Therapy Mode Preference Scale: Preliminary Validation Methodological Design
Therapy Mode Preference Scale: Preliminary Validation Methodological Design

Therapy Mode Preference Scale: Preliminary Validation Methodological Design

JMIR Form Res. 2024 Nov 29;8:e65477. doi: 10.2196/65477.

ABSTRACT

BACKGROUND: The use of tele-mental health care increased rapidly in 2020 as a critical response to the COVID-19 pandemic, serving as an effective contact-free alternative to treatment. Today, tele-mental health care remains a viable option for individuals with geographic and physical barriers to treatment. However, there are several potential therapeutic disadvantages to tele-mental health care (ie, missing nonverbal signals, handling crises, confidentiality, weakened social connection in group therapy) that should be evaluated. While published literature has explored client satisfaction within teletherapy and the effect of using technology for tele-mental health care demands, there is a need for published surveys that evaluate the therapeutic experience in teletherapy and in-person mediums of care.

OBJECTIVE: The authors of this study sought to develop and validate a survey that could evaluate the comparative impact of teletherapy and in-person care from a therapeutic perspective across key factors (ie, therapeutic alliance, engagement, rapport, and confidentiality).

METHODS: Participants were clients who experienced both tele-mental health care and in-person therapy at an intensive outpatient mental health treatment program for young adults from April 2020 through June 2022. Generated items on the survey were formulated based on input from experts in the field and existing validated scales. All individuals completed the survey on the internet, following informed consent (n=89). An exploratory factor analysis was conducted to understand factor structure, and Cronbach α was used to determine internal consistency. Incremental validity was demonstrated through a hierarchical linear regression.

RESULTS: The exploratory factor analysis revealed a 14-item, 3-factor structure. All 14 items correlated at a minimum of 0.30 with at least one other item. Kaiser-Meyer-Olkin measure of sampling adequacy was 0.75 and Bartlett’s test of sphericity was significant (χ291=528.41, P<.001). In total, 3 factors accounted for 61% of the variance, and the preliminary Cronbach α (α=0.71) indicates a satisfactory level of internal consistency. The Zoom Exhaustion and Fatigue Scale (ZEF) and Client Satisfaction Questionnaire (CSQ; -0.29) were significantly correlated, as well as the ZEF and Therapy Mode Preference Scale (TMPS; -0.31), and CSQ and TMPS (0.50; P<.001). Hierarchical linear regression revealed that the CSQ significantly accounted for additional variance in the TMPS (P<.001). With the ZEF entered into the model, no further variance was accounted for (P=.06).

CONCLUSIONS: Continual research is warranted to expand the current findings by validating this standardized tool for assessing the therapeutic impact of teletherapy versus in-person care in a generalizable population.

PMID:39612373 | DOI:10.2196/65477