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Rapid Responses: Rapid Responses published:
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Contradictory reports of urban/rural differences
- Martin Bland (24 March 2000)
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Sex and age discrimination in GP recruitment is not justified by teenage pregnancy survey
- Wai-Ching Leung (25 March 2000)
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The importance of patients' opinions
- Andrew Thornett (27 March 2000)
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Causality or Inference?
- Peter Morrell (29 March 2000)
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Record linkage analysis could have been used
- Babatunde A Gbolade (2 May 2000)
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association betwen teenage pregnancy
- Farokh Abazari (30 July 2000)
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Martin Bland, Prof. of Medical Statistics St. George's Hospital Medical School
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In this paper, the authors say that `We found no evidence to support the introduction of more family planning clinics in rural areas since such practices already have lower teenage pregnancy rates'. In Table 2, they quote the incidence rate ratio for urban practice v rural practice as 0.73. Thus they report that the rate of teenage pregnancy in urban areas is only three quarters of that in rural areas. The other ratios in Table 2, e.g. that for at least one female doctor v no female doctor, 0.84, are clearly interpreted in this way. Is there some mistake here? The subjects are described as `all pregnancies of teenagers aged 13 to 19 . . .'. As they calculate rates based on all teenagers registered with the practice, the subjects are all teenagers, not just the pregnant ones. This might seem nit-picking, but we should try to get these things right. The actual incidence rate ratios reported are close to one and so although these factors may have a relationship to teenage pregnancy, it would not appear to be an important one. We should concentrate on the estimate, not the P value. The authors say that `Practices with a female or young doctor had significantly lower teenage pregnancy rates than those without such doctors. General practices, pilots for primary care medical services, and primary care groups with high teenage pregnancy rates can consider using this information when recruiting medical and nursing staff in primary care'. Are they really advocating sex and age discrimination in employment? I hope not! |
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Wai-Ching Leung, Senior Registrar in Public Health Medicine Epidemiology & Public Health, Newcastle General Hospital, NE4 6BE
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In the "key messages" box of their article, Hippisley-Cox et al (1) concluded that general practices with a female and young doctors had significantly lower teenage pregnancy rates and advised those responsible for recruiting staff in primary care to take these conclusions into account. Their arguments are flawed. There are several methodological problems. First, the authors did not take into account the doctors' inclusion in the "family planning list", their possession of family planning certificates and the DRCOG qualifications. Female and young doctors may be more likely to have undergone family planning training and obtained these qualifications. These are key confounding factors as the doctors' skills in providing contraception were under study. Whether the practice ran a "shared list" system in allocating patients to doctors is also important. Second, whereas teenage conceptions are defined as those from girls aged 13 - 15 in the Health of the Nation targets (2) and in other studies, the authors included all pregnancies from girls aged 19 or under. Third, as a large proportion of "teenage pregnancies" in this study were from girls aged 17 - 19 who were likely to be in further or higher education during term time, terminations of pregnancies may have been performed outside Trent region. Fourth, the incidence rate ratio for the presence of female doctors was adjusted from 0.84 to 0.94 after taking into account Townsend score and practice characteristics. However, as good general education is the most important factor associated with deferring pregnancy (3), Townsend score alone is unlikely to have fully corrected for this factor. Finally, the authors properly acknowledged that causation could not be concluded from a cross-sectional survey Even if the conclusions were valid, the clinical significance for individual practices is minimal. For a 5-partner practice with 10,000 patients, there may be approximately 250 girls aged 13 - 15. Taking the highest teenage conception rate in UK as 16 per 1000 (2), one may expect to see 4 teenage pregnancies in a year. Even if it were true that practices with both a female and a young doctor had 75% of the teenage pregnancy rate, one would only expect one teenage pregnancy to be avoided a year. These results fall far short of the stringent statutory requirements (4) to argue that sex is a genuine occupational qualification to justify sex discrimination. References 1 Hippisley-Cox J, Allen J, Pringle M, Ebdon D, McPhearson M, Churchill D, Bradley S. Association between teenage pregnancy rates and the age and sex of general practitioners: cross sectional survey in Trent 1994-7. BMJ 2000; 320: 842-845. 2 Adler M. Sexual health - health of the nation failure. BMJ 1997; 314: 1743-1748. 3 NHS Centre for Reviews and Dissemination. Effective Health Care. Preventing and reducing the adverse effects of unintended teenage pregnancies, vol. 3. York: University of York, 1997:1-11. 4 Sexual Discrimination Act 1975 section 6(1) |
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Andrew Thornett, Clinical Research Fellow and General Practitioner Department of Psychiatry, University of Southampton, SO14 0YG
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The article by Hippisley-Cox et al in this week's journal has important implications for the organisation of general practice1. General practices with female doctors, young doctors, or more nurse time had lower teenage pregnancy rates. This finding may reflect greater skill in young female doctors or nurses at dealing with this group of patients. However, it is more likely that these professionals are perceived by this client group to be more in touch with their generation and lifestyle. This has led to an increased preparedness to follow advice and a decrease in pregnancy rates. For too long, patients' views have not been given sufficient prominence. As early as 1996 Which? magazine advised patients to shop around and meet local general practitioners prior to registering in a new practice (Sept. 1996), and the Department of Health has encouraged surveys of patient opinions by both health authorities and general practitioners2; and is keen the findings should be considered when decisions about local services are made. Patients value being able to "talk to the doctor", whilst "who chooses your treatment" is less important3. Although patients prefer more information to less, only females and those with extensive education prefer to choose the treatment themselves. Higher levels of patient satisfaction are associated with increasing age in women4 and with agreement between GPs and patients concerning urgency and number of problems5, but satisfaction is unrelated to frequent attendance6. Lower levels are seen with increased waiting room time4. Baker looked at practice characteristics associated with satisfaction using the Consultation Satisfaction Questionnaire7. He found that falls in satisfaction were associated with increasing total list size, the absence of a personal list system, being a training practice, increasing numbers of patients booked per hour, and increasing age of general practitioner8. All general practitioners value high quality care. With the introduction of new technologies in modern primary care, and the current emphasis on evidence-based practice, patients' views should always remain one of the priority criteria used to evaluate the care we give. Reference List 1. Hippisley-Cox J, Allen J, Pringle M, Ebdon D, McPhearson M, Churchill D et al. Association between teenage pregnancy rates and the age and sex of general practitioners: cross sectional survey in Trent 1994-7. BMJ 2000;320:842-5. 2. Department of Health. Medical audit in the family practitioner services. HC(FP)(90)8. 1990. London, Department of Health. 3. Vick S,.Scott A. Agency in health care. Examining patients' preferences for attributes of the doctor-patient relationship. J Health Economics 1998;17:587-605. 4. Young AF, Byles JE, Dobson AJ. Women's satisfaction with general practice consultations. Med J Aust 1998;168:386-9. 5. Ringmann C, Kragstrup J., Stovring H., Rasmussen N.K. How well do patient and general practitioner agree about the content of consultations? Scand J Prim Health Care 1999;17:149-52. 6. Heywood P.L., Blackie G.C., Cameron I.H., Dowell A.C. An assessment of the attributes of frequent attenders to general practice. Fam Pract 1998;15:198-204. 7. Eli Lilly National Clinical Audit Centre Dialogue Service. Consultation Satisfaction Questionnaire. Department of General Practice and Primary Health Care, Leicester University, Leicester General Hospital, Gwendolen Road, Leicester, LE5 4PW, 1996. 8. Baker R. Characteristics of practices, general practitioners and patients related to levels of patients' satisfaction with consultations. BJGP 1996;46:601-5. |
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Peter Morrell, Hon Research Associate, History of Medicine Staffordshire University, UK
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Many errors of scientific method seem to be reflected in this article, not to say some glaring errors about the distinctions between inference and causality. “General practices with female doctors, young doctors, or more nurse time had lower teenage pregnancy rates. The findings may have implications for the mix of health professionals within primary care.” This quote implies that a causal link is going to be drawn between the gender and age of the GP, and the nurse time available, and the number of teenage pregnancies within that medical practice. On what basis is this link being made? Many things can be statistically correlated, which have absolutely no causal association in reality. One thinks of predictions about sunspots and economic cycles. Though such links can be demonstrated as strongly correlating, yet no causal link in reality is to be found, i.e. sunspots do not act as the cause of economic activity, even though that is an observed pattern of correlation. Events occurring together often seem to our mind to be causally linked. A link is suggested, assumed maybe, but not proven. There may be a third underlying cause for both, or it might just be coincidence. Many further observations are required before any single observation [= ‘subjective belief’] can be elevated into a more meaningful status. Even then, it might be coincidental. If we observe two people walking down the street at the same time every day always together, does that mean the one walking is the cause of the other walking? No, it does not. It is an assumption that we have projected onto the observation. We make such assumptions all the time, but they are not proven. Similarly, in former times, the ‘spontaneous generation’ of rats, lice and insects in rotting material, was inferred, from faulty and uncritical observations, and the absence of knowledge of their spores, eggs, larvae, etc. It was derived from unbridled inferences founded upon incomplete observations [see Porter, pp.429-30; Mason, p.293, p.341; Shryock, pp.268-9]. Our minds tend to run after such inferences, and to draw these imperfect conclusions, but that is bad science and as a tendency it should be resisted. Well, they might be good sources of ideas, but can generate strong expectations, making our perception far from neutral and giving rise to shoddy thinking. “High conception rates are associated with having a teenage mother, having divorced parents, poor education, and deprivation. Health professionals may reduce the harmful effects of deprivation and poor education on risk of teenage pregnancy by improving access to effective health education and contraceptive services.” Again, ‘associated’ in this paragraph suggests ‘is caused by’ and hence the directive that ‘health professionals may reduce the harmful effects of deprivation…’ This is an assumption, not a conclusion made from the data. The assumption being made is that the one is the cause of the other. On what basis? It is not known, it is inferred. “We aimed to determine general practice characteristics associated with variations in teenage pregnancy rates. In particular, we investigated the effect of the sex and age of the doctor and the availability of a practice nurse.” The phrase ‘associated with’ then becomes ‘the effect of the sex and age of the doctor and the availability of the nurse’. Effect on what? On teenage pregnancies. Again, we must ask on what basis does this argument rest? In fact, it is a castle built in the air. It is founded upon the contention that a causal link has been found from this research. No such causal link has been found from this research. All that has been found is a correlation. The rest is conjecture and assumption, projected onto the data and which might prove to be unfounded. “Practices with a female doctor, a young doctor, or more practice nurse time had significantly lower teenage pregnancy rates after adjustment for other factors. For example, practices with a female doctor had 91% of the teenage pregnancy rate found in other practices; practices with a doctor under 36 years had 84% of the rate; practices with both a female doctor and one under 36 years had 75% of the teenage pregnancy rate.” Again, a causal link is being imputed to exist between the patterns revealed and those factors in the practice, which have been earmarked by the researchers. Why all the pussyfooting around? They might just as well come right out with it and say: ‘teenage pregnancies are CAUSED by older and male doctors, and by less nurse time’. Would that be a fair conclusion to make? Is this good science or bad science? “A causal relation, however, cannot be inferred from a statistical association, particularly in a cross sectional study.” But we are going to draw them anyway! “General practices with a female partner have lower teenage pregnancy rates than those without a female partner. As our study was cross sectional, we do not know whether female doctors had chosen to work in areas with low teenage pregnancy rates or whether the presence of a female doctor influenced such rates.” This is a supremely illogical paragraph. Do doctors choose to work in areas with low teenage pregnancies? Is this being realistically presented as a factor they take into account when CHOOSING a practice? I thought that doctors more or less ended up where they ended up and had only limited choice over where they happen to find a post. If this is so, then the above statement is not only a good example of unbridled and inaccurate speculation, but also of that wonderful old adage: “lies, damned lies and statistics”. What is being said may or may not be true, but it has not been proved by this research “The association between low teenage pregnancy rate and the presence of a female doctor may be because female doctors tend to have longer consultations and handle more problems per consultation and tend to be more communicative and more patient centred. Female doctors report less difficulty in discussing sexual problems with teenagers and are more likely to provide information about the prevention of sexually transmitted diseases and the use of condoms. Our findings might be due to differences in case mix between practices with and without a female doctor since patients presenting to female doctors tend to be younger, more often female, have female specific problems than those presenting to practices without a female doctor.” They say they are not going to causally link these things and then do precisely that. Why say ‘our findings might be due’? Due means cause. This paragraph reads like a blatant attempt to explain the events shown in the data. Which is what they claim [earlier on] not to be trying to link causally. Which way do they want to play it? “Practices with a young doctor have lower teenage pregnancy rates than those without a young doctor. Although younger doctors may be more interested in teenage health issues, little is known about the effect of the age of the doctor on provision of teenage contraceptive services.” ‘The effect’ is another causal term. This is another blatant attempt to ascribe causality to the data. Why say they are not going to ascribe cause and then go and do exactly that? “Practices with more practice nurse time had significantly lower teenage pregnancy rates than those with less practice nurse time. Since 10% of all practice nurse consultations are with teenagers and up to 3% of all nurse consultations are for contraceptive advice, there may be scope for further developing the practice nurse's role in the delivery of contraceptive services to teenagers. We are unable to explain the association between fundholding and higher teenage pregnancy rates.” They show how the ‘role of the nurse’ might impinge upon teenage pregnancies. Again, a causal relationship [‘explain the association’] is being summoned. If we call ‘low teenage pregnancies’ ‘B’, then we can identify in this article several factors, which are alleged to be causes of B. These are as follows: A = nurse time C = female doctors D = young doctors Thus, a deduction being made is that B is a product of A and C and D. Likewise, they assert that the following are causes of high teenage pregnancies [H]: E = less nurse time F = male doctors G = older doctors They make these assertions because they have been statistically correlated. Yet, common-sense might suggest that these 'causal links' seem nebulous at best. Thus, the attempts to explain the patterns in the data appear feeble, unconvincing, fundamentally flawed and probably futile. Much deeper and more critical thinking should have been engaged in before it was decided that these ‘deductions’ were proven by this research and worthy of publication. Surely, the authors of reports of this kind owe the public a duty of much greater care in the somewhat dubious deductions they are placing into the public domain about such an emotive subject? Ideas can be very easily misinterpreted. It would seem that some help with scientific method relating to causation and inference might not have gone amiss. This type of research might even be seen as bringing medicine into disrepute, by appearing shoddy, unrigorous and unscientific. Much glitters that is not gold; genuine scientific truths are not so easily won. Like the ‘spontaneously generated’ organisms of old, the assertions made by this article seem to stand as a testimony to over-inference from insufficient observations, very uncritically evaluated. And would on those grounds be castigated as ‘bad science’. This might seem somewhat off-topic, and I was preparing this quote for something else, but it seems highly relevant: 'Kant was saying that…the immediate objects of perception depend not only upon our sensations but also on our perceptual equipment which orders and structures those sensations into intelligible unities…some of the properties we observe in objects are due to the nature of the observer rather than the objects themselves. There are basic concepts [or categories] like cause and effect, which are not learnt from experience but constitute our basic conceptual apparatus for making sense of experience and the world.' [Chamber's, p.807] I think that is fair comment on this article. Peter Morrell References Chamber's Biographical Dictionary, 1996 Mason, S F, 1953, A History of the Sciences, RKP, London Porter, Roy, 1998, The Greatest Benefit to Mankind, A Medical History of Humanity, Norton, New York & London Shryock, Richard H, 1936, The Development of Modern Medicine, Univ. Pennsylvania Press, USA |
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Babatunde A Gbolade, Consultant Gynaecologist & Director of Fertility Control Unit St James's University Hospital Leeds
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Editor, In discussing methodological issues of their study, Hippisley-Cox et al. lament their inability to identify teenagers with repeat pregnancies and by inference, repeat abortions in the study period.1 They used the admissions database of Trent regional hospital, which "contains all details of hospital admissions for residents in Trent whether treatment was provided in Trent or not". Does this database contain the NHS number, the only unique identification number that is almost universally held among the population of England and Wales?2 If so, record linkage analysis could have been used to identify repeat pregnancies and by inference repeat abortions, more so since they compared their data with that of the Office for National Statistics of which the National Health Service Central Register (NHSCR) is a part. The goal of record linkage is to link quickly and accurately records corresponding to the same person or entity. A record linkage system exists in England with the most recent development of matching general practice records with hospital and vital records to prepare a file for analysing referral, prescribing and outcome measures.3 This study also highlights a deficiency in the legal abortion data collection system in England and Wales. The abortion statistics data is compiled from the completed abortion notification forms (form HSA4, revised 1991), which does not contain a requirement for a unique personal identification number such as the NHS number. A quick check of abortion referral letters to our unit showed that virtually all contained the patients' NHS number. Although form HSA4 contains a section for the number of previous legal abortions experienced by each woman, the accuracy of the data is dependent on the extent of truthful disclosure by women of their past experience of induced abortion and on accurate reporting by the abortion service providers. The information may not be easily verifiable from hospital case notes if she has attended different hospitals. Record linkage analysis has shown underreporting of experience of induced abortion when the study methodology depends on self-reporting.4 A mandatory requirement for the NHS number on Form HSA4 would enable identification of repeat abortions for individual women through record linkage analysis, thus facilitating accurate calculation of local, regional and national incidence and prevalence rates for repeat abortion. At the present time, there are no published UK regional or national rates. If this requirement were in place, the shortfall of 21.7% of terminations of pregnancy in their study, attributed to the private and charity sectors would have been identified and their dataset would have been more complete and the strength of their study increased. Lastly, their statement that "there is less chance of multiple pregnancies occurring to an individual within the same year" is not in keeping with reality, as those dealing with these patients on a daily basis can readily verify. The distribution of repeat abortion in a population is important for service planning and in order to discover the distribution of induced abortions, one must determine the incidence of repeat abortion. This is where record linkage analysis comes into its own although it may not be perfect.5 References 1 Hippisley-Cox J, Allen J, Pringle M, Ebdon D, McPherson M, Churchill D, Bradley S. Association between teenage pregnancy rates and the age and sex of general practitioners: cross sectional survey in Trent 1994-97. BMJ 2000; 320:842-845. 2 Hattersley L. Record linkage of census and routinely collected vital events data in the ONS longitudinal study. In record Linkage Techniques--1997: Proceedings of an International Workshop and Exposition (Alvey, W. and Jamerson, B. eds). National Academy Press, 1999:57-66 3 Gill LE. OX-LINK: The Oxford medical record linkage system. In record Linkage Techniques--1997: Proceedings of an International Workshop and Exposition (Alvey, W. and Jamerson, B. eds). National Academy Press, 1999:15-33 4 Udry JR, Gaughan, M, Schwingl PM and van den Berg BJ. A medical record linkage analysis of abortion underreporting. Family Planning Perspectives, 1996;28:228-231. 5 Somers RL. Repeat abortion in Denmark: An analysis based on national record linkage. Studies in Family Planning, 1977;8:142-147. |
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Farokh Abazari medical university
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Dwar sirs please send me an guestionnare about your investigation respectfully yours , farokh abazari |
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