Initial Preference Research Articles

Cooperative Content Replacement and Recommendation in Small Cell Networks

Content caching has limitations on achieving cache gains (e.g., cache hit ratio) in small cell networks, due to limited storages of small base stations (SBSs) and inherent user demand patterns (i.e., initial content preferences). Two effective approaches have been proposed to exploit the potential of content caching: SBS cooperation to utilize cache storage, and proactive content recommendation to shape user demand. In this paper, we investigate cooperative content caching and recommendation to maximize cache gains, while guaranteeing users’ satisfaction by recommending appealing content items. We propose a generic framework for cooperative content caching and recommendation, based on which we propose an online and distributed scheme by designing a continuous-time Markov chain (CTMC). In particular, online content caching (a.k.a., content replacement) is implemented by hopping from one cache state to another in the CTMC, while content recommendation is performed heuristically through sequential fixing at each cache state. Besides, we characterize the performance gap between our proposed scheme and the theoretical optimum in terms of cache hit ratio. Simulation results demonstrate that the proposed scheme achieves better cache hit ratios than other schemes in single-BS scenarios, and provides a competitive solution in multiple-BS scenarios.

Factors Associated with Caregiver Preferences for Children's Return to School during the COVID-19 Pandemic.

Amid the COVID-19 pandemic, there is a need to understand caregiver preferences for their children's instructional format for the start of the 2020 to 2021 academic year. The purpose of the current study was to assess caregiver preferences for on-campus versus virtual learning at home during the fall and factors associated with these preferences. Participants were caregivers of 4436 children and adolescents who were enrolled in pre-kindergarten through high school at a large, public school district in Texas. Caregivers were asked to complete an anonymous, online survey about their initial preferences for their student's back to the school learning environment. Caregivers of high- and middle-school students were more likely to endorse a preference for an on-campus/virtual hybrid instructional format and less likely to endorse a preference for a traditional, face-to-face instructional format compared to caregivers of elementary school students. Regardless of the school level, concerns about child health and safety were the factor most strongly associated with caregiver preferences for on-campus versus virtual learning at home during the fall. These data highlight the importance of school re-opening plans offering virtual options and addressing caregiver concerns about children's health and safety amid the COVID-19 pandemic.

Moderating effects of perceived risk on the determinants–outcome nexus of e-money behaviour

PurposeIn recent years, the usage rate of electronic money (e-money) has grown rapidly in many countries around the world and is becoming widely accepted in developing nations due to evolving market conditions and buying patterns. This study explores the determinants of customers' behavioural intention (BI) and actual usage behaviour (UB) of e-money service in a transition economic setting. Additionally, since there has been limited research on moderating influences, this study introduces perceived risk (PR) as a moderator, underpinned by relevant technology acceptance and behavioural theories.Design/methodology/approachThe proposed model and hypothesised variable relationships are tested using partial least squares-structural equation modelling (PLS-SEM) with survey data from 337 e-money service users in Indonesia.FindingsThe empirical results revealed that facilitating conditions (FCs), hedonic motivation (HM), price value (PV), habit (HT) and PR are important determinants of customers’ BI towards e-money and most of these variables also affect actual UB of e-money services. Performance expectancy (PE), effort expectancy (EE) and social influence (SI) emerged to be insignificant determinants. The study also uncovered that PR negatively moderates the links between EE, SI, HM, PV and BI towards e-money services. Likewise, PR has an adverse effect on the BI–actual UB relationship.Research limitations/implicationsA large portion of the sample comprised young individuals with tertiary education. In essence, the sample represents the millennial generation and they are generally characterised as responsive, innovative and technology literate. Future studies could advance the present understanding by comparing different customer backgrounds and country.Practical implicationsThe results shed light into the key factors that enhance e-money usage behaviours and have direct managerial implications with regard to brand strategy and market targeting. The findings imply that e-money service providers should take initiatives to retain users with effective and personalised marketing efforts, particularly via mobile media brand promotions.Originality/valueWhile there has been considerable discussion on how PR may impact on initial preference and adoption of e-money, existing studies seem to fall short in conceptualising and empirically examining the moderating role of PR on the determinants and outcome of e-money BI.

FAME: 3D Shape Generation Via Functionality-Aware Model Evolution.

We introduce a modeling tool which can evolve a set of 3D objects in a functionality-aware manner. Our goal is for the evolution to generate large and diverse sets of plausible 3D objects for data augmentation, constrained modeling, as well as open-ended exploration to possibly inspire new designs. Starting with an initial population of 3D objects belonging to one or more functional categories, we evolve the shapes through part recombination to produce generations of hybrids or crossbreeds between parents from the heterogeneous shape collection. Evolutionary selection of offsprings is guided both by a functional plausibility score derived from functionality analysis of shapes in the initial population and user preference, as in a design gallery. Since cross-category hybridization may result in offsprings not belonging to any of the known functional categories, we develop a means for functionality partial matching to evaluate functional plausibility on partial shapes. We show a variety of plausible hybrid shapes generated by our functionality-aware model evolution, which can complement existing datasets as training data and boost the performance of contemporary data-driven segmentation schemes, especially in challenging cases. Our tool supports constrained modeling, allowing users to restrict or steer the model evolution with functionality labels. At the same time, unexpected yet functional object prototypes can emerge during open-ended exploration owing to structure breaking when evolving a heterogeneous collection.

The Importance of Candidate Sex and Partisan Preference over Time: A Multiday Study of Voter Decision Making

Women often face challenges when running for political office, but precisely when and how candidate sex affects voter decision making is unclear. Using a unique multiday, high-information experiment, we examine how the presence of women candidates in an election influences subjects’ information search, candidate evaluations, and vote decisions. We focus on how the partisan alignment of women candidates (whether they run in the subject’s preferred in-party vs. out-party) matters and at which point in the campaign gender is most influential. We find that subjects who see in-party women candidates are more open to considering the out-party candidate, seeking out more information about the candidates in the race. Out-party women candidates strengthen subjects’ initial partisan preferences, however, leading to less search and higher in-party voting rates. We also find that candidate gender is most influential early in the campaign, and its effects diminish as the campaign progresses.

Influence of Early Lactation Assistance on Inpatient Exclusive Breastfeeding Rates

Human milk feeding reduces the incidence and costs of several maternal and childhood illnesses. Initiation and success of human milk feeding are influenced by race, socioeconomic status, and family support. The influence of early in-hospital lactation assistance in breastfeeding success has been not well described. We aimed to determine how suspected known factors influencing breastfeeding success influence in-hospital human milk feeding rates. Second, we aimed to examine how timing of lactation assistance is related to success of human milk feeding during the newborn hospitalization for healthy infants. We conducted a retrospective cohort study of term infants born between January 1, 2014 and December 31, 2016 at a large tertiary academic hospital. We considered "success" to be 100% human milk feeding during the birth hospitalization, and compared differences in success by demographics, payor, race, and initial feeding preference. Influences of lactation assistance on success were analyzed using multivariable logistic regression. Mean success with exclusive human milk feeding among 7,370 infants was 48.9%, (n = 3,601). Successful participants were more likely to be 39-40 weeks' gestation (64.9%, n = 2,340), non-Hispanic/non-Latino (80.0%, n = 2,882), and using private insurance (69.2%, n = 2,491). Participants who had early feeding assisted by an International Board Certified Lactation Consultant (IBCLC) before being fed any formula were more likely to be successful than participants who had a feeding assisted by a non-IBCLC nurse (80% vs. 40% respectively). Success for exclusive human milk feeding during newborn hospitalization is strongly associated with several factors. Early intervention with IBCLCs can greatly improve breastfeeding success.

Assessing stakeholder preferences on low-carbon energy transitions

ABSTRACT Low carbon transition pathways entail diverse uncertainties and risks in the underlying environmental, social, political, economic and technological factors. Inadequate information about such risks could affect the achievement of climate change mitigation targets negatively. This paper provides a novel experiment in which quantitative tools and stakeholder engagement are combined in order to identify the barriers between stakeholders and scientists concerning climate change mitigation aspects. Technological risks are captured by simulating different low carbon scenarios with limited technology options. Stakeholders are asked about their preferences on technology options regarding a low carbon future. After providing them with the simulation results, they are asked again in order to see whether those initial preferences had changed. Results prove the necessity for better communication between modelers and stakeholders. Closing the gaps between both communities is essential to remove barriers for more ambitious action against climate change.

Pull Factors and Migration Preferences: Evidence from the Middle East and North Africa

Which national characteristics do voluntary migrants prioritize when considering destinations? Although this question is salient for policymakers, extant studies face challenges when seeking to identify how various pull factors shape destination preferences. Surveys of migrants are typically conducted after they arrive, introducing selection bias and post-hoc reasoning. Moreover, desirable national characteristics tend to co-vary, implying that observed relationships with migration flows may be confounded. In this article, we identify the destination preferences of prospective migrants by drawing on a sample of 8,500 respondents from five sending states across the Middle East and North Africa. Prospective migrants completed a series of conjoint survey tasks in which they chose between two destinations with randomly varying characteristics. The results reveal a clear hierarchy of preferences, with prospective migrants placing the greatest priority on liberal democratic governance and employment prospects. The availability of welfare benefits acted as a secondary consideration, while geographic distance and co-ethnic stock did not strongly predict initial destination preferences. While the rank order of these considerations remains consistent across national samples, our results suggest that respondents from different economic and political backgrounds vary in how they navigate potential tradeoffs between national characteristics. These findings address post-arrival bias in extant studies by revealing prospective migrants’ preferences before they interact with the opportunity structures that facilitate and restrict entry into desirable destinations.

BIMBOT-(Artificial intelligence applied to BIM design)

BIMBOT es un asistente de diseño inteligente para la industria AEC. Sus herramientas se ejecutan sobre un software de modelado BIM y producen varias soluciones de diseño con modelos BIM optimizados. Funciona con el uso de métodos avanzados de Inteligencia Artificial (optimización soft computing y Machine Learning) y es compatible con bases de datos NoSQL. Contempla varias etapas: La definición por el usuario de restricciones / prioridades establecidas ejecuta un proceso de diseño generativo impulsado por varios métodos de IA. Éste crea diferentes soluciones en modelos BIM almacenados y refinados a partir de un catálogo de objetos inteligentes. Con ello, los usuarios pueden interactuar importando modelos BIM con diseños propuestos, crearlos o editarlos in situ y recibir asistencia de una serie de métricas configurables que dan calidad al diseño de acuerdo con las preferencias iniciales. Así, obtenemos un Modelo BIM completo como resultado del proceso iterativo. Finalmente, el entrenamiento continuo de los algoritmos mejorará la eficiencia en futuros diseños. BIMBOT está concebido para extender las habilidades de los diseñadores a través del desarrollo de software BIM, permitiéndoles ser más productivos en tareas complejas del proceso de diseño. BIMBOT está financiado por el programa europeo Eureka / Eurostars (E! 12863).

Microtubules originate asymmetrically at the somatic golgi and are guided via Kinesin2 to maintain polarity within neurons.

Neurons contain polarised microtubule arrays essential for neuronal function. How microtubule nucleation and polarity are regulated within neurons remains unclear. We show that γ-tubulin localises asymmetrically to the somatic Golgi within Drosophila neurons. Microtubules originate from the Golgi with an initial growth preference towards the axon. Their growing plus ends also turn towards and into the axon, adding to the plus-end-out microtubule pool. Any plus ends that reach a dendrite, however, do not readily enter, maintaining minus-end-out polarity. Both turning towards the axon and exclusion from dendrites depend on Kinesin-2, a plus-end-associated motor that guides growing plus ends along adjacent microtubules. We propose that Kinesin-2 engages with a polarised microtubule network within the soma to guide growing microtubules towards the axon; while at dendrite entry sites engagement with microtubules of opposite polarity generates a backward stalling force that prevents entry into dendrites and thus maintains minus-end-out polarity within proximal dendrites.

The role of novelty and fat and sugar concentration in food selection by captive tufted capuchins (Sapajus apella).

Capuchins, like other primates, use feedback from sensory cues and digestion to make decisions about which foods to consume and which to avoid. However, little is known about how capuchins make consumption decisions when simultaneously presented with novel and familiar foods, or how food familiarity and macronutrient concentration together influence food choice, topics with potential implications for developmental and health research. In this study, we evaluated the role of familiarity, as well as fat and sugar concentration, in the food selections of captive tufted capuchins (Sapajus apella). In the first experiment, over 10 sessions, subjects were assigned to either a group that chose between one familiar and one novel food item both high in fat or sugar (high condition), or to a group that chose between one familiar and one novel food item both low in fat or sugar (low condition). In the second experiment, subjects were divided into three groups, familiarized with food over five feeding sessions, and then offered the familiarized food and a novel food that varied in fat or sugar for 10 sessions. When offered foods high in fat, capuchins showed no clear signs of neophobia, forming an initial preference for the novel food, rejecting foods less frequently, and selecting foods faster than when offered foods low in fat. These trends were generally not observed in response to foods with sugar. When presented with options that varied in macronutrient concentration, subjects showed an initial interest in the novel food irrespective of whether it was high in fat or sugar, yet formed a final preference for the higher-concentration item. Findings suggest that the concentration of fat or sugar in novel foods may be an important mediator of exploratory behavior and that capuchins rely on immediate feedback from taste and other sensory cues to make consumption decisions.

The value of information for price dependent demand

Predicting demand and determining optimal pricing are essential components of operations management. It is often useful to think in terms of the price elasticity of demand when reasoning about the demand curve. Firms wishing to invest in demand prediction and information gathering should reason about the relationship between the expected value of perfect information (EVPI) on demand and demand elasticity. Should firms pay more/less for information on demand if elasticity is high/low? Furthermore, when considering different product prices, correlation may exist between demand at different prices. Should firms pay more/less for information if the correlation between demand at different prices is high or low? This paper derives analytic and numeric results to answer these questions. We start with the assumption that demand is uncertain and follows a uniformly distributed band around a deterministic demand curve where the upper and lower bounds of the demand distribution vary with price. This formulation enables a closed form expression for EVPI that provides a useful benchmark. We find nuanced behavior of EVPI that depends on both the elasticity and the initial price preference. The EVPI approaches zero as elasticity increases (decreases) for a firm that initially prefers the low (high) price. Numerical results using the truncated normal and beta distributions relax assumptions about the uniform distribution and show EVPI is similar when the distribution variances are similar. Finally, we relax the assumption of perfect information and show the expected value of imperfect information (EVOI) follows similar patterns as EVPI with respect to demand elasticity.

Residual Glucose Taste in T1R3 Knockout but not TRPM5 Knockout Mice

Knockout (KO) mice missing the sweet taste receptor subunit T1R3 or the signaling protein TRPM5 have greatly attenuated sweetener preferences. Yet both types of KO mice develop preferences for glucose but not fructose in 24-h tests, which has been attributed to the postoral reinforcing actions of glucose. Here we probed for residual sugar taste sensitivity in KO mice. Unlike wildtype (WT) mice, food-restricted T1R3 KO and TRPM5 KO mice displayed little attraction for 8% glucose and 8% fructose in 1-min, two-bottle choice tests. However, in 1-h tests about half of the T1R3 KO mice displayed a significant preference for glucose over fructose (78-84%), while WT mice showed either no or weak preferences (41-56%) for glucose. Following one-bottle training sessions, WT mice display greater glucose preferences although still weaker than those observed in T1R3 KO mice. In contrast, TRPM5 KO mice were indifferent to sugars in 1-h tests but developed a strong preference for glucose over fructose in 24-h tests. T1R3 taste cells contain the sodium glucose cotransporter 1 (SGLT1) and the ATP-gated K+ (KATP) metabolic sensor, which may mediate the unlearned glucose preference displayed by T1R3 KO mice. Unlike WT mice, many T1R3 KO mice strongly preferred glucose to a non-metabolizable glucose analog (α-methyl-D-glucopyranoside, MDG) in initial 1-h choice tests. Glucose and MDG are both ligands for SGLT1 which indicates that SGLT1 sensing does not mediate the glucose preference of T1R3 KO mice. Instead, KATP sensing and/or other oral sensors are implicated. The MDG findings also argue against postoral sensing as the primary source of the initial glucose preference displayed by T1R3 KO mice. Why only half of the T1R3 KO mice showed this preference in 1-h tests remains to be determined. All T1R3 KO mice preferred glucose to fructose in 24-h tests, which appears to be due to both oral and postoral glucose sensing.

Effect of Internet vs Face-to-Face Cognitive Behavior Therapy for Health Anxiety

Health anxiety is a common and often chronic mental health problem associated with distress, substantial costs, and frequent attendance throughout the health care system. Face-to-face cognitive behavior therapy (CBT) is the criterion standard treatment, but access is limited. To test the hypothesis that internet-delivered CBT, which requires relatively little resources, is noninferior to face-to-face CBT in the treatment of health anxiety. This randomized noninferiority clinical trial with health economic analysis was based at a primary care clinic and included patients with a principal diagnosis of health anxiety who were self-referred or referred from routine care. Recruitment began in December 10, 2014, and the last treatment ended on July 23, 2017. Follow-up data were collected up to 12 months after treatment. Analysis began October 2017 and ended March 2020. Patients were randomized (1:1) to 12 weeks of internet-delivered CBT or to individual face-to-face CBT. Change in health anxiety symptoms from baseline to week 12. Analyses were conducted from intention-to-treat and per-protocol (completers only) perspectives, using the noninferiority margin of 2.25 points on the Health Anxiety Inventory, which has a theoretical range of 0 to 54. Overall, 204 patients (mean [SD] age, 39 [12] years; 143 women [70%]) contributed with 2386 data points on the Health Anxiety Inventory over the treatment period. Of 204 patients, 102 (50%) were randomized to internet-delivered CBT, and 102 (50%) were randomized to face-to-face CBT. The 1-sided 95% CI upper limits for the internet-delivered CBT vs face-to-face CBT difference in change were within the noninferiority margin in the intention-to-treat analysis (B = 0.00; upper limit: 1.98; Cohen d = 0.00; upper limit: 0.23) and per-protocol analysis (B = 0.01; upper limit: 2.17; Cohen d = 0.00; upper limit: 0.25). The between-group effect was not moderated by initial symptom level, recruitment path, or patient treatment preference. Therapists spent 10.0 minutes per patient per week in the online treatment vs 45.6 minutes for face-to-face CBT. The net societal cost was lower in the online treatment (treatment period point difference: $3854). There was no significant group difference in the number of adverse events, and no serious adverse event was reported. In this trial, internet-delivered CBT appeared to be noninferior to face-to-face CBT for health anxiety, while incurring lower net societal costs. The online treatment format has potential to increase access to evidence-based treatment for health anxiety. ClinicalTrials.gov Identifier: NCT02314065.

A consensus reaching process with quantum subjective adjustment in linguistic group decision making

The consensus reaching process (CRP) is essential to obtain a final solution in group decision making (GDM). This paper focuses on constructing a consensus mechanism where decision makers (DMs) use linguistic term sets (LTSs) to express their preferences. LTSs can describe real decision making well. Adjusting opinions can improve the consensus level, we assume that the adjusted opinion combines an initial preference and a referenced preference. The subjective behavior characteristics expressed by DMs would affect the CRP. To simulate human behavior, quantum probability theory is applied to aggregate referenced opinions, reflecting the interference effect caused by subjective beliefs flowing toward decision classification paths. The paths are composed of the clusters with the highest consensus and consistency degrees. Moreover, the combination is generated based on the subjective willingness defined by the consensus position of the recognized DM in the group. An optimization model is set to control individual consistency after implementing modifications. Finally, a numerical example illustrates the principle of the constructed model.

Contextual imitation in juvenile common ravens, Corvus corax

Social learning is a powerful mechanism of information acquisition and can be found in various species. According to the type of information transmitted, animals may change their motivation to perform actions, shift their perception/attention to relevant stimuli, associate other individuals' behaviours with particular stimuli/events or learn to perform ‘novel’ behaviours. The latter is referred to as imitation and has been considered a cognitively demanding mechanism necessary for high-fidelity copying, which may or may not occur in nonhuman animals. We tested the ability of 20 juvenile ravens to imitate an action demonstrated by a human experimenter. Birds of two test groups could observe a familiar human executing one of two opening techniques at an artificial fruit apparatus (horizontal or vertical hand movements directed towards the same location), whereas birds of a control group observed the human touching but not opening the apparatus. Ravens of both test groups tended to use the same direction of movements as observed, when they opened the apparatus themselves with their beak. Comparison with the control group revealed that ravens had a predisposition to manipulate the apparatus by pecking. Hence, observers of vertical hand movements most likely strengthened their initial preference for executing peck movements towards an item enclosing food, whereas observers of horizontal hand movements started to apply beak/head movements that hardly occur during foraging and are ‘novel’ to this context. Juvenile ravens are thus capable of imitating simple motor actions, even though they may use a different body part to execute the behaviours than human demonstrators.

Evaluating backward chaining methods on vocational tasks by adults with developmental disabilities

AbstractBackward chains are widely used to teach complex skills to individuals with developmental disabilities. Implementation of chaining procedures may vary regarding untaught steps and there is little to guide practitioners in the selection of chaining procedures. Moreover, there is a dearth of research evaluating effectiveness and efficiency of procedural variations of behavior chains. The purpose of this study was to extend previous research by evaluating the effectiveness, efficiency, and preference for four procedural variations (i.e., teacher‐completion, participant‐completion, no‐completion, and a control condition) of backward chains across vocational tasks with adults with developmental disabilities. Although procedural variations effectively established vocational skills, the participant‐completion procedure (in which the instructor implemented a least‐to‐most prompt hierarchy during all untrained steps in the chain) was the most efficacious backward chaining procedural variation and efficient in terms of sessions to mastery. The no‐completion procedure (in which the instructor completed all untrained steps in the chain out of view of the participant) was least efficient across trials, sessions, errors, and total duration to mastery. One participant preferred the no‐completion condition while the other two participants showed an initial preference for the teacher‐completion condition that changed to preference for the no‐completion condition. Vocational skills maintained 1‐ and 4‐weeks postmastery. Stakeholders rated goals, procedures, and outcomes as socially valid.

Improving Auditors' Consideration of Evidence Contradicting Management's Estimate Assumptions

ABSTRACTAuditors have difficulty evaluating the assumptions underlying management's estimates. One source of these problems is that auditors appear to dismiss evidence contradicting management's assumptions because their initial preference to support management's accounting biases their preliminary conclusions and, thus, their interpretation of evidence. We experimentally examine whether auditors with a balanced focus (i.e., a focus on documenting evidence that supports and contradicts their preliminary conclusion) are less likely to dismiss evidence that contradicts management's assumptions than auditors with a supporting focus (i.e., a focus on documenting evidence that supports their preliminary conclusion). We expect and find that, compared with auditors with a supporting focus, auditors with a balanced focus create documentation that is less dismissive of evidence contradicting management's estimate. Importantly, a balanced focus changes auditors' cognition and affects how auditors interpret contradicting evidence rather than merely increasing their documentation of this evidence. The effects of reduced dismissiveness persist to improve auditors' evaluations of a biased estimate and subsequent actions, improving audit quality in an important and difficult area.

A trichotomic segmentation approach for estimating composite indicators

Composite indicators (CIs) are commonly used for benchmarking of countries over the years, summarizing in a single measurement, complex social, economic, environmental etc. concepts by involving several thematically related sub-indicators. When estimating CIs and for a few specific countries, it is possible to have a strong indication and belief about their performance, prior to obtaining their scores. Based on that, a number of countries are likely to occupy the top-ranking positions; some will remain at the bottom list, while others may range in intermediate places. This initial preference information imposes a trichotomic segmentation that divides the countries under assessment into categories of superior, inferior and of ambiguous future performance. In this paper, we introduce the trichotomic segmentation as initial preference information to estimate the values of the CIs. We build on the popular Benefit of the Doubt (BoD) method with common weights and develop a two-goal linear programming model, that next to the evaluation of the common weights for the sub-indicators, estimates cut-off points for the CI values that distinguish the superior and inferior countries. The proposed model maintains the advantages of the common variable weighting and produces scores that induce better discrimination of the countries, having also a significant correlation with the original CI scores. The proposed methodology is applied to reassess the Digital Economy and the Society Index.

Women’s experiences of decision-making and attitudes in relation to induction of labour: A survey study

BackgroundRates of induction of labour have been increasing globally to up to one in three pregnancies in many high-income countries. Although guidelines around induction, and strength of the underlying evidence, vary considerably by indication, shared decision-making is increasingly recognised as key. The aim of this study was to identify women’s mode of birth preferences and experiences of shared decision-making for induction of labour. MethodAn antenatal survey of women booked for an induction at eight Sydney hospitals was conducted. A bespoke questionnaire was created assessing women’s demographics, indication for induction, pregnancy model of care, initial birth preferences, and their experience of the decision-making process. ResultsOf 189 survey respondents (58% nulliparous), major reported reasons for induction included prolonged pregnancy (38%), diabetes (25%), and suspected fetal growth restriction (8%). Most respondents (72%) had hoped to labour spontaneously. Major findings included 19% of women not feeling like they had a choice about induction of labour, 26% not feeling adequately informed (or uncertain if informed), 17% not being given alternatives, and 30% not receiving any written information on induction of labour. Qualitative responses highlight a desire of women to be more actively involved in decision-making. ConclusionA substantial minority of women did not feel adequately informed or prepared, and indicated they were not given alternatives to induction. Suggested improvements include for face-to-face discussions to be supplemented with written information, and for shared decision-making interventions, such as the introduction of decision aids and training, to be implemented and evaluated.