TY - JOUR

T1 - Web-based depression treatment

T2 - associations of clients’ word use with adherence and outcome

AU - van der Zanden, Rianne

AU - Curie, Keshia

AU - van Londen, Monique

AU - Kramer, Jeannet

AU - Steen, Gerard

AU - Cuijpers, Pim

N1 - Funding Information: The data used in this study derived from a randomised controlled trial that was funded by ZonMw (Netherlands Organization for Health Research and Development) , Grant no. 61300036 . Ethical approval was granted by an Independent Medical Ethics Committee (CCMO no. NL18984.097.07 ). No funding bodies had any role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

PY - 2014/5/1

Y1 - 2014/5/1

N2 - Background: The growing number of web-based psychological treatments, based on textual communication, generates a wealth of data that can contribute to knowledge of online and face-to-face treatments. We investigated whether clients' language use predicted treatment outcomes and adherence in Master Your Mood (MYM), an online group course for young adults with depressive symptoms. Methods: Among 234 participants from a randomised controlled trial of MYM, we tested whether their word use on course application forms predicted baseline levels of depression, anxiety and mastery, or subsequent treatment adherence. We then analysed chat session transcripts of course completers (n = 67) to investigate whether word use changes predicted changes in treatment outcomes. Results: Depression improvement was predicted by increasing use of ‘discrepancy words’ during treatment (e.g. should). At baseline, more discrepancy words predicted higher mastery level. Adherence was predicted by more words used at application, more social words and fewer discrepancy words. Limitations: Many variables were included, increasing the chance of coincidental results. This risk was constrained by examining only those word categories that have been investigated in relation to depression or adherence. Conclusions: This is the first study to link word use during treatment to outcomes of treatment that has proven to be effective in an RCT. The results suggest that paying attention to the length of problem articulation at application and to ‘discrepancy words’ may be wise, as these seem to be psychological markers. To expand knowledge of word use as psychological marker, research on web-based treatment should include text analysis.

AB - Background: The growing number of web-based psychological treatments, based on textual communication, generates a wealth of data that can contribute to knowledge of online and face-to-face treatments. We investigated whether clients' language use predicted treatment outcomes and adherence in Master Your Mood (MYM), an online group course for young adults with depressive symptoms. Methods: Among 234 participants from a randomised controlled trial of MYM, we tested whether their word use on course application forms predicted baseline levels of depression, anxiety and mastery, or subsequent treatment adherence. We then analysed chat session transcripts of course completers (n = 67) to investigate whether word use changes predicted changes in treatment outcomes. Results: Depression improvement was predicted by increasing use of ‘discrepancy words’ during treatment (e.g. should). At baseline, more discrepancy words predicted higher mastery level. Adherence was predicted by more words used at application, more social words and fewer discrepancy words. Limitations: Many variables were included, increasing the chance of coincidental results. This risk was constrained by examining only those word categories that have been investigated in relation to depression or adherence. Conclusions: This is the first study to link word use during treatment to outcomes of treatment that has proven to be effective in an RCT. The results suggest that paying attention to the length of problem articulation at application and to ‘discrepancy words’ may be wise, as these seem to be psychological markers. To expand knowledge of word use as psychological marker, research on web-based treatment should include text analysis.

KW - Health sciences

KW - depression

KW - Linguistic

KW - web-based treatment

KW - text analysis

KW - Word use

KW - E-mental health

KW - Psychology

UR - http://www.scopus.com/inward/record.url?scp=84897909905&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/f1f6e69f-787a-3a7a-9aad-725667685eca/

U2 - 10.1016/j.jad.2014.01.005

DO - 10.1016/j.jad.2014.01.005

M3 - Journal articles

C2 - 24709016

VL - 160

SP - 10

EP - 13

JO - Journal of Affective Disorders

JF - Journal of Affective Disorders

SN - 0165-0327

ER -