McFadden Aurora Kinase cancer innovatively introduced the “utility theory” of economics into transportation and proposed a new logit mode called the “random utility model” [21, 22]. Domencich presented a discrete choice

model based on “maximum utility theory” and then further divided the disaggregate model into the logit model family and the probit model family, based on which a theoretical system of the disaggregate model was gradually formed [23]. Ben-Akiva, Lerman, and Vovsha further introduced the theory into traffic demand forecasting, conducting deep research into the transportation division problem and pushing the logit model into the practical application stage [24, 25]. By analyzing individuals’ unobserved and observed preferences and characteristics, Bhat used the multinomial logit model (MNL) to describe the personal preference for transportation and analyzed individuals’ travel mode choice behavior under different service levels [26]. In economics, it is assumed that consumer preferences

can be represented by a continuous utility function, which can be mathematically proved. According to random utility theory, travelers will choose the travel mode at their perceived maximum utility in a specific situation. According to random utility theory, the utility function U consists of nonrandom and random parts as follows: Uin=Vin+εin, (1) where Uin is the utility function of the alternative travel mode i(i = 1,2,…, J) of traveler n(n = 1,2,…, N); Vin is the nonrandom part of the utility function; and εin is the random part of the utility function, which are submitted to Gumbel distribution and independent from each other. Traveler n would choose i if and only if Uin>Ujn, i≠j,  i,j∈An, (2) where An is the set of all possible travel mode choices of traveler

n. According to maximum utility theory, the probability that traveler n will choose travel mode i is denoted as Pin as follows: Pin=ProbUin>Ujn;i≠j, i,j∈An=ProbVin+εin>Vjn+εjn;i≠j, i,j∈An, (3) where 0 ≤ Pin ≤ 1, ∑i∈AnPin = 1. 4. Data and Application 4.1. Sample, Predictor, and Data Processing This paper chooses Tangshan as the sample city. Tangshan is a medium-sized city located in North China, the economic development level, city size, and traffic conditions of which are in the intermediate state. There is no subway in Tangshan, and motorcycles have been banned from the urban district. The set of alternative travel modes available for residents is denoted as GSK-3 A: A = i∣i = 1, walking; i = 2, bicycle; i = 3, electricbicycle; i = 4, bus;i = 5, taxi; i = 6, privatecar. Field investigation by questionnaire survey is conducted to find the factors affecting the travel mode choice. Thirteen possible factors of personal characteristics, family-owned private travel tool characteristics, and travel characteristics are the assumed variables (k is the number of variables; k = 1,2,…, K, K is the total number of variables), which are presented in Table 1.

McFadden Docetaxel ic50 innovatively introduced the “utility theory” of economics into transportation and proposed a new logit mode called the “random utility model” [21, 22]. Domencich presented a discrete choice

model based on “maximum utility theory” and then further divided the disaggregate model into the logit model family and the probit model family, based on which a theoretical system of the disaggregate model was gradually formed [23]. Ben-Akiva, Lerman, and Vovsha further introduced the theory into traffic demand forecasting, conducting deep research into the transportation division problem and pushing the logit model into the practical application stage [24, 25]. By analyzing individuals’ unobserved and observed preferences and characteristics, Bhat used the multinomial logit model (MNL) to describe the personal preference for transportation and analyzed individuals’ travel mode choice behavior under different service levels [26]. In economics, it is assumed that consumer preferences

can be represented by a continuous utility function, which can be mathematically proved. According to random utility theory, travelers will choose the travel mode at their perceived maximum utility in a specific situation. According to random utility theory, the utility function U consists of nonrandom and random parts as follows: Uin=Vin+εin, (1) where Uin is the utility function of the alternative travel mode i(i = 1,2,…, J) of traveler n(n = 1,2,…, N); Vin is the nonrandom part of the utility function; and εin is the random part of the utility function, which are submitted to Gumbel distribution and independent from each other. Traveler n would choose i if and only if Uin>Ujn, i≠j,  i,j∈An, (2) where An is the set of all possible travel mode choices of traveler

n. According to maximum utility theory, the probability that traveler n will choose travel mode i is denoted as Pin as follows: Pin=ProbUin>Ujn;i≠j, i,j∈An=ProbVin+εin>Vjn+εjn;i≠j, i,j∈An, (3) where 0 ≤ Pin ≤ 1, ∑i∈AnPin = 1. 4. Data and Application 4.1. Sample, Predictor, and Data Processing This paper chooses Tangshan as the sample city. Tangshan is a medium-sized city located in North China, the economic development level, city size, and traffic conditions of which are in the intermediate state. There is no subway in Tangshan, and motorcycles have been banned from the urban district. The set of alternative travel modes available for residents is denoted as Carfilzomib A: A = i∣i = 1, walking; i = 2, bicycle; i = 3, electricbicycle; i = 4, bus;i = 5, taxi; i = 6, privatecar. Field investigation by questionnaire survey is conducted to find the factors affecting the travel mode choice. Thirteen possible factors of personal characteristics, family-owned private travel tool characteristics, and travel characteristics are the assumed variables (k is the number of variables; k = 1,2,…, K, K is the total number of variables), which are presented in Table 1.

A direct comparison of HRQoL in patients who are considered progr

A direct comparison of HRQoL in patients who are considered progression-free with those patients who experience tumour growth is often limited. Several investigators have assessed the relationship between HRQoL and tumour response in patients with breast, mTOR activity colorectal and renal cell cancer,7–10 and suggest that patients who remain on treatment and who experience delayed progression have a stable HRQoL or experience a less rapid decline

in HRQoL than patients whose tumours are progressing. To the best of our knowledge, no data have been reported in non-small cell lung cancer (NSCLC). Two RCTs investigated the role of afatinib, an irreversible ErbB Family Blocker, in NSCLC and included assessment of patient-reported symptoms and HRQoL in addition to tumour progression: LUX-Lung 1 (NCT00656136)11 12 and LUX-Lung 3 (NCT00949650).13 14 The analyses reported here use data collected in these trials to investigate HRQoL in patients before and after progression, and to explore the relationship between tumour progression and HRQoL. Two different statistical analysis methods were used in order to assess the strength of the findings. Patients and methods Study design This analysis used data from two RCTs.12 14 Key details of the methodology and findings of these trials are summarised in table 1. Table 1 Summary of trial

design and results of LUX-Lung 111 12 and LUX-Lung 313 14 Health-related quality of life assessment HRQoL was assessed using the self-administered cancer-specific European Organization for Research and Treatment of Cancer (EORTC) multidimensional core questionnaire QLQ-C30.15 QLQ-C30 comprises of 30 questions of multi-item and single-item measures. Individual

items are scored on a four-point scale, while Global health status (question 29) and quality of life (QoL, question 30) are scored on a seven-point scale. For the purpose of this analysis, the QLQ-C30 Global health status/QoL (composite of QLQ-C30 questions 29 and 30) score was used to evaluate patients’ overall self-reported HRQoL. The EuroQol disease-generic questionnaire, comprising the EQ-5D overall utility and EQ-visual analogue scale (VAS),16 Cilengitide was used to assess health status. The EQ-5D measures five dimensions of health (mobility, self-care, usual activities, pain/discomfort and anxiety/depression). Utility scores range from 0 to 1 and were calculated from the five EQ-5D item scores using the UK valuation algorithm.17 The EQ VAS records the patient’s self-rated health status on a vertical graduated (0–100) VAS. In LUX-Lung 1, HRQoL questionnaires were scheduled at randomisation, two weekly during the first 2 months of treatment and then every 4 weeks. In LUX-Lung 3, HRQoL was assessed at randomisation and every 21 days. For chemotherapy patients, this was on day 1 of each cycle and was delayed if the chemotherapy was delayed.

20 In both trials, the HRQoL assessments were comprehensi

20 In both trials, the HRQoL assessments were

comprehensive, providing a strong basis for evaluating the relationship between HRQoL and disease progression. Differences in the findings of the ANCOVA results between LUX-Lung 1 and LUX-Lung 3 may reflect the fact that clinically meaningful ATM inhibitor review changes in HRQoL may be harder to achieve in heavily pretreated patients such as those included in LUX-Lung 1. While the findings reported here indicate that disease progression is accompanied by a statistically significant worsening of HRQoL, it should also be considered whether the results represent a clinically meaningful change in HRQoL. There is continued debate as to what constitutes a meaningful change in oncology HRQoL scores, with data suggesting that patients are more responsive to improvement than decline,22 and that the thresholds for clinically significant improvement and decline are not always uniform.23 While a 10-point change in an individual patient’s EORTC QLQ-C30 item or domain is an accepted threshold for clinically meaningful improvement,24 different thresholds have been proposed for intergroup changes for individual QLQ-C30 QOL scales.25 For the QLQ-C30 Global health status/QoL scale, a mean difference of 0–4 points represents a trivial effect, 4–10 point difference represents a small but clinically

important effect and a 10–15 difference represents a moderate effect.25 These thresholds for QLQ-C30 Global health status/QoL imply that most of the findings reported here are clinically meaningful. For the EQ-5D UK Utility and EQ VAS scores, changes of 0.06–0.11 and 7–12 points, respectively, have been suggested to represent a minimally important difference,26 27 although there is no established consensus on how best to determine the minimally important difference in HRQoL measures.26 Using these values as a guide, some of the changes observed in our study should be considered

clinically meaningful. Brefeldin_A Limitations should be considered. As more HRQoL assessments were conducted up to the time of progression, and fewer at follow-up visit(s) following progression, limited data were available on the health state of patients with progression; this is a common limitation of this type of analysis.4 Further evaluation of HRQoL in these patients may have revealed more pronounced differences in HRQoL between patients with and without progression. Of the two trials, LUX-Lung 3 had more HRQoL data after progression than LUX-Lung 1, indicating that the results from analysis of LUX-Lung 3 data are potentially more robust. Accounting for, and minimising the impact of missing data (which are often not missing at random as assumed here) is an important factor in analyses such as ours.

In most (merged) context related patient groups, however, there i

In most (merged) context related patient groups, however, there is no proportional selleck chem distribution of patients (records) over the distinct parts of the day. A plausible explanation is that the professional interventions that affect the course of childbirth are spread unevenly over a 24 h day.12 This applies first, to referrals from the first line to the second line during labour, and second, to the augmentation of labour under the supervision of the second or third line. This explains why the number

of patients who reach the second stage of labour during daytime while being supervised by an obstetrician in the second/third line is proportionally greater than during the evening/night. Under these conditions, one cannot assume that the actual risk profiles of the ‘daytime group’ and the ‘evening/night group’ within the same (merged) context related patient group are equal to each other (figure 2). To complicate matters, the absolute numbers of adverse outcomes on which the differences in relative incidence are based usually are very small. Thus a simple calculation shows that, in the most recent time period, the ‘night/day difference’ in the relative incidence of perinatal mortality in the total group of (about 40) non-teaching hospitals (RR 1.17)

corresponds to three cases on an annual basis. Perhaps this is a good reason to consider the introduction of a new outcome variable that better matches the desired outcome of childbirth, for example: mother and child back home (in good health) within 1 week after birth. Shifts between (merged) context related patient (sub)groups not only occur within a certain time period, but also in successive periods. Often these shifts are the result of new professional insights, standards and habits that lead to other referral patterns and/or interventions. Examples include the changed

obstetric policy at breech presentations and at post-term pregnancies. With these types of changes over time the effect on the actual risk profile of the (merged) context related group can be assessed with reasonable accuracy. It is therefore Cilengitide easier to interpret a difference in the relative incidence of adverse outcomes by means of longitudinal comparisons than by means of transversal comparisons. Conclusion The complexity of the obstetric care system is not only the result of the multifactorial and dynamic character of the professional organisational contexts in which births take place. The size and the risk profile of the patient groups that are functionally related to these contexts are also in constant flux. This dynamic is to a large extent determined by professional intervention, at patient and also at policy level. All this makes it virtually impossible to demonstrate fixed patterns in the relationships between the separate contextual factors and the (adverse) outcomes of births.

1 Children born to mothers who have smoked

1 Children born to mothers who have smoked sellectchem during pregnancy are more susceptible to respiratory infections and asthma,2 and more likely to experience learning and cognitive development disorders.3 These and the increased risks

of other chronic diseases throughout childhood4 mean that women who are pregnant and smoking are strongly advised to quit. However, many continue to smoke during and beyond pregnancy, putting themselves and their children at risk.5 6 Women who smoke while pregnant often have fewer qualifications, come from poorer communities where smoking is more prevalent,7–9 and experience a reduced urgency to quit.4 10 11 Because smoking is entrenched in some communities, women often see other women smoking while pregnant, and may themselves have been born to smokers.12 The reported harms of smoking during pregnancy may diverge from their own experiences and the absence of overt or perceived harm may imply that continued smoking does not inevitably harm unborn children.12–14 Women who smoke while pregnant (or who smoke following the birth of their child) may also see quitting as segregating them from social networks at the very

time they would like greater support,6 15 and report that smoking fosters social interactions, provides respite from monotonous jobs and represents opportunities to relax.5 11 16–20 Promoting the health risks of smoking during pregnancy may thus fail to trigger quit attempts because the distal risks smokers perceive as uncertain fail to outweigh the proximal benefits they receive.8 21 Cessation messages must decrease the value placed on smoking as a reward, offer alternatives, challenge the myths and self-exempting beliefs pregnant

smokers construct, and provide stimuli that prompt and support quit attempts.9 22 They must balance the risk that dissonance inducing messages promote reactance and counter-argument rather than action, and leave behaviour more ingrained.23 Dissonance and reactance Conflicting beliefs and behaviours create tension that may promote behaviour GSK-3 change as individuals try to align their thoughts, feelings and actions to reduce discord.24 Smokers may experience dissonance in social settings, where smoking has become increasingly unacceptable, and when reflecting on the harm smoking causes to themselves or others.25 The resulting unease may provide a powerful stimulus that potential cessation messages could utilise. However, while cognitive dissonance should logically foster quit attempts, behaviour change is not always straightforward, even when dissonance is high and uncomfortable. For example, addicted smokers may struggle to quit, despite wishing to become smoke-free.13 26 Tensions caused by discrepancies between smokers’ beliefs, a desire to quit and continued smoking may become acute among women who are pregnant and smoking.

The dramatic clinical response to TNFi could have resulted in inc

The dramatic clinical response to TNFi could have resulted in increased awareness and changing perceptions of physicians towards AS. Our data thus do not support the notion that MRI use has resulted in changing gender ratios in the diagnosis of AS. A sharp drop in incidence of AS in males above 65 years kinase inhibitor Lenalidomide was noted from 1995 to 2002, with no significant decrease in female AS incidence in the same age group (see online supplementary figure S1). In the early part of the study some prevalent cases could have been identified wrongly as incident

cases. However, a 36-month look-back period was included in the design to reduce this possibility. Earlier diagnosis of AS in males could have resulted in this shift in age group of incident cases but this was not reflected in an increase in the proportion of patients with AS diagnosed in the younger age groups (see online supplementary figures S1 and S2). Earlier diagnosis and longer survival could have resulted in the increase in prevalence of AS despite stable incidence rates. It is well known that diagnostic delays are higher in female patients with AS.30 A higher proportion of male patients in our study were diagnosed in the 15–45 year age group and this remained stable throughout the follow-up period (see online supplementary figure S2). The increase in female patients with AS seen from early 2000 onwards was reflected in an increasing proportion of female patients

with AS being diagnosed in the 45–65 year age group. Our study is not designed to answer whether this reflects later onset of disease or delay in diagnosis of female patients with AS.

Increased awareness of SpA in early 2000 could have led to the diagnosis of female patients with AS who were symptomatic for several years. This is a health database-based study, one limitation is that the data can only provide information on patients who had access to healthcare providers. We could not study the effect of HLA-B27 on the incidence and prevalence of AS due to the lack of availability of these data from the ICES databases. In addition, some patients with AS could have been misdiagnosed as chronic back pain and wrongly classified. The diagnosis of AS was not based on the modified New York criteria but on a diagnostic algorithm including physicians’ billing codes. Physicians might have used the same code to identify patients with other forms of SpA including nr-axSpA. Diagnostic algorithms utilising health administrative AV-951 data and the ICD-9 code-based definition have been18 25 31 validated.25 But the ICD-9 code 720 for AS has been validated only in the Veterans Affairs healthcare system in the USA.25 The use of one ICD-9 code of 720 has high sensitivity (91%) and specificity (99%) for identifying individuals with AS.25 Compared with the Quebec study that used this algorithm, we used a much stricter algorithm with two billing codes that has 100% specificity for a diagnosis of AS.

Each focus group consisted of 7–9 physicians working in the PHC a

Each focus group consisted of 7–9 physicians working in the PHC as family medicine specialists, residents or general practitioners using the same EMR system since 2008. The characteristics of the focus group participants are reported in table 1. Table 1 Characteristics of physicians Each focus group consisted of a mix of males and females

of different age groups and professional experience. Several themes www.selleckchem.com/products/AG-014699.html emerged from the focus groups about the implementation of the EMR (table 2). The main themes were categorised as physician issues, patient issues and system (Cerner) issues. These categories of main themes were arrived at through consensus during analysis of the focus group transcripts after the interviews. Participants repeatedly referred to or mentioned these themes during their discussions. Table 2 Summary of themes of all focus groups Physician-dependent factors The initial impression of physicians In general, physicians spoke favourably about the EMR system implementation, for example, “I think that, I do believe that my first impression was so amazing” (FG1), but all remarked that the beginning was difficult,

for example, “At the beginning, as anything when you use it for the first time, it will look complex until you get familiar to the system” (FG3). Computer skills They believed that computer skills had a major role in understanding the EMR as they mentioned that old generation physicians were slower in typing and learning new tricks. There is a difference in competency among physicians in dealing with technology, for example, “Old generation doctors, whom I respect a lot of course, let’s say there is a urine culture results, they don’t know that there is a click where you can get the susceptibility” (FG1). Another example, “if

you don’t know like Alt and C is copying and Alt and V is pasting, (it takes) for a lot of people it causes a lot of difficulties” (FG2). “For me for example if I want to explain something for the patient in anatomy, instead of drawing I will just enter the Google and the patient will be very happy: ohm, this is how it look, this is how the Batimastat anatomy. And when you want to illustrate the disease process through pictures the patient will be very happy.” It was also useful to provide the patient with very useful educational materials. The training Physicians appeared to have various opinions about the training period. Some were completely satisfied, for example, “It was sufficient, the training was good, of course the training itself to how to deal with computer at the beginning start in a good way” (FG3), while others were not satisfied and expressed that they were not aware of some facilities available in the EMR system, for example, “How to order everything at the start was very clear and comprehensive in the training part but when we start on the note part the training was not sufficient, in my opinion” (FG3).

Table 2 Test–reliability based on intraclass correlation coeffici

Table 2 Test–reliability based on intraclass correlation coefficient for Hausa IPAQ-LF, overall and selleck chem by gender Similarly, socioeconomic status differences were observed in the reliability coefficients of the modified

IPAQ-LF (table 3). Across all domains of PA, reliability coefficients were substantially higher among participants with less than secondary school education (ICC from 0.77 (sitting activity) to 0.92 (leisure activity)) compared to those with secondary school education (ICC from 0.28 (active transport) to 0.58 (occupational activity)) and those with higher than secondary school education (ICC from 0.23 (sitting activity) to 0.67 (active transport)). While reliability coefficients were higher for overall PA (ICC=0.80, 95% CI 0.71 to 0.86), active transport (ICC=0.83, 95% CI 0.74 to 0.88), occupational PA (ICC=0.79, 95% CI 0.70 to 0.86) and leisure-time PA (ICC=0.79, 95% CI 0.69 to 0.85) among participants who were employed compared to their unemployed counterparts, it was higher for domestic PA (ICC=0.65, 95% CI 0.43 to 0.79) and sitting time (ICC=0.68, 95% CI 0.36 to 0.83) among participants who were unemployed than

in the employed subgroup. Table 3 Socioeconomic status differences in test–retest reliability of the Hausa IPAQ-LF (N=180) Figures 1–3 (Bland-Altman plots) illustrate the agreement in the scores (min/week) of total PA, MVPA and sitting between the first and second administrations of Hausa IPAQ-LF. For total PA, the mean difference was 106.7 min/week, with wide 95% limits of agreement (−762.2 to 965.6 min/week). For MVPA, the mean difference was about one and half hours per week (91.6 min/week), and also demonstrating wide 95% limits of agreement (−744.5 to 927.7 min/week). For sitting time, the mean difference was small (26 min/week) and the 95% limits of agreement ranged from −2178.1 to 2230.9 min/week. Figure 1 Bland-Altman plot min/week reported

in total physical activity (PA) for the first and second administrations of Hausa IPAQ-LF. Mean difference: 106.7±2 SD=−762.2 to 965.6. Figure 2 Bland-Altman plot min/week reported in moderate-to-vigorous physical activity (MVPA) for the first and second administrations AV-951 of Hausa IPAQ-LF. Mean difference: 91.6±2 SD=−744.5 to 927. Figure 3 Bland-Altman plot min/week reported in sitting for the first and second administrations of Hausa IPAQ-LF. Mean difference: 26.4=±2 SD=−2178.1 to 2230.9. Table 4 shows the patterns of PA across sociodemographic subgroups during the first (IPAQ1) and second (IPAQ2) administrations of the modified IPAQ-LF. Overall and across all stratified variables, time spent in PA reported during the first administration tends to be higher than that reported during the second administration. At both time points, men reported significantly (p<0.05) higher mean time (min/week) in active transportation, occupational PA and leisure-time PA than women.

5 Consequently, in order to enhance the utility of IPAQ and to fu

5 Consequently, in order to enhance the utility of IPAQ and to further evaluate its psychometrics worldwide, efforts have been made to translate and adapt the IPAQ in many other countries, but most of the research in this context were from developed Western countries.7–14 In Africa, the psychometric selleck chem properties of IPAQ have only been tested in South Africa as part of the initial development process of the questionnaire,5 and in older adults.15 Since the largest increases and burden

of non-communicable diseases (NCDs) are in low-income countries where the understanding of evidence-based strategies for increasing PA remains poor,16–19 improving PA research is a top priority for them.20 However, to advance PA research in Africa, it is important to first develop or tailor standardised measures to be culturally sensitive to PA behaviours of people in the region’s countries. Since Nigeria is the most populous country in Africa with culture and languages similar to most of the other West

African countries, it is a good choice to evaluate the IPAQ for cultural and psychometric relevance in this country. Recently, a cultural adaptation study of the IPAQ-SF was conducted among adults in Nigeria,21 with good evidence of test–retest reliability similar to findings in some other studies.10 22–24 However, because the IPAQ-SF is not domain specific and does not provide context-specific information on PA behaviour, it is important to evaluate the IPAQ-LF for relevance in Nigeria. Psychometric evaluation of a culturally modified version of the IPAQ-LF in sub-Saharan African

countries can impact PA research and surveillance in the African region where the prevalence of inactivity related NCDs is on the increase.20 25 The aim of the present study was to investigate the reliability and an aspect of validity of a modified version of the IPAQ-LF among adults in Nigeria. Methods Participants A purposive sample of 180 adults from eight neighbourhoods that varied in socioeconomic status and walkability in Maiduguri city were recruited for the study. The sampling and neighbourhood selection strategy have been described in detail elsewhere.26 Maiduguri, with an estimated population of 749 123 people, is the capital and largest city of Borno State in North-Eastern Brefeldin_A Nigeria.27 The city attracts immigrants from neighbouring countries of Cameroon, Niger and Chad Republic and the Hausa language is the common means of communication for commercial activities among the diverse inhabitants of Maiduguri.27 28 Participants were eligible for this study if they were willing to self-complete a written survey twice in either Hausa or English language. However, researchers (UMB and STP) were in attendance to provide translation and interpretation assistance to participants (n=11) who required help to complete the survey.