Determining sample size in a personalized randomized controlled (PRACTical) trial.

In clinical settings with no commonly accepted standard-of-care, multiple treatment regimens are potentially useful, but some treatments may not be appropriate for some patients. A personalized randomized controlled trial (PRACTical) design has been proposed for this setting. For a network of treatments, each patient is randomized only among treatments which are appropriate for them. The aim is to produce treatment rankings that can inform clinical decisions about treatment choices for individual patients. Here we propose methods for determining sample size in a PRACTical design, since standard power-based methods are not applicable. We derive a sample size by evaluating information gained from trials of varying sizes. For a binary outcome, we quantify how many adverse outcomes would be prevented by choosing the top-ranked treatment for each patient based on trial results rather than choosing a random treatment from the appropriate personalized randomization list. In simulations, we evaluate three performance measures: mean reduction in adverse outcomes using sample information, proportion of simulated patients for whom the top-ranked treatment performed as well or almost as well as the best appropriate treatment, and proportion of simulated trials in which the top-ranked treatment performed better than a randomly chosen treatment. We apply the methods to a trial evaluating eight different combination antibiotic regimens for neonatal sepsis (NeoSep1), in which a PRACTical design addresses varying patterns of antibiotic choice based on disease characteristics and resistance. Our proposed approach produces results that are more relevant to complex decision making by clinicians and policy makers.

Interview study exploring how global health partnership principles are enacted and recommendations for practice.

BACKGROUND: Effective global health partnerships can strengthen and improve health and healthcare systems across the world; however, establishing and maintaining effective partnerships can be challenging. Principles of Partnerships have been developed to improve the quality and effectiveness of health partnerships. It is unclear how principles are enacted in practice, and current research has not always included the voices of low-income and middle-income country partners. This study aimed to explore how The Tropical Health and Education Trust's nine Principles of Partnership are enacted in practice, from the points of view of partners from low-income, middle-income and high-income countries, to help improve partnerships' quality and sustainability. METHODS: People who had been a part of previous and/or ongoing health partnerships were interviewed virtually. Participants were purposefully sampled and interviews were conducted using an appreciative inquiry approach. Audio recordings were transcribed and deductive framework analysis was conducted. RESULTS: 13 participants from 8 partnerships were interviewed. Six participants were based in the low-income or middle-income countries and seven in the UK. Key findings identified strategies that enacted 'successful' and 'effective' partnerships within the Principles of Partnerships. These included practical techniques such as hiring a project manager, managing expectations and openly sharing information about the team's expertise and aspirations. Other strategies included the importance of consulting behavioural science to ensure the partnerships consider longevity and sustainability of the partnership. DISCUSSION: Core principles to effective partnerships do not work in isolation of each other; they are intertwined and are complimentary to support equitable partnerships. Good communication and relationships built on trust which allow all partners to contribute equally throughout the project are core foundations for sustainable partnerships. Recommendations for established and future partnerships include embedding behavioural scientists/psychologists to support change to improve the quality and sustainability of health partnerships.

Sharing information across patient subgroups to draw conclusions from sparse treatment networks.

Network meta-analysis (NMA) usually provides estimates of the relative effects with the highest possible precision. However, sparse networks with few available studies and limited direct evidence can arise, threatening the robustness and reliability of NMA estimates. In these cases, the limited amount of available information can hamper the formal evaluation of the underlying NMA assumptions of transitivity and consistency. In addition, NMA estimates from sparse networks are expected to be imprecise and possibly biased as they rely on large-sample approximations that are invalid in the absence of sufficient data. We propose a Bayesian framework that allows sharing of information between two networks that pertain to different population subgroups. Specifically, we use the results from a subgroup with a lot of direct evidence (a dense network) to construct informative priors for the relative effects in the target subgroup (a sparse network). This is a two-stage approach where at the first stage, we extrapolate the results of the dense network to those expected from the sparse network. This takes place by using a modified hierarchical NMA model where we add a location parameter that shifts the distribution of the relative effects to make them applicable to the target population. At the second stage, these extrapolated results are used as prior information for the sparse network. We illustrate our approach through a motivating example of psychiatric patients. Our approach results in more precise and robust estimates of the relative effects and can adequately inform clinical practice in presence of sparse networks.

Supported exercise TrAining for Men wIth prostate caNcer on Androgen deprivation therapy (STAMINA): study protocol for a randomised controlled trial of the clinical and cost-effectiveness of the STAMINA lifestyle intervention compared with optimised usual care, including internal pilot and parallel process evaluation.

BACKGROUND: UK national clinical guidance recommends that men with prostate cancer on androgen deprivation therapy are offered twice weekly supervised aerobic and resistance exercise to address iatrogenic harm caused by treatment. Very few NHS trusts have established adequate provision of such services. Furthermore, interventions fail to demonstrate sustained behaviour change. The STAMINA lifestyle intervention offers a system-level change to clinical care delivery addressing barriers to long-term behaviour change and implementation of new prostate cancer care pathways. This trial aims to establish whether STAMINA is clinically and cost-effective in improving cancer-specific quality of life and/or reducing fatigue compared to optimised usual care. The process evaluation aims to inform the interpretation of results and, if the intervention is shown to benefit patients, to inform the implementation of the intervention into the NHS. METHODS: Men with prostate cancer on androgen deprivation therapy (n = 697) will be identified from a minimum of 12 UK NHS trusts to participate in a multi-centre, two-arm, individually randomised controlled trial. Consenting men will have a 'safety to exercise' check and be randomly allocated (5:4) to the STAMINA lifestyle intervention (n = 384) or optimised usual care (n = 313). Outcomes will be collected at baseline, 3-, 6- and 12-month post-randomisation. The two primary outcomes are cancer-specific quality of life and fatigue. The parallel process evaluation will follow a mixed-methods approach to explore recruitment and aspects of the intervention including, reach, fidelity, acceptability, and implementation. An economic evaluation will estimate the cost-effectiveness of the STAMINA lifestyle intervention versus optimised usual care and a discrete choice experiment will explore patient preferences. DISCUSSION: The STAMINA lifestyle intervention has the potential to improve quality of life and reduce fatigue in men on androgen deprivation therapy for prostate cancer. Embedding supervised exercise into prostate cancer care may also support long-term positive behaviour change and reduce adverse events caused by treatment. Findings will inform future clinical care and could provide a blueprint for the integration of supervised exercise and behavioural support into other cancer and/or clinical services. TRIAL REGISTRATION: ISRCTN 46385239, registered on 30/07/2020. Cancer Research UK 17002, retrospectively registered on 24/08/2022.

A blueprint for a multi-disease, multi-domain Bayesian adaptive platform trial incorporating adult and paediatric subgroups: the Staphylococcus aureus Network Adaptive Platform trial.

The Staphylococcus aureus Network Adaptive Platform (SNAP) trial is a multifactorial Bayesian adaptive platform trial that aims to improve the way that S. aureus bloodstream infection, a globally common and severe infectious disease, is treated. In a world first, the SNAP trial will simultaneously investigate the effects of multiple intervention modalities within multiple groups of participants with different forms of S. aureus bloodstream infection. Here, we formalise the trial structure, modelling approach, and decision rules that will be used for the SNAP trial. By summarising the statistical principles governing the design, our hope is that the SNAP trial will serve as an adaptable template that can be used to improve comparative effectiveness research efficiency in other disease areas.Trial registration NCT05137119 . Registered on 30 November 2021.

Experiences of implementing the 'Making Every Contact Count' initiative into a UK integrated care system: an interview study.

BACKGROUND: The 'Making Every Contact Count' (MECC) approach is in line with the current National Health Service (NHS) strategy to improve and prevent health conditions in England. Despite its importance and value for preventative healthcare, implementation of MECC varies. The aim of this study was to explore the barriers and facilitators of implementing MECC and MECC training into an integrated care system (ICS). METHODS: Remote semi-structured interviews were conducted with staff across an ICS in the North West of England who were involved in implementing and delivering MECC across the region. Data were analysed initially using an inductive thematic analysis approach and then interpreted using the 'Capability, Opportunity, Motivation = Behaviour' (COM-B) model of behaviour change. RESULTS: We interviewed nine stakeholders and identified three superordinate themes: (1) macro-level barriers and facilitators, e.g. funding; (2) organizational level barriers and facilitators, e.g. time and resource; and (3) individual-level barriers/facilitators for both MECC trainers and MECC agents. CONCLUSIONS: MECC has potential to meet the needs of the public's health, but barriers to its implementation exist. MECC must be successfully embedded into organizations and regions in which it is implemented, which relies on further development of an appropriate infrastructure including sustainable funding and a shift in culture to value preventative healthcare.

Automated Video-Based Capture of Crustacean Fisheries Data Using Low-Power Hardware.

This work investigates the application of Computer Vision to the problem of the automated counting and measuring of crabs and lobsters onboard fishing boats. The aim is to provide catch count and measurement data for these key commercial crustacean species. This can provide vital input data for stock assessment models, to enable the sustainable management of these species. The hardware system is required to be low-cost, have low-power usage, be waterproof, available (given current chip shortages), and able to avoid over-heating. The selected hardware is based on a Raspberry Pi 3A+ contained in a custom waterproof housing. This hardware places challenging limitations on the options for processing the incoming video, with many popular deep learning frameworks (even light-weight versions) unable to load or run given the limited computational resources. The problem can be broken into several steps: (1) Identifying the portions of the video that contain each individual animal; (2) Selecting a set of representative frames for each animal, e.g, lobsters must be viewed from the top and underside; (3) Detecting the animal within the frame so that the image can be cropped to the region of interest; (4) Detecting keypoints on each animal; and (5) Inferring measurements from the keypoint data. In this work, we develop a pipeline that addresses these steps, including a key novel solution to frame selection in video streams that uses classification, temporal segmentation, smoothing techniques and frame quality estimation. The developed pipeline is able to operate on the target low-power hardware and the experiments show that, given sufficient training data, reasonable performance is achieved.

A new approach to evaluating loop inconsistency in network meta-analysis.

In network meta-analysis, studies evaluating multiple treatment comparisons are modeled simultaneously, and estimation is informed by a combination of direct and indirect evidence. Network meta-analysis relies on an assumption of consistency, meaning that direct and indirect evidence should agree for each treatment comparison. Here we propose new local and global tests for inconsistency and demonstrate their application to three example networks. Because inconsistency is a property of a loop of treatments in the network meta-analysis, we locate the local test in a loop. We define a model with one inconsistency parameter that can be interpreted as loop inconsistency. The model builds on the existing ideas of node-splitting and side-splitting in network meta-analysis. To provide a global test for inconsistency, we extend the model across multiple independent loops with one degree of freedom per loop. We develop a new algorithm for identifying independent loops within a network meta-analysis. Our proposed models handle treatments symmetrically, locate inconsistency in loops rather than in nodes or treatment comparisons, and are invariant to choice of reference treatment, making the results less dependent on model parameterization. For testing global inconsistency in network meta-analysis, our global model uses fewer degrees of freedom than the existing design-by-treatment interaction approach and has the potential to increase power. To illustrate our methods, we fit the models to three network meta-analyses varying in size and complexity. Local and global tests for inconsistency are performed and we demonstrate that the global model is invariant to choice of independent loops.

A qualitative interview study applying the COM-B model to explore how hospital-based trainers implement antimicrobial stewardship education and training in UK hospital-based care.

BACKGROUND: Antimicrobial resistance (AMR) is a major global health threat caused by the inappropriate use of antimicrobials in healthcare and other settings. Antimicrobial stewardship (AMS) is a broad multi-component health services intervention that promotes and monitors the judicious use of antimicrobials to preserve their future effectiveness. A main component of AMS is education and training (E&T). However, there are often discrepancies in how such interventions are implemented and delivered in hospital-based care. The aim of this study was to explore the factors influencing the implementation of AMS E&T in UK hospitals. METHODS: Semi-structured interviews were carried out with AMS E&T trainers in UK hospitals. The interview schedule was developed using the Capability, Opportunity, Motivation = Behaviour (COM-B) model. Participants were identified via professional networks and social media. Interviews were analysed using inductive thematic analysis, followed by deductive analysis using the COM-B model as a framework. RESULTS: A total of 34 participants (26 antimicrobial pharmacists, 3 nurses, 1 advanced clinical practitioner, 2 infectious disease consultants, 1 microbiologist and 1 clinical scientist). responsible for designing, implementing and evaluating AMS E&T in UK hospitals (five from Northern Ireland, four from Wales, two from Scotland and 23 from England) took part in virtual interviews. Key themes were: (1) The organisational context, including system-level barriers to AMS included competing organisational targets (Reflective motivation and physical opportunity) and the impact of the COVID-19 pandemic on activity (Physical opportunity); (2) Healthcare professionals' roles and the wider multi-disciplinary team, such that AMS roles were defined and addressed poorly in E&T (Social opportunity); and (3) The individual perception of the need for AMS E&T in hospital-based care, manifest in a perceived lack of conviction of the wider threat of AMR and the resulting need for AMS E&T (Reflective motivation). CONCLUSION: This study has identified factors influencing implementation of AMS E&T in UK hospitals and further identified where implemented, AMS E&T did not address real-world challenges. Current AMS E&T needs to be optimised to elicit practice change, with recommendations including training and engaging the wider work-force and drawing upon theoretically-informed intervention development frameworks to inform AMS E&T to better target AMS behaviour change.

"I was simply trying to make it through the day": A collaborative autoethnography of couple/marriage and family therapy program directors in a diversity and anti-racism peer consultation group.

The COVID-19 pandemic and widely depicted incidents of racial injustice in the United States caused marked stress and shifts in society in 2020, leading to an acceleration of discussions related to promoting diversity, equity, inclusion, and justice (DEIJ) in family-oriented mental health professions, including through training. Despite the consequential role leaders of academic programs play in overseeing didactic and clinical training, little research has examined approaches for supporting academic leaders in promoting DEIJ in family science-related academic training programs. In this collaborative autoethnography, we, six participants in a diversity and anti-racism peer consultation group for leaders of couple/marriage and family therapy (C/MFT) programs, present our experiences participating in the group over the past two years. At the start of the group, many of us were experiencing profound isolation and stress due to intensified responsibilities subsequent to the COVID-19 pandemic and broadcast depictions of racial injustice. We experienced the group as a safe, inclusive space to grow personally and professionally, which subsequently inspired us to make changes in our programs. We also recognized the need for greater infrastructure to support program directors in developing DEIJ leadership skills. Future directions for research include examining experiences and outcomes of director-initiated DEIJ change, as well examination of DEIJ-focused peer consultation groups among family systems-oriented academic leaders of diverse disciplines and nations.

Historical plant introductions predict current insect invasions.

Thousands of insect species have been introduced outside of their native ranges, and some of them strongly impact ecosystems and human societies. Because a large fraction of insects feed on or are associated with plants, nonnative plants provide habitat and resources for invading insects, thereby facilitating their establishment. Furthermore, plant imports represent one of the main pathways for accidental nonnative insect introductions. Here, we tested the hypothesis that plant invasions precede and promote insect invasions. We found that geographical variation in current nonnative insect flows was best explained by nonnative plant flows dating back to 1900 rather than by more recent plant flows. Interestingly, nonnative plant flows were a better predictor of insect invasions than potentially confounding socioeconomic variables. Based on the observed time lag between plant and insect invasions, we estimated that the global insect invasion debt consists of 3,442 region-level introductions, representing a potential increase of 35% of insect invasions. This debt was most important in the Afrotropics, the Neotropics, and Indomalaya, where we expect a 10 to 20-fold increase in discoveries of new nonnative insect species. Overall, our results highlight the strong link between plant and insect invasions and show that limiting the spread of nonnative plants might be key to preventing future invasions of both plants and insects.

An interview study to explore applied psychologists' experiences of implementing health psychology in global health partnerships: The Change Exchange.

INTRODUCTION: Health partnerships in global health aim to build capacity by strengthening training and education. Health psychology has an important role to play, as traditionally health partnerships focus upon increasing capability such as increasing knowledge but do not tackle opportunity and motivation. The Change Exchange recruits applied psychologist volunteers to utilize health psychology in global health partnerships, which is a novel approach. This study aimed to understand the experiences of applied psychologist volunteers working in health partnerships and how such interventions were implemented. METHODS: Semi-structured interviews were carried out. Interviews were analysed using inductive thematic analysis to explore the translation and implementation of health psychology in health partnerships. A deductive approach was then taken using the higher level constructs of the Normalization Process Theory to inform and interpret the themes into recommendations. RESULTS: Fifteen applied psychologists, all of whom were from the UK and had volunteered in health partnerships between the UK and low- to middle-income countries participated. Key themes and sub-themes were identified: (1) The challenges of the application of behavioural science within the health partnerships, (2) Building relationships within the health partnership, (3) Exploring the communal and individual effort carried out within the health partnership and (4) Reflecting on the work carried out within the health partnership. DISCUSSION: Barriers exist in regards to the implementation of health psychology in health partnerships but capacity building is possible. Recommendations suggest, future work should establish clear roles for applied psychologists in health partnerships and critical evaluation of current psychological models, methods and measures for use outside of Western, Educated, Industrialized, Rich and Democratic societies.

The Cognitive Daisy (COG-D) for improving care for residents with dementia in care homes: protocol of a feasibility RCT.

BACKGROUND: Cognitive problems associated with dementia affect a large proportion of older adults living in residential care. Knowledge of cognitive impairments is important for providing person-centred care (PCC). The impact of specific cognitive impairments on residents' needs is often overlooked in dementia training and information about residents' individual cognitive profiles are frequently underspecified in care-plans, potentially undermining the delivery of PCC. This can lead to reduced resident quality of life and increased distressed behaviours-a major cause of staff stress and burnout. The COG-D package was developed to fill this gap. Daisies provide a visual representation of a resident's individual cognitive strengths and weaknesses in a colourful flower (Daisy) representing five cognitive domains. By viewing a resident's Daisy, care-staff can flexibly adjust in-the-moment care-decisions and can consult Daisies in care-plans for longer-term planning. The primary aim of this study is to assess the feasibility of implementing the COG-D package in residential care homes for older adults. METHODS/DESIGN: This 24-month feasibility cluster randomized controlled trial involves a 6-month intervention of the use of Cognitive Daisies in 8-10 residential care homes for older adults after training of care staff on the use of Cognitive Daisies in daily care (basic training) and on conducting the COG-D assessments with residents (advanced training). The key feasibility outcomes include % residents recruited, % COG-D assessments completed, and % staff completing the training. Candidate outcome measures for residents and staff will be obtained at baseline, and at 6 and 9 months post-randomization. COG-D assessments of residents will be repeated 6 months after the first assessment. A process evaluation will assess intervention implementation and barriers and facilitators to this through care-plan audits, interviews and focus groups with staff, residents, and relatives. Feasibility outcomes will be analysed against progression criteria to a full trial. DISCUSSION: The results of this study will provide important information about the feasibility of using COG-D in care homes and will inform the design of a future large-scale cluster RCT to assess the effectiveness and cost-effectiveness of the COG-D intervention in care homes. TRIAL REGISTRATION: This trial was registered on 28/09/2022 (ISRCTN15208844) and is currently open to recruitment.

The Personalised Randomized Controlled Trial: Evaluation of a new trial design.

In some clinical scenarios, for example, severe sepsis caused by extensively drug resistant bacteria, there is uncertainty between many common treatments, but a conventional multiarm randomized trial is not possible because individual participants may not be eligible to receive certain treatments. The Personalised Randomized Controlled Trial design allows each participant to be randomized between a "personalised randomization list" of treatments that are suitable for them. The primary aim is to produce treatment rankings that can guide choice of treatment, rather than focusing on the estimates of relative treatment effects. Here we use simulation to assess several novel analysis approaches for this innovative trial design. One of the approaches is like a network meta-analysis, where participants with the same personalised randomization list are like a trial, and both direct and indirect evidence are used. We evaluate this proposed analysis and compare it with analyses making less use of indirect evidence. We also propose new performance measures including the expected improvement in outcome if the trial's rankings are used to inform future treatment rather than random choice. We conclude that analysis of a personalized randomized controlled trial can be performed by pooling data from different types of participants and is robust to moderate subgroup-by-intervention interactions based on the parameters of our simulation. The proposed approach performs well with respect to estimation bias and coverage. It provides an overall treatment ranking list with reasonable precision, and is likely to improve outcome on average if used to determine intervention policies and guide individual clinical decisions.

Practical approaches to Bayesian sample size determination in non-inferiority trials with binary outcomes.

Bayesian analysis of a non-inferiority trial is advantageous in allowing direct probability statements to be made about the relative treatment difference rather than relying on an arbitrary and often poorly justified non-inferiority margin. When the primary analysis will be Bayesian, a Bayesian approach to sample size determination will often be appropriate for consistency with the analysis. We demonstrate three Bayesian approaches to choosing sample size for non-inferiority trials with binary outcomes and review their advantages and disadvantages. First, we present a predictive power approach for determining sample size using the probability that the trial will produce a convincing result in the final analysis. Next, we determine sample size by considering the expected posterior probability of non-inferiority in the trial. Finally, we demonstrate a precision-based approach. We apply these methods to a non-inferiority trial in antiretroviral therapy for treatment of HIV-infected children. A predictive power approach would be most accessible in practical settings, because it is analogous to the standard frequentist approach. Sample sizes are larger than with frequentist calculations unless an informative analysis prior is specified, because appropriate allowance is made for uncertainty in the assumed design parameters, ignored in frequentist calculations. An expected posterior probability approach will lead to a smaller sample size and is appropriate when the focus is on estimating posterior probability rather than on testing. A precision-based approach would be useful when sample size is restricted by limits on recruitment or costs, but it would be difficult to decide on sample size using this approach alone.

Alien insect dispersal mediated by the global movement of commodities.

Globalization and economic growth are recognized as key drivers of biological invasions. Alien species have become a feature of almost every biological community worldwide, and rates of new introductions continue to rise as the movement of people and goods accelerates. Insects are among the most numerous and problematic alien organisms, and are mainly introduced unintentionally with imported cargo or arriving passengers. However, the processes occurring prior to insect introductions remain poorly understood. We used a unique dataset of 1,902,392 border interception records from inspections at air, land, and maritime ports in Australia, New Zealand, Europe, Japan, USA, and Canada to identify key commodities associated with insect movement through trade and travel. In total, 8939 species were intercepted, and commodity association data were available for 1242 species recorded between 1960 and 2019. We used rarefaction and extrapolation methods to estimate the total species richness and diversity associated with different commodity types. Plant and wood products were the main commodities associated with insect movement across cargo, passenger baggage, and international mail. Furthermore, certain species were mainly associated with specific commodities within these, and other broad categories. More closely related species tended to share similar commodity associations, but this occurred largely at the genus level rather than within orders or families. These similarities within genera can potentially inform pathway management of new alien species. Combining interception records across regions provides a unique window into the unintentional movement of insects, and provides valuable information on establishment risks associated with different commodity types and pathways.