Common obstacles and solutions to deliver effective psychotherapy

  • Research type

    Research Study

  • Full title

    Understanding common obstacles and solutions to deliver effective psychological treatment for depression and anxiety

  • IRAS ID

    259658

  • Contact name

    Jaime Delgadillo

  • Contact email

    j.delgadillo@sheffield.ac.uk

  • Sponsor organisation

    University of Sheffield

  • Duration of Study in the UK

    1 years, 1 months, 4 days

  • Research summary

    Large-scale studies of psychotherapy in routine care demonstrate that approximately 30% of patients do not show statistically reliable improvement and around 10% of patients show deterioration following therapy. Previous studies have demonstrated that outcome feedback (OF) can facilitate the early identification of patients at risk of none response to treatment. OF refers to a quality assurance strategy involving the routine monitoring of patients’ symptoms using standardised measures. OF classifies patients as being ‘on track’ or ‘not on track’ (NOT) to a good treatment outcome in line with a comparative clinical sample. When patients are classified as ‘NOT’, an automated alert prompts therapists to assess why their patient is ‘NOT’ and apply trouble-shooting strategies to resolve barriers to treatment progression. Whilst the effectiveness of OF is well-established, there is scarce research about its mechanism of action. The proposed study aims to determine the processes and mechanisms of action that underlie the effectiveness of OF. Therapists will be recruited from IAPT services in England that utilise OF in routine practice. Therapists will use OF and will track sessional outcomes on the patient health questionnaire (PHQ-9) and generalised anxiety scale (GAD-7) with all patients over the course of 10 months. When cases become ‘NOT’, therapists will be required to document the potential obstacles to improvement and the implementation of trouble-shooting strategies using a 'process' measure developed by the research team. Data will be analysed using qualitative and quantitative methods. The text-based process data will be analysed based on the principles of content analysis assisted by natural language processing. Quantitative patient-level outcome data and the trouble-shooting strategy themes derived from the content analysis will then be analysed using logistic regression. The intended output of this exploration is to develop a trouble-shooting guide which can be translated to training courses and utilised in routine care.

  • REC name

    Yorkshire & The Humber - South Yorkshire Research Ethics Committee

  • REC reference

    19/YH/0178

  • Date of REC Opinion

    16 Jul 2019

  • REC opinion

    Further Information Favourable Opinion