A Narrative Review of Vocational Rehabilitation in People with Spinal Cord Injury in Different Countries.

Background: Spinal cord injury (SCI) is a life-long neurological disease. This study reviews the literature on the vocational rehabilitation (VR) of people who experience SCI. Methods: MEDLINE (via PubMed), Web of Science, EMBASE, Google Scholar, ProQuest, and Science Direct databases were searched. The inclusion criteria of the articles included the following: describing adults with SCI only, the English or Persian language, and involving people of workforce age. Conference abstracts, case studies, and editorials were excluded. Results: The eligibility of 186 full-text articles was assessed, and 124 studies met the inclusion criteria. Most studies focused on barriers and facilitators for work in people with SCI. Conclusion: There are no current services and programs in Iran that support post-injury employment of people with SCI, and therefore, there remains a need for studies addressing employment in this population.

Diagnostic accuracy of large language models in psychiatry.

INTRODUCTION: Medical decision-making is crucial for effective treatment, especially in psychiatry where diagnosis often relies on subjective patient reports and a lack of high-specificity symptoms. Artificial intelligence (AI), particularly Large Language Models (LLMs) like GPT, has emerged as a promising tool to enhance diagnostic accuracy in psychiatry. This comparative study explores the diagnostic capabilities of several AI models, including Aya, GPT-3.5, GPT-4, GPT-3.5 clinical assistant (CA), Nemotron, and Nemotron CA, using clinical cases from the DSM-5. METHODS: We curated 20 clinical cases from the DSM-5 Clinical Cases book, covering a wide range of psychiatric diagnoses. Four advanced AI models (GPT-3.5 Turbo, GPT-4, Aya, Nemotron) were tested using prompts to elicit detailed diagnoses and reasoning. The models' performances were evaluated based on accuracy and quality of reasoning, with additional analysis using the Retrieval Augmented Generation (RAG) methodology for models accessing the DSM-5 text. RESULTS: The AI models showed varied diagnostic accuracy, with GPT-3.5 and GPT-4 performing notably better than Aya and Nemotron in terms of both accuracy and reasoning quality. While models struggled with specific disorders such as cyclothymic and disruptive mood dysregulation disorders, others excelled, particularly in diagnosing psychotic and bipolar disorders. Statistical analysis highlighted significant differences in accuracy and reasoning, emphasizing the superiority of the GPT models. DISCUSSION: The application of AI in psychiatry offers potential improvements in diagnostic accuracy. The superior performance of the GPT models can be attributed to their advanced natural language processing capabilities and extensive training on diverse text data, enabling more effective interpretation of psychiatric language. However, models like Aya and Nemotron showed limitations in reasoning, indicating a need for further refinement in their training and application. CONCLUSION: AI holds significant promise for enhancing psychiatric diagnostics, with certain models demonstrating high potential in interpreting complex clinical descriptions accurately. Future research should focus on expanding the dataset and integrating multimodal data to further enhance the diagnostic capabilities of AI in psychiatry.

Testing behaviour change with an artificial intelligence chatbot in a randomized controlled study.

Chatbots can effect large-scale behaviour change because they are accessible through social media, flexible, scalable, and gather data automatically. Yet research on the feasibility and effectiveness of chatbot-administered behaviour change interventions is sparse. The effectiveness of established behaviour change interventions when implemented in chatbots is not guaranteed, given the unique human-machine interaction dynamics. We pilot-tested chatbot-based behaviour change through information provision and embedded animations. We evaluated whether the chatbot could increase understanding and intentions to adopt protective behaviours during the pandemic. Fifty-nine culturally and linguistically diverse participants received a compassion intervention, an exponential growth intervention, or no intervention. We measured participants' COVID-19 testing intentions and measured their staying-home attitudes before and after their chatbot interaction. We found reduced uncertainty about protective behaviours. The exponential growth intervention increased participants' testing intentions. This study provides preliminary evidence that chatbots can spark behaviour change, with applications in diverse and underrepresented groups.

Unpacking Sociotechnical Discourses on Telehealth Use and Data Protection: A Path Towards Digital Health Value Creation.

BACKGROUND: Telehealth uptake will remain sub-optimal without consumer trust. Safeguarding the security and privacy of health information plays an important role in building trust and acceptance of telehealth. OBJECTIVES: This study seeks to unpack the sociotechnical discourses on the use of telehealth with a focus on privacy and security in the context of United States health services. METHODS: A search of the media outlets facilitated via the Factiva database was conducted. Using a qualitative method, thematic analysis was performed on the news texts to identify the key themes and provide contextual explanations. RESULTS: The analysis led to the identification of three key themes: 'data protection practice', 'clinical resilience', and 'digital health business value' perspectives. These themes focus on various concepts of telehealth use including data privacy, security, public health emergency, compliance activities in the use of telehealth, meeting stakeholders' needs, reducing costs of service delivery, the potential of telehealth for informed action, and improving users' experience. Among these themes, 'data protection practice' was directly associated with privacy compliance and telehealth use. Other thematic discourses have provided an indirect reflection on the role of privacy compliance, with a greater emphasis placed on health service delivery and market dynamics rather than compliance in practice. CONCLUSION: Our study revealed the importance of the COVID-19 pandemic in telehealth use, highlighting the move towards 'good faith' and responsible use of telehealth.

Digital Health for Myocardial Infarction: Research Topics and Trends.

We aimed to map the topics and trends of research on digital health for myocardial infarction over the past ten years. This can inform future research directions and newly emerging topics for myocardial infarction care, diagnosis and monitoring. The Web of Science database was searched for papers related to digital health for myocardial infarction. 1,344 retrieved records were used for visualisation through bibliometrics and co-occurrence network analysis of keywords. Our mapping revealed several emerging topics in recent years, including artificial intelligence and deep learning. Higher emphasis on automated and artificially intelligent digital health systems in recent years can inform future clinical practice and research directions for myocardial infarction.

The effect of using a sports application on the quality of sleep in patients with heart failure: a randomized clinical trial study.

BACKGROUND: Patients with heart failure often suffer from sleep disorders. Due to the side effects of medications used to treat this disorder, non-pharmacological methods may be used to improve these patients' sleep quality. This study aimed to determine the effect of a sports application on sleep quality in patients with heart failure. METHODS: In this single-blinded randomized clinical trial, 60 patients aged 30-70 referred to Shafa Hospital in Kerman were randomly assigned to control (n = 30) and intervention (n = 30) groups based on convenience sampling. The intervention group used the sports application for eight consecutive weeks. Data was collected using a demographic questionnaire and the Pittsburgh Sleep Quality Index (PSQI). An independent t-test and a Mann-Whitney U test were used for comparisons between groups and paired t-tests and Wilcoxon tests were used for comparisons within groups. RESULTS: The data analysis revealed a significant difference in sleep quality scores between the two groups after the intervention, meaning that the intervention group had better sleep quality than the control group (P < 0.05). CONCLUSIONS: As a result of the study, it was found that the sport application improved the quality of sleep in patients with heart failure. Our recommendation is for healthcare providers to use this sports application to present educational content related to physical activity and improve the sleep quality of patients. TRIAL REGISTRATION: Iranian Registry of Clinical Trials: IRCT. 2019123045475N1." Registered 16 December 2019.

Patients' perspectives and preferences toward telemedicine versus in-person visits: a mixed-methods study on 1226 patients.

INTRODUCTION: Despite the fact that telemedicine can eliminate geographical and time limitations and offer the possibility of diagnosing, treating, and preventing diseases by sharing reliable information, many individuals still prefer to visit medical centers for in-person consultations. The aim of this study was to determine the level of acceptance of telemedicine compared to in-person visits, identify the perceived advantages of telemedicine over in-person visits, and to explore the reasons why patients choose either of these two types of visits. METHODS: We developed a questionnaire using the rational method. The questionnaire consisted of multiple-choice questions and one open-ended question. A total of 2059 patients were invited to participate in the study. Chi-square tests and descriptive statistics were employed for data analysis. To analyze the data from the open-ended question, we conducted qualitative content analysis using MAXQDA 18. RESULTS: Out of the 1226 participants who completed the questionnaire, 865 (71%) preferred in-person visits, while 361 (29%) preferred telemedicine. Factors such as education level, specific health conditions, and prior experience with telemedicine influenced the preference for telemedicine. The participants provided a total of 183 different reasons for choosing either telemedicine (108 reasons) or in-person visits (75 reasons). Avoiding infectious diseases, saving cost, and eliminating and overcoming geographical distance barriers were three primary telemedicine benefits. The primary reasons for selecting an in-person visit were: more accurate diagnosis of the disease, more accurate and better examination of the patient by the physician, and more accurate and better treatment of the disease. CONCLUSION: The results demonstrate that despite the numerous benefits offered by telemedicine, the majority of patients still exhibit a preference for in-person visits. In order to promote broader acceptance of telemedicine, it becomes crucial for telemedicine services to address patient preferences and concerns effectively. Employing effective change management strategies can aid in overcoming resistance and facilitating the widespread adoption of telemedicine within the population.

Digital Health Secondary Prevention Using Co-Design Procedures: Focus Group Study With Health Care Providers and Patients With Myocardial Infarction.

BACKGROUND: Myocardial infarction (MI) is a debilitating condition and a leading cause of morbidity and mortality worldwide. Digital health is a promising approach for delivering secondary prevention to support patients with a history of MI and for reducing risk factors that can lead to a future event. However, its potential can only be fulfilled when the technology meets the needs of the end users who will be interacting with this secondary prevention. OBJECTIVE: We aimed to gauge the opinions of patients with a history of MI and health professionals concerning the functions, features, and characteristics of a digital health solution to support post-MI care. METHODS: Our approach aligned with the gold standard participatory co-design procedures enabling progressive refinement of feedback via exploratory, confirmatory, and prototype-assisted feedback from participants. Patients with a history of MI and health professionals from Australia attended focus groups over a videoconference system. We engaged with 38 participants across 3 rounds of focus groups using an iterative co-design approach. Round 1 included 8 participants (4 patients and 4 health professionals), round 2 included 24 participants (11 patients and 13 health professionals), and round 3 included 22 participants (14 patients and 8 health professionals). RESULTS: Participants highlighted the potential of digital health in addressing the unmet needs of post-MI care. Both patients with a history of MI and health professionals agreed that mental health is a key concern in post-MI care that requires further support. Participants agreed that family members can be used to support postdischarge care and require support from the health care team. Participants agreed that incorporating simple games with a points system can increase long-term engagement. However, patients with a history of MI emphasized a lack of support from their health care team, family, and community more strongly than health professionals. They also expressed some openness to using artificial intelligence, whereas health professionals expressed that users should not be aware of artificial intelligence use. CONCLUSIONS: These results provide valuable insights into the development of digital health secondary preventions aimed at supporting patients with a history of MI. Future research can implement a pilot study in the population with MI to trial these recommendations in a real-world setting.

Mobile health interventions for cancer patient education: A scoping review.

INTRODUCTION: Mobile health (mHealth) is using mobile devices and applications to deliver health information and services. mHealth has been increasingly applied in cancer care to support patients in various aspects of their disease journey. This scoping review aimed to explore the current evidence on the use of mHealth interventions for cancer patient education. METHODS: This scoping review followed the Joanna Briggs Institute (JBI) methodology for scoping reviews. We searched four electronic databases (PubMed, Web of Science, CINAHL, and Cochrane) using a combination of keywords related to mHealth, cancer, and education. After finding articles at the initial search the screening has been done based on the inclusion and exclusion criteria. We included only original research articles and excluded all other types of publications, such as review papers, reports, editorials, letters to the editor, book reviews, short communications, conference proceedings, graduate dissertations, protocols, and commentaries. We extracted data on the characteristics and outcomes of the included studies using a standardized form. We conducted a narrative synthesis and inductive content analysis to summarize and categorize the evidence. RESULTS: Out of 2131 records found in the initial search, 28 full-text articles reported on the use of mHealth educational interventions for cancer patients. The majority of the studies focused on breast cancer patients (n = 21, 75%). The most common type of mHealth intervention was exercise-based education delivered through various media such as text messages, videos, audio, images, and social networks. The main objectives of mHealth educational interventions were to enhance self-management skills, improve psychological well-being, and promote healthy lifestyle behaviors among cancer patients. The reported outcomes of mHealth interventions included reduced chemotherapy-related side effects, improved mental health, improved quality of life and lifestyle, and better pain management. CONCLUSION: This scoping review showed that mHealth is a promising and feasible modality for delivering educational interventions to cancer patients. However, more rigorous and diverse studies are needed to evaluate the effectiveness and cost-effectiveness of mHealth interventions for different types of cancers, stages, and settings.

A virtual training program for improving cultural competence among academic nurse educators.

BACKGROUND: Everyday, nursing students interact with culturally diverse clients. Nursing education recognizes that cultural competence is a necessary outcome of nursing programs. Nurse educators expect all nursing students to provide culturally congruent care to multicultural clients. Therefore, nurse educators must be culturally competent in order to prepare culturally competent nursing students for clinical practice. This study aimed to evaluate the effect of virtual training program on the cultural competence of academic nurse educators. METHODS: This randomized controlled study included nurse educators working in six nursing schools affiliated with medical universities of Kerman province in southeastern Iran. Sixty-nine nurse educators were randomly assigned to the intervention (n = 35) and control (n = 34) groups. The training program consisted of three 2-hour sessions for a month. Cultural Diversity Questionnaire for Nurse Educators Revised (CDQNE-R) was used to evaluate the cultural competence of educators before and one month after the virtual training program. RESULTS: Both the intervention (3.29 ± 0.58) and control (3.24 ± 0.58) groups demonstrated a similar level of cultural competence before the training program (t = 0.05, p = 0.95). After the training, the intervention group showed a significant increase in cultural competence (3.80 ± 0.7) compared to the control group (3.23 ± 0.67). This improvement resulted in culturally competent participants becoming culturally proficient, as evidenced by a large effect size (t = -4.76, p = 0.001). CONCLUSION: The virtual training program had a positive impact on the cultural competence of nurse educators. Given the importance of cultural competence in nursing education, continuing education programs that focus on strengthening the cultural competence of nurse educators should be prioritized. The experiences gained from implementing virtual training programs can serve as a valuable resource for nurse educators seeking to enhance their cultural competence.

Pregnant women's use and attitude toward Mobile phone features for self-management.

BACKGROUND: This study aimed to examine the current use of mobile phones by pregnant women and their attitudes towards the use of a variety of prenatal care services through mHealth. METHODS: This descriptive cross-sectional study was conducted in Iran in 2021. The study population included 168 pregnant women who referred to specialist obstetrics and gynecology clinic. The data collection tool was a questionnaire that included the demographics of the participants, their current mobile phone usage, and their attitudes toward mobile phone use for prenatal care services. The data were analyzed in SPSS with descriptive and analytical statistics. RESULTS: The majority of participants (84.2%) had a smartphone and access to mobile internet. More than half of the respondents (58.9%) used their mobile phone for (only) phone calls, and 36.7% occasionally used mobile internet to access prenatal care services. To get information about the pregnancy and to communicate with other pregnant women, the participants mainly used social media, and to get reminders, they preferred phone calls. CONCLUSIONS: In this study, pregnant women have a positive attitude towards using mobile phones for obtaining health services and prefer social media to seek prenatal care services. There seems to be a need for pregnant women to have high levels of digital health literacy and be advised by healthcare providers on using this technology to access prenatal care services.

Novel behaviour change frameworks for digital health interventions: A critical review.

Digital health interventions - interventions delivered over digital media to support the health of users - are becoming increasingly prevalent. Utilising an intervention development framework can increase the efficacy of digital interventions for health-related behaviours. This critical review aims to outline and review novel behaviour change frameworks that guide digital health intervention development. Our comprehensive search for preprints and publications used PubMed, PsycINFO, Scopus, Web of Science and the Open Science Framework repository. Articles were included if they: (1) were peer-reviewed; (2) proposed a behaviour change framework to guide digital health intervention development; (3) were written in English; (4) were published between 1/1/19 and 1/8/2021; and (5) were applicable to chronic diseases. Intervention development frameworks considered the user, intervention elements and theoretical foundations. However, the timing and policy of interventions are not consistently addressed across frameworks. Researchers should deeply consider the digital applicability of behaviour change frameworks to improve intervention success.

Artificial intelligence for secondary prevention of myocardial infarction: A qualitative study of patient and health professional perspectives.

BACKGROUND: Artificial intelligence (AI) has potential to improve self-management of several chronic conditions. However, the perspective of patients and healthcare professionals regarding AI-enabled health management programs, which are key to successful implementation, remains poorly understood. PURPOSE: To explore the opinions of people with a history of myocardial infarction (PHMI) and health professionals on the use of AI for secondary prevention of MI. PROCEDURE: Three rounds of focus groups were conducted via videoconferencing with 38 participants: 22 PHMI and 16 health professionals. FINDINGS: We identified 21 concepts stemming from participants' views, which we classified into five categories: Trust; Expected Functions; Adoption; Concerns; and Perceived Benefits. Trust covered the credibility of information and safety to believe health advice. Expected Functions covered tailored feedback and personalised advice. Adoption included usability features and overall interest in AI. Concerns originated from previous negative experience with AI. Perceived Benefits included the usefulness of AI to provide advice when regular contact with healthcare services is not feasible. Health professionals were more optimistic than PHMI about the usefulness of AI for improving health behaviour. CONCLUSIONS: Altogether, our findings provide key insights from end-users to improve the likelihood of successful implementation and adoption of AI-enabled systems in the context of MI, as an exemplar of broader applications in chronic disease management.

Barriers to and Facilitators of Digital Health Among Culturally and Linguistically Diverse Populations: Qualitative Systematic Review.

BACKGROUND: Health care systems have become increasingly more reliant on patients' ability to navigate the digital world. However, little research has been conducted on why some communities are less able or less likely to successfully engage with digital health technologies (DHTs), particularly among culturally and linguistically diverse (CaLD) populations. OBJECTIVE: This systematic review aimed to determine the barriers to and facilitators of interacting with DHTs from the perspectives of CaLD population groups, including racial or ethnic minority groups, immigrants and refugees, and Indigenous or First Nations people. METHODS: A systematic review and thematic synthesis of qualitative studies was conducted. Peer-reviewed literature published between January 2011 and June 2022 was searched across 3 electronic databases. Terms for digital health were combined with terms for cultural or linguistic diversity, ethnic minority groups, or Indigenous and First Nations people and terms related to barriers to accessing digital technologies. A qualitative thematic synthesis was conducted to identify descriptive and analytical themes of barriers to and facilitators of interacting with DHTs. Quality appraisal was performed using the Mixed Methods Appraisal Tool. RESULTS: Of the 1418 studies identified in the electronic search, a total of 34 (2.4%) were included in this review. Half of the included studies (17/34, 50%) were conducted in the United States. There was considerable variation in terms of the CaLD backgrounds of the participants. In total, 26% (9/34) of the studies focused on Indigenous or First Nations communities, 41% (14/34) were conducted among ethnic minority populations, 15% (5/34) of the studies were conducted among immigrants, and 18% (6/34) were conducted in refugee communities. Of the 34 studies, 21 (62%) described the development or evaluation of a digital health intervention, whereas 13 (38%) studies did not include an intervention but instead focused on elucidating participants' views and behaviors in relation to digital health. From the 34 studies analyzed, 18 descriptive themes were identified, each describing barriers to and facilitators of interacting with DHTs, which were grouped into 7 overarching analytical themes: using technology, design components, language, culture, health and medical, trustworthiness, and interaction with others. CONCLUSIONS: This study identified several analytic and descriptive themes influencing access to and uptake of DHTs among CaLD populations, including Indigenous and First Nations groups. We found that cultural factors affected all identified themes to some degree and that cultural and linguistic perspectives should be considered in the design and delivery of DHTs, with this best served through the inclusion of the target communities at all stages of development. This may improve the potential of DHTs to be more acceptable, appropriate, and accessible to population groups currently at risk of not obtaining the full benefits of digital health.

Bibliometric analysis of COVID-19 publications shows the importance of telemedicine and equitable access to the internet during the pandemic and beyond.

BACKGROUND: Pandemics highlight the increasing role of information and communications technology for improving access to health care. This study aimed to present a bibliometric analysis of the concept of digital divide reported in the published articles concerning the coronavirus disease 2019 (COVID-19) pandemic. METHODS: To conduct this bibliometric analysis of research topics and trends, we used VOSviewer software. We developed a search strategy to retrieve peer-reviewed publications related to 'digital divide in the COVID-19 era' from the Scopus database. RESULTS: In total, 241 publications on the topic of digital divide and COVID-19 were retrieved from Scopus database between 2020 and 2021. The analysis of keywords co-occurrence of research topics revealed four main clusters including: 'telemedicine', 'Internet access and Internet use', 'e-learning' and 'epidemiology'. Seven characteristic categories were examined in these research topics, including: sociodemographic, economic, social, cultural, personal, material and motivational. CONCLUSION: 'Telemedicine' and 'Internet access and Internet use' as the largest clusters are connected to topics addressing inequalities in online health care access. Thus, policymakers should develop or modify policies in more egalitarian Internet access for all community members not only during a pandemic like the COVID-19 but also at regular times.

The effect of diabetes training through social networks on metabolic control of individuals with type 2 diabetes; a randomized controlled trial.

Background: Due to spread of smart phones, opportunity to train patients with diabetes and communicate with them using social media is rising. Aim of this study was to evaluate the effect of training through two popular social networks in Iran ("Telegram" and "Soroush") and the metabolic control of people with Type 2 diabetes. Methods: In this randomized controlled trial, we recruited 134 patients with type 2 diabetes, which randomly allocated into two groups: the intervention and the control group on a 1:1 basis. The studied tools included demographic information and awareness of diabetes and international physical activity questionnaires. The intervention comprised a training package that delivered to the intervention group via social media for 45 days. The primary outcome measures included awareness of diabetes management and physical activity level while secondary outcome measures were HbA1c and lipid profile. Results: Social network training led to the increase of the patients' awareness (44.31 ± 2.78 to 46.88 ± 2.25 in intervention group vs 44.14 ± 3.85 to 44.41 ± 3.87 in control group) and physical activities level (23.64 ± 8.46 to 31.68 ± 7.12 in intervention group vs 26.20 ± 9.39 to 30.20 ± 8.11 in control group) (p-value < 0.001). Besides, LDL and HDL levels, and HbA1c (8.19 ± 2.10 to 8.05 ± 1.96 in intervention group vs. 7.53 ± 1.67 to 7.45 ± 1.34 in control group) decreased significantly (p-value < 0.05). Conclusions: Changes in lifestyle and challenges of the patients' attendance in diabetes training sessions, declared that use of social networks can be useful to train diabetes patients remotely, and it is feasible to send training messages to help them improve their diabetes care.

Exploring public opinion about telehealth during COVID-19 by social media analytics.

While COVID-19 catalyzed the acceptance and use of telehealth, our understanding of how it is perceived by multi-stakeholders such as patients, clinicians, and health authorities is limited. Drawing on social media analytics, this research examines social media discourses and users' opinions about telehealth during the COVID-19 pandemic. It applies natural language processing and deep learning to explore word of mouth on telehealth with a contextualized focus on the COVID-19 pandemic. We conducted topic modeling, sentiment analysis, and emotion analysis (fearful, happy, sad, surprised, and angry emotions). The topic modeling analysis led to the identification of 18 topics, representing 6 themes of digital health service delivery, pandemic response, communication and promotion, government action, health service domains (e.g. mental health, cancer, aged care), as well as pharma and drug. The sentiment analysis revealed that while most opinions expressed in tweets were positive, the public expressed mostly negative opinions about certain aspects of COVID-19 such as lockdowns and cyberattacks. Emotion analysis of tweets showed a dominant pattern of fearful and sad emotions in particular topics. The results of this study that inductively emerged from our social media analysis can aid public health authorities and health professionals to address the concerns of telehealth users and improve their experiences.

Assessing the online search behavior for COVID-19 outbreak: Evidence from Iran.

INTRODUCTION: Google Trends (GT) is an important free tool for online search behavior analysis, which provides access to Internet search patterns in Google. In recent decades, this database has been used for predicting the outbreak of epidemics and pandemics in different regions of the world. The present study aimed to evaluate Iranian users' COVID-19-related online search behavior. METHODS: This longitudinal study was conducted in 2021. The data of Iranian users' COVID-19-related online search behavior (trend) were collected from the GT website, and the epidemiological data of the COVID-19 outbreak in Iran from 16 February 2020 to 2 January 2021 were sourced from the Iranian ministry of health and medical education, as well as the World Health Organization. The data were analyzed in SPSS using descriptive and inferential statistics. RESULTS: All the COVID-19-related search terms in Iran gained their highest popularity value (relative search volume = 100) in the first 8 weeks of the pandemic, and then this value assumed a decreasing trend over time. Based on factor analysis, relative search volume (RSV) of factor 1 terms (related to corona [in Persian] and corona) have a low significance relationship with COVID-19 epidemiological data in one-, two-, and three-week time lags. Although, RSV of factor 2 terms (related to COVID [in Persian], COVID-19, and coronavirus) correlated with the total weekly number of COVID-19 cases in mentioned time lags. CONCLUSION: COVID-19-related search terms were popular among Iranian users at the beginning of the pandemic. The online search queries and the key terms searched by Iranian users varied during the COVID-19 pandemic. This study provides evidence in favor of the adoption of GT as an epidemiological surveillance tool but, it is necessary to consider that mass media and other confounders can significantly influence RSVs.

A qualitative analysis of the needs and wishes of people with type 2 diabetes and healthcare professionals for optimal diabetes care.

AIM: Globally, type 2 diabetes care is often fragmented and still organised in a provider-centred way, resulting in suboptimal care for many individuals. As healthcare systems seek to implement digital care innovations, it is timely to reassess stakeholders' priorities to guide the redesign of diabetes care. This study aimed to identify the needs and wishes of people with type 2 diabetes, and specialist and primary care teams regarding optimal diabetes care to explore how to better support people with diabetes in a metropolitan healthcare service in Australia. METHODS: Our project was guided by a Participatory Design approach and this paper reports part of the first step, identification of needs. We conducted four focus groups and 16 interviews (November 2019-January 2020) with 17 adults with type 2 diabetes and seven specialist clinicians from a diabetes outpatient clinic in Brisbane, Australia, and seven primary care professionals from different clinics in Brisbane. Data were analysed using reflexive thematic analysis, building on the Capability, Opportunity, Motivation and Behaviour model. RESULTS: People with diabetes expressed the wish to be equipped, supported and recognised for their efforts in a holistic way, receive personalised care at the right time and improved access to connected services. Healthcare professionals agreed and expressed their own burden regarding their challenging work. Overall, both groups desired holistic, personalised, supportive, proactive and coordinated care pathways. CONCLUSIONS: We conclude that there is an alignment of the perceived needs and wishes for improved diabetes care among key stakeholders, however, important gaps remain in the healthcare system.