Department of Psychotherapy, Manchester Royal Infirmary
Psychological Therapies Research Centre, University of Leeds
Rampton Hospital, Nottinghamshire and Tavistock Centre, London
Correspondence: Dr Frank R. Margison, Gaskell Psychotherapy Centre, Manchester Royal Infirmary, Swinton Grove, Manchester M13 0EU, UK. E-mail: frmargison{at}aol.com
Declaration of interest The Mental Health Foundation, the Counselling in Primary Care Trust, and the Society for Psychotherapy Research (UK) (Northern Group) have supported the work of the CORE System Group.
See editorial, pp. 93-94,
this issue.
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ABSTRACT |
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Aims To review the developments in measurement relevant to psychotherapy.
Method Domains reviewed are: (a) interventions; (b) case formulation; (c) treatment integrity; (d) performance (including adherence, competence and skilfulness); (e) treatment definitions; (f) therapeutic alliance; and (g) routine outcome measurement.
Results Modern methods of measurement can support evidence-based practice for psychological treatments. They also support practice-based evidence, a complementary paradigm to improve clinical effectiveness in routine practice via the infrastructure of Practice Research Networks (PRNs).
Conclusions Advances in measurement derived from psychotherapy research support a model of professional self-management (practice-based evidence) which is widely applicable in psychiatry and medicine.
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INTRODUCTION |
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CONTEXT: EVIDENCE-BASED PRACTICE AND PRACTICE-BASED EVIDENCE |
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Despite these caveats, the evidence base for psychotherapy has been extensively reviewed. One major review (Roth & Fonagy, 1996) focuses almost exclusively on evidence from RCTs. This reveals the lack of evidence concerning many therapies, rather than evidence for or against. However, there is a complementary paradigm which is already well developed in psychotherapy (e.g. Margison et al, 1998). This involves gathering good-quality data from routine practice, a procedure we term practice-based evidence, which is discussed in greater detail below. For psychotherapy to have a robust evidence base both paradigms are needed.
The myth that psychotherapy is not measurable
It has been argued that there has been "a decline in theory-guided
and a rise in pragmatic, clinically-oriented research"
(Omer & Dar, 1992). In
fact, there have been important developments in theory. These include, among
others, attachment theory (e.g. Mace &
Margison, 1997), sign-mediated language theory
(Stiles et al, 1988)
and theories of mind derived from developmental psychology
(Hobson, 1993), the
assimilation model of change in psychotherapy
(Stiles et al, 1988)
and new conceptualisations of personality (e.g.
O'Brien & DeLongis,
1996).
These developments in underlying theory are crucial. However, policy also urges the improvement of measurement, as part of increased accountability within medicine and other clinical practice.
Stakeholders
We have considered the various stake-holders along with the
most salient practice-research questions in
Table 1. This framework sets
the context for a discussion about the most appropriate measurement
strategies. Clearly, different stakeholders will have different priorities and
an overall strategy is needed to coordinate these different needs
(Department of Health,
1996).
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Efficacy and effectiveness
The distinction between efficacy and effectiveness
(Cochrane, 1972) becomes
relevant when considering the different priorities of the different
stakeholders. Efficacy refers to evidence derived from carefully
designed trials where threat to internal validity is minimised. Traditionally,
in evidence-based medicine the randomised controlled trial is considered as
the gold standard because of its ability to deal with bias
through the randomisation process. However, even with the RCT there is a
trade-off between rigour and generalisability
(Shapiro et al,
1995). In particular, the more selective the sample and the more
rigorously defined the intervention, the less applicable the treatment is
likely to be to routine practice. In effectiveness research, the
design is weighted towards high generalisability, but the price is paid in
greater threats to internal validity.
To resolve this dilemma, Barkham & Mellor-Clark (2000) suggest a strategy with three phases: (a) theory and generation of treatment; (b) validation and testing efficacy; and (c) dissemination and measurement of effectiveness in practice. The strategy is logical, but in practice there are difficulties to this orderly approach. First, the need for replication of efficacy studies in phase (b) is understated. Second, the time scale from inception to full implementation of a new treatment is very long, and by that time keen clinicians are likely to be already modifying the treatment. Third, the transfer of knowledge from research studies to normal clinical practice is poor.
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MEASUREMENT STRATEGIES IN PSYCHOTHERAPY |
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(a) Interventions at the level of component skills
This represents the micro level of analysis of a session at
the smallest unit of measurement. Specific interventions are often referred to
in the literature as verbal response modes (VRMs), and these can
be rated reliably (Elliott et al,
1987). The classifications used can be generic (not specific to
the mode of therapy under study) or specific to a particular mode of therapy.
The latter tend to be more reliable but operate over a narrower range of
therapists' behaviour types (Elliott
et al, 1987).
Clinical implications
(b) Case formulation
At the macro level of case analysis, formulation represents
conceptualisation at the level of a whole treatment. Case formulation was
initially developed in relation to psychodynamic approaches
(Luborsky, 1984) and shown to
be a replicable procedure. Recent work has included explicit formulation
techniques in schema-focused cognitive therapy
(Persons, 1989).
Clinical implications
(c) Treatment integrity
Integrity is defined simply as the extent to which treatment procedures are
carried out as intended (Kazdin,
1994). The concept was intended to cover three different aspects:
adherence, competence and differentiation. Adherence refers to the
extent that the therapist is using procedures described as characteristic of
the model being used. Competence goes further, in defining the
appropriate delivery of those elements according to a prior definition.
Differentiation is specifically relevant in both process and efficacy
research, as it "refers to whether two or more treatments differ from
each other along critical dimensions that are central to their
execution" (Kazdin,
1994: 37). This has led to the idea that certain behaviours are
prescribed and others proscribed.
There are well-developed measures to assess the adherence of therapists across several types of therapy. This method, originally developed for the NIMH Treatment of Depression Collaborative Research Program (TDCRP; Elkin, 1994: 116), was called the Collaborative Study Psychotherapy Scale (CSPRS). Initially, it covered interpersonal therapy and cognitive therapy, as well as generic facilitating conditions and skills in clinical management. More recently the domains have been extended to include psychodynamic interpersonal therapy (Startup & Shapiro, 1993). Several other treatments have manuals to assess adherence and competence, and it has been recommended that all such scales be explicitly linked to a treatment manual (Waltz et al, 1993).
The examples from the TDCRP (Elkin, 1994) and Sheffield (UK) (Shapiro et al, 1994) studies demonstrate the conceptual areas covered (see Table 2). Each of the main therapeutic models considered covers a discrete domain, and some generic qualities are relevant across all types of therapy. More competent therapists (rated as such by their supervisors) were able to deviate appropriately from technical recommendations with more difficult patients (Rounsaville et al, 1988). There is also some evidence that patients of these therapists had better outcomes (O'Malley et al, 1988). Experienced clinicians tend to integrate elements from therapies which are differentiated in formal outcome studies. This calls into question one of the main paradigms of psychological treatments research: the so-called drug metaphor implies that pure or unadulterated forms of treatment are likely to be most efficacious.
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Clinical implications
(d) Performance: synthesising adherence, competence and
skilfulness
Competence scales have been rightly criticised in the past because they
tended to reduce the complexity of therapy to a lowest common denominator.
Recently, however, there has been increasing interest in higher levels of
performance that could reasonably be called skilful. Milne et al
(1999) have revised the
competence scale for cognitive therapy. They distinguish six levels of
competence. Interestingly, they take account of the literature on negative
therapeutic effects and incorporate a Level 0 which represents a
harmful state rather than a simple lack of competence, continuing through
Novice, Advanced beginner, Competent, Proficient to Expert. It is interesting
to note that their highest level of competence, Expert, is characterised as
follows:
"The therapist no longer uses rules, guidelines or maxims. He/she has deep tacit understanding of the issues and is able to use novel problem-solving techniques. The skills are demonstrated even in the face of difficulties (e.g. excessive avoidance)."
Their suggestion for cognitive therapy suggests that at the highest level of competence there is an ability to transcend rules, guidelines and maxims, throwing into confusion any attempt to equate expert performance and adherence. Examples of the range of difficult situations across which competence needs to be demonstrated in expert practice might be an intensely suicidal patient, or a marked display of hostility.
In contrast to the research on treatment integrity (which draws heavily on the pure drug metaphor), clinicians have turned increasingly to a hybrid approach where clinical skilfulness is measured in actual performance of the task. Hence, the paradigm suggested by Milne et al (1999) for cognitive therapy is likely to be of wider applicability.
Clinical implications
(e) Treatment definitions
The number of psychological treatments described far exceeds our capacity
to differentiate them at all the levels defined above. All therapies could be
reduced to a generic level: for example, distinguishing cognitive-behavioural,
psychodynamic interpersonal, systemic and humanistic. However, there is still
a substantial problem in allocating explicitly integrative models within the
classification. A theoretical resolution of this would be the therapeutic
equivalent of a colour chart. The proportion of each primary
therapeutic mode present could define a therapy (whether at the global level
or at a session level).
An alternative approach has been to reduce the therapies under serious consideration to those which have well-defined methods and treatment manuals. Manualisation has been another attempt to purify the psychotherapy delivered, but
"it is foolish to believe that the use of manuals alone will standardise a therapy. The actual delivery of therapy is dependent on the contributions and interactions that take place between... people" (Koss & Shiang, 1994: 675).
However, reviews of brief therapy suggest that manualised therapies have better outcomes than less formalised methods (Crits-Cristoph, 1992). Future directions in the development of manuals are likely to focus on broad definitions, with guidance about the underlying conceptualisation from which the treatment techniques would follow. There is likely to be a considerable delay before such integrated treatment manuals become common in both research and routine practice.
Clinical implications
(f) Therapeutic alliance
Most treatment methods and manuals now pay particular attention to one of
the features of therapy that had previously been conceptualised as a
common factor. However, the therapeutic alliance has emerged as
the most consistent predictor of outcome across many studies in different
models of psychotherapy (see Henry et
al, 1994, for a review). Following Bordin
(1979), the alliance has
generally been construed as having three components: the therapeutic bond,
agreement about the task and agreement about goals. The problem in terms of
measurement has been that some aspects of alliance could equally
be seen as early or emerging outcomes. There are well-established and
empirically validated scales to measure alliance, such as the California
Psychotherapy Alliance Scales (CALPAS;
Gaston, 1991), which minimise
potential confounding with early outcome. However, there has been no research
on whether the use of measures of alliance actually enhances routine clinical
practice.
Clinical implications
(g) Routine outcome measurement
For routine outcome assessment to become feasible, several conceptual and
methodological issues need to be resolved. Surveys of outcome measures used in
research and in routine practice show that very many measures are used
(Mellor-Clark et al,
1997). Many are used in only one research project or service
setting, which makes comparability extremely difficult. Many scales have poor
referential data (particularly data applicable to service settings). Scales
often have large numbers of items to increase reliability and to cover
multiple domains. Scales have often not been checked for acceptability in
different ethnic groups or validated across different languages. They often
cover only a single perspective (for example, patient or informant).
Outcomes may be specific to a particular type of problem (for example, an eating disorder) or may refer to more general domains such as well-being, health, symptoms and function. The Compass System (Sperry et al, 1996) was developed as a systematic approach to assessing change in therapy, particularly in the context of health maintenance organisations (HMOs). This approach suggested that outcome could be conceptualised in three phases: remoralisation, remediation and rehabilitation, covering improvement in well-being, symptoms and general life function respectively. The system also measured session-by-session alliance. It was possible to track patients' progress and flag cases needing closer attention by comparing session-by-session progress and variability against the main database.
In the United Kingdom the CORE system (Core System Group, 1998) was developed from initial research about acceptability and from stakeholder views, in conjunction with several practice research networks (Barkham et al, 1998). The measures consist of a 34-item outcome scale (and two parallel short forms, for repeated use), an assessment measure and an end-of-phase summary. The measures can be scanned by computer or scored by hand for immediate use. The outcome measure is designed to assess well-being, problems or symptoms, and functioning, and has additional risk-flagging items. The CORE system uses the measures to provide feedback to individual practitioners, teams and organisations using different modes of therapy and in a wide variety of settings (CORE System Group, 1998).
Reliable and clinically significant change
Measurement systems such as Compass and CORE, along with more specialised
measures for particular problems, can then be utilised in an effectiveness
framework using the concepts and methods of reliable and clinically
significant change (RCSC). One of the main criticisms of efficacy research is
that the results need to be interpreted at the group (or aggregated) level.
Efforts to understand the outcome of an individual patient in the context of a
whole service or outcome study have been limited by methodological and
statistical problems (Evans et
al, 1998).
Jacobson & Truax (1991) summarised a model of the measurement of change which reflected the complementary concepts of the statistical reliability of a change and its clinical significance.
Reliability reflects the extent to which an observed difference between scores (for instance, before and after treatment) is evidence of a true underlying difference in the patient. The statistic for estimating this reliability is the standard error of the difference score (s.e.diff), which relates to the standard deviation of the population and the reliability of the measure (Evans et al, 1998). If the change measured for an individual is more than 1.96 times the s.e.diff then such a change is unlikely to occur on more than 5% of occasions by chance. In practice this leads to a very simple way of representing change for a group of individuals on a two-dimensional graph, where the x-axis represents the pre-treatment score and the y-axis the post-treatment score on the same instrument. Every point on the graph can then represent an individual who has the corresponding pre-treatment and post-treatment scores. Figure 1 shows such a graph. The centre diagonal line represents all the points where there has been no change between before and after treatment (x=y). The tramlines on either side of the diagonal represent the limits of 1.96 x s.e.diff, and so for anyone falling within the tramlines, a change could be attributed to chance. Those falling above the upper diagonal have reliably shown deterioration, whereas those below the lower diagonal line have reliably shown improvement.
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Graphical representation of clinical change
This method of graphically representing change scores as single points in
two-dimensional space (with inbuilt confidence intervals showing where change
can be considered reliable) is an extremely helpful audit tool either for an
individual clinician or to display the results for a whole department.
Jacobson & Truax (1991)
also drew up criteria to determine whether the change was clinically
significant. There are many technical issues to be resolved about skewed
distributions and the choice of cut-off points (see
Evans et al, 1998),
but essentially the argument indicates whether the individual has moved from a
dysfunctional to a more functional sample of scores. This is a norm-referenced
method and is, therefore, vulnerable to changes in the choice of reference
parameters. Even so, it is arguably better than the alternative approach,
which is simply to state an arbitrary drop in the measure used as the
criterion for clinically significant improvement. There are now reasonably
good cut-off points for some measures (for example, the Hamilton Rating Scale:
Grundy et al, 1996;
Symptom Checklist-90-R: Tingey et
al, 1996), but the methodology is still limited by the small
number of normative samples for many instruments. A large normative dataset is
needed to allow clinicians to focus on the expected outcomes for their
particular individual patients.
Clinical implications
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DISCUSSION |
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Use of large datasets
One of the advantages of a PRN in developing practice-based evidence is in
generating very large datasets. This allows much better prediction at the
level of the individual case.
A PRN is defined, somewhat tautologically, as a "network of clinicians that collaborate to conduct research to inform their day-to-day practice" (Audin et al, 2000). In contrast to most formal research, PRNs utilise data gathered in real-world practice settings rather than specifically orchestrated clinical trials, and large, clinically representative, datasets can be developed.
Sperry et al (1996: 70-71) give a clinical example. They cite a 28-year-old female patient with a 2-3 month history of anxiety and depression. She complained of diffuse difficulties which were worse on workday mornings. The therapist provided five sessions of initial therapy, looking for underlying causes. The case manager expressed alarm at the review point because of evident deterioration in her clinical scores. After a second opinion, and a revised focus on the underlying work issues, the patient's clinical state improved.
Case flagging
At the review point, when the case is flagged, it is possible
to use more specific quality measures: Is the therapist following the
procedures for this type of therapy? Is the formulation complete and of
reasonable quality? Are there complicating factors (such as intercurrent
substance misuse) which have been overlooked? The practitioner can then
discuss the case formulation in a peer group to identify any factors which can
be remedied.
In practice, the situation is not always as clear as this account suggests. There are two types of problem. Reducing the dataset to young, female, single patients with anxiety, depression and possible work-related problems will reduce the sample size dramatically, so that the confidence intervals increase (although Sperry et al (1996) demonstrate that reasonable confidence limits can be obtained). The second, and more profound, difficulty is that purely numerical case monitoring is likely to be impossible. Even the strongest advocates of case monitoring would only claim that these methods are adjuncts to clinical methods of supervision and case reviews.
Good clinical practice: bridging the efficacy-effectiveness gap
Good clinical practice can be supported by drawing on various measurement
perspectives. These will include
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CLINICAL IMPLICATIONS AND LIMITATIONS |
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LIMITATIONS
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Received for publication March 5, 1999. Revision received October 25, 1999. Accepted for publication November 10, 1999.