An Expectancy-Value approach to investigate socio-cognitive determinants of speeding among adolescent powered two-wheeled riders in Vietnam.

Speeding increases the likelihood and severity of road traffic crashes, but many riders do not consider speeding as a serious safety issue. By using belief-based variables derived from the Theory of Planned Behaviour (i.e. behavioural beliefs, normative beliefs, and control beliefs), this study investigated the socio-cognitive determinants of speeding intentions among Vietnamese adolescents operating motorized/electrified two-wheelers. 189 adolescent powered two-wheeled riders in Ho Chi Minh City participated in a cross-sectional survey. The results lend clear support to the Expectancy-Value approach since belief-based product factors (e.g. outcome beliefs x outcome evaluations) significantly and independently contributed to the prediction of speeding intentions. Speeding intentions were mostly influenced by behavioural beliefs, followed by normative beliefs and control beliefs, respectively. This study not only proves the Expectancy-Value approach as an appropriate framework for the investigation of speeding intentions but also supports authorities in the formulation and execution of more effective interventions for reducing speeding among adolescent powered two-wheeled riders in Vietnam. Instead of motivation-oriented methods, there is a need for strategies that stimulate the translation of good intentions into the desirable behaviour, and encourage adolescents not to relapse in case they are exposed to risk facilitating circumstances. Yet, besides focussing on person-specific dispositions towards speeding, policy makers are advised to adopt a more broadly encompassing systemic approach with inclusion of safe roads, safe vehicles, improved post-crash care, and shared stakeholder responsibilities.

Identification of beliefs determining wrong lane riding intentions among Vietnamese adolescent two-wheeled riders: An Expectancy-Value approach.

INTRODUCTION: In Vietnam, road traffic crashes are one of the leading causes of death and serious injury in adolescents, especially in the 15-19-year age group. Wrong lane riding (WLR) is seen as the most common risky behavior of adolescent two-wheeled riders. This study (a) tested the expectancy-value model held to underpin the key determinants of behavioral intention (i.e., attitude, subjective norm, perceived behavioral control) as proposed by the Theory of Planned Behavior, and (b) identified appropriate targets for road safety interventions. METHOD: A cluster random sample of 200 adolescent two-wheeled riders in Ho Chi Minh City participated in a cross-sectional study designed to measure the variables of interest (i.e., behavioral beliefs, normative beliefs, control beliefs, and intention towards wrong lane riding). RESULTS: The results of hierarchical multiple regression lend clear support for the expectancy-value theory as an approach to model the different belief components behind the key determinants of behavioral intention. CONCLUSION: Road safety interventions aimed at reducing WLR among Vietnamese adolescent two-wheeled riders would best target both the cognitive and the affective components of attitude, subjective norm, and perceived behavioral control. Interestingly, the sample investigated in this study is rather negatively predisposed toward WLR. PRACTICAL APPLICATIONS: It is recommended to further strengthen and stabilize these safety-oriented beliefs, and to develop the required implementation intentions to guarantee that the appropriate goal intentions in terms of WLR are translated into action. More research is needed to see whether the commission of WLR can also be explained in function of a reactive pathway, or is exclusively under volitional control.

Understanding walking activity in multiple sclerosis: step count, walking intensity and uninterrupted walking activity duration related to degree of disability.

In multiple sclerosis (MS), physical activity (PA) is most commonly measured as number of steps, while also walking intensity and walking activity duration are keys for a healthy lifestyle. The aim of this study was to investigate (1) the number of steps persons with MS (PwMS) take; (2) the number of steps they take at low and moderate intensity; and (3) their walking activity duration for 2, 3, 6, 10, 12 and 14 uninterrupted minutes; all related to the degree of disability. 64 PwMS participated, distinguished in a mild (n = 31) and moderate MS subgroup (n = 34) based on their ambulatory dysfunction (Disease Steps). Standardized clinical tests were performed, and step data from the StepWatch Activity Monitor were collected for seven consecutive days. The results showed that (1) step count in PwMS was lower than PA recommendations, and is negatively influenced by a higher disability degree. (2) No walking was registered during 77 % of the day. PwMS are making steps for 22 % at low and only 1 % at moderate intensity. (3) Both MS subgroups rarely walk for more than six uninterrupted minutes, especially not at moderate intensity. PwMS need to be encouraged to make steps at moderate intensity, and to make steps for longer periods of time (minimal ten uninterrupted minutes).

Documenting outdoor activity and travel behaviour in persons with neurological conditions using travel diaries and GPS tracking technology: a pilot study in multiple sclerosis.

OBJECTIVE: Persons with multiple sclerosis (PwMS) experience several physical and cognitive problems which can influence their travel behaviour. This study aimed to document the number of activities, the activity type and the transport mode of the related trips that are daily made by PwMS. Their outdoor activity and travel behaviour was studied in relation to disease-related disability. METHODS: Thirty six PwMS (Expanded Disability Status Scale, EDSS, 1.5-8.0, age 27-63) and 24 healthy controls (age 25-62) were studied, using activity-related travel diaries and GPS tracking devices. Information about overall disability characteristics was gained by standard clinical tests and questionnaires. PwMS were further divided in three subgroups based on EDSS cut-off scores 4.5 and 6.5. RESULTS: Persons with mild ambulatory dysfunction (EDSS 1.5-4.0, n = 17) showed similar travel characteristics to healthy controls, with few restrictions during travelling. Statistically significant changes in activity and travel behaviour were detected in the moderate (EDSS 4.5-6.5, n = 8) and severe MS subgroups (EDSS > 6.5-8.0, n = 11) compared with healthy controls: driving independently became less frequent, significant more trips were made with company and the duration of performed activities had increased. CONCLUSION: The combination of self-reported travel diaries and objective GPS loggers offered detailed information about the actual outdoor travel behaviour of PwMS, which was significantly changed in PwMS with EDSS greater than 4. Implications for Rehabilitation Activity and travel behaviour changes significantly in persons with multiple sclerosis (MS) with moderate to severe disability (EDSS greater than 4). Behavioural therapy could help to develop better coping and problem-solving skills to overcome anxiety in the making of trips by persons with MS with a mild severity. Enhancing community environments could serve as a promising approach to increase the outdoor participation of persons with (more severe) impairments.

The contribution of activity-based transport models to air quality modelling: a validation of the ALBATROSS-AURORA model chain.

The potential advantages of using activity-based transport models for air quality purposes have been recognized for a long time but models that have been developed along these lines are still scarce. In this paper we demonstrate that an activity-based model provides useful information for predicting hourly ambient pollutant concentrations. For this purpose, the traffic emissions obtained in a previous application of the activity-based model ALBATROSS were used as input for the AURORA air quality model to predict hourly concentrations of NO(2), PM(10) and O(3) in the Netherlands. Predicted concentrations were compared with measured concentrations at 37 monitoring stations from the Dutch air quality monitoring network. A statistical analysis was performed to evaluate model performance for different pollutants, locations and time periods. Results confirm that modelled and measured concentrations present the same geographical and temporal variation. The overall index of agreement for the prediction of hourly pollutant concentrations amounted to 0.64, 0.75 and 0.57 for NO(2), O(3) and PM(10) respectively. Concerning the predictions for NO2, a major traffic pollutant, a more thorough analysis revealed that the ALBATROSS-AURORA model chain yielded better predictions near traffic locations than near background stations. Further, the model performed better in urban areas, on weekdays and during the day, consistent with the emission results obtained in a previous study. The results in this paper demonstrate the ability of the activity-based model to predict the contribution of traffic sources to local air pollution with sufficient accuracy and confirms the usefulness of activity-based transport models for air quality purposes. The fact that the ALBATROSS-AURORA chain provides reliable pollutant concentrations on hourly basis for the whole Netherlands instead of using only daily averages near traffic stations is a plus for future exposure studies aiming at more realistic exposure analyses and health impact assessments.