[15]. They found external situational impact factors and verified the rationality. In recent years, a comprehensive analysis selleckchem named the Scheme for the Comparative Analysis of Public Environmental Decision-Making (SCAPE) has been developed [16]. The basic idea is that since we cannot understand

every person exactly, why not take individuals as a black box with a system opinion and build a model based on input and output to identify the relationship between behavior and motivations? 2.2. Influencing Factors of Travel Mode Choice Understanding the influencing factors of proenvironmental travel behavior and their individual influencing path is the prerequisite for the scientific development of transportation decision-making and intervention strategies. The factors that influence proenvironmental travel can be divided into individual characteristics, social characteristics, and situational variables. In practice, behavioral change theory prevails to promote the voluntary reduction of car use and a shift to proenvironmental travel, of which some classic economic indicators (such as prices and taxes) and land use, transportation network, and behavior-oriented traffic systems have always been welcomed

[17, 18]. Understanding individual travel decision making is considered the key to promoting large-scale change in proenvironmental travel by public policy and education. The quality of the public transport service, travel characteristics, and personal characteristics are confirmed to exert a significant impact on travel choices [19]. Researchers usually choose factors (variables) according to the purpose of specific research topic and considering the difficulties in data collecting. In this paper, we mainly considered the following aspects when selecting variables as done in similar research: (1) the variables group should effectively express the main relationship between travel decision and factors; (2) when satisfying the first consideration,

a feasible and economical investigation should be taken into our consideration. 3. Model Traditionally, aggregate models were always used to study the influence of psychological variables, but when attempting to investigate the influence of some situational factors, a disaggregate model will be more appropriate. The main reason is that the situational factors can be measured although they Anacetrapib are varied, while psychological variables cannot be measured directly, although they are relatively stable [20]. The basic assumption of the disaggregate model is that when travelers are faced with travel mode choices, the “utility value” of choices can be used to describe travelers’ preference for each travel mode. Utility is the function of the selected object’s properties and the decision makers’ characteristics. The disaggregate model is based on utility maximization theory and random utility theory.

[15]. They found external situational impact factors and verified the rationality. In recent years, a comprehensive analysis TBC-11251 structure named the Scheme for the Comparative Analysis of Public Environmental Decision-Making (SCAPE) has been developed [16]. The basic idea is that since we cannot understand

every person exactly, why not take individuals as a black box with a system opinion and build a model based on input and output to identify the relationship between behavior and motivations? 2.2. Influencing Factors of Travel Mode Choice Understanding the influencing factors of proenvironmental travel behavior and their individual influencing path is the prerequisite for the scientific development of transportation decision-making and intervention strategies. The factors that influence proenvironmental travel can be divided into individual characteristics, social characteristics, and situational variables. In practice, behavioral change theory prevails to promote the voluntary reduction of car use and a shift to proenvironmental travel, of which some classic economic indicators (such as prices and taxes) and land use, transportation network, and behavior-oriented traffic systems have always been welcomed

[17, 18]. Understanding individual travel decision making is considered the key to promoting large-scale change in proenvironmental travel by public policy and education. The quality of the public transport service, travel characteristics, and personal characteristics are confirmed to exert a significant impact on travel choices [19]. Researchers usually choose factors (variables) according to the purpose of specific research topic and considering the difficulties in data collecting. In this paper, we mainly considered the following aspects when selecting variables as done in similar research: (1) the variables group should effectively express the main relationship between travel decision and factors; (2) when satisfying the first consideration,

a feasible and economical investigation should be taken into our consideration. 3. Model Traditionally, aggregate models were always used to study the influence of psychological variables, but when attempting to investigate the influence of some situational factors, a disaggregate model will be more appropriate. The main reason is that the situational factors can be measured although they Dacomitinib are varied, while psychological variables cannot be measured directly, although they are relatively stable [20]. The basic assumption of the disaggregate model is that when travelers are faced with travel mode choices, the “utility value” of choices can be used to describe travelers’ preference for each travel mode. Utility is the function of the selected object’s properties and the decision makers’ characteristics. The disaggregate model is based on utility maximization theory and random utility theory.

The protocol for both studies required that patients completed HRQoL questionnaires in the

clinic using an electronic portable data capture tool before they were provided with any test results by their treating physicians or any other health professional. Assessment of tumour progression Hesperidin ic50 Tumour assessments were performed by CT or MRI. In LUX-Lung 1, tumour assessments were undertaken at baseline and every 4 weeks until week 12, and then every 8 weeks until disease progression by independent review. In LUX-Lung 3, tumour assessments were undertaken at baseline and every 6 weeks for the first 48 weeks and then every 12 weeks thereafter until disease progression by independent review or start of new anticancer therapy. RECIST criteria were used for independent review, which was conducted by a central imaging group that included radiologist and oncologist reviewers blinded to treatment assignments; investigators also assessed tumour progression based on radiological

and clinical assessment in both studies. In LUX-Lung 3, the primary end point was based on independent review. Independent review is regarded as the most conservative approach and is recommended in RECIST guidelines.18 19 Statistical analyses The statistical methods used in this analysis were prespecified. For the main analyses, randomised treatment

groups were combined in order to increase the numbers of patients available. Additional subgroup analyses were conducted to assess consistency of results between groups. To be included in analysis, patients had to have completed a baseline assessment and at least one measurement at the time of tumour progression or follow-up assessment. A HRQoL assessment was considered valid for inclusion in the statistical analysis if it occurred within ±7 days of the date of tumour assessment. In the event there was more than one HRQoL assessment, the one nearest the actual tumour assessment date was used. For patients who progressed, only the first HRQoL assessment was used; after that they were censored for future time points. In the longitudinal analysis, all HRQoL assessments at, or after progression, were used but were censored at the start of any new anticancer Brefeldin_A therapy. Assessments that were carried out after the start of other subsequent cancer treatment following progression were excluded. All analyses were conducted using data from independent review and investigator assessment of tumour progression. Statistical programming was carried out using S-Plus. Analysis of covariance The hypothesis for this analysis was that patients with and without progression at any time would have different average levels of QoL.

13 In both trials, compliance with questionnaire completion was high over the duration of treatment in each trial (LUX-Lung 1, 65–100%; LUX-Lung 3, >90%), which helps to reduce concern of bias due to missing data; however, attrition was greater in the control arms, with the main cause being disease progression, potentially resulting in bias. We Ganetespib STA-9090 do not consider missing data due to attrition an issue in these analyses,

because we explicitly compare HRQoL in patients with and without progression at each assessment time (ANCOVA analysis), as well as assessing change in HRQoL due to progression within patients (longitudinal model); therefore, the effect of attrition should only be to reduce sample size at each assessment. Furthermore, both studies extensively evaluated the impact of missing data through sensitivity analyses and found that differences in HRQoL questionnaire completion were unlikely to bias the findings of either study. A limitation associated with all statistical methods that estimate the effect of progression is that the comparison is non-randomised (as in an observational study) leading to potential bias. This potential bias was limited in the ANCOVA analysis by using covariate adjustment, while within patient comparisons in the longitudinal model avoided bias as long

as the piecewise linear model is correct. For ANCOVA as well as longitudinal analyses, data from active and control treatment arms were pooled, which assumes that the effect of progression on HRQoL is independent of treatment. While this may be a potential source of bias, the ANCOVA model included a term for treatment as a covariate, and estimates of treatment-specific effects of progression from mixed-effects longitudinal models did not suggest that this was the case. It should be considered that these findings

are specific to the type of patients with NSCLC enrolled in LUX-Lung 1 and LUX-Lung 3 and may not generalise to other patient types. Finally, adverse events associated with afatinib treatment have the potential to impact on specific HRQoL items11 Dacomitinib 13 and thus have a confounding effect on the results reported here. However, there were few grade 3/4 toxicities, which were confounded with assessments of progression and when these effects were included in longitudinal models the effects of progression on HRQoL were only slightly reduced (data not shown). Additionally, the HRQoL measures used in these analyses (EORTC Global Health/QoL, EQ-5D UK Utility and EQ VAS) measure global health and thus would likely reflect the effects of drug toxicity. Taking these points into consideration, we do not believe drug toxicity is an important confounding factor in our analyses. The demonstration of a relationship between PFS and HRQoL in patients with lung cancer has important implications for healthcare policy decision-making, among others, in patients with NSCLC.

However, obstetrics is not practiced at the macro level. We should therefore consider complementing macro-level evaluations selleck bio with parallel evaluations at the meso level. Here, too, our integral descriptive model could play a useful role. Supplementary Material Author’s manuscript: Click here to view.(3.5M, pdf) Reviewer comments: Click here to view.(245K, pdf) Acknowledgments The authors thank the Netherlands Perinatal Registry for permission

to use the registry data. They especially thank Chantal Hukkelhoven and Leanne Houweling for their help in extracting the data from the Netherlands Perinatal Registry. They also thank Paul van der Linden, Hans Merkus, Mathieu Weggeman and Ruud Jonkers for their critical remarks on the key concept of their study and on the manuscript. Footnotes Contributors:

LH and HS initiated and coordinated the study. LH coordinated data collection and performed quality control of data. HS designed the key concept. Both authors actively participated in interpreting the results and revising the paper. Funding: This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. Competing interests: LH has been president of the board of the Netherlands Perinatal Registry until October 2013. Provenance and peer review: Not commissioned; externally peer reviewed. Data sharing statement: No additional data are available.
Chronic neuropathic pain is defined as “pain arising as a direct consequence of a lesion or disease affecting the somatosensory system.”1 It may be classified as central or peripheral, depending on the site of the lesion.2 Among the causes of chronic neuropathic pain are metabolic disease (eg, diabetes), infection (eg, shingles), trauma (eg, spinal cord injury) and autoimmune disease (eg, multiple sclerosis).3–5 The pain may be spontaneous or evoked in response to physical stimuli. The latter may manifest as increased sensitivity to pain (hyperalgesia) or as a painful response to a stimulus that would not normally be painful (allodynia).4 6 Chronic neuropathic pain is common worldwide, affecting 7% to 10% of the general population.7 It

is associated with depression, anxiety and sleep disturbances, and patients with chronic neuropathic pain experience lower health-related quality of life than the general population.8–11 Chronic neuropathic pain is associated with substantial economic burden. Tarride et al12 estimated that managing a Canadian patient with chronic Batimastat neuropathic pain over a 3-month period costs an average of $2567, of which 52% are direct costs, for example, cost of physicians, diagnostic tests and surgical procedures. Others report that people suffering from chronic neuropathic pain generate medical costs that are three times greater than those not living with pain.11 13 In the USA alone, almost $40 billion annually in healthcare, disability and related costs is attributed to chronic neuropathic pain.

Differentiating direct from indirect admissions based solely on where the patient was initially admitted may introduce bias if no criterion is specified for the upper limit of the interval between arrival at the ED and admission to the Crenolanib manufacturer MICU/HDU.

There is no universally accepted duration which determines that a patient’s condition is not expected to deteriorate to a point that transfer to the MICU/HDU becomes necessary soon after admission to the general ward. However, for this study, the 24 h upper limit from ED presentation to MICU/HDU admission was used as it was considered a reasonable interval during which a non-critical patient admitted to the general ward is expected to remain stable. In the multivariate analysis, MICU and HDU patients were analysed as a single group as analysing them separately would have substantially reduced the sample size. While the magnitude of effects may differ between the two groups, bivariate results suggested similar directions of effect for MICU and HDU patients analysed separately. This study validates previously published findings that indirect ICU admissions or delays lead to adverse patient outcomes. While the direction of effect may be consistent across settings, variations in the magnitude

of effect may be affected by factors such as differences in ICU bed capacity, the profile of patients served, organisational procedures and standards, as well as physician characteristics. For this reason, the estimated risk of adverse outcomes in one setting will not necessarily apply to another, thus highlighting the usefulness of conducting similar studies in one’s own context. These self-assessments enable emergency and ICU departments to customise improvements based on their unique situations. It also facilitates performance

monitoring by providing a baseline measure of the adverse consequences of indirect admissions, against which future results may be compared. Supplementary Material Author’s manuscript: Click here to view.(1.2M, pdf) Reviewer comments: Click here to view.(144K, pdf) Footnotes Contributors: ES, BHH and BH conceived the study. ES and BH facilitated and provided access to the data. All the authors designed the study. JADM and WFC designed and supervised data collection. Carfilzomib JADM supervised data management and quality control and also analysed the data and drafted the manuscript. ES and BHH monitored the study’s progress. All authors provided peer review and substantial inputs to the final form of the manuscript. Funding: This study was internally funded by the Emergency Department, Tan Tock Seng Hospital. Competing interests: None. Ethics approval: The research was approved by the Domain Specific Review Board of the National Healthcare Group (Singapore) Provenance and peer review: Not commissioned; externally peer reviewed. Data sharing statement: No additional data are available.

Another population-based study from Quebec, Canada, presented data on the prevalence of AS between 1996 and 2006.18 The reported incidence sellectchem and prevalence rates were 11.5/100 000 person years and 140/100 000 population, respectively. The diagnosis was established on the basis of one physician claim based on the diagnostic code of AS (ICD-9 code: 720.0). The incidence and prevalence estimates of our study are higher than the Quebec study despite using more stringent criteria for diagnosis of AS. We defined AS based on two physician billing claims for the ICD-9 code 720 over 2 years, with at least one claim by

a rheumatologist or at least one hospitalisation record. Table 2 Comparison of various studies that assessed the incidence and prevalence of ankylosing spondylitis The population of Ontario is very diverse in terms of ethnicity and genetic background. Our extensive literature review reveals a clear need to conduct large population-based studies in Europe and Asia to obtain true estimates of the disease burden. Though there have been similar studies in the past, these attempts were based on cross-sectional studies or rates calculated

from hospital or clinic records and such estimates may be less accurate.13–17 19 There is growing concern about the financial and medical burden imposed on society by changing diagnostic and treatment paradigms of AxSpA. Of major concern is the potential overutilisation of MRI in the diagnosis of AxSpA and inappropriate use of TNFi for treating patients with mechanical back pain. There is immense interest in understanding the effect of these changing trends on the overall diagnosis and prevalence of AxSpA. It has been well understood for some time that all patients with AxSpA may not have classic X-ray changes of AS. Classification criteria for AxSpA that include the entity

non-radiographic axial SpA (nr-AxSpA) were established recently with the first TNFi trial in nr-AxSpA published in 2008.26 27 Classic sacroiliac joint changes seen in AS are not seen in patients with nr-AxSpA. It has AV-951 been argued that nr-AxSpA is a distinct entity and should not be considered early AS.28 Except for higher C-reactive protein (CRP) and slightly better responses to TNFi in AS, the burden of disease appears to be similar in AS and nr-AxSpA.29 A distinct difference between the two groups is the greater proportion of women in nr-AxSpA cohorts. We tracked the sex ratio of new patients diagnosed with AS over time to study the impact of these changes in overall prevalence and incidence trends of AS. Our study shows that the epidemiological trend with more females diagnosed with AS started between 2000 and 2005 when TNFi were introduced for the treatment of AS. Between 2005 and 2010, when we would have seen the greatest impact of MRI, there were steady trends in the sex ratio.

The electronic medical record (EMR) is a new and promising tool for enhancing national and international healthcare delivery.1 Recent research has shown that information technologies can reduce medication errors,2 improve adherence to clinical either practice guidelines,3 and improve the

delivery of preventive health services,4 thereby potentially improving health outcomes for patients.5 6 While electronic medical users can be productive, any disparities in experience, understanding and skills can leave team members feeling less than satisfied and not working to their full potential.1 Clinicians’ perception of the EMR is a crucial determinant of the successful use of the EMR system. United Arab Emirate, Health Authority of Abu-Dhabi (HAAD) has implemented a system developed by one of the top three Healthcare IT vendors in the USA.6 They have been in existence since 1979 and have installations in many countries including the USA, Canada, Australia, Saudi Arabia, Qatar, UAE, France, Spain, Singapore, Malaysia and South America. UAE has implemented the EMR system (Cerner) in 2008 in Abu Dhabi and Al Ain. Information and research studies related to user satisfaction is lacking in the local context. This research study focused on physician user satisfaction with the EMR system in primary healthcare centres

(PHC) in Al Ain and was the first known survey conducted in the UAE exploring this research question. The findings of the quantitative study are reported in separate paper. We conducted a concurrent qualitative study in the same practices selected for the quantitative project. The use of focus group interviews is becoming increasingly popular in healthcare research

to explore the beliefs, feelings, attitudes and behaviour of individuals. Focus group discussions provide information about a range of ideas and feelings of individuals about specific issues and it illuminates the differences in perspective between groups of individuals. A focus group can generate a large amount of data in a relatively short time span.7 In this study, the researchers explored user knowledge, attitude and satisfaction with the EMR system in PHC in Al Ain. Method Study design This descriptive qualitative study was conducted in parallel with a quantitative study reported separately in a paper presented at the 2nd Al Ain Family Medicine Research Day on 3 March 2012 Brefeldin_A at Al Ain, UAE. Study method A purposive sampling strategy was used to recruit the physicians.8 The study was conducted in English. Permission was obtained from the clinic supervisors of each hospital prior to the study. Invitation letters were distributed among the physicians in clinics where the quantitative study on the EMR system was conducted. The management personnel were requested to select the participants for our study. These workers were selected based on their willingness to share their experiences on the EMR with us.

ICC estimates >0.75 were considered as good reliability scores, between 0.50 and 0.75 as moderate reliability, and

<0.50 as poor reliability.31 Second, the Bland and Altman Method was used to assess agreement on scores of PA from the first and second administrations.32 Variables used for the Bland and Altman selleck products analysis were weekly time spent in moderate-to-vigorous activity (MVPA), total PA and sitting. MVPA was computed by summing the total min/week of reported PA of moderate and vigorous intensities across all four domains. For total PA, the total min/week of activities in each domain was summed (total work+total transport+total domestic+total leisure-time min/week scores) to gain an overall estimate of PA in a week. Also, the

independent t test and one-way ANOVA were used as appropriate to compare the time spent (min/week) in PA at both administrations across sociodemographic subgroups. To assess construct validity, the non-parametric Spearman correlation coefficients (r) were utilised to explore the relationship between MET-min/week of PA from the Hausa IPAQ-LF, and resting blood pressure and BMI. Data were analysed using Statistical Package for the Social Sciences (SPSS), V.15.0 for Windows (SPSS Inc, Chicago, Illinois, USA) and the level of significance was set at p<0.05. Results The sociodemographic characteristic of the participants are shown in table 1. The participants comprised equally of women and men, with a mean age of 35.6±10.3 years and BMI of 23.8±3.9 kg/m2. The majority of the participants were married (58.9%, n=106), had more than secondary school education (62.7%, n=111) and were employed (75%, n=117). Compared to men, the women were more likely to be married (71.1% vs 46.7%, p=0.001) and unemployed (52.2% vs 17.8%, p<0.001), but men were more likely to have more than secondary school education (76.7% vs 48.2%, p<0.001). Table 1 Descriptive characteristics of the participants (N=180) Reliability Table 2 shows the test–retest reliability of the modified IPAQ-LF. Overall, reliability coefficients were good (ICC

>75) for total PA, occupational PA, active transportation and vigorous intensity (very hard) PA. Domestic PA, sitting activity and AV-951 leisure PA demonstrated moderate reliability (ICC ranges from 0.51 to 0.71). While the reliability coefficients of total PA (ICC=0.80, 95% CI 0.69 to 0.87), active transportation (ICC=0.83, 95% CI 0.73 to 0.89), occupational PA (ICC=0.78, 95% CI 0.66 to 0.85) and leisure time PA (ICC=0.75, 95% CI 0.63 to 0.84) were substantially higher among men than women, reliability coefficients for domestic PA (ICC=0.38, 95%, CI 0.01 to 0.57) and sitting time (ICC=0.71, 95% CI 0.46 to 0.85) were higher among women than men. According to the intensity of PA, ICCs range between 0.61 and 0.82, with the lowest value recorded for moderate intensity (hard) PA and the highest value for vigorous intensity (very hard) PA.

All participants were fully informed of the study protocol Binimetinib and provided signed informed consent. The study protocol was approved by the Research and Ethics Committee of the University of Maiduguri Teaching Hospital, Maiduguri, Nigeria. Data were collected between March and May, 2012. Measures The adapted IPAQ—long Hausa version The cultural adaptation, translation and back translation of the Hausa version of IPAQ-LF is similar to that of the Hausa IPAQ-SF that has been described

in detail elsewhere.21 Briefly, interviews were conducted with public health experts, exercise scientists and local people,

not highly educated, to identify the items and examples of PA on the original questionnaire that needed to be culturally adapted. Several cultural adaptations were made to the original items to reflect the reality in Nigeria. First, adjustments to English words such as ‘vigorous’ and ‘moderate’ activity, which can be misunderstood and not associated with PA behaviours in Nigeria, were replaced with words that are more representative of the language used in Nigeria, such as ‘very hard’ and ‘hard’, respectively. Second, examples of various intensities of activity that are common in the Nigerian culture were added, and those already on the questionnaire but not common in the Nigerian context were replaced with culturally applicable examples

that are equivalent in energy intensity (metabolic energy turnovers, METs) with the original items and examples. Third, concepts such as PA and walking for transportation, which were misconstrued outside the health context, were refined to indicate they were referring to health behaviours. After adaptation, the questionnaire was independently translated from English into Hausa by two native speakers of Hausa who also speak English, and who are able to read and write in both languages. One of the translators was familiar Dacomitinib with the questionnaire and the second was an expert in Hausa. The translated questionnaires were mutually revised by the translators and the research team for consistency and then back translated into English by a third bilingual person who was familiar with the construct measured by IPAQ. The back translated version was checked by the research team for any discrepancies and to ensure that the construct measures by IPAQ had not been lost during the adaptation and translation process.