scholarly journals Bayesian design and analysis of external pilot trials for complex interventions

2021 ◽  
Author(s):  
Duncan T. Wilson ◽  
James M. S. Wason ◽  
Julia Brown ◽  
Amanda J. Farrin ◽  
Rebecca E. A. Walwyn
Keyword(s):  
Complex Interventions ◽  
Bayesian Design ◽  
Pilot Trials

Pilot trials of hemicelluloses extraction prior to thermomechanical pulp production: Part 1

TAPPI Journal ◽  
2011 ◽  
Vol 10 (5) ◽  
pp. 21-28 ◽  
Author(s):  
CARL HOUTMAN ◽  
ERIC HORN
Keyword(s):  
Oxalic Acid ◽  
Energy Savings ◽  
Wood Chip ◽  
Strength Properties ◽  
Thermomechanical Pulp ◽  
Sugar Solution ◽  
Bisulfite Treatment ◽  
Pilot Trials ◽  
Pulp Production ◽  
Production Part

Pilot data indicate that wood chip pretreatment with oxalic acid reduced the specific energy required to make thermomechanical pulp. A combined oxalic acid/bisulfite treatment resulted in 21% refiner energy savings and 13% increase in brightness for aspen. A low level of oxalic acid treatment was effective for spruce. Energy savings of 30% was observed with no significant change in strength properties. Adding bisulfite did not significantly increase the brightness of the spruce pulp. For pine, the optimum treatment was a moderate level of oxalic acid, which resulted in 34% energy savings and an increase in strength properties. For all of these treatments 1–3 w/w % carbohydrates were recovered, which can be fermented to produce ethanol. The extract sugar solution contained significant quantities of arabinose.

A Local Linear Wavelet Neural Network Based on a Bayesian Design Method

2009 ◽  
Vol 129 (7) ◽  
pp. 1356-1362
Author(s):  
Kunikazu Kobayashi ◽  
Masanao Obayashi ◽  
Takashi Kuremoto
Keyword(s):  
Neural Network ◽  
Design Method ◽  
Wavelet Neural Network ◽  
Bayesian Design ◽  
Local Linear

scholarly journals What methods and challenges for taking account of context when transferring complex interventions?

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
S Villadsen ◽  
S Dias
Keyword(s):  
Public Health ◽  
Health Care ◽  
Reproductive Health ◽  
Health Care Providers ◽  
Complex Interventions ◽  
Health Interventions ◽  
Care Providers ◽  
Public Health Interventions ◽  
Reproductive Health Care

Abstract For complex public health interventions to be effective their implementation needs to adapt to the situation of those implementing and those receiving the intervention. While context matter for intervention implementation and effect, we still insist on learning from cross-country comparison of implementation. Next methodological challenges include how to increase learning from implementation of complex public health interventions from various context. The interventions presented in this workshop all aims to improve quality of reproductive health care for immigrants, however with different focus: contraceptive care in Sweden, group based antenatal care in France, and management of pregnancy complications in Denmark. What does these interventions have in common and are there cross cutting themes that help us to identify the larger challenges of reproductive health care for immigrant women in Europe? Issues shared across the interventions relate to improved interactional dynamics between women and the health care system, and theory around a woman-centered approach and cultural competence of health care providers and systems might enlighten shared learnings across the different interventions and context. Could the mechanisms of change be understood using theoretical underpinnings that allow us to better generalize the finding across context? What adaption would for example be needed, if the Swedish contraceptive intervention should work in a different European setting? Should we distinguish between adaption of function and form, where the latter might be less important for intervention fidelity? These issues will shortly be introduced during this presentation using insights from the three intervention presentations and thereafter we will open up for discussion with the audience.

scholarly journals Determining sample size for progression criteria for pragmatic pilot RCTs: the hypothesis test strikes back!

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
M. Lewis ◽  
K. Bromley ◽  
C. J. Sutton ◽  
G. McCray ◽  
H. L. Myers ◽  
...  
Keyword(s):  
Hypothesis Testing ◽  
Sample Size ◽  
Clinical Outcomes ◽  
Treatment Fidelity ◽  
Outcome Evaluation ◽  
Main Trial ◽  
Process Outcomes ◽  
Pilot Trials ◽  
Green Zone ◽  
Acceptable Outcome

Abstract Background The current CONSORT guidelines for reporting pilot trials do not recommend hypothesis testing of clinical outcomes on the basis that a pilot trial is under-powered to detect such differences and this is the aim of the main trial. It states that primary evaluation should focus on descriptive analysis of feasibility/process outcomes (e.g. recruitment, adherence, treatment fidelity). Whilst the argument for not testing clinical outcomes is justifiable, the same does not necessarily apply to feasibility/process outcomes, where differences may be large and detectable with small samples. Moreover, there remains much ambiguity around sample size for pilot trials. Methods Many pilot trials adopt a ‘traffic light’ system for evaluating progression to the main trial determined by a set of criteria set up a priori. We construct a hypothesis testing approach for binary feasibility outcomes focused around this system that tests against being in the RED zone (unacceptable outcome) based on an expectation of being in the GREEN zone (acceptable outcome) and choose the sample size to give high power to reject being in the RED zone if the GREEN zone holds true. Pilot point estimates falling in the RED zone will be statistically non-significant and in the GREEN zone will be significant; the AMBER zone designates potentially acceptable outcome and statistical tests may be significant or non-significant. Results For example, in relation to treatment fidelity, if we assume the upper boundary of the RED zone is 50% and the lower boundary of the GREEN zone is 75% (designating unacceptable and acceptable treatment fidelity, respectively), the sample size required for analysis given 90% power and one-sided 5% alpha would be around n = 34 (intervention group alone). Observed treatment fidelity in the range of 0–17 participants (0–50%) will fall into the RED zone and be statistically non-significant, 18–25 (51–74%) fall into AMBER and may or may not be significant and 26–34 (75–100%) fall into GREEN and will be significant indicating acceptable fidelity. Discussion In general, several key process outcomes are assessed for progression to a main trial; a composite approach would require appraising the rules of progression across all these outcomes. This methodology provides a formal framework for hypothesis testing and sample size indication around process outcome evaluation for pilot RCTs.

scholarly journals 32.K. Skills building seminar: Using participatory health research to optimise psycho-oncological patient information material

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
◽  
Keyword(s):  
Patient Information ◽  
Health Research ◽  
Service Providers ◽  
Complex Interventions ◽  
User Participation ◽  
End Users ◽  
Vulnerable Groups ◽  
Participatory Health Research ◽  
Practical Instrument

Abstract Patient information material (PIM) is omnipresent in healthcare. It is used to convey information or to familiarize potential end-users to offers of support. PIM recaps or elaborates on relevant information and offers recommendation for action. However, the quality of available PIM varies. When the formal and content-related quality of PIM is suboptimal, it not only fails to be effective but can also lead to uncertainty, misunderstandings, resistance or ignorance (e.g. of a support offer). Highly complex information requires much attention on the quality of the PIM, especially with respect to end-users (e.g. vulnerable groups). Excellent communication through the use of PIM is thus essential within complex interventions. Checklists, such as 'Discern' or 'PEMAT', as well as criteria catalogues or evidence-based patient information standards, may assist in the development, quality assessment and optimization of PIM. The inclusion of the end-users is recommended but for various reasons does not often take place. The innovative “integrated, cross-sectional Psycho-Oncology” (isPO) programme, offers needs-driven, professional support to all adult, newly diagnosed cancer patients early in their sickness trajectory. IsPO was developed in 2018. It was implemented and a formative evaluated in 2019. When developing this programme, different PIM were created top-down by the programme designers. During implementation, it became evident that these PIM materials required further improvement. A testing and optimization process started using the participatory health research (PHR) approach and was completed in a five-month period. A PIM-optimisation team was founded, which included the project partners involved in the network support, self-help organisations and the external evaluation institute. A practical instrument (PIM-checklist) for optimising the isPO-PIM was designed, piloted and used for testing by end-users, isPO service providers, and experts. Based on the recommendations in the checklist, the material was revised accordingly. Additionally, the PIM was completed with the design of two new components. Four optimisation rounds were conducted. The optimized PIM was tested on its comprehensibility (for end-users) and its usability (for service providers). During the presentations, the audience is invited to comment on critical questions that may appear during optimization (e.g. timing). Afterwards, there will be a skill building part with a focus on collaborative learning (45 minutes). First, we will focus on the requirements for a practical instrument that is handy for end-users, service providers and experts (mind mapping exercise). Finally, participants will be able to explore the following topics “World Café” discussion: (1) how to plan, conduct and communicate the development of optimization of PIM in a CI program, (2) what needs to be considered for the optimization (e.g. team composition, resources), and (3) how to continuously achieve end-userś participation. Key messages Excellent PIM are essential for a complex interventiońs success in practice and must include information and foster actionability. the iterative PIM design processes benefits from high user participation.

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