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Definition of the Scientist-Practitioner Framework
Despite the relative youth of psychology as a science, the training and practice of clinical
psychologists has evolved rapidly. As acknowledged by Challmen at al. (1949), the discipline of
clinical psychology born in the early 20th century grew to be known for its strong emphasis on
clinical assessment and relative indifference towards research methodologies. With the aim of
identifying training needs for clinical psychology students, the scientist-practitioner model
emerged as a framework for training students who would be well-prepared in both scientific
research and clinical practice. The APA established the scientist-practitioner model on the basis
of integrating research and practice, to allow each of these two facets of training to inform one
another (Jones & Mehr, 2007). Graduate program educators sought to use the model to “train
psychologists who are capable of applying psychological knowledge to their work… as well as
possessing the ability to move the field forward and generate fresh knowledge in the form of new
empirical findings” (Jones & Mehr, 2007, p. 767). It seems that the most current applications of
the scientist-practitioner model in psychology tend to favour an integrated approach (Healy,
2017; Jones & Mehr, 2007). However, without deeper reflection on the literature, it is unclear
what this integration actually looks like for psychologists operating within this model. Jones &
Mehr (2007) began to concretely illustrate what the integrated model looks like in practice,
stating that “a scientist-practitioner is someone who applies critical thought to practice, uses
proven treatments, evaluates treatment programs and procedures, and applies techniques based
on supportive literature” (p. 770). This quote is helpful for conceptualizing the real-world
applications of the scientist-practitioner framework beyond graduate training; this description
allows clinicians to look ahead to the activities in which they might engage in their future
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practice and facilitated further exploration into what it means to maintain a scientist-practitioner
framework.
Evidence-Based Practice: Maintaining a Scientist-Practitioner Framework
The use of evidence-based practice (EBP) is at the core of maintaining a scientistpractitioner framework. The Canadian Psychological Association’s Task Force on EvidenceBased Practice of Psychological Treatments published an outline of guidelines and standards for
implementing EBP to “develop a position statement regarding the optimal integration of research
evidence into practice” (Dozois et al., 2014, p. 154). Namely, “EBP of psychological treatments
involves the conscientious, explicit, and judicious use of the best available research evidence to
inform each stage of clinical decision-making and service delivery” (Dozois et al., 2014). Upon
reflection, it is clear that the utility of EBP aligns closely with those activities which define
scientist-practitioners, as Jones & Mehr (2007) described.
In 2006, Vespia authored an article to advocate for the benefits of maintaining a scientistpractitioner framework; however, Overholser (2010) identified Vespia’s position as less credible
given that she had not engaged in any service delivery in over 3 years. However, Dozois et al.
(2014) provided some clarity for how Vespia’s position could still be considered to follow the
scientist-practitioner model, indicating that “research should be informed by practice to ensure
that the discipline and profession are providing evidence for treatments that respond to the kinds
of problems that clients bring to psychology practitioners” (p. 154). Although Overholser’s
(2010) concerns for researchers potentially losing touch with practice after periods of clinical
inactivity are warranted, Dozois et al.’s (2014) aim to integrate science and practice across roles
speaks more to the scientist-practitioner framework as a mindset. Using the best available
evidence to inform treatments ensures that our database of scientific knowledge is put to use
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responsibly in alignment with the goal of providing the best possible service to clients. Similarly,
researchers conducting treatment outcome and process studies should be mindful of those
concerns which are brought forth by clinical populations seeking help.
Scientist-Practitioners in Practice
Dozois et al.’s (2014) hierarchy of research evidence provides a helpful framework for
weighing evidence in terms of its strength. As a practitioner delivering psychological
interventions, one might strive to gather as much background information as possible to best
understand the reason for referral to services. This would orient clinicians towards the clients’
goals for treatment, and provide a framework for how we might collaboratively evaluate the
effectiveness of a given intervention based on progress monitoring (Dozois et al., 2014). It may
be most helpful to consider the scientist-practitioner framework as a mindset for approaching
practice; using the best available evidence provides the best chance for a client to succeed.
However, one potential barrier to this approach might emerge when “perhaps… equally strong
studies reach conflicting conclusions” (Rubin, 2007). In this case, it may not be clear whether or
not an intervention’s efficacy is supported or refuted by the “evidence.” Based on the literature,
the solution to this barrier might rely in developing a deeper understanding of client variables
such as their “specific client characteristics, cultural backgrounds, and treatment preferences”
(Dozois et al., 2014, p. 155). It also speaks to the importance of working collaboratively with the
client, an important facet of Dozois et al.’s (2014) definition of “evidence” in EBP: “the process
of evidence-based treatments is one of collaboration with a client” (p. 155). Thus, given a
situation where an intervention was both supported and refuted by literature, one might introduce
the intervention by describing to a client, using accessible language, what the intervention entails
and the fact that there is both evidence in support of and against this intervention’s efficacy. This
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invites the client to take an active role in their treatment plan with the reassurance that the
intention is to continually monitor personal progress. In the event that the intervention turned out
to not meet the client’s needs, Rubin (2007) suggests moving down the hierarchy to studies of
interventions in which methods were less rigorous, but the results were overall still supportive of
the intervention as an alternative to the available best evidence.
Scientist-Practitioners in Research
From the researcher’s perspective, a central challenge to maintaining the scientistpractitioner framework seems to be knowing what is “worth” researching. Reflections in the field
of industrial-organizational (IO) psychology point to this as a pervasive issue outside of the
clinical field. Delmhorst (2018) describe a trend in IO psychology whereby there is a lag
between what is being studied and what questions needed to be answered by employees in the
field. This brings to mind the concept of “trendy” intervention studies where clinical populations,
such as ASD, receive a lot of attention and funding given the disorder’s prevalence. However,
can the same be said for clinical populations of a smaller size? The ideals of high internal
validity in randomized-control studies are sensible from a research perspective; this is the surest
way to have confidence in the generalizability of a study’s results (Dozois et al., 2014). After
browsing some of the Cochrane Reviews, however, it became clear that comorbidity in study
samples made it difficult to summarize the effectiveness of interventions (Macdonald et al.,
2012; Olthius, Watt, Bailey, Hayden & Stewart, 2016). Similarly, practitioners encounter a broad
range of clients who do not present with perfectly distinct, isolated symptoms to address in
intervention (Weisz, Krumholz, Santucci, Thomassin & Ng, 2015). In keeping with the scientistpractitioner model, a solution mentioned several times in the literature was to elicit calls for
research proposals via networks such as Practice Research Networks (Rotolo et al., 2018; Tasca,
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n.d.). Maintaining involvement in such networks would allow researchers to determine whether
or not there was value in studying a smaller clinical population, such as those with comorbid
diagnoses. Referring to these networks provides guidance that supports the development of a
scientific database while addressing concerns brought forth in practice by populations seeking
help.
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