Category: Good Research Practice

 

1. Don’t think of time spent planning as time you could spend doing additional replicates of the procedure. Planned work moves so much faster and more fluidly that you will most likely save time, and won’t just produce a heap of bad data.
2. If you alter the protocol, don’t just scribble the alteration in your rough notes, but make sure the original protocol is adapted. Be sure you know which version of the protocol corresponds to which results. Otherwise, even if you don’t forget the changes entirely, you will forget whether they helped.
3. If there is a protocol already written, read it through beforehand, checking you understand each step.
4. Once you have a plan, don’t just follow it mindlessly. It is entirely possible you made a mistake, or something in the published protocol is not applicable to your work. Stay vigilant and make changes where necessary.

 

1. At the start of each protocol there should be a list of things you need to do before you start such as: booking machines or rooms, turning things on, setting things up, or getting things out of the fridge or freezer so they are ready to use.
2. Check you have all the reagents/equipment you need before you start, especially if they are communal, and check they have not expired.
3. The best plans don’t just give qualitative information like names, but also the quantities like timings, volumes and container sizes if applicable.
4. Sometimes kits come with a quick protocol. Make sure you read the full protocol first. The quick protocol is for people who already know what they are doing.
5. Plan experiments as early as possible, so that if you need to order things or book things it will not cause large delays.
6. Remember to factor your controls into your plans. Sometimes controls need extra equipment or reagents which you may not have on the day of the procedure if you don’t plan.

 
It is still irritating to think about all the time I wasted by forgetting to book machines or pre-warm reagents so they were ready when I needed them. My experiments would sit around waiting for people to finish, or for me to find new reagents as the ones I usually used were empty or expired. Whether these delays were responsible for bad data I will never know, but one of the main reasons planning leads to good data is that it helps you to keep the protocol as constant as possible between replicates.

 

1. Use a computer to make your plan (rather than a paper planner) as it will make it much easier to alter when you inevitably need to make changes. Excel or google calendar are possibilities.
2. You could make up your own colour code system like the example shown below. An important note is the number of large procedures you are doing, so that you can ensure you do not have too many on any single day. If you do, then you can probably rearrange one.
3. Each day, note down exactly what experiments you have to do for that day in your notebook, and then you can tick off the items as you complete them. This will stop you going home with an incomplete list.
4. Remember to allow time to analyse your data.

 
When I started planning not just my individual procedures but the time I allocated between each of them, the quality of my work greatly increased. It removed the stress of finding someone else had booked rooms or machines I needed, and allowed me to space the work out so I wasn’t working until midnight trying to fit three big procedures into a single day. I only wish I started doing this earlier.

 

1. Slowly increase the number of samples/patients/volunteers used in each research project. The first few times you will still be learning, and taking things in steps will reduce the chance of introducing error.
2. If you need something to work first time, then you can try doing a dry run.

 

This advice is especially important if the protocol involves specific incubation times. The more samples you use, the harder it is to keep to those times.

It took me longer to cotton on to this than it should have. In every experiment I did in the early years, my goal was always to obtain the maximum data from it possible.

I watched my supervisor run 50 samples perfectly spaced at the correct intervals, and logic followed that I could do it as well.

WRONG.

After a lot of dead cells, stress and time spent staring at a machine that looked like a 70s black and white TV, I realised I’d forgotten something that made the whole thing pointless.

Instead of wasting one or two samples, I’d depleted my cells to run the maximum amount, and had to wait for them to grow back before I could try again. But even if I had remembered everything, the experiment would still have been a waste because I was so inefficient at the steps that the first samples treated were sitting in the fluorescent dye for much longer than the last ones. Each sample had received significantly different treatment by the time they were ready to analyse.

I wasn’t ready to work with those numbers.

 

1. Once you have got the procedure working, repeat it several times on different days before you move on. Then, if you ever have to come back to it, you will remember how to do it well.
2. If the data are acceptable but not great, then don’t accept mediocrity. Think about how you could make the procedure better.
3. Sometimes it will become clear a procedure has failed before completion. In some cases, where the workload and cost of completing it are not high, it can be worth finishing and analysing it. You can learn a lot from the outcome of failed work, and it may help you to identify future mistakes.
4. Don’t compensate for not understanding the procedure by doing it more times. If you don’t know why it isn’t working, find out by researching the procedure. Otherwise you will just have lots of failures.

 

1. The fastest way to correct error is to change one parameter to several different values at once. Then if none of the values for that parameter yield good results, it is likely (assuming you picked a good range of values) that the test parameter was not the problem.
2. Check to see that none of your reagents have expired. This accounts for many failed experiments. If reagents are cheap make up a new batch before repeating failed experiments.

 

Whenever one of my experiments failed, and admittedly this was not an infrequent occurrence, I always felt rushed to do it again and present something useful to my supervisor as quickly as possible.

This was a huge mistake. It wasn’t until I was doing my first year report that I properly researched the problems with the experiment. After this, things went a lot more smoothly, but if I’d just done the research after the first experiment, I could have saved myself a lot of time.

The problem is not always immediately obvious, requiring more than a token alteration. Although it might feel like you’re wasting time, the opposite is true.

 

1. When experiments have to be done quickly because you are using living things or reacting chemicals which will begin to behave aberrantly if left too long, then you still shouldn’t rush. You are much more likely to have a negative effect on the experiment if you rush. Just move as quickly as you can without focusing on speed.
2. If you are doing cell culture or playing with small animals, rushing can be particularly detrimental. Your speed could hurt or damage them.

 

By the start of the third year of my PhD, the thought of weekend work always filled me with a cold dread. This wasn’t because I preferred to sit at home watching Red Dwarf and eating cheese puffs – though this remains unquestionably true – it was because whenever I worked at weekends I rushed it.

As consistent as my aversion to yellow snow, this resulted in me making obvious and highly avoidable mistakes, which meant I might as well have stayed at home (except for the health benefits of not eating the cheese puffs).

Not labelling things to save time was a key error. Most times I got away with it, but when I didn’t the feeling that I’d basically flushed my weekend down the toilet was not something I’d recommend.

 

1. When you are doing more than one procedure at a time, plan out the steps so that they do not overlap at any point.
2. Planning the time it will take you to complete protocols requires practice. At the start you will inevitably underestimate it. Therefore, if you are trying to fit several things all in the same day, allow extra time to do each bit.
3. If you need to do multiple procedures at once, organisation is the key. Don’t rush in to starting the first one or you might as well not bother. Plan them all thoroughly before starting, so that you know exactly what to do before you have to do it.

 

1. If you are planning to do multiple samples all at once, the first ones to be put in treatment might remain there for significantly longer than the last ones. This can be avoided by always starting with the same sample and staggering them, so that you only do a subset of samples at a time.
2. Use a lab timer. If you don’t have one, then ask for one. Don’t use your phone for this. While you might have a great app, you might also get something nasty on your phone. Then on your face.

 

I can remember weeks when my planner looked like a code book with the page lines cramming multiple sentences on top of each other. I had fallen victim to the fallacy that because I could fit the words describing the tasks in my calendar, it meant I could fit the time it would take to do them into the hours of a day.

When people were using equipment I needed, or it did not immediately work at the required speed, one experiment started to eat into another. Sometimes I was there well into the night, and generally the quality of the work was lower than if I had done them on separate days.

 

1. Even whilst you are performing the same technique over and over it is a good idea to read through the protocol before and after to make sure you are doing it right. If you find you are forgetting steps then highlight them, and specifically remind yourself about those steps before the next experiment.
2. Never assume that steps in established protocols are not necessary. The manufacturers have not added things just to make their procedures look more detailed. Of course, if you understand the protocol and you know that for your purposes specific steps are not needed, then that is different.

 

Once I’d organised myself and stopped trying to cram as much work into each experiment as possible the quality of my data improved. My main problem became that I paid less attention to the protocol because I assumed I knew it.

I rarely missed anything big – I was not such a fool to attempt a protocol I didn’t know pretty well without looking at it. Usually, the timing was a bit off or I didn’t shake mixtures, or I didn’t pre-prepare things that took time to prepare, but small things can still make big differences.

Fortunately, I’ll never know how much extra data I would have got if I’d followed this guideline, but I imagine it isn’t small.

 

Bob has designed a machine for detecting the number of aliens on other planets. He looks at Mars and as expected finds no aliens. Then he looks at two other planets and finds no evidence of alien life there either. Disappointed, he publishes that there are no aliens on either planet. It is only after the invasion that Bob realises the machine wasn’t turned on.

Bob had a negative control which was Mars, where he knew there were no aliens, and when his machine showed no aliens he knew he was not getting false positives. However, Bob had no positive control to show that his machine was actually capable of detecting aliens to rule out false negatives. Your repercussions will probably not be as bad as Bob’s, but if you have any desire for publication, even the lower impact journals will insist on these controls.

 

• Don’t just think about your controls on the day you carry out the procedure. You may well need extra components or additions which have to be ordered or pre-prepared. Like the rest of your protocol, this should be planned well in advance.

 

• Sometimes the most obvious controls are not the best. Try to avoid using substances you are unfamiliar with, or are unreliable. Use whatever substance or object is most likely to work. If your experiment worked but your controls did not, then your experiment is still void, and you will have no way of knowing what needs changing.

 

In the last section of my thesis I had a few experiments which I included to flesh it out a bit.

This was a costly and pointless decision simply because in the rush to complete them I had not used the relevant controls. The result was that my viva took an additional (fairly harrowing) hour where both examiners drilled me on what I could possibly conclude from these data. My answer, irrevocably, was that there was nothing. What else could I say?

No controls = no data.

I was forced to delete the entire section from my thesis. What a waste of time that could so easily have been a solid part of my project.

 

1. If you are collecting data from computer files then you could get someone in your lab to rename all the files for you with random letters, and note down which file corresponds to which letter. If you do this, be sure to have another version of each file saved somewhere else, in case your friend loses the key or makes a mistake. Always check afterward they have not made a mistake.
2. Not all experiments can be blinded. Sometimes you will remember which group the data comes from when you are analysing it, or some groups might be observably different as a result of the treatments used. It is inaccurate to say these data are blinded even if you tried.

 

I once blinded a study by wrapping bits of foil over the labels of my slides then lettering the foil and saving this letter as the file name when I analysed the data. I then went back to match the letters on the foil to the name of the treatment written on the slide beneath. I picked up the tray and it snapped, sending everything to the floor. Needless to say, my loosely attached bits of foil did not survive the journey unscathed. I was left with a bunch of broken slides, some lettered foil and the haunting certainty that I was going to have to start over.