Dataset Information

Can Outcomes of a Chat-Based Suicide Prevention Helpline Be Improved by Training Counselors in Motivational Interviewing? A Non-randomized Controlled Trial.

ABSTRACT:

Objective

To examine whether the outcomes of a chat-based suicide-prevention helpline could be improved by training counselors in motivational interviewing (MI).

Methods

In a pre- and post-test design, visitors of a chat-based suicide prevention helpline received either the Five-Phase Model (treatment as usual [TAU]) or MI. They completed a pre- and post-chat questionnaire on several suicide-related risk factors. Linear mixed modeling was used to estimate the effect of the condition. Furthermore, the treatment proficiency of newly trained counselors was assessed using MI-Scope.

Results

A total of 756 visitors and 55 counselors were included in this study. The visitors showed an improvement in suicidal ideation and psychological risk factors after a chat conversation. However, there were no significant differences between the MI and TAU conditions (β = 0.03, 95% CI [-0.23-0.30], p = 0.80). The treatment integrity indices showed that the counselors mostly used MI-consistent techniques but were unable to strategically employ these techniques to evoke enough change talk.

Conclusions

MI and TAU led to comparable outcomes in a chat-based suicide prevention helpline. The effectiveness of MI might improve by intensifying or improving the training of counselors, keeping the process of engaging more concise or offering visitors multiple sessions of MI.

SUBMITTER: Janssen W

PROVIDER: S-EPMC9253377 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

Can Outcomes of a Chat-Based Suicide Prevention Helpline Be Improved by Training Counselors in Motivational Interviewing? A Non-randomized Controlled Trial.

Janssen Wilco W van Raak Jeroen J van der Lucht Yannick Y van Ballegooijen Wouter W Mérelle Saskia S

Frontiers in digital health 20220621

<h4>Objective</h4>To examine whether the outcomes of a chat-based suicide-prevention helpline could be improved by training counselors in motivational interviewing (MI).<h4>Methods</h4>In a pre- and post-test design, visitors of a chat-based suicide prevention helpline received either the Five-Phase Model (treatment as usual [TAU]) or MI. They completed a pre- and post-chat questionnaire on several suicide-related risk factors. Linear mixed modeling was used to estimate the effect of the conditi ...[more]

PMID: 35801118

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Project description:BackgroundThe working environment of a suicide prevention helpline requires high emotional and cognitive awareness from chat counselors. A shared opinion among counselors is that as a chat conversation becomes more difficult, it takes more effort and a longer amount of time to compose a response, which, in turn, can lead to writer's block.ObjectiveThis study evaluates and then designs supportive technology to determine if a support system that provides inspiration can help counselors resolve writer's block when they encounter difficult situations in chats with help-seekers.MethodsA content-based recommender system with sentence embedding was used to search a chat corpus for similar chat situations. The system showed a counselor the most similar parts of former chat conversations so that the counselor would be able to use approaches previously taken by their colleagues as inspiration. In a within-subject experiment, counselors' chat replies when confronted with a difficult situation were analyzed to determine if experts could see a noticeable difference in chat replies that were obtained in 3 conditions: (1) with the help of the support system, (2) with written advice from a senior counselor, or (3) when receiving no help. In addition, the system's utility and usability were measured, and the validity of the algorithm was examined.ResultsA total of 24 counselors used a prototype of the support system; the results showed that, by reading chat replies, experts were able to significantly predict if counselors had received help from the support system or from a senior counselor (P=.004). Counselors scored the information they received from a senior counselor (M=1.46, SD 1.91) as significantly more helpful than the information received from the support system or when no help was given at all (M=-0.21, SD 2.26). Finally, compared with randomly selected former chat conversations, counselors rated the ones identified by the content-based recommendation system as significantly more similar to their current chats (β=.30, P<.001).ConclusionsSupport given to counselors influenced how they responded in difficult conversations. However, the higher utility scores given for the advice from senior counselors seem to indicate that specific actionable instructions are preferred. We expect that these findings will be beneficial for developing a system that can use similar chat situations to generate advice in a descriptive style, hence helping counselors through writer's block.

Project description:BackgroundWith the rise of computer science and artificial intelligence, analyzing large data sets promises enormous potential in gaining insights for developing and improving evidence-based health interventions. One such intervention is the counseling strategy motivational interviewing (MI), which has been found effective in improving a wide range of health-related behaviors. Despite the simplicity of its principles, MI can be a challenging skill to learn and requires expertise to apply effectively.ObjectiveThis study aims to investigate the performance of artificial intelligence models in classifying MI behavior and explore the feasibility of using these models in online helplines for mental health as an automated support tool for counselors in clinical practice.MethodsWe used a coded data set of 253 MI counseling chat sessions from the 113 Suicide Prevention helpline. With 23,982 messages coded with the MI Sequential Code for Observing Process Exchanges codebook, we trained and evaluated 4 machine learning models and 1 deep learning model to classify client- and counselor MI behavior based on language use.ResultsThe deep learning model BERTje outperformed all machine learning models, accurately predicting counselor behavior (accuracy=0.72, area under the curve [AUC]=0.95, Cohen κ=0.69). It differentiated MI congruent and incongruent counselor behavior (AUC=0.92, κ=0.65) and evocative and nonevocative language (AUC=0.92, κ=0.66). For client behavior, the model achieved an accuracy of 0.70 (AUC=0.89, κ=0.55). The model's interpretable predictions discerned client change talk and sustain talk, counselor affirmations, and reflection types, facilitating valuable counselor feedback.ConclusionsThe results of this study demonstrate that artificial intelligence techniques can accurately classify MI behavior, indicating their potential as a valuable tool for enhancing MI proficiency in online helplines for mental health. Provided that the data set size is sufficiently large with enough training samples for each behavioral code, these methods can be trained and applied to other domains and languages, offering a scalable and cost-effective way to evaluate MI adherence, accelerate behavioral coding, and provide therapists with personalized, quick, and objective feedback.

Project description:BackgroundEvery month, around 3800 people complete an anonymous self-test for suicidal thoughts on the website of the Dutch suicide prevention helpline. Although 70% score high on the severity of suicidal thoughts, <10% navigate to the web page about contacting the helpline.ObjectiveThis study aimed to test the effectiveness of a brief barrier reduction intervention (BRI) in motivating people with severe suicidal thoughts to contact the suicide prevention helpline, specifically in high-risk groups such as men and middle-aged people.MethodsWe conducted a fully automated, web-based, randomized controlled trial. Respondents with severe suicidal thoughts and little motivation to contact the helpline were randomly allocated either to a brief BRI, in which they received a short, tailored message based on their self-reported barrier to the helpline (n=610), or a general advisory text (care as usual as the control group: n=612). Effectiveness was evaluated using both behavioral and attitudinal measurements. The primary outcome measure was the use of a direct link to contact the helpline after completing the intervention or control condition. Secondary outcomes were the self-reported likelihood of contacting the helpline and satisfaction with the received self-test.ResultsIn total, 2124 website visitors completed the Suicidal Ideation Attributes Scale and the demographic questions in the entry screening questionnaire. Among them, 1222 were randomized into the intervention or control group. Eventually, 772 respondents completed the randomized controlled trial (intervention group: n=369; control group: n=403). The most selected barrier in both groups was "I don't think that my problems are serious enough." At the end of the trial, 33.1% (n=122) of the respondents in the intervention group used the direct link to the helpline. This was not significantly different from the respondents in the control group (144/403, 35.7%; odds ratio 0.87, 95% CI 0.64-1.18, P=.38). However, the respondents who received the BRI did score higher on their self-reported likelihood of contacting the helpline at a later point in time (B=0.22, 95% CI 0.12-0.32, P≤.001) and on satisfaction with the self-test (B=0.27, 95% CI 0.01-0.53, P=.04). For male and middle-aged respondents specifically, the results were comparable to that of the whole group.ConclusionsThis trial was the first time the helpline was able to connect with high-risk website visitors who were hesitant to contact the helpline. Although the BRI could not ensure that those respondents immediately used the direct link to the helpline at the end of the trial, it is encouraging that respondents indicated that they were more likely to contact the helpline at a later point in time. In addition, this low-cost intervention provided greater insight into the perceived barriers to service. Follow-up research should be focused on identifying the added value of other components (eg, video or photo material) in the BRI and increasing its effectiveness, especially for men and middle-aged people.

Dataset Information

Can Outcomes of a Chat-Based Suicide Prevention Helpline Be Improved by Training Counselors in Motivational Interviewing? A Non-randomized Controlled Trial.

Objective

Methods

Results

Conclusions

Publications

Can Outcomes of a Chat-Based Suicide Prevention Helpline Be Improved by Training Counselors in Motivational Interviewing? A Non-randomized Controlled Trial.

Similar Datasets

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