4. Numerical Application 4.1. Data Description The studied incident dataset was obtained from the Incident Reporting selleck product and Dispatching System (IRDS) for the Beijing metropolitan area, which covers all kinds of roads. The IRDS database in the traffic control center contains all types of incidents that were reported to the control center, regardless of whether the common incident response units (i.e., traffic police) had responded to these incidents. According to previous studies [4, 27, 35], the roads where incidents occur have significant influences on traffic incident duration, presumably because of various road characteristics

and other unobserved factors. However, at present, we are unable to acquire detailed information on all of the roads in Beijing. Therefore, in this study, only the incident data for the 3rd Ring Road mainline are chosen to aid in reducing the influence of different roads on traffic incident duration time. From the IRDS database, the time of different incident duration phases can be calculated, including preparation time, travel time, clearance time, and total time, which is the sum of the first three phases. The final studied incident dataset contains 2851 incident records for a one-year period (2008), with each incident duration phase being equal to or greater than one minute. Table

1 provides the summary statistics information for the incident dataset used in this study. Table 1 Statistics information of the incident dataset. The positive skewness value, as well as the minimum, maximum, and mean values, indicates that the tail on the right of all four of these distributions is longer than that on the left side; that is, the distributions are right long tailored. The higher kurtoses of the different duration phase data mean that much of the variance is the result of infrequent extreme deviations, suggesting that infrequent extreme values are present in the dataset.

Taking travel time as an example, the longest travel time is 245min, but the second longest is only 114min. Such outliers can present difficulties both in developing estimated models and in predicting duration time. Some candidate variables related to temporal characteristics, incident and traffic condition, and so on, can be Cilengitide extracted from the IRDS. This study analyzes the variables affecting traffic incident duration time to develop incident duration time prediction models, which would be helpful in incident management. Therefore, this study considered and used only specific candidate variables (shown in Table 2) that can be obtained immediately after an incident has been reported to the traffic control center. Table 2 Candidate variables. As mentioned above, traffic incident duration includes four time intervals [6].

In the context of traffic incident duration, specific hazard distributions are suggested by empirical and theoretical analyses using different incident datasets with different supplier Linsitinib incident types and locales. Previous studies have noted various distributions of incident duration, such as log-normal distribution, log-logistic distribution, Weibull distribution, and generalized F distribution. Studies have revealed that the distribution of incident durations can be viewed as log-normal [20, 21]. A different study [5] that focused

on the South Korean freeway system indicated that log-normal is an acceptable, but not the best, distribution for traffic durations. Other researchers have found that the log-logistic distribution is best for traffic incident duration/clearance time. Jones et al. [30] used AFT models with log-logistic distribution on freeway incident records in Seattle to investigate the factors affecting traffic incident duration time. Chung [31] used the log-logistic

AFT model to develop a traffic incident duration time prediction model; the resulting mean absolute percentage error (MAPE) showed that the developed model can provide a reasonable prediction based on a two-year incident duration dataset drawn from the Korea Highway Corporation on 24 major freeways in Korea. Using another dataset obtained from the Korea Highway Corporation, the log-logistic AFT model has also been used to analyze the critical factors affecting incident duration [5]. Qi and Teng [32] developed an online incident duration prediction model based on a log-logistic AFT model. Hu et al. [33] used a log-logistic AFT model to predict incident duration time for in-vehicle navigation systems based on Transport Protocol Experts Group data in London and obtained a reasonable result. Wang et al. [29] estimated traffic duration times by using a log-logistic AFT model based on traffic

incidents occurring on a freeway in China. The Weibull distribution has also been used in previous studies. Nam and Mannering [4] studied Carfilzomib three duration phases (i.e., detection/reporting, response, and clearance times), and the results revealed that the Weibull AFT model with gamma heterogeneity is appropriate for detection/reporting and response time, whereas the log-logistic AFT model is appropriate for clearance time. Kang and Fang [34] used the Weibull AFT model to predict traffic incident duration time in China. To test the goodness of fit, Alkaabi et al. [35] used the Weibull AFT model without gamma heterogeneity to analyze traffic incident clearance time in Abu Dhabi, United Arab Emirates. Tavassoli Hojati et al.

Reviews of cognitive

behavioural therapy (CBT) for adolescent depression have shown that it is effective and currently one of the main treatment options recommended in adolescents.2 8 Trials comparing CBT to either family therapy or supportive psychotherapy show that it is better at both improving mood and achieving remission.9 Seliciclib clinical trial It has also been shown to prevent depression in high-risk adolescent groups including the offspring of depressed adults.10 Since it has a low side effect profile it is an attractive alternative option for the treatment of adolescent depression. However, some studies have questioned its efficacy in young people with moderate to severe depression, questioning how powerful a treatment it is.7 11 The 1 year prevalence of depression in adolescents is about 2%.12 An area with a population of 300 000, such as that served by the York and Selby Community Adolescent Mental Health Service (CAMHS), would be expected to have at least 450 young people

with depression. Delivering CBT to this number of young people is far more resource intensive in terms of time than using medication. Many primary care doctors are referring all young people directly in to CAMHS rather than managing them in primary care, as they are reluctant to use medication and do not have the time or experience to deliver psychological therapy. Most primary care counsellors are not trained to counsel adolescents. This creates an additional pressure in CAMHS. Together with other service pressures, this leads to long waiting

lists in CAMH services in some areas. As a result, it is unlikely that individual CBT needs can be met from existing therapist resources.13 This therefore presents a number of challenges to services, including demands on clinical time, the potential development of waiting lists and issues about prioritisation of services. Given the affinity young people have with information technology, it may be that young people could be treated effectively and more widely using CCBT and at an Entinostat earlier stage in the evolution of their illness. The Improving Access to Psychological Therapies (IAPT) programme was introduced to improve availability of therapies and specifically mentions the use of CCBT in relation to depression. CCBT represents an alternative form of therapy delivery, which has the potential to enhance access to CBT and to provide a realistic alternative therapy or potentially a preventive intervention early in the course of depressive illness. Some argue that many adolescents, often reluctant to engage one to one with a therapist, may be more comfortable accessing computerised material or therapy. CCBT comes in many forms and can be directed at a range of conditions and age groups, but adequate research needs to be conducted to capture this broad range of possible new therapies.

This would most likely include face-to-face CBT, family therapy, medication and in some instances admission to hospital. This is a pragmatic trial and no participants will be denied access to additional treatments

and services (offered under SCH66336 price routine NHS care) by virtue of participating in this trial. Both arms in the trial will also receive care as usual and this could include any of the following. These will be monitored and recorded for each participant: Local counselling services (eg, youth enquiry and support services; tier 1). Primary mental health worker support (tier 1). Individual supportive therapy or brief psychosocial interventions (tier 2). Individual CBT (tier 2). Psychiatric referral (tier 2). Family therapy (tier 3). Group work for self-harm or depression (tier 3). In-patient admission (tier 4). Medication (while medication is not currently

recommended in this group, we will monitor whether any professional prescribes). Procedure Participants in the CCBT group will complete eight sessions of the Stressbusters programme lasting approximately 45 min (with homework between sessions) at a private and user-friendly location. Participants using self-help websites on low mood will be offered equivalent time to access the websites in the same settings. Participants will be given a choice of setting to participate including CAMH clinic sites, schools, a GP surgery or a local community centre. A member of the research team will meet all participants at each of their sessions to provide them with instructions. During the sessions the researcher will wait outside of the room where the session takes place but will remain in close proximity to assist participants if they have any difficulties and answer any

questions. It will be explained to all participants that care as usual will be available to them. For example each school and primary care practice will have a primary mental health worker (PMHW) who will liaise to ensure that any professional who has concerns about any young person can discuss their concerns and make a referral if necessary. PMHWs can provide up to four sessions of support or refer individuals on to an accessible member of the specialist Drug_discovery CAMHS team if necessary. They will also provide consultation to other professionals supporting the young people as usual where necessary (eg, school nurses, school counsellors or mentors, school tutors, Young People Advisory Service workers and other relevant professionals). PMHWs will be able to access tier 2 and tier 3 professionals at any time urgently or non-urgently in the usual way by direct referral through a central allocation system weekly or through a daily ‘duty clinician’ system or an urgent on call psychiatry system, as appropriate.

All authors provided final approval of the version to be published. Funding: This systematic review is supported by the Canadian Anesthesia Research Foundation and the Canadian Institutes of Health Research. Competing

interests: DEM and AP are chair and member, respectively, of the Canadian Pain Society Guideline Committee for management of chronic neuropathic pain. DEM has received research grant funding selleck chemical from Pfizer Canada, and has received honoraria for educational presentations from Jansenn-Ortho, Lilly, Purdue Pharma and Merck-Frosst. Provenance and peer review: Not commissioned; externally peer reviewed.
Obesity (OB) has become a disease of epidemic proportions.1 However, this increasing tendency towards excess weight in childhood and adulthood2 observed in some countries (the UK, France, South Korea, the USA and Spain) has stabilised despite the absolute rates being a cause for concern.1 OB prevalence in children and adolescents is higher in southern regions of Europe.3 4 Accumulation of fat tissue constitutes an increased disease risk in childhood,

as well as in adulthood.5 This disease risk has a multifactorial aetiology, such as an unhealthy diet and sedentary lifestyle.6 7 The Organization for Economic Co-operation and Development (OECD) has predicted an increase of 7% in excess weight prevalence in adulthood over the period spanning 2010 to 2020.8 The WHO proposes the prevention and control of OB prevalence as key in the updated ‘Action Plan 2008–2013’ in which effective health promotion is considered as the principal strategy.9 Since excess weight status in adulthood is almost invariably predicated on childhood and adolescent weight, OB prevention should start early in life.10 The optimum age to start an intervention is between the ages of 7 and 8 years because children are more receptive to guidance.11 The school is an ideal place for the promotion of healthy nutrition and lifestyle habits12 and, as some studies have shown, such interventions have inspired changes in nutritional habits and body mass index

(BMI) status13 14; the message is received by all schoolchildren, irrespective of ethnic and socioeconomic differences.9 The effectiveness of an intervention is when educational strategies and environmental factors such as healthy nutrition and physical activity AV-951 (PA) habits coincide since both aspects are essential in preventing childhood OB.15 Currently, European children spend more of their leisure time in sedentary activities such as watching television (TV), video games or on the internet. These activities represent a decrease in physical movement and lowering of energy expenditure and, as such, are risk factors for OB.16 We had designed the EdAl (Educació en Alimentació) programme as a randomised, controlled, parallel study applied in primary schools, and implemented by university students acting as Health Promoter Agents (HPAs).

Although selleck kinase inhibitor messages arousing strong negative affect were consistently seen as more effective across all ethnicities, participants preferred less didactic messages: “like it

doesn’t say that you should quit- like it’s not so—‘oh you’re a bad mum—you’re smoking—you know you should stop smoking’—it’s kind of saying that you do have a choice.” These messages offered non-judgemental support, stressed quitting was a positive personal choice, and maintained participants’ autonomy: “It’s-it’s saying like ‘when you’re ready’ not like somebody trying to push you to it—to quit….Just with the fact that there’s um—freedom of choice…. You know. It’s your choice. It’s not like somebody nagging at-on you.” However, while participants often resented being advised to quit, they saw messages that appealed to their autonomy as less effective and were more likely to counter-argue these. For example, one message suggested children’s spaces, such as playgrounds, should be smoke-free: “if I was there [in a smokefree playground] I’d be way over there away from them smoking so it wouldn’t really affect them. Like that’s my mind working it out. There’s nothing too bad about it.” These rationalisations typically privileged participants’ rights: “In a way I agree but in a way I don’t because basically that’s taking away your right to like,

example, smoke in your own home…, it’s taking away your rights.” Cognitive appeals almost invariably led participants to assert their rights over those children might enjoy, and some reacted strongly against initiatives that they thought would curtail these perceived

rights. Although participants were much more likely to counter-argue rational messages than negative-affect messages, even the latter still provoked some psychological reactance. Women who had not made a quit attempt since becoming pregnant were more likely to offer rationalisations that enabled them to minimise the risk of smoking and the harm that could result: “With my first two I gave up smoking, and then my sister was smoking when she had her baby and her baby came out perfect, so when I had my third one I was smoking….and she’s all right.” Some also queried the inevitability of harm Cilengitide or attributed harm to other causes: “Some mothers—no matter not smoking—they still have prem [premature] babies, you know.. like I said, smoking isn’t the only cause to—for this particular thing.” Nevertheless, even the minority advancing these rationalisations felt unsettled by the images shown, which they conceded were disturbing. Discussion Participants recognised smoking was harmful and, despite strenuous efforts to assert they chose to smoke, most regretted smoking while pregnant and nearly all had attempted to quit. Their comments revealed tensions between the belief they chose to smoke, the addiction that undermined this belief, and the potential consequences they tried to rationalise.

Ethnicity was subsequently removed as its inclusion inhibitor price did not have an appreciable effect on the result, and its removal appeared to make the model more robust with narrower CIs. For birth weight, the same potential confounders were considered

together with gestational age and smoking during pregnancy. The following variables were significantly associated with the outcome (indicated by Wald, p<0.05) after controlling for other factors in the model: gestational age, education, ethnicity and maternal age. As smoking during pregnancy is likely to be in the causal chain of low birth weight, the model was considered with and without this variable to see to what extent the effect on birth weight is mediated by smoking. The ‘unexposed’ group was used as the reference for these analyses. For univariable analysis, those with missing outcomes of smoking during pregnancy, low birth weight and any breastfeeding following birth were excluded (7 (0.04%), 21 (0.1%) and 4 (0.02%), respectively); all these excluded women were from the 18 201 ‘unexposed’ group. However, 726 women were excluded due to missing data on symptoms of depression (Malaise Inventory score). Women who had been in care were not more likely to have missing

data in this variable than those who had not been in care. In those who had spent some of their childhood in care, 11 of the 291 women had missing data (3.9%). There were no statistically significant differences between those who had missing data and those who did not in terms of age, income, social class and education. Of the women who had not spent any time in care, 715 of the 18 201 women had missing data for symptoms of depression (4.0%). Those who

had missing data were more likely to be in a lower social class, have a lower income and to have lower or no qualifications. For multivariable analysis, a complete case analysis was undertaken. Those excluded due to missing data were less than 10% of the cohort, with resulting sample size ranging from 16 351 to 18 238 (table 4). Table 4 Unadjusted and adjusted ORs (95% CI) for smoking during pregnancy, low birth weight, any breastfeeding and symptoms of depression among mothers according to a history of being in care All analyses took into account the clustered stratified study design by using the survey commands in Stata V.13.0.35 Reported p values and CIs account for clustering, and estimates of proportions and ORs are weighted by sampling weights.36 Results Description of the Entinostat cohort There were 18 552 respondents of the baseline interview of the Millennium Cohort Study. Fifty-seven respondents, who were not the natural mothers of the cohort baby, were excluded, as were three interviewees who did not have data relating to their time in care history. Therefore, our study population included 18 492 natural mothers. In the study population, there were 291 mothers who reported spending time in care as a child, which was 1.6% of the cohort (95% CI 1.3 to 1.8).

14 Many physicians were pleased

about the orders and results of laboratory and radiology as they emphasised that this is the strongest point in the EMR system. They were also happy about the electronic prescription because it reduced errors and saved time. selleck catalog In a survey conducted by Robert et al,15 including 2719 family physicians in the USA, the respondents highlighted the advantages of the EMR which were almost similar to our findings. Their respondents stated that they were pleased with the EMR system since it was fast, easy to use, well documented, more precise and provided patient engagement tools such as the patient education resources and patients’ portal.15 However, American College of Physicians (ACP) and American EHR Partners conducted a survey reporting that physician dissatisfaction with the EMRs increased from 24% in 2010 to 39% in 2012. The reasons provided by the respondents for their dissatisfaction with the EMR was that the system was expensive and

was not significantly reducing their workload.16 They mentioned that computer skills had a major effect on understanding the EMR. In the literature review, computer literacy was identified as a major barrier to the implementation of the EMR. There was a finding that only emerged in the second focus group due to the presence of a physician who was previously exposed to the auditing process. The researchers were of the impression that physicians perceived the EMR as a significant threat when it was used to audit the physicians for documentation and patient confidentiality, for example, “the medical record do regular audit and find out, for example, why the chart has been opened”. Another example, “part of annual appraisal of the physicians is the (audio unclear) we have about eight competencies one of them is the documentation

and we usually audit at least 10 to 20 task for each physician and all the important factors the presenting symptom, the history of present illness the past medical history… we do for audit and this is why the physician are keen to have a complete or as much as we can about full documentation.” Physicians had a negative perception that they were monitored for their performance through the Cerner, which created Dacomitinib some discomfort during the session. This finding was not commonly identified in our literature review except in one study where the respondent reported the feedback as personal criticism.15 It is important to ensure that during the implementation of a new system, like the Cerner, users should be informed about the purpose of the use of the system and also about the auditing tool and the purpose of use of audits to allay fears and negative perceptions. The confidentiality issue was added to the moderators guide as a focus group questions after it emerged as a theme in the first focus group.

Where there was a choice of outcome measures, the outcome chosen was the primary behavioural outcome measure specified by the thereby authors, measured by the most objective means (eg, accelerometer data were preferred to

self-reported minutes of physical activity) and adjusted for baseline differences if this had been seen as necessary by the authors. Synthesis of results Data from included studies were meta-analysed in RevMan (V.5.2) using random effect models. For outcomes where a reduction (eg, mean percentage calories in fat) signifies a change in a healthy direction, data were reverse-scored before being entered for meta-analysis. For continuous diet and physical activity outcomes, standardised mean differences (SMD) were calculated using Hedges’ g28 to express the difference between the means for the intervention and control groups in SD units. For dichotomous smoking outcomes, we calculated relative risk (RR) of smoking abstinence and applied the Cochran-Mantel-Haenszel test.29 Where studies had multiple comparisons (several intervention arms or reported outcomes for different behaviours) or were cRCTs, we adjusted participant numbers in line with Cochrane recommendations where possible.30 We conducted meta-analyses for the three behaviours separately at two time points: the most proximal

time point postintervention and the longest follow-up time point where reported. A 95% CI was used and p<0.05 was taken as significant. We assessed variation in effect size between studies using the I2 statistic, with an I2 >50% interpreted as indicating the presence of heterogeneity.27 Following

Cochrane Handbook recommendations,30 we compared independent subgroups of studies differing for two clinically relevant characteristics: interventions targeting women only versus a mixed sex sample, and interventions targeting a single behaviour versus multiple behaviours. Publication bias was assessed by visually inspecting funnel plots. Results Study selection A flow diagram is presented in figure 1. We identified 3939 references from the database search (including the updated search: numbers for this search are given in figure 1) along with the 13 studies identified in Michie et al’s23 review. After removing 1383 duplicates Dacomitinib and excluding 2439 references on the basis of title and abstract screening 130 full texts were screened, of which 120 full texts were successfully retrieved, as 8 articles had no full text and 2 were irretrievable. Full-text screening initially led to the inclusion of 32 studies. Three further studies were identified from title screening reference sections, so that 35 studies with 45 comparisons met inclusion criteria.25 31–71 Figure 1 Study selection flow diagram (italics signify numbers from July 2014 updated search).

This is the first study in an African country to explore the cultural adaptation and translation of the IPAQ-LF, and its findings sellekchem demonstrated the feasibility of using the IPAQ-LF to reliably collect PA data in a diverse segment of the Nigerian population. In the Africa region, the importance of a valid and established PA scale such as the modified IPAQ-LF is not only important to monitoring the domain in which activity is performed, but also very critical to understanding studies of ecological models of health behaviours

that emphasise the importance of multiple levels of influence on health behaviours including PA.18 42 In Nigeria, emerging evidence from studies using ecological models indicate that favourable built environmental attributes are promising for improving total and moderate-to-vigorous PA and controlling obesity among adults.26 43–45 However, built environment characteristics are expected to be strongly related to specific PA types rather than overall PA.46 47 For example, different environmental variables can be related to walking for leisure or transportation and to moderate PA for household, occupation, recreation or transportation. Thus, a study of adaptation of the IPAQ-LF is very important to understanding the domain-specific nature of ecological model research in the African region. One additional strength was the exploration

of PA patterns by gender, educational level and employment status, the findings of which were consistent with general hypothesis on social patterns of inactivity in low-income countries.20 48 However, the findings of

this study should be interpreted in the light of some important limitations. Direct comparison of our validity findings with previous studies should be made with caution, because unlike in our study, the accelerometer or PA diary were utilised as a common objective criterion standard to validate the IPAQ in the majority of the studies.5 7 8 24 30 33 39 Thus, examining the construct validity through the relationships of PA with BMI and resting blood pressure was an important limitation of our study. The choice and availability of appropriate criterion measures are particular issues of concern for the validation of PA questionnaires in low-income countries of Africa.5 49 50 Despite these issues, the validity coefficients in our study were remarkably similar to those reported in other studies,5 7 8 24 30 33 39 and the consistency of items on IPAQ with variables Cilengitide known to be related to PA, such as BMI, blood pressure, heart rate, indicators of lipid and glucose metabolism and fitness index have previously been used as important construct validity measures.7 10 21 24 Another limitation of the study is the use of non-probability sampling technique. The study finding may have limited generalisability to other samples of Nigerians that have different characteristics from this sample.