The Randomised Controlled Trial design ... - Wiley Online Library

The Randomised Controlled Trial design: unrecognized opportunities for health sciences librarianship Blackwell Publishing Ltd.

Jonathan D. Eldredge, The University of New Mexico, Health Sciences Library and Informatics Center, Albuquerque, NM, USA

Abstract Objectives: to describe the essential components of the Randomised Controlled Trial (RCT) and its major variations; to describe less conventional applications of the RCT design found in the health sciences literature with potential relevance to health sciences librarianship; to discuss the limited number of RCTs within health sciences librarianship. Methods: narrative review supported to a limited extent with PubMed and Library Literature database searches consistent with specific search parameters. In addition, more systematic methods, including handsearching of specific journals, to identify health sciences librarianship RCTs. Results: While many RCTs within the health sciences follow more conventional patterns, some RCTs assume certain unique features. Selected examples illustrate the adaptations of this experimental design to answering questions of possible relevance to health sciences librarians. The author offers several strategies for controlling bias in library and informatics applications of the RCT and acknowledges the potential of the electronic era in providing many opportunities to utilize the blinding aspects of RCTs. RCTs within health sciences librarianship inhabit a limited number of subject domains such as education. This limited scope offers both advantages and disadvantages for making Evidence-Based Librarianship (EBL) a reality. Conclusion: The RCT design offers the potential to answer far more EBL questions than have been addressed by the design to date. Librarians need only extend their horizons through use of the versatile RCT design into new subject domains to facilitate making EBL a reality.

Introduction More than 50 years ago a team of healthcare professionals faced an ethical dilemma involving a fatal disease. This disease caused about 25 000 deaths per year in the UK. A new experimental drug had shown some promise in curing this disease, Correspondence: Jonathan D. Eldredge,. MLS, PhD, The University of New Mexico, Health Sciences Library and Informatics Center, Albuquerque, NM 87131-5686, USA. E-mail: jeldredge@ salud.unm.edu

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but only by utilizing research methods likely to introduce possible bias. The new drug was in extremely limited supply, accentuating the ethical dilemma. The healthcare professionals decided that only a lottery would resolve the ethical issue of which patients would receive this new drug and which patients would not receive the drug. Patients were selected for this study on the basis of laboratory verification of the infection and shared similarly advanced stages of the fatal disease. The patients were in the age range of 15–25 years.

© Health Libraries Group 2003 Health Information and Libraries Journal, 20 (Suppl. 1), pp.34 – 44

RCT design: opportunities, Jonathan D. Eldredge

All patients fulfilling these inclusion criteria had their names entered into the lottery. Only about half of the patients ‘won’ the lottery to belong to an intervention group scheduled to receive the new experimental drug. The other patients in a control group received no treatment. After six months most (51%) of the patients in the intervention group treated with the experimental drug improved considerably whereas all but a few (8%) members of the control group continued their inevitable decline toward death. Viewed another way, only 7% of the intervention group died whereas 27% of the control group died from this disease during the 6-month period. This experiment, conducted by the British Medical Research Council, occurred in the 1940s. It involved 107 soldiers with acute progressive tuberculosis (TB) who were treated by the then experimental drug streptomycin.1 It also was the first instance of using a rigorously designed randomised controlled trial study.2− 4 This landmark experiment illustrates the three essential components of a Randomised Controlled Trial: (1) a carefully assembled group of potential subjects for the population who share certain common characteristics prior to their randomization into either intervention or control groups; (2) an intervention capable of effecting a change, in at least some members of the intervention group; and; (3) an outcome of interest possibly brought about by this intervention. In the first historic use of the Randomised Controlled Trial (RCT), the population consisted of severely tuberculosisinfected soldiers who were entered into a lottery, the intervention was streptomycin for the intervention group, and the outcome of interest was recovery from tuberculosis. Another early RCT conducted during 1954 involved two million US schoolchildren as the study population, the Salk vaccine for the intervention group, and the subsequent incidence of poliovirus as the outcome in this population.5,6 The Randomised Controlled Trial (RCT) gained widespread recognition and application through similar dramatic tests of the efficacy of a series of drugs. Streptomycin and the Salk vaccine were early examples of numerous drug-based RCTs that were to follow. The RCT design nevertheless has far broader applications than many people realise.

This article describes the basic components of RCTs along with their major variations, some less conventional applications of the RCT design of potential applicability within our profession, and the limited applications of the RCT design within health sciences librarianship. The author enhances these descriptions with his own experiences as the principal investigator in three RCTs. This article aims to increase awareness of the many variations of RCTs, and to heighten awareness of how some of these variations might be adaptable to our own evidence-based practise.7 Methods This narrative review draws upon both historic and contemporary examples to describe the RCT and to demonstrate the many potential applications of this experimental design. The author consulted research methods texts to identify major elements of RCTs along with their relevant variations. He then identified famous historic examples of RCTs capable of illustrating these major elements and their variations. In addition, he conducted PubMed searches during 30 January 2003 using the exploded MeSH terms ‘Drug Therapy’, ‘Surgical Procedures, Operative’, ‘Psychotherapy’ and other common clinical interventions. He limited retrieval to the ‘randomized controlled trial’ publication type, Englishlanguage, and human studies to attain a very rough estimate of possible RCTs associated with these interventions published since 1966. Table 1 summarizes these major types of RCTs. He moreover searched PubMed using the exploded MeSH term ‘Social Sciences’ limited to RCTs, English-language and the period January 2000– November 2002 to identify unexpected uses of the RCT design of potential use for the library and informatics profession. A small selection of references from this second PubMed search appears in Table 2. The search strategy to identify all known RCTs within our profession consisted of the author’s hand searching major health sciences librarianship journals as previously described.8 Librarians tend to not label their research designs so the author had to utilize this hand searching strategy. Library Literature, for example, does not utilize

© Health Libraries Group 2003 Health Information and Libraries Journal, 20 (Suppl. 1), pp.34 –44

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RCT design: opportunities, Jonathan D. Eldredge Table 1 Extent of common clinical RCTs since 1966. Therapeutics Surgical procedures, operative Anaesthesia Psychotherapy Physical therapy techniques Catherization Complementary therapies Health Education Respiratory therapy Radiotherapy Diet therapy

57 538* 27 968 6 473 4 062 3 268 2 708 2 565 2 399 1 981 1 590 1 112

*Includes drug therapy. Source. PubMed search on 30 January, 2003 using these specific words or phrases as MeSH terms; limited to Englishlanguage articles, human studies, and RCT publication types. Logically, due to the indexing of individual articles with multiple MeSH terms some specific articles might have been counted in two or possibly more categories.

subject headings to designate RCTs, or even experimental designs. The truncated keywords ‘random+’ and ‘trial+’ produced no relevant additional references relating to health sciences librarianship. He has also monitored the abstracts of Medical Library Association annual meetings since 2000 to identify additional RCTs. The author identified other RCTs from our profession by word of mouth or serendipity. Crumley and Koufogiannakis consulted the author on the legitimacy of possible health sciences librarianship RCTs they had identified for an article9 on Evidence-Based Librarianship (EBL), which resulted in the addition of further RCTs to Table 3. Components of the RCT design Population The RCT requires the use of a carefully defined and assembled population. RCTs delineate this pre-randomization population according to Inclusion and Exclusion criteria. The Medical Research Council in its 1948 article on tuberculosis explained this need for such criteria in an RCT: ‘… no two patients have an identical form of the disease and [yet] it was desired to eliminate as many of the obvious variations as possible.’1 Patients were included in the initial population

following bacteriological confirmation of TB and were excluded if outside the 15–25-year age group. A more recent study of therapies for depression specifies inclusion criteria as having an age of 18 years or older and a Beck Depression Inventory score of at least 14 points. The exclusion criteria dictate that the population does not include patients with suicidal intent, organic brain syndromes, or who have undergone specified psychological therapies within the past 6 months.10 Though RCT populations must be carefully defined, they can occur in a range of sizes. Drug RCTs financed by pharmaceutical firms tend to enlist larger populations than many other types of RCTs.11 Clinical medicine RCTs tend to select populations characterized by pathological conditions such as diabetes, mental disorders or heart disease. Nevertheless, RCT populations can comprise any group sharing certain characteristics including students, faculty members, and cardiologists. However, RCT populations are normally far more stringently defined for inclusion than populations studied in cohort studies.12 While the RCT design might only be a halfcentury old, the concept itself dates back at least to 1662 in van Helmont’s Oriartrike, which describes randomising a population prior to an intervention.13 One medical historian even credits Avicenna (980–1037) for conceptualizing the basic RCT design.14 Incidentally, some credit the Old Testament’s Daniel of Judah15 for having conducted an RCT in 600 , but this report more closely resembles a cohort study. RA Fisher’s 1926 article on techniques for randomization in agricultural field experiments represents another significant historical landmark in RCT development.16 During the 1930s studies on tuberculosis, cold vaccines, and the use of digitalis for pneumonia anticipated the 1940s RCT design breakthroughs.17−19 Historical developments were far more complex and non-linear than might be expected, principally because most physicians did not immediately recognize the utility of RCTs.20 Researchers later reported the first neurosurgery RCT in 196021 and in 1966 others reported the first RCT for a social medicine curriculum.22 Randomization helps ensure that the intervention or the control group do not differ in a way that


RCT design: opportunities, Jonathan D. Eldredge Table 2 Unexpected RCT applications. Population

Intervention

Outcomes

20 rural Swedes self-described as rare attendees at cultural events

Free tickets to multiple cultural events each week

Lower blood pressure and prolactin levels compared with control group45

36 people aged 18 years or older who had experienced at least one full-blown panic attack

Bibliotherapy

Fewer panic attacks than those in control group46

64 high school students assigned a task to learn

Presence of an audience

Neither intervention nor control group learned better than the other47

1615 visitors to a website who took the SF-36 health survey

Matrix survey format

Neither the matrix nor the standard expanded formats took less time to complete48

71 pairs of parents involved in child custody disputes petitioning the family court in Virginia during 1983– 86

Mediation

Those parents randomly allocated to mediation reported more favourable outcomes than those controls who proceeded to court litigation 12 years ago49

38 ‘eyewitnesses’ to a crime ‘witnessed’ on a videotape

Confusing questions commonly employed by lawyers including negatives, double negatives, leading questions, complex vocabulary, complex syntax, and multipart questions asked a week after viewing video

Intervention group responding to confusing questions had lower accuracy scores50

114 parents of children undergoing occlusion therapy at an ophthalmologic clinic

Written information for parents to read on the therapy, the importance of the critical period, and prognosis

Greater parental knowledge of and concordance with occlusion therapy than control group51

245 peer reviewers for the British Journal of Psychiatry

Participation in open peer review process Participants in open peer review were more courteous and took more time to review manuscripts than the anonymous reviewers52

Third- and fourth-grade students at two public schools in San Jose, California

Eighteen 30–50-minute classroom lessons to motivate children to reduce time watching televisions or videos, or the use of video games

Children in intervention group exhibited reduced aggressive behaviour53

69 house officers in Ann Arbor, Michigan

Told ‘you will have a great call day’ at beginning of shift

Intervention participants had no greater number of admissions, less sleep or a harder day than control group54

might explain the observed outcomes. Randomization occurs only after the Inclusion and Exclusion criteria have been clearly defined and implemented for defining and identifying a population. To be precise, randomization refers to random allocation of population members into intervention and control groups. It does not mean that randomization literally will lead to perfectly identical intervention and control groups. As Rothman explains: It is crucial to understand that randomization does not lead to identical distributions … but only to distributions that tend, on repeated trials, to be

identical, the tendency increasing as the size of the study group increases. Thus, randomization works very well to prevent confounding in large studies but it is less effective for smaller studies … Because successful randomization allows one to account for uncontrollable confounding, randomization is a powerful technique for ensuring valid causal inferences from studies, large or small.23 A properly executed research study, regardless of design, requires a clearly formulated hypothesis, a null hypothesis, and to have identified all imaginable hypotheses that could explain possible


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RCT design: opportunities, Jonathan D. Eldredge Table 3 RCTs in health sciences librarianship. 8 healthcare teams randomly selected from a pool of 20 teams. Four teams served as intervention groups and 4 teams served as control groups

Clinical librarians providing information services for healthcare professionals, patients, and patients’ families

Increased meeting of information needs for intervention group55

67 MLIS degree programme students and 133 gifted high school students

Fifteen minute PITTCAT web-based tutorial

Web-based tutorial not as effective as human teaching56

103 general practitioners in the Netherlands randomised into three3 different groups

Separate courses in Index Medicus, Grateful Med, or Silverplatter CD ROM MEDLINE

Effectiveness of searches tested by precision, recall, and overall search quality. Index Medicus group had most effective, but not most efficient performance57

31 OB/Gyn residents training at Thomas Jefferson University Hospital, stratified by postgraduate year in residency

Individual 1-hour MEDLINE tutorial taught by the same librarian for intervention group

Residents valued instruction and hands-on training58

38 senior staff physicians and one resident, stratified by alphabetical last name

Free, unlimited access to PaperChase

Costs for intervention group were similar to control group, which had access only to manual searches of Index Medicus or searches by a hospital librarian59

85 clinical physicians

Users either paid for or received free MEDLINE searches

Free MEDLINE users searched more often; quality of searches between groups about the same60

108 Oxford medical students randomly assigned to intervention (n = 54) or control (n = 54) groups. All assigned an evidence-based searching project

Intervention group received search training

Post-test performance revealed intervention group members had better search scores than pretest scores61

10 medical residents rotating through a neonatal intensive care unit at the University of Michigan

Librarians provided active instruction for intervention (intervention) group (n = 5)

The intervention group performed better searches and expressed greater satisfaction with their searching abilities62,63

311 physicians and physicians-in-training at a 300 bed teaching hospital

Librarians gave intervention group feedback on the efficacy of their first 10 searches

Intervention group neither searched more often nor better than the control group64

308 physicians and physicians-in-training, all of whom were given a 1-hour training class prior to randomization

Clinical preceptors knowledgeable of searching MEDLINE gave feedback to intervention group on their searches

Intervention and control groups performed essentially the same65

Users at an academic health sciences library

Three pairs of monographs ranges matched by similarities in size, decade-long growth, and 1997–2000 era usage. One member of each pair of monographs ranges was selected by random allocation. The intervention range was weeded according to strict criteria

25% greater usage in unweeded (control) monograph ranges; 27.7% greater use of unique items in unweeded (control) ranges29

All UNM College of Pharmacy faculty (n = 18) who returned an initial survey, excluding deans and one faculty with sustained contact with new pharmacy librarian

The pharmacy librarian met face-to-face with faculty in the intervention group for 30 – 60 min. Both intervention and control groups were otherwise communicated with electronically

No significant change in perceptions or use of the library by surveys of either intervention or control group28

All UNM College of Nursing faculty (n = 28) who returned an initial survey, excluding deans and one faculty with sustained contact with new pharmacy librarian

The nursing librarian met face-to-face with faculty in the intervention group for 30 – 60 min. Both intervention and control groups were otherwise communicated with electronically

Intervention group seemed to experience greater number of changes in perception of and use of the library than those in the control group.27

300 parents of consecutive admissions of premature infants. All parents receive routine patient education. Random block assignment into either control or two competing variable intervention groups

First intervention group received a booklet while second intervention group received education on exploring websites for more information

Results pending66



outcomes. Hypothesis generation moreover begins with a coherent research question.24−26 The questions leading to hypotheses in an RCT inform the definitions of the intervention group (hypothesis) and the control group (null hypothesis). Alternative hypotheses might be accounted for as other intervention groups or by careful data analysis. More likely, they will be structured into the design in the form of ‘matched randomization’, particularly in studies involving small populations. The author was principal investigator for two RCTs involving small populations comprised of faculty members of colleges of pharmacy and nursing, respectively. One alternative hypothesis suggested that the length of time a faculty member had spent at the institution served as a better determinant of his or her perceptions of the library and informatics centre’s services and resources than did face-to-face interaction with a librarian27,28 This alternative hypothesis led the researchers to stratify length of service for faculty members at the institution. In another RCT, the author identified three pairs of similar National Library of Medicine call number ranges for monographs and matched them prior to a weeding intervention. One of each pair was then selected as an intervention group subject to weeding according to strict criteria.29 Intervention When researchers employ the RCT they are attempting to answer the question of whether introducing one independent variable into an intervention population group will produce an outcome (dependent variable) different from either the absence of that variable or of some different variable. Most readers will recognise the basic template for an RCT in which researchers test the efficacy of a certain drug. Important variations to this pattern exist for defining intervention as well as control groups. Furthermore, David Sackett has written that ‘Therapeutic reports with controls tend to have no enthusiasm, and reports with enthusiasm tend to have no controls’.30 This strongly worded statement signals a need for an RCT to include clearly defined intervention and control groups, plus a clear understanding of the variations of RCTs.

Conventional clinical interventions consist of administering drugs, performing surgeries, applying ultrasound or heat, nursing techniques, physical therapy manoeuvres or occupational therapy practices. Other interventions have included health education activities to promote healthy behaviours or to discourage unhealthy behaviours. Less conventional clinical interventions include massage therapy, reflexology, healing touch, distance spiritual healing, work therapy, music therapy, Tai Chi, relaxation techniques, aromatherapy, acupuncture, and herbal remedies. Other unconventional interventions include problem-based learning,31 role modelling, imagery rehearsal, advice, stress management training, and instructions for writing structured abstracts. Still other interventions involve brief psychotherapy, exercise regimens, nurse outreach, smoking cessation counselling, non-directive questioning, advanced directives, phone or other types of reminders for scheduled appointments, healthcare professional response, support group, case management, and monetary incentives. Table 2 outlines the populations, interventions, and outcomes of some unexpected RCTs. Such unexpected variants on the RCT design might be adapted at a conceptual level to health sciences librarianship. Untried applications of the RCT design for our profession might occur in areas such as outreach, collaborative learning of database searching skills, professional mentoring approaches, and the reference interview. Other applications could include new book notification, virtual versus phone reference services, and the provision of consumer health information as a means for changing unhealthy patient behaviours. Some applications might lend themselves to collaboration with colleagues outside our profession. Researchers will introduce a variable to the intervention group selected randomly from the population observed in the RCT. Researchers previously will have hypothesized that the independent variable they introduce to the intervention group will have a greater effect than might be observed in the control group. An intervention can be as brief as 20 minutes32 or the intervention can be sustained for a much longer period of time. Researchers sometimes hypothesize that the amount of an intervention variable will have a


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different effect on outcomes (the so-called ‘dose effect’). The researchers in one RCT, for example, randomly assigned physicians to receive either $5, $10, or $20 cash incentives to complete a mail survey. They hypothesized that higher monetary amounts would yield higher survey response rates.33 Harewood et al. compared three interventions in their RCT on e-mail versus standard postal mail versus telephone for surveying endoscopy patients.34 The intervention group sometimes receives the same treatment as the control group with the intervention group receiving the intervention variable in addition to that standard control group treatment. Pelham and colleagues investigated the treatment of all Attention Deficit Hyperactivity Disorder (ADHD) children in a population with only behavioural therapy as the control and combined behavioural and drug therapy for the intervention group.35 Dennis et al. similarly supplemented conventional care for all breast-feeding mothers in their population with a peer support group for the intervention group as the independent variable.36 The author found only one example of this variant of RCT within health sciences librarianship as noted on Table 3. The author hopes that these less typical examples of intervention might inspire readers to think of less conventional applications of the RCT design. A control group simply lacks an intervention with the variable of interest to researchers. Many might equate control group status with receiving a placebo, namely to be ‘ignored’ by the researchers. Experimental designs, including the RCT, do not necessarily dictate such conditions. In clinical medicine the control group patients typically receive the standard or conventional care, mostly for ethical reasons. In health sciences librarianship, a control group might include students receiving the standard library skills instruction training, users having access to the existing online catalogue, and researchers utilizing conventional reference services. In these examples, the intervention group would differ from the control group by perhaps experiencing a new form of instruction, a new online catalogue, or a virtual reference service. Each of these constitutes an intervention variable that, researchers might hypothesize, will result in a different outcome.

The question naturally arises as to whether the intervention group might be given an unethical advantage over the control group. After all, researchers have already hypothesized that the experimental intervention variable will have a greater beneficial effect. One need only consider the popular imagination as captured in the news media to understand this perception. Yet, as with any hypothesis leading to an experiment, no one really knows the outcome. The hypothesis only represents a best guess. Epidemiological researchers use the term ‘equipoise’ to describe the condition of ambiguous uncertainty about the benefits of alternative interventions.37 Only a rigorous test will produce useful evidence. The RCT design can aid in producing evidence, whether as expected or unexpected outcomes. During the 1980s, researchers hypothesized about the probable benefits of tamoxifen in combating breast cancer. They never understood the negative risks of developing endometrial cancer in patients treated with tamoxifen until an RCT brought this subtle possibility to light.38 Nor did researchers anticipate the negative effects upon group participants in another RCT examining the distribution of patient education booklets.39 Gordis discusses these and other ethical aspects of RCTs.40 Thus, in many instances, researchers cannot predict honestly whether the intervention or the control group members have an unethical advantage. Outcome Researchers frequently hypothesize that the independent variable of interest will have an effect or a greater effect upon the outcome (dependent variable) compared with outcomes observed in the control group. The observable effect often does not appear as a dramatic outcome, which might itself surprise readers. In addition, some RCTs answer questions posed at the outset of the study only to generate new questions in due course. The author has served as the principal investigator for three RCTs. Each of these RCTs produced unexpected aspects of their outcomes. The brilliant behavioural scientist Robert Rosenthal has demonstrated repeatedly that even seasoned researchers can misperceive phenomena when led to expect a certain outcome. Rosenthal



also has noted that under other conditions researchers might unwittingly cue their subjects to behave in an expected manner.41,42 This now large and convincing body of evidence indicates the desirability of using ‘blinded’ designs so neither subjects, controls nor researchers know the identities of the group receiving the intervention of interest. Of course, blinding in RCTs that involve small populations, populations in which members of control and intervention groups interact frequently (examples: students or faculty members), interventions difficult to disguise, or those not involving traditional drug trial designs are highly impractical to implement. Researchers and users of research must nevertheless be aware of the likely introduction of bias in those RCTs that lack a double-blind design. Rosenthal demonstrated that even veteran researchers are susceptible to interpreting results in a biased fashion so mere vigilance might not be a sufficient safeguard. Several strategies utilized by the author can approximate the pure double-blind approach. Firstly, the principal investigator can avoid revealing the hypothesis or alternative hypotheses to colleagues involved in the study. Colleagues will often be satisfied to know that multiple approaches are under investigation in a particular study. Secondly, peer review at various points in implementing an RCT design can prevent bias. For example, the author collected data apart from a colleague actually conducting an intervention. He then transcribed data from pre- and post-intervention surveys with two colleagues present to witness the data input process to ensure accuracy. A printout of accurate data spreadsheets was signed and dated for the permanent file. Thirdly, colleagues unfamiliar with the research project might be involved in the actual intervention or the subsequent initial data analysis. These colleagues often are simply not attuned to the major issues or the nuances connected with the study hypotheses, and will tend to perform in strict adherence to the principal investigator’s instructions. The author not only has utilized these strategies in isolation but also in combination to approximate the double blind process. Opportunities for using double-blind approaches should multiply as an increasing proportion of

resources and services are offered via electronic interfaces. We can randomly assign members of a study population into either intervention or control groups via electronic means invisible to that population. Participants need only be alerted to the existence of the study, and to give their consent to participate, to fulfil institutional ethical considerations involving human subjects. Electronic interfaces can record baseline measures prior to random allocation into control and intervention groups. Control groups can continue to receive access to conventional resources or services via the same electronic interface, whereas the intervention group can receive access to variants of the conventional resources or services as part of an intervention. Incidentally, the electronic interface itself could be altered for the intervention group while the control group continues to use a conventional interface. This latter scenario might be a little more difficult to blind from members of the control group, however. Interventions might be experimental versions of existing resources or services and might include web-based instructional modules, databases, virtual reference services, electronic journals or books, online catalogues, promotional messages regarding the library and informatics centre, or aspects of the centre’s website. Intervention groups could even experience access to an electronic collection of resources which has been ‘weeded’ according to pre-determined criteria without the centre even actually removing these resources from the permanent collection of resources. Therefore, the electronic era promises many opportunities to allocate study populations, present these groups with conventional or experimental experiences, measure differences, and reduce contamination between control and intervention groups. Such opportunities need to be seized as a major EBL initiative. The RCT within librarianship Table 3 lists all RCTs, identified by the author, known to exist within health sciences librarianship. A broader literature search, including associated areas such as informatics, undoubtedly would produce a larger table, but would also diminish focus by blurring distinctions. Table 3


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demonstrates clear patterns to health sciences librarianship. Crumley and Koufogiannakis have identified six subject domains for Evidence-Based Librarianship (EBL): reference/enquiries; education; collections; management; information access and retrieval; and marketing/promotion.9 The majority, 57% (n = 8) of the health sciences librarianship RCTs, listed primarily involve education interventions. The first RCT in our field, published in 1981, studying the potential benefits of a Clinical Medical Librarian, probably fits best in the reference/enquiries category. Other RCTs consist of two library liaison studies (located primarily within the education, but also somewhat within the collections, categories) and two studies clearly within the collections category. The predominance of RCTs in the education domain provides a foundation for future metaanalyses or rigorous systematic reviews. Syntheses from multiple RCTs sharing sufficient numbers and areas of similarity might lead to more rigorous evaluations of common library education practices. Existing protocols from these RCTs could enable others to replicate these studies. In addition, these studies would seem easy to replicate due to the frequency of library instruction activities in health sciences librarianship. Such foundations, on which completion of subsequent studies may build a future knowledge base, will contribute much to our profession’s development of EBL. There are disadvantages to the domination of this one subject domain for RCTs, however. Our profession has generated a diversity of high priority research questions43 not addressed at all by existing RCTs. Admittedly, half of these questions probably require research designs other than an RCT if they are to be answered appropriately.44 Many questions, nevertheless best answered by RCTs, remain unanswered. Conclusion This article clearly demonstrates the relative ease of designing and implementing an RCT once one understands the basic principles. Table 2 illustrates the diversity of applications with potential relevance to health sciences librarianship. The author hopes that Tables 2 and 3 will inspire others to use the RCT design to address the many

still-unanswered EBL questions. Health sciences librarians simply need to extend their horizons of what might be possible and to lend their considerable creative energies and resourcefulness to make this new vision a reality. At least four of the identified studies have secured prestigious research awards in the US during the past 2 years. Perhaps this incentive will encourage others to expand their repertoire to use RCTs in pursuit of future awards? We are limited only by our reluctance to employ our vision, imagination, and confidence to adapt the RCT design to our own field. This article facilitates a better understanding of the basic elements of RCTs, plus its important variations. It also describes less conventional forms of RCT designs from the health sciences as well as from health sciences librarianship to point to the potential versatility of RCTs in answering EBL questions. Such versatility has yet to harnessed to anywhere near its full potential in health sciences librarianship. References 1 Medical Research Council. Streptomycin treatment of pulmonary tuberculosis. British Medical Journal 1948, ii, 769–82. 2 Doll, R. Development of controlled trials in preventive and therapeutic medicine. Journal of Biosocial Science 1991, 23, 365–78. 3 Doll, R. Controlled trials: the 1948 watershed. BMJ 1998, 317, 1217–20. 4 Yoshioka, A. Use of streptomycin in the Medical Research Council’s clinical trial of streptomycin in pulmonary tuberculosis in the 1940s. BMJ 1998, 317, 1220–3. 5 Lambert, S. M. & Markel, H. Making history: Thomas Francis Jr, MD, and the 1954 Salk Poliomyelitis Vaccine Field Trial. Archives of Pediatrics and Adolescent Medicine 2000, 154, 512–7. 6 Chase, A. Magic shots: a human and scientific account of the long and continuing struggle to eradicate infectious diseases by vaccination. New York: Morrow, 1982: 293–307. 7 Eldredge, J. D. Evidence-based librarianship: an overview. Bulletin of the Medical Library Association 2000, 88, 289–302. Available from: http://www.pubmedcentral.gov/tocrender.fcgi?journal=93. 8 Eldredge, J. D. Evidence-based librarianship: searching for the needed EBL evidence. Medical Reference Services Quarterly 2000, 19(3), 1–18. 9 Crumley, E. & Koufogiannakis, D. Developing evidence-based librarianship: practical steps for implementation. Health Information and Libraries Journal 2002, 19, 61–70. 10 Ward, E., King, M., Lloyd, M., Bower, P., Sibbald, B., Farrelly, S. et al. Randomised controlled trial of non-directive counseling, cognitive-behaviour therapy, and usual general practitioner care for patients with depression. I. Clinical effectiveness. BMJ 2000, 321, 1383–8. 11 Meldrum, M. L. A brief history of the randomized controlled trial. Hematology/Oncology Clinics of North America 2000, 14(4), 745 – 60. 12 Eldredge, J. D. Cohort studies in health sciences librarianship. Journal of the Medical Library Association 2002, 90, 380–92. Available from: http://www.pubmedcentral.gov/ tocrender.fcgi?journal=93.


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