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• Volume 7, Issue 4

TRIP database

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• Victor M Montori , MD, MSc ,
• Jon O Ebbert , MD
• Mayo Clinic
 Rochester, Minnesota, USA

https://doi.org/10.1136/ebm.7.4.104

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TRIP is easy to use, with a simple web page design that provides quick downloads even with slow internet connections. TRIP organises the links in its database into clinical areas (eg, cancer, cardiovascular, pregnancy and childbirth, and mental health) and features a self directed learning area that offers online continuing medical education based on systematic reviews. A user-friendly search engine is also available on the site. The user can enter a word or phrase (searched exactly as typed) or a simple Boolean expression into a query box. The search is limited to the title of the link or to the title and text that were captured in the database when the hit was first identified by TRIP (this text could include the executive summary of a guideline or the abstract of a manuscript). A helpful troubleshooting guide to improve searching is a click away. Users can store their search terms to be run periodically and can have the results emailed.

The search results are organised into colour coded categories. The categories include evidence-based resources (including links to ACP Journal Club and Evidence Based Medicine and links to databanks of critically appraised topics); query-answering services (mainly the Ask TRIP to Rapidly Alleviate Confused Thoughts [ATTRACT] service, www.attract.wales.nhs.uk ); peer reviewed journals (including the journals published by the BMJ Publishing Group, JAMA , Annals of Internal Medicine , and the New England Journal of Medicine ); guidelines; electronic textbooks (including the Merck Manual and emedicine.com); and links to the Clinical Queries feature of PubMed ( www.pubmed.gov .). Within each of these categories the links are listed by date of publication and include the name of the host website.

To evaluate TRIP, we completed a series of searches using questions that arose during our clinical practice. A search that used the simple Boolean expression “diabetes AND smoking” and that was restricted to “titles” identified 6 hits: 5 articles in peer reviewed journals and 1 guideline from the American Diabetes Association Practice Recommendations. When we completed the search using “titles and text,” it took longer, and most of the 387 resulting hits were not relevant.

A search for “vitamin E” in “titles” led to 19 hits. The results included critically appraised topics of several randomised trials of vitamin E and 3 Cochrane reviews. The hits also included ATTRACT’s answer to a question about the effectiveness of vitamin E in dementia. The peer reviewed journal hits included abstracts to 3 important clinical trials. The electronic textbook hits offered links to narrative reviews of vitamin E toxicity and deficiency.

Unfortunately, the search engine does not enhance the search terms entered by users who type in synonyms or medical subject headings. We found that searching by title and text yielded too many irrelevant hits, but this finding may represent our lack of experience with the search engine. Performance of quick searches on specific topics using TRIP can be hit or miss because success is dependent on the content of the database. We feel that the inclusion of textbooks delays the search and provides information of limited validity and clinical usefulness.

TRIP offers a friendly interface and quick access to the evidence (particularly if the search is limited to titles) with user friendly organisation of search results. We recommend this resource for those seeking pre-appraised evidence, reviews, and guidelines. Those seeking the original studies may be better off using the Clinical Queries and Related Articles functions in PubMed.

Methods/Quality:★☆☆☆☆

The website can be found at http://www.userguides.org

Read the full text or download the PDF:

• En español – ExME
• Em português – EME

Trip database – a different way to find evidence

Posted on 1st July 2013 by Alice Buchan

The Trip database may at first seem like any other search engine for scientific and medical research – plug your key words into the box, press enter, and watch what comes back. What makes Trip different, is what appears on the results page. Trip originally stood for translating research into practice – which is what it aims to help you do.

Searching Trip

To illustrate this, I’ll start by searching the database, with a topical (at the time of writing [1]) entry: “diclofenac heart” . The most obvious point is that results are colour coded – this is made clear by the toolbar at the side, where secondary evidence, such as systematic reviews, is green, primary evidence red, and so on. The order in which the results appear is what makes Trip unique; their algorithm includes research quality, date (more recent first), and a text score (relevance) [2], which combine to give you relevant, recent, and high quality results first (with a few odd exceptions I’ll come to later).

Colour coded results

Back to my search “diclofenac heart” – the default is to sort with quality as the top priority – but you can also make date or relevance more central to the ordering of results. When sorting by date, this highlights one of the idiosyncrasies of Trip; quality is based on journal or source [2], so a meta-analysis, which is high quality secondary research, (Lancet 2013 in the screen grab) is coded red, for key primary research. This isn’t much of an issue, but worth bearing in mind. Flicking through all 3 sorting options can help you find papers the first one might have missed. Another way of finding more relevant papers is by using the synonyms tab at the top of the search results. You may start your search knowing you want a certain type of evidence, such as a Cochrane review or a set of guidelines, and you can filter using the buttons on the right hand side, which also includes filters for evidence relevant to the developing world.

Filtering the results

As with many other databases, Trip features an advanced search, including the ability to define the proximity of key words within the document, but the PICO search is really unique, and I think it’s a fantastic way of finding what you are interested in quickly. For the uninitiated, PICO is Patients, Intervention, Comparison, and Outcome, and the importance of these 4 measures is explained in detail here [3]. Making my search more specific, I searched for heart outcomes in patients with arthritis taking diclofenac.

Searching using PICO

I found Trip really intuitive to use and clearly laid out, but they also have a series of “How-to” videos to help [4] . My favourite features were the wide range of evidence and sources available, including things like guidelines, which aren’t in some other databases, as well as colour-coding.

[1] Trip Database http://www.tripdatabase.com 

[2] Trip Database. About Trip  http://www.tripdatabase.com/about

[3] CEBM. Asking Focused Questions.  http://www.cebm.net/?o=1036

[4] Trip Database. How to use Trip  http://www.tripdatabase.com/how-to-use-trip  

Alice Buchan

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Resources, tools & health news from GW Himmelfarb Health Sciences Library

Trip Database: An Overview

The Trip Database is a medical search engine with an emphasis on evidence based practice (EBP), clinical guidelines and queries. Himmelfarb Library provides access to the freely accessible version of Trip. Started in 1997, Trip aims to help users “find evidence fast” with an easy to use search interface that filters results based on the evidence pyramid . A pyramid icon is displayed with the resource that indicates where the resource falls on the evidence pyramid.

Journals covered in Trip include high impact titles such as the New England Journal of Medicine (NEJM), The Lancet , the Journal of the American Medical Association (JAMA), the British Medical Journal (BMJ), and Annals of Internal Medicine . In addition, content from EvidenceAlerts and PubMed ’s core journal content is included. You can learn more about journal content included in Trip in their recent blog post on the subject.

In addition to the journal articles, Trip results provide a full range of resources including e-textbooks, patient information leaflets, educational courses and news. One thing to keep in mind about Trip is that publishers are classified by their output. Cochrane is known for publishing systematic reviews, and therefore Cochrane published resources will appear in the Systematic Reviews filter. The New England Journal of Medicine (NEJM) is classified as Primary Research. This means that if a systematic review is published in NEJM, it will appear in the Primary Research filter. However, when a systematic review is reviewed by the Database of Abstracts of Reviews of Effects (DARE), it will eventually appear in the Systematic Reviews filter, although there is a time delay.

Trip can be used by practicing physicians who would like to broaden their background knowledge on conditions such as diabetes or cancer, or who need to find relevant evidence-based information on testing guidelines or to make sure a “don’t miss” diagnosis is included in their differential diagnosis. Trip is also useful for medical students who may find the PICO search tool an effective way to search for applicable resources. Check out this blog post to learn more about case studies for using Trip.

Trip has responded to the War in Ukraine by creating a combat injuries filter . While this effort is still a work in progress, the filter attempts to gather the best combat evidence available. 

Interested in learning more about Trip? Check out the short video below:

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Trip: Overview

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Trip Overview

Trip is a clinical search engine designed to allow users to quickly and easily find a variety of high-quality research evidence to support their practice and/or care. Results provided can be sorted by quality, relevance, date or popularity and organized by the type of evidence via a pyramid graphic under the title of each article.

The library provides the free version of Trip. We do not have an institutional subscription to this product. There is a pro version of Trip that can be purchased which allows more full text results and additional tools if you wish to subscribe on your own. The personal subscription has an annual cost of $55 + tax.

For a comparison of free versus paid features see:  Trip Feature Comparison

Special Features

• Trip provides a graphic next to each result to inform you about level of evidence it qualifies as. The hierarchy is shown above.
• Filtering options are provided to focus on the kind of evidence (systematic reviews, primary research, regulatory guidance, etc.) desired.
• Search results can be ranked by quality, relevance, date or popularity.
• Patient/population, Intervention, Comparison and Outcomes ( PICO) searching is available allowing you to focus in on your research question.
• Trip provides a large collection of clinical guidelines and thousands of systematic reviews.
• The SmartSearch feature displays three related articles.
• If you sign up with your email to Trip, you can receive alerts about newly added sources regarding topics of interest to you at no charge.

Trip has a blog and the most recent posts are shown here. Click on the website link below to see the rest.

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Turning Research Into Practice (TRIP)

Turning Research Into Practice (TRIP). Jon Brassey, editor. TRIP Database, 12 Llansannor Drive, Cardiff, UK, CF10 4AW. moc.esabatadpirt@noj . http://www.tripdatabase.com ; free Website.

Readers may use articles without permission of copyright owners, as long as the author and MLA are acknowledged and the use is educational and not for profit.

The Turning Research Into Practice (TRIP) database was launched in 1997 as a medical search engine with a focus on evidence-based medicine (EBM) content. The initial purpose was to speed up the process of answering clinical questions by offering users a one-stop shopping approach to searching. Instead of jumping from one resource to another, the TRIP database allows users to search many at one time [ 1 ].

The resource began as an Excel spreadsheet with three fields: title, uniform resource locator (URL), and year of publication. To search the spreadsheet, users were limited to the “Find” function offered in Microsoft products. Eventually, the resource became Web-based and received its permanent URL in 2000. With its growing content and increase in use, the developers decided to make the resource available through subscription in 2002 to generate revenue to improve the resource. However, to keep with the spirit of accessibility and in turn to ease users into subscription-based access, resource users were allowed to search five times free per week. On September 1, 2006, the resource was relaunched as a free online resource [ 1 ].

One of the nice features of the TRIP database is that results are displayed in categories based on Haynes' work on the 4S approach to current best evidence of studies, syntheses, synopses, and systems [ 2 ] (described on the TRIP Website). The TRIP categories are: Evidence-based Synopses; Clinical Questions; Systematic Reviews; Guidelines (North American, Europe, Other); Core Primary Research; eTextbooks; Clinical Calculators; and core general medical journals retrieved from MEDLINE (PubMed). Each of these cate-gories searches a number of re-sources to produce the results. For example, the Evidence-based Synopses searches Bandolier, BestBets, POEMs, Clinical Evidence, Evidence-based Complementary and Alternative Medicine, and many more.

To further understand the Website and resource inclusion process, the reviewer read through the About Us pages of the Website. The Websites and resources included in the TRIP database are systematically selected using a site evaluation tool. TRIP works closely with the Department of Family Medicine at Laval University, Quebec, Canada, in this process. The department has put together a Directory of Clinical Information Websites, which includes over 100 critically appraised Websites that offer systematic reviews, clinical practice guidelines, and critically appraised topics. TRIP looks at these Websites and evaluates them using an in-house evaluation tool and a team of information experts and clinicians. Once a Website has passed the test, it will become part of the “grabbing” process.

The “grabbing” process begins with identifying the clinically relevant material in a preapproved Website. Then the title, URL, and date of publication is extracted and entered into the TRIP database. The TRIP spidering software is then used to visit the URLs entered into the database and grabs the content of that particular page. It is then processed and ready to be searched in the TRIP database. The database is updated monthly.

The reviewer found searchingthe database relatively easy and straightforward. TRIP states that it takes unknown search terms and matches them against a commonly misspelled word database to try to retrieve matches. TRIP also searches for any keywords and/or synonyms matching valid search terms entered. The database can be searched using Boolean operators as well as natural language searching. The reviewer took a question regarding oral rehydration versus intravenous therapy for gastroenteritis in children aged two to five years and tested it using a few different approaches.

The first attempt was to enter search terms into the general search box on the home page combing the search terms with a Boolean “AND”: “gastroenteritis AND oral rehydration therapy AND intravenous therapy AND children.” The search yielded forty-two EBM-filtered results and thirty-two MEDLINE (PubMed) search results. At first glance, the forty-two results appeared relevant. Some seemed irrelevant, but it was a manageable number to look through and the pre-identified systematic reviews, guidelines, and excerpts from electronic textbooks appeared.

The PubMed search that TRIP does automatically retrieved thirty-two articles. The exact same search was run in PubMed and retrieved seventy results. The reviewer wondered why there would be a difference in the number of results and found the answer to this question in TRIP's About Us pages. When TRIP searches PubMed, it uses the clinical queries search filters offered in PubMed that limit the search results to a specific clinical query category (therapy, diagnosis, prognosis, and etiology). This made sense and was consistent with the categorization by question type for users to quickly identify what type of article they require based on the type of question asked.

Another PubMed feature allows users to further focus a search in PubMed by selecting a specific specialty. It is also noted in the TRIP searching pages that the database goes beyond the filters and includes articles from the top five general internal medical journals ( New England Journal of Medicine, JAMA, Lancet, BMJ, and the Annals of Internal Medicine ) for the past five years, as well as the BMJ Updates.

The second approach to searching the TRIP database involved using the natural language offered by the database. When the reviewer viewed the results, a sentence appeared below the search box: “Do you mean: gastroenteritis oral rehydration therapy intravenous therapy children?” This option was selected to see if it would make any difference, but it did not change the number of results. This is a nice feature for those not familiar with or confident in using Boolean operators for searching. However, the reviewer does not recommend relying on this method of searching. The reviewer entered a question phrase regarding the original example search into the search box and only received a few hits. The results were not relevant and missed the systematic review and current guidelines.

The next step was to rerun the original search string and note whether it was searched in the “title” or the “title and text” of the documents. The search was run again, and, when the results appeared, the reviewer clicked on “Advanced Search.” The screen showed the search string had been run in the “title and text.” When “title” was selected, the search was considerably limited and only retrieved one clinical question, but the same thirty-two results were retrieved from PubMed. The reviewer felt that it would be best to test this approach again with another search to determine whether this was a true representation of the “title” versus “title and text” feature.

The TRIP search page describes the search algorithm used to score the content. It states that TRIP scores content based on three main variables. The first is year of publication, so current material receives a higher score. The second variable is term position/density. This means that the algorithm scores material based on the position of the term in the document (term in the title is given a higher score than if it is in the text). It also scores documents on the number of times a term appears in the document (number of appearances of the term divided by the total number of terms). The third variable is the publication. When a Website or resource is evaluated at the beginning of the process, it is also given a score. The scores are based on clinical usefulness and methodological quality.

The reviewer explored the advanced search feature as well by trying to search each concept separately and combining them using “AND” but only retrieved one result. After reading the Search Help Page, the reviewer revised the strategy based on the suggested methodology. TRIP suggests that the best way to combine search terms is to search the “title” for the condition and then search “title and text” for the intervention.

After users have done this, they should combine the search sets using Boolean operators. This approach received the same forty-two EBM filtered results that the original search yielded. However, it did not retrieve any PubMed search results, which is puzzling. The reviewer assumes that the use of numbers to combine the search is not recognized in the PubMed database because it could not read the search history in the TRIP database.

My Trip is a current awareness– type tool. It allows users to register and select keywords that are automatically searched when the database is updated. If material is retrieved, the results are automatically sent to users by email.

Two important features of the TRIP database are its Medical Images and Patient Information Leaflet options. When users run a search in TRIP, it automatically retrieves any available images and patient information leaflets. This is a fantastic feature. The original search did not retrieve any medical images but did retrieve some great patient information that would be very useful for clinicians to provide to their patients. Some of the resources that appeared with this search were from NHS Direct, eMedicine, and the Merk Manual. More about what resources are searched for Patient Information and Medical Images can be found in the lists under the About Us pages. A few consumer health information resources could be added to the list, but the reviewer applauds TRIP for incorporating patient information features into the database.

Advertising can be found throughout TRIP's Web pages. While advertising is frowned on, TRIP makes it clear on their Website that advertising is simply a way for the company to gain revenue as they no longer rely on subscription revenue. A team of clinicians, consumers, and staff review sponsored advertisements. TRIP also states that they are not by any means influenced by sponsored advertisers and/or pharmaceutical companies. This disclaimer can reassure users that they are entering a resource that is not biased and truly does abide by evidence-based principles.

Because TRIP is moving toward free access, the reviewer wondered what might be next for it. In September, Dean Giustini, reference librarian, Biomedical Branch Library, University of British Columbia, interviewed Jon Brassey, one of TRIP's cofounders. He asked about the move to free access and plans for TRIP. Brassey answered with a few ideas of interest. He discussed becoming compatible for personal digital assistants (PDAs), a related articles feature, and an “ask us a question” option. Although these are still only ideas, it is nice to see TRIP's keen interest in expanding this evolving resource [ 3 ].

The TRIP database has come a long way from its conception. The reader may wish to consult a 2002 review of the database [ 4 ]. The thought put into the design and improvements made to this resource prove that it is truly dedicated to the practice of evidence-based medicine.

• Brassey J. TRIP database: identifying high quality medical literature from a range of sources . New Rev Info Networking . 2005 Nov;  11 ( 2 ):229–34. [ Google Scholar ]
• Haynes RB. Of studies, syntheses, synopses, and systems: the “4S” evolution of services for finding current best evidence . Evid Based Med . 2001 Mar/Apr;  6 ( 2 ):36–8. [ PubMed ] [ Google Scholar ]
• Giustini D. The TRIP Database— open medicine, portal search . [Web document]. UBC Academic Search— Google Scholar Blog. [rev. 6 Oct 2006; cited 14 Nov 2006]. < http://Weblogs.elearning.ubc.ca/googlescholar/ >. [ Google Scholar ]
• Montori VM, Ebbert JO. TRIP database . Evid Based Med . 2002 Jul/Aug;  7 ( 4 ):104. [ Google Scholar ]

Trip Database

A smart, fast tool to find high quality clinical research evidence.

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Health Sciences Resources - Tutorials

• TRIP Database Pro

Link to Database

• TRIP Database [Pro] This link opens in a new window The TRIP (Turning Research into Practice) Database is a clinical search engine designed to allow clinicians to quickly find answers to their clinical questions using the best available evidence. The Library has licensed the professional version of TRIP, which has added features, and requires IP authentication However, the standard version is freely available. See: Sources searched by TRIP to see categories of publications searched by the TRIP database, including: systematic reviews, evidence based synopses, clinical guidelines, regulatory guidance, relevant journals, controlled trials, and other sources.
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The TRIP database

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• PMID: 18364695
• DOI: 10.1038/sj.ebd.6400572

The TRIP (Turning Research into Practice) database has an apparently simple goal: to allow health professionals to easily find the highest-quality material available on the Web to help support evidence-based practice.

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Trip Database Blog

Liberating the literature.

• Add Trip search to your site

If you are interested in adding a TRIP search box to your website then feel free to use the code below. This adds a great feature to your site and once there a search opens into a new window, meaning you don’t lose your users!

• How best to use AI in Trip?

We’ve been experimenting with AI for around a year and are confident enough with it to start to use it! However, a big uncertainty is how best to use it? By that I mean the technology is useless unless it supports our users! So, how best to support you?

We have created a short survey to help inform our decision making. Your opinion really matters and we really do listen. So, please, click here now to do the survey.

• Relevancy – a big change

Trip’s search is sensitive! If a user searches for ‘measles’ and the term is mentioned one time in a document of over 100,000 words, it is still returned as a result. This is not normally an issue if there are lots of results. However, if you select a facet with relatively few results (e.g. UK guidelines) then these very low relevancy results appear.

A real example, if you do a search for measles and go into European guidelines, there are 12 results. These are results 7-12:

• ESPEN expert statements and practical guidance for nutritional management of individuals with sars-cov-2 infection
• Autologous haematopoietic stem cell transplantation and other cellular therapy in multiple sclerosis and immune-mediated neurological diseases
• Hepatitis E Virus Infection
• Autoimmune Hepatitis
• Guideline on the Diagnosis and Treatment of Sclerosing Diseases of the Skin
• ECCO-ESGAR Guideline for Diagnostic Assessment in IBD Part 1: Initial diagnosis, monitoring of known IBD, detection of complications

Result 7, ESPEN expert statements and practical guidance for nutritional management of individuals with sars-cov-2 infection mentions measles 4 times in over 8,000 words. To us, this article is not about measles!

This issue has been frustrating us, and some of our users, for years. But we’ve now made a big step forward in removing low relevancy results from Trip. This feature has been released today – for Pro users only. Repeating the search for measles we now get 6,681 results overall and 4 European guidelines, previously it was 7,764 results and 12 European guidelines.

Overall, there was a 14% reduction in total results, but in European guidelines the reduction was nearly 67%. This is to be expected as guidelines are typically much longer documents and therefore have more scope for mentions of low relevancy terms.

And, if you don’t like this you can revert to the full results by a link at the foot of the results page:

I suspect this feature will not be noticed by many but it should dramatically change the quality of results in some situations. I am delighted to see this feature, it has bothered me for many years.

• We’ve moved

On the weekend we switched over from hosting the website on a dedicated server to ‘the cloud’. After 36 hours there have been no major incidents, just a few ‘niggles’.

This move has seen the site speed up, allow greater flexibility moving forward and saved us a reasonable amount of money – which we can use to improve the site.

• Using document clustering to show evolution of a topic area

Mpox (formerly known as Monkeypox) became a WHO designated Public Health Emergency of International Concern (PHEIC) between 23 July 2022 and 10 May 2023. Using the Carrot2 technology to cluster text ( as shown yesterday ) we thought it might be interesting to look at cluster pre and post the outbreak. So, we did two searches:

• Documents with Mpox or Monkeypox in the title published between 1980-2021. This yielded 104 results .
• Documents with Mpox or Monkeypox in the title published between 2022-2024. This yielded 679 results – showing a huge interest in the topic.

Or, looking at the top ten topic areas in a different format:

Small numbers pre-2022 but clear difference in topic areas. And, as an EBM source, nice to see a prominence for including systematic reviews.

Clustering search results using Carrot2

I’ve been wanting to use Carrot2 for ages and have finally got the chance… Carrot2, as it says on their website “ Carrot2 organizes your search results into topics. With an instant overview of what’s available, you will quickly find what you’re looking for “

So, two examples to show you. The first is for a search for ‘prostate cancer screening’ and we used Carrot2 to process just over 250 results and this is the output:

Treemap view

The second example is using just under 700 results for the search ‘arteriovenous malformation’

I can’t help feeling this topic clustering might be useful in a number of situations. For instance it’d be a nice way of refining your search or it could be useful to give you an overview of the topics covered. Let me know what you think either via comments or via email [email protected] .

Moving to the cloud

Since the start of 2024 the vast majority of our development time has been taken up with moving Trip onto ‘the cloud’. Currently we use a dedicated server, this has served us well but the server was getting old and needed replacing, so moving to the cloud was a no-brainer. We didn’t expect it to take quite so long and we’re currently having to reindex over 5 million documents. This process will be over in the next day or so and then it’ll be on to testing, which will hopefully not take long.

Broadly, users shouldn’t notice any difference. We’ve upgraded the underlying search software which has improved relevancy scoring so that might make the results order change – but I can’t imagine that being huge. I’ll update, if necessary, during testing.

Sorry, boring post saying we’re busy doing stuff, in the background, that you’ll not notice – but I wanted to be transparent. After that we can move on to forward facing developments.

Understanding simple searches – poll

Our previous post highlighted the fact that many of our top searches are for single concepts e.g. asthma, pregnancy, aspirin. In some situations this sort of search is fine but in others it might be imprecise.

If you use simple searches can you answer the following question please..:

If there is another reason, not listed above, please let us know. This can be done via comments or email: [email protected] .

Simple searches

UPDATE : please take our simple poll to help us understand simple searches (if you do simple searches)

One observation we’ve made over the years has been that many of the top searches (by frequency) are for single concepts e.g. asthma, diabetes, aspirin. This seems quite non-specific as the user possibly doesn’t want to know about, say, asthma generally. Perhaps they want to know about asthma diagnosis, asthma in children etc.

At Trip we want to help users get better results faster and we could take the above issue and try to solve it using techniques such as query expansion . However, the fact is we don’t fully understand the issue and we’ve suggested a solution (query expansion) straightaway! I have said the search is non-specific and the user doesn’t want to know about asthma generally . But there are many possible reasons for using such broad terms, for instance:

• They just want to get a feel for the literature
• They are new to the site and want to experiment with using the site
• They are not confident in creating searches that mirror their intention e.g. they may be wanting to know what is the most appropriate diagnostic tests for asthma in children and are not sure how to make a suitable search

There are probably other reasons as well – not really sure. So, leaping into a solution seems foolish. So, we should ask our users! My idea is that for a set number of searches (say every 10th search) we have a pop-up to take the user to a questionnaire to better understand their reasons for using Trip and if we note the search terms used we can cross-check that and see if there is a problem and from there what might the solution be.

I even asked ChatGPT to suggest some Qs and it came up with these:

Q1 Search Intent Understanding : “What is your primary objective when conducting a search with us (e.g., browsing for general information, seeking specific data or studies, looking for treatment guidelines)?”

Q2 Search Term Selection : “How do you decide on the search terms to use? Please select all that apply: a) Based on the specificity of the information needed, b) Using terms familiar to me, c) Repeating terms from educational or professional materials, d) Other (please specify).”

Q3 Experience with Search Outcomes : “How often do the search results meet your expectations in terms of relevance and specificity? Always, Often, Sometimes, Rarely, Never.”

Q4 Challenges in Formulating Search Terms : “What challenges, if any, do you encounter when deciding on which search terms to use? Lack of knowledge on the topic, uncertainty about which terms will produce the best results, other (please specify).”

Q5 Interest in Search Assistance Features : “Would you find it helpful if the search engine offered suggestions or guidance on refining search terms to improve result specificity? Yes, somewhat helpful, No, not necessary.”

These are really interesting questions (thank you ChatGPT) and I think that scrolling through the results will be incredibly useful. So, when we roll out the survey (probably in the next month or so) please consider completing it.

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The Fabulous Four

It tells the story of two friends who travel to be bridesmaids in a surprise wedding of their college girlfriend. It tells the story of two friends who travel to be bridesmaids in a surprise wedding of their college girlfriend. It tells the story of two friends who travel to be bridesmaids in a surprise wedding of their college girlfriend.

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