SEARCH

SEARCH BY CITATION

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

Objective

A sufficient level of physical activity is important in reducing the impact of disease in rheumatoid arthritis (RA) patients. According to self-determination theory, the achievement and maintenance of physical activity is related to goal setting and ownership, which can be supported by health professionals. Our objective was to examine the association between physical activity and the extent to which RA patients 1) believe that physical activity is a goal set by themselves (autonomous regulation) or by others (coerced regulation) and 2) feel supported by rheumatologists (autonomy supportiveness).

Method

A random selection of 643 RA patients from the outpatient clinics of 3 hospitals were sent a postal survey to assess current physical activity level (Short Questionnaire to Assess Health-Enhancing Physical Activity), regulation style (Treatment Self-Regulation Questionnaire), and the autonomy supportiveness of their rheumatologists (modified Health Care Climate Questionnaire).

Results

Of the 271 patients (42%) who returned the questionnaire, 178 (66%) were female, their mean ± SD age was 62 ± 14 years, and their mean ± SD disease duration was 10 ± 8 years. Younger age, female sex, higher education level, shorter disease duration, lower disease activity, and a more autonomous regulation were univariately associated with more physical activity. Hierarchical multiple regression analyses demonstrated that younger age and a more autonomous regulation were significantly associated with a higher physical activity level (P = 0.000 and 0.050, respectively).

Conclusion

Regulation style was a significant determinant of physical activity in RA patients. This finding may contribute to further development of interventions to enhance physical activity in RA patients.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

Over the past decades, there has been growing evidence of the health benefits of physical activity for patients with rheumatoid arthritis (RA) (1). Despite this evidence, however, patients with RA are less physically active than the general population (2–5). As a consequence, physical activity is an important target for health promotion and the development and implementation of specific interventions for patients with RA are necessary. Although some interventions have demonstrated efficacy at increasing physical activity and improving quality of life (6, 7), not all patients benefited from these interventions, and many who did were not able to maintain elevated levels of physical activity in the long term (7). This problem is widely recognized in the literature (8–10).

Because only certain subgroups of patients seem to successfully reach and maintain target physical activity levels, it is important to explore patient characteristics that may differentiate these 2 subgroups. One of the most frequently mentioned patient characteristics in this respect is lack of motivation of the patient (11). Patient motivation is closely linked to goal ownership, or, in other words, the degree to which patients consider the target health behavior as their own self-chosen personal goal. Self-determination theory states that goals can be either internal, i.e., set by the patients themselves (autonomous regulation), or external, which implies that the goal is coerced or set by others (coerced regulation) (12, 13). In patients with type 2 diabetes mellitus (DM), autonomous regulation was found to be associated with beneficial lifestyle changes, medication adherence, and self-management (14). In obese individuals, autonomous regulation was an important predictor of program attendance, weight loss, and weight loss maintenance (15). Among healthy individuals, autonomous regulation proved to be related to frequent exercise behavior (16).

According to self-determination theory, autonomous regulation can be increased by others, for example, by means of autonomy supportiveness (13). An autonomy-supportive communication, offered by the patient's family, friends, medical specialists, or other health professionals, is characterized by supporting or increasing the patient's feelings of competence and responsibility for goal attainment (17). Examples of autonomy supportiveness include the provision of information on the potential health benefits; discussing examples of realistic, feasible goals (e.g., walking the dog for 15 minutes 5 days per week or taking a bicycle to work twice a week); monitoring these goals (e.g., by using an electronic or paper record, or using a pedometer); and how to act when these goals are not achieved (e.g., making a new start with the same goals or adjusting the goals in case they are not attainable). In obese individuals, autonomy supportiveness was also an important predictor of program attendance, weight loss, and weight loss maintenance (15).

To our knowledge, neither the regulatory styles of patients with RA (either autonomous or coerced regulation) nor the autonomy supportiveness of their rheumatologists have been explored in relation to physical activity in patients with RA. The present study aims to investigate 1) whether more autonomously regulated patients with RA report higher physical activity levels than patients with more coerced regulation, 2) whether more autonomy supportiveness on behalf of the rheumatologist is associated with higher levels of physical activity, and 3) to what extent the autonomy supportiveness moderates the impact of the patients' regulation style on physical activity. It was hypothesized that patients with RA with more autonomous regulation or patients with more autonomy supportiveness would be more physically active than patients with RA with more coerced regulation or less autonomy supportiveness. Furthermore, it was hypothesized that patients with RA with more autonomous regulation and more autonomy supportiveness (interaction) would have an even higher level of physical activity than patients with RA with only a more autonomous regulation.

PATIENTS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

Study design and patient recruitment.

This was a multicenter, cross-sectional study performed between October 2006 and April 2007 in the rheumatology outpatient clinics of 3 hospitals (Leiden University Medical Center; Haga Hospital, The Hague; and Reinier de Graaf Hospital, Delft). From the registries in these hospitals, all patients with RA visiting the outpatient rheumatology clinics in the past 12 months were selected. The registries included 1,055, 620, and 555 patients with RA, respectively.

In each registry, patients were randomly assigned a number by means of Microsoft Office Excel 2003 (Redmond, WA). Subsequently, patients with the lowest random numbers were selected: 400 patients from the Leiden University Medical Center registry, 200 from the Reinier de Graaf Gasthuis registry, and 200 from the Haga Hospital registry in The Netherlands. After checking the national registry office and verifying the diagnosis of RA according to the criteria of the American College of Rheumatology (ACR; formerly the American Rheumatism Association) (18) on the basis of the patients' medical records, the patients were sent an information leaflet about the study, a set of questionnaires, an informed consent form, and a prestamped envelope. Three weeks after the questionnaire was sent, nonresponders received a telephone reminder from the principal investigator (EJH). The medical ethics committees of the 3 participating hospitals approved the study protocol, and all patients provided written informed consent.

Measurements.

All data were obtained by means of questionnaires, except for disease duration, which was derived from the medical record.

Patient characteristics.

Sociodemographic data included age (years), sex, living status (living alone or with other people), education level (low, up to and including lower technical and vocational training, or high, up to and including higher technical and vocational training and university), and employment status (part-/full-time job or no job). In addition, disease duration (years) was recorded. Furthermore, functional ability was recorded by means of the Health Assessment Questionnaire (HAQ) (19). The HAQ is an independent patient-reported outcome questionnaire containing 20 questions regarding 8 domains of daily living activities. The total score as well as each subscore range from 0 to 3, where 0 = no disability and 3 = severe disability. The Dutch version of the HAQ has been validated (19).

Physical activity.

The Short Questionnaire to Assess Health-Enhancing Physical Activity (SQUASH) was used to determine the amount of physical activity (20). The SQUASH contains questions regarding physical activity as related to commuting activities (walking or bicycling to/from work or school), leisure time activities (walking, bicycling, gardening, odd jobs) and sports activities (for example, playing tennis and swimming), household activities (light household work such as cooking, washing dishes, and ironing, and intense household work such as scrubbing a floor and walking with heavy shopping bags), and activities at work and school. For each of these domains, the activity level is measured using 2 queries: days per week and average time per day. The time per day (in minutes) was multiplied by the days per week to calculate the total minutes that the patient spent on this specific activity. The scores of all domains were then added up, resulting in the final score. The SQUASH has been found to be a reliable and reasonably valid questionnaire (20).

Regulatory style.

The Treatment Self-Regulation Questionnaire (TSRQ) concerning physical activity (16, 21, 22) was used to discriminate between an autonomous regulatory style (3 items) and a controlled regulatory style (7 items). It contained questions such as: “I am physically active because I think this is important to stay healthy” (autonomous regulation) versus “I don't want other people to be disappointed in me” (coerced regulation). As an introduction to the questionnaire, it was explained what was meant by physical activity. It was said that physical activity is not only related to sports or exercise, but to any type of bodily movement, including walking indoors or outdoors or climbing the stairs. This means that every person is physically active at some level and can fill in the questionnaire. Each item was rated on a 7-point Likert scale, where 1 = not true at all and 7 = very true. The scores of the 3 items with regard to autonomous regulation were added up and divided by 3, resulting in the final score for autonomous regulation. The scores of the 7 items with regard to coerced regulation were also added up and divided by 7, resulting in the final score for coerced regulation. By subtracting the Z score for coerced regulation from the Z score for autonomous regulation, a combined score (for the regulatory style) was calculated. The interpretation of this combined score is as follows: a high score for the regulatory style indicates a more autonomous style, whereas a low score indicates a more coerced style. The TSRQ has a reasonable validity, reliability, and internal consistency (21).

Autonomy supportiveness of the rheumatologist.

A Dutch translation and adaptation of the Health Care Climate Questionnaire (HCCQ) consisting of 15 items was used to assess patients' perception of the degree of their rheumatologists' autonomy supportiveness in providing care. The lead-in statement was “The following questions concern your contact with your rheumatologist. All rheumatologists have their own way of communicating with patients, and we would like your opinion about that.” The questionnaire itself contained questions such as “I feel that my rheumatologist has provided me choices and options” and “My rheumatologist listens to how I would like to deal with things.” All items were rated on a 7-point Likert scale, where 1 = not true at all and 7 = very true. The score of all 15 items are added and divided by 15, resulting in the final score. The HCCQ has a good internal consistency and has been validated in studies of weight loss (16) and glucose control (23).

Disease activity.

The Rheumatoid Arthritis Disease Activity Index (RADAI) measures self-assessed disease activity in patients with RA (24). The RADAI contains 5 items concerning global disease activity during the last 6 months (item 1), current disease activity in terms of swollen and tender joints (item 2), current amount of arthritis pain (item 3), current duration of morning stiffness (item 4), and current number of tender joints (item 5). The first 3 items are scored on an 11-point numerical rating scale, with verbal anchors at no disease activity/no pain (score of 0) and extreme disease activity/extreme pain (score of 10). Item 4 is scored on a 7-point verbal rating scale, with verbal anchors at no morning stiffness (score of 0) and all day (score of 6). Item 5 is scored on a 4-point verbal rating scale (for the left and right shoulder, elbow, wrist, fingers, hip, knee, ankle, and toes), with verbal anchors at not tender (score of 0) and severely tender (score of 3). The scores of items 4 and 5 range from 0 to 6 and from 0 to 48, respectively, and were each transformed to a 0–10 scale. The total score (range 0–10) of the RADAI was computed by summing the scores of the individual 5 items and dividing by 5. The Dutch RADAI was found to have a good validity and internal consistency (24).

Statistical analysis.

With respect to the patient characteristics, categorical data were described as numbers and percentages. Continuous data with a Gaussian distribution were described as means and SDs, and other continuous data were presented as medians and interquartile ranges. Differences in patient characteristics between the 3 centers were analyzed by means of the analysis of variance, Student's t-test, or chi-square tests, where appropriate.

First, preliminary analyses were carried out (with Pearson's correlations and t-tests) to examine the univariate relationships between the physical activity level and the sociodemographic, disease-related, and regulation variables. Second, a multiple hierarchical regression analysis was conducted with physical activity as the dependent variable. In the first block, the regulation style was entered in the analysis (model 1). In the second block, the autonomy supportiveness of the rheumatologist was entered into the model (model 2). In the third block, the interaction term between the regulation style and autonomy supportiveness was added to the model (model 3). The interaction term was computed by multiplying the score on the regulation style with the score on autonomy supportiveness. To avoid multicolinearity, both variables were centered (by subtracting the mean value from each individual value) before calculating the interaction term. In the fourth block, the disease-related variables that were found to be univariately significantly associated with physical activity were added to the model (model 4). Finally, in the last block, the sociodemographic characteristics that were found to be univariately significantly associated with physical activity were entered into the model (model 5). P values less than 0.05 were considered statistically significant in these analyses, and all analyses were conducted using SPSS 14.0 for Windows (SPSS, Chicago, IL).

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

Patients.

Of the 800 randomly selected patients, 643 fulfilled the ACR criteria and were sent a questionnaire (326 in the Leiden University Medical Center, 159 in the Reinier de Graaf Gasthuis, and 158 in the Haga Hospital). Initially, 213 patients returned the questionnaire, resulting in a response rate of 33% after 3 weeks. After telephone contact with the nonresponders, the response rate increased to 42% (n = 271). No statistical difference was found between the responders and nonresponders with regard to age (P = 0.239), but the proportion of men was significantly higher in the group of patients who returned the questionnaire (P = 0.003).

Patient characteristics and preliminary analyses.

Patient characteristics are shown in Table 1. No significant differences were found between the 3 centers with respect to the sociodemographic variables, the disease-related variables, or the dependent and independent variables (data not shown).

Table 1. Characteristics of 213 patients with rheumatoid arthritis*
 Value
  • *

    Values are the mean ± SD unless otherwise indicated. HAQ = Health Assessment Questionnaire; RADAI = Rheumatoid Arthritis Disease Activity Index; SQUASH = Short Questionnaire to Assess Health-Enhancing Physical Activity.

  • Low = up to and including lower technical and vocational training; high = up to and including higher technical and vocational training and university.

Patient characteristics 
 Age, years62 ± 14
 Female patients, no. (%)178 (66)
 Living alone, no. (%)66 (25)
 Educational level, no. (%) 
  Low168 (63)
  High99 (37)
 Paid job (full time and part time), no. (%)76 (28)
 HAQ (range 0–3)1.1 ± 0.8
Disease-related variables 
 Disease duration, years10 ± 8
 Disease activity (RADAI, range 0–10)3.5 ± 4.6
Dependent and independent variables 
 Physical activity (SQUASH), minutes  per week1,717 ± 1,166
 Regulation style (range −6 to 3)0.012 ± 1.44
 Autonomous supportiveness (range 1–7)5.6 ± 0.8

The Pearson's correlations between the sociodemographic variables, disease-related variables, regulation variables, and physical activity are shown in Table 2. Of the sociodemographic variables, a lower age, female sex, and a higher educational level were significantly associated with a higher physical activity level (P < 0.001, P = 0.036, and P = 0.016, respectively). With respect to the disease-related variables, both a shorter disease duration and a lower disease activity were significantly associated with a higher physical activity level (P = 0.002 and P = 0.015, respectively). With respect to the regulation variables, only the regulation style was significantly associated with physical activity (more autonomous regulation was associated with higher physical activity levels, and more coerced regulation with lower physical activity levels).

Table 2. Correlation matrix
 AgeSexDisease durationDisease activityRegulation styleAutonomous supportPhysical activity
  • *

    Significant; P = 0.05.

  • Significant; P = 0.01.

  • 0 = male, 1 = female.

Age1−0.147*0.125*0.208*−0.3430.111−0.493
Sex 10.032−0.0350.206−0.0870.130*
Disease duration  10.0090.100−0.001−0.192
Disease activity   1−0.176*−0.021−0.159*
Regulation style    10.0210.299
Autonomous support     10.022
Physical activity      1

Hierarchical regression analysis.

The results of the hierarchical regression analysis with physical activity as the dependent variable are shown in Table 3. The first model including the regulation style as the predictor was significantly different from the null model (F = 18.09, df = 1, P < 0.001) and allowed us to explain 10% of the variance (R2 = 0.11, adjusted R2 = 0.10) in physical activity. More autonomous regulation style significantly predicted a higher level of physical activity (P < 0.001). Adding autonomy supportiveness to the regression model (model 2; R2 = 0.11, adjusted R2 = 0.10, F = 9.37, df = 2, P < 0.001), the interaction term between the regulation style and autonomy supportiveness (model 3; R2 = 0.12, adjusted R2 = 0.10, F = 6.77, df = 3, P < 0.001), and the disease-related variables disease activity and disease duration (model 4; R2 = 0.14, adjusted R2 = 0.11, F = 4.66, df = 5, P = 0.001), did not lead to a significant increase in explained variance. The only significant predictor of physical activity in models 2, 3, and 4 was therefore the regulation style (P < 0.001) (Table 2). Finally, adding age, sex, and educational level to the regression model (model 5) resulted in a significant increase in the amount of explained variance (R2 = 0.26, adjusted R2 = 0.21, F = 6.03, df = 8, P < 0.001). Both a lower age and a higher autonomous regulation style significantly predicted a higher level of physical activity (P < 0.001 and P = 0.049, respectively), whereas more autonomy supportiveness of the rheumatologist did not (P = 0.148).

Table 3. Summary of hierarchic regression analysis for variables associated with the total amount of physical activity (amount of minutes on the SQUASH)*
 Model 1Model 2Model 3§Model 4Model 5#
B (β)SE BPB (β)SE BPB (β)SE BPB (β)SE BPB (β)SE BP
  • *

    SQUASH = Short Questionnaire to Assess Health-Enhancing Physical Activity; B = unstandardized coefficient; β = standardized coefficient.

  • R2 = 0.109; F for change in R2 = 18.093 (P < 0.001).

  • R2= 0.113; F for change in R2 = 0.687.

  • §

    R2= 0.122; F for change in R2 = 1.498.

  • R2= 0.139; F for change in R2 = 1.430.

  • #

    R2= 0.255; F for change in R2 = 7.291 (P < 0.001).

Constant1,847.6192.320.0001,845.0592.460.0001,850.3892.410.0002,072.33167.210.0003,597.32643.250.000
Regulation style278.26 (0.33)65.420.000280.16 (0.33)65.530.000268.52 (0.32)66.100.000264.32 (0.314)67.530.000138.70 (0.17)69.880.049
Autonomy supportiveness   7.02 (0.06)8.450.4084.86 (0.05)8.630.5745.32 (0.05)8.620.53812.02 (0.11)8.260.148
Regulation style and autonomy supportiveness interaction      7.96 (1.00)6.510.2235.82 (0.07)6.610.3814.14 (0.05)6.240.507
Disease duration         −15.28 (0.09)12.880.237−7.23 (−0.04)12.310.558
Disease activity         −22.78 (−0.10)18.810.228−10.49 (−0.04)17.980.560
Age            −33.47 (−0.36)7.780.000
Sex            174.94 (0.07)187.430.352
Educational level            10.32 (0.02)43.990.815

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

The results of this study indicate that 1) a higher level of autonomous regulation significantly predicts a higher level of physical activity, 2) more autonomy supportiveness from the rheumatologists does not predict a higher level of physical activity, and 3) more autonomy supportiveness from the rheumatologist does not significantly contribute to a higher level of physical activity when the regulatory style is taken into account. Therefore, in patients with RA with a more autonomous regulation, receiving more autonomy supportiveness does not necessarily lead to a higher physical activity level.

Although this is the first study on the relation between regulation style and physical activity in patients with RA, the results are comparable with those of the studies by Senecal and Nouwen (14) and by Wilson et al (16). Senecal and Nouwen (14) conducted a study with 638 DM patients and found that a more autonomous regulatory style was associated with more self-care activities, including physical activity. In the second study, Wilson and colleagues (16) explored the relationship between exercise behavior and exercise motivation in 500 healthy subjects. The results indicated that intrinsic motivation (autonomous regulation) was positively correlated with exercise behavior.

No significant effect of autonomy supportiveness on physical activity was found in our study, although the results go in the expected direction. In the study by Williams et al (15), autonomy supportiveness was found to be an important predictor of program attendance, weight loss, and weight loss maintenance among 128 obese individuals. One reason for this difference may be that Williams and colleagues measured overall autonomy supportiveness (of all relevant health care providers), whereas our study only measured the supportiveness of the rheumatologist. Another reason may be that the study by Williams et al focused on program effects, whereas our study describes the natural development of physical activity in a patient population. In addition, our autonomy supportiveness measure evaluated the overall support of the rheumatologists, not the specific support of the rheumatologists with regard to exercise and/or physical activity. All of these factors may have weakened the influence of support on physical activity in our study. Our findings suggest that in future research, the role of autonomy supportiveness with respect to the physical activity behavior of patients with RA should be evaluated in the context of a specific physical activity intervention, and include, apart from the rheumatologist, relevant health professionals such as physical therapists and clinical nurse specialists as well. Moreover, it should be examined how the results of a physical activity–specific version of the HCCQ would relate to the more general version.

With respect to other determinants of physical activity, we found that a younger age, female sex, higher educational level, lower disease activity, and shorter disease duration were significantly associated at a univariate level with a higher level of physical activity. Previous studies among patients with arthritis have shown comparable results: age, education, and pain have all been found to be determinants of physical activity levels (2, 3, 25, 26). In contrast, in one of these studies it was found that male rather than female sex was associated with higher levels of physical activity (26). Most of these relations, except the relation between age and physical activity, disappear, however, at a multivariate level when the influence of the motivational orientation of the patient is taken into account.

The physical activity levels as found in the present study are in line with the results of an earlier study performed in 2004 by our group, in which the average was 1,535 minutes per week in 232 patients with RA (5). In that study, the amount of physical activity in an age- and sex-matched sample from the general population in The Netherlands was 1,869 minutes per week, the difference of which was statistically significant (5). Because it has been found that the average amount of physical activity has increased by ∼100 minutes per week over the last 3 years in the general population in The Netherlands (27), the average amount of 1,700 minutes for the patients with RA in our study may be considered relatively low.

The results of this study have potentially important consequences for the daily practices of various health professionals such as rheumatologists, specialist nurses, and physical therapists. If health professionals want to promote physical activity in patients with RA, they should also take the regulation style into account by measuring the patients' motivational orientation. By merging the scores for autonomous and coerced regulation of the TSRQ into a total regulation score, this study provides a useful tool for this purpose that is short, easy to score, and easy to interpret. A patient is indentified as a more autonomous regulator by a higher score and as a more coerced regulator by a lower score.

It is quite clear that health professionals should try to increase and support autonomous regulation in their patients in order to enhance physical activity. A specific clinical method that fits this purpose is motivational interviewing. Motivational interviewing is a client-centered, directive method for enhancing intrinsic motivation, or, in other words, autonomous regulation. The health professional's role in this process is to help the patient locate and clarify their motivation for change, providing information and support and offering alternative perspectives on the problem behavior and potential ways of changing. Motivational interviewing can only be successful when the patients decide for themselves that a behavioral change is needed (28). That this approach is promising can be illustrated by means of 2 recent randomized controlled studies in patients with type 2 DM (29) and chronic heart failure (30), respectively. In the first study, by Rubak et al, motivational interviewing improved patients' understanding of DM, their beliefs regarding treatment aspects, and their contemplation on and motivation for behavioral change. The second study, by Brodie et al, demonstrated that motivational interviewing, incorporating behavior change principles to promote physical activity, is effective in increasing patients' quality of life.

The current study had a few limitations. First, the study had a cross-sectional design, and should therefore be complemented by a followup over time in order to allow for firmer conclusions about causality. Second, the mean disease duration of the patients with RA included in our study was 10 years. Therefore, conclusions are limited to patients with an established rheumatic disease. At the onset of the disease, patients experience in general a more unstable disease course with flares of disease activity and pain. It is unknown to what extent the disease course and the patient's adjustment influence regulation style. Third, we only used a self-reported measurement for physical activity, whereas physical activity can be assessed in various ways (31, 32). The use of a performance-based measure of physical activity such as an accelerometer or a pedometer could have added to this study. However, due to the design of the study and limited resources, a performance-based measurement was not applied. Fourth, the response rate was 42%. Although this is acceptable and comparable with other studies (33), it is quite possible that the most motivated patients responded, which could have resulted in a higher score for autonomous regulation.

In conclusion, the findings indicate that patients' regulation style is related to their daily physical activity level. This study therefore suggests that increasing patients' intrinsic motivation (autonomous regulation), perhaps through the use of motivational interviewing, may result in increased levels of physical activity among patients with RA.

AUTHOR CONTRIBUTIONS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be submitted for publication. Ms Hurkmans had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study conception and design. Hurkmans, Maes, de Gucht, Vliet Vlieland.

Acquisition of data. Hurkmans, Peeters, Ronday, Vliet Vlieland.

Analysis and interpretation of data. Hurkmans, Maes, de Gucht, Knittle, Vliet Vlieland.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES

The authors thank Rebecca Schouten, student of Health Psychology, Leiden University, for her contribution to the construction of the data bank.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. PATIENTS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. AUTHOR CONTRIBUTIONS
  8. Acknowledgements
  9. REFERENCES