhD, FBASES: University of Strathclyde

Contact details
Graham Baker
PhD Candidate
PESOE Building
Strathclyde University (Jordanhill Campus)
Glasgow
G13 1PP
UK
g.baker@strath.ac.uk


Abstract
Walking helps people achieve the recommended accumulation of 30 minutes moderate activity
daily. It is accessible to both genders, young and old, and is capable of overcoming many
barriers such as time or expense. The aim of this study was to investigate the effectiveness of
pedometers, in conjunction with goal setting programmes (designed to accumulate 30 minutes of
walking at least 5 days of the week), in providing motivation for walking. The study used the
transtheoretical model of behaviour change (TTM) as a framework for behaviour change.
Seventy-one participants (54 women and 17 men, aged 42±11 years; range 18-61 years) wore a
sealed pedometer for 7 days to establish baseline step counts. Participants were randomly
assigned to; pedometer intervention (n=23, pedometer open for feedback plus 4-week goal
setting programme in steps), minutes goal setting intervention (n=24, 4-week goal setting
programme in minutes) or control group (n=24, no action for 4 weeks). Questionnaires based on
the 4 components of the TTM (self-efficacy, decisional balance, process of change, stage of
change) and a 7-day recall of physical activity (PA) were completed at baseline and week 4.
A one-way ANOVA was performed between the groups for step-count at baseline, week 4 and
step-count difference (week 4 minus baseline). No significant difference was found between the
groups at baseline in terms of step-count. However at week 4 (p=0.044) and for step-count
difference (p=0.000) significant differences were found. A one sample t-test identified that the
pedometer intervention group significantly increased step count from baseline to week 4 (mean
increase of 20,186 steps, p<0.001). Both other groups displayed no significant difference. 1-
sample Wilcoxon tests showed both the pedometer intervention group (p=0.012) and minutes
goal setting group (p=0.002) significantly increased their total 7-day recall of PA. The control
group reported no significant difference. For all groups (at baseline and at week 4), the
processes of self-liberation and self re-evaluation received the highest frequency of use scores.
Wilcoxon analysis found the minutes goal setting group significantly increased their use of
counter conditioning (p=0.022), while the control group significantly increased their use of
stimulus control (p=0.007). 69% of participants considered themselves inactive at baseline,
decreasing significantly (p<0.05) to 45% at 4 weeks. Neither self-efficacy or decisional balance
displayed any change over time for any group, or differed significantly between groups.
The combination of pedometer feedback and a goal-setting programme appears to provide
additional short-term motivation for those wishing to increase walking over a goal-setting
programme alone. Further research needs to examine possible long-term motivational effects of
pedometers. The application of the transtheoretical model within active living interventions
should be examined with specific attention to the questionnaires.
Biographies

Graham Baker

Graham Baker has a Faculty of Education PhD scholarship at the University of Strathclyde and
is investigating the motivational effect of pedometers in sedentary individuals. Previously
Graham achieved a first class Honours degree in Physiology and Sports Science at the
University of Glasgow.


Professor Nanette Mutrie

Nanette Mutrie is Professor of Exercise and Sport Psychology at the University of Strathclyde
and is also a visiting professor at the MRC Social and Public Health Sciences Unit at the
University of Glasgow. She is an Accredited Sport and Exercise Psychologist with the British
Association of Sport and Exercise Science (BASES).
Are pedometers useful motivational tools for increasing walking in
sedentary adults?

Graham Baker, BSc (Hons): University of Strathclyde
Professor Nanette Mutrie, DPE, M.Ed, PhD, FBASES: University of Strathclyde


Introduction

In 1995 the American College of Sports Medicine issued new physical activity guidelines which
shifted from the traditional cardiovascular fitness message and towards “active living
recommendations” (Pate et al, 1995). The new guidelines state that attaining 30 minutes of
accumulated moderately intense physical activity is sufficient to achieve the associated health
benefits of physical activity, such as decreased mortality and morbidity. Moderately intense
physical activity is defined as activity performed at 3-6 MET’s which is the equivalent of
walking 3-4mph for most healthy adults (Pate et al, 1995). There is now an accumulation of
evidence which supports the active living recommendations, including the US Surgeon
General’s report, (US Department of Health and Human Services, 1996), and walking as a way
to achieve the recommendations.

Walking has been increasingly promoted as a viable tool for increasing ones’ physical activity
given its’ numerous and varying benefits. Walking has many associated health benefits, with the
possibility of being used as a weight management technique. It can be employed all year round,
carries little risk and is perhaps the one activity that is available to almost all individuals,
(Morris and Hardman, 1997). Walking also overcomes many of the barriers associated with
more structured forms of exercise such as time and expense. Previous walking interventions
have been successful in both raising awareness and promoting short-term behaviour change,
however the challenge still remains to provide walking interventions that can bring long-term
adherence to walking.

Pedometers have recently been promoted in the media as effective tools to increase walking,
with the target of achieving 10,000 steps/day being the most popular proposal. Pedometers are
well established as a form of objectively measuring walking through step-counts, and have been
proven to be both valid and reliable (Tudor-Locke et al, 2002; Crouter et al, 2003; Schneider et
al, 2004). Traditionally pedometers were sealed to provide objective measurement. However
recent studies designed to increase walking have employed the pedometer open for feedback
(Sugiura et al, 2003; Talbot et al, 2003; Chan et al, 2004). This has led to the suggestion that
pedometer feedback, by allowing the individual to monitor the step-count and set goals, may be
used as a motivational tool.

The majority of recent pedometer research has focused on identifying the best way to implement
the pedometer in terms of step-goals and targets. The popular 10,000steps/day target is deemed
inappropriate, as is any universal step-goal due to the variations noted in different sub-
populations, (Tudor-Locke and Myers, 2001). Research from Welk et al, (2000), Wilde et al,
(2001) and others has indicated that future walking programmes should be based on
personalized step-goals. With the overall aim of achieving the accumulated 30 minutes of
activity a day by adding 3,100-4,000 steps onto initial baseline step-counts.
However, there is in fact little empirical evidence to support the claim of pedometers as
motivational tools. Marshall and Ferney, (2003) have shown that having access to pedometer
feedback can result in significantly increased walking compared to those who wore a sealed
pedometer. Rooney et al, (2003) has also suggested that the mere presence of a pedometer may
increase walking. A study from Mutrie et al, (2004) attempted to establish whether using a
pedometer for feedback combined with a goal setting programme provided additional
motivation over use of only a goal setting programme. Both groups significantly increased their
walking over 4-weeks regardless of whether the pedometer was open for feedback or sealed.
Further, Mutrie et al also established that the increase in step-counts was only evident in the
short-term and after 52-weeks walking levels had returned to baseline. Contrasting to these
studies Eastep et al, (2004) found no increase in walking levels either in those who wore a
pedometer open for feedback, or a sealed pedometer. However, Easteps’ study failed to
implement a goal setting strategy which has been suggested as vital to the success of
pedometers, (Tudor-Locke and Myers, 2001).
The Transtheoretical Model (TTM) for behaviour change is a theoretical framework for how
behaviour change occurs. It consists of 4 basic constructs and has been adapted to deal with
exercise behaviours. The 4 constructs are: stage of change – 5 distinct stages of an individuals’
readiness to cease inactivity; processes of change – 10 processes which represent an individuals
behaviours; emotions when becoming active; self-efficacy – the scale of confidence about
becoming more active and decisional balance – weighing of the pros and cons in becoming more
active. A review from Adams and White, (2002) suggest that physical activity interventions
based around the TTM can be effective in encouraging short-term physical activity adoption.
However, the long-term effects of the TTM are limited. It has also been suggested the relevance
of the TTM relating to the active living message is not established and that the reliability of
measurement needs to be improved (Marshall and Biddle, 2001).

Aim

The aim of this study is to investigate the effectiveness of pedometers, in conjunction with goal-
setting programme in providing additional motivation for walking compared with a goal-setting
programme only using the transtheoretical model as a framework for behaviour change.

Methods

Participants

Individuals (n=71) were volunteers who responded to adverts (posters, newsletters and emails)
and all displayed an interest in improving physical activity levels by increasing walking.

Instruments & Questionnaires

Participants used the Omron HJ-104 Step-O-Meter due to its’ 7-day memory capability and
automatic daily reset function. All participants completed the Physical Activity Readiness
Questionnaire (Thomas et al, 1992) to ensure they were physically able to participate. The 4
constructs of the transtheoretical model (TTM) were measured using standard questionnaires.
The stage of exercise behaviour change questionnaire was employed (Marcus et al, 1992b).
Questionnaires developed by Marcus and Simkin (1994) to measure decisional balance and self-
efficacy were employed. Processes of exercise behaviour change were measured by the standard
40-item instrument commonly used for exercise behaviour, (Marcus et al, 1992a). A 7-day
recall of physical activity was obtained using The Scottish Physical Activity Questionnaire
(SPAQ) (Lowther et al, 1999).
Procedures

Participants were met at the initial meeting and completed the questionnaires based on the 4
constructs of the TTM. Participants were then instructed to wear a sealed pedometer for 7 days
to establish baseline step-counts. Participants were instructed not to alter normal walking
patterns and to wear the pedometer continuously apart from when sleeping, showering or
engaging in any form of structured physical activity or sport. At 7 days baseline step-counts
were obtained and all participants completed the 7-day recall of physical activity SPAQ.
Participants were then randomly assigned to either the pedometer intervention group, the
minutes intervention group or the control group using allocation by sequentially ordered
envelopes.

Participants in the pedometer intervention group (n=23) wore a pedometer, open for feedback,
for 28 days during which they followed a goal-setting programme based on steps (see Table 1).
Given that 1,000 steps is roughly equivalent to 10 minutes moderate walking (Sidman, 2002),
participants were instructed to walk 3,000 extra steps on at least 5 days of the week in order to
meet active living recommendations. At 28 days participants were met and their previous 7-day
step-count recorded. Participants also completed the 7-day recall of physical activity and
questionnaires based on the 4 basic constructs of the TTM.

Participants in the minutes intervention group (n=24) followed a corresponding goal-setting
programme based in minutes for 28 days (see Table 1). At 21 days they were met and asked to
wear a sealed pedometer for the final 7 days of the walking programme. At 28 days participants
were met and their previous 7-day step-count recorded, at which time they also completed the 7-
day recall of physical activity and the questionnaires based on the 4 basic constructs of the
TTM.

Participants in the control group (n=24) were instructed to follow their normal walking patterns
for 28 days. At 21 days participants were met and asked to wear a sealed pedometer for the final
7 days. At 28 days participants were met and their previous 7-day step-count recorded, at which
time the 7-day recall of physical activity was completed as were the questionnaires based on the
4 basic constructs of the TTM.

Table 1: Graduated weekly step-counts targets for both intervention groups
over the 4-week study
    Week Pedometer Intervention Targets            Minutes Intervention Targets
    1       1500 extra steps at least 3 days of    15 extra minutes at least 3 days of the
            the week                               week
    2       1500 extra steps at least 5 days of    15 extra minutes at least 5 days of the
            the week                               week
    3       3000 extra steps at least 3 days of    30 extra minutes at least 3 days of the
            the week                               week
    4       3000 extra steps at least 5 days of    30 extra minutes at least 5 days of the
            the week                               week
Results

Participants

Participants (n=71) who completed the 4-week programme had an average age of 42.41±10.95
years with a range of 18-61 years. There were no significant differences between groups in
terms of age. The participants consisted of 76% (n=54) women and 24% (n=17) men.

Step-counts

A one-way ANOVA was performed between the groups for step-count at baseline, week 4 and
step-count difference (week 4 minus baseline). No significant difference was found between the
groups at baseline in terms of step-count. However at week 4 (p=0.044) and for step-count
difference (p<0.001) significant differences were found. Follow-up Bonferroni comparisons
failed to identify the exact location of the difference at week 4, however Bonferroni
comparisons identified that the change from baseline to week 4 between the pedometer
intervention group and the control group was significant (p<0.001).

One-sample t-tests performed on each group identified that from baseline to week 4 the minutes
intervention group and the control group did not significantly alter their step-count. The
pedometer intervention group significantly increased their step-count from baseline to week 4,
by a mean increase of 20,186 steps (p<0.001, CI: 12194, 28178). Figure 1 displays the mean
step-count over time for each group.

           85000

           80000

           75000
    te s




           70000
   S p




           65000

           60000

           55000

           50000
                             Baseline                    Week 4
                                         Tim e

              Peodmeter Intervention    Minutes Intervention       Control



Figure 1: Mean step-counts for each group at baseline and week 4

7-day recall of physical activity

Kruskal Wallis tests identified that there were no significant differences between groups in
terms of total minutes recalled either at baseline or week 4. Wilcoxon within group tests
identified that in terms of total minutes of recalled physical activity the pedometer intervention
group (p=0.012) significantly increased the total minutes recalled from baseline to week 4 by
336 minutes. The minutes intervention group significantly (p=0.002) increased the total minutes
recalled from baseline to week 4 by 466 minutes. The control group displayed no significant
increase in total minutes recalled from baseline to week 4.

The total minutes were then broken down into minutes recalled in leisure time and minutes
recalled in occupational time. Kruskal Wallis tests identified that there were no significant
differences between groups at either baseline or week 4 in terms of either leisure or occupational
minutes recalled. Wilcoxon within group tests identified that no group significantly altered their
recall of occupational minutes between baseline and week 4. However, Wilcoxon tests identified
that both the pedometer intervention group (p=0.001) by a mean increase of 316 minutes and the
minutes intervention group (p=0.001) by a mean increase of 403 minutes significantly increased
their recall of leisure minutes from baseline to week 4. The control group displayed no
significant difference.

Stage of Change

Chi-squared analysis determined that there were no significant differences between the groups at
baseline or at week 4 in terms of stage of change. For analysis it was decided to combine the
stages of pre-contemplation, contemplation and preparation to establish those who were
inactive, and combine the stages of action and maintenance to establish those who were active.
At baseline 69% of all participants considered themselves inactive, which fell to 45% of all
participants at week 4. This movement of 17 participants from being inactive at baseline to
active at week 4 was statistically significant (p<0.005).

Self-efficacy

Self-efficacy was scored on a 7-point Likert scale where 1 = extremely unconfident and 7 =
extremely confident. A median score of 6 was found for each group at both baseline and week 4.
Kruskal Wallis analysis identified that there were no significant differences between groups in
terms of reported self-efficacy either at baseline or week 4. Wilcoxon within group tests
identified that no group altered their reported self-efficacy from baseline to week 4.

Decisional Balance

Decisional Balance was scored on a 5-point Likert scale with a minimum score of 3 and a
maximum score of 15 obtainable for both pros and cons. Median scores for each group are
displayed in Table 2.

Table 2: Median scores for pros and cons by group at each time-point
                    Pedometer              Minutes                Control
                    Intervention           Intervention
                 Baseline 4-Week Baseline 4-Week Baseline 4-Week
  Median         12.00       13.00      11.50      11.50       12.00      11.50
  Pros
  Median         5.00        6.00       5.00       5.00        5.00       6.00
  Cons

Kruskal Wallis tests identified that there were no significant differences between groups either
for pros or cons at baseline or week 4. Wilcoxon within group tests identified that there were no
significant changes from baseline to week 4 for either pros or cons in any group.

Processes of Exercise Behaviour Change

The process of change questionnaire contains 40 questions, the 10 processes covered equally
with 4 questions each. A Likert scale, of 1-5, is employed for each question, used as a rating
scale for the frequency of each process used, 1 being “used never”, and 5 being “used
repeatedly”. By addition of the 4 questions, a score can be established for each process, with 4
being the minimum score and 20 the maximum score possible.
Kruskal Wallis analysis of each process at baseline established that 9 of the 10 processes were
not significantly different. A significant difference in process use between the groups was found
at baseline for the process of self-liberation (p=0.023). Follow-up Mann Whitney tests
established that the pedometer group reported a significantly lower use of self-liberation than the
control group. Kruskal Wallis analysis of each process at week 4 established that there were no
significant differences in process use for any process between groups. Table 3 displays the
ranked median process use at week 4 for each group. A similar table is found for process use at
baseline with the processes of self-liberation and self re-evaluation being the most frequently
used processes and the processes of helping relationships and stimulus control being the least
frequently used processes.

Table 3: Ranked median process use by group at week 4
    Process                    Pedometer         Minutes                 Control
                               Intervention      Intervention
    Self Liberation            14.0              14.5                    14.0
    Self Re-evaluation         14.0              13.5                    13.0
    Counter Conditioning       11.0              14.0                    11.0
    Consciousness Raising      11.0              11.0                    10.0
    Reinforcement              9.0               10.5                    10.5
    Management
    Environmental        Re- 9.0                 11.0                    9.0
    evaluation
    Social Liberation          9.0               10.0                    9.0
    Dramatic Relief            8.0               8.0                     9.0
    Helping Relationships      6.0               10.5                    7.5
    Stimulus Control           7.0               6.5                     8.0

Wilcoxon tests were performed on each group to determine any change in process use from
baseline to week 4. The pedometer intervention group displayed no significant differences in
process use from baseline to week 4. Wilcoxon analysis found that the minutes intervention
group significantly increased their use of counter-conditioning (p=0.022) from baseline to week
4, and the control group significantly increased their use of stimulus control (p=0.007) from
baseline to week 4.

Discussion

The results from this study suggest there is a short-term additional motivational effect of using a
pedometer compared with using only a goal-setting programme. The pedometer intervention
group was the only group to significantly increase their step-count from baseline to week 4.
Despite the minutes intervention group receiving corresponding targets they failed to
significantly increase their step-count. This would indicate that the feedback received from the
pedometer allowed the pedometer intervention group to monitor their walking levels to a greater
degree. Indeed, a significantly higher percentage of the pedometer intervention group (77%)
achieved their 4 week walking goals, compared with the minutes intervention group (33%) and
control group (17%).

This is further supported by qualitative data from participants in the pedometer intervention
group who suggested that the pedometer allowed them to easily set short-term goals and
provided motivation to achieve these. The minutes intervention group also suggested that having
the pedometer would have helped them achieve their goals.
These results concur with previous research such as Rooney et al, (2003) which suggest that
pedometers can provide a short-term motivational effect. Whereas Mutrie et al, (2004) suggests
that a goal setting programme alone can provide the same motivational effect as those also
employing pedometer feedback, these results would suggest that it is the pedometer feedback
which is imperative to increase walking. This could be explained by the participants in Mutrie et
al, (2004) who followed a goal setting programme alone, actually wore a sealed pedometer at all
times, and it could be the mere presence of the pedometer which accounted for the increase in
walking in that group.

Both the pedometer intervention and the minutes intervention group significantly increased their
recalled physical activity, by significantly recalling a greater number of leisure minutes spent
being physically active. No group altered their recalled minutes being physically active at work
which suggests that it is difficult to incorporate walking during working hours due to the nature
of the participants’ occupation.

The decisional balance and self-efficacy results indicate that walking is seen as an activity
which most people can participate comfortably and successfully in. The high levels of self-
efficacy reported throughout the study would suggest that the active living recommendations are
seen as realistic and achievable. Despite this the minutes intervention group did not achieve the
recommendations by week 4 indicating that a successful intervention, such as the pedometer, is
still necessary to help people achieve these. There may be a suggestion that these questionnaires
do not fully explore an individuals’ self-efficacy and decisional balance with respect to walking,
and there perhaps needs to be re-development or refining of the questionnaires.

Current theory regarding the processes of exercise behaviour change is that experiential
processes are more commonly used during the early stages of change. However, 69% of all
participants considered themselves inactive at baseline yet certain behavioural processes such as
self-liberation and counter-conditioning were used just as frequently as experiential processes.
This would agree with previous research which has suggested that experiential and behavioural
and experiential processes may not operate according to current theory with regards to physical
activity (Marshall and Biddle, 2001). Marcus et al, (1992a) suggested that all processes of
change might be important at all stages of change. Our results indicate that this may indeed be
the case, and further qualitative data from participants indicated that several of the questions
were either not relevant or simply confusing. Indeed Pate et al, (1995) suggested a need to
refine the process questionnaire when dealing with the active living message.

Conclusion

These results agree with previous research that pedometers can provide a short-term
motivational effect for people wishing to increase walking. This study helps to establish a
knowledge base that highlights and identify this effect. The results also identify aspects of the
transtheoretical model that need to be further examined for future use with active living
interventions. This study further emphasizes the need for research into the long-term effect of
pedometer motivation and adherence.

Acknowledgements

   1. Walking the Way to Health Initiative – for the supply of the Omron HJ-104 Step-O-
      Meters
   2. Ashley Gillies, Louise Galloway, Sabina McDonald, Paul MacDonald, Jessica Tyrrell
      for help with data collection.
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Description: Mainly by electronic pedometer vibration sensors and electronic counter. People walking up and down the center of gravity should be a little bit. Displacement of the waist and down to the most obvious, step counter so the most suitable for hanging on the belt. The so-called vibration sensor is actually a balance weight in the upper and lower vibration balance is upset to make a contact to appear on / off action by the electronic counter to record and display the main function is complete, the other calorie consumption, distance to complete conversion by the circuit .