If you are reading this page, there is a good chance you are a veterinary student, clinical resident, or postgraduate student who has been assigned the task of coming up with ideas for a research project as part of your training programme. Or you may be a practicing animal health professional looking to expand your career into the research realm. You may have already tried asking ChatGPT or one of it’s numerous rivals for help and are still feeling a little lost with turning those vague suggestions into a concrete research idea. This section provides an overview of strategies to spark some inspiration for research project ideas that you can later formulate into defined research questions and rationales in Phase 2.
Before you begin exploring research ideas, it’s helpful to be clear about your goals, constraints, and what support you have available. Ask yourself:
Don’t forget that this project is likely just a stepping stone in your journey toward becoming an independent researcher, or simply a taster to help you understand more about how research works. Choose an idea that will help you take the next step you’re aiming for, but set realistic boundaries around what you what you want to achieve so you don’t get stuck.
Practicing evidence-based medicine requires research to inform all stages of the consult process. In general, most clinical epidemiological studies will address one of the following focus areas:
Measuring how frequently a disease condition occurs in the population. This helps us get a sense of the likelihood of our patients having or developing disease.
Examples:
What proportion of dairy cows in spring-calving herds in the Waikato region develop clinical mastitis during the first 30 days of lactation?
What is the annual incidence of lameness in pasture-based sheep flocks managed under extensive grazing systems?
What proportion of companion cats presented to urban veterinary clinics are microchipped at the time of first vaccination?
Used to examine whether an exposure or characteristic is associated with increased or decreased risk of an outcome.
Examples
Are calves fed pooled colostrum at increased risk of failure of passive transfer compared with calves fed colostrum from their own dam?
Is indoor-only housing associated with a reduced risk of feline trauma compared with outdoor access in owned cats?
Do dogs fed raw meat–based diets have a higher risk of Salmonella shedding than dogs fed commercially cooked diets?
Used to evaluate the accuracy or usefulness of a diagnostic test or method.
Examples
In dogs with suspected hyperadrenocorticism, how accurately does the ACTH stimulation test diagnose disease compared with low-dose dexamethasone suppression testing?
In dairy cows with suspected subclinical mastitis, how well does on-farm California Mastitis Test performance agree with laboratory somatic cell count results?
In horses with distal limb lameness, does standing MRI detect soft tissue injury more accurately than ultrasonography when surgical findings are used as the reference standard?
Used when evaluating the effect of a treatment, management strategy, or intervention.
Examples
In weaned piglets, does zinc oxide supplementation compared with no supplementation reduce the incidence of post-weaning diarrhoea over four weeks?
In cats undergoing desexing, does pre-operative gabapentin compared with placebo reduce stress-related behaviours during hospitalisation?
In dairy herds, does selective dry cow therapy compared with blanket dry cow therapy reduce antimicrobial use without increasing mastitis rates in the subsequent lactation?
Used to examine how a factor influences future outcomes in individuals with a defined condition.
Examples
In dogs diagnosed with lymphoma, does lymphocyte count at diagnosis predict survival time over the following 12 months?
In dairy cows with retained fetal membranes, does time to placental expulsion predict subsequent reproductive performance during the breeding season?
In foals admitted for neonatal sepsis, do blood lactate concentrations at admission predict survival to discharge?
Used for qualitative research exploring perceptions, experiences, or meanings.
Examples
How do farmers perceive the practicality and economic impact of transitioning to once-a-day milking during periods of labour shortage?
What are the experiences of veterinary nurses managing compassion fatigue in high-euthanasia shelter environments?
How do dog owners describe their decision-making process when considering palliative care versus euthanasia for terminally ill pets?
When you’re starting to think about what kind of project you want to do, it helps to know the different ways that research questions can be explored. Some projects involve collecting new data, while others make use of information that already exists. Each approach has its own advantages, challenges, and time commitments, and the best choice will depend on your goals, timelines, and access to resources.
This is often considered the classic approach to research: where you design a prospective study, recruit participants or collect samples, and gather the data yourself. It gives you hands-on experience with study design, data collection, and practical problem-solving. If you’re interested in fieldwork, lab work, or understanding how data are generated, this approach can be both rewarding and highly educational.
However, this approach may not work well if you’re on a very tight timeline for completing your project as it can sometimes take months to years to get the study on place and enough data collected for analysis.
Another possibility you might not have considered is re-analysing previously collected data. Sometimes it is possible to come up with an idea for a study based on data which are already available instead of the more common approach of collecting it for yourself.
If you have the ability to access existing data sets, it might be possible to use the variables in a different way to answer a new research question. Sometimes existing data from two or more different sources can be merged to address a new issue. For example, merging national level disease incidence data with weather and climate data can be used to explore environmental risk factors for disease.
This approach may not be acceptable in all programmes. In some courses, the reason for assigning a research project requirement is to give the you practice doing laboratory or field research and therefore using somebody else’s data may be unacceptable. Always check the departmental policy on this type of research project with a faculty member.
Rather than collecting new data, you could consider performing a meta-analysis on a body of existing literature to answer a specific research question.
Meta-analysis refers to a statistical approach to integrating information from many different research studies. Because meta-analysis uses existing research, students will not have the opportunity to collect data on their own. However, meta-analysis can still be used to examine previously unexplored relationships, integrate new areas of research, and examine new techniques for performing meta-analysis.
For example, you might combine studies on the effectiveness of different antiparasitic treatments in dogs to assess which products consistently perform best across regions, breeds, or study designs.
There are obvious advantages to this approach in that you don’t have to worry about recruiting participants or collecting data, which can be ideal if you have to fit research around other study or work commitments. The main disadvantage is that it can be quite exhausting searching through the literature to find relevant studies and collate data in a format that can be analysed.
One method of carrying out research or developing a new theory is to produce a model of the phenomenon under study. In veterinary medicine, computer simulation models are often used to explore how diseases spread through populations of animals or to estimate the economic impact of performing different animal health interventions. A good simulation model can be used to demonstrate a theory and can also allow research which would be too expensive, dangerous, or impractical to actually perform.
If you like problem-solving, coding, or systems thinking, modelling can be a very engaging approach. The main disadvantage is that it can take time to learn how to code and you might not always have the right data available for the model to make realistic predictions.
Replication studies are surprisingly rare, yet incredibly valuable. Repeating a study either exactly as the previous researchers did or with a small variation can help confirm important results, challenge unexpected findings, and document changes over time. For example, you might repeat a study on parasite prevalence to see whether new treatments have shifted disease patterns.
Replication can be a great option if you want a clearly defined structure with room to apply your own analytical skills.
Sometimes a very interesting study can be achieved by simply applying a given design to a different type of sample. For example, a lot of veterinary studies are conducted using medical records from tertiary referral hospitals. Would the same trends hold true if the study was repeated at a first-opinion veterinary practice?
Care must be taken, however, in avoiding very specific populations. If, for example, you are interested in exploring disease issues in Maine Coon cats, you should consider the prevalence of the breed and associated difficulties in locating a sample before making a final decision on their topic. No matter how common a particular type of subject may seem to be, recruiting subjects when they are needed may be difficult.
It is also possible to obtain interesting findings by testing old ideas in new situations or with different samples.
One of the easiest ways to spark research ideas is to spend time reading broadly across veterinary and animal health journals. Exposure to different topics, methods, and debates often triggers new questions or helps you see where gaps in the evidence might be
Some general clinical and research journals worth browsing include:
There are also many discipline-specific journals covering fields such as surgery, internal medicine, anaesthesia, pathology, nutrition, ophthalmology, oncology, dermatology, and more. Reading across a wide range of topics even outside your initial area of interest can help you spot patterns, limitations, or opportunities that lead naturally to a research idea.
As you read, try evaluating each article with a critical eye by looking for the following:
These are also termed research hypotheses. Within the introduction to the journal article, the researcher starts with a broad area of interest that is gradually refined down to a specific issue. In some cases, there will be concluding sentences stating the research question(s) usually in the format “this study will test the hypotheses” or “the objectives of this study were”. In other articles with a more narrative approach, it can be more difficult to identify the specific research questions. Sometimes reading the discussion or conclusion section first will shed more light on the purpose of the study more readily than wading through the introduction.
This is the methodology being used to address the research topic. Consider if the same topic could be approached from a different theoretical perspective. For example, one research study may have used logistic regression models to explore the association between lifestyle risk factors and obesity in companion animals. You could apply a different statistical methodology such as principal component analysis to better sort out the relationships between risk factors.
Briefly note the research design used in the study. This might include surveys, observational studies, or experimental studies. Consider if you could address the research topic using a different or stronger study design. For example, a retrospective case-control study on risk factors in calves may have found an association between the frequency of cleaning bedding material and the development of diarrhoea. The student could potentially design a prospective cohort study to provide stronger evidence of a causal relationship.
These are the techniques or approaches being used collect data about the study participants. Often many research studies in veterinary medicine use very simple measures to describe behaviours of biological phenomena. For example, a cross-sectional study looking at risk factors for the introduction of infectious diseases to a herd may ask simple survey questions like “Do you disinfect vehicles entering the farm?”. If that was found to be a significant risk factor, you could design a new survey to collect more information about the vehicle disinfection practices such as the cleaning agent used, contact time of the cleaning agent, and which specific vehicles are targeted for disinfection.
In the discussion and conclusion section of journal articles, most authors will include a brief outline of the path that future research should explore or gaps in existing research that still need to be addressed. In some cases, it can be relatively easy to adapt these ideas into a suitable research topic.
Even if your reading does not immediately lead to a project idea, it is not a wasted effort. You will build familiarity with research methods, analytical approaches, and scientific writing. You will also start to notice patterns in how studies are structured, how results are presented, and how arguments are built, all of which will help you plan and communicate your own work more effectively.
Sometimes research ideas do not come easily, and that is completely normal. The following sections offer suggestions that can help you identify a topic, an approach, or a general area of interest that you can then refine with support from a supervisor.
Based on your everyday experiences working in veterinary clinics or interacting with animals at home, you will often come up with questions such as “What caused that particular animal to get sick?” or “Is it true than a particular breed will respond better to a treatment?”. This relationship may in itself be an interesting research question to examine. Once the relationship has been established, then you can try to explore causality with a well-designed research study.
When drawing on experiences from everyday life, you should always do a careful literature search to determine if the idea is original or a replication (this refers to duplication of an existing study). Whereas in some circumstances a replication is a worthwhile project, in others it might not meet the requirements that the research study make an original or innovative contribution. You should confirm the requirements for your particular programme. A literature search may also allow you to locate other studies that support the approach and/or methodologies they might be planning to use in the research.
A hobby, sport, or other special interest may also be a source of ideas. For example, if you are interested in equestrian sports, you might be motivated and have the contacts to explore equine behaviour, or examine the outcomes of a riding for the disabled programme.
You should also be careful about choosing a project topic that you feel strongly about on a personal level. When a topic is closely tied to your own experiences or beliefs, it can become difficult to stay objective. You may find yourself wanting to add extra analyses, consider additional angles, or keep refining the project long past what is realistic for the scope or timeframe. Strong personal investment can also make it harder to receive feedback, because suggestions or critiques may feel like they are directed at you rather than at the work itself.
For example, a student who is passionate about animal welfare and chooses a project on food-animal production may interpret technical feedback as a challenge to their values, even when the intention is simply to strengthen the research. Being aware of this risk can help you choose a topic that allows you to stay open, balanced, and able to engage constructively with your supervisor and the research process.
Many practices in clinical veterinary medicine and animal care rely heavily on underlying assumptions, which have not always been tested. You may be able to make an important contribution by exploring untested assumptions. If an assumption proves to be invalid, you could suggest modifications which, in turn, would have to be tested in subsequent research projects. This could be particularly useful if you are a Masters student looking to continue into doctoral research.
If you decide to think about your project as a means-ends, start by being clear about the goal you want to achieve and the tools you have available. Your goal might be to test a theory, explore a relationship, or simply describe something in a population. Your tools might include information you already have, research methods you know how to use, existing measurement techniques, software, or other resources.
Once you have listed your goal and your tools, ask yourself a few practical questions. Can the tools I have be used to achieve this goal? What sequence of steps would I need to follow to complete the project? While working through this, you may realise that one of the tools you need is missing. If that happens, you will need to decide whether to find or develop the missing tool or to adjust your planned steps so they match the resources you already have.
Interesting parallels can sometimes be found in areas that seem completely unrelated to your topic. One useful approach is to ask yourself how someone from a different background might view the same problem. For example, how would a sociologist, engineer, computer scientist, biologist, physician, or even a client or patient think about this issue? You can also try viewing the problem through a different theoretical lens. Shifting perspectives in this way can help you see new angles, generate creative questions, and uncover ideas you might not notice when staying within a single discipline.
You may also have specific career goals that can guide the type of project you choose. For example, if you are interested in clinical teaching, you might explore a question in veterinary education. If you see yourself working in regulatory medicine, you could look at topics related to national disease surveillance or food safety. The deeper understanding you gain through this kind of project can strengthen future applications for jobs or professional programmes.
If you are planning to pursue a clinical residency, it makes sense to choose a project that aligns with the specialty you hope to enter. Similarly, if you are an undergraduate or masters student considering a doctoral degree, this is a good opportunity to gain practical research experience and decide whether a particular field is the right fit before committing to long-term study.
Veterinary researchers utilize many tools for measuring animal health and behaviour. When starting research in a new area, you should consider whether the measurement techniques are appropriate and exhibit acceptable reliability and validity. An example from veterinary research is the use of standard biosecurity questions to assess the risk of disease being introduced onto farm. There is a strong need for research studies to determine whether the answers provided by farmers actually match the true biosecurity practices implemented on the farm. Borrowing a standard tool and applying it in a novel manner can resolve contradictions and clarify ambiguities in existing research.
After you have reviewed the relevant research, you may start to see clear opportunities for new work. This could involve developing new research methods, creating better ways to measure animal health variables, or refining tools that already exist. Once you can see the path that previous researchers have taken, you can investigate the next logical step or explore what might happen further along that path. In either case, you are contributing something new and helping to move the field forward.
If you have tried the strategies above and still cannot come up with a research idea, do not panic! There are still several other approaches you can use to get unstuck.
Try brainstorming
Brainstorming involves gathering a small group and generating as many ideas as possible without judging them. During the session, the goal is quantity rather than quality. Every idea is accepted, and nothing is critiqued until later. If a few of you are struggling to choose a topic, joining forces for a group brainstorming session can be surprisingly productive.
Take a break
Staring at a blank screen rarely produces inspiration. Give yourself permission to step away for a short while. A few minutes, a few hours, or even a couple of days can give you the perspective you need. A break does not have to mean doing nothing. Working on something else, going for a walk, or chatting with someone about your general interests can often spark an idea. Sometimes people who know nothing about your area can ask simple questions that lead you in a new direction.
Talk to faculty
Do not hesitate to reach out to faculty members for advice, suggestions, or help refining your thinking. You will get far more out of these conversations if you prepare in advance. It helps to identify a broad area you are interested in, read a few papers to get a sense of the existing research, and think about a specific angle you might want to explore. It is also useful to reflect on your preferences for qualitative or quantitative approaches, any methods you are interested in learning, and the kinds of measures commonly used in that area.
Just as writers expect to revise a manuscript several times, you should expect that your research idea will also go through several rounds of refinement. Early ideas often need reshaping before they become a viable proposal, and sometimes running a small pilot or testing a method helps you see what will and will not work. An idea that seems unpromising at first can often be reworked into something strong.
It can help to write a one-page summary of your idea before meeting with your supervisor. You might organise it as a simple outline that starts broad and narrows to a specific question, or as a visual map showing how your ideas connect. If your original concept turns out to be impractical, these notes may contain a related idea that is more feasible.
When you plan a study, always think ahead to how the data will be analysed. If you skip this step, you may end up with data that cannot answer your research question or that cannot be analysed in a meaningful way. Talk through the analytical approach with your supervisor in detail. It is not enough to say you will use a particular method. You should be able to specify which variables you plan to collect, how those variables will be used in the analysis, and what role each will play.
It is also helpful to think through possible outcomes before you start collecting data. A study could produce results that are not statistically significant, results that match your expectations, or results that go in an unexpected direction. Thinking about how you would interpret each scenario can help you identify additional variables you should collect and may even alert you if the study design is likely to produce uninterpretable results. If the risk of a dead end seems high, it may be better to change the topic or the design at this early stage.
Alongside methodological planning, you also need to think about the practical realities of completing your project. Your idea must fit within the time and resources available in your programme. For example, a prospective field survey that requires biological samples, owner questionnaires, and ethics approvals may take months to set up. This sort of project may be unrealistic for a short research placement.
Instead of discarding the idea, you might consider alternative approaches. Historical medical records from the same clinic could provide the information you need without the delays involved in organising new data collection. Keep in mind that accessing existing records can also take time, so factor this into your planning.
It is always wise to talk to someone who has completed a similar project. Learning from their experience can help you anticipate potential roadblocks and avoid common pitfalls.
Every institution has its own policies around ethical approval, and you must follow the guidelines set by your department and your supervisor. Think carefully about whether your study raises any ethical or legal concerns. For example, it would not be appropriate to ask veterinarians about illegal or off-label drug use if those answers could place them at risk of prosecution. It would also be unacceptable to design a study that requires participants to engage in illegal behaviour.You may also need to consider social or political sensitivities, depending on your topic.
2. Question Development
Advancing Animal Care through Shared Learning