Article Analysis and Evaluation of Research Ethics and Summary and Descriptive Statistics
Complete an article analysis and ethics evaluation of the research using the “Article Analysis and Evaluation of Research Ethics” template. See Chapter 5 of your textbook as needed, for assistance.
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Provide the following descriptive statistics:
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RESEARCH Open Access
Why are some people more successful at
lifestyle change than others? Factors
associated with successful weight loss in the
BeWEL randomised controlled trial of adults
at risk of colorectal cancer
Martine Stead1*, Angela M. Craigie2, Maureen Macleod2, Jennifer McKell1, Stephen Caswell2, Robert J. C. Steele2
and Annie S. Anderson2
Abstract
Background: The BeWEL (BodyWEight and physicaL activity) randomised controlled trial demonstrated that a
weight management programme offered in the colorectal cancer screening setting was effective. However, the
differential responses of participants to the programme were notable. This study aimed to explore the factors
associated with success and to identify implications for future programme design.
Methods: Analyses were conducted of quantitative data (n = 148) from the BeWEL intervention group to compare
demographic and psychosocial characteristics and lifestyle changes in those who met and exceeded the target 7 %
weight loss (‘super-achievers’) with those who achieved only ‘moderate’ or ‘low’ amounts of weight loss (2–7 %
loss, or <2 % loss, respectively). In-depth qualitative interviews (n = 24) explored in detail the motivations, actions,
pathways to weight loss and circumstances of study participants.
Results: Over the 12 month intervention period, mean percentage weight loss of super-achievers (n = 33) was
11.5 %, compared with moderate-achievers (n = 58) who lost 4.2 %, and low-achievers (n = 57) who gained 0.8 %.
Compared to other groups, super- achievers increased their fruit and vegetable intake (p < 0.01) and physical activity
(step count, p < 0.01). ‘Super-achievers’ did not differ in baseline demographic characteristics from other participants.
However, significantly fewer reported that their activities were limited by physical and emotional health and they
were more likely to perceive their current diet as harmful. Qualitative analyses found no consistent patterns among
super-achievers in relation to some factors identified as important in previous studies, such as social support.
However, super-achievers shared several characteristics such as determination and consistency in their engagement
with the intervention, receptivity to new information and prompts, previous positive experience of changing health
behaviours, being motivated by early success, making changes routine, and an ability to devise and apply strategies
for dealing with setback and ‘relapse’ triggers.
Conclusions: Successful lifestyle change depends on active engagement as well as effective intervention
ingredients. Weight loss interventions are likely to be more effective where they can adapt to participants’ differing
characteristics and needs, while also providing core elements likely to build success.
Keywords: Lifestyle change, Intervention, Diet, Physical activity, Weight loss, Colorectal cancer screening, Factors,
Qualitative, Quantitative
* Correspondence: martine.stead@stir.ac.uk
1Institute for Social Marketing, University of Stirling, Stirling FK9 4LA, Scotland, UK
Full list of author information is available at the end of the article
© 2015 Stead et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution License
(http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://
creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Stead et al. International Journal of Behavioral Nutrition
and Physical Activity (2015) 12:87
DOI 10.1186/s12966-015-0240-2
http://crossmark.crossref.org/dialog/?doi=10.1186/s12966-015-0240-2&domain=pdf
mailto:martine.stead@stir.ac.uk
http://creativecommons.org/licenses/by/4.0
http://creativecommons.org/publicdomain/zero/1.0/
http://creativecommons.org/publicdomain/zero/1.0/
Background
Prevention trials have shown that lifestyle interventions
that achieve and maintain significant weight loss can
have a favourable effect on diabetes and cardiovascular
risk factors [1, 2]. It is plausible that these lifestyle
changes would also have favourable effects on the risk of
obesity-related neoplasia. With respect to colorectal can-
cer, Jacobs and colleagues [3] reported obesity as a risk
factor for short-interval (3 year follow up) development
of colorectal adenomas (identifiable pre-cursor lesions of
CRC), and although it is unclear at what stage obesity
impacts on adenoma development, there is evidence that
adenoma risk increases amongst adults who have gained
weight in the 5 years prior to colonoscopy investigations
[4]. The same study also demonstrated that a higher
BMI was a stronger risk factor for advanced adenoma
recurrences, when compared with non-advanced lesions.
It is interesting to note that a study from Japan of 1650
subjects diagnosed with an adenoma reported that the
subsequent incidence of adenomas was significantly
lower in people who lost weight in the one year follow
up period than in those who maintained or gained
weight [5]. The case for exploring weight reduction
strategies in people diagnosed with CRC adenomas is
also supported by long term follow up trials of bariatric
surgery showing significant reductions in CRC risk [6].
In light of the evidence above, the colorectal cancer
screening setting has been described as an unexplored
opportunity for endorsing changes in health behaviours
[7, 8]. The BeWEL randomised controlled trial (RCT) [9]
demonstrated that the colorectal cancer screening setting
offers a useful opportunity to initiate and achieve suc-
cessful weight management in colorectal adenoma
bearers aged 50 to 74 years with a body mass index
(BMI) >25 kg/m2. The trial demonstrated sustained
changes in body weight, physical activity, eating and drink-
ing habits over a 12 month intervention programme deliv-
ered through three face-to-face visits with a counsellor
and nine monthly telephone calls.
Both groups lost significant weight, with the inter-
vention group losing on average 3.50 kg (SD 4.91 kg,
95 % CI 2.70 to 4.30) and the control group losing
0.78 kg (SD 3.77 kg, 95 % CI 0.19 to 1.38) [9]. However,
the significant group difference of 2.69 kg (95 % CI 1.70
to 3.67) highlights the overall success associated with
the intervention programme and merits further investi-
gation to examine the differential responses of partici-
pants to the programme. For example, only 33 (22 %)
participants achieved the programme target of >7 %
body weight loss [9]. While there is increasing evidence
that carefully designed programmes can lead to suc-
cessful weight loss [10], the reasons for the variation in
outcomes found in such programmes are not well
understood.
A number of studies have attempted to shed some
light on why some people are more successful at achiev-
ing or maintaining weight loss than others. For example,
an online survey of participants in a commercial weight
loss programme found that success was associated with
various types of control over eating, such as greater diet-
ary restraint, less tendency to eat to control mood and
emotion, not skipping meals, not keeping snack foods in
the house and eating takeaway foods less frequently [11].
Similarly, Fuglestad and colleagues’ [12] study of weight
loss among individuals who had recently lost substantial
weight on their own initiative found that greater regularity
and control in eating was associated with greater recent
weight loss and greater fruit and vegetable intake. How-
ever, neither study investigated the potential contribution
of wider factors which might explain why some partici-
pants were better able to control their eating than others.
A systematic review [13] of the factors reported in
quantitative studies which were associated with success-
ful participation in lifestyle behaviour change pro-
grammes (not solely focused on weight loss) found that
the factors most consistently associated with uptake of
lifestyle change related to support from family and
friends, transport and other costs, and beliefs about the
causes of illness and lifestyle change, with depression
and anxiety also appearing influential. However, the re-
view reported that many factors showed inconsistent
patterns with respect to uptake and completion of life-
style change programmes. Another review, this time fo-
cusing on factors identified in qualitative studies [14],
found that the most commonly reported influences were
those relating to social support (whether provided for-
mally or informally), beliefs (about the self or the causes
and management of poor health, and the value of main-
taining lifestyle behaviours), and other psychological fac-
tors (including attitude, thinking and coping styles, and
problem solving skills). The same review notes that influ-
encing factors are interlinked, and that while the literature
may help us to identify individual factors associated with
successful lifestyle change, there is still a limited under-
standing of the nature of the relationships between factors
and how they differ between individuals. Similarly, Dalle
Grave and colleagues [10] state that despite some gains in
insight, knowledge regarding predictors of weight loss re-
mains incomplete.
The current work aimed to explore the factors associ-
ated with success in weight loss in the BeWEL study by
comparing, both quantitatively and qualitatively, those
who succeeded in achieving more than 7 % weight loss with
those who were less successful. The quantitative analysis
examined the possible contribution of a range factors
thought to be associated with weight loss, including socio-
demographic and body weight characteristics, health per-
ceptions, quality of life, self-efficacy and perceptions of
Stead et al. International Journal of Behavioral Nutrition and Physical Activity (2015) 12:87 Page 2 of 12
lifestyle, while the qualitative study enabled a more open-
ended exploration of possible factors.
Methods
Quantitative and qualitative methods were used to identify
the factors associated with success in weight loss. Two ap-
proaches were used: a sub-group analysis of quantitative
data for those participants who participated in the BeWEL
intervention and completed follow-up measures, and quali-
tative interviews with a sample of 24 intervention partici-
pants who achieved varying levels of weight loss success.
Recruitment
Recruitment for the BeWEL RCT took place in four
Scottish NHS health board areas from November 2010
to May 2013. Participants aged 50 to 74 years who had
taken part in the Scottish Bowel Screening programme
and undergone polypectomy for adenoma were informed
about the study in writing. Those indicating an interest
in participating were telephone-screened by a research
nurse for eligible criteria: BMI >25 kg/m2, able to under-
take physical activity and provide informed consent, not
pregnant and without insulin dependent diabetes melli-
tus or any cancer diagnosis. Eligible participants were
then posted a more detailed information leaflet and in-
vited to attend their local study centre to provide in-
formed written consent and undergo baseline measures.
Baseline and follow up measures
Socio-demographic data on age, gender, ethnicity, mari-
tal status, education, employment and postcode were re-
corded at baseline [15]. Objective measures recorded at
baseline, three months and 12 months included height,
weight, waist circumference, blood pressure, fasting
blood samples and physical activity.
Physical activity
levels were measured objectively using a SenseWearTM
armband (BodyMedia Inc. Pittsburgh, PA) worn on the
upper arm for 7 days to provide participants’ daily step
count, and time spent in sedentary, moderate (3 to <6
METS) and vigorous (≥6 METS) activities [16].
An interviewer-administered questionnaire was used
to record self-reported dietary intake, frequency of alco-
hol consumption, and self-efficacy and perceptions of
lifestyle [17, 18]. Participants were assigned scores for
fibre, fat and unsaturated fat using the Dietary Instru-
ment for Nutrition Education (DINE) questionnaire [19].
The fibre score (range 3–88) was based on the frequency
of intake of bread, rice, potatoes, pasta, other starchy
foods and fruit and vegetables (including beans and len-
tils). The fat score (range 7–>72) was based on intakes
of substantial contributors to fat intake i.e. dairy foods,
meat, processed meat, fish, fried foods, sweet and
savoury snacks and fat spreads, and the unsaturated fat
score (range 3–12) was based on the type of fats used.
Daily portions of fruit and vegetables were estimated
using a modification of Cappuccio and colleagues’ two-
item questionnaire [20], which asked ‘How many pieces
of fruit and vegetables (excluding potatoes) do you
eat—of any sort—on a typical day?’, recording fruit and
vegetable portions separately. Fruit and vegetable juices
only counted as a maximum of one portion per day. Por-
tion sizes were illustrated using show-cards as defined
by the NHS Livewell Portion Size guidance [21].
Sugary drink intake (excluding diet, low-calorie drinks
and fresh fruit juice) was self-reported using nine fre-
quency categories whereas typical consumption of alco-
hol (on week days and weekends) was assessed using
questions from the Alcohol Use Disorders Inventory
Test (AUDIT) [22] questionnaire.
Ethical approval was granted by NHS Tayside Committee
on Medical Research Ethics (Ref 10/S1402/34).
Randomisation
Following baseline measures, participants were rando-
mised, 1:1, to parallel-groups using a permuted-block
technique. Allocation was to either a control group
(weight loss booklet) or a 12-month intervention group
(three face-to-face visits with a counsellor and nine tele-
phone calls, one per month).
Intervention
The intervention protocol is described in full by Caswell
and colleagues [23], but in brief targeted a 7 % reduction
in body weight through diet, activity and behaviour
change, including a personalised energy prescription
(600kcals below that required for weight maintenance).
Motivational interviewing techniques explored self-
assessed confidence, ambivalence and personal values
concerning weight. To assist change in both diet and
physical activity, participants were encouraged to focus
on one topic (diet or physical activity) during visit one,
and the remaining topic on visit two, and were generally
advised to begin with the topic where they had the
strongest likelihood of success. Behaviour change tech-
niques were employed including goal setting, identifying
implementation intentions, self-monitoring of body
weight (scales were provided) and counsellor feedback
about reported diet, physical activity and weight change.
The intervention was delivered in four NHS areas with
one lifestyle counsellor in each area, and all counsellors
received the same training to ensure consistency in de-
livery. The primary outcome was change in body weight
at 12 months. Secondary outcomes included percentage
weight loss, change in BMI and waist circumference,
health behaviours (dietary and alcohol habits and phys-
ical activity) and self-reported psycho-social variables
(self-efficacy and self-assessed health and quality of life).
Stead et al. International Journal of Behavioral Nutrition and Physical Activity (2015) 12:87 Page 3 of 12
Sub-group analysis of quantitative data
A sub-group analysis was undertaken of the intervention
participants who completed the study to compare partic-
ipants according to their percentage weight loss. Partici-
pants were divided into ‘super-achievers’ (≥7 % weight
loss), ‘moderate-achievers’ (2–< 7 % weight loss) or ‘low-
achievers’ (<2 % loss, or weight gain). Weight loss across
the sample was normally distributed. Descriptive statistics
were used to quantify socio-demographic and body weight
characteristics, health perceptions, quality of life, self-
efficacy and perceptions of lifestyle at baseline, and changes
in anthropometry and health behaviours (dietary and alco-
hol habits and physical activity) at 12 months. Chi-squared
tests were used to identify differences in proportions, and
analysis of variance with post-hoc Bonferroni tests (to min-
imise the likelihood of type 1 errors) to detect differences
in continuous variables. Between group differences are
expressed as Odds Ratios (OR) or means with 95 % Confi-
dence Intervals (CI) and p-values (p < 0.05 signifies statis-
tical significance).
Statistical analyses were carried out using SPSS
(Version 21.0, IBM, Armonk, NY, USA).
Qualitative interviews and analysis
Qualitative in-depth individual interviews were con-
ducted with a sample of 24 intervention group partici-
pants on study completion, between July 2012 and
January 2013. Purposeful sampling was employed, strati-
fied by gender, socioeconomic status, and research site
and weight loss achieved, with the aim of interviewing
participants at all points on the weight loss spectrum.
The achieved sample comprised almost equal propor-
tions of males and females (13 and 12 respectively), and
included participants across all five Scottish Index of
Multiple Deprivation (SIMD) [24] quintiles. Baseline
age, weight, BMI and waist circumference were repre-
sentative of the whole cohort, although a higher propor-
tion of the interviewees were classified as obese.
Interviews were conducted in participants’ own homes
and lasted an average of 60 min. Written informed con-
sent was provided for participation in the interview and
its audio-recording and transcription verbatim. An inter-
view topic guide was developed which investigated the
acceptability of the BeWEL programme, the participants’
initial expectations and motivations and the extent to
which these were met by their subsequent experiences, and
how well participants engaged with the programme. Fac-
tors influencing patients’ willingness and ability to comply
with programme advice were explored including lifestyle,
attitudinal and other differences which might explain vari-
able response to and engagement with the programme.
All transcripts were imported into NVivo (Version 10,
QSR International, Melbourne, Australia) to facilitate
coding and analysis. The transcripts underwent several
stages of analysis. Each transcript was read and coded by
one of two researchers (JM and MS), with four transcripts
read and coded by both researchers. Emerging themes
were identified through a process of thorough familiarisa-
tion with the texts and discussion between the researchers.
Drawing on the framework approach (eg. [25]), an initial
framework was developed organised around the different
aspects of engagement in the programme: the decision to
participate and the factors associated with that decision,
experiences of initial engagement in the programme, expe-
riences of making changes, facilitators and barriers to
change, and intentions and hopes for future maintenance.
This framework was then expanded to incorporate more
detailed examination of the motivators, facilitators and
barriers to initiating and sustaining change. A series of
matrices were generated which illustrated the pattern of
factors for each participant. Using weight loss outcome
data, the 24 participants were then grouped into ‘super-’,
‘moderate-’ and ‘low-achievers’ using the same percentage
weight loss cut-offs as in the quantitative analyses. This re-
sulted in 10 super-achievers, six moderate-achievers and
eight low-achievers within the qualitative sample. The
matrices of motivators, facilitators and barriers were then
re-examined for any patterns relating to the three categor-
ies of weight loss. Pseudonyms are used throughout the
paper to preserve participants’ anonymity.
Results
Quantitative study findings
Of the 148 (91 %) participants who were randomised to
receive the BeWEL intervention and completed 12 month
assessments, 33 (22 %) were ‘super-achievers’, 58 (39 %)
‘moderate-achievers’ and 57 (39 %) ‘low-achievers’.
Participants ranged in age from 50 to 75 years (reflect-
ing the colorectal cancer screening age in Scotland).
Overall, 74 % of the participants were male, and 35 %
lived in the two most deprived SIMD quintiles of socio-
economic deprivation. Almost half (n = 72, 49 %) were in
the obese category (BMI >30 kg/m2) and 60 % (52 %
males and 84 % females) reported having previously tried
(80 % successfully) to lose weight (Table 1).
When the three achievement groups were compared,
no significant differences were found in their socio-
demographic or body weight characteristics at baseline,
nor their previous history of weight loss attempts
(Table 1). In addition, no significant differences were
found between NHS sites in baseline characteristics or
weight loss outcomes, suggesting that ‘super-achieve-
ment’ was not explained by differences in implementa-
tion between the lifestyle counsellors allocated to each
NHS site.
Following the 12 month intervention, ‘super-achievers’
had lost an average of 10.2 kg (11.5 %) body weight, 3.5
BMI units, and 11.7 cm from their waist circumference.
Stead et al. International Journal of Behavioral Nutrition and Physical Activity (2015) 12:87 Page 4 of 12
In contrast, ‘moderate-achievers’ had lost 3.8 kg (4.2 %),
1.3 BMI units and 4.4 cm, and ‘low-achievers’ had
gained 0.7 kg (0.8 %), 0.3 BMI units and lost 1.6 cm
(Table 2).
Lifestyle behaviours assessed at the end of the
12 month intervention period indicated that super-
achievers had increased their daily step count by 1878 ±
3556 steps per day, whereas moderate and low-achievers
had reduced theirs (−109 ± 3335 and−372 ± 2118 steps
per day, respectively, p < 0.01). A higher proportion of
super-achievers also increased the number of portions of
fruit and vegetables they reported consuming per day,
but no other differences in fat or fibre scores, or in the
proportions reducing their consumption of sugary drinks
or alcohol between the groups, were identified.
The majority (79 %) of participants had rated their
current health as ‘good’ or better at baseline. However,
while there were no significant differences in perceptions
of current health, super-achievers were significantly less
likely than the rest to report that their activities (e.g.
stair climbing, moderate activity and general accom-
plishments) and work were affected by physical and
emotional health (Table 3).
Super-achievers were no different in how they had
rated their self-efficacy, beliefs about their lifestyle risk
and perceptions of their own lifestyle and bodyweight at
baseline, with one exception: they were significantly
more likely to believe their diet was harmful to their
health (Table 4).
Qualitative study findings
Analysis across the sample, comparing super, moderate
and low-achievers, found no clear patterns in relation to
some key factors which previous studies have suggested
may contribute to differences in success, such as family
and social support, quality of relationship with counsellor
and access to healthy food and opportunities for physical
activity. Although having an involved and supportive
spouse was important to some super-achievers, others,
particularly female super-achievers, did well with either no
partner to support them, or in the context of family indif-
ference to their efforts. Similarly, although participants
generally spoke positively about the counsellors, the depth
and nature of the relationship varied, and there appeared
not to be a consistent link between degree of weight loss
achievement and relationship with the counsellor: for ex-
ample, one super-achiever had requested extra contact
with the counsellor during the 9-month telephone support
period because he felt he needed this external prompting
and validation to keep on track, while another super-
achiever could not even remember the counsellor’s name,
and was satisfied with a much more arm’s length relation-
ship. What seemed more important was that the individ-
ual was sufficiently driven to make changes for themselves
Table 1 Baseline socio-demographic and body weight characteristics of intervention participants who completed, by subsequent
achievement category
Super-achievers Moderate-achievers Low-achievers
Between group differences p-value
Mean or
Odds Ratio (95%CI)
n = 33 n = 58 n = 57 Super vs. moderate Super vs. low
Male gender: n (%) 22 (66.7) 44 (75.9) 44 (77.2) 0.6 (0.2, 1.6) 0.6 (0.2, 1.5) 0.51
Age (years): Mean (SD) 65.2 (SD 6.7) 63.7 (SD 6.5) 62.3 (SD 7.2) 1.5 (−1.4, 4.3) 2.9 (−0.2, 5.9) 0.15
SIMD quintiles: n (%)
1 (most deprived) 4 (12.1) 11 (19.0) 6 (10.5) — — 0.29
2 6 (18.2) 12 (20.7) 12 (21.1)
3 3 (9.1) 13 (22.4) 10 (17.5)
4 12 (36.4) 7 (12.1) 14 (24.6)
5 (least deprived) 8 (24.2) 15 (25.9) 15 (26.3)
In least deprived 5 SIMD deciles 21 (63.6) 29 (50.0) 37 (64.9) 1.8 (0.7, 4.2) 0.9 (0.4, 2.3) 0.22
Married/Cohabiting: n (%) 29 (87.9) 47 (81.0) 43 (75.4) 1.7 (0.5, 5.8) 2.4 (0.7, 7.9) 0.35
Retired: (%) 20 (60.6) 35 (60.3) 32 (56.1) 1.0 (0.4, 2.4) 1.2 (0.5, 2.9) 0.88
Baseline weight (kg): Mean (SD) 89.2 (12.1) 89.7 (16.1) 92.6 (15.5) −0.4 (−6.8, 6.0) −3.3 (−9.2, 2.5) 0.48
Baseline BMI (kg/m2): Mean (SD) 31.1 (3.4) 30.8 (4.9) 31.4 (4.9) 0.3 (−1.6, 2.2) −0.3 (−2.0, 1.4) 0.78
Obesea at baseline: n (%) 19 (57.6) 26 (44.8) 27 (47.4) 1.7 (0.7, 4.0) 1.5 (0.6, 3.6) 0.49
Baseline waist circumference (cm): Mean (SD) 105.5 (9.2) 103.5 (11.2) 106.4 (11.8) 2.0 (−2.5, 6.6) −0.8 (−5.3, 3.6) 0.37
Made previous attempt at weight loss: n (%) 24 (72.7) 31 (53.4) 34 (59.6) 2.3 (0.9, 5.8) 1.8 (0.7, 4.6) 0.20
Successful at previous weight loss attempts: n (%) 21 (87.5) 25 (80.6) 30 (88.2) 1.7 (0.4, 7.5) 0.9 (0.2, 4.6) 0.65
aBMI > 30 kg/m2
Stead et al. International Journal of Behavioral Nutrition and Physical Activity (2015) 12:87 Page 5 of 12
Table 2 Behaviour changes associated with ‘super-achievement’ at 12 months
Mean (Standard Deviation) Between group differences P-value
Mean or Odds Ratio (95%CI)
Super-achievers Moderate-achiever Low-achiever Super Vs Moderate Super Vs Low
(n = 33) (n = 58) (n = 57)
Anthropometry
• Weight loss (kg) −10.2 (4.3) −3.8 (1.5) 0.7 (2.4) −6.4 (−7.8,−5.0) −11.0 (−12.4,−9.6) <0.01*
• % body weight change −11.5 (4.3) −4.2 (1.4) 0.8 (2.6) −7.2 (−8.7,−5.8) −12.2 (−13.7,−10.8) <0.01*
• BMI change (kg/m2) −3.5 (1.5) −1.3 (0.5) 0.3 (0.9) −2.2 (−2.7,−1.7) −3.8 (−4.3, 3.3) <0.01*
• Change in waist circumference (cm) −11.7 (5.1) −4.4 (2.6) −1.6 (3.9) −7.3 (−9.3,−5.2) −10.1 (−12.1,−8.1) <0.01*
Physical activity
• Change in daily average time spent active (mins) 25.2 (63.0) −0.30 (68.9) 2.1 (43.9) 25.5 (−6.7, 57.6) 23.1 (−10.0, 56.2) 0.14
• Change in daily average time spent in:
○ Sedentary activity (mins) −29.8 (100.0) −8.3 (187.0) −23.6 (143.0) −21.5 (−108.1, 65.2) −6.2 (−94.6, 82.3) 0.80
○ Moderate activity (mins) 27.3 (61.8) −1.0 (57.9) 1.9 (42.8) 28.3 (−1.6, 58.2) 25.4 (−5.2, 55.9) 0.06
○ Vigorous activity (mins) 0.9 (4.6) −2.1 (18.5) −0.7 (2.8) 3.0 (−3.8, 9.8) 1.6 (−5.4, 8.5) 0.56
• Change in daily average step count 1878 (3556) −109 (3335) −372 (2118) 1987 (363, 3611) 2250 (581, 3918) <0.01*
Dietary intake
• Change in fat consumption score −8.6 (11.3) −7.4 (8.2) −6.6 (11.3) −1.3 (−6.7, 4.2) −2.0 (−7.5, 3.4) 0.66
• Change in unsaturated fat score 0.5 (1.7) 0.6 (1.8) 0.3 (1.5) −0.1 (−1.0, 0.8) 0.2 (−0.7, 1.1) 0.59
• Change in fibre food consumption score 0.5 (9.0) 0.6 (10.6) −1.6 (11.1) −0.8 (−5.6, 5.4) 2.1 (−3.4, 7.7) 0.47
• Increased fruit and vegetable portions (%) 25 (75.8 %) 32 (55.2 %) 20 (35.1 %) 2.54 (0.98, 6.56) 5.78 (2.20, 15.16) <0.01*
• Lowered sugary drink consumption [drinkers only] (%) 5 (71.4 %) 10 (90.9 %) 3 (60 %) 0.25 (0.02, 3.47) 1.67 (0.15, 18.9) 0.33
Lowered alcohol consumption [drinkers only] (%):
• Frequency 5 (19.2 %) 19 (37.3 %) 14 (27.5 %) 0.40 (0.13, 1.24) 0.63 (0.20, 1.99) 0.24
• Amount on weekdays 9 (34.6 %) 15 (29.4 %) 14 (27.5 %) 1.27 (0.46, 3.48) 1.40 (0.51, 3.86) 0.54
• Amount at the weekend 4 (15.4 %) 10 (19.6 %) 13 (25.5 %) 0.75 (0.21, 2.65) 0.53 (0.15, 1.83) 0.43
Chi-squared test used for differences in proportions, Independent samples t-test used for differences in continuous variables
*p < 0.05, significant
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and did not feel the need for external approbation from
those around them:
“Once you are into it it’s your own discipline, it
doesn’t matter what they say to you because in the
end it’s up to you, they can encourage you and
everything else but they can’t make you do anything
… it’s up to yourself, totally up to yourself. They are
only there for suggestions and encouragement, that’s
all” (‘Joe’, aged 70, super-achiever).
In terms of access to healthy food and opportunities for
physical activity, participants generally felt that they had
been able to afford any changes to their shopping patterns,
albeit that prices had risen generally over the study period
because of the economic recession. Some low-achievers
offered reasons for their lack of physical activity based on
unsuitable facilities—for example, that a local swimming
pool was not set up for lane swimming—but these ap-
peared to mask underlying reasons such as a dislike of ex-
ercise. Many observed that walking, the main physical
activity change made in most cases, did not cost anything.
Whilst the themes of support and access did not ap-
pear to help explain differences in achievement, several
patterns did emerge in relation to other themes both
across the sample and from looking in-depth at the
super-achiever sample. These were health, lifestyle adap-
tation, flexibility, drawing on previous success, coping
with set-backs, motivation, determination/commitment,
and the use of prompts, aids and information.
Health
Several participants experienced health problems which
made it difficult for them to undertake exercise. One
low-achiever, ‘Len’, aged 64, described how a stroke, back
problems and a history of work-related injuries had left
him tremendously frustrated at his inability to be as ac-
tive as he once was; he felt that these physical problems
had been an important barrier to success. The pattern
across the sample was not clear-cut, with not all
low-achievers having health problems and some super-
achievers facing substantial health challenges—‘Bill’, aged
62, for example, managed to lose 9.7 kg despite sciatica,
thyroid problems, incontinence, pain in his legs and
spine which made walking difficult, and mental health
problems. However, there was a tendency for more im-
portance to be attached to physical and mental health
problems by low-achievers than by super-achievers in
their accounts of how and why they had progressed on
the programme.
Lifestyle adaptation
Super-achievers tended to describe having made specific
and extensive changes, both to diet and to physical activ-
ity, and to have incorporated these changes quickly into
their daily routines. For example, several adopted daily
walking, even in bad weather, or other forms of exercise.
Many also reported concerted efforts to reduce their in-
take of high fat foods and processed meats; to increase
their intake of fruit and vegetables, low fat variants and
fibre; and to control their portion sizes and frequency of
Table 3 Baseline health perceptions and quality of life of intervention participants who completed, by subsequent
achievement category
Between group differences p-value
Odds Ratio (95%CI)
Super-achievers Moderate-achievers Low-achievers Super vs. moderate Super vs. low
n = 33 n = 58 n = 57
Health poor/fair: n (%) 2 (6.1) 12 (20.7) 20 (35.1) 0.2 (0.1, 1.2) 0.2 (0.0, 0.6) 0.06
Health limits moderate activities: n (%) 3 (9.1) 11 (19.0) 19 (33.3) 0.4 (0.1, 1.7) 0.2 (0.1, 0.7) 0.02*
Health limits ability to climb stairs: n (%) 6 (18.2) 13 (22.4) 28 (49.1) 0.8 (0.3, 2.3) 0.2 (0.1, 0.6)* <0.01*
Accomplishes less due to physical health: n (%) 4 (12.1) 14 (24.1) 22 (38.6) 0.4 (0.1, 1.4) 0.2 (0.1, 0.7)* 0.02*
Limited due to physical health most/all of
the time: n (%)
1 (3.0) 3 (5.2) 8 (14.0) 0.6 (0.1, 5.7) 0.2 (0.0, 1.6) 0.11
Accomplishes less due to emotional health: n (%) 5 (15.2) 18 (31.0) 18 (31.6) 0.4 (0.1, 1.2) 0.4 (0.1, 1.2) 0.19
Work less carefully due to emotional health: n (%) 0 (0) 11 (19.0) 11 (19.3) — — 0.03*
Pain interferes with normal work; n (%) 11 (33.3) 24 (41.4) 30 (52.6) 0.7 (0.3, 1.7) 0.5 (0.2, 1.1) 0.18
Feel calm/peaceful most/all of the time: n (%) 23 (69.7) 33 (56.9) 40 (70.2) 1.7 (0.7, 4.3) 1.0 (0.4, 2.5) 0.27
Feel full of energy most/all of the time: n (%) 19 (57.6) 27 (46.6) 23 (40.4) 1.6 (0.7, 3.7) 2.0 (0.8, 4.8) 0.29
Feel depressed most/all of the time: n (%) 0 (0) 5 (8.6) 4 (7.0) — — 0.24
Problems interfered with social activities
most/all of the time: n (%)
3 (9.1) 4 (6.9) 4 (7.0) 1.4 (0.3, 6.4) 1.3 (0.3, 6.3) 0.92
*P < 0.05, significant
Stead et al. International Journal of Behavioral Nutrition and Physical Activity (2015) 12:87 Page 7 of 12
eating throughout the day. Low-achievers, in contrast,
tended to talk more vaguely about the changes they had
attempted, with references to “being more aware of”
what they should be doing, “trying to” change and “mak-
ing little tweaks”, but fewer specific examples. Some felt
they were already doing the right things or doing as
much as they could, while others admitted that they
struggled against the temptation to “overload your plate”
(‘Duncan’, aged 65, low-achiever) or to snack: “It’s the
portions. I have to try and regulate portions. Also I have
to stop mooching in the fridge at night—boredom”
(‘Hetty’, aged 72, low-achiever).
Flexibility
Although super-achievers made these extensive changes
to diet and physical activity, they permitted themselves
some flexibility within this wider framework of change.
One strategy was not to waste energy on attempting
changes to which they knew they were not committed:
as ‘Joe’, aged 70, put it, “Brown rice, I’d rather jump out
Table 4 Baseline self-efficacy and perceptions of lifestyle in intervention participants who completed, by subsequent
achievement category
Mean (Standard Deviation) rating:
(range 1 = lowest, 7 = highest)
Between group differences p-value
Mean (95%CI)
Super-achievers Moderate-achiever Low-achiever Super vs. Moderate Super vs. Low
(n = 33) (n = 58) (n = 57)
Self-efficacy a
• How sure are you that you will
control your weight?
5.0 (1.3) 5.0 (1.8) 5.1 (1.7) 0.00 (−0.88, 0.88) −0.14 (−1.0, 0.74) 0.88
• How sure are you that you will
exercise regularly?
5.6 (1.5) 5.7 (1.5) 5.4 (1.8) −0.16 (−1.01, 0.69) 0.20 (−0.66, 1.04) 0.49
• How sure are you that you will
control your diet?
5.2 (1.1) 5.4 (1.4) 5.3 (1.5) −0.15 (−0.88, 0.58) −0.08 (−0.83, 0.66) 0.88
• How sure are you that you will
control alcohol intake?
6.0 (1.3) 6.0 (1.5) 5.8 (1.5) 0.03 (−0.74, 0.80) 0.22 (−0.56, 0.99) 0.73
Perceptions of riskb
• Do you believe being overweight
is harmful?
6.7 (0.6) 6.4 (1.0) 6.5 (0.7) 0.27 (−0.16, 0.70) 0.12 (−0.31, 0.56) 0.30
• Do you believe not exercising
regularly is harmful?
6.3 (1.0) 6.0 (1.5) 6.4 (0.8) 0.27 (−0.34, 0.88) −0.15 (−0.76, 0.46) 0.15
• Do you believe your current diet
is harmful?
4.0 (1.7) 3.0 (1.7) 3.8 (1.7) 1.03 (0.13, 1.93)* 0.27 (−0.64, 1.18) 0.01*
• Do you believe that excessive
alcohol intake is harmful?
6.8 (0.5) 6.8 (0.7) 6.6 (1.3) −0.04 (−0.53, 0.46) 0.19 (−0.31, 0.69) 0.39
Perceptions of own lifestyle and body weight
• How would you describe your
present bodyweight?c
5.7 (1.0) 5.3 (1.1) 5.3 (1.2) 0.46 (−0.14, 1.07) 0.47 (−0.14, 1.08) 0.12
• How would you describe your
typical alcohol intake?d
3.0 (1.7) 3.3 (1.7) 3.3 (1.7) −0.28 (−1.17, 0.62) −0.31 (−1.21, 0.60) 0.68
• How do you rate your weekly
physical activity levels?e
3.7 (1.3) 4.0 (1.4) 3.7 (1.6) −0.31 (−1.08, 0.47) 0.02 (−0.76, 0.80) 0.43
• How would you describe your
red meat intake?f
3.6 (1.4) 3.4 (1.2) 3.8 (1.4) 0.14 (−0.57, 0.84) −0.24 (−0.95, 0.47) 0.32
• How would you describe your
soft drink intake?f
2.5 (1.7) 2.3 (1.5) 2.0 (1.1) 0.22 (−0.54, 0.98) 0.50 (−0.27, 1.27) 0.27
• How would you describe your
water intake?f
3.4 (1.5) 3.7 (1.6) 3.6 (1.7) −0.30 (−1.16, 0.55) −0.23 (−1.10, 0.64) 0.69
*p < 0.05, significant a1 = Not at all sure, 7 = Very sure b1 = Not at all harmful, 7 = Very harmful c1 = I am very underweight, 7 = I am very overweight d1 = I don’t drink alcohol, 7 = I drink far too much alcohol e1 = I do no activity, 7 = I am far too active f1 = I do not eat/drink, 7 = I eat/drink far too much
Stead et al. International Journal of Behavioral Nutrition and Physical Activity (2015) 12:87 Page 8 of 12
the window than eat brown rice”. Another strategy was
to permit occasional lapses and treats, not regarding
them as taboo or as signs of failure, but as permissible
so long as the overall direction of change remained
positive. Indeed, several super-achievers felt they could
not have been successful if they had adhered to a joy-
less regime in which these ‘treats in moderation’ were
not permitted.
Drawing on previous success
For super-achievers (and to a lesser extent some of the
moderate-achievers), early experience of weight loss
within BeWEL drove them on—“I couldn’t believe how
it was coming off, just going out [for] walks” (‘Sandra’,
aged 65, super-achiever); “I liked the fact that when I
would go on the scales on a weekly basis and I had
maybe just lost that wee bit, the thrill it gave me. Oh
you dancer! [expression of pleasure]” (‘Ronnie’, aged 69,
moderate-achiever). Super-achievers could also draw on
successful change which they had achieved prior to
BeWEL, such as having quit smoking, to bolster their
determination and confidence: “I was really being very
strong willed at that point in time. I’d mastered the
smoking which had really—I thought if I can do the
smoking, I can definitely get rid of the weight” (‘Aggie’,
aged 67, super-achiever).
Coping with set-backs
Setbacks, such as a plateauing of weight or weight gain,
were experienced by many participants. Here, a key dif-
ference between super-achievers and low and moderate-
achievers was in how these were dealt with. Low-
achievers in particular tended to become demoralised by
poor progress or by relapses, leading to a weakening of
subsequent effort: ‘Eileen’, aged 63, described it as “a wee
bit soul destroying after about 3 weeks and you’ve only
lost a pound or something”, while ‘Len’, aged 64,
reflected that his impatient nature had led to feelings of
frustration when progress seemed slow or non-existent:
“If things don’t happen quickly enough for me—that is
just cos of the way I’ve been all my life—I like to get on
and get things done. And I just wonder if that [was what
made] a difference”. Super-achievers were similarly “dis-
appointed” or “annoyed” when their weight loss progress
appeared to stall or reverse, but, importantly, were
spurred on by these feelings, and by the memory of earl-
ier success, to renew their efforts.
Motivation, determination and commitment
These were key themes in the interviews. Super-
achievers made frequent reference to their own “deter-
mination” and “discipline” and identified these as key
factors in their persistence and ultimate success. Several
invoked notions of ‘doing themselves justice’ by commit-
ting wholeheartedly to the study and seeing it through:
“Just willpower and thinking I’m not letting [the
counsellor] down and the nurse. …
It’s not that, if I let Karen and the nurse down I was
letting myself down as well and I didn’t want to do
that either” (‘Bill’, aged 62, super-achiever).
“There was a sense that you had a responsibility to do
it honestly.” (‘Joe’, aged 70, super-achiever).
Similarly, some low-achievers identified that, while their
initial expectations and motivation had been high, their
willpower had been lacking and had let them down:
“At the end of the day, it was me who didn’t stop
eating the ice cream and it was me who didn’t do the
exercise, so I can only blame myself” (‘George’, aged
72, low-achiever).
Prompts, aids and information
Finally, for some super-achievers, simple prompts, aids
and information proved helpful in motivating and sus-
taining change. For example, ‘Aggie’ responded well to
the simple provision of scales (she had not weighed her-
self in years) and a pedometer, which gave her a daily
target. ‘Joe’ in contrast felt no further need of the ped-
ometer after using it for a few days and did not want
any of the exercise aids offered, but became fascinated
by information about the calorie content of foods, a sub-
ject he had never previously considered, and drew on
this new knowledge to reinforce his dietary changes. For
‘Ken’, completing the sheets and forms offered by the
counsellor for recording daily time spent in physical ac-
tivity became a project he completed “religiously” and
with great enjoyment. It is likely that these prompts, aids
and pieces of information would not have been sufficient
in themselves to motivate and sustain changes without
the other factors discussed above, but in conjunction
with them, for some super-achievers they were helpful.
Discussion
During a 12 month weight loss programme, one group
of participants (‘super-achievers) attained significantly
greater reductions in body weight, BMI and waist cir-
cumference compared to other achievement groups.
These changes were accompanied by some improve-
ments in both diet and physical activity. Whilst the data
did not indicate any differences in demographic charac-
teristics between achievement groups, significantly fewer
super-achievers reported that their activities were limited
by their physical (and emotional) health compared to
Stead et al. International Journal of Behavioral Nutrition and Physical Activity (2015) 12:87 Page 9 of 12
those who lost less weight, and super-achievers were more
likely to think that their current diet was harmful. Differ-
ences in achievement were not explained by differences in
intervention delivery: no significant differences were found
between participants in different areas in baseline charac-
teristics or weight loss outcomes, suggesting that greater
achievement by some participants was not related to dif-
ferences in the type of support they received. Qualitative
analysis showed that super-achievers shared several char-
acteristics such as determination and consistency in their
engagement with the intervention, receptivity to new in-
formation and prompts, previous positive experience of
changing health behaviours, being motivated by early suc-
cess, making changes routine, and an ability to devise and
apply strategies for dealing with setback and ‘relapse’ trig-
gers. Both the quantitative and the qualitative analysis sug-
gested that physical and mental health problems were a
possible contributory factor to the lower levels of engage-
ment and success among moderate and low-achievers.
These finding serve as a reminder of the challenge of
addressing low levels of physical activity amongst multi-
morbid populations in Scotland where it has been esti-
mated that in areas of deprivation, by age 50, half of all
Scots have at least one morbidity and by age 65 most are
multi-morbid [26].
One limitation of this study is that the participants are
likely to represent a somewhat motivated group, having
voluntarily taken part in both the screening process and
the subsequent weight loss trial. Uptake of bowel screening
is also known to be poorer in more socio-economically de-
prived groups [27], and this is to some extent reflected in
the distribution of participants in the quantitative analysis.
However, deprivation had no influence on weight loss
achievement, and the relatively even distribution of partici-
pants throughout qualitative analysis ensured the views of
those at all levels of deprivation were represented. Consid-
eration should also be given to the fact that this analysis
purposefully considered only those in the intervention arm
in an effort to pinpoint aspects of the intervention that
were most or least effective. While this could have
limited our understanding of the impact of any non-
interventional factors on weight loss, considerable
opportunity was given in the interview topic guide for
participants to discuss these. It should also be noted
that the BeWEL trial sample size was based on provid-
ing sufficient power (80 %) to detect a 7 % weight loss,
and not on the ability to detect the differences in the
sub-group comparisons reported here. Therefore, the
quantitative results should be interpreted on their basis
of being able to provide indicative findings that may
warrant further testing in a larger fully powered trial.
A particular strength of this study was the combination
of data collection methods, which combined both quanti-
tative and qualitative analyses. While the quantitative
analysis established the relative importance (or not) of
various demographic, health status and attitudinal mea-
sures, the qualitative analysis was able to explore in more
depth the differences in mindset and approach which
appeared to characterise the super-achievers. This ana-
lysis suggested that success appeared to be associated
with engaging in the study wholeheartedly (in particular,
making changes routine and adhering to them) and
taking personal responsibility for change rather than
blaming external factors for any lapses in willpower.
Successful participants also drew on new information,
such as information on calorie content or number of
steps walked per day, to motivate and reinforce deter-
mination. These findings are consistent with Rise and
colleagues’ [28] qualitative analysis of factors associated
with successful lifestyle change in a type 2 diabetes
programme, which identified ‘new knowledge’, ‘taking
responsibility’ and ‘formation of new habits’ as some of
the important factors. It was also notable that, in the
quantitative analysis, super-achievers were more likely
at baseline to perceive their current diet to be ‘harmful’.
Being willing to acknowledge personal inadequacies in
their diet may have motivated them to identify specific
areas for improvement.
The findings in the current study also echo some of
the themes described in a qualitative study [29] with
Scottish adults, where weight maintenance was associ-
ated with a range of behavioural strategies and making
several (typically small) adjustments to diet and physical
activity. The same study also found that those who suc-
cessfully maintained their weight used more cognitive
strategies for coping with setbacks and tended not to
worry about minor fluctuations in weight or lapses in
lifestyle habits, while in contrast, those who gained
weight tended to give up at signs of difficulty or per-
ceived failure. Similar themes emerged in the BeWEL
study, with super-achievers tending to be committed to
weight loss but also being flexible rather than fanatical
in their adherence to the new regime, such that they
could incorporate occasional treats and setbacks without
losing focus or motivation and thus avoiding an ‘all or
nothing’ approach which may lead people to attempt un-
realistic goals [30, 31]. Another factor which did help
super-achievers was being able to draw on previous ex-
perience of success, such as having given up smoking
before entering the BeWEL study, or experiencing early
weight loss in the first few weeks of the study. These ex-
periences gave participants the knowledge and confi-
dence that they could meet their weight goals and
reinforced their motivation.
Interestingly, the qualitative analysis did not suggest
that partner/family and social support helped to explain
the differences in weight loss between super-achievers
and others. This is a departure from the findings of
Stead et al. International Journal of Behavioral Nutrition and Physical Activity (2015) 12:87 Page 10 of 12
several other studies [13, 14, 28, 32], which posit social
support as an important factor in successful behaviour
change. In the current study, super-achievers—several of
whom lived on their own or engaged in the programme
against a backdrop of family indifference—appeared to
draw as much on their own reserves and motivation as
on the support of those around them. While this is not
to deny the importance of social support in lifestyle
change programmes, it does suggest that it is not a pre-
requisite for success. This is an encouraging finding in
relation to people who engage in lifestyle change pro-
grammes with limited social support.
It has become an established approach to seek to iden-
tify the intervention factors associated with effectiveness
[33, 34]. The rationale is that, if effective intervention in-
gredients can be identified and implemented, impact is
likely to be greater. BeWEL used intervention techniques
which are associated with greater effectiveness, such as
goal-setting, self-monitoring, and providing feedback
[35]. However, interventions are not one-way channels,
through which effective ingredients are poured on to re-
cipients; interventions only ‘work’ when people engage
with and act on them. What was clear from the BeWEL
study was that even where lifestyle counsellors used the
same set of methods and techniques with each individ-
ual, some responded more successfully than others, for
reasons to do with motivation, previous experience, will-
power, ways of thinking about the challenge and other
issues. The BeWEL findings highlight the need not to
lose sight of the person at the centre of the intervention.
Greaves and colleagues [35] underline this point in their
review of facilitating factors for obesity-reducing lifestyle
change, noting that people have different needs both
from each other and at different moments in time. This
highlights the importance of offering opportunities and
support for lifestyle change not just on a one-off basis in
a single intervention, but at multiple points over the life
course and at all key encounters with health services, so
that people can engage with them opportunely when
motivation and circumstances coincide.
Conclusions
The findings point to several implications for future
weight loss interventions. Support and interventions for
weight loss are likely to be more effective where they are
able to adapt flexibly to participants’ differing character-
istics and needs, while at the same time providing core
elements likely to build success. These core elements in-
clude: providing early experience of success (to encour-
age continued effort and commitment); understanding
what prompts might be motivating to particular individ-
uals at different points in the process; helping partici-
pants to identify and make changes which are quickly
incorporated into daily routines, whilst at the same time
encouraging them to adopt flexible thinking which can
cope with setbacks and lapses; and helping participants
to identify previous experience of success which they
can draw on to motivate and sustain them.
Competing interests
All authors declare no competing interests with the exception of Prof
Robert J.C. Steele who declares his work as Director of the Scottish Bowel
Screening Programme.
Authors’ contribution
ASA (guarantor) had the original idea for the main study. AA, AMC, SC, MS,
RJCS were part of the investigator group which obtained the funding for the
main study. ASA, AMC, RJCS and SC were responsible for overseeing study
implementation and data collection. MS and JM conducted the qualitative
data collection. MS, MM, JM and AMC carried out the analyses reported in
this paper. MS, AMC, MM and ASA drafted the manuscript which was revised
by all authors. All researchers were independent from funders. The study
sponsor and funder played no role in study design; in the collection, analysis,
and interpretation of data; in the writing of the report; and in the decision to
submit the article for publication. All authors, external and internal, had full
access to all of the data (including statistical reports and tables) in the study
and can take responsibility for the integrity of the data and the accuracy of
the data analysis. All authors read and approved the final manuscript.
Acknowledgements
We would like to thank the participants of this trial, the trial manager, trial
administrator, research nurses and lifestyle counsellors whose enthusiastic
support made the trial possible. We would also like to thank members of the
wider BeWEL study team for their advice on the study and for their comments
on this manuscript: Shaun Treweek, Jane Wardle, Jill Belch, Joyce Thompson,
Alison Kirk and Douglas Eadie.
Funding
Financial support was provided by the National Prevention Research Initiative
(http://www.npri.org.uk), grant award number G0802030. National Prevention
Research Initiative is a national research initiative administered by the Medical
Research Council made up of the following funding partners: Alzheimer’s
Research Trust; Alzheimer’s Society; Biotechnology and Biological Sciences
Research Council; Cancer Research UK; Chief Scientist Office, Scottish
Government Health Directorate; Department of Health; Diabetes UK; Economic
and Social Research Council; Engineering and Physical Sciences Research
Council; Health & Social Care Research & Development Office for Northern
Ireland; Medical Research Council; Welsh Assembly Government and WCRF.
Further financial support was provided by NHS Research Scotland to carry
out this work.
Transparency statement
The lead author (the manuscript’s guarantor) affirms that the manuscript is
an honest, accurate, and transparent account of the study being reported;
that no important aspects of the study have been omitted; and that any
discrepancies from the study as planned (and, if relevant, registered) have
been explained.
Ethical approval
Ethics committee approval was granted by Tayside Committee on Medical
Research Ethics B on 16 July 2010 (REC ref no 10/S1402/34).
Author details
1Institute for Social Marketing, University of Stirling, Stirling FK9 4LA, Scotland, UK.
2Centre for Research into Cancer Prevention and Screening, Cancer Division,
Medical Research Institute, Level 7, Ninewells Hospital and Medical School,
Dundee DD1 9SY, UK.
Received: 2 December 2014 Accepted: 12 June 2015
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Stead et al. International Journal of Behavioral Nutrition and Physical Activity (2015) 12:87 Page 12 of 12
http://dx.doi.org/10.1017/S1368980011003090
http://dx.doi.org/10.1186/1479-5868-9-79
http://dx.doi.org/10.1186/1471-2261-12-120
http://dx.doi.org/10.1186/1471-2261-13-48
http://www.nhs.uk/Livewell/5ADAY/Pages/Portionsizes.aspx
http://www.nhs.uk/Livewell/5ADAY/Pages/Portionsizes.aspx
http://whqlibdoc.who.int/hq/1992/WHO_PSA_92.4
http://whqlibdoc.who.int/hq/1992/WHO_PSA_92.4
http://dx.doi.org/10.1136/bmjopen-2012-001276
http://www.scotland.gov.uk/Topics/Statistics/SIMD/
http://www.isdscotland.org/Health-Topics/Cancer/Bowel-Screening/
http://www.isdscotland.org/Health-Topics/Cancer/Bowel-Screening/
http://dx.doi.org/10.1371/journal.pone.0064009
http://dx.doi.org/10.1111/j.2044-8287.2011.02030
http://dx.doi.org/10.1111/j.1745-7599.2011.00647.x
http://dx.doi.org/10.1186/1471-2458-11-119
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| American Indian / Alaska Native (includes Hispanic) | Asian / Pacific Islander (includes Hispanic) | Black (includes Hispanic) | Hispanic (any race) | White (includes Hispanic) | National Cancer Institute (2018) Lung and bronchus cancer. Retrieved from Janary 8, 2019 from https://seer.cancer.gov/explorer/application.php?site=47&data_type=1&graph_type=2&compareBy=race&chk_sex_1=1&chk_race_5=5&chk_race_4=4&chk_race_3=3&chk_race_6=6&chk_race_2=2&chk_age_range_1=1&chk_data_type_1=1&advopt_precision=1&advopt_display=1&showDataFor=sex_1_and_age_range_1_and_data_type_1 | ||||
| Year of Diagnosis | Rate per 100,000 | ||||||||
| 2000 | 45 | 41 | 77.8 | 34 | 68 | ||||
| 2001 | 47.9 | 79 | 34.1 | 68.7 | |||||
| 2002 | 44.6 | 40.4 | 75.8 | ||||||
| 2003 | 50 | 40.9 | 77.3 | 34.5 | 67.1 | ||||
| 2004 | 51.7 | 40.5 | 75.1 | 35 | 65.8 | ||||
| 2005 | 48.7 | 40.2 | 73.7 | 33.8 | 65.9 | ||||
| 2006 | 46.4 | 39 | 73.4 | 32 | |||||
| 2007 | 43.1 | 38.8 | 71.2 | 32.7 | 65.2 | ||||
| 2008 | 38.5 | 70.8 | 32.2 | 63.9 | |||||
| 2009 | 40.1 | 71.6 | 31.8 | 63.1 | |||||
| 2010 | 42.4 | 37 | 67.8 | 30.3 | 60.4 | ||||
| 2011 | 39.6 | 36.6 | 64.1 | 29.4 | 58.5 | ||||
| 2012 | 36.7 | 64.3 | 28.2 | 57.5 | |||||
| 2013 | 39.9 | 60.5 | 28.8 | 56.3 | |||||
| 2014 | 61.3 | 26 | 55.4 | ||||||
| 2015 | 38.7 | 34.4 | 57.4 | 53.2 |
Article Analysis and Evaluation of Research Ethics
Article Citation and Permalink
(APA format)
Article 1
Point
Description
Broad Topic Area/Title
Problem Statement
(What is the problem research is addressing?)
Purpose Statement
(What is the purpose of the study?)
Research Questions
(What questions does the research seek to answer?)
Define Hypothesis
(Or state the correct hypothesis based upon variables used)
Identify Dependent and Independent Variables and Type of Data for the Variables
Population of Interest for Study
Sample
Sampling Method
Identify Data Collection
Identify how data were collected
Summarize Data Collection Approach
Discuss Data Analysis
Include what types of statistical tests were used for the variables.
Summarize Results of Study
Summary of Assumptions and Limitations
Identify the assumptions and limitations from the article.
Report other potential assumptions and limitations of your review not listed by the author.
Ethical Considerations
Evaluate the article and identify potential ethical considerations that may have occurred when sampling, collecting data, analyzing data, or publishing results. Summarize your findings below in 250-500 words. Provide rationale and support for your evaluation.
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