Decision Making in Stepped Care: How Do Therapists Decide Whether to Prolong Treatment or Not?

Exploring the Stepped Care Model in Delivering Primary Mental Health Services-A Scoping Review

The stepped care model (SCM) is a patient-centred approach to mental health care, offering a range of services from least to most intensive, tailored to individual needs. This scoping review examines the adoption, effectiveness, challenges and implications associated with applying SCM within primary mental health service delivery. Evidence from global sources suggests the model is viable, effective and useful. This review explores the literature available, clarifies fundamental concepts and identifies existing knowledge gaps. The literature search included CINAHL, MEDLINE, PsycINFO, Scopus, the Federation University library, Google and Google Scholar databases. A systematic keyword-based search using terms like "stepped care model," "mental health," and "primary care"; and a combination of keywords and subject headings, were used. The search strategy was refined by considering factors such as relevance, publication date, objectives and outcomes. This strategy yielded 20 papers compiled in this review. They include randomised controlled trials and cross-sectional studies. The review supports SCM adoption in primary mental health care but acknowledges the need for further research. Key inclusions of the review include cost-effectiveness, diverse diagnoses, efficacy and the model's structural configuration. Clear treatment details, delivery methods, intervention durations and chronological sequences are essential. This systematic approach enhances generalisability across different SCM models and areas, strengthening reliable inferences. In summary, the SCM holds promise for enhancing mental health service delivery. However, there is a need to further examine the factors that determine its effectiveness and understand the different ways in which SCM is implemented. Such inquiry forms the foundation for implementing and advancing mental health care services in Australia and internationally.

Is clinical decision making in stepped-care psychological services influenced by heuristics and biases?

BACKGROUND

The manner in which heuristics and biases influence clinical decision-making has not been fully investigated and the methods previously used have been rudimentary.

AIMS

Two studies were conducted to design and test a trial-based methodology to assess the influence of heuristics and biases; specifically, with a focus on how practitioners make decisions about suitability for therapy, treatment fidelity and treatment continuation in psychological services.

METHOD

Study 1 (N=12) used a qualitative design to develop two clinical vignette-based tasks that had the aim of triggering heuristics and biases during clinical decision making. Study 2 (N=133) then used a randomized crossover experimental design and involved psychological wellbeing practitioners (PWPs) working in the Improving Access to Psychological Therapies (IAPT) programme in England. Vignettes evoked heuristics (anchoring and halo effects) and biased responses away from normative decisions. Participants completed validated measures of decision-making style. The two decision-making tasks from the vignettes yielded a clinical decision score (CDS; higher scores being more consistent with normative/unbiased decisions).

RESULTS

Experimental manipulations used to evoke heuristics did not significantly bias CDS. Decision-making style was not consistently associated with CDS. Clinical decisions were generally normative, although with some variability.

CONCLUSIONS

Clinical decision-making can be 'noisy' (i.e. variable across practitioners and occasions), but there was little evidence that this variability was systematically influenced by anchoring and halo effects in a stepped-care context.

Impact of Comorbid Personality Disorders on Depression Treatment in Routine Outpatient Care

OBJECTIVE

The impact of personality disorder on treatment effectiveness for depression has been debated, and study results have been inconsistent. However, studies that report a negative impact of personality disorders on depression treatment outcomes are often characterized by uncontrolled treatment designs. Within such contexts, individuals with depression and personality disorders are at risk to receive suboptimal treatment. The aim of this retrospective observational study was to investigate whether and to what extent comorbid personality disorders were associated with the type and amount of depression treatment received in routine outpatient care.

METHODS

Retrospectively extracted data from electronic records of 1,455 outpatients treated for depression at several sites of a nationwide mental health provider in the Netherlands were included. The type and number of treatment sessions and visits were analyzed by using regression models.

RESULTS

Individuals with depression and comorbid personality disorders received more psychotherapy sessions than individuals without personality disorders, irrespective of depression severity. The number of pharmacotherapy sessions and supportive and crisis visits did not differ between individuals with and without comorbid personality disorders.

CONCLUSIONS

Individuals with depression and personality disorders received more intensive treatment than individuals without comorbid personality disorders. These results conflict with treatment guidelines and recommendations from high-quality studies and may be indicative of overtreatment among this large group of patients.

Impact of Comorbid Personality Disorders on Depression Treatment in Routine Outpatient Care

OBJECTIVE

The impact of personality disorder on treatment effectiveness for depression has been debated, and study results have been inconsistent. However, studies that report a negative impact of personality disorders on depression treatment outcomes are often characterized by uncontrolled treatment designs. Within such contexts, individuals with depression and personality disorders are at risk to receive suboptimal treatment. The aim of this retrospective observational study was to investigate whether and to what extent comorbid personality disorders were associated with the type and amount of depression treatment received in routine outpatient care.

METHODS

Retrospectively extracted data from electronic records of 1,455 outpatients treated for depression at several sites of a nationwide mental health provider in the Netherlands were included. The type and number of treatment sessions and visits were analyzed by using regression models.

RESULTS

Individuals with depression and comorbid personality disorders received more psychotherapy sessions than individuals without personality disorders, irrespective of depression severity. The number of pharmacotherapy sessions and supportive and crisis visits did not differ between individuals with and without comorbid personality disorders.

CONCLUSIONS

Individuals with depression and personality disorders received more intensive treatment than individuals without comorbid personality disorders. These results conflict with treatment guidelines and recommendations from high-quality studies and may be indicative of overtreatment among this large group of patients.

Selecting the optimal treatment for a depressed individual: Clinical judgment or statistical prediction?

BACKGROUND

Optimizing treatment selection is a way to enhance treatment success in major depressive disorder (MDD). In clinical practice, treatment selection heavily depends on clinical judgment. However, research has consistently shown that statistical prediction is as accurate - or more accurate - than predictions based on clinical judgment. In the context of new technological developments, the current aim was to compare the accuracy of clinical judgment versus statistical predictions in selecting cognitive therapy (CT) or interpersonal psychotherapy (IPT) for MDD.

METHODS

Data came from a randomized trial comparing CT (n=76) with IPT (n=75) for MDD. Prior to randomization, therapists' recommendations were formulated during multidisciplinary staff meetings. Statistical predictions were based on Personalized Advantage Index models. Primary outcomes were post-treatment and 17-month follow-up depression severity. Secondary outcome was treatment dropout.

RESULTS

Individuals receiving treatment according to their statistical prediction were less depressed at post-treatment and follow-up compared to those receiving their predicted non-indicated treatment. This difference was not found for recommended versus non-recommended treatments based on clinical judgment. Moreover, for individuals with an IPT recommendation by therapists, higher post-treatment and follow-up depression severity was found for those that actually received IPT compared to those that received CT. Recommendations based on statistical prediction and clinical judgment were not associated with differences in treatment dropout.

LIMITATIONS

Information on the clinical reasoning behind therapist recommendations was not collected, and statistical predictions were not externally validated.

CONCLUSIONS

Statistical prediction outperforms clinical judgment in treatment selection for MDD and has the potential to personalize treatment strategies.

Improving the efficiency of psychological treatment using outcome feedback technology

AIMS

This study evaluated the impact of applying computerized outcome feedback (OF) technology in a stepped care psychological service offering low and high intensity therapies for depression and anxiety.

METHODS

A group of therapists were trained to use OF based on routine outcome monitoring using depression (PHQ-9) and anxiety (GAD-7) measures. Therapists regularly reviewed expected treatment response graphs with patients and discussed cases that were "not on track" in clinical supervision. Clinical outcomes data were collected for all patients treated by this group (N = 594), six months before (controls = 349) and six months after the OF training (OF cases = 245). Symptom reductions in PHQ-9 and GAD-7 were compared between controls and OF cases using longitudinal multilevel modelling. Treatment duration and costs were compared using MANOVA. Qualitative interviews with therapists (N = 15) and patients (N = 6) were interpreted using thematic analysis.

RESULTS

OF technology was generally acceptable and feasible to integrate in routine practice. No significant between-group differences were found in post-treatment PHQ-9 or GAD-7 measures. However, OF cases had significantly lower average duration and cost of treatment compared to controls.

CONCLUSIONS

After adopting OF into their practice, this group of therapists attained similar clinical outcomes but within a shorter space of time and at a reduced average cost per treatment episode. We conclude that OF can improve the efficiency of stepped care.