statistics assignment 代写

100%原创包过,高质量代写&免费提供Turnitin报告--24小时客服QQ&微信：273427

statistics assignment 代写
G Critical appraisal is the process of carefully and systematically

examining research to judge its trustworthiness, and its value

and relevance in a particular context.

G The Critical Appraisal Skills Programme aims to help

people develop the necessary skills to make sense of scientific

evidence, and has produced appraisal checklists covering

validity, results and relevance.

G Different research questions require different study

designs. The best design for studies evaluating the effectiveness

of an intervention or treatment is a randomised controlled

trial.

G Studies are also subject to bias and it is important that

researchers take steps to minimise this bias; for example, use of a

control group, randomisation and blinding.

G Odds ratios, risk ratios and number needed to treat are

methods of analysing results in order to determine if an

intervention is effective.

G Systematic reviews, which collect, appraise and combine

evidence, should be used when available.

statistics assignment 代写

What is...? series

Second edition

Evidence-based medicine

For further titles in the series, visit:

www.whatisseries.co.uk

What is

critical

appraisal?

Supported by sanofi-aventis

Date of preparation: February 2009

NPR09/1113

Amanda Burls MBBS
statistics assignment 代写

BA MSc FFPH Director

of the Critical

Appraisal Skills

Programme, Director

of Postgraduate

Programmes in

Evidence-Based

Health Care,

University of Oxford

Critical appraisal is the process of carefully

and systematically examining research to

judge its trustworthiness, and its value and

relevance in a particular context. It is an

essential skill for evidence-based medicine

because it allows clinicians to find and use

research evidence reliably and efficiently (see

What is evidence-based medicine?1for further

discussion).

All of us would like to enjoy the best

possible health we can. To achieve this we

need reliable information about what might

harm or help us when we make healthcare

decisions. Research involves gathering data,

then collating and analysing it to produce

meaningful information. However, not all

research is good quality and many studies are

biased and their results untrue. This can lead

us to draw false conclusions.

So, how can we tell whether a piece of

research has been done properly and that the

information it reports is reliable and

trustworthy? How can we decide what to

believe when research on the same topic

comes to contradictory conclusions? This is

where critical appraisal helps.

If healthcare professionals and patients are

going to make the best decisions they need to

be able to:

G Decide whether studies have been

undertaken in a way that makes their

findings reliable

G Make sense of the results

G Know what these results mean in the

context of the decision they are making.

What makes studies reliable?

‘Clinical tests have shown…’

Everyday we meet statements that try to

influence our decisions and choices by

claiming that research has demonstrated that

something is useful or effective. Before we

believe such claims we need to be sure that

the study was not undertaken in a way such

that it was likely to produce the result

observed regardless of the truth.

Imagine for a moment that you are the

maker of the beauty product ‘EverYoung’ and

you want to advertise it by citing research

suggesting that it makes people look younger;

for example, ‘nine out of every ten woman we

asked agreed that “EverYoung” makes their

skin firmer and younger looking.’

You want to avoid making a claim that is

not based on a study because this could

backfire should it come to light. Which of the

following two designs would you choose if

you wanted to maximise the probability of

getting the result you want?

A. Ask women in shops who are buying

‘EverYoung’ whether they agree that it

makes their skin firmer and younger

looking?

B. Ask a random sample of women to try

‘EverYoung’ and then comment on

whether they agree it made their skin

firmer and younger looking?

Study A will tend to select women who are

already likely to believe that the product

works (otherwise they would not be parting

with good money to buy it). This design thus

increases the chance of a woman being

surveyed agreeing with your statement. Such

a study could find that nine out of ten

women agreed with the statement even

when study B shows that nine out of ten

women who try the product do not believe it

helps. Conducting a study in a way that

tends to lead to a particular conclusion,

regardless of the truth, is known as bias.

Bias can be defined as ‘the systematic

deviation of the results of a study from the

truth because of the way it has been

conducted, analysed or reported’. Key

sources of bias are shown in Table 1,2while

further discussion can be found on the

CONSORT Statement website.3

When critically appraising research, it is

important to first look for biases in the study;

that is, whether the findings of the study

might be due to the way the study was

designed and carried out, rather than

reflecting the truth. It is also important to

remember that no study is perfect and free

from bias; it is therefore necessary to

What is critical appraisal?

What is

critical appraisal?

Date of preparation: February 2009

NPR09/1113

What is

critical appraisal?

systematically check that the researchers have

done all they can to minimise bias, and that

any biases that might remain are not likely to

be so large as to be able to account for the

results observed. A study which is sufficiently

free from bias is said to have internal

validity.

Different types of question require

different study designs

There are many sorts of questions that

research can address.

G Aetiology: what caused this illness?

G Diagnosis: what does this test result mean

in this patient?

G Prognosis: what is likely to happen to this

patient?

G Harm: is having been exposed to this

substance likely to do harm, and, if so,

what?

G Effectiveness: is this treatment likely to

help patients with this illness?

G Qualitative: what are the outcomes that

are most important to patients with this

condition?

Different questions require different study

designs. To find out what living with a

condition is like, a qualitative study that

explores the subjective meanings and

experiences is required. In contrast, a

qualitative study relying only on the

subjective beliefs of individuals could be

misleading when trying to establish whether

an intervention or treatment works. The best

design for effectiveness studies is the

randomised controlled trial (RCT),

discussed below. A hierarchy of evidence

exists, by which different methods of

collecting evidence are graded as to their

relative levels of validity.4When testing a

particular treatment, subjective anecdotal

reports of benefit can be misleading and

qualitative studies are therefore not

appropriate. An extreme example was the

fashion for drinking Radithor® a century ago.

The death of one keen proponent, Eben Byer,

led to the 1932 Wall Street Journal headline,

‘The Radium Water Worked Fine until His Jaw

Came Off.’5

A cross-sectional survey is a useful

design to determine how frequent a

particular condition is. However, when

determining an accurate prognosis for

someone diagnosed with, say, cancer, a cross-

sectional survey (that observes people who

have the disease and describes their

condition) can give a biased result. This is

because by selecting people who are alive, a

cross-sectional survey systematically selects a

group with a better prognosis than average

because it ignores those who died. The

design needed for a prognosis question is an

inception cohort – a study that follows up

a recently diagnosed patient and records

what happens to them.

It is important to recognise that different

questions require different study designs for

critical appraisal; first, because you need to

choose a paper with the right type of study

design for the question that you are seeking to

answer and, second, because different study

designs are prone to different biases. Thus,

when critically appraising a piece of research

it is important to first ask: did the researchers

use the right sort of study design for their

question? It is then necessary to check that

the researchers tried to minimise the biases

(that is, threats to internal validity) associated

with any particular study design; these differ

between studies.

The Critical Appraisal Skills Programme

(CASP) aims to help people develop the skills

they need to make sense of scientific

evidence. CASP has produced simple critical

appraisal checklists for the key study designs.

These are not meant to replace considered

thought and judgement when reading a paper

but are for use as a guide and aide memoire.

Date of preparation: February 2009

NPR09/1113

Selection bias

Biased allocation to comparison groups

Performance bias

Unequal provision of care apart from treatment under evaluation

Detection bias

Biased assessment of outcome

Attrition bias

Biased occurrence and handling of deviations from protocol and

loss to follow up

Table 1. Key sources of bias in clinical trials2

All CASP checklists cover three main areas:

validity, results and clinical relevance. The

validity questions vary according to the type

of study being appraised, and provide a

method to check that the biases to which that

particular study design is prone have been

minimised. (The first two questions of each

checklist are screening questions. If it is not

possible to answer ‘yes’ to these questions, the

paper is unlikely to be helpful and, rather

than read on, you should try and find a

better paper.)6

Effectiveness studies – the

randomised controlled trial

Validity

‘The art of medicine consists in amusing the

patient while nature cures the disease.’ –

Voltaire

The fact that many illnesses tend to get better

on their own is one of the challenges

researchers face when trying to establish

whether a treatment – be it a drug, device or

surgical procedure – is truly effective. If an

intervention is tested by giving it to a patient

(such an experiment is known as a trial), and

it is shown that the patient improves, it is

often unclear whether this is because the

intervention worked or because the patient

would have got better anyway. This is a well-

known problem when testing treatments and

researchers avoid this bias by comparing how

well patients given the intervention perform

with how well patients not given the

intervention perform (a control group).

Trials in which there is a comparison group

not given the intervention being tested are

known as controlled trials.

It is important that the intervention and

control groups are similar in all respects apart

from receiving the treatment being tested.

Otherwise we cannot be sure that any

difference in outcome at the end is not due to

pre-existing differences. If one group has a

significantly different average age or social

class make-up, this might be an explanation

of why that group did better or worse. Most of

the validity questions on the CASP RCT

checklist are concerned with whether the

researchers have avoided those things we

know can lead to differences between

the groups.

The best method to create two groups that

are similar in all important respects is by

deciding entirely by chance into which

group a patient will be assigned. This is

known as randomisation. In true

randomisation all patients have the same

chance as each other of being placed into

any of the groups.

If researchers are able predict which

group the next patient enrolled into the trial

will be in, it can influence their decision

whether to enter the patient into the trial or

not. This can subvert the randomisation and

produce two unequal groups. Thus, it is

important that allocation is concealed from

researchers.

Sometimes even randomisation can

produce unequal groups, so another CASP

question asks whether baseline characteristics

of the group were comparable.

Even when the groups are similar at the

start, researchers need to ensure that they do

not begin to differ for reasons other than the

intervention. To prevent patients’

expectations influencing the results they

should be blinded, where possible, as to

which treatment they are receiving; for

example, by using a placebo. Blinding of staff

also helps stop the groups being treated

differently and blinding of researchers stops

the groups having their outcomes assessed

differently.

It is also important to monitor the dropout

rate, or treatment withdrawals, from the trial,

as well as the number of patients lost to

follow-up, to ensure that the composition of

groups does not become different. In

addition, patients should be analysed in the

group to which they were allocated even if

they did not receive the treatment they were

assigned to (intention-to-treat analysis).

Further discussion can be found on the

CONSORT Statement website.3