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(Chest. 2005;128:3133-3139.)
© 2005 American College of Chest Physicians

Understanding Participation in an Asthma Self-Management Program*

Valentine Lemaigre, MA; Omer Van den Bergh, PhD; Katrien Van Hasselt, MA; Steven De Peuter, PhD; An Victoir, MA and Geert Verleden, MD, PhD

* From the Department of Respiratory Diseases (Dr. Verleden and Mr. Lemaigre), University Clinic Gasthuisberg; and Research Centre for Stress, Health and Well-Being (Dr. Van den Bergh, Ms. Van Hasselt, Dr. De Peuter, and Mr. Victoir), Department of Psychology, Leuven, Belgium.

Correspondence to: Geert Verleden, MD, PhD, University Clinic Gasthuisberg, Department of Respiratory Diseases, Herestraat 49, 3000 Leuven, Belgium; e-mail: Geert.Verleden{at}uz.kuleuven.ac.be


   Abstract
TOP
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 Appendix
 References
 
Study objective: Asthma education programs improve asthma treatment results significantly. Low participation rate is a recurrent problem that impedes the efficiency of those programs. The purpose of this study was to investigate social cognitive determinants of the intention to participate in an asthma self-management program.

Design: Structured interview.

Setting: Outpatient clinic, University Hospital Gasthuisberg, Leuven, Belgium.

Patients: One hundred seven asthmatic outpatients (mean age 42 years; 35% male).

Interventions: Patients received a standard explanation about the asthma program, were invited to participate, and were questioned about their beliefs about the program offered.

Measurements and results: A social cognitive framework (attitude, social influence, and self-efficacy model) was used to compose a structured interview that was administered to assess the patients’ attitude toward the program (perceived benefits), their social influence, and self-efficacy expectations to participate (perceived barriers). Asthma-related health behavior and clinical and demographic characteristics were evaluated by means of questionnaires. Fifty-nine percent of the patients expressed the intention to participate. Logistic regression analysis resulted in a model explaining 72% of the variance of intentions (Nagelkerke R2 = 0.72). Having few structural barriers to participate was a significant predictor of participation (odds ratio [OR], 12.5; 95% confidence interval, 5.2 to 19.3), next to believing in the personal benefits of the program (OR, 7.6; 95% confidence interval, 2.4 to 12.5), social influence (OR, 3.3; 95% confidence interval, 1.3 to 8.4), and education level (OR, 2.7; 95% confidence interval, 1.3 to 5.6).

Conclusions: Recruitment of patients with asthma for an educational program should emphasize personal benefits of the program, should include patients’ social network, and should consider the impact of structural barriers on participation behavior.

Key Words: asthma program • participation • self-management • social cognitive determinants


   Introduction
TOP
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 Appendix
 References
 
Asthma self-management programs are set up to teach asthmatic patients better self-care. They usually include education, making action plans, regular medical review, and self-monitoring exercises. Previous research has repeatedly demonstrated that education programs are effective and should be integrated in the asthma treatment.1 A recurrent problem asthma educators observe, however, is low participation of the patients.2 This is in line with other health domains emphasizing self-management, such as pain and diabetes.34 A low participation rate is problematic because it impedes the efficiency of the programs and leads to an underuse of the programs offered.

Previous research on participation in self-management programs has mainly focused on demographic and clinical determinants.567 Demographic characteristics such as gender, smoking status, age, and education level were found to be significant predictors of participating in or attending an asthma program, in addition to asthma duration and severity of the baseline asthma attack. Muntner et al7 performed a closer investigation of determinant patient characteristics and found that having low confidence in the medical treatment regimen was also a significant predictor for participation.

In the present study, we aim to increase the understanding of participation behavior by focusing on patients’ beliefs about the program offered. According to the attitude, social influence and self-efficacy (ASE) model, the intention to perform a behavior is determined by a set of proximal social cognitive determinants.8 Attitude refers to the sum of positive and negative beliefs and evaluation of the behavior. Social influence refers to the perceived social pressure an individual may feel to perform the particular behavior, and self-efficacy is the perceived ease or difficulty to perform the behavior. The behavioral intention can further be determined by more distal variables, such as social, cultural factors, and biological factors. The ASE model, applied to the intention to participate in an asthma program, is shown in Figure 1 , top, a. The purpose of this study was to use the ASE model to investigate social cognitive determinants of the intention to participate in an asthma self-management program.



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  		Figure 1. Top, a: Theoretical model. ASE model is applied to the behavioral intention of participation in an asthma program. Bottom, b: Actual model. Model used for logistic regression analysis. The separate fields represent the distal and proximal factors with possible predictive value on the intention to participate in an asthma program, following the ASE model. Relations between the fields are indicated with arrows.

 

   Materials and Methods
TOP
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 Appendix
 References
 
Subjects and Procedure
Inclusion criteria were as follows: outpatients coming to the hospital for pulmonary consultation, aged between 18 and 65 years, with asthma diagnosis made according to Global Initiative for Asthma guidelines at least 6 months before recruitment.9 Exclusion criteria were comorbidity (somatic and psychiatric diseases), non-Dutch speaking, brittle asthma, occupational asthma, and previous participation in an asthma education program. One of the researchers (V.L.) addressed the patients before their visit to the physician and invited them to take part in a study on participation in an asthma program. Patients gave their oral informed consent to receive information about the program and to be questioned about their opinion on the program. While showing the workbook used in the education sessions, we gave the patients a standard description of our asthma program:
We would like to invite you to an asthma program set up for patients with asthma who wish to learn more about their asthma, who wish to be more involved in their asthma treatment, or whose asthma is uncontrolled despite optimal treatment. By means of education, exercises, and interactive discussions, we teach participants ways to improve their self-care. The program takes place in the late afternoon over a period of one and a half months and includes 3 sessions: 2 group sessions of 2 hours and 1 individual session of 1 hour. Participation is free. We asked the participants to fill in questionaires at several fixed time points to evaluate the effects of the program.

We told the patients that they would be informed about the exact time and date of the sessions 3 weeks ahead of the program start. A structured interview, as described below, was administered to the patient. Subsequently, we handed questionnaires to the patients. These had to be filled in at home and sent back with a prestamped envelope to save time on the day of the study. We told the patients the interview and the questionnaires were meant to get a better understanding of their reasons to participate or not in our program. Finally, the patients indicated on a form their intention to participate. To avoid socially desirable answers, the researcher made sure respondents noted that she did not look at the answer they filled in on the form. This study was part of a larger effectiveness study of our asthma program and was approved by the local Ethical Committee.

Measures
The intention to participate in the program was measured as a desire to participate. Patients indicated with yes or no whether they wanted to participate. Patients who declined participation mentioned on the answering form the main reason for their decision.

Interview:
A structured interview was set up to measure the proximal factors put forward in the ASE model (Appendix). When developing the interview, 15 pilot patients were probed for their beliefs about the program by means of open questions. The open questions addressed possible advantages of and barriers to participating. The answers were used to compose the final structured interview, consisting of 17 questions as described in the Appendix.

Of these, nine questions were developed to assess the patient’s attitude toward the program in terms of perceived benefits (1, 2, 5, 7, 11, 13, 14, 15, and 16); and seven questions assessing beliefs about barriers to participate were set up as a self-efficacy measure (3, 4, 6, 8, 9, 10, and 12). These 16 questions had an answering format on a 5-point Likert scale ranging from "I do not agree at all" (score = 1 for attitude questions; score = 5 for self-efficacy questions) to "I totally agree" (score = 5 for attitude questions; score = 1 for self-efficacy questions). A higher score reflects a more positive attitude. Self-efficacy scores were reversed for convenience sake; higher scores reflect fewer barriers and therefore higher self-efficacy.

The 17th and last section of the interview assessed social influence by asking 10 subquestions evaluating (1) social norms the patients experience to take better care of their asthma, such as "do(es) your partner/children/parents/best friend/others think you should take better care of your asthma?" (17A, 17B, 17C, 17D, and 17E); and (2) the patients’ motivation to comply with these social norms, such as "do you agree with him/her/them?" (17Ai, 17Bi, 17Ci, 17Di, and 17Ei). All 10 questions were answered with yes (score = 1) or no (score = 0). When the answer to questions 17A, 17B, 17C, 17D, or 17E was no (score = 0), the score stayed 0 no matter whether or not the patients were motivated to comply, because in that case no social influence was experienced to take better care of the asthma. When the answer to the questions 17A, 17B, 17C, 17D, or 17E was yes (score = 1), the score of the answer to the questions 17Ai, 17Bi, 17Ci, 17Di, or 17Ei was added. Thus, for every referent (partner, children), a minimum score of 0 and a maximum score of 2 could be obtained. Scores for the five referents were added to obtain a final social influence score, ranging from 0 to 10. All patients were required to find five referents who had an opinion on the way patients handled their asthma.

Questionnaires:
Some additional issues were evaluated with the following questionnaires:

The McMaster Asthma Quality of Life Questionnaire:
The McMaster Asthma Quality of Life Questionnaire (AQLQ) measures health-related limitations in quality of life experienced by patients with asthma during the past 2 weeks.10 Thirty-two items assess four domains: symptoms (12 items), emotions (5 items), exposure to environmental stimuli (4 items), and activity limitations (11 items), and have to be rated on a scale from 1 (low quality of life) to 7 (high quality of life).

The Asthma Symptom Checklist:
The Asthma Symptom Checklist (ASC) is a 36-item questionnaire developed to assess subjective symptomatology in asthma.1112 It consists of six symptom scales: symptoms of airway obstruction (five items), dyspnea (three items), fatigue (six items), anxiety (eight items), irritation (six items), and symptoms suggestive of hyperventilation (six items). The subjects rate on an 11-point scale the intensity with which they experienced a symptom the past 2 weeks (0 = no symptom, 10 = symptom as bad as possible).

The Knowledge, Attitude and Self-Efficacy Asthma Questionnaire:
The Knowledge, Attitude and Self-Efficacy Asthma Questionnaire (KASE-AQ) consists of three subscales of 20-items each and assesses the following: (1) patients’ knowledge regarding asthma (every item rated 0 or 1, total scores ranging from 0 to 20); (2) patients’ attitude toward the illness; and (3) self-efficacy regarding the perceived ability to control the disorder (every item rated on a 5-point scale, total scores ranging from 20 to 100 per subscale).13

The Positive and Negative Affect Schedule:
The Positive and Negative Affect Schedule (PANAS) consists of two subscales (10 items per scale), assessing positive and negative affectivity as a personality trait.14 On a list of 20 adjectives (eg, sad, enthusiastic, nervous), the subjects indicate the degree to which the adjective is applicable to him/her, from "very little or not at all" (score = 1) to "very much" (score = 5).

In addition to the questionnaires, the highest level of education obtained and marital status were questioned.

Clinical Characteristics:
The following clinical characteristics were collected from the medical files: pulmonary function performed on the day of the visit: FEV1, FVC, peak expiratory flow (PEF), number of years with asthma, and previous hospitalizations due to an asthma exacerbation (0 = none, 1 = one or more hospitalizations in the past).

Statistical Analysis
Statistical analyses were performed on data obtained from the 107 patients who returned the questionnaires. Missing values in the questionnaire data were replaced by individual scale means when at least 50% of the scale items were filled in, to guarantee representative results. All statistical analysis was performed after the distributions had been checked for normality. A principal component analysis with varimax rotation was performed on the attitude, self-efficacy, and social influence interview questions to evaluate their psychometric characteristics.

Group means of the questionnaire data assessed in the participant and nonparticipant groups were compared with one-way analysis of variance tests, {chi}2 tests, or Mann-Whitney U tests when appropriate. The characteristics that were significantly different in the two groups were included in the regression model as distal factors.

We performed a series of logistic regressions on the distal and proximal factors included in the model and evaluated the predictive power of the factors on the intention to participate in the program. Statistical analyses were computed with the statistical program (SPSS version 11.0; SPSS; Chicago, IL).


   Results
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 Appendix
 References
 
The structured interview was administered to 138 asthmatic patients. One hundred seven patients returned the questionnaires (response, 78%). Fifty-nine percent of this final group of patients expressed the desire to participate in the program (n = 63). Reasons for declining participation were, in order of importance as determined by the number of patients who offered the reason: lack of time, distance to the hospital, no symptoms and therefore no need to participate, and lack of interest in the program.

The principal component analysis performed on the interview questions resulted in four components explaining 61% of the variance of the interview questions (Table 1 ). Interview questions 2, 6, 9, and 10 had to be excluded because of recurrent low loadings on components or high loadings on isolated components.


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  		Table 1. Principal Component Analysis Results of the Interview Questions*

 
The attitude questions loaded on two distinct components: a component "personal benefits" and a component "general benefits." Cronbach {alpha} was high for the personal benefits and general benefits scales (0.80 and 0.76, respectively) and somewhat lower for the self-efficacy scale (0.50), reflecting the diverse nature of barriers patients perceive to participating. Overall, the principal component analysis results showed that interview questions 1, 3, 4, 5, 7, 8, 11, 12, 13, 14, 15, 16, and 17 had factor loadings ≥ 0.50 and therefore measured ASE in an adequate way. The four components resulting from the analysis were included in the regression model as proximal factors.

Characteristics of the participants and nonparticipants are described in Table 2 . Even if the mean differences between the two groups of patients were all in the expected direction, this difference was significant for some of the characteristics only as indicated with significance levels in Table 2.


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  		Table 2. Characteristics of Participants and Nonparticipants*

 
The Pearson correlations between the significant group means differences were investigated to decide on the distal factors to include in the model (Table 3 ). Because AQLQ scores correlated with two other factors, we decided to exclude AQLQ results from the model to avoid multicollinearity in the regression analysis, whereas we kept education level in the analysis because previous research had repeatedly demonstrated its importance.57 Because of the low correlation between PEF scores and previous hospitalizations, both factors were included resulting in a final regression model (Fig 1, bottom, b) with the four components from Table 1, education level, PEF scores, previous hospitalizations, and ASC scores (Table 2).


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  		Table 3. Pearson Correlations Between Demographic, Clinical, and Questionnaire Data

 
Determinants of Intending To Participate in Our Asthma Program: Logistic Regression Analysis
We performed two logistic regression analyses. The first analysis examined the predictive power of the distal factors on intending to participate in the asthma program. The second analysis examined the predictive power of the distal and proximal factors together on the patients’ intention. This last analysis was performed to evaluate the relative importance of the distal factors when proximal factors were added to the model. Results are shown in Table 4 .


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  		Table 4. Predictors of Intending To Participate in the Asthma Program

 
Education level was a significant predictor of the intention to participate. Higher educated asthmatic patients were more likely to participate in the self-management program than lower educated asthmatic patients. Neither previous hospitalizations due to an asthma exacerbation or PEF scores had a predictive value for the intention to participate. The ASC score was a significant predictor of the intention to participate. This means that patients who experienced more intense symptoms the 2 weeks before recruitment were more likely to express the intention to participate. When social cognitive variables were added to the model, they carried the weight of the prediction and ASC lost its significant predictive value. Significant predictors of intention behavior were education level, perceiving personal benefits, self-efficacy and social influence. Perceiving more personal benefits in participation in the program (having a more positive attitude), having fewer barriers to participate (having higher self-efficacy expectations), and experiencing more social influence for better self-care made a patient more likely to intent to participate in our program. Believing in the general benefits of the program had no predictive value for the intention to participate.


   Discussion
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
Appendix
 References
 
We studied determinants of the intention to participate in an asthma self-management program using the ASE model. Overall, the results of our analysis showed that the ASE model is useful to understand determinants of participation. Including ASE on top of educational status and clinical variables raised the percentage of explained variance in participation behavior from 23 to 72%.

Our results showed that higher-educated asthmatic patients were twice more likely to participate in the program than patients with fewer years of education. This has repeatedly been found in previous research,7 although the exact reasons for this effect remain unclear. Most likely, differences in knowledge about asthma rather than attitudinal variables account for this effect, because the odds ratio (OR) of education level as predictor in the first logistic regression analysis did not alter by adding the ASE variables in the second logistic regression analysis. We further on hypothesize that higher educated people can express themselves more easily than lower-educated people and therefore would be more confident in participating in talking sessions.

Interestingly, neither previous hospitalizations nor PEF scores seemed to have predictive value for the intention to participate in an education program, meaning that the clinical status did not seem to convince patients to participate. This finding may parallel Yoon and colleagues5 observation of a very low participation rate in a group of asthmatic inpatients recovering from a severe asthma exacerbation. The fear, often experienced after an exacerbation, apparently may not last long enough to keep on motivating the patient for an educational program. Some might be surprised to notice that PEF scores had no predictive value for the intention to participate. Indeed, asthma specialists are often tempted to convince patients with more severe asthma to participate in an education program by referring to their poor PEF values. However, objective pulmonary function severity results did not determine participation behavior. The one clinical characteristic with some predictive value was the asthma symptom score: patients having had more intense subjective asthma symptoms 2 weeks before recruitment had more chance to participate in our education program. However, the predictive value of this symptom score seemed to be mediated by social cognitive variables because the initial significant OR in the first regression analysis dropped below conventional significance levels in the second regression analysis.15 This suggests that more symptomatic patients perceive more personal benefits of the program, have higher self-efficacy expectations or experience more social pressure for better self-care and, as a consequence, are more likely to participate.

Patients’ beliefs about the program appeared of paramount importance. Patients having less structural barriers to participate (such as no time, living too far away, financial barriers or program characteristic barriers—in this case the group format) were 12 times more likely to participate in the program. Perceived personal benefits increased the chance that patients intended to participate by seven to eight times, whereas believing in the general benefits of the program had no predictive value. Finally, our results showed that patients experiencing higher social pressure to take better care of their asthma had approximately three times more chance to intent to participate.

A few limitations may be mentioned here. First, the participation rate in our study might have been influenced by the fact that our study was also an evaluation study. Having to perform effectiveness measures may have dissuaded patients to participate. Second, employment status and flexibility issues in this respect were not included as a measure in this study as we did not realize its importance a priori. Patients’ reactions to the invitation to participate suggested that current employment and the difficulty to leave the job for medical reasons may be an important structural variable. A more in-depth analysis of the social context of the patient may be important in future studies. Finally, the factor analysis of the interview questions resulted in a self-efficacy scale including mostly external barriers. These barriers seemed of predictive importance for the intention to participate in the program. From a theoretical point of view, it might be worth it to explore the role of more intrinsic barriers and the confidence patients have to overcome them.16

In order to get more patients involved in asthma education programs, it is essential to develop better recruitment strategies. The present results show that motivation induction to participate in a program should rather focus on patients’ beliefs and attitudes toward the program than on patients’ clinical status. Future studies are needed to investigate the relative importance of the different patients’ beliefs. We conclude that recruitment of patients with asthma for an educational program should emphasize personal benefits of the program, should include patients’ social network, and should consider the impact of structural barriers on participation behavior.


   Appendix
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Appendix
References
 
Structured Interview

  1. The asthma program would be useful to me.
  2. I would participate in the program out of curiosity.
  3. I do not think I have time to participate.
  4. I live too far away from the hospital to participate in the program.
  5. I would like to participate in the program to be more involved with my asthma treatment.
  6. I would not want to participate in the program because I have too little asthma complaints.
  7. I would like to participate in the program to learn more about my asthma.
  8. I think participating would be too expensive.
  9. I think I would only want to participate in program day sessions.
  10. I think I would only want to participate in program evening sessions.
  11. I would like to participate in the program to obtain a reduction of my asthma complaints.
  12. The fact that the program consists of some group sessions impedes me to participate.
  13. I believe that the program influences the asthma control of the participants.
  14. I believe that patients get more involved with their asthma treatment when participating in the asthma education program.
  15. I think that patients learn more about their asthma when participating in the asthma program.
  16. I think that asthma complaints decrease in patients participating in the asthma education program offered.
  17. Social influence
  1. Does your partner think you should take better care of your asthma? (yes/no)
    1. Do you agree with him/her? (yes/no)
  2. Do your children think you should take better care of your asthma? (yes/no)
    1. Do you agree with them? (yes/no)
  3. Do your parents think you should take better care of your asthma? (yes/no)
    1. Do you agree with them? (yes/no)
  4. Does your best friend think you should take better care of your asthma? (yes/no)
    1. Do you agree with him/her? (yes/no)
  5. Do other important persons think you should take better care of your asthma? (yes/no)
    1. Do you agree with them? (yes/no).


   Footnotes
 
Abbreviations: AQLQ = Asthma Quality of Life Questionnaire; ASC = Asthma Symptom Checklist; ASE = attitude, social influence, and self-efficacy; KASE-AQ = Knowledge, Attitude and Self-Efficacy Asthma Questionnaire; OR = odds ratio; PANAS = Positive Affect and Negative Affect Schedule; PEF = peak expiratory flow

This study was performed at the University Clinic Gasthuisberg, Department of Respiratory Diseases, Leuven, Belgium, and was sponsored by Astra Zeneca, Belgium.

Received for publication October 26, 2004. Accepted for publication May 20, 2005.


   References
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Appendix
 References
 

  1. Gibson, PG, Powell, H, Coughlan, J, et al (2003) Self-management education and regular practitioner review for adults with asthma. Cochrane Database Syst Rev 1,CD001117
  2. Sudre, P, Jacquemet, S, Uldry, C, et al Objectives, methods and content of patient education programmes for adults with asthma: systematic review of studies published between 1979 and 1998. Thorax 1999;54,681-687[Abstract/Free Full Text]
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  4. Graziani, C, Rosenthal, MP, Diamond, JJ Diabetes education program use and patient-perceived barriers to attendance. Fam Med 1999;31,358-363[Medline]
  5. Yoon, R, McKenzie, DK, Miles, DA, et al Characteristics of attenders and non-attenders at an asthma education programme. Thorax 1991;46,886-890[Abstract]
  6. Abdulwadud, O, Abramson, M, Forbes, A, et al Attendance at an asthma educational intervention: characteristics of participants and non-participants. Respir Med 1997;91,524-529[CrossRef][ISI][Medline]
  7. Muntner, P, Sudre, P, Uldry, C, et al Predictors of participation and attendance in a new asthma patient self-management education program. Chest 2001;120,778-784[Abstract/Free Full Text]
  8. De Vries, H, Dijkstra, M, Kuhlman, P Self-efficacy: the third factor besides attitude and subjective norm as predictor of behavioral intentions. Health Educ Res 1988;3,273-282[Abstract/Free Full Text]
  9. Global strategy for Asthma Management and Prevention. April 2002 National Institutes of Health. National Heart, Lung and Blood Institute. Bethesda, MD: publication No. 02–3659
  10. Juniper, EF, Guyatt, GH, Epstein, RS, et al Evaluation of impairment of health-related quality of life in asthma: development of a questionnaire for use in clinical trials. Thorax 1992;47,76-83[Abstract]
  11. Kinsman, RA, Luparello, T, O’Banion, K, et al Multidimensional analysis of the subjective symptomatology of asthma. Psychosom Med 1973;35,250-267[Abstract/Free Full Text]
  12. Ritz, T, Bobb, C, Edwards, M, et al The structure of symptom report in asthma: a reevaluation. J Psychosom Res 2001;51,639-645[CrossRef][ISI][Medline]
  13. Wigal, JK, Stout, C, Brandon, M, et al The knowledge, attitude and self-efficacy asthma questionnaire. Chest 1993;104,1144-1148[Abstract/Free Full Text]
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