Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: The recent onset of the COVID-19 pandemic and the social distancing requirement have created an increased demand for virtual support programs. Advances in artificial intelligence (AI) may offer novel solutions to management challenges such as the lack of emotional connections within virtual group interventions. Using typed text from online support groups, AI can help identify the potential risk of mental health concerns, alert group facilitator(s), and automatically recommend tailored resources while monitoring patient outcomes. Objective: The aim of this mixed methods, single-arm study was to evaluate the feasibility, acceptability, validity, and reliability of an AI-based co-facilitator (AICF) among CancerChatCanada therapists and participants to monitor online support group participants’ distress through a real-time analysis of texts posted during the support group sessions. Specifically, AICF (1) generated participant profiles with discussion topic summaries and emotion trajectories for each session, (2) identified participant(s) at risk for increased emotional distress and alerted the therapist for follow-up, and (3) automatically suggested tailored recommendations based on participant needs. Online support group participants consisted of patients with various types of cancer, and the therapists were clinically trained social workers. Methods: Our study reports on the mixed methods evaluation of AICF, including therapists’ opinions as well as quantitative measures. AICF’s ability to detect distress was evaluated by the patient's real-time emoji check-in, the Linguistic Inquiry and Word Count software, and the Impact of Event Scale-Revised. Results: Although quantitative results showed only some validity of AICF’s ability in detecting distress, the qualitative results showed that AICF was able to detect real-time issues that are amenable to treatment, thus allowing therapists to be more proactive in supporting every group member on an individual basis. However, therapists are concerned about the ethical liability of AICF’s distress detection function. Conclusions: Future works will look into wearable sensors and facial cues by using videoconferencing to overcome the barriers associated with text-based online support groups.

This study aimed to explore the relationship between gender socialization and psychosocial well-being among young women diagnosed with and treated for breast cancer. A total of 113 women between the ages of 18–49 completed a one-time questionnaire package. Four key measures of gender socialization were included: Gender Role Socialization Scale (GRSS), Objectified Body Consciousness Scale (OBCS), Mental Freedom Scale (MFS), and Silencing the Self Scale (SSS). Two measures of psychosocial well-being were included: Functional Assessment of Cancer Therapy-Breast (FACT-B) and Experience of Embodiment Scale (EES). Correlational and regression analyses were conducted to assess the relationship between gender socialization variables and well-being. In multiple regression models, GRSS and MFS added significant increments to the prediction of variance of the FACT-B (R² = 23.0%). In contrast, the OBCS and MFS added significant increments to the prediction of variance of the EES (R² = 47.0%). Findings suggested that women with greater endorsements to proscribed gender socialization were associated with poor well-being scores. Women who endorsed a critical stance, resisting traditional gender-role expectations, objectification pressures, and other social discourses, were associated with greater well-being scores. Future studies are needed to examine the impact of gender socialization on the well-being of young people with breast cancer.

Background: Educational programs that enhance healthcare providers’ competence in managing the care of patients with sexual dysfunction following prostate cancer treatments are needed to facilitate comprehensive sexual health treatments for patients and their partners. Aim: In this study we evaluated the impact of a real-world online sexual health educational intervention called the True North Sexual Health and Rehabilitation eTraining Program. This program is designed to increase healthcare providers’ knowledge and self-efficacy in providing sexual healthcare to prostate cancer patients and their partners. Methods: Healthcare providers were invited to join a 12-week virtual training program. Participants completed precourse surveys (n = 89), retrospective prepost surveys (n = 58), and a 3-month follow-up survey (subset n = 18) to assess retention of relevant outcomes. Additionally, a course satisfaction survey was administered to participants (n = 57) at the end of the course. Outcomes: The main outcomes focused on participants’ perceived knowledge and self-efficacy in conducting assessments and providing interventions for various relevant physical, functional, psychological, and relational domains of sexual dysfunction in prostate cancer patients and their partners. Results: According to the retrospective analysis of post-then-pre–survey results, graduates perceived that their knowledge of and self-efficacy in providing sexual health counseling improved after completing the course. The 3-month follow-up survey indicated that the course graduate self-efficacy remained high 3 months after the course. Furthermore, the satisfaction survey indicated that a vast majority (98.2%) of participants were satisfied with the educational intervention. Clinical Implications: This real-world sexual health educational intervention can increase self-efficacy and knowledge in healthcare providers who are supporting prostate cancer patients dealing with sexual dysfunction. Strengths and Limitations: The use of a retrospective post-then-pre–survey helped to mitigate response shift bias while minimizing data gaps. However, it is important to note that this investigation was not a traditional research study and lacked a control group, thus limiting causal attributions. Conclusion: The True North Sexual Health and Rehabilitation eTraining program acts as an accessible and effective resource for healthcare providers seeking specialized training in providing sexual healthcare for prostate cancer patients and their partners.

A growing number of face-to-face group therapy interventions are being translated into online versions in psycho-oncology. Yet few researchers have systematically described the complex translation process or systematic approaches used to maintain the integrity of the original empirically supported interventions. In this article, we present a case study to illustrate the process of translating an evidence-based face-to-face therapy group, Restoring Body Image after Cancer (ReBIC) into an online format. We highlight how three critical therapeutic components from the original intervention (guided imagery exercises, psychoeducational reading materials, and psychotherapeutic group processes) were maintained and translated for online delivery. We provide preliminary recommendations for future translation efforts of text-based online group therapies to encourage best practices.

Background: Commonly offered as supportive care, therapist-led online support groups (OSGs) are a cost-effective way to provide support to individuals affected by cancer. One important indicator of a successful OSG session is group cohesion; however, monitoring group cohesion can be challenging due to the lack of nonverbal cues and in-person interactions in text-based OSGs. The Artificial Intelligence–based Co-Facilitator (AICF) was designed to contextually identify therapeutic outcomes from conversations and produce real-time analytics. Objective: The aim of this study was to develop a method to train and evaluate AICF’s capacity to monitor group cohesion. Methods: AICF used a text classification approach to extract the mentions of group cohesion within conversations. A sample of data was annotated by human scorers, which was used as the training data to build the classification model. The annotations were further supported by finding contextually similar group cohesion expressions using word embedding models as well. AICF performance was also compared against the natural language processing software Linguistic Inquiry Word Count (LIWC). Results: AICF was trained on 80,000 messages obtained from Cancer Chat Canada. We tested AICF on 34,048 messages. Human experts scored 6797 (20%) of the messages to evaluate the ability of AICF to classify group cohesion. Results showed that machine learning algorithms combined with human input could detect group cohesion, a clinically meaningful indicator of effective OSGs. After retraining with human input, AICF reached an F1-score of 0.82. AICF performed slightly better at identifying group cohesion compared to LIWC. Conclusions: AICF has the potential to assist therapists by detecting discord in the group amenable to real-time intervention. Overall, AICF presents a unique opportunity to strengthen patient-centered care in web-based settings by attending to individual needs. International Registered Report Identifier (IRRID): RR2-10.2196/21453