Dataset Information

Do individual, online motivational interviewing chat sessions enhance weight loss in a group-based, online weight control program?

ABSTRACT:

Objective

To examine whether the addition of online motivational interviewing (MI) chats to a Web-based, group behavioral obesity treatment program augments weight loss outcomes relative to the Web-based weight control program alone.

Methods

Healthy individuals (N = 398, 24% minority) with overweight/obesity were randomized to a 36-session group Internet behavioral weight control treatment (BT) or the same group Internet treatment plus six individual MI chat sessions (BT + MI). Both conditions received weekly synchronous online chat group sessions for 6 months followed by 12 monthly group chats. Participants in both groups received identical behavioral lessons and individualized therapist feedback on progress toward meeting exercise and calorie goals. BT + MI also received six individual MI sessions delivered by a separate MI counselor via Web chat. Weight loss was measured at 6 and 18 months.

Results

There were no significant differences in weight loss between BT (-5.5 ± 6.0 kg) and BT + MI (-5.1 ± 6.3 kg) at 6 months or at 18 months (-3.3 ± 7.1 kg vs. -3.5 ± 7.7 kg for BT and BT + MI, respectively). Attendance at group chats did not differ between groups, nor did self-monitoring patterns, suggesting comparable engagement in the weight control program in both conditions.

Conclusions

Online MI chat sessions were not a viable strategy to enhance Web-based weight control treatment outcomes.

SUBMITTER: West DS

PROVIDER: S-EPMC5093069 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Publications

Do individual, online motivational interviewing chat sessions enhance weight loss in a group-based, online weight control program?

West Delia Smith DS Harvey Jean R JR Krukowski Rebecca A RA Prewitt T Elaine TE Priest Jeffrey J Ashikaga Takamaru T

Obesity (Silver Spring, Md.) 20160912 11

<h4>Objective</h4>To examine whether the addition of online motivational interviewing (MI) chats to a Web-based, group behavioral obesity treatment program augments weight loss outcomes relative to the Web-based weight control program alone.<h4>Methods</h4>Healthy individuals (N = 398, 24% minority) with overweight/obesity were randomized to a 36-session group Internet behavioral weight control treatment (BT) or the same group Internet treatment plus six individual MI chat sessions (BT + MI). Bo ...[more]

PMID: 27616628

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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:Background:Motivational climate in exercise group environments would have an impact on adherence, effort and enjoyment. We examined the motivational climate among nursing home residents who were involved in group exercise sessions. Methods:This cross-sectional study was conducted in 10 nursing homes of Liège area that offer group exercise sessions. Sociodemographic data (age, sex, body mass index), cognitive status (by the Mini Mental State Examination) and independence in activities of daily living (by the Katz Scale) were retrieved in the medical records. The "Abbreviated-Perceived Motivational Climate in Exercise Questionnaire" was translated into French and then administered face to face with a clinical researcher. This is composed of 6 ego-involving climate items (corresponding to rivalry, comparison and favoritism) and 6 task-involving climate items (corresponding to valorization, individual efforts, self-improvement and cooperation). Each item is ranged on a 5-point Likert scale ranging from 1 (not at all focused on ego or task) to 5 (totally focused on ego or task). Each subscale has a total score expressed as an average. Results:A total of 102 subjects of exercise group sessions were included (84.3?±?7.7?years and 83 (81.4%) women). The mean score of task-involving and ego-evolving motivational climate was respectively 3.57 (SD?=?0.67) and 1.52 (SD?=?0.49), suggesting that the motivational climate was more focused on the task-involving climate than on ego-involving climate. Some items results were of particular interest: 55.9% of the respondents found that the instructor doesn't remark/reward when they try hard, 63.7% said that the instructor doesn't encourage mutual aid and 38.2% found that instructor doesn't encourage to do new exercises. Conclusions:Participants tended to perceive motivational climate as more task-involving than ego-involving. The absence of individual positive feedback, new exercises and mutual aid were also highlighted.

Dataset Information

Do individual, online motivational interviewing chat sessions enhance weight loss in a group-based, online weight control program?

Objective

Methods

Results

Conclusions

Publications

Do individual, online motivational interviewing chat sessions enhance weight loss in a group-based, online weight control program?

Similar Datasets

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