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While the global health crisis was not responsible for the creation of virtual environments, the COVID-19 pandemic has spawned increased interest in the use of virtual technologies in the workplace and beyond. The current review highlights some of the methods, modalities, and outcomes of the pivot from in-person (offline) therapeutic interactions to the mode of telehealth (online) strategies. Global social-distancing mandates were especially troubling for mental health clients accustomed to in-person counseling and psychotherapy. Panic, fear, and isolation only compounded the reality of health and financial concerns. Lessons about the advantages of telehealth therapies during the most recent global health crisis, will help prepare us all for the next Disease X event. The primary aim of this brief report is to inform the reader about recent research on the advantages of telehealth modalities. In particular, an examination of online technologies in the midst of a Disease X milieu (i.e., COVID-19) was explored. While the current review is far from exhaustive, research in general should leave us optimistic about the "new normal" of utilizing online communication strategies in mental health and beyond. While a Disease X event did not directly lead to the creation of virtual meetings, emerging research is beginning to enlighten the positive consequences of making the pivot from offline to online therapeutic interventions.
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Objectives: This study examines the effects of an online support program for nurses with Covid-19 patients on their professional quality of life and psychological empowerment.Methods: This parallel randomized controlled experimental study with a pre-and post-test was prepared using the CONSORT 2010 checklist. This study was conducted online from July to December 2020 in Turkiye. The study was con-ducted with 48 nurses intervention group (n=24);control group (n=24) who were directly involved in the care of pa-tients with Covid-19. The study data were collected using a personal information form, the Professional Quality of Life Scale and the Psychological Empowerment Scale (PES). An eight-session online support program was administered to the intervention group once a week. The scales were re-administered to the intervention and control groups after the program.Results:The intervention group's post-test PES (t=-2.757;p=0.008;d=0.79) and compassion satisfaction scores (t=-3.887;p=0.000;d=1.12) increased significantly;their burnout (t=2.917;p=0.005;d=0.84) and compassion fatigue (t=3.134;p=0.003;d=0.90) post-test scores decreased significantly (p<0.05). The intervention group's post-test PES (t=-4.926;p=0.000;d=1.01) and compassion satisfaction scores (t=-3.524;p=0.002;d=0.71) were significantly higher than their pre-test scores, and their compassion fatigue post-test score (t=3.646;p=0.001;d=0.72) was significantly lower (p<0.05).Conclusion: This study's online support program for nurses with Covid-19 patients increased their psychological em-powerment and compassion satisfaction, and reduced their levels of burnout and compassion fatigue.
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Balint group helps health professionals to get emotional support and different perspectives of feedback, inspire reflection, and alleviate job burnout. During the outbreak of COVID-19, it was difficult for medical staff to carry out the traditional form of in person Balint group. Referring to the work of international pilot online Balint group, leaders of Balint group all over China have accumulated some experience and encountered new problems by using the internet to carry out discussion. In order to assist and standardize the work of online Balint group and enrich the ways of expanding Balint work, the Working Committee on Doctor-patient Relationship, Chinese Psychiatrist Association, Chinese Medical Doctor Association organized experts to have two rounds of discussion, and developed the consensus on: Principles and forms of online Balint group, the way of using web platforms for demonstration and learning, matters needing attention, the future development, and so on.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.
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Social media are the influential Internet community for general netizens to disseminate information, views, and opinions extensively. Recently, the research on Sentiment analysis has intensified due to the vast amount of data obtained from these numerous social networking platforms. During this COVID-19 pandemic, one of the great social networking sites viz. Twitter has experienced a significant increase in online posts and reviews concerning COVID-19 related tweets. In the view of Twitter, the spread of news concerning coronavirus variants has impacted many aspects of the public by providing messages around different issues and opinions to its potential users. In this study, we have used Twitter as a source of data for searching the index keywords and hashtag versions for the terms like "Pandemic”, "Coronavirus”, "COVID-19”, "SARS-CoV-2”, and "Omicron”, and we have examined the psychological and emotional impact it had on the public. This paper provides analytical information about people's perceptions of coronavirus (tweets were collected from March 2020 to December 2021). With those tweets, sentiment analysis was performed using the TextBlob text processing python module to acquire the people's subjective data (opinions and feelings) polarity concerning the effects of coronavirus. Furthermore, for effective text classification, we have applied classification methodologies like Support Vector Machine (SVM), K Nearest Neighbor (KNN), Logistic Regression (LR), and Decision Tree (DT). The SVM concerning feature extraction produced the results with 99.49% accuracy. This study assists the government organizations in attaining COVID-19 insights by implying public mental health sentiments in social networks. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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In recent years, the majority of the world's population has been impacted by the COVID-19 pandemic, but owing to the invention of vaccinations, the epidemic has been brought under control. Most people are hesitant to share their experiences on official platforms after being vaccinated. As a result, information about vaccine-related adverse effects other than clinical trial results is challenging to identify. However, most people have shared their opinions about vaccines on social media since the COVID-19 immunization program began worldwide. This study aims to assess, using social media, the adverse effects of the COVID-19 vaccination as perceived by the general population. The authors of the previous studies did not categorize tweets on the COVID-19 vaccine adverse effects as personal experience, informative, or advice-seeking. The authors of this study aim to classify tweets in the manner described above to fill a research gap and increase public awareness of the COVID-19 vaccine's side effects. The Kaggle repository collected tweets pertaining to COVID-19 vaccinations for this investigation. The authors manually classified collected tweets into two categories: those connected to COVID-19 vaccinations' adverse effects and those unrelated to COVID-19 vaccines' adverse effects. Then, valid tweets were further classified into three categories: personal experience, informative, and seeking advice. The authors then used the data to train four ML models. There are also SVM, Logistic Regression, LSTM, and ANN. The LSTM algorithm generated the most outstanding results, with an accuracy of 97.64&. In addition, the researchers conclude that the SVM may not be suitable for planned research since it gave the lowest degree of accuracy, 80%. © 2022 IEEE.
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The outbreak of the pandemic, caused by Coronavirus Disease 2019 (COVID-19), has affected the daily activities of people across the globe. During COVID-19 outbreak and the successive lockdowns, Twitter was heavily used and the number of tweets regarding COVID-19 increased tremendously. Several studies used Sentiment Analysis (SA) to analyze the emotions expressed through tweets upon COVID-19. Therefore, in current study, a new Artificial Bee Colony (ABC) with Machine Learning-driven SA (ABCML-SA) model is developed for conducting Sentiment Analysis of COVID-19 Twitter data. The prime focus of the presented ABCML-SA model is to recognize the sentiments expressed in tweets made upon COVID-19. It involves data pre-processing at the initial stage followed by n-gram based feature extraction to derive the feature vectors. For identification and classification of the sentiments, the Support Vector Machine (SVM) model is exploited. At last, the ABC algorithm is applied to fine tune the parameters involved in SVM. To demonstrate the improved performance of the proposed ABCML-SA model, a sequence of simulations was conducted. The comparative assessment results confirmed the effectual performance of the proposed ABCML-SA model over other approaches. © 2023 Tech Science Press. All rights reserved.
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COVID-19 has become a mental health pandemic. The impact on vulnerable demographic groups has been particularly severe. This paper focuses on women in employment in Hong Kong who have had to balance remote work and online schooling for over 2 years. Using semi-ethnography and theme-oriented discourse analysis, we examine 200 threads that concern members' mental health on a popular Facebook support group for mothers. We demonstrate that mental health messages are typically framed as 'troubles talk'. Other support group members actively align with a trouble-teller through 'caring responses', namely expressions of empathy and sympathy. These are realized through assessments of the trouble-teller's experience, reports of similar experiences;expressions of compassion and advice-giving. Mental health talk online is heavily mitigated, nevertheless the medium provides a space for expressing mental health troubles and providing informal psychosocial support. We advocate the importance of microanalytic discourse studies for mental health research to get insights into people's lived experiences during the pandemic. [ABSTRACT FROM AUTHOR] Copyright of Discourse & Society is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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Public opinions shared in common platforms like Twitter, Facebook, Instagram, etc. act as the sources of information for experts. Transportation and analysis of such data is very important and difficult due to data regulations and its structure. The pre-processing approaches and word-based dictionaries are used to understand the unprocessed data and make possible the opinions/tweets to be analyzed. Machine learning algorithms learn from past experience and use a variety of statistical, probabilistic and optimization algorithms to detect useful patterns from unstructured data sets. Our study aims to compare the performance of classification algorithms to predict individuals with COVID-19(+ ) or COVID-19(−) using the emotions among the tweets by text mining procedures. Logistic Regression (LR), Support Vector Machine (SVM), Naive Bayes (NB), Decision Trees (DT), Random Forest (RF), Artificial Neural Networks (ANN), Gradient Boost (GBM) and XGradient algorithms were used to extract the accuracy of model performance of each model for the detection and identification of the disease related to the COVID-19 virus, which has been on the agenda recently. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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During the COVID-19 pandemic, many traditional psychiatric rehabilitation staff training and support strategies were disrupted or discontinued. This article describes the strategies used by one state system to rapidly migrate many state psychiatric rehabilitation training and support activities to a website. Site analytics showed high use of the website in the first year, with 6,673 unique visitors and 4,529 visits to the site's staff support materials. Additionally, more than 4,879 online trainings were accessed on the website. Given the low cost;ease of development, implementation, and maintenance;and the high access rate of this website, migration of some staff training and support activities online may be appropriate and feasible for other state psychiatric hospital systems both during and after the pandemic. Copyright © 2020, University of Nebraska Press. All rights reserved.
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User training and support are crucial factors in bridging the digital divide. The Illuminated Devices sociotechnical system, inspired by our experiences providing online support during COVID-19, will provide personal digital tutoring, accessible anywhere, even with limited prior technology experience. System development leverages a human-centered, design-based research approach. The project will culminate in a pilot rollout and evaluation at three community sites. © ISLS.
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The COVID-19 pandemic has negatively influenced the psychological well-being of people around the world; university students have experienced feelings of fear of the COVID-19 pandemic, due to the intolerance of uncertainty, and a worsened quality of life, related to the reduction of social contacts. Scholars all around the world widely suggest the need to take care of this issue, proposing solutions to support students' adjustment in the post-pandemic period. The literature on positive psychology and the life design approach has identified multiple psychological resources, the character strengths, that can sustain people's life satisfaction and well-being in changing contexts, including their university experience. We proposed an online group career counseling intervention for 30 Italian university students (experimental group) to promote university students' psychological resources and mitigate the long-term negative implications of the COVID-19 pandemic on life satisfaction. The other 30 students formed the control group. We found that the students engaged in the online group career counseling intervention evidenced, at the post-test, higher levels than the pre-test of (a) resilience, (b) subjective risk intelligence, (c) career adaptability, (d) self-efficacy, (e) optimism, (f) hope, (g) life satisfaction, and lower levels than the pre-test of (h) fears of COVID-19 pandemic. No differences at Time 1 and Time 2 were found in the control group. Implications for future research and practice will be discussed.
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Care homes care for people with complex needs, supporting them to the end of life and are now being seen as the 'de facto' hospice. Reflective debriefing for care home staff has been found to help support staff and provide an educative and communicative function when a resident dies. Pre-COVID-19, one of the authors had been conducting reflective debriefings face-to-face with care home staff but when COVID-19 struck, face-to-face sessions were impossible. An online format was developed with the aim of providing emotional support and practice-based learning in relation to death and dying through reflection. This study assessed the acceptability and feasibility of delivering online supportive conversations and reflective sessions (OSCaRS) on palliative and end of life care to care home staff during the pandemic. A mixed methods study design was undertaken in April to September 2020. Qualitative data comprised of digital recordings of sessions and semi-structured interviews with OSCaRS participants, managers and session facilitators. An online survey was sent to all staff and had a response rate of 12%. Eleven OSCaRS were conducted over ten weeks. Thirty-four staff members attended one or more sessions. Three overarching themes were identified from the data: pressures of working in a pandemic, practicalities of delivering online support and, practice development opportunities. Engaging care home staff in online structured supportive conversations and reflections in relation to death and dying is acceptable, feasible and valuable for providing support with the pressures of working in a pandemic. There is value for OSCaRS to continue as online sessions as they provide care home staff access to practice-based learning and support from professionals and allows specialists based in a range of settings to in-reach into care homes in an efficient way. Future implementation must consider the availability of sufficient devices with cameras to aid participation, timing and frequency of sessions to accommodate staff workflows, the engagement and support of managers and post-session support. © 2022 Lucy Johnston, Jo Hockley, Julie Watson & Susan D. Shenkin. This Open Access article is distributed under the terms of the Creative Commons Attribution Attribution-Non-Commercial No Derivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited and is unaltered.
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COVID-19 has become a mental health pandemic. The impact on vulnerable demographic groups has been particularly severe. This paper focuses on women in employment in Hong Kong who have had to balance remote work and online schooling for over 2 years. Using semi-ethnography and theme-oriented discourse analysis, we examine 200 threads that concern members’ mental health on a popular Facebook support group for mothers. We demonstrate that mental health messages are typically framed as ‘troubles talk’. Other support group members actively align with a trouble-teller through ‘caring responses’, namely expressions of empathy and sympathy. These are realized through assessments of the trouble-teller’s experience, reports of similar experiences;expressions of compassion and advice-giving. Mental health talk online is heavily mitigated, nevertheless the medium provides a space for expressing mental health troubles and providing informal psychosocial support. We advocate the importance of microanalytic discourse studies for mental health research to get insights into people’s lived experiences during the pandemic. [ FROM AUTHOR] Copyright of Discourse & Society is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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BACKGROUND: Compared to other types of dementia, family caregivers of people with Lewy body dementia (LBD) report higher stress levels and more severe depressive symptoms. Although several digital support interventions for caregivers of persons with dementia exist, few target LBD specifically or leverage a fully remote and asynchronous approach suitable for pandemic circumstances. OBJECTIVE: We performed a pilot evaluation of a digital intervention designed to help caregivers of people with LBD address challenges they have experienced, with the end goal of reducing psychological distress in this population. METHODS: We recruited 15 family caregivers of people with LBD to participate in the quasi-experimental, single-arm, mixed methods study titled Virtual Online Communities for Aging Life Experience-Lewy Body Dementia (VOCALE-LBD). The study offers an 8-week web-based intervention that uses a digital discussion platform and involves moderation, peer-to-peer support, didactic training, and problem-solving skill enactment. RESULTS: Participants' baseline characteristics were the following: mean age 66 (SD 8) years; 14 of 15 (93%) of them were female; all (15/15, 100%) were White; and 8 (53%) of them had at least a postgraduate degree. Throughout the intervention, participants engaged in weekly web-based discussions, generating a total of 434 posts (average 4 posts per week). Attrition was 20% (3/15). Upon study exit, participants showed the following average improvements: 3.0 (SD 6.0) in depression, 8.3 (SD 16.7) in burden, 2.9 (SD 6.8) in stress, and 0.3 (SD 0.8) in loneliness. When looking at the proportion of participants with clinically signiï¬cant improvement versus those with a worsening of ≥0.5 SD for each outcome, we observed net improvements of 50% (6/12), 33% (4/12), 25% (3/12), and 25% (3/12) in depression, loneliness, burden, and stress, respectively. In terms of the benefits of participation, participants reported that participation helped them "a great deal" to (1) improve their understanding of LBD (9/12, 75%), (2) gain confidence in dealing with difficult behaviors of the care recipient (6/12, 50%), and (3) improve in one's abilities to provide care to the care recipient (4/12, 33%). CONCLUSIONS: The study generated promising feasibility and preliminary efficacy data for a low-cost, web-based intervention designed for caregivers of persons with LBD. Though the study was not powered for significance, we observed nominal average and net improvements in important psychological outcomes. Moreover, many caregivers reported that study participation helped them better understand the disease, feel more conï¬dent in dealing with difficult behaviors of the care recipient, and improve their ability to care for the care recipient. If validated in future studies, the intervention could be an accessible, on-demand resource for caregivers, enabling them to engage in moderated remote discussions with peers at their own convenience in terms of location, time of the day, and frequency.
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BACKGROUND: The negative psychosocial impacts of cancer diagnoses and treatments are well documented. Virtual care has become an essential mode of care delivery during the COVID-19 pandemic, and online support groups (OSGs) have been shown to improve accessibility to psychosocial and supportive care. de Souza Institute offers CancerChatCanada, a therapist-led OSG service where sessions are monitored by an artificial intelligence-based co-facilitator (AICF). The AICF is equipped with a recommender system that uses natural language processing to tailor online resources to patients according to their psychosocial needs. OBJECTIVE: We aimed to outline the development protocol and evaluate the AICF on its precision and recall in recommending resources to cancer OSG members. METHODS: Human input informed the design and evaluation of the AICF on its ability to (1) appropriately identify keywords indicating a psychosocial concern and (2) recommend the most appropriate online resource to the OSG member expressing each concern. Three rounds of human evaluation and algorithm improvement were performed iteratively. RESULTS: We evaluated 7190 outputs and achieved a precision of 0.797, a recall of 0.981, and an F1 score of 0.880 by the third round of evaluation. Resources were recommended to 48 patients, and 25 (52%) accessed at least one resource. Of those who accessed the resources, 19 (75%) found them useful. CONCLUSIONS: The preliminary findings suggest that the AICF can help provide tailored support for cancer OSG members with high precision, recall, and satisfaction. The AICF has undergone rigorous human evaluation, and the results provide much-needed evidence, while outlining potential strengths and weaknesses for future applications in supportive care.
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Background: Patients with locally advanced squamous cell carcinoma of the head and neck (SCCHN) undergo multimodality treatments that result in significant morbidity. For patients undergoing definitive chemoradiation, functional deficits and significant decrease in quality of life contribute to tremendous social isolation. Peer-to-peer (P2P) support programs have a number of beneficial effects including improved satisfaction with medical care, improved mood, and decreased social isolation. Online support groups represent a new and vastly underused and understudied medium. While there have been a few studies evaluating online support groups, to our knowledge none of these have focused specifically on patients with SCCHN. The goal of the current study is to conduct a randomized controlled trial (RCT) of a digitized peer-to-peer communication system for patients with newly diagnosed locally advanced SCCHN. Methods: This is a pilot feasibility study of a digitized smart-phone enabled P2P application. Eligible patients are at least 18 years old, able to speak/read English, and slated to start definitive chemoradiation for their locally advanced SCCHN at Moffitt Cancer Center. The mobile application serves as a digitized patient support group/P2P communication system. Patients are randomly assigned in a 2:1 ratio to receive the mobile application or standard of care supportive services. A convenience sample of thirty patients are chosen for this pilot study. Results: To date, eighteen patients have been enrolled to the study. Eleven patients were randomized to the intervention arm, and seven patients were randomized to the standard of care arm. Baseline surveys were administered to enrolled patients. Of the patients who filled out baseline surveys, the majority of patients (62%) desired to be matched with someone undergoing similar therapy, 25% preferred someone with comparable age, and 13% preferred someone of their own gender. One patient was unable to fill out baseline surveys due to worsening of their medical condition. Due to the COVID-19 pandemic, the trial was closed for the eight months but is now open to accrual. Conclusions: This trial is currently open and accruing patients. Feasibility will be analyzed after completion of study recruitment.
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This study was conducted to determine the mixed-method usability evaluation of the Iranian national covid-19 electronic screening system. The cross-sectional study was carried out in partnership with 116 users of the Iranian national covid-19 electronic screening system and five experts. As a result of the experts' assessment, the Iranian national covid-19 electronic screening system scored 0-2 out of the 10 principles of Nielsen Jacob, which indicates a good approach to the design of this system. To evaluate, the questionnaire for user interaction satisfaction (QUIS) version 7 was used. Data were analyzed by spss version 19. A total of 112 out of 116 questionnaires were obtained. In the Iranian national covid-19 electronic screening system, nine (33.3%) of the 27 sections scored higher than seven. More than half scored over five. There were no factors in the terminology and system information and learning section between 7 and 9;the highest rankings in the section overall responses to the software were 1) terrible-wonderful 2) difficult-easy;in the section overall reactions to the software, all of the factors were highest;also, the highest rankings were in the section 'system capability' for 1) system speed 2) system reliability 3) designed for all levels of users. © 2022 IEEE.
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Background and aim: A group-based fatigue management programme called FACETS has typically been delivered face-to-face to people living with MS within a neuropsychology service. In response to Covid-19 government guidelines, this service adapted to online delivery of their fatigue management group intervention. This study aims to evaluate two FACETS group interventions which were delivered online consecutively within this service. Methods: Group 1 was delivered face-to-face for the first three sessions before being adapted for virtual delivery for the final three sessions. Group 2 was delivered virtually for all six sessions. Quantitative data was collected from outcome measures collected pre-and post-group. Qualitative feedback was gathered to explore participants’ experience of the group as well as the adapted virtual delivery. A thematic analysis was undertaken to identify key themes. Results: Participants in both groups felt they had more control over managing their fatigue and it was having less of an impact on their quality of life. Five themes were identified from participants’ qualitative feedback (knowledgeable content, awareness and learning, validating experience, accessible amendments, patient choice). Discussion: Feedback was largely positive from both groups following the adaptation to online delivery as it offered a cost-and time-effective solution. Participants reflected on the value of a mixed delivery option for future group interventions to facilitate rapport with other participants and empower self-management of their fatigue. © 2022, British Psychological Society. All rights reserved.