Intervention Optimization: A Paradigm Shift and Its Potential Implications for Clinical Psychology.

To build a coherent knowledge base about what psychological intervention strategies work, develop interventions that have positive societal impact, and maintain and increase this impact over time, it is necessary to replace the classical treatment package research paradigm. The multiphase optimization strategy (MOST) is an alternative paradigm that integrates ideas from behavioral science, engineering, implementation science, economics, and decision science. MOST enables optimization of interventions to strategically balance effectiveness, affordability, scalability, and efficiency. In this review we provide an overview of MOST, discuss several experimental designs that can be used in intervention optimization, consider how the investigator can use experimental results to select components for inclusion in the optimized intervention, discuss the application of MOST in implementation science, and list future issues in this rapidly evolving field. We highlight the feasibility of adopting this new research paradigm as well as its potential to hasten the progress of psychological intervention science.

Soil water and nutrient availability interactively modify pollinator-mediated directional and correlational selection on floral display.

The individual and combined effects of abiotic factors on pollinator-mediated selection on floral traits are not well documented. To examine potential interactive effects of water and nutrient availability on pollinator-mediated selection on three floral display traits of Primula tibetica, we manipulated pollination and nutrient availability in a factorial experiment, conducted at two common garden sites with different soil water content (natural vs addition). We found that both water and nutrient availability affected floral trait expression in P. tibetica and that hand pollination increased seed production most when both nutrient content and water content were high, indicating joint pollen and resource limitation. We documented selection on all floral traits, and pollinators contributed to directional and correlational selection on plant height and number of flowers. Soil water and nutrient availability interactively influenced the strength of both pollinator-mediated directional and correlational selection, with significant selection observed when nutrient or water availability was high, but not when none or both were added. The results suggest that resource limitation constrains the response of P. tibetica to among-individual variation in pollen receipt, that addition of nutrients or water leads to pollinator-mediated selection and that effects of the two abiotic factors are nonadditive.

Optimising engagement in a digital parenting intervention to prevent violence against adolescents in Tanzania: protocol for a cluster randomised factorial trial.

BACKGROUND: Violence against adolescents is a universal reality, with severe individual and societal costs. There is a critical need for scalable and effective violence prevention strategies such as parenting programmes, particularly in low- and middle-income countries where rates of maltreatment are highest. Digital interventions may be a scalable and cost-effective alternative to in-person delivery, yet maximising caregiver engagement is a substantial challenge. This trial employs a cluster randomised factorial experiment and a novel mixed-methods analytic approach to assess the effectiveness, cost-effectiveness, and feasibility of intervention components designed to optimise engagement in an open-source parenting app, ParentApp for Teens. The app is based on the evidence-based Parenting for Lifelong Health for Teens programme, developed collaboratively by academic institutions in the Global South and North, the WHO, and UNICEF. METHODS/DESIGN: Sixteen neighbourhoods, i.e., clusters, will be randomised to one of eight experimental conditions which consist of any combination of three components (Support: self-guided/moderated WhatsApp groups; App Design: sequential workshops/non-sequential modules; Digital Literacy Training: on/off). The study will be conducted in low-income communities in Tanzania, targeting socioeconomically vulnerable caregivers of adolescents aged 10 to 17 years (16 clusters, 8 conditions, 640 caregivers, 80 per condition). The primary objective of this trial is to estimate the main effects of the three components on engagement. Secondary objectives are to explore the interactions between components, the effects of the components on caregiver behavioural outcomes, moderators and mediators of programme engagement and impact, and the cost-effectiveness of components. The study will also assess enablers and barriers to engagement qualitatively via interviews with a subset of low, medium, and high engaging participants. We will combine quantitative and qualitative data to develop an optimised ParentApp for Teens delivery package. DISCUSSION: This is the first known cluster randomised factorial trial for the optimisation of engagement in a digital parenting intervention in a low- and middle-income country. Findings will be used to inform the evaluation of the optimised app in a subsequent randomised controlled trial. TRIAL REGISTRATION: Pan African Clinical Trial Registry, PACTR202210657553944. Registered 11 October 2022, https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=24051 .

A factorial experiment grounded in the multiphase optimization strategy to promote viral suppression among people who inject drugs on the Texas-Mexico border: a study protocol.

BACKGROUND: People who inject drugs living with HIV (PWIDLH) suffer the lowest rates of HIV viral suppression due to episodic injection drug use and poor mental health coupled with poor retention in HIV care. Approximately 44% of PWIDLH along the US-Mexico border are retained in care and only 24% are virally suppressed. This underserved region faces a potential explosion of transmission of HIV due to highly prevalent injection drug use. This protocol describes an optimization trial to promote sustained viral suppression among Spanish-speaking Latinx PWIDLH. METHODS: The multiphase optimization strategy (MOST) is an engineering-inspired framework for designing and building optimized interventions and guides this intervention. The primary aim is to conduct a 24 factorial experiment in which participants are randomized to one of 16 intervention conditions, with each condition comprising a different combination of four behavioral intervention components. The components are peer support for methadone uptake and persistence; behavioral activation therapy for depression; Life-Steps medication adherence counseling; and patient navigation for HIV care. Participants will complete a baseline survey, undergo intervention, and then return for 3-,6-,9-, and 12-month follow-up assessments. The primary outcome is sustained viral suppression, defined as viral loads of < 40 copies per mL at 6-,9-, and 12-month follow-up assessments. Results will yield effect sizes for each component and each additive and interactive combination of components. The research team and partners will make decisions about what constitutes the optimized multi-component intervention by judging the observed effect sizes, interactions, and statistical significance against real-world implementation constraints. The secondary aims are to test mediators and moderators of the component-to-outcome relationship at the 6-month follow-up assessment. DISCUSSION: We are testing well-studied and available intervention components to support PWIDLH to reduce drug use and improve their mental health and engagement in HIV care. The intervention design will allow for a better understanding of how these components work in combination and can be optimized for the setting. TRIAL REGISTRATION: This project was registered at clinicaltrials.gov (NCT05377463) on May 17th, 2022.

LIBERTI: A SMART study in plastic surgery.

BACKGROUND/AIMS: Laser treatment of burns scars is considered by some providers to be standard of care. However, there is little evidence-based research as to the true benefit. A number of factors hinder evaluation of the benefit of laser treatment. These include significant heterogeneity in patient response and possible delayed effects from the laser treatment. Moreover, laser treatments are often provided sequentially using different types of equipment and settings, so there are effectively a large number of overall treatment options that need to be compared. We propose a trial capable of coping with these issues and that also attempts to take advantage of the heterogeneous response in order to estimate optimal treatment plans personalized to each individual patient. It will be the first large-scale randomized trial to compare the effectiveness of laser treatments for burns scars and, to our knowledge, the very first example of the utility of a Sequential Multiple Assignment Randomized Trial in plastic surgery. METHODS: We propose using a Sequential Multiple Assignment Randomized Trial design to investigate the effect of various permutations of laser treatment on hypertrophic burn scars. We will compare and test hypotheses regarding laser treatment effects at a general population level. Simultaneously, we hope to use the data generated to discover possible beneficial personalized treatment plans, tailored to individual patient characteristics. RESULTS: We show that the proposed trial has good power to detect laser treatment effect at the overall population level, despite comparing a large number of treatment combinations. The trial will simultaneously provide high-quality data appropriate for estimating precision-medicine treatment rules. We detail population-level comparisons of interest and corresponding sample size calculations. We provide simulations to suggest the power of the trial to detect laser effect and also the possible benefits of personalization of laser treatment to individual characteristics. CONCLUSION: We propose, to our knowledge, the first use of a Sequential Multiple Assignment Randomized Trial in surgery. The trial is rigorously designed so that it is reasonably straightforward to implement and powered to answer general overall questions of interest. The trial is also designed to provide data that are suitable for the estimation of beneficial precision-medicine treatment rules that depend both on individual patient characteristics and on-going real-time patient response to treatment.

Food provisioning alters infection dynamics in populations of a wild rodent.

While pathogens are often assumed to limit the growth of wildlife populations, experimental evidence for their effects is rare. A lack of food resources has been suggested to enhance the negative effects of pathogen infection on host populations, but this theory has received little investigation. We conducted a replicated two-factor enclosure experiment, with introduction of the bacterium Bordetella bronchiseptica and food supplementation, to evaluate the individual and interactive effects of pathogen infection and food availability on vole populations during a boreal winter. We show that prior to bacteria introduction, vole populations were limited by food availability. Bordetella bronchiseptica introduction then reduced population growth and abundance, but contrary to predictions, primarily in food supplemented populations. Infection prevalence and pathological changes in vole lungs were most common in food supplemented populations, and are likely to have resulted from increased congregation and bacteria transmission around feeding stations. Bordetella bronchiseptica-infected lungs often showed protozoan co-infection (consistent with Hepatozoon erhardovae), together with more severe inflammatory changes. Using a multidisciplinary approach, this study demonstrates a complex picture of interactions and underlying mechanisms, leading to population-level effects. Our results highlight the potential for food provisioning to markedly influence disease processes in wildlife mammal populations.

Determining Relative Importance and Effective Settings for Genetic Algorithm Control Parameters.

Setting the control parameters of a genetic algorithm to obtain good results is a long-standing problem. We define an experiment design and analysis method to determine relative importance and effective settings for control parameters of any evolutionary algorithm, and we apply this method to a classic binary-encoded genetic algorithm (GA). Subsequently, as reported elsewhere, we applied the GA, with the control parameter settings determined here, to steer a population of cloud-computing simulators toward behaviors that reveal degraded performance and system collapse. GA-steered simulators could serve as a design tool, empowering system engineers to identify and mitigate low-probability, costly failure scenarios. In the existing GA literature, we uncovered conflicting opinions and evidence regarding key GA control parameters and effective settings to adopt. Consequently, we designed and executed an experiment to determine relative importance and effective settings for seven GA control parameters, when applied across a set of numerical optimization problems drawn from the literature. This paper describes our experiment design, analysis, and results. We found that crossover most significantly influenced GA success, followed by mutation rate and population size and then by rerandomization point and elite selection. Selection method and the precision used within the chromosome to represent numerical values had least influence. Our findings are robust over 60 numerical optimization problems.

Investigating the added effects of guidance in digital psychological self-care for alcohol problems (ALVA)-protocol for a randomized factorial optimization trial.

BACKGROUND: The continual development and implementation of effective digital interventions is one important strategy that may serve to bridge the well-known treatment gap related to problematic alcohol use. Research suggests that clinician guidance, provided in different ways during the digital intervention (i.e., written weekly messages, phone calls etc.), can boost intervention engagement and effects. Digital psychological self-care (DPSC) is a new delivery format wherein an unguided digital intervention is provided within the framework of a structured care process that includes initial clinical assessment and follow-up interviews. In a recent feasibility study, a DPSC intervention for problematic alcohol use, ALVA, provided without any extra guidance, was found safe and credible and to have promising within-group effects on alcohol consumption. The aim of the current study is to gather information on the effects and efficiency of different forms of guidance added to ALVA, in order to optimize the intervention. METHODS: This protocol describes a randomized factorial trial where the effects of two different ways of providing guidance (mid-treatment interview, weekly written messages, respectively) in DPSC for problematic alcohol use are investigated. Optimization criteria will be applied to the results regarding how effective the intervention is at reducing alcohol consumption measured by the number of standard drinks per week together with the clinician time spent on guidance. DISCUSSION: This study will investigate the added benefit of different forms of guidance to DPSC for problematic alcohol use. These added effects will be compared to the added cost of guidance, according to pre-defined optimization criteria. TRIAL REGISTRATION: Clinicaltrials.gov: NCT05649982. Registered on 06 December 2022. Prospectively registered.

Optimizing milling parameters based on full factorial experiment and backpropagation artificial neural network of lamina milling temperature prediction model.

BACKGROUND: Milling operations of laminae in spinal surgery generate high temperatures, which can lead to thermal injury and osteonecrosis and affect the biomechanical effects of implants, ultimately leading to surgical failure. OBJECTIVE: In this paper, a backpropagation artificial neural network (Bp-ANN) temperature prediction model was developed based on full factorial experimental data of laminae milling to optimize the milling motion parameters and to improve the safety of robot-assisted spine surgery. METHODS: A full factorial experiment design were used to analyze the parameters affecting the milling temperature of laminae. The experimental matrixes were established by collecting the corresponding cutter temperature Tc and bone surface temperature Tb for the milling depth, feed speed and different bone densities. The Bp-ANN lamina milling temperature prediction model was constructed from experiment data. RESULTS: Increasing milling depth increases bone surface and cutter temperature. Increasing feed speed had little effect on cutter temperature, but decreased bone surface temperature. Increasing bone density of laminae increased cutter temperature. The Bp-ANN temperature prediction model had best training results in the 10th epoch, and there is no overfitting (training set R= 0.99661, validation set R= 0.85003, testing set R= 0.90421, all temperature data set R= 0.93807). The goodness of fit R of Bp-ANN was close to 1, indicating that the predicted temperature was in good agreement with the experiment measurements. CONCLUSION: This study can help spinal surgery-assisted robot to select appropriate motion parameters at different density bones to improve lamina milling safety.

Optimizing UVC-LED application to improve the shelf life of vacuum-packed refrigerated stored Nile tilapia (Oreochromis niloticus) fillets.

Although ultraviolet-C light-emitting diode (UVC-LED) has proven antimicrobial effectiveness doses needed to reach it cause adverse effects on the physicochemical quality of fish, and thus, optimization studies are crucial to boost its industrial application. This study aimed to identify optimal UVC-LED conditions for maximum shelf life extension with the least possible quality changes of refrigerated stored tilapia fillets from a central composite rotatable design (CCRD). UVC-LED powers (1, 1.38, and 1.58 mW/cm2 ) and times (500, 1800, and 2700 s) were set on the CCRD, which generated 11 treatments, including three replicate experiments. Treatments were analyzed for total aerobic psychrotrophic count, lipid oxidation, instrumental color, and texture parameters on days 0, 2, 4, 7, 11, and 14. The UVC-LED affected shelf life and physicochemical parameters in a nonlinear fashion. UVC-LED-treated fish had increased shelf life by 2.80-4.76 days and increase or decrease in lipid oxidation (0.025-0.276 mg of malondialdehyde [MDA]/kg), total color change (∆E = 3.47-9.06), and hardness (1.31-8.51 N) over the refrigerated storage depending on specific UVC-LED conditions applied. The optimal UVC-LED condition was 0.97 mW/cm2 with 2503.6 s (2428.50 mJ/cm2 ), which increased the fillet's shelf life by 2.5-fold (2 days) while maintaining quality closer to the original throughout refrigerated storage, resulting in ∆E < 5, an increase of only 0.05 mg of MDA/kg, and preservation of the decrease in hardness by 3.38 N compared to its control counterparts. Therefore, it represents an eco-friendly technology that can easily scaled industrially to enhance the sustainable fish production chain. PRACTICAL APPLICATION: The high fish perishability is a global concern due to food safety risks and waste generation impacting the environment adversely, especially nowadays, where fish production and consumption have increased, and there are more evident efforts to sustainable production. UVC-LED is an eco-friendly technology with proven antimicrobial effectiveness but doses needed to reach this effect enhance oxidative degradation. Despite that, optimization studies concerning the maximum shelf life extension while retaining the physicochemical quality of refrigerated stored fish are a gap in the literature and a barrier to its industrial application. Our findings are helpful in sustainably enhancing the fish production chain.

Water status dynamics and drought tolerance of juvenile European beech, Douglas fir and Norway spruce trees as dependent on neighborhood and nitrogen supply.

To increase the resilience of forests to drought and other hazards, foresters are increasingly planting mixed stands. This requires knowledge about the drought response of tree species in pure and mixed-culture neighborhoods. In addition, drought frequently interacts with continued atmospheric nitrogen (N) deposition. To disentangle these factors for European beech, Norway spruce and Douglas fir, we conducted a replicated 3-factorial sapling growth experiment with three moisture levels, (high, medium, and low), two N levels (high and ambient), and pure and mixed-culture neighborhoods. We measured biomass, stomatal conductance (GS), shoot water potential (at predawn: ΨPD, midday, and turgor loss point: ΨTLP), branch xylem embolism resistance (Ψ50) and minimum epidermal conductance (Gmin). The three species differed most with respect to Gmin (10-fold higher in beech than in the conifers), hydroscape area (larger in beech), and the time elapsed to reach stomatal closure (TΨGS90) and ΨTLP (TTLP; shorter in beech), while Ψ50 and ΨTLP were remarkably similar. Neighborhood (pure vs mixed-culture) influenced biomass production, water status and hydraulic traits, notably GS (higher in Douglas fir, but lower in spruce and beech, in mixtures than pure culture), hydraulic safety margin (smaller for beech in mixtures), and TΨGS90 and TTLP (shorter for spruce in mixture). High N generally increased GS, but no consistent N effects on leaf water status and hydraulic traits were detected, suggesting that neighbor identity had a larger effect on plant water relations than N availability. We conclude that both tree neighborhood and N availability modulate the drought response of beech, spruce, and Douglas fir. Species mixing can alleviate the drought stress of some species, but often by disadvantaging other species. Thus, our study suggests that stabilizing and building resilience of production forests against a drier and warmer climate may depend primarily on the right species choice; species mixing can support the agenda.

Modeling of the Efficiency of the Centrifugal Conical Disk Dispenser of Bulk Materials.

Centrifugal disk dispensers are widely used in various tasks of dosing bulk, dispersed materials. The design of the disk depends on the physical and mechanical characteristics of the dosing medium. The work discusses the development of an analytical model of the movement of a material particle along a conical centrifugal disk depending on the kinematic characteristics of the dosing process and the characteristics of the dosing material, as well as experimental confirmation of the theoretical model, which is relevant for the calculation and design of working elements of this type. The obtained system of differential equations is solved using the Runge-Kutta numerical method. Experimental studies were carried out using the method of a planned factorial experiment. The experiment was conducted for three factors at three levels. The feedback criterion was the performance of a centrifugal conical disk dispenser for bulk materials. The disk cone angle was set at 10, 20, and 30°. The disk diameter was 130, 150, and 170 mm, the gap between the disk and the edge of the hopper neck was 6, 8, and 10 mm, and the rotational speed of the conical disk was 0.65, 1.02, and 1.39 rad/s. The dispensing rate of the dispenser ranged from 15 to 770 g/s, depending on the values of the experimental factors. For use in the regression equation of the natural values of the factors, a method of transforming the terms of the equation from coded values to natural ones is provided. The obtained experimental correlation dependencies were checked for reproducibility with Cochrane's test, and the adequacy of the model was checked using Fisher's test. The significance of the coefficients in the correlation equation was evaluated using the Student's t-test. The difference between the experimental data and the results of the theoretical modeling does not exceed 5%. The obtained system of differential equations makes it possible to model the radial velocity of the ascent of bulk material from the conical rotating disk depending on the rotation frequency, disk diameter, and the height of the annular gap between the discharge throat of the hopper and the conical disk. The analytical model enables the modeling of the productivity of the conical dispenser for bulk materials for arbitrary parameters of rotation frequency, disk diameter, and the size of the annular gap between the discharge throat of the hopper and the conical disk.

What to do after smoking relapse? A sequential multiple assignment randomized trial of chronic care smoking treatments.

AIM: To compare effects of three post-relapse interventions on smoking abstinence. DESIGN: Sequential three-phase multiple assignment randomized trial (SMART). SETTING: Eighteen Wisconsin, USA, primary care clinics. PARTICIPANTS: A total of 1154 primary care patients (53.6% women, 81.2% White) interested in quitting smoking enrolled from 2015 to 2019; 582 relapsed and were randomized to relapse recovery treatment. INTERVENTIONS: In phase 1, patients received cessation counseling and 8 weeks nicotine patch. Those who relapsed and agreed were randomized to a phase 2 relapse recovery group: (1) reduction counseling + nicotine mini-lozenges + encouragement to quit starting 1 month post-randomization (preparation); (2) repeated encouragement to quit starting immediately post-randomization (recycling); or (3) advice to call the tobacco quitline (control). The first two groups could opt into phase 3 new quit treatment [8 weeks nicotine patch + mini-lozenges plus randomization to two treatment factors (skill training and supportive counseling) in a 2 × 2 design]. Phase 2 and 3 interventions lasted ≤ 15 months. MEASUREMENTS: The study was powered to compare each active phase 2 treatment with the control on the primary outcome: biochemically confirmed 7-day point-prevalence abstinence 14 months post initiating phase 2 relapse recovery treatment. Exploratory analyses tested for phase 3 counseling factor effects. FINDINGS: Neither skill training nor supportive counseling (each on versus off) increased 14-month abstinence rates; skills on versus off 9.3% (14/151) versus 5.2% (8/153), P = 0.19; support on versus off 6.6% (10/152) versus 7.9% (12/152), P = 0.73. Phase 2 preparation did not produce higher 14-month abstinence rates than quitline referral; 3.6% (8/220) versus 2.1% [3/145; risk difference = 1.5%, 95% confidence interval (CI) = -1.8-5.0%, odds ratio (OR) = 1.8, 95% CI = 0.5-6.9]. Recycling, however, produced higher abstinence rates than quitline referral; 6.9% (15/217) versus 2.1% (three of 145; risk difference, 4.8%, 95% CI = 0.7-8.9%, OR = 3.5, 95% CI = 1.0-12.4). Recycling produced greater entry into new quit treatment than preparation: 83.4% (181/217) versus 55.9% (123/220), P < 0.0001. CONCLUSIONS: Among people interested in quitting smoking, immediate encouragement post-relapse to enter a new round of smoking cessation treatment ('recycling') produced higher probability of abstinence than tobacco quitline referral. Recycling produced higher rates of cessation treatment re-engagement than did preparation/cutting down using more intensive counseling and pharmacotherapy.

Using Behavioral Insights to Market a Workplace Safety Program: Evidence From a Multi-Armed Experiment.

This paper describes how a multi-armed randomized experiment was used to test multiple variants of a behaviorally informed marketing strategy. In particular, we tested whether specific behavioral messages could be used to increase demand for a safety consultation service offered by the U.S. Occupational Safety and Health Administration. Our experiment used a partial factorial design with 19 study arms and a very large research sample-97,182 establishments-to test the impact of various message, formats, and delivery modes compared with an existing (not behaviorally informed) informational brochure and a no-marketing counterfactual. A secondary research goal was to predict the impact of the most successful marketing strategy (i.e., combination of message, format, and mode) so that OSHA would know what to anticipate if that strategy were implemented at scale. We used two related (but distinct) methods to address these two goals. Both begin with a common mixed (i.e., fixed and random effects) ANOVA model. We addressed the first research goal primarily from the fixed effects; we addressed the second research goal by calculating best linear unbiased predictions (BLUPs) from the full mixed model, where the BLUP involves "shrinkage" as in empirical Bayes (EB) approaches. Marketing via brochures was effective overall, nearly doubling the rate of requests for services. However, the behaviorally informed materials performed no better than OSHA's existing informational brochure. This study also highlights the conditions under which a factorial design can be used to efficiently address questions about which of several program variants are most effective.

The detection and management of attempted fraud during an online randomised trial.

BACKGROUND: Online studies offer an efficient method of recruiting participants and collecting data. Whilst delivering an online randomised trial, we detected unusual recruitment activity. We describe our approach to detecting and managing suspected fraud and share lessons for researchers. METHODS: Our trial investigated the single and combined effects of different ways of presenting clinical audit and feedback. Clinicians and managers who received feedback from one of five United Kingdom national clinical audit programmes were emailed invitations that contained a link to the trial website. After providing consent and selecting their relevant audit, participants were randomised automatically to different feedback versions. Immediately after viewing their assigned feedback, participants completed a questionnaire and could request a financial voucher by entering an email address. Email addresses were not linked to trial data to preserve participant anonymity. We actively monitored participant numbers, questionnaire completions, and voucher claims. RESULTS: Following a rapid increase in trial participation, we identified 268 new voucher claims from three email addresses that we had reason to believe were linked. Further scrutiny revealed duplicate trial completions and voucher requests from 24 email addresses. We immediately suspended the trial, improved security measures, and went on to successfully complete the study. We found a peak in questionnaires completed in less than 20 seconds during a likely contamination period. Given that study and personal data were not linked, we could not directly identify the trial data from the 268 duplicate entries within the 603 randomisations occurring during the same period. We therefore excluded all 603 randomisations from the primary analysis, which was consequently based on 638 randomisations. A sensitivity analysis, including all 961 randomisations over the entire study except for questionnaire completions of less than 20 seconds, found only minor differences from the primary analysis. CONCLUSION: Online studies offering incentives for participation are at risk of attempted fraud. Systematic monitoring and analysis can help detect such activity. Measures to protect study integrity include linking participant identifiers to study data, balancing study security and ease of participation, and safeguarding the allocation of participant incentives. TRIAL REGISTRATION: International Standard Randomised Controlled Trial Number: ISRCTN41584028. Registration date is August 17, 2017.

Supporting Autonomous Motivation for Physical Activity With Chatbots During the COVID-19 Pandemic: Factorial Experiment.

BACKGROUND: Although physical activity can mitigate disease trajectories and improve and sustain mental health, many people have become less physically active during the COVID-19 pandemic. Personal information technology, such as activity trackers and chatbots, can technically converse with people and possibly enhance their autonomous motivation to engage in physical activity. The literature on behavior change techniques (BCTs) and self-determination theory (SDT) contains promising insights that can be leveraged in the design of these technologies; however, it remains unclear how this can be achieved. OBJECTIVE: This study aimed to evaluate the feasibility of a chatbot system that improves the user's autonomous motivation for walking based on BCTs and SDT. First, we aimed to develop and evaluate various versions of a chatbot system based on promising BCTs. Second, we aimed to evaluate whether the use of the system improves the autonomous motivation for walking and the associated factors of need satisfaction. Third, we explored the support for the theoretical mechanism and effectiveness of various BCT implementations. METHODS: We developed a chatbot system using the mobile apps Telegram (Telegram Messenger Inc) and Google Fit (Google LLC). We implemented 12 versions of this system, which differed in 3 BCTs: goal setting, experimenting, and action planning. We then conducted a feasibility study with 102 participants who used this system over the course of 3 weeks, by conversing with a chatbot and completing questionnaires, capturing their perceived app support, need satisfaction, physical activity levels, and motivation. RESULTS: The use of the chatbot systems was satisfactory, and on average, its users reported increases in autonomous motivation for walking. The dropout rate was low. Although approximately half of the participants indicated that they would have preferred to interact with a human instead of the chatbot, 46.1% (47/102) of the participants stated that the chatbot helped them become more active, and 42.2% (43/102) of the participants decided to continue using the chatbot for an additional week. Furthermore, the majority thought that a more advanced chatbot could be very helpful. The motivation was associated with the satisfaction of the needs of competence and autonomy, and need satisfaction, in turn, was associated with the perceived system support, providing support for SDT underpinnings. However, no substantial differences were found across different BCT implementations. CONCLUSIONS: The results provide evidence that chatbot systems are a feasible means to increase autonomous motivation for physical activity. We found support for SDT as a basis for the design, laying a foundation for larger studies to confirm the effectiveness of the selected BCTs within chatbot systems, explore a wider range of BCTs, and help the development of guidelines for the design of interactive technology that helps users achieve long-term health benefits.

Analysis of Kerf Quality Characteristics of Kevlar Fiber-Reinforced Polymers Cut by Abrasive Water Jet.

Abrasive water jet machining has become an indispensable process for cutting Kevlar fiber-reinforced polymers used in applications such as ballistics protection, race cars, and protective gloves. The complex and diffuse action of a large number of input parameters leads to the need to evaluate the quality characteristics of the technological transformation as a result of the deployment of experimental studies adapted to the specific processing conditions. Thus, the paper focuses on identifying the influence of different factors and modeling their action on the characteristics that define the quality of the cut parts, such as the kerf taper angle and the Ra roughness parameter, by applying statistical methods of design and analysis of experiments.

Propagation of Sounds through Small Panels Made of Polymer Materials by 3D Printing.

To evaluate the sound insulation capacity of small panels made of polymeric materials by 3D printing, a Taguchi L18-type factorial experiment with eight independent variables was designed and materialized. The independent variables were the panel thickness, polymer material type, 3D printing speed, infill percent, infill pattern, layer thickness, frequency, and sound volume. Empirical mathematical models were determined through the mathematical processing of the experimental results using specialized software. These empirical mathematical models highlight the meaning and intensity of the influence exerted by the input factors in the process on the acoustic pressure level of the energy absorbed after the passage of sounds through the small panels manufactured by 3D printing from polylactic acid and polyethylene terephthalate glycol. The factor with the strongest influence was the frequency of the sounds, with a maximum of the sound pressure level for a frequency of 13,000 Hz. A polylactic acid panel between the sound source and the sound-receiving sensor reduces the sound pressure level by about 45% from 95.8 to 65.8 dB. The power function type mathematical model in the case of the energy absorbed by the panel highlights the fact that the highest values of the exponents are those attached to the sound frequency (exponent equal to 1.616) and, respectively, to the thickness of the panel (exponent equal to -0.121).

Using factorial mediation analysis to better understand the effects of interventions.

To improve understanding of how interventions work or why they do not work, there is need for methods of testing hypotheses about the causal mechanisms underlying the individual and combined effects of the components that make up interventions. Factorial mediation analysis, i.e., mediation analysis applied to data from a factorial optimization trial, enables testing such hypotheses. In this commentary, we demonstrate how factorial mediation analysis can contribute detailed information about an intervention's causal mechanisms. We briefly review the multiphase optimization strategy (MOST) and the factorial experiment. We use an empirical example from a 25 factorial optimization trial to demonstrate how factorial mediation analysis opens possibilities for better understanding the individual and combined effects of intervention components. Factorial mediation analysis has important potential to advance theory about interventions and to inform intervention improvements.

A randomised fractional factorial screening experiment to predict effective features of audit and feedback.

BACKGROUND: Audit and feedback aims to improve patient care by comparing healthcare performance against explicit standards. It is used to monitor and improve patient care, including through National Clinical Audit (NCA) programmes in the UK. Variability in effectiveness of audit and feedback is attributed to intervention design; separate randomised trials to address multiple questions about how to optimise effectiveness would be inefficient. We evaluated different feedback modifications to identify leading candidates for further "real-world" evaluation. METHODS: Using an online fractional factorial screening experiment, we randomised recipients of feedback from five UK NCAs to different combinations of six feedback modifications applied within an audit report excerpt: use effective comparators, provide multimodal feedback, recommend specific actions, provide optional detail, incorporate the patient voice, and minimise cognitive load. Outcomes, assessed immediately after exposure to the online modifications, included intention to enact audit standards (primary outcome, ranked on a scale of -3 to +3, tailored to the NCA), comprehension, user experience, and engagement. RESULTS: We randomised 1241 participants (clinicians, managers, and audit staff) between April and October 2019. Inappropriate repeated participant completion occurred; we conservatively excluded participant entries during the relevant period, leaving a primary analysis population of 638 (51.4%) participants. None of the six feedback modifications had an independent effect on intention across the five NCAs. We observed both synergistic and antagonistic effects across outcomes when modifications were combined; the specific NCA and whether recipients had a clinical role had dominant influences on outcome, and there was an antagonistic interaction between multimodal feedback and optional detail. Among clinical participants, predicted intention ranged from 1.22 (95% confidence interval 0.72, 1.72) for the least effective combination in which multimodal feedback, optional detail, and reduced cognitive load were applied within the audit report, up to 2.40 (95% CI 1.88, 2.93) for the most effective combination including multimodal feedback, specific actions, patient voice, and reduced cognitive load. CONCLUSION: Potentially important synergistic and antagonistic effects were identified across combinations of feedback modifications, audit programmes, and recipients, suggesting that feedback designers must explicitly consider how different features of feedback may interact to achieve (or undermine) the desired effects. TRIAL REGISTRATION: International Standard Randomised Controlled Trial Number: ISRCTN41584028.