Reports on the state of knowledge about medicines and driving showed an increased concern about the role that the use of medicines might play in car crashes. Much of patient knowledge regarding medicines comes from communications with healthcare professionals. This study, part of the DRUID  project, was carried out in four European countries and attempts to define predictors for knowledge of patients who use driving-impairing medicines. The influence of socio-demographic variables on patient knowledge was investigated as well as the influence of socio-demographic factors, knowledge and attitudes on patients' reported behaviour regarding driving under the influence of medicines.Pharmacists handed out questionnaires to patients who met the inclusion criteria: 1) prevalent user of benzodiazepines, antidepressants or first generation antihistamines for systemic use; 2) age between 18 and 75 years old and 3) actual driver of a motorised vehicle. Factors affecting knowledge and reported behaviour towards driving-impairing medicines were analysed by means of multiple linear regression analysis and multiple logistic regression analysis, respectively.A total of 633 questionnaires (out of 3.607 that were distributed to patients) were analysed. Patient knowledge regarding driving under the influence of medicines is better in younger and higher educated patients. Information provided to or accessed by patients does not influence knowledge. Patients who experienced side effects and who have a negative attitude towards driving under the influence of impairing medicines are more prone to change their driving frequency behaviour than those who use their motorised vehicles on a daily basis or those who use anti-allergic medicines.Changes in driving behaviour can be predicted by negative attitudes towards driving under the influence of medicines but not by patients' knowledge regarding driving under the influence of medicines. Future research should not only focus on information campaigns for patients but also for healthcare providers as this might contribute to improve communications with patients regarding the risks of driving under the influence of medicines. It has been known for many years that the consumption of psychoactive substances, such as alcohol, sedatives, anxiolytics, antidepressants or illicit drugs, has a negative effect on the ability to drive . In factTherefore, special efforts are needed in order to have a better knowledge of the various aspects of this specific problem and to develop appropriate solutions. This is the reason why an EU-project under the acronym of DRUID   was fundReports on the state of knowledge about drugs and driving  showed aIn order to better understand and predict human behaviour, some theories have been derived to describe and explain how and why people behave the way they do. The theory of planned behaviour (TPB), the theory of interpersonal behaviour (TIB), and other more recent models with direct application in health research are examples of what has been done in the field of predictive behaviour. TBP was first suggested by Fishbein and Ajzen  and TIB Having the TBP and TIB as a main reference, this research attempts to determine predictors that can influence not only patients' reported behaviour, but also their knowledge. In a simplified way, the theoretical reasoning behind the construction of the models was based on the assumption that socio-demographic characteristics play a central role in knowledge . Both socio-demographic characteristics and knowledge in combination with attitudes, defined as feelings towards driving under the influence of medicines, were used to predict reported behavior (in terms of change in driving frequency and/or in terms of change in the use of medicines). Figure The study was conducted in four countries: Belgium, Germany, Spain and the Netherlands, in 2007. The reason why these four countries were selected is because the Ministry of Transport or the national organization of pharmacists developed materials related to drugs and driving, and, therefore, they were very sensitive to the topic and, as a consequence, more willing to participate.The questionnaire used in our study was derived from a previous Dutch national survey . The oriPatients received the questionnaire through their pharmacy. Pharmacists were asked to hand out a questionnaire to approximately 1.000 patients (per country) who went to a community pharmacy and met the established inclusion criteria (see below).The study was approved by the Medical Ethical Committee of the Universitair Medisch Centrum Groningen , the Netherlands as well as by the Medical Ethics Committee of the Universidad de Valladolid (Spain) and Ghent University Hospital Medical Ethics Committee (Belgium). Patient anonymity was ensured and all data were kept confidential.Different approaches were used to select the pharmacies, depending on the country.In Belgium, only Flemish pharmacies were approached. A message was spread through the APB  and Escapo  to a selected number of pharmacies . A total of 40 pharmacies (43% response rate) agreed to participate in the study.In collaboration with ABDA , a total of 3.600 pharmacies, part of the ABDA network, were invited to participate in the study, from which 38 pharmacies (1% response rate) accepted the invitation.The pharmacies invited to participate in the Dutch patient questionnaires were selected among all the pharmacies that already cooperated with the University of Groningen, Pharmacy (RuG-Pha). Pharmacies that were participating in on-going projects were excluded. A total of 93 pharmacies were invited to participate in the study and 36 pharmacies (39% response rate) accepted the invitation.In Spain, the institute responsible for the dissemination of the questionnaires was the University of Valladolid (UVa), in collaboration with the Spanish Society of Community pharmacies (Sociedad Espańola de Farmacia Comunitaria). Nationalwise, a total of 80 pharmacies were invited to participate. Of these, 35 (44% response rate) were actually enrolled in the study.Pharmacists who agreed to participate in this study were not trained for this study. Yet, all participating pharmacists were provided with detailed information about the study, which included a list of participant inclusion criteria translated into the national language of each country. The reliability of the method to select patients was assured by addressing questions covering the inclusion criteria in the questionnaire and by excluding the patient from the analysis whenever the inclusion criteria was not fulfilled. Pharmacists looked for potential participants during working hours for a period of 3 weeks.Patients were eligible to participate in the study if they met the following inclusion criteria:1. The patient uses anyone of the following medicines that are known to impair driving ability:2. The patient is a prevalent user (2nd prescription or more); ensuring that they experienced any possible side effects and resulting changes in reported behaviour.3. The patient is 18-75 years of age, as it is known to be the age group that actively participates in driving and that takes medicines.4. The patient actually drives a motorised vehicle in traffic (is to be asked at the time of dispensing).Benzodiazepines (as hypnotic or anxiolytic): flunitrazepam, flurazepam, loprazolam, nitrazepam, zopiclon, alprazolam, bromazepam, buspirone (> 2dd 10 mg), chlordiazepoxide, diazepam, lorazepam, oxazepam.• Antihistamines (1st generation antihistamines): clemastine, dexchlorpheniramine, promethazine, cyproheptadine, tripelennamine, hydroxyzine.• Antihistamines (1st generation antihistamines): clemastine, dexchlorpheniramine, promethazine, cyproheptadine, tripelennamine, hydroxyzine.• When the patient met the four criteria mentioned above, he/she was asked to participate in the survey. A patient information letter, a paper questionnaire, and a stamped addressed return envelope were given to patients who agreed to participate in the study. Participants filled in the questionnaire at home and no information on the time for completion of the questionnaire was asked.No records on the non-respondents were kept. This methodological decision was made for a practical reason based on the extra administrative work that pharmacists would have to do, which would have drastically decreased the number of pharmacists enrolled in the study. As a consequence, it is not possible to correlate participants' refusal patterns with time consumed filling in the questionnaire, age, gender, or any other socio-demographic variable.The questionnaire was developed in English and, after consensus about the content, it was translated into the national language of each participant country (it was decided to use only a Dutch version for Belgium). Thereafter, reverse translation back into English was performed to ensure consistency between the translations.The questionnaire consisted of 43 questions (39 closed questions and 4 open questions). The questions were grouped into 6 topics of interest covering general information (including information related with the inclusion criteria), participation in traffic, medicines in traffic, use of medicines, information about medicines, and attitude towards reported behaviour in traffic. By doing so, it was possible to collect data on general items regarding the patient characteristics as a participant in traffic and about patients medicine use. Specific items to assess patient knowledge, attitude, and reported behaviour were gathered as well. The questionnaire was provided as an Additional file Patient knowledge regarding medicines that have a hazardous influence on driving ability was assessed with respect to the knowledge about the risk of having a traffic accident when driving under the influence of driving-impairing medicines. By using a 5-scale parameter , patients could agree (or disagree) with the following sentences: "the risk of having a road accident is smaller when you have just started taking a driving-impairing medicine compared to long term treatment" or "the risk of having a road accident is similar when you take more of a driving-impairing medicine than prescribed" or "the risk of having a road accident remains the same when you use several driving-impairing medicines at the same time." The internal consistency of the scale was checked by means of the Cronbach alfa coefficient (0.64) and the sum score was calculated.Patient reported behaviour was analysed in terms of a change in their frequency of driving (yes or no) or in terms of changing the use of driving-impairing medicines (yes or no). For each questions, the sum score of the different statements was calculated. Table The following variables were included in the multi- and logistic- regression analysis:• Country .• Patient gender and age category .• Educational level .• Use of motorised vehicles .• Experienced side effects that can potentially impair driving ability such as sleepiness or drowsiness, decrease of alertness, problems concentrating, blurred vision and dizziness (yes/no).• Information received from healthcare providers related with the influence of medicines on driving ability (yes/no).• Information looked up by patients themselves, related to the influence of medicines on driving ability (yes/no).• Whether patients read the Patient Information Leaflet (PIL) or not (yes/no). This question did not attempt to investigate comprehension. Instead, it was used to know whether patients used the PIL as source of information.• Patient attitude-In order to assess patient attitudes towards the use of medicines that potentially impair patients while driving, a 5-scale parameter  was used to analyse patient's opinion in relation with the use of impairing medicines and driving as well as the consequences of driving under the influence of impairing medicines. In both cases, the internal consistency of the scale was checked by means of the Cronbach alfa coefficient (0.85 and 0.69 respectively) and the sum score was calculated. To investigate patient attitude towards the use of impairing medicines, questions such as "when I drive while using driving-impairing medicines I endanger my personal safety" or "when I have been prescribed a driving-impairing medicine I choose not to use my car and choose other types of transportation" or "when I have been prescribed a driving-impairing medicine, I try to use my car as little as possible" were asked. Questions such as "the risk of driving under the influence of driving-impairing medicines is being exaggerated" were used to address patient attitude towards the consequences of driving under the influence of impairing medicines.Guidelines were developed for all participating countries in order to ensure that data entry was conducted the same way. Additionally, all databases were checked for undefined values and extreme outliers. Data were analysed using SPSS 16.0 for Windows.p-value < 0.05 was considered as statistically significant.Descriptive analysis was used to report on respondent characteristics such as gender, age and educational level. Multiple linear regression analysis was used to identify patient knowledge about driving while using medicines that might impair driving ability, whereas reported behaviour was analysed by means of multiple logistic regression. Multiple linear regression analysis could not be used in both situations because this statistical test is only applicable when the dependent variable is continuous (which is the case with investigating participant knowledge). As behaviour is a dichotomous variable (yes/no), multiple logistical regression was applied in order to predict which factors influence patient behaviour. Knowledge and reported behaviour were considered as dependent variables of the equation. Independent variables, those that can theoretically influence the dependent variables, consisted of country, gender, age category, educational level, use of motorised vehicles, self-report of experienced side effects, information about medicines , intake of medicines, knowledge itself, and, finally, attitudes towards use of medicines and driving and towards driving under the influence. Prior to the construction of the models, univariate analysis of variance was conducted to verify whether or not there was an interaction effect between the consumption of medicines and age influencing patients' knowledge. As no interaction effects between medicines' consumption and age were found, it was decided not to include them, as variables, in the models. A Data collected from 633 questionnaires  were used, as shown in Table The relevant characteristics of the study population are summarised in Table Concerning self-reported medication that patients were taking, within countries, antidepressants were the most stated medicines  followed by anti-allergics , sedatives , and tranquilisers . Figure With regard to side effects, 40.4%  of Belgian participants did not receive this information. Considering the four countries together, 62.5% (n = 349) of the patients received information from healthcare providers.Patient knowledge about the risk of having a road accident was similarly low in all countries . Regarding reported behaviour (Table 2) of the differences found between patients. The age of the patient is correlated with the knowledge about the risk of being involved in a traffic accident: the younger the patient the greater the knowledge about the risk. Regarding educational level, knowledge is higher among patients with an academic degree. Information patients received from healthcare providers, looked-up by patients themselves, or the information stated in the PIL did not appear to contribute to patient knowledge. The use of motorised vehicles had no effect on patient knowledge. Self-report of experience of side effects was also not significant.Multiple linear regression analysis was used to assess factors influencing patient knowledge Table  towards 2) of the variance for changes in driving frequency and in the use of driving-impairing medicines, respectively. Patients were more likely to change their frequency of driving when they are between 26 and 34 years old, when they report side effects, and when they have a negative attitude towards driving under the influence of impairing medicines. In contrast, patients who drive frequently and those who take anti-allergics tend to change their driving frequency less often compared to users of tranquilisers  by experienced side effects and knowledge about the risk of having a road accident and negatively influenced by country  and by the use of anti-depressant medicines.Among the 4 participating countries, self-reported medication use indicated that patients took, on average, 1.3 medicines that are known to be driving-impairing. For antihistamines  and antiSleepiness, decrease in alertness, problems concentrating, dizziness or blurred vision were reported at least one time during treatment by almost 60% of the participants. These side effects are presumed to be potentially dangerous for driving ability . HoweverMuch of patients' knowledge regarding medicines and side effects, in general, comes from communication with their general practitioner ,15. SimiThe information that patients received from healthcare providers, or that patients looked up themselves, did not appear to be effective enough to influence patient knowledge regarding the risk of being involved in a traffic accident. This is in line with previous research where it is shown that patients who are at a greater risk of being involved in a traffic accident due to medicines do not necessarily have more knowledge of increased risk . Age andAge is the variable with a greater positive impact in the model: participants between 26 and 34 years-old are the ones more likely to change their driving behaviour. Patient self-report of side effects also correlates positively with changes in frequency of driving; this means that patients who felt side effects are more likely to change their driving behaviour. The same holds true for attitude towards driving under the influence of medicines. This variable positively influences the model, meaning that patients with a stronger attitude towards the consequences of driving under the influence are the ones changing the frequency of driving. Conversely, the use of motorised vehicles influences patient reported behaviour negatively, i.e. the more patients drive the less they change their driving behaviour in terms of frequency of driving. The use of anti-allergic medicines also correlates negatively with the model, making patients taking these medicines less prone to change their frequency of driving. This could be due to the fact that patients might not be aware that anti-allergic medication has a negative effect on driving ability or that side-effects occur when the patient is not driving. Another explanation for this fact could be due to the less sedative effect of the 2nd generation antihistamines, and, therefore, patients do not recognize any signs of impairment on their psychomotor abilities and, as a consequence, patients feel safe to drive.Living in the Netherlands, experiencing side effects, using antidepressants, and knowledge about the risk of having a traffic accident are the factors that significantly account for changes in the use of medicines. Patients living in the Netherlands and using antidepressant medicines change the use of medicines less often. This could be due to the fact that antidepressants are well known to affect driving. As a consequence, healthcare providers, such as physicians or pharmacists, can immediately provide patients with preventive measures , which might reduce the negative effects of the medicines on driving ability resulting in a less need to change driving frequency.In contrast, self-report of experiencing side effects and knowledge about risk of being involved in a road accident contribute positively to change in the use of driving-impairing medicines. This means the more side effects a patient experiences and the greater their knowledge about the side effect, the bigger the chances that they will change the intake of their medicines.Similarly to knowledge, the findings on predictors for patients' reported behaviour support the theoretical model developed. Reported behaviour is not always influenced by the same range of variables, meaning that behavioural actions result from a combination of different factors that ultimately lead to an action.The results of this study should be considered in the light of several strengths and limitations. The major limitation of this study is the low response-rate, in all 4 participating countries. As a consequence, results should be considered with care and conclusions should be drawn with caution, as the results might not be representative of the whole driving population that takes driving-impairing medicines. However, the actual number of questionnaires that was handed out to patients was not known but the authors believe it was smaller than 3607, meaning that the actual response rate could be higher than 18%. There could be, as well, a potential selection bias. To ensure that only data referring to patients who met the inclusion criteria were part of the analysis, the survey included questions covering the inclusion criteria. Nevertheless, the authors are confident that it is possible to draw relevant conclusions.Main results were achieved based on patient self-report of medicine use, and knowledge, attitude and behaviour related with medicines and driving. Self-report is a widely and valuable method in social sciences research . Therefoet al. was very much oriented to the knowledge that older adults who face serious driving safety and mobility issues have. The present study attempts to reflect knowledge and reported behaviour of a much broader and heterogeneous population, which makes it relevant for the field of medicines and driving and traffic safety. By accessing predictors for patient knowledge and reported behaviour, it is possible to develop more effective campaigns that point out exactly what is relevant for the patients, i.e. campaigns tailored to the patients' needs. At the same time, it is possible to give positive feedback to patients who already possess good knowledge (and therefore do not need to change) and also to help patients' with making decisions of whether they should drive their car or not while taking driving-impairing medicines.To our knowledge, only one American study  addresseFuture research should not only focus on information campaigns for patients but also for healthcare providers. Interventions that might raise awareness about the topic and might improve communication with patients about the risk of driving under the influence of psychotropic medicines are important topics for future research, as well. As current information does not effectively contribute to patient knowledge, the authors believe there is the need for more effective ways to communicate information to patients, which might be capable of increasing patient knowledge and changing patient attitudes towards driving under the influence of medicines. New strategies to enhance communication could make use of pictograms on the box of medicines that are known to impair driving fitness. Well designed pictograms are known to improve comprehension and recall of information and can be used to trigger the discussion between healthcare providers and patients. This could potentially contribute to increasing the patient's knowledge about the use of medicines that might affect driving fitness.Finally, research can also contribute to develop, implement, and evaluate guidelines and other information materials and/or tools that aim to provide decision support to physicians and pharmacists in prescribing and dispensing potentially impairing medicines. Additionally, the information provided to patients during the consultation can be improved if healthcare providers know how to advise their patients, which leads to the conclusion that the advice to the patient should be part of the developed information materials as well. Without a doubt, this is also a task for implementers or policy makers.Patient knowledge regarding driving under the influence of medicines does not predict changes in driving behaviour. Rather, negative attitudes towards driving under the influence of medicines is a better predictor of changes in patients' driving behaviour.Patients' knowledge is influenced by socio-demographic parameters such as age and educational level. Behavioural changes can be explained both in terms of changes in frequency of driving and in terms of changes in the use of driving-impairing medicines. Patients who experienced side effects and who have negative attitudes towards driving under the influence of impairing medicines are more prone to change their driving behaviour (positive influence in behaviour) than those who use motor vehicles on a daily basis or those who use anti-allergic medicines. Patients who experienced side effects and who have a good knowledge of risks of having road accidents seem to change the use of driving-impairing medicines more easily than those who come from the Netherlands or take antidepressant medicines.Future research should focus on more effective ways to increase patient knowledge and to help patients' decision making towards driving behaviour and medication intake. This could be done by implementing new strategies of communication in order to prevent patients from driving under the influence of medicines. Special attention should be paid to healthcare providers as they are the main source of information for patients. By increasing healthcare provider awareness about medicines and driving, we believe that patient knowledge will also increase and as a consequence could be responsible for a decrease in patients' driving frequency or a stabilisation in patient behaviour regarding changes in the use of medicines.The authors of this study (except for LvD) are part of the DRUID  project. DRUID is financed by the European Community within the framework of the EU 6th Framework Program (Contract No TREN-05-FP6TR-S07.61320-518404-DRUID). This article reflects only the authors' views. The European Community is not liable for any use that may be made of the information contained therein. The authors declare that they do not have any competing interests.SPM performed the data analysis, helped by LvD who gave substantial contributions for the statistical analysis, and drafted the final manuscript. AGV (Belgium), FJA (Spain), MH (Germany) and JJdeG (the Netherlands) designed and were responsible for the implementation of the study in the different countries. All authors read, reviewed and approved the final manuscript.This study was financed by the European DRUID project.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/12/59/prepubQuestionnaire for patients. The use of medicines in traffic.Click here for file


Bipolar disorder is a severe mental illness with serious consequences for daily living of patients and their caregivers. Care as usual primarily consists of pharmacotherapy and supportive treatment. However, a substantial number of patients show a suboptimal response to treatment and still suffer from frequent episodes, persistent interepisodic symptoms and poor social functioning. Both psychiatric and somatic comorbid disorders are frequent, especially personality disorders, substance abuse, cardiovascular diseases and diabetes. Multidisciplinary collaboration of professionals is needed to combine all expertise in order to achieve high-quality integrated treatment. 'Collaborative Care' is a treatment method that could meet these needs. Several studies have shown promising effects of these integrated treatment programs for patients with bipolar disorder. In this article we describe a research protocol concerning a study on the effects of Collaborative Care for patients with bipolar disorder in the Netherlands.The study concerns a two-armed cluster randomised clinical trial to evaluate the effectiveness of Collaborative Care (CC) in comparison with Care as usual (CAU) in outpatient clinics for bipolar disorder or mood disorders in general. Collaborative Care includes individually tailored interventions, aimed at personal goals set by the patient. The patient, his caregiver, the nurse and the psychiatrist all are part of the Collaborative Care team. Elements of the program are: contracting and shared decision making; psycho education; problem solving treatment; systematic relapse prevention; monitoring of outcomes and pharmacotherapy. Nurses coordinate the program. Nurses and psychiatrists in the intervention group will be trained in the intervention. The effects will be measured at baseline, 6 months and 12 months. Primary outcomes are psychosocial functioning, psychiatric symptoms, and quality of life. Caregiver outcomes are burden and satisfaction with care.Several ways to enhance the quality of this study are described, as well as some limitations caused by the complexities of naturalistic treatment settings where not all influencing factors on an intervention and the outcomes can be controlled.NTR2600.The Netherlands Trial Registry,  Bipolar disorder is a severe mental illness with an estimated lifetime prevalence of 1.5 to 2% show thaTreatment of bipolar disorders in the Netherlands primarily consists of pharmacotherapy, supportive treatment, and psycho education, sometimes combined with improvement of self-management skills or psychotherapy. Many patients respond well to this treatment and may stabilize for longer periods. However, a substantial number of patients do not respond adequately to these treatment efforts. They suffer from frequent episodes, persisting symptoms, cognitive problems, limited social support and poor social functioning. Comorbid psychiatric disorders, such as personality disorders and substance abuse, are common, as are somatic disorders i.e. cardiovascular disease, partly associated with prolonged use of maintenance medication ,9.Multidisciplinary collaboration of professionals is needed to involve optimal specialist skills on all aspects of the disorder, and to properly combine all expertise in order to achieve an optimally integrated care . The DutCollaborative Care (CC) programs have been developed to integrate multidisciplinary care for complex disorders and to date, three research projects show promising results with bipolar patients. Bauer et al. ,13 have Simon et al. ,17 have Suppes et al.  studied It is striking that all three studies show improvement of manic but not depressive symptoms.In the Netherlands, until now no studies have been performed on the effects of CC for patients with bipolar disorder. The current study will be the first to implement CC for patients with bipolar disorder, and moreover, to add a specific intervention to improve depression. Furthermore, CC appears to offer good possibilities to strengthen the position of the nurse in the care process for patients with a bipolar disorder, both at the organizational and content levels.In this article we describe the study protocol for investigating the effectiveness of a CC program for patients with bipolar disorder. We set out the following three research questions to answer:A What are the effects of a CC program, compared to Care as Usual (CAU), for patients with bipolar disorder, with regard to their psychosocial functioning, psychiatric symptoms, quality of life, attitudes towards medication, mastery, and satisfaction with care?B What are the effects of a CC program, compared to CAU, for informal caregivers of patients with a bipolar disorder, with regard to the experienced burden and satisfaction with care?C What is the cost effectiveness of a CC Program compared to CAU?A pragmatic two-armed cluster randomized controlled trial (RCT) will be carried out in mental health outpatient clinics in the Netherlands. A Collaborative Care program will be executed in the experimental condition, whereas the control condition will continue to deliver Care as Usual (CAU). CC will be performed by the CC-team, with mental health nurses in a coordinating role. Baseline measurements will be obtained at inclusion and follow-up measurements will take place at 6 months and 12 months. The primary outcome measures are psychosocial functioning, symptoms, and quality of life. Secondary outcome measures are mastery, attitude towards medication and satisfaction with care. Family members or friends of patients will be asked to fill in questionnaires regarding perceived burden and satisfaction with care.The level of CAU may vary considerably among the various outpatients clinics in the Netherlands, and there is a lack of clarity about the specific content of CAU for patients with bipolar disorder. However, there is more detailed knowledge available about care provided in some highly specialized centres for patients with bipolar disorder that may resemble CC. In the Netherlands, about 20.000 patients receive care for bipolar disorder but it is estimated that only 1500 patients receive this care in these specialized centres. Hence, about 18.500 patients receive CAU at a less specific level. Our presumption is that CC will differ considerably from CAU, which we expect to be mainly supportive and not systematically delivered. In order to increase our knowledge about the characteristics of CAU another study has started to describe current CAU for bipolar disorders in the Netherlands. In this study, psychiatrists and patients are being asked to describe the care actually delivered to patients with bipolar disorder, by means of questionnaires. These data will be used in the current study: (1) to objectively describe CAU; (2) to select sites (based on our inclusion criteria) that can be included in our CC-trial; and (3) to perform the matching of sites for the (cluster) randomization. Furthermore, if outpatient care teams are interested in participating in the CC-trial, we will interview two members of that team to investigate the nature and intensity of care currently delivered to patients with bipolar disorder. Clinics that currently have a level of CAU that does not already resemble CC can be considered for randomisation.In this trial we will use clustered randomisation with outpatient clinic teams as clusters. Randomisation will be performed as follows: the CAU-study as well as the interviews with team members provide us with insight in the nature and intensity of CAU at that site. This enables us to describe CAU more precisely and formulate criteria for inclusion. Sites that meet the criteria for CAU will be invited to join in the CC-trial. Teams will be matched for characteristics of care offered to bipolar patients, as well as organisational characteristics such as team composition or type of organisation. One team of every pair will be randomly assigned to the experimental condition, and the other to the control condition. Patients in both teams who meet the inclusion criteria will be asked to participate in the study.Patients who meet the following inclusion criteria will be included:• diagnosis of bipolar disorder according to DSM- IV-TR ;• age 18-65 years.Exclusion criteria:• Acute phase of severe depression or mania (CGI-BP: degree of illness score 6 or score 7).• A very stable course of illness (during the last year) that allows low intensity of treatment (2-4 consults with the psychiatrist per year suffice), to be judged by the treating psychiatrist.• Insufficient command of the Dutch language.• Not able or willing to give informed consent.If the patient consents, a family member or friend will also be asked to participate in the study, according to the following inclusion criteria:• The family member or friend is assigned by the patient.• The family member or friend is 18 years or older.• The family member or friend has a sufficient command of the Dutch language.• The family member or friend is able and willing to give informed consent.Since the current study is a pragmatic intervention study, blinding of patients and professionals for care modality is not possible. However, blinding is performed in the procedure of randomisation and the statistical analysis. Furthermore, the research assistant who performs interviews by telephone to administer the Life Chart, will be blind to the condition of the respondent.CC will be recovery-oriented, meaning that it supports the personal process of the patient towards redefining and achieving his goals in life despite the disorder. It will consist of the following systematically delivered elements of treatment:• The formation of a Collaborative Care team, including at least the patient, the nurse and the psychiatrist, were all decisions concerning treatment and care will be made, using shared decision making. If possible, a family member or friend will be engaged in the treatment and be part of the CC team. Teams meet every three months. Coordination of care and continuity of care is provided by the nurse.• Contracting. Agreement on the most important problems to be worked on, and on which treatment is needed to help the patient achieve his personal goals, will be striven for. A treatment plan will be made, formulated as a contract, in which goals and treatment activities are recorded.• Working with the treatment plan based on systematic care needs assessment, and that will focus specifically on recovery-oriented goals, defined by the patient. Systematic monitoring of outcomes.• Psycho education ,21), pro• Problem Solving Treatment (PST) ,23, deli• Mood charting by means of the Life Chart Method  and reco• Pharmacotherapy and somatic care, as usual. In addition, structured and continuous monitoring of the effects.• If indicated, specialised PST will be delivered (1) to patients who remain depressed, aimed at increasing the amount of pleasant or fulfilling activities, and (2) to patients with wishes or care needs on the subject of participation in society, aimed at rehabilitation.These interventions will be tailored to the individual needs of the patient.In the CC trial, CC will be implemented in the experimental teams by the use of the Replicating Effective Programs framework (REP) . This frA manual-based training program will be developed by the researchers with assistance of an expert panel consisting of expert nurses, psychiatrists, patients and family members. Nurses in the experimental condition will receive a three-day training program, and psychiatrists and psychologists will receive parts of this training. The trained teams will perform CC during one year. They will be primarily responsible for the coordination and continuity of treatment and care for patients with bipolar disorder. The primary investigator (TV) will supervise the nurses intensively during the performing stage of the intervention, by weekly contact by telephone and regular meetings in the facility with colleagues who also participate in the study. Fidelity will be assessed by means of checklists filled out by the nurses in the experimental group, and by randomly checking the electronic files of patients, by the primary investigator.Nurses in the control group will be performing Care As Usual, of which the content will be assessed by the researcher at baseline, by means of the checklist mentioned before. The Care consumption will be measured with the TIC-P questionnaire in both groups.Measurements will take place at baseline and after 6 and 12 months of follow-up in patients, clinicians and family members or friends of the patients. All questionnaires are available in Dutch. At baseline, demographics, illness history and current characteristics of bipolar disorder will be recorded with the Questionnaire for Bipolar Illness (QBP-NL), that has been used previously in a large naturalistic cohort study ,30. We wPrimary outcomes are psychosocial functioning; course, prevalence and severity of psychiatric symptoms and quality of life.Data will be analyzed according to the intention to treat-principle. Baseline comparability of the experimental and control groups in demographic and clinical variables will be evaluated with ANOVA/independent samples t-test and Chi-square tests. Differences in outcome between CC and CAU will be evaluated by means of (mixed model) analysis of covariance. A group*time-interaction term will be entered into the model to test for a difference in treatment effect over time. In analyzing a specific outcome variable, the baseline score of that variable will be used as covariate. The analysis will be extended using multilevel analysis that takes the nesting of measurements into account. In the multilevel analyses we consider location as the first level, patient as the second level, and the three measurements as a third level, using the principles of Twisk . FinallyThe power calculation concerns the comparison at T12 compared to T0 between the two groups (CC vs. CAU). We were not able to detect studies sufficiently comparable to ours to find a basis for estimating an effect size. We assume the effect size Cohen's d = 0,5, because we consider this a clinically relevant effect. Setting α < .05 (two-tailed), and the power (1-β) = .80, the required sample size is 2 × 63 patients. In cases of clustered randomisation the standard is to add 25% to this amount (n = 2 × 79). Taking into account an expected loss of 30%, a sample of 103 patients in each group is needed.This study protocol has been reviewed by the Scientific Committee of the EMGO Institute of VU University Medical Center in Amsterdam, The Netherlands, and by the Research Committee of Inholland University for Applied Sciences, Amsterdam, and has been approved for by the Medical Ethical Committee of the VU University Medical Centre for final approval. Patients will obtain oral and written information about the study and will be asked to sign an informed consent form if they are willing to participate. They will give informed consent for participation of a specific caregiver, who will also be asked to give separate informed consent.This pragmatic trial will to our knowledge be the first to evaluate the effectiveness of recovery oriented Collaborative Care for patients with bipolar disorder outside the United States. Our study will assess primarily the effects of CC on functioning, psychiatric symptoms and quality of life. We expect that CC contributes to an increased quality of care for these patients.The quality of the study is enhanced in four ways. Firstly, we included the expertise of patients, informal caregivers, psychiatrists and nurses during the process of development of the CC intervention. Secondly, we carefully planned implementation of CC in the experimental group, with the three days of training, weekly coaching for the nurses, regular meetings with the group of nurses that perform CC, and fidelity assessments. In this way we intend to improve intervention compliance in the experimental group. Thirdly, we apply very few a priori exclusion criteria, hence we will be able to generalise our findings to a large group of outpatients with bipolar disorder. Finally, the interviewing research assistant is blinded for the treatment condition of the respondents, while administering the Life Chart by telephone.Besides these strong points, this study has some limitations, which should be acknowledged. The main limitation is that patients and professional care providers cannot be blinded for the treatment condition to which they will be randomised. This is a possible source of bias, as patients as well as nurses in the intervention group may be more actively involved in the treatment because they expect it to work, which may enhance the effect of the intervention we find. A second limitation is the possibility that participation in the study and being exposed to follow-up assessments may affect the outcome of the CAU control group. This may decrease the contrast between the two groups and thus the probability to find statistically significant differences between the CC and the CAU condition. The third limitation is that it is not possible to discern which component of CC contributed to the effect.Limitations of this kind are inevitable in a pragmatic trial, because of the complexities of naturalistic treatment settings where not all influencing factors on our intervention and the outcomes can be controlled. Despite this, we hypothesize that this program will improve the quality of care for patients with bipolar disorder, thereby optimizing symptomatic recovery, level of functioning and in the end their quality of life.The authors declare that they have no competing interests.TV drafted this paper and it was modified by all other authors. AB, RK, BM, PG, JR en TV contributed to the design of the study protocol. TV and BM designed the intervention protocol, which was discussed and enhanced with the expert panel on two occasions. All authors contributed to and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-244X/11/133/prepub


Tsunami of 2004, caused by a 9.0 magnitude earthquake, is the most devastating tsunami in modern times, affecting 18 countries in Southeast Asia and Southern Africa, killing more than 250,000 people in a single day, and leaving more than 1.7 million homeless. However, less reported, albeit real, is its impact in the islands of the Indian Ocean more than 1,000 miles away from its epicenter. This is the first peer-reviewed paper on the 2004 tsunami events specifically in the eleven nations bordering the Indian Ocean, as they constitute a region at risk, due to the presence of tectonic interactive plate, absence of a tsunami warning system in the Indian Ocean, and lack established communication network providing timely information to that region. Our paper has a dual objective: the first objective is to report the 2004 tsunami event in relation to the 11 nations bordering the Indian Ocean. The second one is to elaborate on lessons learned from it from national, regional, and international disaster management programs to prevent such devastating consequences of tsunami from occurring again in the future. Tsunami is a series of ocean waves typically caused by large undersea earthquakes or volcano eruptions at tectonic plate boundaries. These surges of water may reach 100 feet and cause widespread destruction when they crash ashore. They race across the sea at a speed up to 500 miles per hour and cross the entire Pacific Ocean in less than one day. Their long wavelength means that they lose very little energy along the way.Tsunami of December 2004, caused by a 9.0 magnitude earthquake, is the most infamous tsunami of modern times with disastrous consequences in many areas humanitarian toll: it affected more than 18 countries from Southeast Asia to Southern Africa, killing more than 250,000 people in a single day and leaving more than one million homeless,economic toll: it left several million of dollars of economic loss affecting fishing and tourist industries,environmental and medical threats including water pollution and flooding and endemic diseases.The rationale for writing this paper is to report the tsunami events in the eleven nations bordering the Indian Ocean, as they received less publicity than their Southeast Asian countries counterpart although the 2004 tsunami had real humanitarian, economic, and environmental impact in these regions more than 1,000 miles away from the epicenter [Furthermore, these regions are at risk from the devastating effects of future tsunami due to the presence of a tectonic interactive plate , absenceThis paper is a review of documents collected by WHO and other organizations/authors involved in disaster management during the 2004 tsunami.These eleven countries bordering the Indian Ocean are Mauritius, Madagascar, Reunion Island, and Seychelles, Comoros islands and by geographical extension include countries in southern borders of Africa such as Somalia, Tanzania, Mozambique, and South Africa.These individual countries suffered humanitarian loss with more than 3,000 people killed and left more than 10,000 homeless about 1,000 miles away from epicenter. In terms of economic toll, several million dollars were reported accompanied by environmental threat due to flooding.Specifically included is a country by country report  with oth Large waves completely submerged one village in north of the island. Although there was no death published, a significant economic loss in millions of dollars was reported.http://savannah.gatech.edu/cee/groups/tsunami/madagascar.html). Waves up to 10 meters were seen in southeastern region of the island. There was one death and more than 1,000 people homeless. Furthermore, there were considerable economic damages inflicted in touristic and fishing industries and infrastructure disruptions due to flooding and beach erosion , which focused on defining disaster management and reduction  of disaster by all the participating countries,development of integrated regional information network (IRIN) with the goals of creation of an early warning system for the islands in the Indian Ocean and ensuring adequate equipment to manage natural disasters including tsunamis.The important issues are the cost of establishing such warning system in the Indian Ocean, the transfer of existing technology versus improving, old one, global warming and extreme weather events in that region.A series of international meetings have been convened to discuss the role international organizations :international coordination meeting sponsored by UNESCO intergovernmental oceanographic commission in Mauritius in 2005 with a dual goal:development of tsunami warning and mitigation system,coordination of national tsunami warning center with regional centers,international strategy for disaster reduction (UN/ISDR) attended by representatives from the Indian Ocean countries and international experts on early warning system in 2006 with two objectives:funding of projects and rehabilitation of roads and bridgesincrease public awareness and training of key staff in tsunami preparedness and warning at all levels. The main challenge for all the islands of the Indian Ocean is to coordinate all the national efforts with existing regional and international endeavors to meet their stated priorities before the next tsunami events. The role of one special group of physicians should be mentioned at all these levels.Emergency physicians are knowledgeable on the risks of tsunami and are trained in the field of disaster management, thus they are true expert. They should get involve as leaders in local, national, and international organizations as resources in disaster management as well as humanitarian institutions such as Red Cross.This paper is the first peer-reviewed paper on the impact of the 2004 tsunami on the islands bordering the Indian Ocean and the lessons learned from this event from national, regional, and international organizations to prevent such events from occurring again in the future.Tsunami is an ever-present and real threat for the these islands of the Indian Ocean due to the presence of a tectonic interactive plate.Their disaster management priority is the development of an early tsunami warning system in order to effectively and timely communicate with all the people in that region. Disaster management should involve national, regional, and international organizations at all levels in order to develop tsunami program, fund tsunami projects, and continue research program.


In order to improve the health of the most vulnerable groups in society, the WHO Commission on Social Determinants of Health (CSDH) called for multi-sectoral action, which requires research and policy on the multiple and inter-linking factors shaping health outcomes. Most conceptual tools available to researchers tend to focus on singular and specific social determinants of health (SDH) . However, a new and innovative conceptual framework, known as social quality theory, facilitates a more complex and complete understanding of the SDH, with its focus on four domains: social cohesion, social inclusion, social empowerment and socioeconomic security, all within the same conceptual framework. This paper provides both an overview of social quality theory in addition to findings from a national survey of social quality in Australia, as a means of demonstrating the operationalisation of the theory.Data were collected using a national random postal survey of 1044 respondents in September, 2009. Multivariate logistic regression analysis was conducted.Statistical analysis revealed that people on lower incomes (less than $45000) experience worse social quality across all of the four domains: lower socio-economic security, lower levels of membership of organisations , higher levels of discrimination and less political action  and lower social empowerment. The findings were mixed in terms of age, with people over 65 years experiencing lower socio-economic security, but having higher levels of social cohesion, experiencing lower levels of discrimination  and engaging in more political action . In terms of gender, women had higher social cohesion than men, although also experienced more discrimination .Applying social quality theory allows researchers and policy makers to measure and respond to the multiple sources of oppression and advantage experienced by certain population groups, and to monitor the effectiveness of interventions over time. Both trans-nationally -3 and wiWe concur with the need to focus on both the multiple forms of disadvantage and thus the complex and holistic policy responses required, although we argue that many conceptual frameworks currently used in public health research do not lend themselves easily to being useful for these purposes. For example, there are large amounts of research which provide evidence that certain population groups are more socially excluded , have loThis paper attempts to redress this problem. Firstly we introduce a theoretical and conceptual framework developed in social policy in Europe, known as social quality theory -16, whicThe notion of social quality is gaining international recognition as an innovative theoretical and methodological tool for researchers and policy makers in social policy ,14-22. H"the extent to which people are able to participate in the social, economic life and development of their communities under conditions which enhance their wellbeing and individual potential" [Social quality has been defined by Beck (1998: 3) as tential" . Social tential" . The indtential" . Whilst as individuals, rather than as individuals in groups, communities and other social relations. The development of social quality theory is an attempt to redress this imbalance, by refocusing on 'the social', which does not sit in contradistinction to 'the individual', but rather, akin to the ideas of Bhaskar [Social quality theory was originally developed as a response to the hegemony of individualised quality of life measures , and ind Bhaskar , Archer  Bhaskar  and Gidd Bhaskar ,29, are Social quality theory does not dismiss the individual quality of life approach, since it is useful for clinical situations and individualised solutions. However, the point is that it provides relatively little use for developing population-level social or public health policy. The individual quality of life approach can tell us a great deal about how to improve individual circumstances  but it cannot elucidate either the reasons why some population groups fair worse than others in society, or more importantly, how we may be able to respond in terms of policy and practice . In addinormative factors that determine the quality of the social structures, policies and relationships within a society: social justice; solidarity; equal value of all humans; and human dignity [conditional factors which are aimed at rendering the normative factors 'researchable'. The four conditional factors are socio-economic security , social cohesion (linked to solidarity), social inclusion  and social empowerment (linked to human dignity).Social quality theory has both ideological and methodological underpinnings. In terms of its underlying ideology, social quality theory argues that there are four key  dignity . A socieSocio-economic security is concerned with the extent to which people or groups have access to, utilisation of, and successful outcomes related to, a variety of resources over time, and the protection from poverty and other forms of material deprivation. These resources may be associated with, among other things, finance, housing, healthcare, employment and education, which have been shown to be important in shaping inequities in health and health care ,31. SociAs can be seen in this brief overview, the multi-dimensional and multi-level approach represents an advancement of public health research, theory, policy and practice, which is not solely aimed at either individuals or systems, but instead realises the intimate linkages between systems and individuals and thus provides an understanding of both within the same theoretical framework. The long-term aim of developing and implementing social quality theory is to enhance the social quality of peoples' lives , but as already stated, we firstly need to have empirical data on the domains of social quality  before we can inform changes in policy and/or practice.It has been suggested that research in social epidemiology and public health in general is strongly focused on empirical research and remains atheoretical . RichterThe original indicators of social quality, developed by the ENISQ, were developed into a questionnaire, which was tested for both validity and reliability , includiA postal questionnaire survey of a random sample of households was undertaken for each Australian state. It was necessary to divide the national population by state  because A copy of the questionnaire, a letter of information, a letter of introduction, and a stamped return envelope was sent to each mail-out address September 2009. A postcard reminder was only sent out to those who had not returned the questionnaire after two weeks.The hypothesised response rate was around 20% , and in order to obtain a final sample size of 1000, it was estimated that an initial sample of 5000 addresses was required. Out of the 5000 surveys that were sent out, 638 were returned due to invalid addresses and 1044 were returned completed surveys. The actual response rate of 24% 1044/4362) was regarded as acceptable for this type of survey because of the decline in participation in survey research. Between 1986-1995, survey response rates in Australia remained consistent at around 50% . However62 was reAfter data entry had been completed, an extra two variables were created from the postcode of the respondent. Both variables are derived from the national census. The first variable is called the Socio-Economic Indicator For Areas (or SEIFA) and provides a score for the level of socio-economic deprivation or affluence of the area. The second variable is called Accessibility and Remoteness Indicator for Areas (or ARIA) which provides a score for the distance of the postcode from major service centres. Both of these variables were thought to be potentially important when analysing differences in social quality.'Please indicate whether you or your family have experienced any of the following negative life events in the last 12 months?', 'How much do you trust various groups of people?' were found to be associated with demographic variables; however, for the purpose of this paper we have limited our results to one variable per domain. The independent variables chosen to investigate associations between social quality and demographic variables were age, sex, SEIFA IRSD (Socio-economic Index for Areas Index of Relative Socio-economic Disadvantage), ARIA , employment status and income.Initially, descriptive analyses were undertaken in order to explore overall levels of social quality. We then performed bivariate logistic regression analyses in order to explore simple associations between a range of socio-demographic variables and the indicators of social quality. For the regression models, four questions identified by the ENISQ in 2004  as indicBivariate analyses were conducted using Chi Squares (Cramer's V and Phi) as well as T-tests, one-way ANOVAs, Mann-Whitney U, and Kruskal-Wallis H. Each test produced a table which was subsequently analysed for statistically significant associations. Any bivariate odds ratios with P < 0.25 were then included in multivariate logistic regression analyses . The tabThis study was given ethical clearance by the Social and Behavioural Research Ethics Committee at Flinders University.The following section provides statistical description and analysis of the data. One survey question is presented to investigate each of the four domains of social quality. The sample questions used to investigate each of the four domains were chosen because each question has been identified as an valid and reliable indicator of one of the four domains by the ENISQ in 2004 .This section of the paper provides statistical description and analysis of the data, focussing specifically on the four conditional factors within the social quality theory, namely socio-economic security, social cohesion, social inclusion and social empowerment. One multivariate regression model is presented for each of the four domains as a means of introducing the practical application of social quality theory. Each of the four models includes one social quality variable  as the dependent variable with the socio-demographic variables  as independent variables.There were a number of variables that related to socio-economic security within the dataset, but for the purpose of this paper, we have just used one variable. The question used to measure socio-economic security in the survey is outlined below:During the past year, did you1. Save money2. Just get by3. Spent some savings4. Spent savings and borrowed moneyIn terms of saving or spending money, Table The variable chosen to examine social cohesion was:For each of the following organisations, please indicate your membership status1. Church or religious organisation2. Sport or recreational organisation3. Art, music, educational, or cultural organisation4. Other community based organisationIn terms of membership of organisations, 26% were members of church organisations, 41% were members of sporting organisations, 22% were members of art/cultural organisations and 36% were members of community based organisations.The variable was then recoded into two categories, those who were a member of at least one organisation (71.0%) and those who were not a member 29.0%). Univariate odds ratios examined the relationship between those who were a member and demographic characteristics , and the multivariate analysis is presented in Table 9.0%. UniTable Social inclusion deals with an individual's accessibility to institutions and the degree of social integration that the individual attains to . The varDuring the past 12 months, have you ever experienced discrimination against you due to any of the following reasons?1. Physical/mental disability2. Age3. Sexual harassment4 Gender5. Nationality6. Physical appearance7. Ethnic background8. Criminal record9. Religion10. OtherThe proportion of respondents who had experienced discrimination varied: 4% experienced disability discrimination, 14% age discrimination, 2% sexual discrimination, 7% gender discrimination, 4% nationality discrimination, 6% physical appearance discrimination, 3% ethnic background discrimination, 1% criminal record discrimination, 2% religious discrimination, and 4% other discrimination. The variable was then recoded into two categories, those who had experienced discrimination (23.9%) (excluding the 'other' responses due to the large number of missing) and those who had not experienced discrimination (76.1%). Univariate odds ratios then examined the relationship between those who experienced discrimination and demographic characteristics . The multivariate analysis is presented in Table Table In interpreting the data in Table The variable chosen to examine social empowerment was:Have you or would you participate in any of the political actions listed below?1. Petition2. Boycotts3. Protests4. Strikes5. Online political actionsWhilst previous validity testing found this question to be a good proxy for social empowerment, we also recognize the potential for some groups  to perceive little need to engage in the political actions listed in this question, even though they are highly socially empowered.In terms of political actions, 70% of people took part in petitions, 19% in boycotts, 23% in protests, 19% in strikes and 13% in online political action.The variable was then recoded into two categories, those who had participated in a political action 74.1%) and those who had not (25.9%). Univariate odds ratios then examined the relationship between those who participated in a political action and demographic characteristics . The multivariate analysis is presented in Table .1% and tTable In summary, the findings outlined by the above questions suggest that retired respondents have lower socio-economic security, and women and respondents of lower income have lower social inclusion. However, the findings also suggest lower social quality for disadvantaged individuals who scored poorly in social cohesion, social empowerment and social inclusion. This snapshot of social quality in Australia identifies the gravity of the lack of social quality for poor people, the financial security for older people, and the discrimination experienced by women.For well over twenty years policy makers, health and social reformers in Australia have advocated the practical sense of an integrated approach in policy making and service delivery; to move from 'silos to a system', towards 'whole of government approaches', and 'health in all' -48. HoweSocial quality theory aims to move beyond partial understandings of social problems informed by single disciplinary knowledge, and partial explanations afforded by theories that examine only one area of social life. On the basis of the data reported upon in this paper we contend social quality is useful because of this emphasis on a total or integrated picture. The picture developed in this paper, using the four conditional factors of social quality, is that the social quality of life in Australia is high across the four domains. Socio-economic security is high (except for the third of people who spent savings and/or borrowed money), social cohesion is fairly high (relatively high levels of membership of organisations), social inclusion is high (low levels of perceived discrimination) and social empowerment is fairly high .However social quality theory, in drawing together individual measures, does more than provide a holistic picture. It develops a picture of systematic differences in social quality between population groups at a point in time. As seen in this paper, notwithstanding the relatively positive picture of social quality in Australia, there were systematic differences in social quality between population groups. This was most pronounced for people on lower incomes (less than $45000) who were more likely to have spent their savings (lower socio-economic security), had lower levels of membership of organisations , experienced higher levels of discrimination , and were involved in less political action . On all four domains of social quality, people with lower incomes were disadvantaged and may therefore be seen as having generally lower social quality than people on higher incomes. The picture identified higher social quality in older respondents. Older respondents had higher levels of membership of organisations and were more likely to trust , experienced lower levels of discrimination  and engaged in more political action  than younger respondents. The findings regarding higher levels of membership may be explained by older respondents being more likely to be retired or working part-time and thus, having more opportunity to be members of organisations. The findings also identified lower social quality for older people in respect to financial security. This may be indicative of the fact that older individuals are likely to be living off of pensions and/or retirement plans and are thus, less likely to be saving which does not necessarily indicate poor social quality. However, this finding remains an important consideration in view of the estimations of population numbers who will be over 65 years by the year 2040 and that life expectancy is lengthening. In terms of gender, women experience more discrimination  than men. This may reflect lower social inclusion in women but may also be interpreted from the perspective that women and men may differ in their assessment of discriminatory acts.The difference here between the social quality findings and those from research in the individual research areas  is that in this study the findings about social cohesion, social empowerment, social inclusion and socio-economic security are pulled together empirically which makes it more amenable to policy changes and action. Our findings highlight areas of lower social quality but in providing a snapshot of the findings, we acknowledge that a more comprehensive presentation of our survey results will lead to more generalisable results regarding areas of high and low social quality. Nonetheless, it is not easy to ignore the gravity of the lack of social quality for poor people, the long term implications of low financial security for older people, or the discrimination experienced by women. Our initial approach to operationalising social quality theory emphasises social solidarity as a policy principle and data analyses may be viewed through a socio-political lens.In addition there is further practical utility for policy makers derived from value of an integrative perspective on social quality in a context of hyper-fragmentation in the Australian social welfare system. The Australian social policy system has always been a mixed welfare economy  but thisSocial quality theory is an innovative and beneficial theoretical tool that warrants greater utilisation in research and policy development in social determinants of health. The findings presented in this paper provide only an example of how the survey conducted may be used to inform policy. The findings presented here are too general but provide a snapshot of the utility of the tool for policy development. This paper is a first attempt to demonstrate the operationalisation of social quality theory and how data outcomes may be used to inform policy. Statistical analyses revealed that people on lower incomes (less that $45000) had lower socio-economic security, lower levels of membership of organisations , experienced higher levels of discrimination and were involved in less political action  and had lower social empowerment. The findings were more mixed in terms of age, with people over 65 years experiencing lower socio-economic security, but having higher levels of social cohesion, experiencing lower levels of discrimination  and engaging in more political action . In terms of gender, women had higher social cohesion than men, although also experienced more discrimination .As demonstrated in this paper, the social quality approach keeps the social analytical lens wide, both in how the social is conceived and related, and in how social and health policy responses are formulated. In addition, it may be used to measure the outcomes of policy and political interventions over time through repeated measurement within a given population. We suggest that whilst we know the potential impact of policy on health in terms of the social and structural determinants, we need a way of measuring the affects of policy on improving the condition under which health is determined. We argue that the social quality approach is a comprehensive measure of social quality  which may be used as such a tool for monitoring the impact of policy on health. These data may then be used as a point of comparison for future investigations into the social quality of Australians as a means of identifying the potential effectiveness of public health policy.The authors declare that they have no competing interests.CNL and SBM participated in the design of the study, data collection, and piloting. TKG was responsible for the sampling strategy and obtaining a random sample of the electronic white pages. TKG, CNL, SBM and PRW carried out the data analysis. PRW, SBM and FV drafted the manuscript. PRW wrote the grant application and received funding for the study. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/11/630/prepubSocial Quality questionnaire. This is a copy of the validated questionnaire used within the study to measure Social Quality.Click here for file


This paper aims to identify health research priorities that could improve the rate of progress in reducing global neonatal mortality from preterm birth and low birth weight (PB/LBW), as set out in the UN's Millennium Development Goal 4.We applied the Child Health and Nutrition Research Initiative (CHNRI) methodology for setting priorities in health research investments. In the process coordinated by the World Health Organization in 2007–2008, 21 researchers with interest in child, maternal and newborn health suggested 82 research ideas that spanned across the broad spectrum of epidemiological research, health policy and systems research, improvement of existing interventions and development of new interventions. The 82 research questions were then assessed for answerability, effectiveness, deliverability, maximum potential for mortality reduction and the effect on equity using the CHNRI method.The top 10 identified research priorities were dominated by health systems and policy research questions . These were followed by priorities for improvement of the existing interventions  to keep LBW infants warm in community settings). The highest-ranked epidemiological question suggested improving criteria for identifying LBW infants who need to be cared for in a hospital. Among the new interventions, the greatest support was shown for the development of new simple and effective interventions for providing thermal care to LBW infants, if KMC is not acceptable to the mother.The context for this exercise was set within the MDG4, requiring an urgent and rapid progress in mortality reduction from low birth weight, rather than identifying long-term strategic solutions of the greatest potential. In a short-term context, the health policy and systems research to improve access and coverage by the existing interventions, coupled with further research to improve effectiveness, deliverability and acceptance of existing interventions, and epidemiological research to address the key gaps in knowledge, were all highlighted as research priorities. GeneratTo assist policy makers and donors alike in understanding the potential of different research avenues to contribute to reducing the burden of disease and disability, the Child Health and Nutrition Research Initiative (CHNRI) recently developed a methodology that allows systematic listing and transparent scoring of many competing research options, thus exposing their strengths and weaknesses -8. The DThe cause “preterm birth complications”, which comprises the old causes “preterm birth” and “low birth weight” (PB/LBW), is on a continuous rise as a proportional cause of child deaths globally and it may become the leading cause over the next decade, as the importance of infectious diseases steadily decreases. Currently, PB/LBW are estimated to cause around 1 million deaths each year . UnfortuThe CHNRI methodology for setting priorities in health research investments was proposed as a tool that could be used by those who develop research policy and/or invest in health research -8. This The WHO Maternal, Newborn, Child and Adolescent Health and Development program (MNCAHD) coordinated a large international exercise in 2007-2008, involving more than 200 experts from about 80 different countries, to identify health research priorities that could directly tackle the main causes of global child mortality: pneumonia, diarrhea, birth asphyxia, preterm birth/low birth weight and neonatal infections. The aim was to inform key global donors, public investors in health research, and international agencies on research investment policies that could support efforts to accelerate the progress toward the MDG4. Thus, the context for this exercise was a short-term one, set within the MDG4 and requiring an urgent and rapid progress in mortality reduction from childhood pneumonia rather than identifying long-term strategic solutions of the greatest potential. While defining this context, the WHO also recognized the importance of context-specific issues at local or regional levels, the large problem of pneumonia morbidity, and the beneficial effects of investments in the improvement of malnutrition and other cross-cutting and cross-sectoral issues ,18. FurtIndividuals with a wide range of technical expertise and regional representation were recruited to participate. A large list of research questions was drafted by the technical expert group based on recent systematic reviews and a survey of experts. Eventually, 21 researchers with interest in child, maternal and newborn health suggested 82 research ideas that spanned across the broad spectrum of epidemiological research, health policy and systems research, improvement of existing interventions and development of new interventions. They were organized using the CHNRI framework for listing research questions, shown in The five criteria for scoring  may be perceived to be of varying importance and the value given to each criterion may vary with the perspective of stakeholders. For example, parents who have experienced a pneumonia associated death may rate mortality reduction much higher than a research funder who may value answerability, or a health system planner who may be most concerned with deliverability. Hence, CHNRI undertook an exercise to poll a wide range of stakeholders and to weight the criteria based on values assigned by these stakeholders, as described elsewhere . The weiCompleted worksheets were returned to the group coordinator. The overall research priority score (RPS) was computed as the mean of the scores for the five criteria , weightewhere C designates the scores for relevant criteria.Average Expert Agreement (AEA) scores were also computed for each research question as the average proportion of scorers that agreed on the 15 questions asked. This is computed for each scored research investment option as:where q is a question that experts are being asked to evaluate competing research investment options, ranging from 1 to 15. For further details regarding the choice of methods, agreement statistics and interpretation see the Online Supplementary DocumentThe scores given to all 82 research questions from individual experts are presented in Online Supplementary Document (table w2), while the final list of priorities with intermediate and final priority scores for all research questions is presented in Online Supplementary DocumentThe predominance of research questions from the domain of health systems and policy research is not surprising, because technical experts were asked to define research priorities that could lead to notable improvements in reduction of PB/LBW mortality by the year 2015. This short time frame benefited research questions that proposed to identify key obstacles to delivery, affordability, and sustainability of implementation of existing cost-effective interventions on a larger scale. The exercise also highlighted the value of investments that aimed to improve and optimise the use of those interventions  in different contexts, and to develop entirely new approaches that could assist delivery or acceptance of the existing cost-effective interventions.Research questions seeking to develop new interventions had only three representatives among the 30 highest-ranked questions. This is not surprising given the short specified time frame (the year 2015) by when it would be difficult to envisage new interventions that could have substantial impact, as the CHNRI exercise was conducted in 2007 and 2008. The three ideas that were still encouraged by the experts were: (i) the development of new simple and effective interventions for providing thermal care to LBW infants, if KMC is not acceptable to the mother – which was ranked at the high 12th position on the final list; (ii) identifying micronutrients whose supplementation improves functional outcomes including survival in distinct subgroups of preterm and growth retarded infants; and (iii) development of new simple and effective interventions that prevent infections and improve survival, such as new emollients for massage  to 31.5 (the lowest-ranked) out of the maximum 100. Furthermore, there was also a substantial gradient in the level of agreement among the scorers on the priority of the 82 questions, investigated by calculating “average expert agreement” (AEA). The AEA scores ranged from 0.533 to 0.828 . AEA indicates the proportion of scorers that gave the same most frequent answer to an average question they were asked in relation to a specific research investment option. Average expert agreement values are also presented for the top and bottom 10 research questions in Investment in global health research today would benefit from consensus regarding the context, appropriate investment strategies, and co-ordination to achieve significant reduction of the disease burden in the foreseeable future. The present exercise was designed to assist investors and policy makers in making more informed choices on their investments in health research on PB/LBW by making apparent the risks and potential benefits associated with investments in a broad spectrum of health research options. The expected “profit” from investments is associated with generating new knowledge that can be translated into development of new (or improvement of existing) interventions, which are effective, deliverable, affordable, and can reduce the existing burden of disease and disability in an equitable way. The risk is associated with research that is not likely to be answerable, or that develops products unlikely to be effective, deliverable, affordable, or sustainable by those who need them most. Investors' preference for high-risk investment in health research is particularly questionable when it is occurring in a context that requires urgent progress, such as PB/LBW mortality. The focus on complex challenges of implementation , highlighted in this exercise, was reflected in many research questions being ranked near the top of the list of overall priorities.The context for this exercise was set within the MDG4, requiring an urgent and rapid progress in mortality reduction from low birth weight, rather than identifying long-term strategic solutions of the greatest potential. In a short-term context, the health policy and systems research to improve access and coverage by the existing interventions, coupled with further research to improve effectiveness, deliverability and acceptance of existing interventions, and epidemiological research to address the key gaps in knowledge, were all highlighted as research priorities.Although the advantages of the CHNRI methodology represent a serious attempt to deal with many issues inherent to a highly complex process of research investment priority setting, there are still concerns over the validity of the CHNRI approach and related biases. One of them is related to the fact that many possible good ideas (“research investment options”) may not have been included in the initial list of research options that was scored by the experts, and to the potential bias toward items that get the greatest press. Another concern over the CHNRI process is that its end product represents a possibly biased opinion of a very limited group of involved people. In theory, a chosen group of experts can have biased views in comparison to any other potential groups of experts. Those limitations are described and discussed in greater detail in the Online Supplementary DocumentThe implementation of the CHNRI methodology showed that, within the context of MDG4, a better balance should be achieved between specific domains of health research. Along with continuing strategic long-term investments in new interventions, which represent high-risk high-profit strategies, the CHNRI process suggested that more attention should be given to health policy research, health systems research, operations research, and research that addresses political, economic, social, cultural, behavioral, and infrastructure issues surrounding the problem of child mortality from PB/LBW. These domains of health research are rarely recognized as attractive by investors in health research because their results are unlikely to grab the newspaper headlines, get published in journals with high impact factors, or lead to patents and commercial products. Yet, they can generate new knowledge that can be very helpful in achieving real progress in disease burden reduction. The identified priorities are also in good agreement with the research supported by WHO’s MNCAHD Department at present. They emphasize the evaluation of existing interventions and the development and testing of new delivery approaches for existing interventions. They also highlight the value of research on preventive measures, with research on new interventions being downplayed within the short-term context.The context for this exercise was set within the MDG4, requiring an urgent and rapid progress in mortality reduction from PB/LBW, rather than identifying long-term strategic solutions of the greatest potential. In a short-term context, the health policy and systems research to improve access and coverage by the existing interventions, coupled with research to improve deliverability of existing cost-effective interventions in low resource contexts, and epidemiological research to address the key gaps in knowledge, were all highlighted as research priorities. These questions are mainly targeted at better understanding the barriers toward implementation, effectiveness and optimization of use of available interventions and programmes. If progress toward reduction of global PB/LBW mortality is to be improved by 2015, these are the research questions that are most likely to be of greatest importance. However, very few donors agencies recognize the importance of these domains of health research to readily invest in those options ,15,18. T