Do gender and year of study affect the ability of the theory of planned behaviour to predict binge-drinking intentions and episodes?

Background: The present study tested the utility of the theory of planned behaviour (TPB), augmented with anticipated regret, as a model to predict binge-drinking intentions and episodes among female and male undergraduates and undergraduates in different years of study. Method: Undergraduate students (N = 180, 54 males, 126 females, 60 per year of study) completed baseline measures of demographic variables, binge-drinking episodes (BDE), TPB constructs and anticipated regret. BDE were assessed one-week later. Results: The TPB accounted for 60% of the variance in female undergraduates' intentions and 54% of the variance in male undergraduates' intentions. The TPB accounted for 57% of the variance in intentions in first-year undergraduates, 63% of the variance in intentions in second-year undergraduates and 68% of the variance in intentions in final-year undergraduates. Follow-up BDE was predicted by intentions and baseline BDE for female undergraduates as well as second- and final-year undergraduates. Baseline BDE predicted male undergraduates’ follow-up BDE and first-year undergraduates’ follow-up BDE. Conclusion: Results show that while the TPB constructs predict undergraduates’ binge-drinking intentions, intentions only predict BDE in female undergraduates, second- and final-year undergraduates. Implications of these findings for interventions to reduce binge drinking are outlined.

Anticipated behaviours of emergency prehospital medical care providers during an influenza pandemic

Introduction: Emergency prehospital medical care providers are frontline health workers during emergencies. However, little is known about their attitudes, perceptions, and likely behaviors during emergency conditions. Understanding these attitudes and behaviors is crucial to mitigating the psychological and operational effects of biohazard events such as pandemic influenza, and will support the business continuity of essential prehospital services. ----- ----- Problem: This study was designed to investigate the association between knowledge and attitudes regarding avian influenza on likely behavioral responses of Australian emergency prehospital medical care providers in pandemic conditions. ----- ----- Methods: Using a reply-paid postal questionnaire, the knowledge and attitudes of a national, stratified, random sample of the Australian emergency prehospital medical care workforce in relation to pandemic influenza were investigated. In addition to knowledge and attitudes, there were five measures of anticipated behavior during pandemic conditions: (1) preparedness to wear personal protective equipment (PPE); (2) preparedness to change role; (3) willingness to work; and likely refusal to work with colleagues who were exposed to (4) known and (5) suspected influenza. Multiple logistic regression models were constructed to determine the independent predictors of each of the anticipated behaviors, while controlling for other relevant variables. ----- ----- Results: Almost half (43%) of the 725 emergency prehospital medical care personnel who responded to the survey indicated that they would be unwilling to work during pandemic conditions; one-quarter indicated that they would not be prepared to work in PPE; and one-third would refuse to work with a colleague exposed to a known case of pandemic human influenza. Willingness to work during a pandemic (OR = 1.41; 95% CI = 1.0–1.9), and willingness to change roles (OR = 1.44; 95% CI = 1.04–2.0) significantly increased with adequate knowledge about infectious agents generally. Generally, refusal to work with exposed (OR = 0.48; 95% CI = 0.3–0.7) or potentially exposed (OR = 0.43; 95% CI = 0.3–0.6) colleagues significantly decreased with adequate knowledge about infectious agents. Confidence in the employer’s capacity to respond appropriately to a pandemic significantly increased employee willingness to work (OR = 2.83; 95% CI = 1.9–4.1); willingness to change roles during a pandemic (OR = 1.52; 95% CI = 1.1–2.1); preparedness to wear PPE (OR = 1.68; 95% CI = 1.1–2.5); and significantly decreased the likelihood of refusing to work with colleagues exposed to (suspected) influenza (OR = 0.59; 95% CI = 0.4–0.9). ----- ----- Conclusions:These findings indicate that education and training alone will not adequately prepare the emergency prehospital medical workforce for a pandemic. It is crucial to address the concerns of ambulance personnel and the perceived concerns of their relationship with partners in order to maintain an effective prehospital emergency medical care service during pandemic conditions.

A Stochastic View of Optimal Regret through Minimax Duality

We study the regret of optimal strategies for online convex optimization games. Using von Neumann's minimax theorem, we show that the optimal regret in this adversarial setting is closely related to the behavior of the empirical minimization algorithm in a stochastic process setting: it is equal to the maximum, over joint distributions of the adversary's action sequence, of the difference between a sum of minimal expected losses and the minimal empirical loss. We show that the optimal regret has a natural geometric interpretation, since it can be viewed as the gap in Jensen's inequality for a concave functional--the minimizer over the player's actions of expected loss--defined on a set of probability distributions. We use this expression to obtain upper and lower bounds on the regret of an optimal strategy for a variety of online learning problems. Our method provides upper bounds without the need to construct a learning algorithm; the lower bounds provide explicit optimal strategies for the adversary. Peter L. Bartlett, Alexander Rakhlin

Closing the gap between bandit and full-information online optimization : high-probability regret bound

We demonstrate a modification of the algorithm of Dani et al for the online linear optimization problem in the bandit setting, which allows us to achieve an O( \sqrt{T ln T} ) regret bound in high probability against an adaptive adversary, as opposed to the in expectation result against an oblivious adversary of Dani et al. We obtain the same dependence on the dimension as that exhibited by Dani et al. The results of this paper rest firmly on those of Dani et al and the remarkable technique of Auer et al for obtaining high-probability bounds via optimistic estimates. This paper answers an open question: it eliminates the gap between the high-probability bounds obtained in the full-information vs bandit settings.

Optimistic linear programming gives logarithmic regret for irreducible MDPs

We present an algorithm called Optimistic Linear Programming (OLP) for learning to optimize average reward in an irreducible but otherwise unknown Markov decision process (MDP). OLP uses its experience so far to estimate the MDP. It chooses actions by optimistically maximizing estimated future rewards over a set of next-state transition probabilities that are close to the estimates, a computation that corresponds to solving linear programs. We show that the total expected reward obtained by OLP up to time T is within C(P) log T of the reward obtained by the optimal policy, where C(P) is an explicit, MDP-dependent constant. OLP is closely related to an algorithm proposed by Burnetas and Katehakis with four key differences: OLP is simpler, it does not require knowledge of the supports of transition probabilities, the proof of the regret bound is simpler, but our regret bound is a constant factor larger than the regret of their algorithm. OLP is also similar in flavor to an algorithm recently proposed by Auer and Ortner. But OLP is simpler and its regret bound has a better dependence on the size of the MDP.

High-probability regret bounds for bandit online linear optimization

We present a modification of the algorithm of Dani et al. [8] for the online linear optimization problem in the bandit setting, which with high probability has regret at most O ∗ ( √ T) against an adaptive adversary. This improves on the previous algorithm [8] whose regret is bounded in expectation against an oblivious adversary. We obtain the same dependence on the dimension (n 3/2) as that exhibited by Dani et al. The results of this paper rest firmly on those of [8] and the remarkable technique of Auer et al. [2] for obtaining high probability bounds via optimistic estimates. This paper answers an open question: it eliminates the gap between the high-probability bounds obtained in the full-information vs bandit settings.

General characteristics of anticipated user experience (AUX) with interactive products

Providing a positive user experience (UX) has become the key differentiator for products to win a competition in mature markets. To ensure that a product will support enjoyable experiences for its users, assessment of UX should be conducted early during the design and development process. However, most UX frameworks and evaluation techniques focus on understanding and assessing user’s experience with functional prototypes or existing products. This situation delays UX assessment until the late phases of product development which may result in costly design modifications and less desirable products. A qualitative study was conducted to investigate anticipated user experience (AUX) to address this issue. Twenty pairs of participants were asked to imagine an interactive product, draw their product concept, and anticipate their interactions and experiences with it. The data was analyzed to identify general characteristics of AUX. We found that while positive AUX was mostly related to an imagined/desired product, negative AUX was mainly associated with existing products. It was evident that the pragmatic quality of product was fundamental, and significantly influenced user’s anticipated experiences. Furthermore, the hedonic quality of product received more focus in positive than negative AUX. The results also showed that context, user profile, experiential knowledge, and anticipated emotion could be reflected in AUX. The understanding of AUX will help product designers to better foresee the users’ underlying needs and to focus on the most important aspects of their positive experiences, which in turn facilitates the designers to ensure pleasurable UX from the start of the design process.

Rate of torque and electromyographic development during anticipated eccentric contraction is lower in previously strained hamstrings

Background: Hamstring strain injuries are prevalent in sport and re-injury rates have been high for many years. Whilst much focus has centred on the impact of previous hamstring strain injury on maximal eccentric strength, high rates of torque development is also of interest, given the important role of the hamstrings during the terminal swing phase of running. The impact of prior strain injury on myoelectrical activity of the hamstrings during tasks requiring high rates of torque development has received little attention. Purpose: To determine if recreational athletes with a history of unilateral hamstring strain injury, who have returned to training and competition, will exhibit lower levels of myoelectrical activity during eccentric contraction, rate of torque development and impulse 30, 50 and 100ms after the onset of myoelectrical activity or torque development in the previously injured limb compared to the uninjured limb. Study design: Case-control study Methods: Twenty-six recreational athletes were recruited. Of these, 13 athletes had a history of unilateral hamstring strain injury (all confined to biceps femoris long head) and 13 had no history of hamstring strain injury. Following familiarisation, all athletes undertook isokinetic dynamometry testing and surface electromyography assessment of the biceps femoris long head and medial hamstrings during eccentric contractions at -60 and -1800.s-1. Results: In the injured limb of the injured group, compared to the contralateral uninjured limb rate of torque development and impulse was lower during -600.s-1 eccentric contractions at 50 (RTD, injured limb = 312.27 ± 191.78Nm.s-1 vs. uninjured limb = 518.54 ± 172.81Nm.s-1, p=0.008; IMP, injured limb = 0.73 ± 0.30 Nm.s vs. uninjured limb = 0.97 ± 0.23 Nm.s, p=0.005) and 100ms (RTD, injured limb = 280.03 ± 131.42Nm.s-1 vs. uninjured limb = 460.54.54 ± 152.94Nm.s-1,p=0.001; IMP, injured limb = 2.15 ± 0.89 Nm.s vs. uninjured limb = 3.07 ± 0.63 Nm.s, p<0.001) after the onset of contraction. Biceps femoris long head muscle activation was lower at 100ms at both contraction speeds (-600.s-1, normalised iEMG activity (x1000), injured limb = 26.25 ± 10.11 vs. uninjured limb 33.57 ± 8.29, p=0.009; -1800.s-1, normalised iEMG activity (x1000), injured limb = 31.16 ± 10.01 vs. uninjured limb 39.64 ± 8.36, p=0.009). Medial hamstring activation did not differ between limbs in the injured group. Comparisons in the uninjured group showed no significant between limbs difference for any variables. Conclusion: Previously injured hamstrings displayed lower rate of torque development and impulse during slow maximal eccentric contraction compared to the contralateral uninjured limb. Lower myoelectrical activity was confined to the biceps femoris long head. Regardless of whether these deficits are the cause of or the result of injury, these findings could have important implications for hamstring strain injury and re-injury. Particularly, given the importance of high levels of muscle activity to bring about specific muscular adaptations, lower levels of myoelectrical activity may limit the adaptive response to rehabilitation interventions and suggest greater attention be given to neural function of the knee flexors following hamstring strain injury.

The 'variety effect' is anticipated in meal planning

The 'variety effect' describes the greater consumption that is observed when multiple foods with different sensory characteristics are presented either simultaneously or sequentially. Variety increases the amount of food consumed in test of ad libitum intake. However, outside the laboratory, meals are often planned in advance and then consumed in their entirety. We sought to explore the extent to which the variety effect is anticipated in this pre-meal planning. Participants were shown two food images, each representing a first or a second course of a hypothetical meal. The two courses were either, i) exactly the same food, ii) different foods from the same sensory category (sweet or savoury) or, iii) different foods from a different sensory category. In Study 1 (N = 30) these courses comprised typical ‘main meal’ foods and in Study 2 (N = 30) they comprised snack foods. For each pair of images, participants rated their expected liking of the second course and selected ideal portion sizes, both for the second course and the first and second course, combined. In both studies, as the difference between the courses (from (i) same to (ii) similar to (iii) different) increased, the second course was selected in a larger portion and it was rated as more pleasant. To our knowledge, these are the first studies to show that the variety effect is evident in the energy content of self-selected meals. This work shows that effects of variety are learned and anticipated. This extends our characterisation beyond a passive process that develops towards the end of a meal.

Self-gifting guilt : an examination of self-gifting motivations and post-purchase regret

Purpose Self-gifting is a performative process in which consumers purchase products for themselves. The literature to date remains silent on a determination and connection between the extents of post-purchase regret resulting from self-gifting behavior. The purpose of this paper is to examine identification and connection of self-gifting antecedents, self-gifting and the effect on post purchase regret. Design/methodology/approach This study claims the two antecedents of hedonistic shopping and indulgence drive self-gifting behaviors and the attendant regret. A total of 307 shoppers responded to a series of statements concerning the relationships between antecedents of self-gifting behavior and the effect on post-purchase regret. Self-gifting is a multi-dimensional construct, consisting of therapeutic, celebratory, reward and hedonistic imports. Confirmatory factor analysis and AMOS path modeling enabled examination of relationships between the consumer traits of hedonistic shopping and indulgence and the four self-gifting concepts. Findings Hedonic and indulgent shoppers engage in self-gifting for different reasons. A strong and positive relationship was identified between hedonic shoppers and reward, hedonic, therapeutic and celebratory self-gift motivations. hedonic shoppers aligned with indulgent shoppers who also engaged the four self-gifting concepts. The only regret concerning purchase of self-gifts was evident in the therapeutic and celebratory self-gift motivations. Research limitations/implications A major limitation was the age range specification of 18 to 45 years which meant the omission of older generations of regular and experienced shoppers. This study emphasizes the importance of variations in self-gift behaviors and of post-purchase consumer regret. Originality/value This research is the first examination of an hedonic attitude to shopping and indulgent antecedents to self-gift purchasing, the concepts of self-gift motivations and their effect on post-purchase regret.

Anticipated user experience in the early stages of product development

This research investigates users' anticipation of their future experiences with interactive products to support design for experience in the early stages of product development. This research generates new knowledge of anticipated user experience (AUX), which reveals users' tendency to perceive the pragmatic quality of products as the main determinant of their positive future experiences. The AUX Framework has been an important outcome of this study. The exploration of the components of this framework allows a better prediction and understanding of users' underlying needs and potential usage contexts valuable for the early design phases.

India's vocational education capacity to support the anticipated economic growth

The buoyancy that the Indian economy experienced between 2000 and 2010, in spite of the global downturn of 2008, is no longer a reality. Growth projections for 2012-13 have been reassessed to 6.5 per cent. This is still higher than most other developed economies of the world (see Figure 1.1), however the growth rate is slowing. The World Bank in its recent forecasts1 expects India’s growth rates not to extend beyond 7.2 % and 7.4 % in the years 2013-14 and 2014-15, respectively. Similarly, the Planning Commission has scaled down the growth target for the 12th Five Year Plan (2012-17) from 9% to 8%. Different reports note different rates, but the consistent message is that the projection of India’s economy is on a downward trend...

The Pareto regret frontier

Performance guarantees for online learning algorithms typically take the form of regret bounds, which express that the cumulative loss overhead compared to the best expert in hindsight is small. In the common case of large but structured expert sets we typically wish to keep the regret especially small compared to simple experts, at the cost of modest additional overhead compared to more complex others. We study which such regret trade-offs can be achieved, and how. We analyse regret w.r.t. each individual expert as a multi-objective criterion in the simple but fundamental case of absolute loss. We characterise the achievable and Pareto optimal trade-offs, and the corresponding optimal strategies for each sample size both exactly for each finite horizon and asymptotically.

Surrogate Regret Bounds for Bipartite Ranking via Strongly Proper Losses

The problem of bipartite ranking, where instances are labeled positive or negative and the goal is to learn a scoring function that minimizes the probability of mis-ranking a pair of positive and negative instances (or equivalently, that maximizes the area under the ROC curve), has been widely studied in recent years. A dominant theoretical and algorithmic framework for the problem has been to reduce bipartite ranking to pairwise classification; in particular, it is well known that the bipartite ranking regret can be formulated as a pairwise classification regret, which in turn can be upper bounded using usual regret bounds for classification problems. Recently, Kotlowski et al. (2011) showed regret bounds for bipartite ranking in terms of the regret associated with balanced versions of the standard (non-pairwise) logistic and exponential losses. In this paper, we show that such (non-pairwise) surrogate regret bounds for bipartite ranking can be obtained in terms of a broad class of proper (composite) losses that we term as strongly proper. Our proof technique is much simpler than that of Kotlowski et al. (2011), and relies on properties of proper (composite) losses as elucidated recently by Reid and Williamson (2010, 2011) and others. Our result yields explicit surrogate bounds (with no hidden balancing terms) in terms of a variety of strongly proper losses, including for example logistic, exponential, squared and squared hinge losses as special cases. An important consequence is that standard algorithms minimizing a (non-pairwise) strongly proper loss, such as logistic regression and boosting algorithms (assuming a universal function class and appropriate regularization), are in fact consistent for bipartite ranking; moreover, our results allow us to quantify the bipartite ranking regret in terms of the corresponding surrogate regret. We also obtain tighter surrogate bounds under certain low-noise conditions via a recent result of Clemencon and Robbiano (2011).