Counselor Education Training Clinic Performance: An Archival Outcome Study

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Outcome research of counseling centers and community behavioral agencies has become central for evaluating services, clients’ protection, and stakeholders’ accountability requests. Research on the outcomes of counselor education training clinics is limited. Studying their client outcomes is especially important because all the providers in these clinics are counseling students-in-training with limited experience and practice. The results of these studies could serve to assess and improve service effectiveness and protect clients from potential harm. With these purposes in mind, we studied the outcomes of a counselor education training clinic during two periods in which they provided two different counseling modalities: in-person and telemental health. Significant psychological symptom reductions were observed in both periods. These findings provide positive accountability for the performance of a counselor education training clinic served by counseling students-in-training.

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Evaluating Effectiveness in a Hispanic-Serving Counselor Training Clinic
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Establishing the Reliability of a Tool for Assessing Israeli Physical Therapy Students' Clinical Performance
  • Sep 1, 2019
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  • Donny Schwartz + 1 more

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  • The Cochrane database of systematic reviews
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BackgroundSupervision is widely recognised as an important form of support for lay health service providers. However, guidance in appropriate supervision practices for task-shifting health interventions within the unique context of humanitarian emergencies is lacking. This review set out to identify empirically supported features of supervisory practices for lay health care providers in humanitarian emergencies, towards a stronger evidential basis for best practice in supportive supervision.MethodsIn January 2021, six databases and five non-governmental organizations’ websites were searched for articles examining the effectiveness of supervision for health care interventions delivered by lay providers in humanitarian settings. The inclusion criteria for study selection were qualitative or quantitative primary studies, articles published in peer reviewed journals or technical reports and the availability of the studies in English. The outcomes of interest were client clinical outcomes, health service efficiency and sustainability, and lay health care providers well-being. All articles were independently reviewed by the first and last authors.ResultsA total of 3371 articles were initially identified, with a total of 11 articles retained following the systematic screening process (two quantitative, four mixed methods and five qualitative studies). All studies generally reported positive impacts of supportive supervision on client outcomes, service sustainability, staff well-being and staff performance. Only four studies offered emotional support as part of supportive supervision. No studies evaluated the effect of supportive supervision on service efficiency. The narrative synthesis suggests significant challenges with providing supportive supervision, including excessive workloads, difficult supervisory relationships, geographic dispersion of lay providers, safety concerns, poorly trained supervisors, and lack of supervisory guidelines.ConclusionsMore efforts are needed to prioritize supportive supervision in task-shifting frameworks and to ensure that supervision is regular, consistent and of high-quality, with well-trained and well-supported supervisors.

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  • Counselling and Psychotherapy Research
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IntroductionMachine learning techniques have been leveraged to predict client psychological treatment outcomes. Few studies, however, have tested whether providing such model predictions as feedback to therapists improves client outcomes. This randomised controlled trial examined (1) the effects of implementing therapist feedback via a deep‐learning model (DLM) tool that predicts client treatment response (i.e., reliable improvement on the Patient Health Questionnaire‐9 [PHQ‐9] or Generalized Anxiety Disorder‐7 [GAD‐7]) to internet‐delivered cognitive behavioural therapy (iCBT) in routine clinical care and (2) therapist acceptability of this prediction tool.MethodsFifty‐one therapists were randomly assigned to access the DLM tool (vs. treatment as usual [TAU]) and oversaw the care of 2394 clients who completed repeated PHQ‐9 and GAD‐7 assessments.ResultsMultilevel growth curve models revealed no overall differences between the DLM tool vs. TAU conditions in client clinical outcomes. However, clients of therapists with the DLM tool used more tools, completed more activities and visited more platform pages. In subgroup analyses, clients predicted to be ‘not‐on‐track’ were statistically significantly more likely to have reliable improvement on the PHQ‐9 in the DLM vs. TAU group. Therapists with access to the DLM tool reported that it was acceptable for use, they had positive attitudes towards it, and reported it prompted greater examination and discussion of clients, particularly those predicted not to improve.ConclusionAltogether, the DLM tool was acceptable for therapists, and clients engaged more with the platform, with clinical benefits specific to reliable improvement on the PHQ‐9 for not‐on‐track clients. Future applications and considerations for implementing machine learning predictions as feedback tools within iCBT are discussed.

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