The mean age (SD) of the GPs was 42.8 years (7.7), 65.9% were men. 46.9 % of the GPs worked single-handed. GPs were predominantly rewarded by fee for service; 24.9% had more than 120 patient encounters per week.
Considering the determinants in decision making
Assessing to what extent GPs consider the determinants for antibiotic prescribing in decision making (Q1), on average GPs considered all 42 items. Factor analysis suggests groups of variables whose values are similar, in this case GPs' responses to Q1 items. Factor analysis of all items from Q1 yielded three factors, i.e. groups of items which GPs considered similarly, explaining 33 % of the variance (Fig. 1). Factor 1 included all the items relating to the lung auscultation. Factor 2 included only items relating to non-medical reasons, either patient or physician related. Factor 3 included items determining whether or not there is something unusual happening. Each factor grouping had good internal consistency, with Cronbach α equal to .90 for factor 1, .86 for factor 2 and .87 for factor 3.
The median (interquartile range) scores as defined by factor analysis were 5.0 (from 5.0 to 5.0) for factor 1, lung auscultation, 3.0 (form 2.8 to 4.0) for factor 2, non-medical reasons, and 4.0 (from 4.0 to 5.0) for factor 3, unusual or not.
Using Wilcoxon Matched Pairs test to compare the scores of the factors – scores of factor 1 did not approximate a normal distribution – the differences between all three factors are significant at P < 0.001 (Fig. 2). Since the differences between the scores approximate a normal distribution, this test is almost as powerful as the t-test.
Of course, GPs also considered items from Q1 not presented in figure 1 (factor loading ≤ .40 to the yielded three factors); always (median = 5) whether the patient has fever, is coughing up sputum and whether the sputum is coloured, whether the patient is looking ill and whether he/she has a medical history of COPD or smoking; often (median = 4) whether the coughing is frequent or started suddenly and whether the patient consults for the first time with this complaint, is saying he/she is feeling ill, is older than 60 years of age, tried self-management first, is known to you or has a red throat, as well as whether there is an RTI epidemic and whether the patient rapidly consults and will reconsult if not better; sometimes (median = 3) whether the patient is compliant, or is recovering slowly even under antibiotic treatment; seldom (median = 2) whether the patient is visited at home or that you make the patient reconsult anyway after 3 to 4 days. For most items the interquartile range was 1.
In favour or against antibiotics
Assessing how strongly the determinants for antibiotic prescribing support or counter antibiotic treatment (Q2), none of the 63 items is strongly in favour or against antibiotic treatment. Factor analysis of all items from Q2 yielded two factors, i.e. groups of items which according to the GPs support antibiotic treatment similarly. The factors included items expressing a need for antibiotic treatment, and no need for antibiotic treatment respectively. This confirmed our construction of Q2.
In favour
Factor analysis of all 37 items that support antibiotic treatment according to their mean and sumscore, yielded two factors, i.e. groups of items which according to the GPs are equally in favour of antibiotic treatment, explaining 24% of the variance (Fig. 3). Factor 1 only included items relating to medical reasons, either from the lung auscultation or determining whether or not there is something unusual happening, factor 2 only included items relating to non-medical reasons, either patient or physician related. Each factor grouping had good internal consistency, with Cronbach α equal to .82 for factor 1, .83 for factor 2.
The median (interquartile range) scores as defined by factor analysis were 1.0 (from 0.5 to 1.0) for factor 1, medical reasons and 0.0 (from 0.0 to 1.0) for factor 2, non-medical reasons. Using Wilcoxon Matched Pairs test the scores of the two factors differed significantly at P < 0.001 (Fig. 4).
Against
Factor analysis of all 26 items that fail to support antibiotic treatment according to their mean and sumscore, yielded only one factor, i.e. group of items which according to the GPs are equally against antibiotic treatment, explaining 17% of the variance (Fig. 5). The factor only included items expressing no need for antibiotic treatment, either medical or non-medical. Factor grouping had good internal consistency, with Cronbach α equal to .80.
The median (interquartile range) score as defined by factor analysis was -1.0 (from -1.0 to -0.5). Using Wilcoxon Matched Pairs test the score of this factors differed significantly at P < 0.001 form the scores of the two factors in favour of antibiotics (Fig. 4).
Items from Q2 not presented in figure 3, and figure 5 respectively (factor loading ≤ .40 to the yielded three factors) support or counter antibiotic treatment as well. In favour (median = 1) are crepitations at lung auscultation, medical history of COPD, onset of new complaints in a viral syndrome, consulting for the second time, dyspnoea, tachypnoea, localised thoracic pain, painful teeth or sinuses, coloured sputum, haemoptysis, reduced vesicular breathing, red throat with exudate on the tonsils, the patient being older than 60 years of age and not consulting rapidly. Neutral (median = 0) are smoking, home visit, frequent coughing, no swollen cervical lymph nodes, no localised thoracic pain, medication demand, as well as an RTI epidemic, a dry cough, a red throat without exudate on the tonsils, the patient is known to you, that you make the patient reconsult anyway after 3 to 4 days, that without antibiotic treatment the patient will already reconsult within two days, if not better and bad compliance with antibiotics. Against (median = -1) are consulting rapidly, influenza-like symptoms, no worsening after two days and not wanting antibiotic treatment. For most items the interquartile range was 1.
No relation between the response groups characteristics and the scores as defined by factor analyses of Q1 and Q2 was found to be relevant and significant.