Health Education Research, Vol. 18, No. 4, 429-438,
August 2003
© 2003 Oxford University Press
Does Stage of Change predict outcome in a primary-care intervention to encourage an increase in fruit and vegetable consumption?
Division of Public Health and Primary Health Care, University of Oxford, Institute of Health Sciences, Old Road, Headington, Oxford OX3 7LF, UK
*To whom correspondence should be addressed E-mail: sue.ziebland{at}dphpc.ox.ac.uk
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Abstract |
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Our aim was to investigate the response of participants in different Stage of Change (SOC) groups to an intervention to increase fruit and vegetable consumption. Participants recruited from a primary-care health centre were entered into a trial investigating an intervention to increase fruit and vegetable consumption. A total of 729 men and women were randomized into intervention and control groups. Participants attended two appointments 6 months apart and completed postal questionnaires before each appointment. The questionnaire included SOC questions which were used to classify participants into ‘pre-contemplation’, ‘contemplation’ and ‘action’ groups at baseline and at follow-up. All intervention participants received a standard intervention to increase consumption of fruit and vegetables to at least five portions per day. After 6 months at the end of the trial control participants received the same intervention. The main outcome measures were the changes in plasma concentrations of antioxidant vitamins. Changes in self-reported fruit and vegetable intake were a secondary outcome measure. At baseline, 38% (113/297) of the intervention participants were described as being in the ‘pre-contemplation’ stage, 35% in ‘contemplation’ and 27% in ‘action’ groups. For control participants, 36% (112/310) were in ‘pre-contemplation’, 34% in ‘contemplation’ and 30% in ‘action’ groups. In the intervention groups, 50% (57/113) of ‘pre-contemplators’ moved to the ‘action’ stage and 37% (42/113) moved to ‘contemplation’. There was little movement in the control ‘SOC’ groups between baseline and follow-up, other than a small drift to ‘contemplation’. Overall, the intervention group reported a greater increase in fruit and vegetable consumption than the controls (mean difference in change of 1.4 daily portions; 95% confidence interval 1.2, 1.6; after adjustment for baseline intake and gender) and significantly greater changes were reported in all three intervention ‘SOC’ groups compared to the corresponding ‘control’ groups (P < 0.001 in each case). These results suggest that peoples’ SOC may have little bearing on their success in increasing fruit and vegetable consumption.
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Introduction |
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The Stage of Change (SOC) model of behaviour change developed by Prochaska and DiClemente in 1984 integrates findings from a range of different theories (Prochaska et al., 1988
). The current model (Prochaska et al., 1992) proposes that individuals can be categorized into different stages of readiness with respect to a particular behaviour such as stopping smoking or eating less fatty foods. These stages are called pre-contemplation (not considering a change in behaviour), contemplation (considering change), preparation (decided to take action in the next month), action (changed behaviour in the last 6 months) and maintenance (maintaining new behaviour for longer than 6 months). The model implies that interventions would be most effective if they were tailored to the SOC of the individual. Thus, awareness-raising strategies should be more useful for the pre-contemplation stage to encourage individuals to start to think about the benefits of change, while action-oriented and supportive methods should work better for those in the later stages.
Although the model was originally developed for addictive behaviours, it has since been applied to a wide range of behaviours including physical activity (Booth et al., 1993), contraceptive use (Grimley et al., 1993), and dietary fat and fibre intake (Glanz et al., 1994; Greene et al., 1994; Greene and Rossi, 1998). Research in smoking cessation has suggested that smokers move through the different stages from pre-contemplation to contemplation, action and then maintenance (DiClemente et al., 1991). Critics of the model question the applicability of the SOC model to complex behaviours such as diet (Bandura, 2002) and also point out difficulties with the methods used to allocate people into the different stages (Comments on Farkas et al., 1996; Farkas et al., 1996; Sutton, 2001). A central tenet of the model is that the different stages are distinct from each other. However, studies using the SOC model use different time periods to classify people into the stages, suggesting that this may not be the case (Povey et al., 1999). Despite these concerns, the model remains popular in health promotion interventions
It has been suggested that since most interventions are directed at changing people’s behaviour, concentrating on those who express a readiness to change would enable resources to be used with optimum effect. Cox et al. (Cox et al., 1998) specifically recruited community volunteers classified as ‘contemplators’ to their trial investigating an intervention to increase fruit and vegetable intake. At the 6-month follow-up, 65% of intervention subjects reported that they had achieved the five-a-day target. This targeting approach may seem particularly appealing for interventions in primary care or other settings where resources are stretched and time is limited.
The SOC theory has also been used to develop tailored interventions to help people progress through the stages to action and maintenance. Marcus et al. (Marcus et al., 1998) used stage-tailored messages in their intervention trial designed to increase fruit and vegetable consumption among callers to the Cancer Information Centre. At 4 months, self-reported fruit and vegetable intake increased significantly by 0.34 daily portions in the intervention group, as determined by a seven-item food-frequency questionnaire administered over the telephone. Campbell et al. (Campbell et al., 1994) compared the effect of individually computer-tailored messages to standardized non-tailored messages on intake of fat, and fruit and vegetables. The group which received tailored messages reported a greater decrease in total and saturated fat intake over the control group than the non-tailored group. There was no increase in fruit and vegetable intake in any of the three groups (tailored intervention, non-tailored intervention or control). Brug et al. (Brug et al., 1997) investigated eating practices and psychosocial factors across SOC for fruit and vegetable consumption in a convenience sample of 739 Dutch adults using a self-administered questionnaire. They found that attitudes were most positive in preparation and action and least positive in pre-contemplation. Intake and self-efficacy were more positive in action/maintenance than in pre-action stages. The authors concluded that tailored interventions targeted at attitudes would be more effective for those in pre-contemplation and self-efficacy information to help in overcoming barriers more useful for those in contemplation and preparation.
We conducted a randomized control trial of a primary-care intervention (John et al., 2002) which used a brief negotiation method (Rollnick et al., 1993) to encourage an increase in fruit and vegetable consumption. Three broad categories of SOC were assessed in a postal questionnaire completed by participants before their baseline appointment and repeated before a follow-up appointment 6 months later. The intervention was not tailored to the individual’s SOC. This paper uses the longitudinal data available from the trial to investigate the responses of participants in different ‘SOC’ groups to the intervention in terms of their movement between SOC categories, and change in self-reported fruit and vegetable consumption
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Methods |
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Participants
All patients aged 25–64 years without serious chronic illness were identified from the lists of two general practices based in a health centre in Thame, Oxfordshire, UK. We excluded patients with cardiovascular diseases (other than hypertension), gastrointestinal disease, cancer, serious psychiatric disorder, hypercholesterolaemia, a recent traumatic event (such as bereavement) and those unable to give informed consent. Letters inviting patients to participate in a project giving advice about increasing ‘natural protective factors’ against cancer and heart disease were mailed sequentially until the target number of patients had been recruited. Only one participant from each household was recruited. Respondents who reported using dietary supplements or who were pregnant (or attempting to conceive) were not contacted further. Ethical approval for the study was obtained from the Central Oxford Research Ethics Committee.
Study design
Eligible subjects who agreed to participate in the trial were allocated sequentially to the intervention or control group by the trial administrator using a computer-generated randomization list. Randomization was in blocks of four and was stratified by reported smoking status. All those randomized were invited to attend two appointments 6 months apart with a trained research nurse at the health centre.
Questionnaire
Before each of the two appointments, all participants were mailed a self-completion questionnaire. Both questionnaires contained the previously validated DINE food-frequency questionnaire (Roe et al., 1994), and additional questions to record fruit and vegetable consumption, and SOC questions for exercise, and intake of fat, fruit and vegetables (Prochaska and DiClemente, 1983). Questions about fruit and vegetables were embedded within other questions to avoid alerting the control group to the nature of the intervention.
Health checks were carried out at both visits by the study research nurses, including height and weight measurement, and a 10-ml non-fasting venous blood sample was taken for measurement of antioxidant vitamins and total cholesterol.
Development of the intervention
The intervention was designed to deliver a simple, positive message about the benefits of eating more fruit and vegetables; to collect a realistic assessment of current consumption patterns, tastes and preferences; and to discuss barriers to change and agree a feasible action plan to increase consumption to five or more portions a day. We were aware that there is some confusion about what constitutes a portion, and of the effect that this might have both on participants’ recognition that an increase might be desirable and how they might achieve it. Others (Lechner and Brug, 1997) have found that respondents tend to over-estimate how many portions of fruit and vegetables they eat, and have highlighted the importance of making people more aware of their own fruit and vegetable intake. We therefore designed a pictorial guide, based on the portion sizes calculated by Williams (Williams, 1995), and developed an Eating Pattern Assessment Questionnaire (EPAQ) which was used to elicit meal and snack patterns on weekdays and weekends. Together with the portion guide, this was used to increase the accuracy with which fruit and vegetable consumption was reported. The EPAQ, set out in sections to parallel different parts of the day, also acted as a visual representation to highlight where and when increases might be made. For example, it was very clear to the participant if their usual weekday pattern did not include any portions until their evening meal or if all of their portions were consumed at home rather than at work and this immediately suggested ways that they could try to increase their intake.
The brief negotiation method (Rollnick et al., 1993) was used to encourage participants to identify specific, practical ways, consistent with their habits and preferences, of eating more fruit and vegetables. This method uses a discussive approach where the practitioner (the nurse in this instance) and the participant exchange their views on the behaviour change. The practitioner provides structure to the discussion and expert information about the behaviour change, and the participant is the active decision maker in the process. The trial nurses attended a custom-designed training course for the intervention.
Participants were encouraged to discuss possible barriers to eating more fruit and vegetables. A review of the literature guided the preparation of leaflets and other materials, which were designed to address a range of anticipated barriers, such as cost, eating out and catering for children, and a personalized selection of leaflets was given to each participant. All of the participants were given a copy of their action plan, a refrigerator magnet with the five-a-day logo and a 2-week self-monitoring record book (to keep track of their own fruit and vegetable intake) as well as the portion guide. The dietary intervention took approximately 25 min.
Two weeks after the initial intervention, the research nurse telephoned participants to reinforce the message and discuss any problems. At 3 months a letter was sent reinforcing the five-a-day message, together with a booklet of seasonal recipes, and a strategy check list suggesting various ways of incorporating additional portions of fruit and vegetable into the diet (Cox et al., 1998).
Control group
The control group consisted of participants randomized to receive the intervention after 6 months (delayed intervention group). They received the same health check, self-completed questionnaire and blood sampling as the intervention group. At the 6-month follow-up, they were given information about the benefits of eating fruit and vegetables, and offered the same materials as the intervention group.
SOC allocation
The SOC questions in the postal questionnaire (which was completed by all participants before their baseline and follow-up appointments) were used to allocate participants into three broad ‘SOC’ groups. Those who reported not thinking about changing either fruit or vegetable consumption in the next 6 months were classified as ‘pre-contemplators’. Those who reported increasing their consumption of either fruit or vegetables consumption in the past were classified as ‘action’. Those who said that they were thinking about increasing their fruit or vegetable consumption in the next 6 months were classified as ‘contemplators’. These three groups were chosen because we were interested in exploring changes over time in a trial population—particularly the effect of the intervention on those who were initially contemplators and pre-contemplators. The distinction between action and maintenance was of less interest to this study, which delivered the same type of intervention to all participants, regardless of SOC.
Statistical methods
Comparisons between proportions were made using the 
2-test and between means using the t-test. Adjustment for covariates was made using multiple regression analysis. Results are presented after adjustment for baseline and gender (which was unbalanced in the trial groups), but not for the other patient characteristics (smoking, age, social class, body mass index) since these made no difference to the results. Differences in outcome between the intervention and control group are shown with 95% confidence intervals (CI). Analysis was carried out using SPSS (version 9.0) and CIA (Confidence Interval Analysis, version 1.1)
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Results |
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Characteristics of participants
Participants
The response rate to the initial invitation was 45.4% (1045/2302). Respondents were older than non-respondents [mean (SD) age 46.1 (10.1) versus 40.1 (10.3) years; difference 6.0 years, 95% CI 5.2, 6.9] and included a higher proportion of women (55.3 versus 48.3%; difference 7.0%; 95% CI 2.9, 11.1). Respondents were also less materially deprived than non-respondents [mean (SD) Townsend Material Deprivation score (Morris and Carstairs, 1991) –0.98 (1.35) versus –0.75 (1.38); difference –0.23; 95% CI –0.34, –0.12). In total, 316 respondents [207 women (65.5%)] were excluded before randomization, including 312 because they were taking dietary supplements. Of the 729 participants randomized, data from 690 were included in the final analysis. See Table I.
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Outcome measures
The main results of the trial have been reported elsewhere (John et al., 2002
) and are not the main concern of this paper, but in brief the intervention was shown to have statistically significant effects (P values ranging from 0.032 to <0.001) on plasma concentrations of a range of antioxidants, on self-reported fruit and vegetable consumption [the difference in change after adjustment was 1.4 daily portions (95% CI 1.2, 1.6), bringing the intervention group mean to 4.9 (SD 1.6) portions], and on both systolic and diastolic blood pressure.
Changes in ‘SOC’ groups
Table II shows that at baseline there was little difference in the distribution of ‘SOC’ groups between the intervention and control participants. At baseline, 38% (113/297) of the intervention participants were described as being in the ‘pre-contemplation’ stage, 35% in ‘contemplation’ and 27% in ‘action’ groups. For control participants, 36% were in ‘pre-contemplation’, 34% in ‘contemplation’ and 30% in ‘action’ groups.
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At follow-up, only 5.4% (16/297) of the intervention group were classified as ‘pre-contemplators’. The majority were categorized as ‘contemplators’ or in ‘action’. This change was primarily due to the movement of ‘pre-contemplators’ to the ‘action’ stage (50.4%; 95% CI 41.2, 59.7; 57/113) and, to a lesser extent, to ‘contemplation’ (37.2%; 95% CI 28.3, 46.1; 42/113).
In contrast, 28.0% (87/310) of the control group were still classified as ‘pre-contemplators’ at follow-up. Of the 112 pre-contemplators at baseline, 59.8% (95% CI 50.7, 68.9; 67/112) remained pre-contemplators at follow-up. Although there was a suggestion of a slight drift towards contemplation and action, this change was smaller than in the intervention group (P < 0.0001).
Changes in self-reported intake
Overall, the intervention group reported a greater increase in fruit and vegetable intake (difference after adjustment for gender and baseline intake 1.4 daily portions, 95% CI 1.2, 1.6). Significantly greater increases in self-reported intake were recorded for all three ‘SOC’ groups in the intervention arm compared to control groups (Table III). There was a mean difference (after adjustment for gender and reported baseline intake) of 1.3 daily portions (95% CI 0.9,1.6) between intervention and control for ‘pre-contemplators’, 1.6 daily portions (95% CI 1.2, 1.9) for contemplators and 1.3 daily portions (95% CI 0.9, 1.7) for those in ‘action’.
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Table IV further explores the relationship between participants’ baseline and follow-up SOC and their self-reported consumption of fruit and vegetables. At the follow-up visit, all intervention group participants who were in the action stage at this point reported that they had increased mean consumption to at least five (95% CI 4.6, 5.4) daily portions, regardless of their baseline SOC. The 14 intervention participants who were classified as pre-contemplators at both baseline and at follow-up reported the highest mean baseline intake of 4.6 (95% CI 3.5, 5.7) daily portions.
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Discussion |
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This analysis was designed to explore the relationship between ‘SOC’ group and self-reported outcome in a trial of an intervention to increase fruit and vegetable consumption. Participants were not selected according to their SOC nor was the intervention adapted for different ‘SOC’ groups. Three basic categories of SOC were assessed solely to enable the analyses reported in this paper. These analyses represent an important opportunity to add to the theoretical work and cross-sectional studies on SOC and diet by including a longitudinal study of participants in an intervention trial.
According to the SOC model, interventions are most likely to be effective in those who are contemplating making the change. Therefore the intervention we used would not have been expected to have an effect on the intakes of those who had not considered eating more fruit and vegetables. Participants in our trial responded to a letter inviting them to take part in a study of ‘natural protective factors’ against heart disease and cancer. We were careful not to reveal the precise nature of the study until the intervention appointment with the nurse. Questions on fruit and vegetable intake and SOC questions for these foods were embedded within other questions. These questions may have encouraged some participants to change their diets or contemplate doing so. However, it seems unlikely that would have affected participants in intervention and control groups differently.
An examination of the relationship between baseline SOC and outcome suggests a different pattern of responses to the intervention. ‘Contemplators’ reported the largest increase in the number of portions consumed, which is consistent with the theory. However, baseline ‘pre-contemplators’ as well as those who described themselves as being in ‘action’ also reported substantial increases. Pre-contemplators seem to have been particularly receptive to the intervention—95% of the pre-contemplators in the intervention arm of the trial progressed to contemplation of action even though the theory suggests that this is not the appropriate approach with this group. A possible explanation for this apparent contradiction of the SOC theory could be that those who were originally ‘pre-contemplators’ were motivated by the intervention appointment and subsequently moved through the stages. Interim changes would not have been detected in our study since the only assessments were at baseline and after 6 months. The ‘pre-contemplation’ and ‘action’ (our classification did not distinguish between action and maintenance) stages may also be more long-term states, while ‘contemplation’ is more dynamic and may be quite short-lived. It is also possible that various aspects of this intervention (such as the brief negotiation method, simple, positive message, pictorial information about portion sizes and the completion of a questionnaire which identified current eating habits and identified opportunities for increased consumption) encouraged changes in those who had never thought about trying to eat more fruit or vegetables in the past. This suggests that participants’ baseline SOC may have little bearing on their success in increasing fruit and vegetable intake over a 6-month period.
In contrast to interventions which have been tailored to the individuals SOC (Campbell et al., 1994; Marcus et al., 1998), in our trial all participants received the same style of intervention which included an adaptable action plan, guided by the participant, to reach the five-a-day target. If different interventions tailored to different ‘SOC’ groups had been used, only the ‘contemplators’ would have been offered detailed dietary advice of the sort used in this intervention. ‘Pre-contemplators’ would have received information targeted at changing their attitudes, not their behaviour, and those in ‘action’ would have been given support to maintain their fruit and vegetable intake, rather than encouraged to increase it. It is uncertain if these other forms of advice would have had the same effect on these groups as the detailed suggestions and action plan given to all participants.
Research indicates that determining an individual’s SOC with respect to dietary behaviour may be more difficult than with addictive behaviour such as smoking. Povey et al. (Povey et al., 1999) conducted a questionnaire survey of 541 volunteers to measure their SOC with respect to three dietary behaviours: healthy eating, eating a low-fat diet, and eating five portions of fruit and vegetables per day. They found that those who were in the ‘action’ or ‘maintenance’ stage had been in these stages for a range of different time periods with no specific cut-off point to distinguish the two. Steptoe et al.’s (Steptoe et al., 1996) postal survey investigated stages of change for fat reduction and associations with dietary fat intake. In this survey, ‘pre-contemplators’ and ‘contemplators’ reported a higher fat intake than individuals at later stages, indicating some agreement between stage classification and dietary choice, but a significant proportion of people in the ‘action’ and ‘maintenance’ stages were actually not eating low-fat diets. The authors suggest that there may be an element of self-deception in response to questions on fat intake, and that respondents who were not on a low-fat diet may have reported that they were. Brug et al. (Brug et al., 1999) conducted a review of eight studies on tailored nutrition interventions for primary prevention of chronic disease. They concluded that personalization of fat reduction education was especially useful. since many people were aware of their high-fat intake. The authors also believed that people had many different misconceptions about low-fat alternatives to high-fat choices.
Work by Steptoe (Steptoe, 1996), Brug (Brug, 1997) and Povey (Povey, 1999) has alerted us to the fact that people may believe they are eating a healthy, low-fat diet with adequate portions of fruits and vegetables, even though it may not conform to nutritional guidelines. In our intervention we clarified what counted as a portion with our pictorial guide, which the participants were given to take home with a fridge magnet. An interesting finding in our study is that participants whose questionnaire responses put them in the ‘action’ group at baseline had a mean fruit and vegetable consumption that was less than the recommended five daily portions. However, at follow-up all participants in the intervention group reported a mean of five or more daily portions (including those in ‘action’), whilst consumption in the control remained below five a day in all ‘SOC’ groups. This suggests that respondents may have believed that they were eating sufficient quantities of fruit and vegetables, when in fact their intake was below recommended levels.
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Conclusions |
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Selecting participants or designing different approaches according to their SOC has been recommended in smoking cessation interventions (Prochaska and Goldstein, 1991
), but smoking and diet are very different behaviours. All smokers know that the recommendation is that they should stop smoking. While fruits and vegetables are widely regarded as healthy foods, many people are uncertain about what constitutes a portion or how many portions are recommended. Those who are not aware that their current consumption levels fall short of the recommendation, are unlikely to be considering or attempting changes. Those who might, if fully informed, be responsive to an uncontroversial intervention with a positive message could be ignored by programmes that only target those who express a readiness to change. Our trial results suggest that assessing SOC for fruit and vegetable interventions in primary care may be unnecessary or even misleading. Decisions about behaviour changes are complex, but a simple and positive message may be well received and acted upon, even by people who were not consciously contemplating a change. This is particularly the case with fruit and vegetable consumption, which is a widely recognized and uncontroversial component of a healthy diet. The self-monitoring booklets were popular with participants in our trial. The eating pattern assessment questionnaire, used with the portion guide, can be used to help people to identify when and where they might increase their consumption of fruit and vegetables. Primary-care staff may be better engaged in reviewing eating patterns and discussing barriers with patients whose diets are agreed to be deficient in fruit and vegetables, than in trying to categorise motivation to change.
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References |
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Received on February 12, 2002; accepted on July 9, 2002
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