Background Non-attendance at diabetes outpatient appointments is a sizeable problem worldwide and has been associated with suboptimal health outcomes. We aimed to describe the characteristics, health outcomes and reasons given for non-attendance at doctor-or nurse-led diabetes appointments, and interventions to improve attendance. Methods PubMed, EMBASE, CINAHL and PsychInfo were searched from database inception to February 2019. Included articles were peer-reviewed, published in English, related to adults or young people with type 1 or type 2 diabetes, and addressed one of the above aspects of non-attendance. Studies were excluded if reporting on other types of diabetes or reviewing attendance at structured education, retinal screening, paediatric, antenatal, podiatry or dietetic clinics. Results Thirty-four studies of varied designs were identified (15 observational, 1 randomized control trial, 9 qualitative, 5 surveys, 4 service improvements). The definition of non-attendance varied. Younger adults, smokers and those with financial pressures were less likely to attend. Non-attendance was associated with higher HbA 1c ; other outcomes were varied but typically worse in non-attenders. Reasons for non-attendance in qualitative studies fell into three categories: balancing the costs and benefits of attendance, coping strategies, and the relationships between the person with diabetes and healthcare professionals. Interventions included appointment management strategies, service improvements, patient navigators and WebCam appointments. Conclusions Non-attendance is only partially explained by logistical issues. Qualitative studies suggest complex psychosocial factors are involved. Interventions have progressed from simple appointment reminders in an attempt to address some of the psycho-social determinants, but more work is needed to improve attendance.

Implementation intentions have the potential to break unwanted habits and help individuals behave in line with their goal intentions. We tested the effects of implementation intentions in the context of drivers' speeding behavior. A randomized controlled design was used. Speeding behavior, goal intentions and theoretically derived motivational pre-cursors of goal intentions were measured at both baseline and follow-up (one month later) using self-report questionnaires. Immediately following the baseline questionnaire, the experimental (intervention) group (N=117) specified implementation intentions using a volitional help sheet, which required the participants to link critical situations in which they were tempted to speed with goal-directed responses to resist the temptation. The control group (N=126) instead received general information about the risks of speeding. In support of the hypotheses, the experimental group reported exceeding the speed limit significantly less often at follow-up than did the control group. This effect was specific to 'inclined abstainers' (i.e., participants who reported speeding more than they intended to at baseline and were therefore motivated to reduce their speeding) and could not be attributed to any changes in goal intentions to speed or any other measured motivational construct. Also in line with the hypotheses, implementation intentions attenuated the past-subsequent speeding behavior relationship and augmented the goal intention - subsequent speeding behavior relationship. The findings imply that implementation intentions are effective at reducing speeding and that they do so by weakening the effect of habit, thereby helping drivers to behave in accordance with their existing goal intentions. The volitional help sheet used in this study is an effective tool for promoting implementation intentions to reduce speeding.

Attitudes are typically treated as unidimensional predictors of both behavioural intentions and subsequent behaviour. On the basis of previous research showing that attitudes comprise two independent, positive and negative dimensions, we hypothesized that attitudes would be bi-dimensional predictors of both behavioural intentions and subsequent behaviour. We focused on health-risk behaviours. We therefore also hypothesized that the positive dimension of attitude (evaluations of positive behavioural outcomes) would better predict both behavioural intentions and subsequent behaviour than would the negative dimension, consistent with the positivity bias/offset principle. In Study 1 (cross sectional design), N = 109 university students completed questionnaire measures of their intentions to binge-drink and the positive and negative dimensions of attitude. Consistent with the hypotheses, both attitude dimensions independently predicted behavioural intentions and the positive dimension was a significantly better predictor than was the negative dimension. The same pattern of findings emerged in Study 2 (cross sectional design; N = 186 university students) when we predicted intentions to binge-drink, smoke and consume a high-fat diet. Similarly, in Study 3 (prospective design; N = 1,232 speed limit offenders), both the positive and negative dimensions of attitude predicted subsequent (6-month post-baseline) speeding behaviour on two different road types and the positive dimension was the better predictor. The implications for understanding the motivation of behaviour and the development of behaviour-change interventions are discussed.

We tested the prototype willingness model (PWM). The participants (N=198) completed online questionnaire measures of PWM constructs (time 1) and subsequent speeding behaviour (time 2). Path analyses showed that the PWM accounted for 89% of the variance in subsequent (self-reported) speeding behaviour. This significantly exceeded the variance accounted for by the theory of planned behaviour. In line with the PWM, both behavioural intention and behavioural willingness had direct effects on behaviour. Behavioural willingness had a significantly larger effect. Attitude and subjective norm both had indirect effects on behaviour through both behavioural intention and behavioural willingness. Prototype (similarity) perceptions had indirect effects on behaviour through behavioural willingness only. The findings support the notion that driving is governed by reactive decision-making (willingness), underpinned by prototype perceptions, attitudes and subjective norms, to a greater extent than it is deliberative decision-making (intentions), underpinned by attitudes and subjective norms. The implications for safety interventions are discussed