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Background Implementation science has a core aim – to get evidence into practice. Early in the evidence-based medicine movement, this task was construed in linear terms, wherein the knowledge pipeline moved from evidence created in the laboratory through to clinical trials and, finally, via new tests, drugs, equipment, or procedures, into clinical practice. We now know that this straight-line thinking was naïve at best, and little more than an idealization, with multiple fractures appearing in the pipeline. Discussion The knowledge pipeline derives from a mechanistic and linear approach to science, which, while delivering huge advances in medicine over the last two centuries, is limited in its application to complex social systems such as healthcare. Instead, complexity science, a theoretical approach to understanding interconnections among agents and how they give rise to emergent, dynamic, systems-level behaviors, represents an increasingly useful conceptual framework for change. Herein, we discuss what implementation science can learn from complexity science, and tease out some of the properties of healthcare systems that enable or constrain the goals we have for better, more effective, more evidence-based care. Two Australian examples, one largely top-down, predicated on applying new standards across the country, and the other largely bottom-up, adopting medical emergency teams in over 200 hospitals, provide empirical support for a complexity-informed approach to implementation. The key lessons are that change can be stimulated in many ways, but a triggering mechanism is needed, such as legislation or widespread stakeholder agreement; that feedback loops are crucial to continue change momentum; that extended sweeps of time are involved, typically much longer than believed at the outset; and that taking a systems-informed, complexity approach, having regard for existing networks and socio-technical characteristics, is beneficial. Conclusion Construing healthcare as a complex adaptive system implies that getting evidence into routine practice through a step-by-step model is not feasible. Complexity science forces us to consider the dynamic properties of systems and the varying characteristics that are deeply enmeshed in social practices, whilst indicating that multiple forces, variables, and influences must be factored into any change process, and that unpredictability and uncertainty are normal properties of multi-part, intricate systems.

Background Patient‐reported outcome measures (PROMs) are questionnaires that collect health outcomes directly from the people who experience them. This review critically synthesizes information on generic and selected condition‐specific PROMs to describe trends and contemporary issues regarding their development, validation and application. Methods We reviewed academic and grey literature on validated PROMs by searching databases, prominent websites, Google Scholar and Google Search. The identification of condition‐specific PROMs was limited to common conditions and those with a high burden of disease (eg cancers, cardiovascular disorders). Trends and contemporary issues in the development, validation and application of PROMs were critically evaluated. Results The search yielded 315 generic and condition‐specific PROMs. The largest numbers of measures were identified for generic PROMs, musculoskeletal conditions and cancers. The earliest published PROMs were in mental health‐related conditions. The number of PROMs grew substantially between 1980s and 2000s but slowed more recently. The number of publications discussing PROMs continues to increase. Issues identified include the use of computer‐adaptive testing and increasing concerns about the appropriateness of using PROMs developed and validated for specific purposes (eg research) for other reasons (eg clinical decision making). Conclusions The term PROM is a relatively new designation for a range of measures that have existed since at least the 1960s. Although literature on PROMs continues to expand, challenges remain in selecting reliable and valid tools that are fit‐for‐purpose from the many existing instruments. Patient or public contribution Consumers were not directly involved in this review; however, its outcome will be used in programmes that engage and partner with consumers.

Background Q-methodology is an approach to studying complex issues of human ‘subjectivity’. Although this approach was developed in the early twentieth century, the value of Q-methodology in healthcare was not recognised until relatively recently. The aim of this review was to scope the empirical healthcare literature to examine the extent to which Q-methodology has been utilised in healthcare over time, including how it has been used and for what purposes. Methods A search of three electronic databases (Scopus, EBSCO-CINAHL Complete, Medline) was conducted. No date restriction was applied. A title and abstract review, followed by a full-text review, was conducted by a team of five reviewers. Included articles were English-language, peer-reviewed journal articles that used Q-methodology (both Q-sorting and inverted factor analysis) in healthcare settings. The following data items were extracted into a purpose-designed Excel spreadsheet: study details (e.g., setting, country, year), reasons for using Q-methodology, healthcare topic area, participants (type and number), materials (e.g., ranking anchors and Q-set), methods (e.g., development of the Q-set, analysis), study results, and study implications. Data synthesis was descriptive in nature and involved frequency counting, open coding and the organisation by data items. Results Of the 2,302 articles identified by the search, 289 studies were included in this review. We found evidence of increased use of Q-methodology in healthcare, particularly over the last 5 years. However, this research remains diffuse, spread across a large number of journals and topic areas. In a number of studies, we identified limitations in the reporting of methods, such as insufficient information on how authors derived their Q-set, what types of analyses they performed, and the amount of variance explained. Conclusions Although Q-methodology is increasingly being adopted in healthcare research, it still appears to be relatively novel. This review highlight commonalities in how the method has been used, areas of application, and the potential value of the approach. To facilitate reporting of Q-methodological studies, we present a checklist of details that should be included for publication.

Location-based augmented reality (AR) games, such as Pokémon GO and Harry Potter: Wizards Unite, have been shown to have a beneficial impact on the physical activity, social connectedness, and mental health of their players. In March 2020, global social distancing measures related to the COVID-19 pandemic prompted the AR games developer Niantic Inc to implement several changes to ensure continued player engagement with Pokémon GO and Harry Potter: Wizards Unite. We sought to examine how the physical and mental well-being of players of these games were affected during the unprecedented COVID-19 restriction period as well as how their video game engagement was affected. The aims of this study were to examine the impact of COVID-19-related social restrictions on the physical and mental well-being of AR game players; to examine the impact of COVID-19-related social restrictions on the use of video games and motivations for their use; and to explore the potential role of AR games (and video games in general) in supporting well-being during COVID-19-related social restrictions. A mixed methods web-based self-reported survey was conducted in May 2020, during which COVID-19-related social restrictions were enforced in many countries. Participants were recruited on the web via four subreddits dedicated to Pokémon GO or Harry Potter: Wizards Unite. Data collected included quantitative data on demographics, time spent playing video games, physical activity, and mental health; qualitative data included motivations to play and the impact of video games on mental health during COVID-19 lockdown. We report results for 2004 participants (1153/1960 male, 58.8%, average age 30.5 years). Self-reported physical activity during COVID-19-related social restrictions significantly decreased from 7.50 hours per week on average (SD 11.12) to 6.50 hours (SD 7.81) (P<.001). More than half of the participants reported poor mental health (925/1766, 52.4%; raw World Health Organization-5 Well-Being Index score <13). Female gender, younger age, and reduced exercise were significant predictors of poor mental health. Participants reported a significant increase in video game play time from 16.38 hours per week on average (SD 19.12) to 20.82 hours (SD 17.49) (P<.001). Approximately three quarters of the participants (n=1102/1427, 77.2%) reported that playing video games had been beneficial to their mental health. The changes made to Pokémon GO and Harry Potter: Wizards Unite were very well received by players, and the players continued to use these games while exercising and to maintain social connection. In addition to seeking an escape during the pandemic and as a form of entertainment, participants reported that they used video games for emotional coping and to lower stress, relax, and alleviate mental health conditions. AR games have the potential to promote physical and mental health during the COVID-19 pandemic. Used by populations under isolation and distress, these games can improve physical and mental health by providing virtual socialization, sustained exercise, temporal routine, and mental structure. Further research is needed to explore the potential of AR games as digital behavioral interventions to maintain human well-being in the wider population.

Background When healthcare professionals’ workloads are greater than available resources, care activities can be missed, omitted or delayed, potentially leading to adverse patient outcomes. Prioritisation, a precursor to missed care, involves decision-making about the order of care task completion based on perceived importance or urgency. Research on prioritisation and missed care has predominantly focused on acute care settings, which differ from residential aged care facilities in terms of funding, structure, staffing levels, skill mix, and approaches to care. The objective of this study was to investigate how care staff prioritise the care provided to residents living in residential aged care. Methods Thirty-one staff members from five Australian residential aged care facilities engaged in a Q sorting activity by ranking 34 cards representing different care activities on a pre-defined grid from ‘Least important’ (− 4) to ‘Most important’ (+ 4). Concurrently, they participated in a think-aloud task, verbalising their decision-making processes. Following sorting, participants completed post-sorting interviews, a demographics questionnaire and semi-structured interviews. Q sort data were analysed using centroid factor analysis and varimax rotation in PQMethod. Factor arrays and data from the think-aloud task, field notes and interviews facilitated interpretation of the resulting factors. Results A four-factor solution, representing 22 participants and 62% of study variance, satisfied the selection criteria. The four distinct viewpoints represented by the solution were: 1. Prioritisation of clinical care, 2. Prioritisation of activities of daily living, 3. Humanistic approach to the prioritisation of care, and 4. Holistic approach to the prioritisation of care. Participants’ prioritisation decisions were largely influenced by their occupations and perceived role responsibilities. Across the four viewpoints, residents having choices about their care ranked as a lower priority. Conclusions This study has implications for missed care, as it demonstrates how care tasks deemed outside the scope of staff members’ defined roles are often considered a lower priority. Our research also shows that, despite policy regulations mandating person-centred care and the respect of residents’ preferences, staff members in residential aged care facilities tend to prioritise more task-oriented aspects of care over person-centredness.

Despite more than 2 decades of telehealth use in Australia and the rapid uptake during the COVID-19 pandemic, little is known about its unintended consequences beyond its planned and intended outcomes. The aim of this review was to synthesize evidence on the unintended consequences of telehealth use in Australia to clarify its impact beyond its planned and intended outcomes. We conducted a search of 4 electronic databases: Ovid MEDLINE, Ovid Embase, EBSCO CINAHL, and Scopus. A critical interpretive synthesis approach was adopted for its flexibility and interpretive nature. We extracted data about study characteristics and the types and models of telehealth services. The extracted unintended consequences were coded and mapped into the domains and dimensions of the Australian Health Performance Framework. Of the 4241 records identified by the search, 94 (2.22%) studies were eligible for data extraction and analysis. Of these 94 studies, 23 (24%) reported largely positive unintended consequences of telehealth associated with health status, while 6 (6%) noted a potential negative impact of telehealth on socioeconomic status. The findings of 4 (4%) of the 94 studies highlighted societal and financial consequences of telehealth beyond the health system. Almost all studies (93/94, 99%) reported unintended consequences under the 5 dimensions of the Australian Health Performance Framework. Our synthesis offers a framework for understanding the unintended consequences of the use of telehealth as an alternative to in-person care in Australia. While we have documented many unintended benefits of telehealth use, our findings also shed light on many challenges of delivering care via telehealth across different domains and dimensions. These findings hold significant practice and policy-making implications for ensuring safe and high-quality care delivery via telehealth.

Is national healthcare performance associated with country-level characteristics, and if so what are the implications for international health policy? We compared Hofstede's six cultural dimensions against relative health systems performance of 35 countries. Hierarchical cluster analysis identified best-matched groupings of countries. Performance was measured by the Organisation for Economic Co-operation and Development's (OECD's) Health at a Glance indicators data framework (five dimensions with 57 indicators) and the United Nations' (UNs') Sustainability Development Goals (SDG) data set (15 indicators). Three country clusters emerged: Collective-Pyramidal (n = 9: comprising Slovak Republic, Mexico, Poland, Greece, Spain, Turkey, Portugal, Chile, and Slovenia); Collaborative-Networked (n = 12: UK, Canada, Australia, USA, Ireland, New Zealand, Netherlands, Finland, Iceland, Norway, Denmark, and Sweden); and Orderly-Future Orientated (n = 14: Korea, Estonia, Latvia, Austria, Israel, Japan, Czech Republic, Hungary, Italy, Belgium, France, Germany, Luxembourg and Switzerland). The Collaborative-Networked cluster had significantly better performing health systems measured by both the Health at a Glance and SDG performance data, followed by the Orderly-Future Orientated cluster, followed by the Collective-Pyramidal cluster. The Collaborative-Networked Cluster was characterized by low power distance (e.g., greater levels of equity), low uncertainty avoidance (e.g., toleration of others' opinions), individualism (e.g., self-reliance) and indulgence (e.g., drives and norms to enjoy life and have fun). National cultures are associated with healthcare performance on two key international measures. In national and international efforts to improve health system performance, cultural characteristics play an important role. This information may be of value to regulators, policymakers, researchers and clinicians examining the practical impact of culture on healthcare performance.

BackgroundThe study of safety culture and its relationship to patient care have been challenged by variation in definition, dimensionality and methods of assessment. This systematic review aimed to map methods to assess safety culture in hospitals, analyse the prevalence of these methods in the published research literature and examine the dimensions of safety culture captured through these processes.MethodsWe included studies reporting on quantitative, qualitative and mixed methods to assess safety culture in hospitals. The review was conducted using four academic databases (PubMed, CINAHL, Scopus and Web of Science) with studies from January 2008 to May 2020. A formal quality appraisal was not conducted. Study purpose, type of method and safety culture dimensions were extracted from all studies, coded thematically, and summarised narratively and using descriptive statistics where appropriate.ResultsA total of 694 studies were included. A third (n=244, 35.2%) had a descriptive or exploratory purpose, 225 (32.4%) tested relationships among variables, 129 (18.6%) evaluated an intervention, while 13.8% (n=96) had a methodological focus. Most studies exclusively used surveys (n=663; 95.5%), with 88 different surveys identified. Only 31 studies (4.5%) used qualitative or mixed methods. Thematic analysis identified 11 themes related to safety culture dimensions across the methods, with ‘Leadership’ being the most common. Qualitative and mixed methods approaches were more likely to identify additional dimensions of safety culture not covered by the 11 themes, including improvisation and contextual pressures.DiscussionWe assessed the extent to which safety culture dimensions mapped to specific quantitative and qualitative tools and methods of assessing safety culture. No single method or tool appeared to measure all 11 themes of safety culture. Risk of publication bias was high in this review. Future attempts to assess safety culture in hospitals should consider incorporating qualitative methods into survey studies to evaluate this multi-faceted construct.

Objective To identify barriers and facilitators associated with the sustainability of implemented and evaluated improvement programs in healthcare delivery systems. Data sources and study setting Six academic databases were searched to identify relevant peer-reviewed journal articles published in English between July 2011 and June 2022. Studies were included if they reported on healthcare program sustainability and explicitly identified barriers to, and facilitators of, sustainability. Study design A systematic integrative review guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. Study quality was appraised using Hawker’s Quality Assessment Tool. Data collection/extraction methods A team of reviewers screened eligible studies against the inclusion criteria and extracted the data independently using a purpose-designed Excel spreadsheet. Barriers and facilitators were extracted and mapped to the Integrated Sustainability Framework (ISF). Frequency counts of reported barriers/facilitators were performed across the included studies. Results Of the 124 studies included in this review, almost half utilised qualitative designs ( n  = 52; 41.9%) and roughly one third were conducted in the USA ( n  = 43; 34.7%). Few studies ( n  = 29; 23.4%) reported on program sustainability beyond 5 years of program implementation and only 16 of them (55.2%) defined sustainability. Factors related to the ISF categories of inner setting ( n  = 99; 79.8%), process ( n  = 99; 79.8%) and intervention characteristics ( n  = 72; 58.1%) were most frequently reported. Leadership/support ( n  = 61; 49.2%), training/support/supervision ( n  = 54; 43.5%) and staffing/turnover ( n  = 50; 40.3%) were commonly identified barriers or facilitators of sustainability across included studies. Forty-six (37.1%) studies reported on the outer setting category: funding ( n  = 26; 56.5%), external leadership by stakeholders ( n  = 16; 34.8%), and socio-political context ( n  = 14; 30.4%). Eight studies (6.5%) reported on discontinued programs, with factors including funding and resourcing, poor fit, limited planning, and intervention complexity contributing to discontinuation. Conclusions This review highlights the importance of taking into consideration the inner setting, processes, intervention characteristics and outer setting factors when sustaining healthcare programs, and the need for long-term program evaluations. There is a need to apply consistent definitions and implementation frameworks across studies to strengthen evidence in this area. Trial registration https://bmjopen.bmj.com/content/7/11/e018568 .

Health systems must solve two climate-related problems simultaneously: mitigate their greenhouse gas emissions and adapt to additional patient loads associated with climate-induced demands for care from weather sequalae and vector-borne diseases. We aimed to benchmark the mitigation and adaptive efforts of OECD member countries compared with their health system performance. We used Multidimensional Scaling and Hierarchical Cluster Analysis to group all 38 OECD member countries as at January 2024. Clusters were defined according to greenhouse gases per capita, vulnerability to climate change and the United Nations’ Human Development Index. Post hoc analyses compared each cluster’s performance to the OECD’s Health Care Quality Indicators. The countries fell into five profiles: Vulnerable low emitters; Vulnerable aspiring; Middle of the road; Robust aspiring; and Goldilocks zone. Post-hoc analyses revealed strong links between the profiles and health system performance. Characterising countries in a five-dimensional model may help policymakers to share benchmarked country-level information, devise ways to support resilient care practices, better target healthcare investments, and improve access to needed care.