Pettersson et al. (1999) carried out an evaluation of a nurse-run asthma school, an educational activity for asthma patients. This exercise uses extracts from their paper.
The exercise is more wide-ranging than earlier Applied Biostatistics exercises, attempting to interpret statistics in the general research context.
Pettersson et al. (1999) asked whether attending the asthma school led to improved knowledge of the disease, to improved self-medication and self-management and to improved self-rated functional status.
The patients were recruited consecutively over one year among all patients (n=60) who agreed to participate in the Asthma School. Fifty-two of these patients (87%) initially agreed to participate in the study. However, 19 patients were excluded for the following reasons: they attended the Asthma School for less than three sessions (n = 14), they were admitted to Åre Hospital, a special asthma-care clinic (n = 2), they did not answer the questionnaires after completed education (n = 2) or they stopped using asthma drugs (n = 1). One patient died during the study period, owing to a malignancy. Finally, 32 patients (6 males, 26 females, mean age 43, range 18-67 years) remained for the evaluation. The duration of asthma ranged from 9 months to 54 (median 6) years.
The Asthma School included education on the anatomy and physiology of the lungs, the pathophysiology and the pharmacological treatment of asthma, breathing technique, exercise and training suitable for asthmatics and the psychosocial aspects of asthma. All participants were also lent a PEF-meter and instructed how to use it. They were told to register their peak flow values twice daily. This was done in order to enable the patients to understand better the variability of the disease, to let them self-adjust their daily treatment with inhaled steroids and thereby showing them the benefits of using a PEF-meter every day.
Two study-specific questionnaires were developed for this study. The first questionnaire consisted of 24 items concerning demographic data, the use of asthma drugs and the PEF-meter, smoking habits, need for medical care and sick-leave. The second questionnaire consisted of 26 items. Eight items concerned knowledge of the disease and included questions on physiology and pathophysiology. Another eight items concerned knowledge of asthma medication and included questions on bronchodilators and anti-inflammatory drugs, their different mechanisms and when to use them, questions on the side-effects of different drugs, and prophylactic medication. Ten items included questions on asthma-triggering factors, self-monitoring of the disease, breathing techniques and physical exercise. The maximum score for the questionnaire was 28.
The Sickness Impact Profile (SIP) is a behaviorally based measure of health-related limitations in the daily lives of both chronically and acutely diseased subjects. It is self-administered and consists of 136 items that can be grouped into 12 multi-item subscales: ambulation, body care and movement, mobility, emotional behavior, social interaction, alertness behavior, communication, sleep and rest, household management, work, recreation and pastimes and food intake. A percentage score (0-100) can be calculated for each of the 12 subscales. The subscales ambulation, body care and movement, and mobility are aggregated to form a physical index and the subscales emotional behavior, social interaction, alertness behavior and communication are aggregated to form a psychosocial index. Moreover, it is also possible to calculate the total SIP score. The higher the scores, the poorer the patients’ perceived, health-related, functional status.
A monthly diary card with 11 questions was used during the year following the Asthma School. The items concerned the patients’ medication, absence from work due to asthma, hospital care and visits to the emergency room.
The forced expiratory volume in one second, FEV1, was measured by spirometry on two occasions, immediately prior to the Asthma School and one year later.
Statistical significance over time were tested by the Sign Test.
Before attending the Asthma School, the mean score for the 26 items concerning knowledge of the disease, asthma medication, asthma-triggering factors, self-monitoring of the disease, breathing techniques and physical exercise was 15 (range 4-24) out of a possible 28. One year later, the mean total score had increased to 20 (range 14-26) (p < 0.001). No statistical differences as regarded gender, age or educational level were seen.
Before the Asthma School six patients (19%) were current smokers, 12 patients (37%) were ex-smokers and 14 patients (44%) had never smoked. One year later, three patients (9%) were current smokers and consequently 29 patients (91 %) were ex-smokers (n.s.).
All 32 patients were treated with inhaled bronchodilators on a daily basis both before and during the year after the intervention. Before the education, 14 patients (44%) used this type of treatment on an as-required basis. One year later, 20 patients (63%) used inhaled bronchodilators on an as-required basis (p < 0.05).
The SIP scores are shown in the following table:
|Before Asthma School||12 months after Asthma School||Sign test|
|Sleep and rest||9.7||9.2||9.8||0.0-35.9||7.6||8.5||9.8||0.0-33.7||n.s.|
|Recreation and pastimes||9.9||11.0||8.5||0.0-39.6||7.7||11.3||0.0||0.0-42.4||n.s.|
One year after the completion of the Asthma School program, the patients rated their physical capacity as improved (p < 0.01). There were no significant statistical changes for the rest of the SIP scales (Table 2).
Check suggested answer 1.
2. In 'Smoking habits', what is meant by ‘n.s.’? What can we conclude from this?
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3. What limitations does the lack of a control group lead to?
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4. What bias, if any, might there be in the patients’ response concerning the use of a PEF-meter?
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5. What bias, if any, might there be in the FEV1 measurement?
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6. From the table of overall Sickness Impact Profile, what can we conclude about the shape of the distribution of the overall Sickness Impact Profile? What three features of the data support this?
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7. In the SIP table, what is the mode for the score in the ambulation dimension?
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8. In the SIP table, why should we be cautious in interpreting the significant change in the physical dimension?
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