Cited by 12Psychotherapy Techniques and ApplicationsDigital Mental Health InterventionsAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes

Action recommendations review in community-based therapy and depression and anxiety outcomes: a machine learning approach

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Spinrad, Amit, Taylor, C. Barr, Ruzek, Josef I., Jefroykin, Samuel, Friedlander, Tamar, Feleke, Israela, Lev-Ari, Hila, Szapiro, Natalia +1 more·2024·BMC Psychiatry

Abstract

Background: While the positive impact of homework completion on symptom alleviation is well-established, the pivotal role of therapists in reviewing these assignments has been under-investigated. This study examined therapists' practice of assigning and reviewing action recommendations in therapy sessions, and how it correlates with patients’ depression and anxiety outcomes. Methods: We analyzed 2,444 therapy sessions from community-based behavioral health programs. Machine learning models and natural language processing techniques were deployed to discern action recommendations and their subsequent reviews. The extent of the review was quantified by measuring the proportion of session dialogues reviewing action recommendations, a metric we refer to as “review percentage”. Using Generalized Estimating Equations modeling, we evaluated the correlation between this metric and changes in clients' depression and anxiety scores. Results: Our models achieved 76% precision in capturing action recommendations and 71.1% in reviewing them. Using these models, we found that therapists typically provided clients with one to eight action recommendations per session to engage in outside therapy. However, only half of the sessions included a review of previously assigned action recommendations. We identified a significant interaction between the initial depression score and the review percentage (p = 0.045). When adjusting for this relationship, the review percentage was positively and significantly associated with a reduction in depression score (p = 0.032). This suggests that more frequent review of action recommendations in therapy relates to greater improvement in depression symptoms. Further analyses highlighted this association for mild depression (p = 0.024), but not for anxiety or moderate to severe depression. Conclusions: An observed positive association exists between therapists’ review of previous sessions’ action recommendations and improved treatment outcomes among clients with mild depression, highlighting the possible advantages of consistently revisiting therapeutic homework in real-world therapy settings. Results underscore the importance of developing effective strategies to help therapists maintain continuity between therapy sessions, potentially enhancing the impact of therapy.

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  • Therapists follow up on homework with clients only approximately 50% of the time, which reduces opportunities to reinforce and consolidate client learning.

    “In addition, therapists follow up on homework with clients only approximately 50% of the time, which reduces opportunities to reinforce and consolidate client learning [10,11].”

    From Clinical Effects of Asynchronous Provider-Guided Practice Sessions During Blended Care Therapy for Anxiety and Depression: Pragmatic Retrospective Cohort Study (2024) · cites this paper as [10]

    The Discussion reports that approximately half of the sessions included a review of the previous session’s action recommendations, supporting the approximate frequency. The study measured session-level review of action recommendations, not follow-up on every homework assignment, and it does not establish that limited review reduces opportunities to reinforce and consolidate client learning. (LLM, conf=0.86)

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Research works printed but not linked: 3

  1. [25]Bahar L, Rego S, Sadeh-Sharvit S. Use of Natural Language Processing to Identify Climate Distress in Therapy. Under Review.
  2. [34]Osborne JW. Notes on the use of data transformations. Practical Assessment, Research and Evaluation. 2002;8(6):1–7.
  3. [43]Ruzek J, Sadeh-Sharvit S, Bunge E, Sheperis D, Fitzsimmons-Craft E, Guinn V, et al. How to Train the Psychologist of the Future in the Use of Digital Therapeutics. Psychol Res Pr. In press. EMID: e0da8b1535788574.

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Authors
Spinrad, A., Taylor, C. B., Ruzek, J. I., Jefroykin, S., Friedlander, T., Feleke, I., Lev-Ari, H., Szapiro, N., & Sadeh-Sharvit, S.
Affiliations
Palo Alto University (US)
Corresponding author
Spinrad, Amit
Venue
BMC Psychiatry
Published
2024-02-16
Volume
24
Issue
1
Pages
133-133
ISSN
1471-244X (ISSN-L)
OpenAlex
W4391882748
Cited by
12
References
39
Citations by year
2026: 1 · 2025: 5 · 2024: 6
FWCI
5.93
Type
journal article
Language
en
Open access
Locations
  • BMC Psychiatry (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Topics
  • Social Sciences › Psychology › Clinical Psychology › Psychotherapy Techniques and Applications
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Keywords
action recommendations, homework review, depression outcomes, mild depression, continuity of care
MeSH terms
Anxiety, Anxiety Disorders, Depression, Depressive Disorder, Humans, Treatment Outcome

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