Lay conceptions of the ethical and scientific justifications for random allocation in clinical trials. Factual understanding of randomized clinical trials: a multicenter case-control study in cancer patients A reanalysis of cluster randomized trials showed interrupted time-series studies were valuable in health system evaluation. Understanding and Misunderstanding Randomized Controlled Trials Increasing participation of cancer patients in randomised controlled trials: a systematic review Evidence-based public health: moving beyond randomized trials. Fusing Randomized Trials With Big Data: The Key to Self-learning Health Care Systems? Randomised controlled trials – the gold standard for effectiveness research The CONSORT Statement: Revised Recommendations for Improving the Quality of Reports of Parallel-Group Randomized Trials Challenges and Innovations in a Community-Based Participatory Randomized Controlled Trial [CONSORT for reporting randomized controlled trials in journal and conference abstracts: explanation and elaboration]. The quality of randomized trial reporting in leading medical journals since the revised CONSORT statement. CONSORT for Reporting Randomized Controlled Trials in Journal and Conference Abstracts: Explanation and Elaboration A simplified search strategy for identifying randomised controlled trials for systematic reviews of health care interventions: a comparison with more exhaustive strategies Evaluation of cluster randomized controlled trials in sub-Saharan Africa. Community-led trials: Intervention co-design in a cluster randomised controlled trial Randomised controlled trials: an introduction for nurse researchers.
R and omised controlled trials ( RCTs ) play a central role in modern medical advance , and they require participants who underst and and accept the procedures involved . Published evidence suggests that RCT participants often fail to underst and that treatments are allocated at r and om and that clinicians are in equipoise about which treatment is best . We examine background assumptions that members of the public might draw upon if invited to take part in a RCT .  Four studies ( N=82 ; 67 ; 67 ; 128 ) , in the UK , identified whether members of the public ( i ) . accept that an individual clinician might be genuinely unsure which of two treatments was better ; ( ii ) . judge that when there is uncertainty it is acceptable to suggest deciding at r and om ; ( iii ) . recognise scientific benefits of r and om allocation to treatment conditions in a trial . Around half the participants were loathe to accept that a clinician could be completely uncertain , and this was no different whether the context was one of individual treatment or research . Most participants found it unacceptable to suggest allocating treatment at r and om , though there was weak evidence that a research context may reduce the unacceptability . Participants did not judge that more certain knowledge would be gained about which treatment was best when treatments were allocated at r and om rather than by patient/doctor choice : scientific benefits of r and omisation were apparently not recognised . Judgements were no different in non-medical context s. Results suggest a large mismatch between the assumptions underlying the trial design , and the assumptions that lay participants can bring to bear when they try to make sense of descriptive information about r and omisation and equipoise . Previous attempts to improve underst and ing by improving the clarity or salience of trial information , or of making explicit the research context , while helpful , may need to be supplemented with accessible explanations for r and om allocation Summary Objective Several reports have shown that despite the informed consent process , enrolled patients misunderst and the modalities and goals of r and omized clinical trials ( RCTs ) . We believe that this may be linked to a priori misconceptions in the main population . The purpose of this study is to compare the knowledge about cancer RCTs in enrolled participants ( cases ) versus patients treated under cancer st and ard care who have never taken part in RCTs ( controls ) . Methods We su bmi tted a vali date d question naire ( ICEC-R ) to both population s to explore their knowledge about RCTs . A total of 75 cases and 107 controls were included . Results Globally , the cases ’ knowledge was significantly better , especially about ( i ) the r and omization process , ( ii ) the uncertain potential benefits , and ( iii ) the right to withdraw consent . Both population s presented the lowest scores for items exploring the r and omization process and uncertain treatment benefits . Conclusion Enrolled patients ’ comprehension of the goals and means of RCTs is actually better than controls ’ . Nevertheless , additional efforts should be made to enhance information about clinical research to patients as well as to the main population . Practice Implication s Having better knowledge about patients ’ difficulties in underst and ing RCTs would allow physicians to adjust the information they give and then to enhance patients ’ well-being OBJECTIVES There is often substantial uncertainty about the impacts of health system and policy interventions . Despite that , r and omized controlled trials ( RCTs ) are uncommon in this field , partly because experiments can be difficult to carry out . An alternative method for impact evaluation is the interrupted time-series ( ITS ) design . Little is known , however , about how results from the two methods compare . Our aim was to explore whether ITS studies yield results that differ from those of r and omized trials . STUDY DESIGN AND SETTING We conducted single-arm ITS analyses ( segmented regression ) based on data from the intervention arm of cluster r and omized trials ( C- RCTs ) , that is , discarding control arm data . Secondarily , we included the control group data in the analyses , by subtracting control group data points from intervention group data points , thereby constructing a time series representing the difference between the intervention and control groups . We compared the results from the single-arm and controlled ITS analyses with results based on conventional aggregated analyses of trial data . RESULTS The findings were largely concordant , yielding effect estimates with overlapping 95 % confidence intervals ( CI ) across different analytical methods . However , our analyses revealed the importance of a concurrent control group and of taking baseline and follow-up trends into account in the analysis of C- RCTs . CONCLUSION The ITS design is valuable for evaluation of health systems interventions , both when RCTs are not feasible and in the analysis and interpretation of data from C- RCTs RCTs would be more useful if there were more realistic expectations of them and if their pitfalls were better recognized . For example , and contrary to many cl aims in the applied literature , r and omization does not equalize everything but the treatment across treatments and controls , it does not automatically deliver a precise estimate of the average treatment effect ( ATE ) , and it does not relieve us of the need to think about ( observed or unobserved ) confounders . Estimates apply to the trial sample only , sometimes a convenience sample , and usually selected ; justification is required to extend them to other groups , including any population to which the trial sample belongs . Dem and ing “ external validity � ? is unhelpful because it expects too much of an RCT while undervaluing its contribution . Statistical inference on ATEs involves hazards that are not always recognized . RCTs do indeed require minimal assumptions and can operate with little prior knowledge . This is an advantage when persuading distrustful audiences , but it is a disadvantage for cumulative scientific progress , where prior knowledge should be built upon and not discarded . RCTs can play a role in building scientific knowledge and useful predictions but they can only do so as part of a cumulative program , combining with other methods , including conceptual and theoretical development , to discover not “ what works , � ? but “ why things work � ? Background There are many barriers to patient participation in r and omised controlled trials of cancer treatments . To increase participation in trials , strategies need to be identified to overcome these barriers . Our aim was to assess the effectiveness of interventions to overcome barriers to patient participation in  r and omised controlled trials ( RCTs ) of cancer treatments . Methods A systematic review was conducted . Published and unpublished studies in any language were search ed for in fifteen electronic data bases , including MEDLINE , EMBASE , CINAHL and PsycINFO , from inception to the end of 2004 . Studies of any interventions to improve  cancer patient participation  in RCTs , which reported the change in recruitment rates , were eligible for inclusion . RCTs and non-r and omised controlled trials as well as before and after studies reporting baseline rates specific to the population being investigated were included . Data were extracted by one review er into structured summary tables and checked for accuracy by a second review er . Each included study was assessed against a checklist for method ological quality by one review er and checked by a second review er . A narrative synthesis was conducted . Results Eight studies were identified that met the inclusion criteria : three RCTs , two non-r and omised controlled trials and three observational studies . Six of the studies had an intervention that had some relevance to the UK . There was no robust evidence that any of the interventions investigated led to an increase in  cancer patient participation in RCTs , though one good quality RCT found that urologists and nurses were equally effective at recruiting participants to a treatment trial for prostate cancer . Although there was no evidence of an effect in any of the studies , the evidence was not of sufficient quality to be able to conclude that these interventions therefore do not work . Conclusion There is not a strong evidence -base for interventions that increase  cancer patient participation  in r and omised trials . Further research is required to evaluate the effectiveness of strategies to increase participation in cancer treatment trials R and omized controlled trials ( RCTs ) are essential for evaluating the efficacy of clinical interventions , where the causal chain between the agent and the outcome is relatively short and simple and where results may be safely extrapolated to other setting s. However , causal chains in public health interventions are complex , making RCT results subject to effect modification in different population s. Both the internal and external validity of RCT findings can be greatly enhanced by observational studies using adequacy or plausibility design s. For evaluating large-scale interventions , studies with plausibility design s are often the only feasible option and may provide valid evidence of impact . There is an urgent need to develop evaluation st and ards and protocol s for use in circumstances where RCTs are not appropriate R and omized clinical trials ( RCTs ) have revolutionized medicine by providing evidence on the efficacy and safety of drugs , devices , and procedures . Today , more than 40 000 RCTs are reported annually , their quality continues to increase , and oversight mechanisms ensure adequate protection of participants . However , RCTs have at least 4 related problems : ( 1 ) they are too expensive and difficult ; ( 2 ) their findings are too broad ( average treatment effect not representative of benefit for any given individual ) and too narrow ( trial population and setting not representative of general practice ) ; ( 3 ) r and omizing patients can make patients and physicians uncomfortable , especially when comparing different types of existing care ; and ( 4 ) there are often long delays before RCT results diffuse into practice . The new alternative is “ big data . ” Because medical care is increasingly digitized in electronic health record ( EHR ) data sets and linked biological and genetic data banks , proponents suggest that health care systems are at the dawn of an era in which a patient ’s prognosis and optimal therapy will be generated from rapid analysis of these data sets using sophisticated machinelearning strategies . The information is relatively inexpensive , generated as a by-product of patient care ( overcoming the cost problem ) , and both specific to individuals ( ie , adequately narrow ) and , en masse , descriptive of the entire delivery system ( ie , adequately broad ) . No individuals are r and omized , so the ethical issues appear less complex . The richness and immediacy of these new data could allow tailored treatment decisions in real time , overcoming delays in knowledge translation . As such , although the RCT remains the gold st and ard for evaluation of experimental therapies , big data is proposed as a better approach for the broad swath of comparative effectiveness questions that arise in clinical practice . Indeed , the Institute of Medicine envisions big data as the engine for so-called learning health care systems.1 Yet big data is not a replacement for the RCT . The singular beauty of the RCT is the strength of causal inference that arises from r and om assignment . All known and unknown factors that can influence outcome , other than the treatment assignment , are distributed r and omly— and , if r and omization is effective , evenly — among the groups . Thus , any statistical difference in outcome between groups can be attributed to the assigned interventions . In contrast , big data exploits variation that may appear r and om but is not in fact r and omized . For example , big data may compare patients who did or did not receive a particular drug and then attempt to determine the extent to which any difference in patient outcome may be related to receiving the drug . However , for all the allure of inexpensive access to massive amounts of data , the Achilles ’ heel is lack of causal inference . No matter how detailed the measurement and how sophisticated the adjustment for all known variables , big data can not eliminate unmeasured factors coincident with a particular treatment assignment that could explain an apparent change in outcome .2 Thus , each approach has complementary strengths : RCTs offer causal inference , and big data offers the potential for low-cost , high-volume , nuanced answers with immediate feedback . Rather than debate which is better , the greatest promise may come from fusing them Learning points R and omised controlled trials ( RCTs ) are the reference st and ard for study ing causal relationships between interventions and outcomes as r and omisation eliminates much of the bias inherent with other study design s. To provide a true , reliable assessment of effectiveness , RCTs need to be conducted robustly , i.e. with concealment of allocation , blinding , intention-to-treat analysis and sufficiently large sample size A report of a r and omized , controlled trial ( RCT ) should convey to the reader , in a transparent manner , why the study was undertaken and how it was conducted and analyzed . For example , a lack of adequately reported r and omization has been associated with bias in estimating the effectiveness of interventions ( 1 , 2 ) . To assess the strengths and limitations of an RCT , readers need and deserve to know the quality of its methods . Despite several decades of educational efforts , RCTs still are not being reported adequately ( 3 - 6 ) . For example , a review of 122 recently published RCTs that evaluated the effectiveness of selective serotonin-reuptake inhibitors as first-line management strategy for depression found that only 1 ( 0.8 % ) paper described r and omization adequately ( 5 ) . Inadequate reporting makes the interpretation of RCT results difficult if not impossible . Moreover , inadequate reporting borders on unethical practice when biased results receive false credibility . History of CONSORT In the mid-1990s , two independent initiatives to improve the quality of reports of RCTs led to the publication of the CONSORT ( Consoli date d St and ards of Reporting Trials ) statement ( 7 ) , which was developed by an international group of clinical trialists , statisticians , epidemiologists , and biomedical editors . CONSORT has been supported by a growing number of medical and health care journals ( 8 - 11 ) and editorial groups , including the International Committee of Medical Journal Editors ( ICMJE , also known as the Vancouver Group ) ( 12 ) , the Council of Science Editors ( CSE ) , and the World Association of Medical Editors ( WAME ) . CONSORT is also published in Dutch , English , French , German , Japanese , and Spanish . It can be accessed on the Internet , along with other information about the CONSORT group ( 13 ) . The CONSORT statement comprises a checklist and flow diagram for reporting an RCT . For convenience , the checklist and diagram together are called simply CONSORT . They are primarily intended for use in writing , review ing , or evaluating reports of simple two-group , parallel RCTs . Preliminary data indicate that the use of CONSORT does indeed help to improve the quality of reports of RCTs ( 14 , 15 ) . In an evaluation ( 14 ) of 71 RCTs published in three journals in 1994 , allocation concealment was not clearly reported in 43 ( 61 % ) of the RCTs . Four years later , after these three journals required that authors reporting an RCT use CONSORT , the proportion of papers in which allocation concealment was not clearly reported had dropped to 39 % ( 30 of 77 ; mean difference , 22 % [ 95 % CI of the difference , 38 % to 6 % ] ) . The usefulness of CONSORT is enhanced by continuous monitoring of the biomedical literature ; this monitoring allows CONSORT to be modified depending on the merits of maintaining or dropping current items and including new items . For example , when Meinert ( 16 ) observed that the flow diagram did not provide important information about the number of participants who entered each phase of an RCT ( enrollment , treatment allocation , follow-up , and data analysis ) , the diagram could be modified to accommo date the information . The checklist is similarly flexible . This iterative process makes the CONSORT statement a continually evolving instrument . While participants in the CONSORT group and their degree of involvement vary over time , members meet regularly to review the need to refine CONSORT . At the 1999 meeting , the participants decided to revise the original statement . This report reflects changes determined by consensus of the CONSORT group , partly in response to emerging evidence on the importance of various elements of RCTs . Revision of the CONSORT Statement Thirteen members of the CONSORT group met in May 1999 with the primary objective of revising the original CONSORT checklist and flow diagram , as needed . The group discussed the merits of including each item in the light of current evidence . As in developing the original CONSORT statement , our intention was to keep only those items deemed fundamental to reporting st and ards for an RCT . Some items not considered essential may well be highly desirable and should still be included in an RCT report even though they are not included in CONSORT . Such items include approval of an institutional ethical review board , sources of funding for the trial , and a trial registry number ( as , for example , the International St and ard R and omized Controlled Trial Number [ IS RCT N ] used to register an RCT at its inception [ 17 ] ) . Shortly after the meeting , a revised version of the checklist was circulated to the group for additional comments and feedback . Revisions to the flow diagram were similarly made . All these changes were discussed when CONSORT participants met in May 2000 , and the revised statement was finalized shortly afterward . The revised CONSORT statement includes a 22-item checklist ( Table ) and a flow diagram ( Figure ) . Its primary aim is to help authors improve the quality of reports of simple two-group , parallel RCTs . However , the basic philosophy underlying the development of the statement can be applied to any design . In this regard , additional statements for other design s will be forthcoming from the group ( 13 ) . CONSORT can also be used by peer review ers and editors to identify reports with inadequate description of trials and those with potentially biased results ( 1 , 2 ) . Table . Checklist of Items To Include When Reporting a R and omized Trial Figure . Flow diagram of the progress through the phases of a r and omized trial ( enrollment , intervention allocation , follow-up , and data analysis ) . During the 1999 meeting , the group also discussed the benefits of developing an explanatory document to enhance the use and dissemination of CONSORT . The document is patterned on reporting of statistical aspects of clinical research ( 18 ) , which was developed to help facilitate the recommendations of the ICMJE 's Uniform Requirements for Manuscripts Su bmi tted to Biomedical Journals . Three members of the CONSORT group , with assistance from members on some checklist items , drafted an explanation and elaboration document . That document ( 19 ) was circulated to the group for additions and revisions and was last revised after review at the latest CONSORT group meeting . Changes to CONSORT 1 . In the revised checklist , a new column for Paper Section and Topic integrates information from the Subheading column that was contained in the original statement . 2 . The Was It Reported ? column has been integrated into a Reported on Page Number column , as requested by some journals . 3 . Each item of the checklist is now numbered , and the syntax and order have been revised to improve the flow of information . 4 . Title and Abstract are now combined in the first item . 5 . While the content of the revised checklist is similar to that of the original one , some items that previously were combined are now separate . For example , authors had been asked to describe primary and secondary outcome ( s ) measure(s ) and the minimum important difference(s ) , and indicate how the target sample size was projected . In the new version , issues pertaining to outcomes ( item 6 ) and sample size ( item 7 ) are separate , enabling authors to be more explicit about each . Moreover , some items request additional information . For example , for outcomes ( item 6 ) authors are asked to report any methods used to enhance the quality of measurements , such as multiple observations . 6 . The item asking for the unit of r and omization ( for example , cluster ) has been dropped because specific checklists have been developed for reporting cluster RCTs ( 20 ) and other design types ( 13 ) since publication of the original checklist . 7 . Whenever possible , new evidence is incorporated into the revised checklist . For example , authors are asked to be explicit about whether the analysis reported is by intention to treat ( item 16 ) . This request is based in part on the observations ( 21 ) that authors do not adequately describe and apply intention-to-treat analysis and that reports not providing this information are less likely to provide other relevant information , such as losses to follow-up ( 22 ) . 8 . The revised flow diagram depicts information from four stages of a trial ( enrollment , intervention allocation , follow-up , and analysis ) . The revised diagram explicitly includes the number of participants , for each intervention group , included in the primary data analysis . Inclusion of these numbers lets the reader know whether the authors have performed an intention-to-treat analysis ( 21 - 23 ) . Because some of the information may not always be known and to accommo date other information , the structure of the flow diagram may need to be modified for a particular trial . Inclusion of the participant flow diagram in the report is strongly recommended but may be unnecessary for simple trials , such as those without any participant withdrawals or dropouts . Discussion Specifically developed to guide authors about how to improve the quality of reporting of simple two-group , parallel RCTs , CONSORT encourages transparency with reporting of the methods and results so that reports of RCTs can be interpreted both readily and accurately . However , CONSORT does not address other facets of reporting that also require attention , such as scientific content and readability of RCT reports . Some authors , in their enthusiasm to use CONSORT , have modified the checklist ( 24 ) . We recommend against such modifications because they may be based on a different process than the one used by the CONSORT group . The use of CONSORT seems to reduce ( if not eliminate ) inadequate reporting of RCTs ( 14 , 15 ) . Potentially , the use of CONSORT should positively influence the manner in which RCTs are conducted . Granting agencies have noted this potential relationship and , in at least in one case ( 25 ) , have encouraged grantees to consider in their application how they have dealt with the CONSORT items . The evidence -based approach used to develop CONSORT has also been used R and omized controlled trials ( RCTs ) are a long-st and ing and important design for conducting rigorous tests of the effectiveness of health interventions . However , many questions have been raised about the external validity of RCTs , their utility in explicating mechanisms of intervention and participants ’ intervention experiences , and their feasibility and acceptability . In the current mixed- methods study , academic and community partners developed and implemented an RCT to test the effectiveness of a collaboratively developed community-based advocacy , learning , and social support intervention . The goals of the intervention were to address social determinants of health and build trust and connections with other mental health services in order to reduce mental health disparities among Afghan , Great Lakes Region African , and Iraqi refugee adults and to engage and retain refugees in trauma-focused treatment , if needed . Two cohorts completed the intervention between 2013 and 2015 . Ninety-three adult refugees were r and omly assigned to intervention or control group and completed four research interviews ( pre- , mid- , and postintervention , and follow-up ) . Several challenges to conducting a community-based RCT emerged , including issues related to interviewer intervention to assist participants in the control group , diffusion of intervention re sources throughout the small refugee communities , and staff and community concerns about the RCT design and what evidence is meaningful to demonstrate intervention effectiveness . These findings highlight important epistemological , method ological , and ethical challenges that should be considered when conducting community-based RCTs and interpreting results from them . In addition , several innovations were developed to address these challenges , which may be useful for other community – academic partnerships engaged in RCTs BACKGROUND Clear , transparent , and sufficiently detailed abstract s of conferences and journal articles related to r and omized controlled trials ( RCTs ) are important , because readers often base their assessment of a trial solely on information in the abstract . Here , we extend the CONSORT ( Consoli date d St and ards of Reporting Trials ) Statement to develop a minimum list of essential items , which authors should consider when reporting the results of a RCT in any journal or conference abstract . METHODS AND FINDINGS We generated a list of items from existing quality assessment tools and empirical evidence . A three-round , modified-Delphi process was used to select items . In all , 109 participants were invited to participate in an electronic survey ; the response rate was 61 % . Survey results were presented at a meeting of the CONSORT Group in Montebello , Canada , January 2007 , involving 26 participants , including clinical trialists , statisticians , epidemiologists , and biomedical editors . Checklist items were discussed for eligibility into the final checklist . The checklist was then revised to ensure that it reflected discussion s held during and subsequent to the meeting . CONSORT for Abstract s recommends that abstract s relating to RCTs have a structured format . Items should include details of trial objectives ; trial design ( e.g. , method of allocation , blinding/masking ) ; trial participants ( i.e. , description , numbers r and omized , and number analyzed ) ; interventions intended for each r and omized group and their impact on primary efficacy outcomes and harms ; trial conclusions ; trial registration name and number ; and source of funding . We recommend the checklist be used in conjunction with this explanatory document , which includes examples of good reporting , rationale , and evidence , when available , for the inclusion of each item . CONCLUSIONS CONSORT for Abstract s aims to improve reporting of abstract s of RCTs published in journal articles and conference proceedings . It will help authors of abstract s of these trials provide the detail and clarity needed by readers wishing to assess a trial 's validity and the applicability of its results If r and omized controlled trials ( RCTs ) are to fulfill their potential to allow health care providers to make informed inferences about the validity of the trials upon which they base their clinical practice , then the reporting of key method ological factors must improve . The revised Consoli date d St and ards for Reporting Trials ( CONSORT ) were developed to improve the suboptimal reporting of RCTs . We aim ed to determine the extent to which RCTs report key method ological factors included in the revised CONSORT recommendations following publication of these recommendations . We conducted an observational study of RCTs published between July 2002 and June 2003 in 5 leading general medicine journals . We determined the proportion and 95 % confidence intervals of RCTs that reported sequence generation , allocation concealment , r and omization implementation , blinding status of participants , health care providers , outcome assessors , and data analysts , sample size justification , method of analysis ( e.g. intention-to-treat ) , and a participant flow diagram .  We included a total of 253 RCTs . RCTs reported : sequence generation 80 % ( 95 % CI 75 - 80 % ) , allocation concealment 48 % ( 95 % CI 42 - 54 % ) , r and omization implementation 55 % ( 95 % CI 49 - 61 % ) , blinding status of participants 40 % ( 34 - 46 % ) , health care providers 17 % ( 95 % CI 13 - 22 % ) , outcome assessors 47 % ( 95 % CI 41 - 53 % ) , data analysts 15 % ( 10 - 19 % ) , sample size justification 83 % ( 95 % CI 78 - 87 % ) , method of analysis 87 % ( 95 % CI 83 - 91 % ) ) , and participant flow diagrams 86 % ( 95 % CI 82 - 90 % ) . Although reporting of some CONSORT recommendations is high , reporting of several essential recommendations remains suboptimal . Authors need to comply with and journals need to enforce reporting of the revised CONSORT recommendations Background Clear , transparent , and sufficiently detailed abstract s of conferences and journal articles related to r and omized controlled trials ( RCTs ) are important , because readers often base their assessment of a trial solely on information in the abstract . Here , we extend the CONSORT ( Consoli date d St and ards of Reporting Trials ) Statement to develop a minimum list of essential items , which authors should consider when reporting the results of a RCT in any journal or conference abstract . Methods and Findings We generated a list of items from existing quality assessment tools and empirical evidence . A three-round , modified-Delphi process was used to select items . In all , 109 participants were invited to participate in an electronic survey ; the response rate was 61 % . Survey results were presented at a meeting of the CONSORT Group in Montebello , Canada , January 2007 , involving 26 participants , including clinical trialists , statisticians , epidemiologists , and biomedical editors . Checklist items were discussed for eligibility into the final checklist . The checklist was then revised to ensure that it reflected discussion s held during and subsequent to the meeting . CONSORT for Abstract s recommends that abstract s relating to RCTs have a structured format . Items should include details of trial objectives ; trial design ( e.g. , method of allocation , blinding/masking ) ; trial participants ( i.e. , description , numbers r and omized , and number analyzed ) ; interventions intended for each r and omized group and their impact on primary efficacy outcomes and harms ; trial conclusions ; trial registration name and number ; and source of funding . We recommend the checklist be used in conjunction with this explanatory document , which includes examples of good reporting , rationale , and evidence , when available , for the inclusion of each item . Conclusions CONSORT for Abstract s aims to improve reporting of abstract s of RCTs published in journal articles and conference proceedings . It will help authors of abstract s of these trials provide the detail and clarity needed by readers wishing to assess a trial 's validity and the applicability of its results Background It is generally believed that exhaustive search es of bibliographic data bases are needed for systematic review s of health care interventions . The CENTRAL data base of controlled trials ( RCTs ) has been built up by exhaustive search ing . The CONSORT statement aims to encourage better reporting , and hence indexing , of RCTs . Our aim was to assess whether developments in the CENTRAL data base , and the CONSORT statement , mean that a simplified RCT search strategy for identifying RCTs now suffices for systematic review s of health care interventions . Methods RCTs used in the Cochrane review s were identified . A brief RCT search strategy ( BRSS ) , consisting of a search of CENTRAL , and then for variants of the word r and om across all fields ( r and om$.af . ) in MEDLINE and EMBASE , was devised and run . Any trials included in the meta-analyses , but missed by the BRSS , were identified . The meta-analyses were then re-run , with and without the missed RCTs , and the differences quantified . The proportion of trials with variants of the word r and om in the title or abstract was calculated for each year . The number of RCTs retrieved by search ing with " r and om$.af . " was compared to the highly sensitive search strategy ( HSSS ) . Results The BRSS had a sensitivity of 94 % . It found all journal RCTs in 47 of the 57 review s. The missing RCTs made some significant differences to a small proportion of the total outcomes in only five review s , but no important differences in conclusions result ed . In the post-CONSORT years , 1997–2003 , the percentage of RCTs with r and om in the title or abstract was 85 % , a mean increase of 17 % compared to the seven years pre-CONSORT ( 95 % CI , 8.3 % to 25.9 % ) . The search using r and om$.af . reduced the MEDLINE retrieval by 84 % , compared to the HSSS , thereby reducing the workload of checking retrievals . Conclusion A brief RCT search strategy is now sufficient to locate RCTs for systematic review s in most cases . Exhaustive search ing is no longer cost-effective , because in effect it has already been done for CENTRAL Cluster r and omized controlled trials ( C RCTs ) are attractive in setting s in which individual r and omization is difficult or impossible . This issue is common when study ing several health problems in developing countries . The authors aim ed to assess empirically the extent to which the prerequisite design and analysis aspects of cluster r and omization were taken into account and reported properly in C RCTs conducted in sub-Saharan Africa . C RCTs published in the last three decades were evaluated by using a checklist based on the Consoli date d St and ards of Reporting Trials ( CONSORT ) statement . The authors identified 51 eligible C RCTs ; 40 of them ( 78 % ) had been published after 1990 . Only 10 ( 20 % ) studies took clustering into account in sample size or power calculations , and only 19 ( 37 % ) took clustering into account in the analysis . Intracluster correlation coefficients and design effects were reported in only one ( 2 % ) and three ( 6 % ) trials , respectively . An increasing number of C RCTs are conducted in sub-Saharan Africa , but many are not analyzed and reported properly . The special features stemming from cluster r and omization need to be addressed in the design , analysis , and reporting of these studies In conventional r and omised controlled trials ( RCTs ) , research ers design the interventions . In the Camino Verde trial , each intervention community design ed its own programmes to prevent dengue . Instead of fixed actions or menus of activities to choose from , the trial r and omised clusters to a participatory research protocol that began with sharing and discussing evidence from a local survey , going on to local authors hip of the action plan for vector control . Adding equitable stakeholder engagement to RCT infrastructure anchors the research culturally , making it more meaningful to stakeholders . Replicability in other conditions is straightforward , since all intervention clusters used the same engagement protocol to discuss and to mobilize for dengue prevention . The ethical codes associated with RCTs play out differently in community-led pragmatic trials , where communities essentially choose what they want to do . Several discussion groups in each intervention community produced multiple plans for prevention , recognising different time lines . Some chose fast turnarounds , like elimination of breeding sites , and some chose longer term actions like garbage disposal and improving water supplies . A big part of the skill set for community-led trials is being able to st and back and simply support communities in what they want to do and how they want to do it , something that does not come naturally to many vector control programs or to RCT research ers . Unexpected negative outcomes can come from the turbulence implicit in participatory research . One example was the  gender dynamic  in the Mexican arm of the Camino Verde trial . Strong involvement of women in dengue control activities seems to have discouraged men in setting s where activity in public spaces or outside of the home would ordinarily be considered a “ male competence”.Community-led trials address the tension between one-size-fits-all programme interventions and local needs . Whatever the conventional wisdom about how prevention works at a system level , programmes have to be perceived as locally relevant and they must engage stakeholders who make them work . Locally , each participating community has to know the intervention is relevant to them ; they have to want to do it . That happens much more easily if they design the programme themselves AIM To present an overview of the main components of r and omised controlled trials and identify issues for consideration during their design and management . BACKGROUND R and omised controlled trials ( RCTs ) are considered to be the gold st and ard for determining causality and can provide high quality evidence to inform nursing practice . DATA SOURCES A search of online data bases and websites was undertaken to identify relevant contemporary literature to inform the discussion . DISCUSSION / CONCLUSION Conducting a robust r and omised controlled trial can present research ers with numerous challenges and practical considerations . The importance of taking account of the Consort guidelines during their design , conduct and reporting is emphasised . IMPLICATION S FOR RESEARCH / PRACTICE Evidence from well conducted RCTs contributes to the development of effective nursing interventions . To avoid bias and ensure valid results , the design , conduct and reporting of RCTs should follow the Consort guidelines . Service users should be involved in the design and management of RCTs
The Camino Verde trial of community mobilisation for control of dengue reported a significant impact on entomological indices of the Aedes aegypti vector , and on serological dengue virus infection and self-reported dengue cases .
One reason for doing r and omised controlled trials ( RCTs ) is that experiments can be convincing .
Early epidemiological experimenters , such as Jenner and the smallpox vaccine and Snow and his famous Broad Street pump h and le , already knew the answer they were demonstrating ; they used the experiments as knowledge translation devices to convince others .
More sophisticated modern experiments include cluster r and omised controlled trials ( C RCTs ) for experiments in the public health setting .
Those who are convinced by a trial and want to act , need to know how the trial relates to their own context , what contributed to success , and what might make it even more effective .