Thursday, March 12, 2026

Subject Headings explained: Unlock the secret language of the databases

 

We have all been there. You type a perfectly reasonable search into one of the medical databases, hit enter, and find yourself overwhelmed by thousands of irrelevant database results — or frustrated that a search returns almost nothing. Something is going wrong — but what?

The answer is that you're speaking a different language from the database. Medical databases aren't like Google. They aren't built to interpret natural language and guess what you mean. They're built around a precise, controlled vocabulary — and unless you know how to use it, you can leave the best evidence buried.

This post will walk you through subject headings: what they are, why they exist, how to find the right ones, and how to use them to make your searches more comprehensive.


What Are Subject Headings?

Every article indexed in a medical database is read by a trained indexer — a human expert who assigns standardised labels to describe what that article is about. These labels are called subject headings, and they come from a fixed, carefully maintained list of approved terms.

Different databases use different systems:












Think of it like a library catalogue. If every librarian labelled books differently — one calling it "heart attack," another "myocardial infarction," another "MI" — finding everything on the topic would be more difficult. Subject headings solve this by insisting that every article about a heart attack gets the same tag, no matter what term the authors use.

All those terms — heart attack, MI, coronary thrombosis, cardiac infarction — feed into a single subject heading. Search the heading, and you capture them all.

Subject Headings vs. Keywords: What's the Difference?

A keyword search asks: "does this word appear somewhere in the article?"
A subject heading search asks: "was this article tagged as being about this concept?" These are very different questions.

Keywords (sometimes called free-text or text words) search for the word you type — in the title, abstract, or sometimes the full text. They are flexible and can pick up new terminology, but if you miss a synonym, you miss the evidence.

Subject headings search the controlled vocabulary tags assigned by the indexer. They're consistent, precise, and enormously powerful — but they require you to know the right heading to use.













***TOP TIP*** For a thorough search — especially a systematic review or comprehensive literature review — always use both subject headings and keywords together. Subject headings give you comprehensiveness; keywords catch what the subject headings miss. Combining both in a single search is the gold standard approach recommended and practiced by Information Specialists.


How to Find the Right Subject Heading

The good news: you don't have to memorise every single subject heading. Every database has a built-in thesaurus tool to help you find the right heading for your concept.

Step 1: Use the thesaurus or index tool

In Ovid MEDLINE or Ovid Embase, there's a dedicated Map Term to Subject Heading feature, or you can use the Term Finder tool.


                  

In CINAHL via EBSCOhost, use the CINAHL Headings browser. In PubMed, go to the MeSH Database (found under "Explore" in the menu). Type your concept in plain language and let the system suggest headings.

Step 2: Read the scope note

Every subject heading comes with a scope note — a brief definition explaining exactly what it covers and, crucially, what it does not cover. Always read this. It tells you whether a heading matches your concept or whether you need a different one (or several). It is also a good place to find alternative keywords

Step 3: Check the entry terms

Entry terms (sometimes called "see also" terms) are all the synonyms and variant terms that map onto this heading. If you can see your keyword in the entry terms list, you know you've found the right heading.
















Step 4: Look at the tree structure

Subject headings exist within a hierarchy — a branching tree from the very broad down to the very specific. Viewing the tree shows you what sits above your heading (broader concepts) and below it (more specific ones). This is invaluable for deciding how wide or narrow you want your search to be.















Step 5: Test with a known article

If you have a highly relevant article already, look at its subject headings in the database record. This is an excellent way to verify you have the right heading and often reveals additional headings you hadn't considered.


Broadening and Narrowing Your Search

One of the most powerful features of subject headings is the ability to control the scope of your search with surgical precision. You can deliberately cast a wider or narrower net depending on what your research question demands.

Exploding a heading — to broaden

Most databases allow you to "explode" a subject heading, which means your search automatically includes that heading and all the narrower terms beneath it in the hierarchy. This is enormously useful when you want to be comprehensive.

By exploding "Antidepressant Agent," a single subject heading retrieves articles about all antidepressants — including specific drugs — without you needing to list them individually. This is far more reliable than trying to think of every synonym yourself.












Focusing a heading — to narrow further

In some databases, particularly those using the Ovid interface, you can "focus" a subject heading (often marked with an asterisk, e.g. *Hypertension). This restricts results to articles where that heading is considered a major topic — meaning the article is primarily about that concept, rather than merely mentioning it in passing. This is useful when precision matters more than comprehensiveness.

Subheadings (qualifiers) — to narrow

Subject headings can be refined using subheadings (also called qualifiers) — these are standard modifiers that specify a particular aspect of the topic. When you select a subject heading, the database will typically offer you a menu of relevant subheadings to apply.

Common subheadings include:

  • /drug therapy - treatment with medications, e.g. Hypertension/drug therapy retrieves only articles about treating hypertension with drugs
  • /diagnosis - diagnostic aspects, e.g. Depression/diagnosis focuses on identifying and diagnosing depression
  • /surgery - surgical treatment, e.g. Breast Neoplasms/surgery limits to surgical management of breast cancer
  • /prevention & control – preventive measures
  • /epidemiology - incidence, prevalence, distribution
  • /adverse effects - unwanted effects of an intervention

Applying a subheading dramatically reduces noise while retaining highly relevant results.

The tree structure works in both directions. If your search is returning too little, move up the tree to a broader heading and explode it. If you're drowning in results, move down the tree to a more specific heading, or add a subheading to constrain the aspect you care about.

 

Differences Between Databases 

It's tempting, once you've learned MeSH, to assume the same headings will work in Embase or CINAHL. They won't — not exactly. Each database has its own vocabulary, and the headings, though often similar in concept, differ in terminology, hierarchy, and scope.

Embase's Emtree tends to have more granular terms for drugs and pharmacological interventions — useful if your search involves specific medications. CINAHL Headings include terms specific to nursing practice, patient care, and allied health that don't always exist in MeSH. If you are using multiple databases, you will need to translate your strategy into each database's own vocabulary. This can take some time but is a mark of a rigorous, comprehensive search.

Where to get help

if you need help contact the Clinical Librarians for help – we know the quirks of each thesaurus and can translate strategies reliably between databases.

Email: mtw-tr.clinical.librarians@nhs.net















The cognitive effects of dark chocolate: critically appraising a randomised trial

 

Disclaimer: this blog post has been created as an example of critical appraisal and doesn’t constitute medical advice. For expert advice, please speak to your health professional!

With Easter approaching, you may be thinking of chocolate eggs as an Easter treat. But did you know, some studies have explored the health benefits of chocolate eaten in small amounts regularly? In the library team, we encourage and provide training for critical appraisal of research studies. So, we decided to present a critical appraisal of a study about the cognitive effects of eating chocolate – how reliable is the research? Read on to find out…

Photo by Elena Leya on Unsplash

What is critical appraisal?

Critical appraisal is evaluating information to determine its trustworthiness and its relevance to a particular context. There are several published checklists that provide guidance for this evaluation, such as those produced by CASP, JBI and CEBM. Each checklist is usually tailored to a particular type of research study. So first we want to identify – what type of study is the article that we’re looking at?

The article

We’ll be looking at Sub-Chronic Consumption of Dark Chocolate Enhances Cognitive Function and Releases Nerve Growth Factors: A Parallel-Group Randomized Trial by Sumiyoshi et al., published in 2019. It’s a randomised trial so, if taking the CASP checklists as an example, the closest fit will be the checklist for randomised controlled trials.

The article explores the cognitive effects of regularly eating dark chocolate in the medium term, in comparison to white chocolate. If you’re a white chocolate fan, the bad news is that white chocolate contains fewer of the nutrients that have previously been found to have beneficial health effects. The nutrients specifically mentioned in this article are flavonoids – namely epicatechin and catechin - and methylxanthines - namely theobromine and caffeine - with regard to dark chocolate.

The researchers recruited participants to be divided into two groups: one group eating a set daily amount of dark chocolate and the other group eating a set daily amount of white chocolate, over 30 days. They were instructed not to eat any other chocolate during this time and not to exceed more than 3 cups of caffeinated drink per day. At the start of the trial, at the end of the trial and 3 weeks after the trial finished, the key measurements were taken. These included two cognitive tests: the Stroop Colour Word Test (modified), which uses names of colours printed in different coloured ink to test reaction to cognitive interference (disruption to usual thinking/processing), and the Digital Cancellation Test, which involves finding numbers amongst a sheet of digits, in order to measure attention, processing speed and executive functioning. The researchers also measured some physical attributes such as weight, BMI, heart rate and various chemicals in the blood.

Image by Willfried Wende from Pixabay


CASP Section A: Is the basic study design valid for a randomised controlled trial (RCT)?

This study isn’t claiming to be an RCT, rather a randomised trial. This is probably because the factors aside from chocolate consumption (like a participant having extra cake, biscuits etc.!) weren’t absolutely controlled, they were only given limited instructions to follow at home. The lack of control over these other factors could allow them to influence the findings – something to bear in mind.

On the other hand, participants were assigned to white chocolate or dark chocolate randomly using a computer generator, which is good practice. Randomisation is important because it minimises bias. For example, if the researchers were to allocate participants non-randomly, they might assign healthier-looking participants to dark chocolate for better likelihood of outcomes.

Another aspect to mention in terms of study design is the sample size. Twenty students were recruited for the study and two of them dropped out. This is a very small sample which means the reliability of results hasn’t been tested on enough people to be really trustworthy. It suggests that the results might not reflect the wider population. Seeing as the whole sample was made up of healthy undergraduate students (aged 20-31 years), this is even more the case. It means we don’t know for sure if the findings could be applied to other types of people with different ages or health conditions.

Image by mcmurryjulie from Pixabay


CASP Section B: Was the study methodologically sound?

Can you taste the difference between dark chocolate and white chocolate? Probably very easily yes, because white chocolate is much sweeter. So, in this study it wouldn’t have been possible to ‘mask’ or ‘blind’ the participants, to prevent them from knowing which chocolate intervention they received. ‘Blinding’ or ‘masking’ is normally carried out in RCTs when possible, because it minimises bias caused by participants knowing which type of treatment they’ve been given. For example, if a person knows that they are only receiving a placebo (‘dummy drug’) rather than a real drug, their mind and body could actually respond differently than if they believed they were receiving the real drug (known as the placebo effect).

That said, the participants weren’t told the exact objective of the study until after the course of chocolate was complete. In a way, this acted as an alternative form of masking, limiting the influence of participants’ knowledge on outcomes – unless of course they guessed what the experiment might be about! The article also says that the researchers were unaware of which participants were consuming which type of chocolate. This limits the potential bias from researchers’ knowledge of groupings.

Next, we want to know – were the characteristics of the participants allocated to dark chocolate similar to the participants allocated to white chocolate, at the start of the study? If one group was particularly sporty and fit, but the other wasn’t, that wouldn’t be a fair test!  The article tells us that there were no significant differences, so we’re assuming they distributed genders etc. evenly between groups. From the supplementary tables we can see that the weight, BMI, heart rate, blood composition etc. of the 2 groups didn’t vary significantly. This all means there’s low likelihood of any of these factors affecting the results. In that case, if the results show differences between groups, it’s more likely down to the type of chocolate.

Similarly, we want to know if the groups were treated any differently during the trial, besides being given different types of chocolate. Unless the participants had some sneaky extra chocolate or coffee, we know that they followed instructions to limit caffeine intake, refrain from other chocolate and avoid intense exercise. Again, this would prevent other factors influencing results. In other aspects, such as other food or drink intake while at home, we don’t know whether this varied between groups during the trial.

 

Image by Memed_Nurrohmad from Pixabay


CASP Section C: What are the results?

According to the scores from the cognitive function tests, there was some improvement in outcomes for the dark chocolate group, but results were mixed. For example, in the Stroop Colour Word Test, the dark chocolate group showed improved performance after starting the course of chocolate; but the white chocolate group also improved on the colour part of the test. In the third part of the Digital Cancellation Test, the dark chocolate group showed significant improved total performance, but not in the first and second parts of the test (neither did the white chocolate group). Basically, in this study, there are signs of a link between dark chocolate and improvement in cognitive tests, but the pattern isn’t really consistent or strong enough to be completely certain.

The measures of theobromine (a nutrient which previous studies have linked with cognitive performance) from blood plasma show it rose significantly in the dark chocolate group but not in the white chocolate group. Caffeine and other chemicals didn’t show such a significant increase. So, if dark chocolate does improve cognitive function, theobromine is probably at least one of the reasons behind it. Another contributing element that the authors describe is Nerve Growth Factor, which was also elevated in the dark chocolate group compared to the white chocolate group.

The researchers calculated the statistical significance of their results, to show whether the findings were likely to be due to chance (p-values). Overall, some of the measurements couldn’t be said to be statistically significant, but others were, including the increased number of correct answers for the Stroop test in the dark chocolate group.

Image by Mohamed Hassan from Pixabay
 

CASP Section D: Will the results help locally?

So, overall, what should we make of this study? If you are a healthy student (or young adult), aged 20-31, eating around 24g of dark chocolate with at least 70% cocoa every day (cocoa is the key ingredient, so higher percentages may make a difference!), it’s quite likely that your cognitive functioning would be higher than a similar person eating white chocolate (0% cocoa) daily.

However, it’s not so certain whether this applies to the same extent if you are of a different age etc. or if you consume a significantly lower or higher amount of the chocolate per day. There could be some anomalies in cognitive performance even if you mirrored the participants in the study. Meanwhile, you might not be particularly bothered about cognitive performance. You might be more interested in other health factors related to chocolate consumption, such as cardiovascular function, diabetes etc. which aren’t covered in this study. Some other studies have looked at these sort of aspects, both positive and negative (e.g. Morze et al. (2020), Amoah et al. (2022) and Yuan et al. (2017), to name just a few). It really is a case of weighing up the strengths and weaknesses of this study and other studies then coming to a critical judgement depending on your circumstances (and possibly professional advice - health professionals rather than confectionery professionals, that is!). 

Whatever your own conclusions, we hope you can enjoy the spring/Easter season!

(No chocolate was harmed in the making of this blog post…probably.)

We hope you found this article interesting. If you’d like to find further evidence about the health effects of chocolate, you could search on the NHS Knowledge and Library Hub using keywords such as ((chocolate OR cacao OR cocoa) AND (health OR wellbeing OR benefit* OR risk* OR effect* OR outcome*)).

Your library team are always happy to support with locating articles.