Next week One of the key EPIET objectives Cover all the ingredients that should go into the recipe
Temptation to be veryAmbitious Opportunity to identify gaps – ensure collect crucial information
Key investigators Main centres involved in study SC responsible for overseeing the conduct of the study Summary of main elements of the protocol
Statement of the problem, why are you undertaking the study? What is the PH importance of the disease or the condition that you want to study. Is it very common? Is it very serious? Is there a lot of public concern? Are there any gaps in existing knowledge that could aid the development of intervention measures? This could be in terms of risk factors for infection or identifying or effective control measures What is the principle question that you want to address? Important the study is focused. Not too many questions that you are trying to address. How will the results of your study contribute to the what we already know. How can the results be used in public health terms. An important part of the background – is a short focused review of the literature, identifying they key, most recent articles.
Next section is the OBJECTIVES. These should ANSWER the study question. Your objectives should be SMART: Specific = focused Measurable = Action Oriented = measure/describe something IN ORDER TO Realistic = Time oriented = Divided into primary and secondary objectives. PRIMARY - have to be achieved. THIS objective is the one the dictates how you undertake the study – in terms of study design and the methods used. SECONDARY – are of interest, but not so critical if not able to achieve.
Example 1: Principle and secondary objectives. Are these SMART? Specific = …Study population. Clear question. Non-specific would be “to identify risk factors for HCV infection”…no primary question Measurable = …could think of potential study designs to address this objective for example case-control design… Action oriented = why undertaking study? In order to inform HD prevention measures. Realistic = HCV prevalence pretty high in this population….probably realistic to undertake a study such as this. Time oriented =
Is this SMART? Specific = study population (IPD in Darfur), outcome = mortality Measurable = using survey Action-oriented = ? Lacking. Why are we looking at this objective. Realistic = seems quite ambitious….. Time-oriented = when is the study period?
Once you’ve defined your SMART objectives….you then need to turn your objectives into terms that allow you to undertake statistically test…..
So how do we do that practically? When we hypthothsis test, we usullay start with a null hypthosis – that there is not a significant effect – with our alternative hypothsis, we define the effect or the difference that we wish to detect. If we look at the objectives that we have already defined, our alternative hypothsis is: Analytical study: Outcome (incidence of HCV) Exposures (patients sharing machine and NOT sharing a machine)
Descriptive survey: Outcome of interest – crude mortality rate. Is the CMR above a certain critical threshold level….1/10 000….which Is indicative of a public health emergency…..highlights need to PH action.
What should the methods include? Describe what needs to be done to achieve your objectives – i.e. details of your study design. Need to include enough information on your methods to be able to judge whether or not they are actually valid…will they be able to answer the question you set out at the beginning.
Study design Type of study design cross sectional, longitudinal retrospective prospective , case-control, For example to answer your question regarding HCV amongst haemodialysis patients. Brief justification for the design chosen – why have you chosen a cohort study, rather than a case-control design to answer your question?? Study population What will be the study population? For your study on HCV in haemodialysis patients. Will it be all patients attending a particular clinic, or a series of clinics? The criteria that you will use to select and define the study population needs to be carefully defined. This needs to be linked to your original study objectives. You need to take into account various factors including the accessibility, co-operation and stability of your study population – which has important implications for follow up. Also the representativeness of your study sample – which will allow you to generalise your results. So you need to think carefully about which population you would like your results to be applied to. For example: nurses studies, physician cohort – have different issues regarding accessibility, co-operation, stability and implications for follow up. What will be your criteria for inclusion and exclusion. Time, place and person issues can help here. For example only including persons who were resident in a certain place in a certain period of time, can be used to define your study cohort.
What will be your sampling design? What will be the sampling frame? We heard earlier that the frame is the list of all the sampling units that you will sample from. It could be all the households in a certain town, or all the persons in a school etc…. What will be the method of sampling? Will it be simple, random sampling, cluster sampling, stratified sampling. We heard earlier about the indications for each…and their strengths and weaknesses. For any randomisation procedures – how will these be undertaken? Using software such as Epi-Info or random number tables or….. If you are not able to recruit a particular sampling unit – if it is not accessible (e.g. in certain parts of Darfur) or if a person refuses to take part in the study. What do you do then? Do you recruit a replacement – and if so how selected? …. It is also critical that you include sample size or power calculations. This should be based upon your primary objective. If there are important sub-group analyses – then these should be included too. The results of this will also give a clear indication of the feasibility of your study…particularly in terms of the resources that might be avilable – in terms time, persons and money…….
You need to include in very clear terms in the methods: Definitions of both the EXPOSURES and the OUTCOMES need to be clearly made. EXPOSURES can be of three types – risk factors e.g. particular food item, protective factors e.g. vaccination and (potential) confounding factors e.g. age, gender. You also need to define your OUTCOMES – i.e. clear case definition….and for a case-control study defining the control population….and how each will be selected. For each of these items – you need to define carefully the scale you will be using. E.g. for a case-control study on whether smoking causes lung cancer – you need to carefully define your exposure – which in this case is SMOKING. Are we only interested in active, current smoking? How will we quantify – cigarettes/day? What categories will we use? We also need to define our outcomes. What will be a case of lung cancer? How will we define our control population – who should provide an estimate of the exposure in the source population which gave rise to the cases.
Here, we have a practical example. A case-control study of looking for risk factors for infection amongst sporadic cases of Salmonella enteritidis. In this study, we have carefully defined our: Exposure: Who is a case: in terms of time, place, person and clinical features. How we will find our cases. Who will be in our control series: and thus provide an estimate of exposure in the source population which gave rise to the cases. Finally – how we will find our controls: using random selection.
Your methods also need to include a data analysis plan. This should be structured according to your principle and secondary objectives. You need to make sure that you test each of your hypotheses – and present the dummy (or pretend tables) to show how you will do this. State what statistical tests you will use – will you estimate the relative risk – with 95% ci. Or the OR. Matched or unmatched? Will this just be the crude or adjusted – what variables will potentially be included in your adjustment.
So your data analysis plan will define the indicators that you will need to present to reach your objectives. And also indicate the data that you will need to collect to meet those objectives. Once you have seen your data analysis plan – you may then realise the key importance of some sub-group analyses – and you can then refine your sample size estimates accordingly.
This is a dummy table for a retrospective cohort study of an otbreak of Salmonella in a day-care centre in Paris. You can clearly see the different exposures that will be examined. The number of ill cases and totals in the exposed and unexposed cohorts, the AR and finally the RR for each food item together with its associated 95% confidence interval.
Contrarily, this is a dummy table for a case-control study to look at risk factors for brucellosis infection in France. Here we can see our cases and controls and the numbers of each that will have been exposed and unexposed for a series of different exposures. From this can be derived the odds ratio of various exposures amongsts cases compared to controls.
Then in the methods, you need to describe how the data will be collected. HOW, BY WHOM, WITH WHAT. The HOW – could be by interview, observation of the study participant or review of medical records. The BY WHOM – will
Another important methods section is how will the data be handled? This should include: CODING of the data that you have collected. E.g. male = 0, female = 1 etc. When will this happen – during data collection, or after? Who will do it? 2. DATA PROCESSING – what software and hardware will be used? To create the data-base. When will the data be entered – during or after the study. Will there be single or double entry. 3. WHAT VALIDATION CHECKS and CLEANING will be undertaken. This could be e.g. range checks, outlying values etc etc.
One of the key messages is NO STUDY WITHOUT A TEST or PILOT…… This allows the team to look at the feasibility of the proposed sampling method, to test the data collection tool…in particular the questionnaire Try to outline how it will be tested….on whom? Where? When?
It is usually good practice to also give some thought already to the possible limitations of your study…this allows you to already think in the design phase how you might deal with these issues. In particular, you should think of potential biases in your study…you will hear in the next lecture by MARTA, what the various different biases are…these might be selection or information biases etc etc. There might be possibilities to correct them..either in your design – or possibly in your analysis. If not, you need to state how they might distort your results
The final part of your protocol outline, should include these key elements……
You need to give careful thought to the ethical dimensions of your study. Usually planned research studies should be submitted for review by an ethical committee… In this you will need to give thought to issues such will there be informed consent to take part in a study. How will this operate for children etc…. How will you ensure confidentiality? Will you anonymise records? How will data be stored? For how long? Which could be patient identifiable and potentially of a sensitive nature be protected.
There should be a section devoted to how the project will be managed. This should include all the participating institutes and persons. What each of their roles and responsiblites will be? Who will analyse the data, who will write it up? Who will own the data? Publication of report and articles – including issues such as authorship – which can often be contentious.
Another important part of the protocol is the study time-table. You can make one of these summaries in a GANTT chart (microsoft project), but also Excel. This should include the timing of all the elements from beginning to end – from planning the study, the pilot and the main study – data collection, analysis and presentation.
Resources….can be critical. It depends on the audience. At a minimum, it should include information on what possible sources of funding might be approached, or perhaps have been approached and the total sum involved. If this is an application to a funding agency – it will need to reasonable, quite detailed and justified – broken down into the various sections – person time consummables, overheads etc.
Key references should be included. Not an exhaustive list – just the key ones. Follow the recommended style….the default is Vancouver. More details available at….
In the appendix – you can include various other sections for reference for those who might be interested…..
What are the most common problems in a study protocol? One of the most common…is being overly ambitious…too many questions. It is really critical that you focus on a key question…the rest of the protocol should follow from that. Another is not enough attention being paid to the literature…what is already known and has been done before. You need to identify the gaps in knowledge that your study will address….. You need to give a strong justification for your study – why is your question of particular importance, what impact will your study have on public health. Remember – you will usually be competing for limited resources Your objectives need to be very clearly stated (SMART!!) Ensure your analysis is appropriate e.g. matched design = matched analysis. Give adequate description to each stage…particularly the methods And finally ensure you have a pilot.
13 studyprotocol 2006
How to write a study protocol
EPIET, Lazareto, Menorca
What is it?
• Describes every step of a study
• Answer relevant questions
- public health problem important?
- study question relevant to problem?
- objectives consistent with study
- study design achieves objectives?
- sufficient power?
- public health impact of the findings?
Why do it?
- can objectives be achieved?
- is study feasible?
• Ensure collect crucial information
• Lay down rules for all partners (quality)
• Obtain approval of ethical committee(s)
• Apply for funds
How to start ?
– good examples
– ideas from similar published studies
– ideas from colleagues
• Use a checklist of items to include
• Obtain requested format
– short, accurate, concise
• Main centres
• Steering committee
• Summary of the protocol
2. Background and justification
• Statement of problem, study justification
− importance of subject area
• magnitude, frequency
− gaps in existing knowledge
− principal question(s) to be addressed
− contribution of results to existing knowledge
− public health use of results
• Review relevant literature
• Should answer the study question
• Must be achieved
• Dictates design and methods
• Of interest, but not essential
• To determine if sharing a haemodialysis
machine with an HCV infected patient
is a risk factor for HCV infection.
• To identify failures in procedures
designed to prevent cross-infection
via haemodialysis machines
• To estimate the current mortality,
among the Internally Displaced
Population present in the
settlements at the time of the
survey, in each of the
three states of Greater Darfur region
• Translation of the objectives
in terms that allow statistical testing
• Translation of the objectives
in terms that allow statistical testing
“The incidence of HCV infection
in haemodialysis patients
in patients sharing machines
with HCV infected patients
in patients not sharing machines
with HCV infected patients”
• The current crude mortality rate
in IDPs in Darfur
is above 1 death per
10,000 per day
CMR > 1/10,000/day
• Procedures to achieve objectives
– what will be done?
• Information used to judge validity
• Study design
− cohort, case-control, cross-sectional…
− brief justification
• Study population
− criteria for inclusion and exclusion
− mechanisms of recruitment
− accessibility, follow up, representativeness
• Sampling design
− frame: district, household, persons,…
− method: random, cluster, stratified,…
− randomisation procedures
− replacement procedures (in case of refusal)
• Sample size
− sample size, power calculations based on
• Selection and definition
risk factors, protective factors, confounding factors
definition of case and the control group
• Items to be measured
– scales used
• e.g: smoking ? lung cancer
- smoking: definition, quantification, categories
- lung cancer: case definition, control group definition
CC study of sporadic cases
of Salmonella Enteritidis infection
– consumption of custard slices
– a person living in South-West Wales with
a laboratory confirmed infection due to S.Enteritidis
in June and July 1991
• Case finding
– through Public Health Laboratory; weekly notifications
– persons living in SW Wales in same neighborhood as
• Control finding
– random selection of people using telephone’s directory
Data analysis plan
• Structured in terms of objectives
• Hypotheses tested, dummy tables
• Statistical tests used, adjustment,
Data analysis plan
– indicators you will need to reach objectives
– data you will need to collect
• Better estimates of sample size
for analysis of sub groups
Food specific attack rates of Salmonella infection
in a day care centre, Paris, May 1999
fruit cake yes
fruit cake no
Case-control study, risk factors for brucellosis in France
Cases Controls OR
Exposed Unexp Exposed Unexp
15 – 25
26 - 60
− interview, observation, record review
• By whom
− interviewers: selection, training
− level of supervision
− questionnaires, recording materials
− questionnaires: self or interviewer administered,
face to face or telephone interview
• Procedures for taking samples
− during data collection, afterwards?
− by whom?
− software, hardware
• during the study, afterwards?
• single entry, double entry?
• Validation and data cleaning
Pilot studies, pre-testing
• No study without test
− Feasibility of sampling
− Data collection, measurement methods
• Describe how to test
• Identification of potential sources of biases
− selection bias
− information bias
• How to deal with them
− possibilities for correcting
− how they will affect the results
5. Ethical considerations
• Informed consent
• Confidentiality, record anonymity
• Data storage and protection
• Ethical committee
6. Project management
• Participating institutes and persons
• Responsibilities and tasks of each partner
• Data ownership
Planning/organisation of the study
• questionnaire design, recruitment, purchases
• obtain funding
• data collection
• presentation of results and write up
• Extent of this section depends on target
− available sources
− requested sources
• Keep budget
− well justified
• Limit number of references to key
• Follow recommended style
• Methodological appendices
• List of definitions
• Introductory letters to study participants
• Forms for informed consent
• Too ambitious: too many questions
• Insufficient attention to literature
• Poor justification
− why is it important to answer this question?
− what impact does it have on public health?
• Poorly formulated objectives
• Inappropriate analysis
• Inadequate description
• Absence of pilot