The objective was to identify and describe the published guidance and current academic discourse of ethical issues and standards related to the use of Social Media Research for generating patient insights for the use by health technology assessment (HTA) or health policy decisions.

A scoping review of the literature was conducted in PubMed and Embase and identified 935 potential references published between January 2017 and June 2021. After title and abstract screening by three reviewers, 40 publications were included, the relevant information was extracted and data were collected in a mind map, which was then used to structure the output of the review.

Social Media Research may reveal new insights of relevance to HTA or health policies into patient needs, patient experiences, or patient behaviors. However, the research approaches, methods, data use, interpretation, and communication may expose those who post the data in social media channels to risks and potential harms relating to privacy, anonymity/confidentiality, authenticity, context, and rapidly changing technologies.

An actively engaged approach to ensuring ethical innocuousness is recommended that carefully follows best practices throughout planning, conduct, and communication of the research. Throughout the process and as a follow-up, there should be a discourse with the ethical experts to maximally protect the current and future users of social media, to support their trust in the research, and to advance the knowledge in parallel to the advancement of the media themselves, the technologies, and the research tools.

The aim of this initiative was to examine collaboratively, in a multi-stakeholder team (health technology assessment (HTA) practitioners with patient involvement expertise, health technology industry, patient advocates, health policy experts, patient engagement experts), whether evidence generated through social media research (SMR) fills current information gaps relating to insights on specific aspects of patient experiences, preferences, or patient needs and delivers additional value to HTA.

The framing of the project was done in a co-creative, deliberative multi-stakeholder process. Challenge and refinement happened through discussions with 25 independent stakeholders from HTA bodies, industry, academia, and patient advocacy. For critical themes identified during the framing phase, scoping literature reviews were performed including the state of methods and examples for the use of SMR in HTA.

The framing and stakeholder discussions specified a set of expectations and requirements, and the scoping reviews revealed the current state of methods and usage of SMR in health-policy decision making.

The project concluded that SMR can contribute new, relevant evidence to HTA. It is however recommended to evolve the science through defining best practices when planning, conducting, and using SMR and to conduct multi-stakeholder pilot SMR projects to address questions relevant to current HTAs and to validate and improve the proposed practices.

Social media and other technologies are reshaping communication and health.

This review addresses the relationship between social media use, behavioural health conditions and psychological well-being for youth aged <25 years.

A scoping review of 11 literature databases from 2000 to 2020 explored research studies in youth in five areas: clinical depression and anxiety, quantitative use, social media mode, engagement and qualitative dimensions and health and well-being.

Out of 2820 potential literature references, 140 met the inclusion criteria. The foci were clinical depression and anxiety disorders (n = 78), clinical challenges (e.g. suicidal ideation, cyberbullying) (n = 34) and psychological well-being (n = 28). Most studies focused on Facebook, Twitter, Instagram and YouTube. Few studies are longitudinal in design (n = 26), had comparison groups (n = 27), were randomised controlled trials (n = 3) or used structured assessments (n = 4). Few focused on different youth and sociodemographic populations, particularly for low-income, equity-seeking and deserving populations. Studies examined association (n = 120; 85.7%), mediating (n = 16; 11.4%) and causal (n = 4; 2.9%) relationships. Prospective, longitudinal studies of depression and anxiety appear to indicate that shorter use (≤3 h/day) and purposeful engagement is associated with better mood and psychological well-being. Depression may predict social media use and reduce perception of support. Findings provide families, teachers and providers ways to engage youth.

Research opportunities include clinical outcomes from functional perspective on a health continuum, diverse youth and sociodemographic populations, methodology, intervention and privacy issues. More longitudinal studies, comparison designs and effectiveness approaches are also needed. Health systems face clinical, training and professional development challenges.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) hospital outbreaks have been common and devastating during the coronavirus disease 2019 (COVID-19) pandemic. Understanding SARS-CoV-2 transmission in these environments is critical for preventing and managing outbreaks.

Outbreak investigation through epidemiological mapping and whole-genome sequencing phylogeny.

Hospital in-patient medical unit outbreak in Toronto, Canada, from November 2020 to January 2021.

The outbreak involved 8 patients and 10 staff and was associated with 3 patient deaths.

Patients being cared for in geriatric chairs at the nursing station were at high risk for both acquiring and transmitting SARS-CoV-2 to other patients and staff. Furthermore, given the informal nature of these transmissions, they were not initially recognized, which led to further transmission and missing the opportunity for preventative COVID-19 therapies.

During outbreak prevention and management, the risk of informal patient care settings, such as geriatric chairs, should be considered. During high-risk periods or during outbreaks, efforts should be made to care for patients in their rooms when possible.

To test a culturally tailored obesity prevention intervention in low-income, minority preschool age children.

A three-group clustered randomised controlled trial.

Twelve Head Start centres were randomly assigned to a centre-based intervention, a combined centre- and home-based intervention, or control using a 1:1:1 ratio. The centre-based intervention modified centre physical activity and nutrition policies, staff practices, and child behaviours, while the home-based intervention supported parents for obesity prevention at home.

The primary end point was change in children’s BMI (kg/m2) at post-test immediately following completion of the 8-month intervention. Secondary end points included standardised scores for BMI (BMIz) and body weight (WAZ), and BMI percentiles (BMI pctl).

Three-year-old children enrolled in Head Start in San Antonio, Texas, with written parent consent (n 325), 87 % Latino, 57 % female with mean age (sd) of 3·58 years (0·29).

Change in BMI at post-test was 1·28 (0·97), 1·28 (0·87) and 1·41 (0·71) in the centre + home-based intervention, centre-based intervention and control, respectively. There was no significant difference in BMI change between centre + home-based intervention and control or centre-based intervention and control at post-test. BMIz (adjusted difference –0·12 (95 % CI, –0·24, 0·01), P = 0·06) and WAZ (adjusted difference, –0·09 (–0·17, –0·002), P = 0·04) were reduced for children in centre + home-based intervention compared with control group.

There was no reduction in BMI at post-test in children who received the intervention. Findings shed light on methodological challenges in childhood obesity research and offer future directions to explore health equity-oriented obesity prevention.

Mood episodes in bipolar disorder (BD) are still identified with subjective retrospective reports and scales. Digital biomarkers, such as actigraphy, heart rate variability, or ElectroDermal activity (EDA) have demonstrated their potential to objectively capture illness activity.

To identify physiological digital signatures of illness activity during acute episodes of BD compared to euthymia and healthy controls (HC) using a novel wearable device (Empatica´s E4).

A pragmatic exploratory study. The sample will include 3 independent groups totalizing 60 individuals: 36 BD inpatients admitted due to severe acute episodes of mania (N=12), depression (N=12), and mixed features (N=12), will wear the E4-device at four timepoints: the acute phase (T0), treatment response (T1), symptoms remission (T2) and during euthymia (T3; outpatient follow-up). 12 BD euthymic outpatients and 12 HC will be asked to wear the E4-device once. Data pre-processing included average downsampling, channel time-alignment in 2D segments, 3D-array stacking of segments, and random shuffling for training/validation sets. Finally, machine learning algorithms will be applied.

A total of 10 patients and 5 HC have been recruited so far. The preliminary results follow the first differences between the physiological digital biomarkers between manic and depressive episodes. 3 fully connected layers with 32 hidden units, ectified linear activation function (ReLU) activation, 25% dropout rate, significantly differentiated a manic from a depressive episode at different timepoints (T0, T1, T2).

New wearables technologies might provide objective decision-support parameters based on digital signatures of symptoms that would allow tailored treatments and early identification of symptoms.

No significant relationships.

Major Depressive Disorder (MDD) is prevalent, often chronic, and requires ongoing monitoring of symptoms to track response to treatment and identify early indicators of relapse. Remote Measurement Technologies (RMT) provide an exciting opportunity to transform the measurement and management of MDD, via data collected from inbuilt smartphone sensors and wearable devices alongside app-based questionnaires and tasks.

To describe the amount of data collected during a multimodal longitudinal RMT study, in an MDD population.

RADAR-MDD is a multi-centre, prospective observational cohort study. People with a history of MDD were provided with a wrist-worn wearable, and several apps designed to: a) collect data from smartphone sensors; and b) deliver questionnaires, speech tasks and cognitive assessments and followed-up for a maximum of 2 years.

A total of 623 individuals with a history of MDD were enrolled in the study with 80% completion rates for primary outcome assessments across all timepoints. 79.8% of people participated for the maximum amount of time available and 20.2% withdrew prematurely. Data availability across all RMT data types varied depending on the source of data and the participant-burden for each data type. We found no evidence of an association between the severity of depression symptoms at baseline and the availability of data. 110 participants had > 50% data available across all data types, and thus able to contribute to multiparametric analyses.

RADAR-MDD is the largest multimodal RMT study in the field of mental health. Here, we have shown that collecting RMT data from a clinical population is feasible.

No significant relationships.

This study aimed to investigate the use of the head and neck cancer risk calculator version 2 in a primary care setting and to evaluate the impact of the risk calculator on the number of referrals stratified by urgency and cancer yield.

Referrals between April 2019 and August 2019, April 2020 and July 2020 (pre-risk calculator) and August 2020 and July 2021 (post-risk calculator) were analysed. Referral urgency, head and neck cancer risk calculator version 2 score, cancer diagnosis, cancer type and further investigations were recorded.

The 2023 patient encounters were analysed; there were 1110 (55 per cent) referrals before head and neck cancer risk calculator version 2 use and 913 (45 per cent) after head and neck cancer risk calculator version 2 use. A higher proportion of older (p < 0.001) and male (p < 0.013) patients were seen post-head and neck cancer risk calculator version 2 use. All cancer cases were seen on the urgent suspicion of cancer pathway post-head and neck cancer risk calculator version 2 use; however, a higher proportion of patients were seen as urgent suspicion of cancer (51.1 vs 83.5 per cent; p < 0.001). Overall, the cancer diagnosis rate increased from 2.7 to 4.1 per cent.

The head and neck cancer risk calculator version 2 had high sensitivity in cancer diagnosis. More studies are required to optimise the predicted versus actual cancer probability gap.