Volunteering provides unique benefits to organisations, recipients, and potentially the volunteers themselves. This umbrella review examined the benefits of volunteering and their potential moderators. Eleven databases were searched for systematic reviews on the social, mental, physical, or general health benefits of volunteering, published up to July 2022. AMSTAR 2 was used to assess quality and overlap of included primary studies was calculated. Twenty-eight reviews were included; participants were mainly older adults based in the USA. Although overlap between reviews was low, quality was generally poor. Benefits were found in all three domains, with reduced mortality and increased functioning exerting the largest effects. Older age, reflection, religious volunteering, and altruistic motivations increased benefits most consistently. Referral of social prescribing clients to volunteering is recommended. Limitations include the need to align results to research conducted after the COVID-19 pandemic. (PROSPERO registration number: CRD42022349703).

Background: Healthcare workers (HCWs) and healthcare students display high levels of vaccine hesitancy with impact on healthcare provision, patient safety, and health promotion. The factors related to vaccine hesitancy have been reported in several systematic reviews. However, this evidence needs to be synthesised, as interventions to reduce vaccination hesitancy in this population are needed. Methods: This Umbrella Review aimed to explore the barriers and facilitators of vaccine hesitancy toward the COVID-19 vaccine for HCWs and healthcare students. The review was performed and reported in accordance with Joanna Briggs Institutes guidelines and the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. A protocol was preregistered on PROSPERO (CRD42022327354). Eight databases were searched from November 2019 to 23^rd May 2022 to identify any systematic reviews that explored factors associated with hesitancy towards the COVID-19 vaccine for HCWs or healthcare students. Results: A total of 31 studies were included in the review. The majority of studies (71%) were appraised as strong or moderate quality and there was a slight degree of overlap (<5%) of primary studies between the reviews. Vaccine hesitancy was more common among HCWs and healthcare students in specific occupational roles (e.g. nurses) than others (e.g. physicians). Frequent reasons for hesitancy were related to sociodemographic factors (gender, age, ethnicity), occupational factors (COVID-19 exposure, perceived risk, mandatory vaccination), health factors (vaccination history), vaccine-related factors (concerns about safety, efficacy, side-effects, rapid development, testing, approval and distribution of the vaccine), social factors (social pressure, altruism and collective responsibility), distrust factors (key social actors, pandemic management), information factors (inadequate information and sources, exposure to misinformation). Conclusion: The results from this Umbrella Review have wide-reaching implications for the research area, healthcare systems and institutions and governments worldwide. Designing tailored strategies for specific occupational groups is pivotal to increasing vaccine uptake and securing a safe healthcare provision worldwide.

Socially assistive robots offer an alternate source of connection for interventions within health and social care amidst a landscape of technological advancement and reduced staff capacity. There is a need to summarise the available systematic reviews on the health and wellbeing impacts to evaluate effectiveness, explore potential moderators and mediators, and identify recommendations for future research and practice. To explore the effect of socially assistive robots within health and social care on psychosocial, behavioural, and physiological health and wellbeing outcomes across the lifespan (PROSPERO registration number: CRD42023423862). An umbrella review utilising meta-analysis, narrative synthesis, and vote counting by direction of effect. 14 databases were searched (ProQuest Health Research Premium collection, Scopus, PubMed, Web of Science, ASM Digital Library, IEEE Xplore, Cochrane Reviews, and EPISTEMONIKOS) from 2005 to May 4, 2023. Systematic reviews including the effects of socially assistive robots on health outcomes were included and a pooled meta-analysis, vote counting by direction of effect, and narrative synthesis were applied. The second version of A MeaSurement Tool to Assess systematic Reviews (AMSTAR-2) was applied to assess quality of included reviews. 35 reviews were identified, most focusing on older adults with or without dementia (n = 24). Pooled meta-analysis indicated no effect of socially assistive robots on quality of life (standard mean difference (SMD) = 0.43), anxiety (SMD = -0.02), or depression (SMD = 0.21), although vote counting identified significant improvements in social interaction, mood, positive affect, loneliness, stress, and pain across the lifespan, and narrative synthesis identified an improvement in anxiety in children. However, some reviews reported no significant difference between the effects of socially assistive robots and a plush toy, and there was no effect of socially assistive robots on psychiatric outcomes including agitation, neuropsychiatric symptoms, and medication use. Socially assistive robots show promise for improving non-psychiatric outcomes such as loneliness, positive affect, stress, and pain, but exert no effect on psychiatric outcomes such as depression and agitation. The main mechanism of effect within group settings appeared to be the stimulation of social interaction with other humans. Limitations include the low quality and high amount of overlap between included reviews. Socially assistive robots may help to improve loneliness, social interaction, and positive affect in older adults, decrease anxiety and distress in children, and improve mood, stress, and reduce pain across the lifespan. However, before recommendations for socially assistive robots can be made, a cost-effectiveness analysis of socially assistive robots to improve mood across the lifespan, and a quantitative analysis of the effects on pain, anxiety, and distress in children are required.

Improving healthcare professionals' digital health competence is critical to providing safer care. However, there is still a lack of empirical studies exploring the factors influencing healthcare professionals' digital health competence, even though significant investments have been made to advance digitalisation of healthcare globally. This study aimed to identify the key characteristics influencing healthcare professionals' digital health competence. Cross-sectional data was collected from 252 healthcare professionals using two instruments measuring the digital health competences and the associated educational and organisational factors in 2024 via an online and paper-based survey. Univariate and binary logistic regression analyses were performed to identify the key characteristics influencing digital health competence. Higher levels of education, working in a hospital, more professional experience, and increased use of digital solutions at work or during free time were associated with higher digital health competence. Higher qualifications were linked to greater digital health competence across several factors, with postgraduate degrees increasing health-related counselling competence and undergraduate degrees enhancing work-related attitudes and evaluating digital solutions. Professionals with university qualifications and those working in hospital settings showed higher ICT competence, while more years of professional experience increased ethical competence in using digital solutions. Digital health competence development should prioritise healthcare professionals with lower educational levels. Additionally, such initiatives should include supporting those who work in non-hospital settings, have less professional experience, and use digital solutions less frequently at work or in their free time. Professional experience increases ethical competence in using digital solutions. Continuous professional development interventions and organisational policies should consider these factors to improve healthcare professionals' digital health competences.

The Making Every Contact Count (MECC) initiative is broadly defined as an opportunistic approach to prevention by making use of the thousands of conversations service providers have with service users every day. However, since its conception, the application of MECC has diverged and developed considerably. Thus, the current study aimed to revise the definition according to current research and practice to better describe what is and is not included. A consensus building classic Delphi methodology, completed by an expert panel. Round 1 asked open questions around the definition of MECC. Content analysis of round 1 identified statements that were rated for agreement in round 2. Statements achieving ≥80% agreement were included in a short, long, or operational definition of MECC that were rated for agreement in round 3 (the minimum number required). An agreement of ≥80% indicated consensus. Forty out of 100 contacted experts completed three rounds. Experts in practice and research were recruited internationally although most were from England. From round 1, 274 statements were generated, of which 96 achieved consensus and were included within round 3. The short and long definition received consensus in round 3, the operational definition required four rounds to reach consensus. MECC is a person-centred approach to health behaviour change that, provided an individual possesses the relevant skills, can be delivered by anyone and anywhere. The distinguishing feature of MECC is not in its duration, target behaviour, or conditions for delivery, but rather in the approach taken and the mechanisms applied to conversations. Implications for research and practice are discussed, and the limits for applicability acknowledged.

Background The Making Every Contact Count (MECC) programme provides training and materials to support public-facing workers to encourage health-promoting behaviour change by using the day-to-day interactions between organisations and individuals. This project aimed to analyse MECC implementation through a comparative analysis of implementation stage, strategies used for implementation and enablers/barriers of the implementation process within a region in England—the North East and North Cumbria (NENC). Methods A mixed-methods process evaluation was conducted applying normalisation process theory and theoretical domains framework. MECC programme documents were reviewed and mapped against specific criteria (eg, implementation strategies). An online mapping survey was conducted to establish current implementation/delivery of MECC within NENC settings (eg, local government, healthcare and voluntary community sector). Qualitative research, using individual interviews and group discussions, was conducted to establish further understanding of MECC implementation. Results Our findings were informed by reviewing documents (n=5), surveying participants (n=34), interviews (n=18) and group discussions (n=48). Overall, the implementation of MECC within the region was at an early stage, with training mostly delivered between, rather than within, organisations. Qualitative findings highlighted factors that influence stakeholders to implement MECC (eg, organisational goals that were facilitated by MECC implementation, including the prevention agenda), supported resources that facilitate the implementation of MECC (eg, logic models) and enabling factors that promote MECC sustainability across the region (eg, buy-in from leadership and management). Conclusions The NENC MECC programme is built around regional leadership that supports the implementation process. This process evaluation identified key influences of MECC implementation across the region. We discuss evidence-based recommendation for policy and practice that can be taken forward to develop targeted strategies to support future MECC implementation. For example, a co-ordinated infrastructure and strategy is needed to combat delivery and implementation issues identified.