https://mental.jmir.org/issue/feedJMIR Mental Health2023-01-09T10:00:08-05:00JMIR Publicationseditor@jmir.orgOpen Journal Systems Unless stated otherwise, all articles are open-access distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work ("first published in the Journal of Medical Internet Research...") is properly cited with original URL and bibliographic citation information. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. Internet interventions, technologies, and digital innovations for mental health and behavior change. JMIR Mental Health is the official journal of the Society of Digital Psychiatry . https://mental.jmir.org/2024/1/e55528/ Efficacy of BrighterSide, a Self-Guided App for Suicidal Ideation: Randomized Controlled Trial2024-03-18T14:30:11-04:00Natasha JosifovskiMichelle TorokPhilip BatterhamQuincy WongJoanne R BeamesAdam TheobaldSarah HollandKit HuckvaleJo RileyNicole CockayneHelen ChristensenMark LarsenBackground: Self-guided digital interventions can reduce the severity of suicidal ideation, although there remain relatively few, rigorously evaluated, smartphone apps targeting suicidality. Objective: This trial evaluated whether the BrighterSide® smartphone app intervention was superior to a waitlist control group at reducing the severity of suicidal ideation. Methods: 550 adults aged 18-65 with recent suicidal ideation were recruited from the Australian community. In this randomized controlled trial, participants were randomly assigned to receive either the BrighterSide® intervention app, or to a waitlist control group which involved treatment as usual. The app was self-guided, and participants could use the app at their own pace for the duration of the study period. Self-report measures were collected at baseline, 6-weeks, and 12-weeks. The primary outcome was severity and frequency of suicidal ideation, and secondary outcomes included psychological distress and functioning and recovery. Additional data were collected on app engagement and participant feedback. Results: Suicidal ideation reduced over time for all participants, but there was no significant interaction between group and time. Similar improvements were observed for self-harm, functioning and recovery, days out of role, and coping. Psychological distress was significantly lower in the intervention group at the 6-week follow-up, but this was not maintained at 12 weeks. Conclusions: The BrighterSide® app did not lead to a significant improvement in suicidal ideation, relative to a waitlist control group. Possible reasons for this null finding are discussed. Clinical Trial: Australian New Zealand Clinical Trials Registry (ACTRN12621000712808). 2024-03-18T14:30:11-04:00 https://mental.jmir.org/2024/1/e53043/ Comparing the Perspectives of Generative AI, Mental Health Experts, and the General Public on Schizophrenia Recovery: Case Vignette Study2024-03-18T13:45:08-04:00Zohar ElyosephInbar LevkovichBackground: Background: The current paradigm in mental healthcare focuses on clinical recovery and symptom remission. This model’s efficacy is influenced by therapist trust in patient recovery potential and therapeutic relationship depth. Schizophrenia is a chronic illness with severe symptoms where the possibility of recovery is a matter of debate. As artificial intelligence (AI) becomes integrated into the healthcare field, it is important to examine its ability to assess recovery potential in major psychiatric disorders such as schizophrenia. Objective: Objectives: To evaluate the ability of Large Languets Models (LLMs) in comparison to mental health professionals to assess the prognosis of schizophrenia with and without treatments and the long term positive and negative outcomes. Methods: Methods: Vignettes were input to LLMs interfaces and assessed ten times by four AI platforms: ChatGPT-3.5, ChatGPT-4, Google Bard, and Claude. A total of 80 evaluations were collected and benchmarked against existing norms to analyze what mental health professionals (general practitioners, psychiatrists, clinical psychologists and mental health nurses) and the general public think about schizophrenia prognosis with and without treatment and the positive and negative long-term outcomes of schizophrenia interventions. Results: Results: Prognosis with professional help: ChatGPT-3.5 was notably pessimistic, whereas ChatGPT-4, Claude and BARD aligned with professional views but differed from the general public. All LLMs believed untreated schizophrenia would remain static or worsen without professional help. Long-term outcomes: ChatGPT-4 and Claude predicted more negative outcomes than BARD and ChatGPT-3.5. For positive outcomes, ChatGPT-3.5 and Claude were more negative than BARD and ChatGPT-4. Conclusions: Conclusions: The findings that three out of the four LLMs aligned closely with the predictions of mental health professionals when considering the 'with treatment' condition is a demonstration of the potential of this technology in providing professional clinical prognosis. The pessimistic assessment of ChatGPT 3.5 is a disturbing finding since it may reduce the motivation of patients to start or persist with treatment for schizophrenia. Overall, while LLMs hold promise in augmenting healthcare, their application necessitates rigorous validation and a harmonious blend with human expertise. 2024-03-18T13:45:08-04:00 https://mental.jmir.org/2024/1/e52790/ Effectiveness of One Videoconference-Based Exposure and Response Prevention Session at Home in Adjunction to Inpatient Treatment in Persons With Obsessive-Compulsive Disorder: Nonrandomized Study2024-03-13T10:30:03-04:00Ulrich VoderholzerAdrian MeuleStefan KochSimone PfeufferAnna-Lena NetterDirk LehrEva Maria Zisler<strong>Background:</strong> Therapist-guided exposure and response prevention (ERP) for the treatment of obsessive-compulsive disorder (OCD) is frequently conducted within clinical settings but rarely at places where patients are usually confronted with OCD symptom-provoking situations in daily life (eg, at home). <strong>Objective:</strong> This study aimed to investigate patients’ views on 1 ERP session at home via videoconference and its impact on treatment outcome. <strong>Methods:</strong> A total of 64 inpatients with OCD received 1 session of therapist-guided videoconference-based ERP at home in adjunction to a multimodal inpatient treatment between 2015 and 2020. <strong>Results:</strong> Compared with 64 age- and sex-matched controls who received a multimodal inpatient treatment without 1 session of videoconference-based ERP at home, patients who received 1 session of videoconference-based ERP in adjunction to a multimodal inpatient treatment showed stronger reductions in OCD symptom severity from admission to discharge. Before the videoconference-based ERP session, patients reported high rationale credibility and treatment expectancy. After the videoconference-based ERP session, patients reported medium-to-high positive mood as well as depth and smoothness of the session, and they perceived the working alliance as high. <strong>Conclusions:</strong> Results highlight the importance of administering therapist-guided ERP sessions in patients’ natural environment to enhance treatment response in OCD. Videoconference-based ERP as add-on to treatment as usual is, therefore, a promising approach to facilitate the application of ERP in patients’ natural environment and foster the generalization of ERP conducted in clinical settings. 2024-03-13T10:30:03-04:00 https://mental.jmir.org/2024/1/e48147/ Action Opportunities to Pursue Responsible Digital Care for People With Intellectual Disabilities: Qualitative Study2024-02-28T10:15:04-05:00Nienke M SiebelinkKirstin N van DamDirk R M LukkienBrigitte BoonMerlijn SmitsAgnes van der Poel<strong>Background:</strong> Responsible digital care refers to any intentional systematic effort designed to increase the likelihood of a digital care technology developed through ethical decision-making, being socially responsible and aligned with the values and well-being of those impacted by it. <strong>Objective:</strong> We aimed to present examples of action opportunities for (1) designing “technology”; (2) shaping the “context” of use; and (3) adjusting the behavior of “users” to guide responsible digital care for people with intellectual disabilities. <strong>Methods:</strong> Three cases were considered: (1) design of a web application to support the preparation of meals for groups of people with intellectual disabilities, (2) implementation of an app to help people with intellectual disabilities regulate their stress independently, and (3) implementation of a social robot to stimulate interaction and physical activity among people with intellectual disabilities. Overall, 26 stakeholders participated in 3 multistakeholder workshops (case 1: 10/26, 38%; case 2: 10/26, 38%; case 3: 6/26, 23%) based on the “guidance ethics approach.” We identified stakeholders’ values based on bottom-up exploration of experienced and expected effects of using the technology, and we formulated action opportunities for these values in the specific context of use. Qualitative data were analyzed thematically. <strong>Results:</strong> Overall, 232 effects, 33 values, and 156 action opportunities were collected. General and case-specific themes were identified. Important stakeholder values included quality of care, autonomy, efficiency, health, enjoyment, reliability, and privacy. Both positive and negative effects could underlie stakeholders’ values and influence the development of action opportunities. Action opportunities comprised the following: (1) technology: development of the technology (eg, user experience and customization), technology input (eg, recipes for meals, intervention options for reducing stress, and activities), and technology output (eg, storage and use of data); (2) context: guidelines, training and support, policy or agreements, and adjusting the physical environment in which the technology is used; and (3) users: integrating the technology into daily care practice, by diminishing (eg, “letting go” to increase the autonomy of people with intellectual disabilities), retaining (eg, face-to-face contact), and adding (eg, evaluation moments) certain behaviors of care professionals. <strong>Conclusions:</strong> This is the first study to provide insight into responsible digital care for people with intellectual disabilities by means of bottom-up exploration of action opportunities to take account of stakeholders’ values in designing technology, shaping the context of use, and adjusting the behavior of users. Although part of the findings may be generalized, case-specific insights and a complementary top-down approach (eg, predefined ethical frameworks) are essential. The findings represent a part of an ethical discourse that requires follow-up to meet the dynamism of stakeholders’ values and further develop and implement action opportunities to achieve socially desirable, ethically acceptable, and sustainable digital care that improves the lives of people with intellectual disabilities. 2024-02-28T10:15:04-05:00 https://mental.jmir.org/2024/1/e49317/ HealthySMS Text Messaging System Adjunct to Adolescent Group Cognitive Behavioral Therapy in the Context of COVID-19 (Let’s Text!): Pilot Feasibility and Acceptability Study2024-02-19T10:15:04-05:00Lauren M HaackCourtney C ArmstrongKate TravisAdrian AguileraSabrina M Darrow<strong>Background:</strong> The widespread occurrence and devastating impact of adolescent depression warrant health service research focused on feasible and acceptable digital health tools to supplement evidence-based intervention (EBI) efforts, particularly in the context of shelter-in-place guidelines disrupting youth socialization and service use in the wake of the COVID-19 pandemic. Given the promise of SMS text message interventions to enhance EBI engagement, our team developed the HealthySMS system as an adjunct to one of the most empirically supported interventions for adolescent depression: cognitive behavioral therapy (CBT) group services. The system sends daily SMS text messages requesting responses assessing mood, thoughts, and activities; weekly attendance reminder messages; daily tips about adherence (eg, a prompt for activity completion); and personalized responses based on participants’ texts. <strong>Objective:</strong> This study aims to evaluate the feasibility and acceptability of HealthySMS in a real-world setting and explore potential mechanisms of change in EBI engagement, before evaluating the system’s impact on adolescents’ group CBT engagement and, ultimately, depression outcomes. <strong>Methods:</strong> Over the course of 2020, we invited all 20 adolescents receiving CBT group services for depression at an outpatient psychiatry clinic to enroll in our HealthySMS study; ultimately, 17 (85%) adolescents agreed to participate. We tracked participant initiation and engagement with the HealthySMS system as well as the content of SMS text message responses to HealthySMS. We also invited each participant to engage in a semistructured interview to gather additional qualitative inputs on the system. <strong>Results:</strong> All (n=17, 100%) research participants invited agreed to receive HealthySMS messages, and 94% (16/17) of the participants maintained use during the first month without opting out. We uncovered meaningful qualitative themes regarding the feasibility and acceptability of HealthySMS, as well as its potential impact on EBI engagement. <strong>Conclusions:</strong> Taken together, the results of this pilot study suggest that HealthySMS adjunct to adolescent CBT group depression services is feasible and acceptable, as evidenced by high rates of HealthySMS initiation and low rates of dropout, as well as meaningful themes uncovered from participants’ qualitative feedback. In addition, the findings provide evidence regarding iterative improvements to the HealthySMS system and research protocol, as well as potential mechanisms of change for enhanced EBI engagement and, ultimately, adolescent depression outcomes, which can be used in future effectiveness research. 2024-02-19T10:15:04-05:00 https://mental.jmir.org/2024/1/e51704/ Incorporating a Stepped Care Approach Into Internet-Based Cognitive Behavioral Therapy for Depression: Randomized Controlled Trial2024-02-09T09:45:04-05:00Jasleen Kaur JagayatAnchan KumarYijia ShaoAmrita PannuCharmy PatelAmirhossein ShiraziMohsen OmraniNazanin Alavi<strong>Background:</strong> Depression is a hidden burden, yet it is a leading cause of disability worldwide. Despite the adverse effects of depression, fewer than one-third of patients receive care. Internet-based cognitive behavioral therapy (i-CBT) is an effective treatment for depression, and combining i-CBT with supervised care could make the therapy scalable and effective. A stepped care model is a framework for beginning treatment with an effective and low-intensity intervention while adapting care based on the patient’s needs. <strong>Objective:</strong> This study investigated the efficacy of a stepped care i-CBT model for depression based on changes in self-reported depressive symptoms. <strong>Methods:</strong> In this single-blinded, randomized controlled trial, participants were allocated to either the i-CBT–only group (28/56, 50%) or the i-CBT with stepped care group (28/56, 50%). Both groups received a 13-week i-CBT program tailored for depression. The i-CBT program was provided through a secure, online mental health clinic called the Online Psychotherapy Tool. Participants read through the sessions and completed the assignments related to each session. Participants in the stepped care group received additional interventions from their care provider based on standard questionnaire scores (ie, Patient Health Questionnaire–9 [PHQ-9], Quick Inventory of Depressive Symptomatology [QIDS], and Quality of Life Enjoyment and Satisfaction Questionnaire–Short Form) and their assignment responses. From lowest to highest intensity, the additional interventions included SMS text messages, phone calls, video calls, or a video call with a psychiatrist. <strong>Results:</strong> For this study, 56 participants were recruited to complete an i-CBT program (n=28, 50%; mean age 37.9; SD 13.08 y; 7/28, 27% were men) or an i-CBT with stepped care program (n=28, 50%; mean age 40.6; SD 14.28 y; 11/28, 42% were men). The results of this study indicate that the i-CBT program was effective in significantly reducing depressive symptoms, as measured by the PHQ-9 (<i>F</i><sub>4,80</sub>=9.95; <i>P</i><.001) and QIDS (<i>F</i><sub>2,28</sub>=5.73; <i>P</i>=.008); however, there were no significant differences in the reduction of depressive symptoms between the 2 groups (PHQ-9: <i>F</i><sub>4,80</sub>=0.43; <i>P</i>=.78; QIDS: <i>F</i><sub>2,28</sub>=3.05; <i>P</i>=.06). The stepped care group was not significantly better in reducing depressive symptoms than the i-CBT group (PHQ-9, <i>P</i>=.79; QIDS, <i>P</i>=.06). Although there were no significant differences observed between the number of participants who completed the program between the groups (<i>χ</i><sup>2</sup><sub>1</sub>=2.6; <i>P</i>=.10), participants in the stepped care group, on average, participated in more sessions than those who prematurely terminated participation in the i-CBT group (<i>t</i><sub>55</sub>=−2; <i>P</i>=.03; 95% CI –4.83 to –0.002). <strong>Conclusions:</strong> Implementing a stepped care approach in i-CBT is an effective treatment for depression, and the stepped care model can assist patients to complete more sessions in their treatment. <strong>Trial Registration:</strong> Clinicaltrials.gov NCT04747873; https://clinicaltrials.gov/study/NCT04747873 2024-02-09T09:45:04-05:00 https://mental.jmir.org/2024/1/e48916/ Effectiveness and User Experience of Virtual Reality for Social Anxiety Disorder: Systematic Review2024-02-08T10:15:04-05:00Simon ShahidJoshua KelsonAnthony Saliba<strong>Background:</strong> Social anxiety disorder (SAD) is a debilitating psychiatric disorder that affects occupational and social functioning. Virtual reality (VR) therapies can provide effective treatment for people with SAD. However, with rapid innovations in immersive VR technology, more contemporary research is required to examine the effectiveness and concomitant user experience outcomes (ie, safety, usability, acceptability, and attrition) of emerging VR interventions for SAD. <strong>Objective:</strong> The aim of this systematic review was to examine the effectiveness and user experience of contemporary VR interventions among people with SAD. <strong>Methods:</strong> The Cochrane Library, Emcare, PsycINFO, PubMed, ScienceDirect, Scopus, and Web of Science databases were searched between January 1, 2012, and April 26, 2022. Deduplicated search results were screened based on title and abstract information. Full-text examination was conducted on 71 articles. Studies of all designs and comparator groups were included if they appraised the effectiveness and user experience outcomes of any immersive VR intervention among people with SAD. A standardized coding sheet was used to extract data on key participant, intervention, comparator, outcome, and study design items. <strong>Results:</strong> The findings were tabulated and discussed using a narrative synthesis. A total of 18 studies met the inclusion criteria. <strong>Conclusions:</strong> The findings showed that VR exposure therapy–based interventions can generally provide effective, safe, usable, and acceptable treatments for adults with SAD. The average attrition rate from VR treatment was low (11.36%) despite some reported user experience difficulties, including potential simulator sickness, exposure-based emotional distress, and problems with managing treatment delivered in a synchronous group setting. This review also revealed several research gaps, including a lack of VR treatment studies on children and adolescents with SAD as well as a paucity of standardized assessments of VR user experience interactions. More studies are required to address these issues. <strong>Trial Registration:</strong> PROSPERO CRD42022353891; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=353891 2024-02-08T10:15:04-05:00 https://mental.jmir.org/2024/1/e54369/ Capacity of Generative AI to Interpret Human Emotions From Visual and Textual Data: Pilot Evaluation Study2024-02-06T10:00:04-05:00Zohar ElyosephElad RefouaKfir AsrafMaya LvovskyYoav ShimoniDorit Hadar-Shoval<strong>Background:</strong> Mentalization, which is integral to human cognitive processes, pertains to the interpretation of one’s own and others’ mental states, including emotions, beliefs, and intentions. With the advent of artificial intelligence (AI) and the prominence of large language models in mental health applications, questions persist about their aptitude in emotional comprehension. The prior iteration of the large language model from OpenAI, ChatGPT-3.5, demonstrated an advanced capacity to interpret emotions from textual data, surpassing human benchmarks. Given the introduction of ChatGPT-4, with its enhanced visual processing capabilities, and considering Google Bard’s existing visual functionalities, a rigorous assessment of their proficiency in visual mentalizing is warranted. <strong>Objective:</strong> The aim of the research was to critically evaluate the capabilities of ChatGPT-4 and Google Bard with regard to their competence in discerning visual mentalizing indicators as contrasted with their textual-based mentalizing abilities. <strong>Methods:</strong> The Reading the Mind in the Eyes Test developed by Baron-Cohen and colleagues was used to assess the models’ proficiency in interpreting visual emotional indicators. Simultaneously, the Levels of Emotional Awareness Scale was used to evaluate the large language models’ aptitude in textual mentalizing. Collating data from both tests provided a holistic view of the mentalizing capabilities of ChatGPT-4 and Bard. <strong>Results:</strong> ChatGPT-4, displaying a pronounced ability in emotion recognition, secured scores of 26 and 27 in 2 distinct evaluations, significantly deviating from a random response paradigm (<i>P</i><.001). These scores align with established benchmarks from the broader human demographic. Notably, ChatGPT-4 exhibited consistent responses, with no discernible biases pertaining to the sex of the model or the nature of the emotion. In contrast, Google Bard’s performance aligned with random response patterns, securing scores of 10 and 12 and rendering further detailed analysis redundant. In the domain of textual analysis, both ChatGPT and Bard surpassed established benchmarks from the general population, with their performances being remarkably congruent. <strong>Conclusions:</strong> ChatGPT-4 proved its efficacy in the domain of visual mentalizing, aligning closely with human performance standards. Although both models displayed commendable acumen in textual emotion interpretation, Bard’s capabilities in visual emotion interpretation necessitate further scrutiny and potential refinement. This study stresses the criticality of ethical AI development for emotional recognition, highlighting the need for inclusive data, collaboration with patients and mental health experts, and stringent governmental oversight to ensure transparency and protect patient privacy. 2024-02-06T10:00:04-05:00 https://mental.jmir.org/2024/1/e51126/ Reasons for Acceptance or Rejection of Online Record Access Among Patients Affected by a Severe Mental Illness: Mixed Methods Study2024-02-05T10:00:29-05:00Julian SchwarzEva Meier-DiedrichKatharina NeumannMartin HeinzeYvonne EisenmannSamuel Thoma<strong>Background:</strong> Over the past few years, online record access (ORA) has been established through secure patient portals in various countries, allowing patients to access their health data, including clinical notes (“open notes”). Previous research indicates that ORA in mental health, particularly among patients with severe mental illness (SMI), has been rarely offered. Little is known about the expectations and motivations of patients with SMI when reading what their clinicians share via ORA. <strong>Objective:</strong> The aim of this study is to explore the reasons why patients with SMI consider or reject ORA and whether sociodemographic characteristics may influence patient decisions. <strong>Methods:</strong> ORA was offered to randomly selected patients at 3 university outpatient clinics in Brandenburg, Germany, which exclusively treat patients with SMI. Within the framework of a mixed methods evaluation, qualitative interviews were conducted with patients who chose to participate in ORA and those who declined, aiming to explore the underlying reasons for their decisions. The interviews were transcribed and analyzed using thematic analysis. Sociodemographic characteristics of patients were examined using descriptive statistics to identify predictors of acceptance or rejection of ORA. <strong>Results:</strong> Out of 103 included patients, 58% (n=60) wished to read their clinical notes. The reasons varied, ranging from a desire to engage more actively in their treatment to critically monitoring it and using the accessible data for third-party purposes. Conversely, 42% (n=43) chose not to use ORA, voicing concerns about possibly harming the trustful relationship with their clinicians as well as potential personal distress or uncertainty arising from reading the notes. Practical barriers such as a lack of digital literacy or suspected difficult-to-understand medical language were also named as contributing factors. Correlation analysis revealed that the majority of patients with depressive disorder desired to read the clinical notes (<i>P</i><.001), while individuals with psychotic disorders showed a higher tendency to decline ORA (<i>P</i><.05). No significant group differences were observed for other patient groups or characteristics. <strong>Conclusions:</strong> The adoption of ORA is influenced by a wide range of motivational factors, while patients also present a similar variety of reasons for declining its use. The results emphasize the urgent need for knowledge and patient education regarding factors that may hinder the decision to use ORA, including its practical usage, its application possibilities, and concerns related to data privacy. Further research is needed to explore approaches for adequately preparing individuals with SMI to transition from their inherent interest to active engagement with ORA. <strong>Trial Registration:</strong> German Clinical Trial Register DRKS00030188; https://drks.de/search/en/trial/DRKS00030188 2024-02-05T10:00:29-05:00 https://mental.jmir.org/2024/1/e46637/ Effectiveness of Online and Remote Interventions for Mental Health in Children, Adolescents, and Young Adults After the Onset of the COVID-19 Pandemic: Systematic Review and Meta-Analysis2024-02-05T10:00:04-05:00Linda Fischer-GroteVera FössingMartin AignerElisabeth FehrmannMarkus Boeckle<strong>Background:</strong> The prevalence of mental illness increased in children, adolescents, and young adults during the COVID-19 pandemic, while at the same time, access to treatment facilities has been restricted, resulting in a need for the quick implementation of remote or online interventions. <strong>Objective:</strong> This study aimed to give an overview of randomized controlled studies examining remote or online interventions for mental health in children, adolescents, and young adults and to explore the overall effectiveness of these interventions regarding different symptoms. <strong>Methods:</strong> A systematic literature search was conducted according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines using PubMed, PsycInfo, Psyndex, Embase, and Google Scholar. A meta-analysis was conducted using a random effects model to calculate overall effect sizes for interventions using standardized mean differences (SMDs) for postintervention scores. <strong>Results:</strong> We identified 17 articles with 8732 participants in the final sample, and 13 were included in the quantitative analysis. The studies examined different digital interventions for several outcomes, showing better outcomes than the control in some studies. Meta-analyses revealed significant medium overall effects for anxiety (SMD=0.44, 95% CI 0.20 to 0.67) and social functioning (SMD=0.42, 95% CI –0.68 to –0.17) and a large significant effect for depression (SMD=1.31, 95% CI 0.34 to 2.95). In contrast, no significant overall treatment effects for well-being, psychological distress, disordered eating, and COVID-19–related symptoms were found. <strong>Conclusions:</strong> The qualitative and quantitative analyses of the included studies show promising results regarding the effectiveness of online interventions, especially for symptoms of anxiety and depression and for training of social functioning. However, the effectiveness needs to be further investigated for other groups of symptoms in the future. All in all, more research with high-quality studies is required. 2024-02-05T10:00:04-05:00