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سفيرة الغد
2-the different treatments people use for one illness
William CheseldenThe 18th century surgeon William Cheselden was aware of the 'dissimilar groups' problem when surgeons were comparing their respective mortality rates after operations to remove bladder stones. Cheselden pointed out that it was important to take account of the ages of the people treated by different surgeons. He drew attention to the fact that mortality rates varied with the patients’ ages (Cheselden 1740) - older patients were more likely than younger patients to die. This meant that, if one wished to compare the frequency of deaths in groups of patients who had undergone different types of operation, one had to take account of differences in the ages of the patients in the comparison groups.
Comparing the experiences and outcomes of patients who happened to have received different treatments in the past is still used today as a way of trying to assess the effects of treatments. The challenge is to know whether the comparison groups were sufficiently alike before receiving treatment. This is illustrated by attempts to assess the effects of hormone replacement therapy (HRT) by comparing the illness experiences of women who had used HRT with those of other women who had not used it. As subsequent analysis of fair tests of HRT showed, trying to assess the effects of treatments in retrospect in this way can sometimes be dangerously misleading (McPherson 2004).
It is rarely possible to be completely confident that comparison groups selected from people who have been given one treatment in the past are comparable in all the respects that matter with people who have more recently received an alternative treatment. This is the case even if some information about the patients who have received different treatments is available (such as their ages, or their past history of illness). Other information that may be of great importance (such as the likelihood of spontaneous recovery) may simply not be available.
A better approach is to plan the treatment comparisons before starting treatment. For example, before beginning his comparison of six treatments for scurvy on board HMS Salisbury in 1747, James Lind took care to select patients who were at a similar stage of this often fatal disease. He also ensured that they had the same basic diet and were accommodated in similar conditions. These were factors, other than treatment, that might have influenced their likelihood of recovering (Lind 1753). Comparable efforts must be made to try to ensure that treatment comparison groups are composed of similar people.
Unbiased assembly of treatment comparison groups using alternation or randomization
Although Lind took care to ensure that the sailors in his six comparison groups were alike, he didn’t describe how he decided which sailors would receive which of the six treatments. There is only one way to ensure that treatment comparison groups are setup in such a way that they are similar in all the ways that matter, known and unknown. This is by using some form of chance process to assemble treatment comparison groups, so avoiding biased selection for different treatments before starting treatment.
One hundred years after Lind, an army doctor, Graham Balfour, illustrated how this could be done in a test to see whether belladonna prevented scarlet fever in children. In the military orphanage for which he had responsibility, he used alternation - “to prevent the imputation of selection” - to decide which boys would receive and which would not receive belladonna (Balfour 1854). Alternation is one of several unbiased methods for assembling similar treatment comparison groups before giving the treatments being compared. During the first half of the 20th century, there are many examples of treatment comparison groups being assembled using alternation or rotation (for example Hamilton 1816; MRC 1944), or by drawing lots (Colebrook 1929) – for example, using dice (Doull et al. 1931), coloured beads (Theobald 1937), or random sampling numbers (Bell 1941; MRC 1948; MRC 1950; MRC 1951). This ‘random allocation’ is the sole, but crucially important, feature of the category of fair tests referred to as ‘randomized’. A random (as distinct from haphazard) allocation means that the chances of something happening are known, but the results can not be anticipated on any particular occasion. So for example, if a coin is used to randomize, the chance of getting heads is 50%, but it is impossible to know what the result of a particular toss will be.
As illustrated in the essay available by clicking here, casting or drawing lots is a time-honoured way of making fair decisions. These methods help to ensure that comparison groups are not composed of different types of people. Known and measured factors of importance, like age, can be checked. However unmeasured factors that may influence recovery from illness, such as diet, occupation, and anxiety, can be expected to balance out on average. If you would like to see how random allocation generates similar groups of people .
As experience of using alternation and random allocation for unbiased assembly of groups of patients for comparing different treatments became more widespread, it became clear that strict adherence to allocation schedules was required to avoid biased creation of treatment comparison groups (MRC 1934). The risk of biased allocation can be abolished if treatment allocation schedules are concealed from those making decisions about participation in treatment comparisons – in brief, to prevent them cheating, and thus biasing the comparisons (MRC 1944; MRC 1948; MRC 1950; MRC 1951).
Failure to do this can result in unfair tests of treatments. Take, for example, two very different ways of treating people experiencing dizzy spells because of partially blocked blood vessels supplying their brains. Treatment for this condition can be important because these people experiencing dizzy spells for this reason are at increased risk of suffering a stroke, which may leave them disabled, or even kill them. One of the treatments for the dizzy spells involves taking aspirin to stop the blockage getting worse; the other involves a surgical operation to try to remove the blockage in the blood vessel.
A fair comparison of these two approaches to treating dizzy spells would involve creating two groups of people using an unbiased allocation method (like randomization). The comparison would thus begin by comparing two groups of patients who were alike, and go on to compare their respective frequencies of subsequent strokes. But if the frequency of strokes in the surgically treated group was only recorded among patients who had survived the immediate effects of the operation, the important fact that the operation itself can cause stroke and death would be missed. This would result in an unfair comparison of the two treatments, resulting in a biased and misleadingly optimistic picture of the effects of the operation. Like would not be being compared with like.
The principal comparison in randomized trials must be based, as far as possible, on all the people assigned to receive each of the treatments compared, without exceptions, and in the groups to which they were originally assigned. If this principle is not observed, people may receive biased information about the overall effects of treatments.
المراجع References
Balfour TG (1854). Quoted in West C. Lectures on the Diseases of Infancy and Childhood. London, Longman, Brown, Green and Longmans, p 600.
Bell JA (1941). Pertussis prophylaxis with two doses of alum-precipitated vaccine. Public Health Reports 56:1535-1546.
Cheselden W (1740). The anatomy of the human body. 5th edition. London: William Bowyer.
Colebrook D (1929). Irradiation and health. Medical Research Council Special Report Series No.131.
Doull JA, Hardy M, Clark JH, Herman NB (1931). The effect of irradiation with ultra-violet light on the frequency of attacks of upper respiratory disease (common colds). American Journal of Hygiene 13:460-77.
Hamilton AL (1816). Dissertatio Medica Inauguralis De Synocho Castrensi (Inaugural medical dissertation on camp fever). Edinburgh: J Ballantyne.
Lind J (1753). A treatise of the scurvy. In three parts. Containing an inquiry into the nature, causes and cure, of that disease. Together with a critical and chronological view of what has been published on the subject. Edinburgh: Printed by Sands, Murray and Cochran for A Kincaid and A Donaldson.
McPherson K (2004). Where are we now with hormone replacement therapy? BMJ 328:357-358.
Medical Research Council Therapeutic Trials Committee (1934). The serum treatment of lobar pneumonia. BMJ 1:241-245.
Medical Research Council (1944). Clinical trial of patulin in the common cold. Lancet 2:373-5.
Medical Research Council (1948). Streptomycin treatment of pulmonary tuberculosis: a Medical Research Council investigation. BMJ 2:769-782.
Medical Research Council (1950). Clinical trials of antihistaminic drugs in the prevention and treatment of the common cold. BMJ 2:425-431.
Medical Research Council (1951). The prevention of whooping-cough by vaccination. BMJ 1:1463-1471
Parry CH (1786). Experiments relative to the medical effects of Turkey Rhubarb, and of the English Rhubarbs, No. I and No. II made on patients of the Pauper Charity. Letters and Papers of the Bath Society III:407-422.
Silverman WA, Chalmers I. Casting and drawing lots. The James Lind Library ( www.jameslindlibrary.org) .
Theobald GW (1937). Effect of calcium and vitamin A and D on incidence of pregnancy toxaemia. Lancet 2:1397-1399.
30-12-2022 - 10:46 am
- Differences between the people compared
- Comparing different treatments given to groups of people
- Avoiding biased losses from treatment comparison groups
2-the different treatments people use for one illness
Differences between the people compared
Comparing different treatments given to groups of people
Treatment comparisons usually entail comparing the experiences of groups of people who have received different treatments. If these comparisons are to be fair, the composition of the groups must be similar – so that like will be compared with like. If those who receive one treatment are more likely anyway to do well (or badly) than those receiving an alternative treatment, this allocation bias makes it impossible to be confident that outcomes reflect differential effects of the treatments, rather than the effects of nature and the passage of time.William CheseldenThe 18th century surgeon William Cheselden was aware of the 'dissimilar groups' problem when surgeons were comparing their respective mortality rates after operations to remove bladder stones. Cheselden pointed out that it was important to take account of the ages of the people treated by different surgeons. He drew attention to the fact that mortality rates varied with the patients’ ages (Cheselden 1740) - older patients were more likely than younger patients to die. This meant that, if one wished to compare the frequency of deaths in groups of patients who had undergone different types of operation, one had to take account of differences in the ages of the patients in the comparison groups.
Comparing the experiences and outcomes of patients who happened to have received different treatments in the past is still used today as a way of trying to assess the effects of treatments. The challenge is to know whether the comparison groups were sufficiently alike before receiving treatment. This is illustrated by attempts to assess the effects of hormone replacement therapy (HRT) by comparing the illness experiences of women who had used HRT with those of other women who had not used it. As subsequent analysis of fair tests of HRT showed, trying to assess the effects of treatments in retrospect in this way can sometimes be dangerously misleading (McPherson 2004).
It is rarely possible to be completely confident that comparison groups selected from people who have been given one treatment in the past are comparable in all the respects that matter with people who have more recently received an alternative treatment. This is the case even if some information about the patients who have received different treatments is available (such as their ages, or their past history of illness). Other information that may be of great importance (such as the likelihood of spontaneous recovery) may simply not be available.
A better approach is to plan the treatment comparisons before starting treatment. For example, before beginning his comparison of six treatments for scurvy on board HMS Salisbury in 1747, James Lind took care to select patients who were at a similar stage of this often fatal disease. He also ensured that they had the same basic diet and were accommodated in similar conditions. These were factors, other than treatment, that might have influenced their likelihood of recovering (Lind 1753). Comparable efforts must be made to try to ensure that treatment comparison groups are composed of similar people.
Unbiased assembly of treatment comparison groups using alternation or randomization
Although Lind took care to ensure that the sailors in his six comparison groups were alike, he didn’t describe how he decided which sailors would receive which of the six treatments. There is only one way to ensure that treatment comparison groups are setup in such a way that they are similar in all the ways that matter, known and unknown. This is by using some form of chance process to assemble treatment comparison groups, so avoiding biased selection for different treatments before starting treatment.
One hundred years after Lind, an army doctor, Graham Balfour, illustrated how this could be done in a test to see whether belladonna prevented scarlet fever in children. In the military orphanage for which he had responsibility, he used alternation - “to prevent the imputation of selection” - to decide which boys would receive and which would not receive belladonna (Balfour 1854). Alternation is one of several unbiased methods for assembling similar treatment comparison groups before giving the treatments being compared. During the first half of the 20th century, there are many examples of treatment comparison groups being assembled using alternation or rotation (for example Hamilton 1816; MRC 1944), or by drawing lots (Colebrook 1929) – for example, using dice (Doull et al. 1931), coloured beads (Theobald 1937), or random sampling numbers (Bell 1941; MRC 1948; MRC 1950; MRC 1951). This ‘random allocation’ is the sole, but crucially important, feature of the category of fair tests referred to as ‘randomized’. A random (as distinct from haphazard) allocation means that the chances of something happening are known, but the results can not be anticipated on any particular occasion. So for example, if a coin is used to randomize, the chance of getting heads is 50%, but it is impossible to know what the result of a particular toss will be.
As illustrated in the essay available by clicking here, casting or drawing lots is a time-honoured way of making fair decisions. These methods help to ensure that comparison groups are not composed of different types of people. Known and measured factors of importance, like age, can be checked. However unmeasured factors that may influence recovery from illness, such as diet, occupation, and anxiety, can be expected to balance out on average. If you would like to see how random allocation generates similar groups of people .
As experience of using alternation and random allocation for unbiased assembly of groups of patients for comparing different treatments became more widespread, it became clear that strict adherence to allocation schedules was required to avoid biased creation of treatment comparison groups (MRC 1934). The risk of biased allocation can be abolished if treatment allocation schedules are concealed from those making decisions about participation in treatment comparisons – in brief, to prevent them cheating, and thus biasing the comparisons (MRC 1944; MRC 1948; MRC 1950; MRC 1951).
Avoiding biased losses from treatment comparison groups
After taking the trouble to ensure that treatment comparison groups are assembled in ways that ensure that like will be compared with like, it is important to avoid bias being introduced as a result of selective withdrawal of patients from the comparison groups. As far as possible, group similarity should be maintained by ensuring that all the people allocated to the treatment comparison groups are followed up and included in the main analysis of the test results – a so-called ‘intention-to-treat’ analysis (Bell 1941).Failure to do this can result in unfair tests of treatments. Take, for example, two very different ways of treating people experiencing dizzy spells because of partially blocked blood vessels supplying their brains. Treatment for this condition can be important because these people experiencing dizzy spells for this reason are at increased risk of suffering a stroke, which may leave them disabled, or even kill them. One of the treatments for the dizzy spells involves taking aspirin to stop the blockage getting worse; the other involves a surgical operation to try to remove the blockage in the blood vessel.
A fair comparison of these two approaches to treating dizzy spells would involve creating two groups of people using an unbiased allocation method (like randomization). The comparison would thus begin by comparing two groups of patients who were alike, and go on to compare their respective frequencies of subsequent strokes. But if the frequency of strokes in the surgically treated group was only recorded among patients who had survived the immediate effects of the operation, the important fact that the operation itself can cause stroke and death would be missed. This would result in an unfair comparison of the two treatments, resulting in a biased and misleadingly optimistic picture of the effects of the operation. Like would not be being compared with like.
The principal comparison in randomized trials must be based, as far as possible, on all the people assigned to receive each of the treatments compared, without exceptions, and in the groups to which they were originally assigned. If this principle is not observed, people may receive biased information about the overall effects of treatments.
المراجع References
Balfour TG (1854). Quoted in West C. Lectures on the Diseases of Infancy and Childhood. London, Longman, Brown, Green and Longmans, p 600.
Bell JA (1941). Pertussis prophylaxis with two doses of alum-precipitated vaccine. Public Health Reports 56:1535-1546.
Cheselden W (1740). The anatomy of the human body. 5th edition. London: William Bowyer.
Colebrook D (1929). Irradiation and health. Medical Research Council Special Report Series No.131.
Doull JA, Hardy M, Clark JH, Herman NB (1931). The effect of irradiation with ultra-violet light on the frequency of attacks of upper respiratory disease (common colds). American Journal of Hygiene 13:460-77.
Hamilton AL (1816). Dissertatio Medica Inauguralis De Synocho Castrensi (Inaugural medical dissertation on camp fever). Edinburgh: J Ballantyne.
Lind J (1753). A treatise of the scurvy. In three parts. Containing an inquiry into the nature, causes and cure, of that disease. Together with a critical and chronological view of what has been published on the subject. Edinburgh: Printed by Sands, Murray and Cochran for A Kincaid and A Donaldson.
McPherson K (2004). Where are we now with hormone replacement therapy? BMJ 328:357-358.
Medical Research Council Therapeutic Trials Committee (1934). The serum treatment of lobar pneumonia. BMJ 1:241-245.
Medical Research Council (1944). Clinical trial of patulin in the common cold. Lancet 2:373-5.
Medical Research Council (1948). Streptomycin treatment of pulmonary tuberculosis: a Medical Research Council investigation. BMJ 2:769-782.
Medical Research Council (1950). Clinical trials of antihistaminic drugs in the prevention and treatment of the common cold. BMJ 2:425-431.
Medical Research Council (1951). The prevention of whooping-cough by vaccination. BMJ 1:1463-1471
Parry CH (1786). Experiments relative to the medical effects of Turkey Rhubarb, and of the English Rhubarbs, No. I and No. II made on patients of the Pauper Charity. Letters and Papers of the Bath Society III:407-422.
Silverman WA, Chalmers I. Casting and drawing lots. The James Lind Library ( www.jameslindlibrary.org) .
Theobald GW (1937). Effect of calcium and vitamin A and D on incidence of pregnancy toxaemia. Lancet 2:1397-1399.
التعليقات (5)
مشكوره ويعطيك الف عافيه
معليش عارفه إني تعبتك معاي
وجعله الله في موازين حسناتك
وربي يوفقك في حياتك
معليش عارفه إني تعبتك معاي
وجعله الله في موازين حسناتك
وربي يوفقك في حياتك
the different treatments people use for one illness
Differences between the people compared
Comparing different treatments given to groups of people
Treatment comparisons usually entail comparing the experiences of groups of people who have received different treatments. If these comparisons are to be fair, the composition of the groups must be similar – so that like will be compared with like. If those who receive one treatment are more likely anyway to do well (or badly) than those receiving an alternative treatment, this allocation bias makes it impossible to be confident that outcomes reflect differential effects of the treatments, rather than the effects of nature and the passage of time.
William CheseldenThe 18th century surgeon William Cheselden was aware of the 'dissimilar groups' problem when surgeons were comparing their respective mortality rates after operations to remove bladder stones. Cheselden pointed out that it was important to take account of the ages of the people treated by different surgeons. He drew attention to the fact that mortality rates varied with the patients’ ages (Cheselden 17-40) - older patients were more likely than younger patients to die. This meant that, if one wished to compare the frequency of deaths in groups of patients who had undergone different types of operation, one had to take account of differences in the ages of the patients in the comparison groups.
Comparing the experiences and outcomes of patients who happened to have received different treatments in the past is still used today as a way of trying to assess the effects of treatments. The challenge is to know whether the comparison groups were sufficiently alike before receiving treatment. This is illustrated by attempts to assess the effects of hormone replacement therapy (HRT) by comparing the illness experiences of women who had used HRT with those of other women who had not used it. As subsequent analysis of fair tests of HRT showed, trying to assess the effects of treatments in retrospect in this way can sometimes be dangerously misleading (McPherson 2004).
It is rarely possible to be completely confident that comparison groups selected from people who have been given one treatment in the past are comparable in all the respects that matter with people who have more recently received an alternative treatment. This is the case even if some information about the patients who have received different treatments is available (such as their ages, or their past history of illness). Other information that may be of great importance (such as the likelihood of
spontaneous recovery) may simply not be available
.
James Lind took care to select patients who were at a similar stage of this often fatal
disease. He also ensured that they had the same basic diet and were accommodated in similar conditions. These were factors, other than treatment, that might have influenced their likelihood of recovering . Comparable efforts must be made to try to ensure that treatment comparison groups are composed of similar people.
Unbiased assembly of treatment comparison groups using alternation or randomization
Although Lind took care to ensure that the sailors in his six comparison groups were alike, he didn’t describe how he decided which sailors would receive which of the six treatments. There is only one way to ensure that treatment comparison groups are setup in such a way that they are similar in all the ways that matter, known and unknown. This is by using some form of chance process to assemble treatment comparison groups, so avoiding biased selection for different treatments before starting treatment.
One hundred years after Lind, an army doctor, Graham Balfour, illustrated how this could be done in a test to see whether belladonna prevented scarlet fever in children. In the military orphanage for which he had responsibility, he used alternation - “to prevent the imputation of selection” - to decide which boys would receive and which would not receive belladonna (Balfour 1854).. During the first half of the 20th century, there are many examples of treatment comparison groups being assembled using alternation or rotation This ‘random allocation’ is the sole, but crucially important, feature of the category of fair tests referred to as ‘randomized’. A random (as distinct from haphazard) allocation means that the chances of something happening are known, but the results can not be anticipated on any particular occasion. So for example, if a coin is used to randomize, the chance of getting heads is 50%, but it is impossible to know what the result of a particular toss will be.
As illustrated in the essay available by clicking here, casting or drawing lots is a time-honoured way of making fair decisions. These methods help to ensure that comparison groups are not composed of different types of people. Known and measured factors of importance, like age, can be checked. However unmeasured factors that may influence recovery from illness, such as diet, occupation, and anxiety, can be expected to balance out on average. If you would like to see how random allocation generates similar groups of people .
As experience of using alternation and random allocation for unbiased assembly of groups of patients for comparing different treatments became more widespread, it became clear that strict adherence to allocation schedules was required to avoid biased creation of treatment comparison groups. The risk of biased allocation can be abolished if treatment allocation schedules are concealed from those making decisions about participation in treatment comparisons – in brief, to prevent them cheating, and thus biasing the comparisons.
Avoiding biased losses from treatment comparison groups
After taking the trouble to ensure that treatment comparison groups are assembled in ways that ensure that like will be compared with like, it is important to avoid bias being introduced as a result of selective withdrawal of patients from the comparison groups. As far as possible, group similarity should be maintained by ensuring that all the people allocated to the treatment comparison groups are followed up and included in the main analysis of the test results – a so-called ‘intention-to-treat’ analysis (Bell 1941).
Failure to do this can result in unfair tests of treatments. Take, for example, two very different ways of treating people experiencing dizzy spells because of partially blocked blood vessels supplying their brains. Treatment for this condition can be important because these people experiencing dizzy spells for this reason are at increased risk of suffering a stroke, which may leave them disabled, or even kill them. One of the treatments for the dizzy spells involves taking aspirin to stop the blockage getting worse; the other involves a surgical operation to try to remove the blockage in the blood vessel.
A fair comparison of these two approaches to treating dizzy spells would involve creating two groups of people using an unbiased allocation method (like randomization). The comparison would thus begin by comparing two groups of patients who were alike, and go on to compare their respective frequencies of subsequent strokes. But if the frequency of strokes in the surgically treated group was only recorded among patients who had survived the immediate effects of the operation, the important fact that the operation itself can cause stroke and death would be missed. This would result in an unfair comparison of the two treatments, resulting in a biased and misleadingly optimistic picture of the effects of the operation. Like would not be being compared with like.
on all the people assigned to receive each of the treatments compared, without exceptions, and in the groups to which they were originally assigned. If this principle is not observed, people may receive biased information about the overall effects of treatments
Differences between the people compared
Comparing different treatments given to groups of people
Treatment comparisons usually entail comparing the experiences of groups of people who have received different treatments. If these comparisons are to be fair, the composition of the groups must be similar – so that like will be compared with like. If those who receive one treatment are more likely anyway to do well (or badly) than those receiving an alternative treatment, this allocation bias makes it impossible to be confident that outcomes reflect differential effects of the treatments, rather than the effects of nature and the passage of time.
William CheseldenThe 18th century surgeon William Cheselden was aware of the 'dissimilar groups' problem when surgeons were comparing their respective mortality rates after operations to remove bladder stones. Cheselden pointed out that it was important to take account of the ages of the people treated by different surgeons. He drew attention to the fact that mortality rates varied with the patients’ ages (Cheselden 17-40) - older patients were more likely than younger patients to die. This meant that, if one wished to compare the frequency of deaths in groups of patients who had undergone different types of operation, one had to take account of differences in the ages of the patients in the comparison groups.
Comparing the experiences and outcomes of patients who happened to have received different treatments in the past is still used today as a way of trying to assess the effects of treatments. The challenge is to know whether the comparison groups were sufficiently alike before receiving treatment. This is illustrated by attempts to assess the effects of hormone replacement therapy (HRT) by comparing the illness experiences of women who had used HRT with those of other women who had not used it. As subsequent analysis of fair tests of HRT showed, trying to assess the effects of treatments in retrospect in this way can sometimes be dangerously misleading (McPherson 2004).
It is rarely possible to be completely confident that comparison groups selected from people who have been given one treatment in the past are comparable in all the respects that matter with people who have more recently received an alternative treatment. This is the case even if some information about the patients who have received different treatments is available (such as their ages, or their past history of illness). Other information that may be of great importance (such as the likelihood of
spontaneous recovery) may simply not be available
.
James Lind took care to select patients who were at a similar stage of this often fatal
disease. He also ensured that they had the same basic diet and were accommodated in similar conditions. These were factors, other than treatment, that might have influenced their likelihood of recovering . Comparable efforts must be made to try to ensure that treatment comparison groups are composed of similar people.
Unbiased assembly of treatment comparison groups using alternation or randomization
Although Lind took care to ensure that the sailors in his six comparison groups were alike, he didn’t describe how he decided which sailors would receive which of the six treatments. There is only one way to ensure that treatment comparison groups are setup in such a way that they are similar in all the ways that matter, known and unknown. This is by using some form of chance process to assemble treatment comparison groups, so avoiding biased selection for different treatments before starting treatment.
One hundred years after Lind, an army doctor, Graham Balfour, illustrated how this could be done in a test to see whether belladonna prevented scarlet fever in children. In the military orphanage for which he had responsibility, he used alternation - “to prevent the imputation of selection” - to decide which boys would receive and which would not receive belladonna (Balfour 1854).. During the first half of the 20th century, there are many examples of treatment comparison groups being assembled using alternation or rotation This ‘random allocation’ is the sole, but crucially important, feature of the category of fair tests referred to as ‘randomized’. A random (as distinct from haphazard) allocation means that the chances of something happening are known, but the results can not be anticipated on any particular occasion. So for example, if a coin is used to randomize, the chance of getting heads is 50%, but it is impossible to know what the result of a particular toss will be.
As illustrated in the essay available by clicking here, casting or drawing lots is a time-honoured way of making fair decisions. These methods help to ensure that comparison groups are not composed of different types of people. Known and measured factors of importance, like age, can be checked. However unmeasured factors that may influence recovery from illness, such as diet, occupation, and anxiety, can be expected to balance out on average. If you would like to see how random allocation generates similar groups of people .
As experience of using alternation and random allocation for unbiased assembly of groups of patients for comparing different treatments became more widespread, it became clear that strict adherence to allocation schedules was required to avoid biased creation of treatment comparison groups. The risk of biased allocation can be abolished if treatment allocation schedules are concealed from those making decisions about participation in treatment comparisons – in brief, to prevent them cheating, and thus biasing the comparisons.
Avoiding biased losses from treatment comparison groups
After taking the trouble to ensure that treatment comparison groups are assembled in ways that ensure that like will be compared with like, it is important to avoid bias being introduced as a result of selective withdrawal of patients from the comparison groups. As far as possible, group similarity should be maintained by ensuring that all the people allocated to the treatment comparison groups are followed up and included in the main analysis of the test results – a so-called ‘intention-to-treat’ analysis (Bell 1941).
Failure to do this can result in unfair tests of treatments. Take, for example, two very different ways of treating people experiencing dizzy spells because of partially blocked blood vessels supplying their brains. Treatment for this condition can be important because these people experiencing dizzy spells for this reason are at increased risk of suffering a stroke, which may leave them disabled, or even kill them. One of the treatments for the dizzy spells involves taking aspirin to stop the blockage getting worse; the other involves a surgical operation to try to remove the blockage in the blood vessel.
A fair comparison of these two approaches to treating dizzy spells would involve creating two groups of people using an unbiased allocation method (like randomization). The comparison would thus begin by comparing two groups of patients who were alike, and go on to compare their respective frequencies of subsequent strokes. But if the frequency of strokes in the surgically treated group was only recorded among patients who had survived the immediate effects of the operation, the important fact that the operation itself can cause stroke and death would be missed. This would result in an unfair comparison of the two treatments, resulting in a biased and misleadingly optimistic picture of the effects of the operation. Like would not be being compared with like.
on all the people assigned to receive each of the treatments compared, without exceptions, and in the groups to which they were originally assigned. If this principle is not observed, people may receive biased information about the overall effects of treatments
woooow such a hard worker ((mash Allah))
keep it up and God bless you boss
keep it up and God bless you boss
مطلوب موقع للقصص تعلم English→
There are various different treatments available for mental illness, and treatment often involves a combination of approaches, which may be offered by different professionals. Depending on your problem, you may receive treatment from a doctor — either your general practitioner or a psychiatrist — or you may find help by utilising one of the psychological, ‘talking’ therapies.
Who should I turn to for treatment of mental illness?
If you or someone you are close to is experiencing a problem which may be related to mental health, the first place you should look for help should be your doctor or community mental health centre. Community support is an important aspect of treatment for mental illness, and ongoing support and treatment can be provided by a community health service clinic.
Some of the professionals involved in the treatment of mental health problems include:
*
General practitioners
You should see your general practitioner (GP) if you are experiencing problems such as depression or anxiety. A GP can help determine whether your symptoms are part of a mental illness, or whether they are the result of an underlying physical illness, a side effect of a medication you have been taking, or a normal reaction to current life circumstances. If your symptoms are in fact caused by a mental illness, your GP might prescribe a course of medication, provide counselling (some GPs have a special interest in counselling), or refer you to someone who has expertise in your particular problem. GPs have a special role in ensuring that a person with a mental illness maintains good physical health, even if the mental illness is being treated elsewhere.
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Psychiatrists
Psychiatrists are fully qualified medical doctors with specialist training in how to diagnose and treat mental illness. Psychiatrists work in hospitals, community mental health centres, and also in private practice. Psychiatrists are able to prescribe and monitor medications, and can also offer psychological therapy.
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Psychologists and other therapists
Psychologists and counsellors are professionals who specialise in counselling and interpersonal therapies. They are not medical doctors, so they do not prescribe medications. Psychologists work in both community health centres and in private practice.
Are there medications that can help?
Medication is usually the main form of treatment for people with serious, ongoing mental health problems. Although medication is not a cure for mental illness, it can allow many people to have a greatly improved quality of life. For some people, medication is a short-term solution, used to help them over an immediate crisis. Others may need ongoing, long-term treatment with medication to help them live with their illness.
Medications for mental illness include:
* antipsychotics, which are used to treat illnesses such as schizophrenia;
* antidepressants, which are used to treat depression and some anxiety disorders;
* mood stabilizers, which can be taken to treat bipolar disorder (manic depression); and
* anti-anxiety medications, which can be used on a short-term basis for acute attacks of anxiety.
What about psychological treatments?
‘Talking’ treatments, or psychological therapies, try to help people understand the basis of their problem, and how they can overcome it. Psychotherapy may be effective for a range of mental health problems, and can be combined with other forms of therapy, such as medications.
There are many different psychological treatments available, and some are more well-known and widely used than others. Some of the many available therapies include:
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Cognitive-behavioural therapy (CBT)
This treatment is based on the idea that the way that we feel and behave depends on how we think about and interpret experiences. CBT can help you discover how thoughts, feelings and behaviour can get stuck in unhelpful patterns.
Identifying and challenging negative thinking patterns, and developing alternative ways of thinking and acting, can reduce stress and improve your coping abilities and self-esteem. A range of illnesses, including depression, anxiety disorders and schizophrenia, can be effectively treated with this type of therapy.
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Counselling
In counselling, you will talk about your difficulties on a one-to-one basis with a professional (a counsellor). The counsellor will listen and give you support, and may also offer you advice on how to deal with your problems in a practical way. Counselling is appropriate for treating milder forms of mental illness, such as grief reactions.
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Interpersonal psychotherapy
This type of treatment has been found to effectively treat a range of mental illnesses, including mild to moderate depression, but it is not commonly used to treat more serious illnesses, such as schizophrenia.
It examines how you relate to other people, and how this affects the way you think, feel and act. You work with the therapist to develop more positive ways of interacting, and by strengthening communication skills and self-esteem, this form of therapy can help improve interpersonal relationships.
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Psychoanalysis
This is somewhat similar to counselling in that it involves one-to-one communication with a professional, but it is much more intensive. A psychoanalyst will encourage you to explore your feelings in depth, particularly in relation to how these feelings relate to experiences you have had early in your life. Psychoanalysis is very often a long-term treatment.
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Group therapy
Sometimes people who share a common problem, for example, self-harm or substance abuse, may benefit from working together in small groups, to resolve their difficulties in a supportive environment under the guidance of a professional.
The most important question you should ask yourself if you decide to see a psychological therapist is whether you will be able to develop a good relationship with them. If you establish rapport with the therapist and have a positive attitude towards the treatment, the treatment will be more likely to benefit you. You should also ask about the therapist’s training, experience and the treatment approach they prefer.
If your doctor recommends counselling or psychological therapy, you should always ask if there will be any costs involved and what these will be.
Are there any other forms of treatment for mental illness?
Electroconvulsive therapy (ECT) is also used in the treatment of certain mental illnesses. This treatment is usually reserved for people with very severe depression, especially where doctors believe someone may be at risk of suicide. It involves giving a person a general anaesthetic and muscle relaxant, and passing a dose of electric current through their brain. Although it is used less often than it was in the past, it can be highly effective for people who have not been helped by other treatments. ECT can only be given if the person consents to having the treatment.
Do people with mental health problems need to be treated in hospital?
Most treatment for people with a mental illness will be carried out in the community. Treatment in hospital is usually only required when a person is very ill and needs intensive treatment and/or supervision. In the majority of cases, treatment in hospital is only required for a few weeks.
Which treatment is right for me?
Because the range of options for treating mental health problems can appear confusing, you should always ask your doctor for guidance as a first step. The most important thing is that your doctor understands your symptoms so that he or she can advise on the treatment that is likely to be of most help.