This study examined outcomes for two groups of stroke survivors treated in Veteran Health Administration (VHA) hospitals, those with a severe mental illness (SMI) and those without prior psychiatric diagnoses, to examine risk of non-psychiatric medical hospitalizations over five years after initial stroke.This retrospective cohort study included 523 veterans who survived an initial stroke hospitalization in a VHA medical center during fiscal year 2003. The survivors were followed using administrative data documenting inpatient stroke treatment, patient demographics, disease comorbidities, and VHA hospital admissions. Multivariate Poisson regression was used to examine the relationship between patients with and without SMI diagnosis preceding the stroke and their experience with non-psychiatric medical hospitalizations after the stroke.The study included 100 patients with SMI and 423 without SMI. Unadjusted means for pre-stroke non-psychiatric hospitalizations were higher (p = 0.0004) among SMI patients (1.47 ± 0.51) compared to those without SMI (1.00 ± 1.33), a difference which persisted through the first year post-stroke . Number of non-psychiatric hospitalizations were not significantly different between the two groups after adjustment for patient sociodemographic, comorbidity, length of stay and inpatient stroke treatment characteristics. Antithrombotic medications significantly lowered risk  for stroke-related readmission within 30 days of discharge.No significant differences in medical hospitalizations were present after adjusting for comorbid and sociodemographic characteristics between SMI and non-SMI stroke patients in the five-year follow-up. However, unadjusted results continue to draw attention to disparities, with SMI patients experiencing more non-psychiatric hospitalizations both prior to and up to one year after their initial stroke. Additionally, stroke survivors discharged on antithrombotic medications were at lower risk of re-admission within 30 days suggesting the VHA should continue to focus on effective stroke management irrespective of SMI. Persons with severe mental illness (SMI) including schizophrenia, bipolar disorder and major depression are approximately twice as likely to have a stroke ,2. IncreLittle is known about stroke survivors with SMI regarding their patterns of post-stroke hospitalization. Unplanned hospitalizations among stroke survivors are costly , may refThe current study compares the risk of non-psychiatric hospitalizations for veteran stroke survivors with and without SMI and examines patterns of hospitalization in Veterans Health Administration (VHA) hospitals over a five-year period. Veteran stroke survivors, whether or not they have severe mental illnesses, are vulnerable and have relatively poor health status. For example, the health status of veterans is consistently found to be poorer in comparison to the rest of the United States with increased rates of obesity , diabeteWe conducted a five-year retrospective cohort study of veterans identified through the U.S. Department of Veterans Integrated Service Network Five  as havinOur hypothesis was that stroke survivors with SMI would have increased risk of non-psychiatric hospitalizations over five-years compared to stroke survivors without SMI after adjustment for inpatient stroke treatment variation, age, race, marital status, education, income, health insurance coverage above VHA benefits, proximity of patient’s home to a VHA hospital, physical co-morbid conditions, prior pre-stork hospitalizations, mental co-morbid conditions and history of stroke risk factors of hypertension, diabetes, and peripheral vascular disease. The rationale for this hypothesis was that individuals with SMI have myriad lifestyle factors, health care access difficulties, and medication side effects, which increase their risk of physical diseases resulting in greater non-psychiatric hospitalization rates.The International Classification of Diseases, Ninth Revision (ICD-9) was used to identify ischemic and hemorrhagic stroke participants. ICD-9 diagnosis codes have been extensively used for stroke outcomes research , 28 and Non-psychiatric hospitalizations were defined as inpatient admissions for any cause except treatment for psychiatric or substance abuse disorders from the VHA Inpatient data file. Consistent with previous research, non-psychiatric hospitalizations were considered within the following time intervals from index stroke discharge: within 30 days, 31 to 90 days, 91 to 364 days, and within year-long intervals thereafter up to five years [Unadjusted bivariate analyses were used to describe the differences between stroke survivors with SMI compared to those without SMI for all covariates and hospitalizations over time. Bonferroni corrected significance was used to minimize the chances of making a Type I error across multiple comparisons with a p< 0.0030 needed for statistical significance. Hospitalizations in the VHA dataset were skewed to the right with substantial zero admissions at each time interval and had distributions with long right tails. Deviance and Kolmogorov-Smirnov tests for goodness-of-fit were calculated for negative binomial, zero inflated negative binomnial, ordered probit and logit, and Poisson distribution models for each time period examined. The data best fit a Poisson distribution model for every time period except for between 4 and 5 years post-stroke, where a negative binomial model had preferable deviance and Kolmogorov-Smirnov scores. However, the Poisson model for between 4 and 5 years post-stroke had a nearly equal mean (1.48) and variance (1.63). Therefore, for consistency Poisson regression was used at every time period with log-linked functions and corrections for overdispersion to test the hypothesis that SMI is associated with non-psychiatric hospitalizationsAdditionally, negative binomial regression model for the time period between 4 and 5 years post-stroke was calculated yielding equivalent results as the Poisson regression. Confounding between the variable SMI and other independent variables was assessed by adding and then removing each independent variable to a Poisson model. Independent variables that altered the parameter estimate for SMI by greater than ±15% were considered to be confounding and were removed from final models. All statistical calculations were performed using SAS version 9.3 . The UniThe study population consisted of 523 patients with an index stroke in fiscal year 2003, 100 with SMI comorbidity and 423 with no SMI comorbidity. Causes of non-psychiatric hospitalizations were examined in the year preceding stroke and after being discharged from inpatient care for index stroke. In the year prior to stroke, patients with SMI had significantly (p<0.05) more admissions related to cardiovascular (SMI 46.3% vs. No SMI 31.6%) and infectious (SMI 17.0% vs. No SMI 8.7%) causes, and fewer admissions related to orthopedic (SMI 1.4% vs. No SMI 10.1%) causes. Patients with SMI had significantly (p<0.05) more hospitalizations related to cardiovascular (SMI 42.5% vs. No SMI 31.2%) causes and significantly fewer hospitalizations related to recurrent stroke (SMI 1.5% vs. No SMI 6.7%) during the first year post-stroke. Patients with SMI, who were re-hospitalized with a stroke complication within 30 days after being discharged for index stroke had significantly more cardiovascular complications (SMI 42.8% vs. No SMI 32.4%), but fewer hospitalizations related to neurological causes (SMI 18.4% vs. 32.4%). During the period 31 to 90 days post-stroke SMI patients had significantly more hospitalizations related to cardiovascular (SMI 40.0% vs. No SMI 25.5%) and infectious (SMI 20.0% vs. No SMI 9.9%) causes. Patients with SMI had significantly more cardiovascular causes (SMI 37.0% vs. No SMI 26.5%) of hospitalization during the period of 1 to <2 years post-stroke. There were no significant differences between patients with and without SMI regarding causes of hospitalization in any time period greater than two years.Tables While history of SMI was not associated with post-stroke non-psychiatric hospitalizations after adjustment, a number of other independent variables were signficantly associated with non-psychiatric hospitalizations. Patients discharged on antithrombotic medications had a lower risk for re-admission  for a stroke-related complication within 30-days of index stroke discharge compared to patients not discharged on antithrombotics. During the time period 91 to 364 days post-stroke discharge minority patients  had signficantly lower risk for non-psychiatric hospitalizations compared to white patients, while patients with higher Elixhauser co-morbidity index scores  were at greater risk for non-psychiatric hospitalizations. Additionally, during the time period 91 to 364 days the longer the initial stroke hospital length stay the greater risk for non-psychiatric hospitalizations . During the time period 1 to < 2 years post-stroke patients with higher Elixhauser co-morbidity index scores  and patients with more hospitalizations in the year preceding index stoke  were at signficantly greater risk for non-psychiatric hospitalizations, while patients with a history of substance abuse  had lower risk for non-psychiatric hsopitalization. Additionally, patients discharged on statin medications  were at signficantly increased risk for non-psychiatric hospitalization. During the time period 3 to < 4 years post-stroke patients with higher Elixhauser co-morbidity index scores  were at significantly greater risk for non-psychiatric hospitalizations, while patients with at history of depression  and a history of substance abuse  were at lower risk for non-psychiatric hospitalizations. Lastly, during the time period of 4 to < 5 years post-stroke, patients with higher Elixhauser co-morbidity index scores  and patients with more hospitalizations in the year preceding index stroke  were at signficantly greater risk for non-psychiatric hospitalizations.Tables The aim of this study was to determine the relationship between SMI and non-SMI and the risk for non-psychiatric hospitalization in the five years after index stroke. In unadjusted descriptive analyses, patients with a history of SMI had significantly higher mean non-psychiatric hospitalizations in the year prior to index stroke and over the course of the entire first year post-stroke compared to patients with no SMI comorbidity. In Poisson regression analysis after adjusting for a broad set of patient characteristics, differences in non-psychiatric hospitalizations between the two groups were no longer significant. Patient characteristics included in the regression analysis were age, marital status, income, insurance status, proximity to hospital, physical co-morbidity, acute mental health history, hospital length of stay at index stroke, and quality of inpatient stroke treatment. This analysis highlights that patients with SMI are medically complex with multiple risk factors for hospitalization, including significantly higher levels of physical co-morbidity. Patients with this type of profile, notwithstanding mental illness, are likely to have increased non-psychiatric hospitalizations. Because individuals with SMI have extensive co-morbidity , 6, tendOur findings differ with several studies examining the association between hospital admissions and mental illness in the general population. Saravay and colleagues  found thIn our sample, 43.3% of veterans had health insurance coverage with Medicare or Medicaid or both. Patients with SMI were significantly more likely (70%) to have only VHA benefits compared to those without SMI (54%). Those veterans with Medicare or Medicaid are likely to have received a portion of their care outside of the VHA system. Since we did not have access to data describing non-VHA care we are unable to account for the full spectrum of care delivered to stroke patients in our sample. However, it is more likely that stroke survivors with SMI received more of their care in the VHA system compared to those without SMI. Nevertheless, insurance status was not a significant predictor of hospitalizations in our sample.It is possible that the results obtained by the regression analysis reflect the success of longstanding effort to integrate physical and mental health care in the VHA. Hankin and colleagues  indicateIt is notable that in the time period of within 30-days post-stroke, both SMI and non-SMI patients who were discharged on antithrombotic medications had significantly lower risk for stroke-related readmission. Blood clots complicate recovery from stroke  and antiThere are several limitations of our study that may have implications on the interpretation and generalizability of results. First, caution should be used when generalizing results beyond the VHA because of the unique sociodemographic and health profiles of the veteran population and the integrated nature of mental health care within the VHA. Second, the study utilized administrative data that, as we have noted, has limitations. Third, as mentioned previously, our data set does not contain health care utilization outside of the VHA system. Since veterans without SMI were more likely to have Medicare, Medicaid or other insurances, they would be more likely than the SMI to have utilized health services that remain unmeasured in this study. Further, since the VHA does not provide emergency department services for acute stroke, patients being transported to the hospital in response to a 911 call will be taken to a non-VHA hospital. We assume that veterans without health insurance, and particularly those with SMI, who require hospitalization will be transferred as soon as possible to the VHA. Consequently, examining non-VHA care might yield different results regarding the relationship between SMI and non-psychiatric hospitalizations. Fourth, several additional relevant variables were not available for our analysis. For instance, there were no direct measures of stroke severity based on clinical measures, rather we relied on index stroke hospital length of stay as a proxy for severity. Data on lifestyle factors such as obesity, alcohol use, smoking, and physical activity were also not available. Additionally, antipsychotic medication usage was not considered in regression models and may have provided valuable insight into the results. These factors should be assessed in future studies.Strengths of the study are 1) the VHA system is one of the largest integrated and standardized health systems in the United States and regular audits conducted by clinical specialists are in place to cross-check diagnosis codes with more robust patient chart review . MoreoveThe severely mentally ill present a challenging and costly patient population for health systems. Although previous studies have examined hospitalizations among stroke survivors, limited data are available on the burden of SMI on post-stroke non-psychiatric hospitalizations. Unadjusted results highlight differences between the SMI and non-SMI stroke survivors, with the SMI experiencing more non-psychiatric hospitalizations both prior to and up to one year after their initial stroke. After adjusting for numerous patient characteristics, we found that patients with SMI, who were receiving services in the VHA system, were not at higher risk for non-psychiatric hospitalization during any time period after their index stroke for up to five years, when compared to patients without SMI. These findings suggest that the integrated nature of VHA healthcare for patients with SMI may confer benefits to this high risk population through coordination between mental and physical health care. Because integrated services for the SMI are considered one of the strengths of the VHA, our findings are provocative, suggesting that the VHA model may be useful to other health systems as the country is challenged by an aging population living with SMI, stroke, and other chronic conditions. Additionally, the adjusted difference demonstrating that individuals discharged on antithrombotic medications were at lower risk of re-admission within 30 days highlight the importance of this quality indicator for effective stroke management, irrespective of mental illness.S1 AppendixCode identifying ICD-9 diagnosis, procedure, and inpatient pharmacy administration codes for stroke processes of care.(DOCX)Click here for additional data file.


Self-management support for chronic obstructive pulmonary disease (COPD) patients is recommended by UK national guidelines, but extent of implementation is unknown. We aimed to describe self-management behaviour and support among COPD patients and explore behaviour associated with having a self-management plan. We undertook cross-sectional analysis of self-reported data from diagnosed COPD patients in the Birmingham COPD Cohort study. Questionnaire items relevant to self-management behaviour, knowledge of COPD, receipt of self-management plans and advice from healthcare professionals were examined. Multiple regression models were used to identify behaviour associated with having a self-management plan. One-thousand seventy-eight participants  years) were included. The majority reported taking medications as instructed  and receiving annual influenza vaccinations . Only 400 (40.4%) participants had self-management plans, 538 (49.9%) reported never having received advice on diet/exercise and 110 (42.7%) current smokers had been offered practical help to stop smoking in the previous year. General knowledge about COPD was moderate ; max score 65), corresponding to 48.5% of questions answered correctly. Having a self-management plan was positively associated with self-reported adherence to medication , attendance at a training course , attendance at a support group  and better disease knowledge . Primary care healthcare professionals should ensure more widespread implementation of individualised self-management plans for all patients and improve the lifestyle advice provided. Health professionals should ensure all patients with chronic lung disease receive individualized self-management plans and lifestyle advice. UK national guidelines state that patients with chronic obstructive pulmonary disease (COPD) should receive personalized self-management plans and comprehensive support to help them manage their disease. Ainee Khan and colleagues at the University of Birmingham analyzed patient questionnaire data gathered during the Birmingham COPD Cohort study to explore self-management behavior, receipt of self-management plans and advice, and patient knowledge of COPD. Of 1,078 participants, only 400 had self-management plans, and less than half reported receiving lifestyle advice or support. Those with plans were more likely to adhere to medication, had greater knowledge about COPD and were more likely to attend support groups and training courses. The authors recommend carefully-planned, wider implementation of COPD self-management plans and associated support. It affects at least 1.9% of the UK population2 and is a costly disease with acute exacerbations being the second leading cause of emergency respiratory hospital admissions in England,3 with a similar burden worldwide. Such exacerbations lead to poor prognosis for patients, with reductions in health-related quality of life and increased risk of mortality.4Chronic obstructive pulmonary disease (COPD) is an important long-term condition characterised by persistent decline in airflow6 Exact definitions of self-management and the most effective components of interventions to support patients are ongoing debates.7 Self-management support programmes should be collaborative between healthcare professionals and patients, to help them acquire skills to understand and manage their medications and exacerbations, adopt healthier behaviours and manage the social-emotional consequences of the disease.11 Systematic reviews among patients with COPD show that overall, interventions by healthcare professionals to support patient self-management reduce respiratory-related hospital admissions and improve quality of life,9 although the content of the interventions are complex and heterogeneous and which components are the most important is still unclear.13Support to help COPD patients self-manage their condition is recommended by national guidelines to improve their health-related quality of life and reduce avoidable inpatient admissions.6Despite limitations in our understanding of which self-management support strategies are the most effective, guidance from the National Institute for Health and Care Excellence (NICE) recommends that all patients with COPD should receive an individualised comprehensive management plan that includes information and educational material about the condition and its management, and that those at risk of exacerbations should be offered advice about how to recognise and respond promptly to the symptoms of an exacerbation.14 In this paper, we describe the current self-management behaviours of patients with COPD in a large primary care cohort in Birmingham, UK. We also describe the support that patients report receiving from their healthcare professionals and whether a collaborative self-management plan is associated with positive self-management behaviours in real life. Our study, therefore, may help in designing and implementing future self-management interventions.The literature describing self-management behaviours of COPD patients in the UK and the support they receive is minimal.At the time of analysis, 1078/1547 participants (69.7%) had returned a valid 6-month questionnaire  were male, 258 (24.3%) were current smokers and 653 (61.5%) were former smokers  did not meet the NICE criteria for airflow obstruction at the baseline study assessment. Of those that did, most respondents  had mild to moderate disease (GOLD stage 1 and 2). Almost two thirds (62.9%) of respondents reported severe dyspnoea  grade 3–5) and the mean COPD Assessment Test (CAT) score was 19.3 (SD 8.6), indicating moderate impact on patients’ lives. The most prevalent co-morbidities reported by patients were hypertension  and asthma . There were no marked differences in baseline characteristics between all included participants diagnosed with COPD and respondents to the 6-month questionnaire  reported taking their inhalers or medications as instructed Table . In the The mean overall disease knowledge score of respondents on the Bristol COPD Knowledge Questionnaire (BCKQ) scale was 31.5 (SD 10.7) out of a maximum score of 65 (score range: 0–56). This corresponds to answering 48.4% of questions correctly (Table p < 0.05) and steroids  at home. Irrespective of prior exacerbation, most patients were confident/very confident in using both antibiotics and steroids, and reported knowing what to do  if their breathing deteriorated.Table Four-hundred (40.4%) patients reported having an agreed self-management plan, including only 214 (44.9%) of those with exacerbations in the last 6 months Table .Table 5SThe majority of respondents  appeared satisfied with the information given to them by their healthcare professionals about their medications. Of the 258 respondents who were current smokers at baseline, 56.2% had been advised by a healthcare professional to give up smoking within the last 12 months, and 42.7% were offered practical help  to do so. Approximately half of respondents reported ever having been advised about diet or exercise, but only 15.0% had been advised to lose or gain weight.Reported attendance at training courses (7.7%) and support groups (3.1%) in the last 12 months was low. Of the 72 patients (6.7%) that had been offered pulmonary rehabilitation in the past 6 months, 45 (62.5%) had attended.Table After adjusting for age, sex, smoking status, educational level, MRC dyspnoea score and number of co-morbidities, those who had a self-management plan in place were more likely to have attended a training course (odds ratio (OR) 2.72; 95% confidence interval (CI) 1.81–4.12), support group , or to have received advice on physical activity . They were also more likely to have better COPD knowledge scores , and self-reported adherence to medication . These patients also tended to have better CAT scores and were more likely to have been offered NRT, although these effects were not statistically significant.Patients who experienced an exacerbation within the last 6 months were more likely to have ever attended a training course  or a support group , and have better COPD knowledge  compared to those not reporting an exacerbation  if necessary.In this study, we report self-management support and behaviour patterns among a large, broadly representative primary care cohort of COPD patients in England. Although the majority of participants reported taking their medications as instructed by their healthcare professional and receiving annual influenza injections, a striking finding is that less than half of respondents reported having an agreed self-management plan; including patients reporting a recent exacerbation. Similarly, despite 62.9% reporting severe dyspnoea and, therefore, having the potential to benefit from pulmonary rehabilitation,Our findings indicate clear potential for improvement in the promotion of healthy lifestyles, considering that only 56% of current smokers reported receiving smoking cessation advice in the last year. In addition, only 15% were advised about weight management despite nearly three quarters of the sample being either overweight or obese and 2% being underweight.It was interesting to note that participants’ general knowledge about COPD (BCKQ) was moderate, and improvement here has potential. Despite patients’ poor knowledge regarding the use and benefit of inhaled medications, the high proportion of patients reporting satisfaction with the level of information provided about their medication suggested a discrepancy between perceived and actual knowledge. Attempts to improve the content or mode of delivery of medication information may, therefore, be warranted to optimise patient knowledge of this important area.Our study indicates various patient benefits associated  with receiving a self-management plan, including increased medication adherence, greater disease knowledge, increased attendance of training courses and support groups, and improved quality of life. However, despite such benefits, presence of a self-management plan was not associated with practical support, such as NRT, being offered.17 There is little other evidence regarding the reality of patients’ self-management behaviour or the support offered by healthcare professionals in the UK.Self-management in COPD is a relatively under-researched topic in comparison with other chronic diseases.20 However, in contrast to our study, a cross-sectional study20 found that community-dwelling COPD patients in Canada reported better engagement with other self-management behaviours, where higher proportions of patients engaged in aerobic activity (74% vs. our 14%) and breathing exercises (70%). They also reported that 68% of patients made collaborative management decisions with their healthcare professional and 20% had attended pulmonary rehabilitation.Our findings that patients adhere well and report understanding their medication reflect those of previous Canadian studies.14 and Canada,19 our study supports and extends these observations in a larger generalisable primary care population. Furthermore our study adds to this by indicating that, in the UK, self-management plans are also associated with better reported adherence to medication, more support/self-management advice and better quality of life.Although the limited use of self-management plans has previously been reported in two small studies of patients with recent exacerbations in the UKWe have described major facets within self-management behaviours in a large COPD population, from general practices representative of primary care in the UK.21It is, however, possible that the relatively low recruitment rate into the cohort (24%) might affect generalisability to a certain extent as participants were more likely to be male and of white British ethnicity than all eligible COPD patients in our participating general practices.While we have demonstrated that presence of a self-management plan is associated with better support and behaviours, the analyses were conducted using cross-sectional data. Analyses would need to be repeated with longitudinal data to ascertain whether the association was causal, or simply indicated that patients received a better overall package of care from their practitioner.22 in relation to self-management behaviour. Mediating factors, such as willingness to quit in the case of smoking cessation, would need to be accounted for in analyses to assess the true impact of self-management plans. Inconsistencies in the definition and measurement of self-management7 further limit our ability to compare the findings with existing evidence. The date of COPD diagnosis was not available for this analysis; hence we were unable to explore if duration of disease impacted on self-management behaviour or support.Study questionnaires completed by patients in the current analysis did not explore patients’ self-efficacy and motivation23 However, it is unclear whether the relationship between having a self-management plan and adherence to medication would be affected. Additionally, the BCKQ COPD knowledge questionnaire is now dated, and question 13 regarding knowledge about inhaled steroids is no longer current. However, this only represents 5 out of a total of 65 points and the questions about inhaled bronchodilators also scored low marks. We also asked questions regarding the confidence of patients to act (such as to start taking their rescue medication) during their exacerbation. Confidence rates were high, but it is acknowledged that such positive self-efficacy does not always translate into timely action.24 We were not able to observe actual self-administration of medication during exacerbations.Data presented in this paper were collected via patient self-completed questionnaire as objective measures were not feasible, although validated instruments were used where possible. As a result, data should, therefore, be interpreted with appropriate caution, allowing for potential biases. Self-report of behaviours such as compliance with medication is likely to be prone to overestimation by respondents compared with objective measurement.6 implementation in practice appears clearly inadequate. Understanding this mismatch, particularly from the healthcare practitioner perspective, is an important area for future research in order to understand the potential barriers and enablers involved. Annual reviews of COPD patients in primary care seem the ideal opportunity to discuss self-management, as they are attended by over 90% of patients2 and already include some relevant aspects, e.g., desire to stop smoking, inhaler technique and referral to further services such as pulmonary rehabilitation. Wider health promotion behaviours such as weight management and physical activity were apparently not discussed by healthcare professionals, and had low uptake among patients. Improving the general health of patients could benefit management of their COPD symptoms, such as breathlessness, and improve outcomes.25Despite NICE recommendations that all COPD patients should receive an individualised self-management plan,25 with an alternative being referrals to allied services. However, the majority of patients  had never attended a training course, a support group or pulmonary rehabilitation, indicating a lack of self-management support outside primary care-based patient and healthcare professional interactions. Further research is needed to explore the adequacy of referral pathways in primary care, whether resources are available to support training courses and pulmonary rehabilitation, as well as patients’ reasons for poor participation in existing services.26The time constraint within primary care consultations is a potential barrier to the inclusion of thorough self-management support,27 is needed to explore how to expand current self-management recommendations to all COPD patients, within the confines of current financial constraints.Future implementation research29 with those who successfully self-manage their condition being younger and not living alone. Recent evidence suggests that motivation of non-compliant patients may be enhanced through multimodal approaches , reporting reductions in readmissions and improved quality of life.30Finally, engaging the patient in their condition is a major challenge for health professionals managing COPD and other long-term health conditions, which if achieved could improve patients’ self-management behaviour. Studies report compliance rates of approximately 40% with self-management advice among patients with COPD,This study increases understanding about the real life practice of self-management behaviours in COPD patients. Patients are indeed partially using a self-management approach in their condition as recommended by bodies such as NICE. Adults with COPD are using inhaled medications, having annual influenza vaccinations, and some are engaging in partnerships with the healthcare service. However, healthcare professionals need to make explicit self-management plans with all of their patients, provide consistent advice and offer practical support regarding smoking cessation, diet, exercise and attendance at support groups, and actively ensure that their patients understand their condition and its management. This may require a new approach in primary care to achieve satisfactory implementation.Cross-sectional analysis of data collected as part of the Birmingham COPD Cohort Study between 2011 and 2015, to establish self-management behaviours and support; and outcomes associated with having a self-management plan among primary care patients with COPD.21 The cohort comprises patients with existing diagnosed COPD, newly case-found COPD and those with chronic respiratory symptoms without airflow obstruction. This analysis focuses on those with existing diagnosed COPD. Briefly, 6383 patients aged 40 years or over with a GP-recorded COPD diagnosis from 71 general practices across the West Midlands, UK, were invited to take part, of whom 1558 (24.4%) were eventually consented into the study. At the time of this analysis, 1547 had consented. The current analysis was based on prevalent patients with 6-month questionnaire data (n = 1078), which specifically asked about self-management behaviours.Recruitment to the Birmingham COPD Cohort Study has been described elsewhere.Participants attended a baseline study assessment at their own GP practice, conducted by trained research assistants. Patients completed questionnaires at this assessment and then at 6-monthly intervals, with a further final face-to-face clinical assessment at approximately three years. The questionnaires were self-completed and included items on sociodemographic characteristics, health , lifestyle behaviours, medications, health service usage and disease knowledge. Validated tools were used where possible. Data for the current analyses came primarily from the 6-month questionnaire or baseline assessment as appropriate.1) and forced vital capacity (FVC) were deemed viable if they met American Thoracic Society acceptability criteria and were repeatable to within 200 ml. COPD was defined as airflow obstruction using a fixed ratio of FEV1/FVC < 0.70 and severity was graded according to the European Community of Coal and Steel (ECCS) equations.31At baseline assessment, trained research assistants performed spirometry using the nddEasy One spirometer , pre and post administration of 400 µg salbutamol. A minimum of three and a maximum of six blows post-bronchodilator were allowed, until repeatability within 100 mls was reached and the best reading was recorded. Specialised software (MMiller) and real-time show of volume-time and flow-volume graphs were used to ensure quality. All traces were over-read and data for forced expiratory volume in 1 s  having a self-management plan, (2) having an exacerbation within the previous 6 months, and reported self-management behaviours and support, adjusting for age, sex, smoking status, education, MRC dyspnoea score and co-morbidities.All analyses were undertaken in Stata13.The cohort received ethical approval from the National Research Ethics Service Committee West Midlands, Solihull (ref.: 11/WM/0304). Methods were performed in accordance with relevant regulations and guidelines. Written informed consent was obtained from each participant at the start of the baseline assessment.The data that support the findings of this study are held by the BLISS research team at the University of Birmingham. Copies of the questionnaires, measurement procedures and administrative processes are available on request, through our website [www.birmingham.ac.uk/bliss]. The data are not publicly available due to them containing information that could compromise research participant privacy/consent.Appendix 1


Stunting is the most prevalent manifestation of childhood malnutrition. To characterize factors that contribute to stunting in resource-poor settings, we studied a priori selected biological and social factors collected longitudinally in a cohort of newborns.Z-scores into 3 groups , and used multivariable ordinal logistic regression to model the cumulative odds of being in a lower length-for-age category (at risk or stunted). A total of 1,197 children with complete longitudinal data were available for analysis. The prevalence of having a length-for-age Z-score below −1 increased from 43% (range 37%–47% across sites) shortly after birth  to 74% (16%–96%) at 24 months. The prevalence of stunting increased 3-fold during this same time period. Factors that contributed to the odds of being in a lower length-for-age category at 24 months were lower enrollment weight-for-age , shorter maternal height , higher number of enteropathogens in non-diarrheal stools , lower socioeconomic status , and lower percent of energy from protein . Site-specific analyses suggest that reported associations were similar across settings. While loss to follow-up and missing data are inevitable, some study sites had greater loss to follow-up and more missing data than others, which may limit the generalizability of the findings.We enrolled 1,868 children across 7 resource-poor settings in Bangladesh, Brazil, India, Nepal, Peru, South Africa, and Tanzania shortly after birth and followed them for 24 months between 2 November 2009 and 28 February 2014. We collected longitudinal anthropometry, sociodemographic factors, maternal-reported illnesses, and antibiotic use; child feeding practices; dietary intake starting at 9 months; and longitudinal blood, urine, and stool samples to investigate non-diarrheal enteropathogens, micronutrients, gut inflammation and permeability, and systemic inflammation. We categorized length-for-age Neonatal and maternal factors were early determinants of lower length-for-age, and their contribution remained important throughout the first 24 months of life, whereas the average number of enteropathogens in non-diarrheal stools, socioeconomic status, and dietary intake became increasingly important contributors by 24 months relative to neonatal and maternal factors. Using data from the MAL-ED longitudinal birth cohort study, William Checkley and colleagues examine factors associated with childhood stunting during first two years of life in Bangladesh, Brazil, India, Nepal, Peru, South Africa and Tanzania. MAL-ED  is a multidisciplinary, prospective, longitudinal cohort study of the growth and development of children living at sites in southern Asia , Latin America , and sub-Saharan Africa .The study goal was to better understand the complicated interrelationships among enteric infections, nutrition, and other environmental exposures and child growth. The overarching hypothesis of the MAL-ED study was that repeated enteropathogen infections in infants and young children affect physical growth.In our analysis of the MAL-ED study, we found that factors leading to childhood stunting were established early in life.Neonatal and maternal factors were found to play a more influential role than postnatal factors during early childhood, and their contributions remained significant throughout the first 24 months.Postnatal exposures, including a higher burden of non-diarrheal enteropathogens, lower socioeconomic status, and lower protein content of the diet became increasingly important contributors with age relative to neonatal and maternal factors.Maternal interventions, especially during pregnancy, are likely to have intergenerational effects and a lasting impact on birthweight and child growth outcomes.Initiatives to address childhood stunting should also consider improvements to the composition of complementary foods  and strategies to reduce gut pathogen exposure. Stunting is the most prevalent condition of child malnutrition worldwide , and it Ethics approval was obtained from the institutional review boards at participating institutions . WrittenThe MAL-ED study is a longitudinal study of the role of enteric infections in health outcomes in children followed from birth to age 24 months living in resource-poor settings across diverse geographical areas. The study design has been described in detail elsewhere  9]. Thi. Thi9]. Z-score < −2 or height-for-age Z-score < −2) at the end of 2 years and if an enteropathogen infection affected 50% of the children over 2 years, we would have 60% power for a single site and 100% power for all sites combined to detect a 50% higher risk of being malnourished with 95% confidence. The power of the study to detect a 70% increase in malnutrition risk associated with an infection  was 82% for a single site and 100% for all sites combined. Additional details are provided elsewhere  standardized into a standard  as a surstandard .Mothers or caregivers were questioned every 6 months about their sources of water and sanitation facilities, assets, income, and food security. Level of maternal education was collected in the baseline survey. We combined water and sanitation, assets, maternal education, and income into a composite score (WAMI index) , and calAt twice weekly home visits, daily information on child illnesses and antibiotic use was collected from the mother. We evaluated 3 common illnesses—diarrhea, acute lower respiratory infection (ALRI), and fever—and, as detailed elsewhere, used standard definitions of illness onset and episodes . We calcField workers collected monthly (during the first year of life) and quarterly (during the second year of life) non-diarrheal stool samples. A non-diarrheal stool sample was considered as any specimen collected 2 or more days apart from an episode of diarrhea. As previously described, these specimens were tested for ≥40 enteropathogens . We calcInitiation of breastfeeding was recorded and surveillance of infant and young child feeding practices was undertaken by teams of field workers who visited the homes of participating children twice weekly. Days between twice weekly visits were assumed to have the same status as the preceding visit for the calculation of duration of each breastfeeding practice in days, as previously described . We defiAdditionally, starting at 9 months, field workers conducted 24-hour complementary food intake recall interviews once monthly; this information was linked to country-specific nutritional databases to quantify energy, macronutrient, and micronutrient intakes from non-breast-milk foods. Dietary intake over time was characterized by integrating these multiple types of data .Longitudinal visits were conducted to collect blood , urine , and monthly or quarterly non-diarrheal stool samples (as specified above) for the assessment of micronutrient status, systemic inflammation, and gut inflammation and permeability markers. From blood, we evaluated concentrations of altitude-adjusted hemoglobin, inflammation-adjusted retinol, alpha-1-acid glycoprotein (AGP), and inflammation-adjusted plasma ferritin by averaging the values of the 3 measurements obtained during the study period. If a child had only 2 measurements, we averaged the 2 values; if only 1 measurement, we used that value alone. From non-diarrheal stools, we measured myeloperoxidase (MPO), neopterin (NEO), and alpha-1 antitrypsin (AAT) concentrations as previously described . These gChildren were visited monthly to measure length and weight. We measured length with 3 different types of commercially made measuring boards to the nearest 0.1 cm and weight with 2 different types of scales to the nearest 10 g. We used 2 staff members at all times to conduct these assessments. A total of 152 field workers (range 7 to 36 per site) were standardized in the measurement of anthropometry by local investigators using a common protocol. To ensure quality control, extreme measurements were investigated, and secondary measurements were collected within 24 h for approximately 5% of all metrics. Reliability estimates for both weights and lengths were >0.9. Details of equipment, anthropometric assessments, and quality control procedures are found in Z-score categorized into 3 groups: −1 SD or greater (not stunted), less than −1 SD to −2 SD (at risk), and less than −2 SD (stunted). We chose to stratify length-for-age into 3 categories because children who have a length-for-age Z-score from less than −1 SD to −2 SD, while technically not considered stunted, have an increased risk of death, especially from diarrhea and pneumonia, compared to those with Z-score ≥ −1 SD [Z-scores by site.The main outcome variable was monthly length-for-age  ≥ −1 SD . We alsoWe used a longitudinal multivariable ordinal logistic regression  to modelResults of the regression model are presented as the adjusted cumulative odds ratios (ORs) of being in a lower length-for-age category for the risk factor of interest. In this analysis, adjusted cumulative ORs for the population represent age-specific associations between each risk factor and being in a lower length-for-age category. We estimated interquartile cumulative ORs for continuous variables, i.e., the ratio of odds between the 25th and 75th percentiles or between the 75th and 25th percentiles of the risk factor, depending on the direction that indicated worse exposure. In subset analyses, we ran site-specific regressions to describe heterogeneity in ORs across sites.https://www.r-project.org, Foundation for Statistical Computing, Vienna, Austria).An assumption of ordinal logistic regression is that the cumulative log odds are proportional among the different length-for-age thresholds. To graphically assess proportionality of odds, we compared the ORs and corresponding 95% confidence intervals for each factor obtained from a logistic regression model evaluated at each of the threshold points in length-for-age (−1 SD and −2 SD). There was substantial overlap in the 95% confidence intervals for each factor between threshold points, and departures from proportionality did not substantively impact the relative importance or factor-specific effects ; S4 Fig.Our analysis followed our proposed analytical plan but for some minor changes . We origA total of 1,868 children were enrolled across the 7 sites, of whom 11 died, 269 moved away, 87 were lost to follow-up, and 210 did not meet minimal criteria for longitudinal follow-up, leaving 1,291 (69%) children for our analysis. Of these, 1,197 children had complete data for all risk factors analyzed here, contributing 23,629 monthly observations. Factors under study exhibited considerable heterogeneity across sites .First, we compared trajectories in length-for-age across 7 sites and saw an almost uniform decrease in length-for-age with age except in BRF . The aveZ-score of <−1 to −2 was 30% at enrollment (range of 27% in BRF and NEB to 33% in PEL) and 37% at age 24 months (range of 13% in BRF to 46% in PEL). With the exception of BRF, which had minimal stunting, age patterns were the same; however, the magnitude was different among sites.The prevalence of stunting at enrollment was 13% (range of 10% in BRF and SAV to 16% in BGD and TZH), and it tripled to 41% by 24 months (range of 4% in BRF to 72% in TZH), with the greatest increases occurring after 6 months of age. The prevalence of having a length-for-age We present single variable analyses of risk factors in n = 81) contributed by this site to the analysis.Adjusted interquartile cumulative ORs by site were mostly in the same direction for the majority of risk factors, especially for low enrollment weight-for-age and maternal height, with some exceptions. To assess heterogeneity, we estimated site-specific interquartile cumulative ORs and contrasted these results against those obtained in the overall population . While wp = 0.54), ALRI (p = 0.87), and fever (p = 0.28). Nor were 2 of the gut inflammation biomarkers, namely stool MPO (p = 0.77) and NEO concentrations (p = 0.07), associated with lower length-for-age. Higher AAT and AGP concentrations were associated with being in a lower length-for-age category at younger ages, but the direction of this association changed at older ages  had linear growth faltering during childhood, with the prevalence of stunting reaching a plateau by 2 years, as per a previously reported observation . SpecifiLower enrollment weight, a surrogate for lower birthweight, was associated with having a lower length-for-age during the first 24 months of life. While its relative contribution diminished with age, enrollment weight remained significantly associated with lower length-for-age at 24 months, i.e., these children never caught up. This finding is consistent with a meta-analysis conducted among 19 studies and 44,374 children less than 5 years of age that showed that low birthweight was associated with 3-fold higher odds of stunting . OverallShort maternal height is a key indicator for identifying populations at high risk for low birthweight . As evidOf the accumulated postnatal insults that we measured, the presence of enteropathogens in the absence of diarrhea, a lower SES, and a lower percent of energy from protein were all strongly associated with lower length-for-age, and the magnitude of their effects became stronger with age. The importance of protein in the diet for growth of children has recently been reported in an analysis of 2 other large cohort studies . In thisIn our analysis, we also focused on the accumulation of multiple enteropathogens—rather than on specific enteropathogens in non-diarrheal or diarrheal stools—and its association with lower length-for-age, because of its value as a surrogate measure of fecal contamination in the environment. Frequent enteropathogenic infections have a high metabolic cost. It has been estimated that infants and young children need to produce and secrete 3 to 5 g of secretory IgA into the gut per day to control enteropathogenic infections . Prior sIllnesses reported by mothers were also not associated with being in a lower length-for-age category. The lack of association with diarrheal illness, when analyzed individually or alongside other risk factors, is surprising as diarrhea has historically been reported to be associated with adverse growth outcomes ,35–38. HOur finding that lower SES was also associated with length-for-age shortfalls, a trend that was consistent across the majority of sites, suggests that targeted reductions in disparities of modifiable SES factors may be an effective intervention strategy to reduce stunting in resource-poor communities. While SES is a likely surrogate for more immediate causes, including poor nutrition and higher prevalence of infections, the association with stunting may also be mediated in part by social and psychological stress. Recent studies have shown that SES stressors may result in epigenetic changes and activation of inflammatory pathways . A low pOur study has some potential shortcomings. First, complicated feedback loops between layers of risk factors render analysis difficult. For example, gut inflammation and permeability and systemic inflammation may co-vary with the prevalence of enteropathogenic infections or poor sanitary conditions. Second, although the study was conducted in 8 settings, bias in length-for-age measurements at the Pakistan site meant excluding data from this site from our analysis. Third, missing data were another drawback; with the breadth of data collected and range of settings, loss to follow-up and missing data were inevitable. Specifically, our analysis obtained longitudinal data for only 69% of the cohort. Fourth, some of the factors were averaged across age given the limited number of measurements available, which may not reflect true temporal associations. Some individuals had only 1 or 2 measurements of these factors. Therefore, to include these data without losing information, we thought it would be best to average the information across the follow-up period. This is a limitation and comes at the cost of being able to more carefully analyze the temporal contributions of these factors, but we thought it was better to include them crudely with an average than to not include them at all. However, the use of age by factor interaction terms allowed us to evaluate how these indices had a temporal effect on being in a lower length-for-age category with respect to age. Fifth, participating families in Fortaleza, Brazil, had a high dropout rate either because they left the study area due to problems with urban violence or because it was too dangerous for study staff to visit them routinely. Sixth, we recognize that some of our resource-poor populations may have been better off than others, as noted by differences in caloric and protein intake, WAMI index, and linear growth outcomes. The study populations in Brazil, Nepal, and South Africa, while poor, were indeed better off populations than many other resource-poor settings in these countries, thus limiting our capacity make generalizations from site-specific findings. Finally, gestational age at delivery was not assessed in our study, and this may have affected our assessment of length-for-age. It is important to note that our eligibility criteria excluded children weighing < 1.5 kg at birth (a proxy for preterm birth). However, our study also has several strengths. First, the MAL-ED study collected a comprehensive array of postnatal exposures across a diversity of settings worldwide. Second, all sites used a standardized protocol and data collection tools. Regular training, quality assurance, and quality control procedures enabled the study to maintain comparability across sites. Third, prospective follow-up with regular home visits allowed us to capture longitudinal morbidity and dietary information.In summary, the results presented here from one of the most comprehensive, multi-center longitudinal studies to date suggest that factors leading to stunting are established early in childhood. Neonatal and maternal factors were found to play a more influential role than postnatal factors in defining length-for-age category during early childhood, and their contributions persisted throughout the first 24 months of life. Postnatal exposures, specifically a higher average number of non-diarrheal enteropathogens, lower SES, and lower protein content of the diet, became increasingly important contributors with age. Our results suggest that maternal interventions, especially during pregnancy, are likely to have intergenerational effects and a lasting impact on birthweight and child growth outcomes. Initiatives to address childhood stunting can also consider improvements to the composition of non-breast-milk foods  and strategies to reduce gut pathogen exposure.S1 STROBE Checklist(DOCX)Click here for additional data file.S1 Fig(TIFF)Click here for additional data file.S2 FigThe top panels show the time-varying values (wami), and the bottom panels show the averaged values (mean_wami).(TIFF)Click here for additional data file.S3 FigThe top panels show the time-varying values (fsqscore), and the bottom panels show the averaged values (mean_fsq).(TIFF)Click here for additional data file.S4 Fig(TIFF)Click here for additional data file.S5 FigWe calculated 2 standard error bands for the observed probabilities using standard methods, and a 95% confidence interval using 2,000 bootstrap replications in which children were chosen with replacement.(TIFF)Click here for additional data file.S6 FigWe conducted a sensitivity analysis using all data available (full data), instead of limiting our analysis to the data of children who met minimal criteria for longitudinal follow-up. The adjusted cumulative ORs and 95% CIs were similar when either the full data or analytical sample were used for analysis, suggesting that our results are robust to the dataset used.(TIFF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 TableThe MAL-ED study accumulated a wide array of data collected over many assessments given at separate intervals in accordance with a priori considerations such as cost, relevance, and biological significance. For example, a socioeconomic questionnaire was administered every 6 months to capture changes in household socioeconomics, whereas the main anthropometric outcomes, length and weight, were obtained at regularly planned intervals in the first 2 years of life. In this table, we show the data that were used and when those data were targeted for collection.(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.S2 Text(DOCX)Click here for additional data file.S3 Text(DOCX)Click here for additional data file.S4 Text(DOCX)Click here for additional data file.S5 Text(DOCX)Click here for additional data file.S6 Text(DOCX)Click here for additional data file.


The media has devoted significant attention to anecdotes of individuals who post messages on Facebook prior to suicide. However, it is unclear to what extent social media is perceived as a source of help or how it compares to other sources of potential support for mental health problems.This study aimed to evaluate the degree to which military veterans with depression use social media for help-seeking in comparison to other more traditional sources of help.t tests, Chi-square, and mixed effects regression models. Associations between types of help-seeking were examined using mixed effects models.Cross-sectional self-report survey of 270 adult military veterans with probable major depression. Help-seeking intentions were measured with a modified General Help-Seeking Questionnaire. Facebook users and nonusers were compared via The majority of participants were users of social media, primarily Facebook (n=162). Mean overall help-seeking intentions were similar between Facebook users and nonusers, even after adjustment for potential confounders. Facebook users were very unlikely to turn to Facebook as a venue for support when experiencing either emotional problems or suicidal thoughts. Compared to help-seeking intentions for Facebook, help-seeking intentions for formal , informal , or phone helpline sources of support were significantly higher. Results did not substantially change when examining users of other social media, women, or younger adults.In its current form, the social media platform Facebook is not seen as a venue to seek help for emotional problems or suicidality among veterans with major depression in the United States. Social media has become an integral part of people’s daily lives, including military veterans. As of 2016, there were 1.89 billion active users on Facebook . All tolFacebook is most commonly used for purposes such as entertainment, communicating with friends and family, and keeping up with news and current events, with 31% to 47% of users citing such reasons .Social media may be a valuable venue for help-seeking for several reasons. It is a highly accessible resource, and use of internet-based sources of help for health issues is common . ResearcThe importance of novel approaches to enhance help-seeking is accentuated by the fact that rates of help-seeking are generally low in proportion to the number of people suffering from psychiatric problems such as depression  and evenThus, the aim of this study was to evaluate the degree to which veterans with depression use social media for help-seeking in comparison to other more traditional sources of help.We drew participants from a larger study of 301 primary care patients at a VA hospital and its satellite clinics who had symptoms of major depression and reported having at least one close relationship. Patients were excluded if they had severe hearing impairment or recently active major psychiatric comorbidities . Due to the low percentage of women veterans, we oversampled women to increase diversity of our sample. Potentially eligible veterans were first screened for depression via a phone-administered 8-item Patient Health Questionnaire (PHQ-8) followed by an in-person visit if eligible and interested. Those eligible for inclusion in this study were the 270 individuals who had a PHQ-8 score ≥9, who were then administered a set of survey items about social media use. Meta-analyses have found that a cutoff score of 9 on the PHQ-9 is one of the optimal choices for diagnosing major depression in primary care settings ; the ideWe administered the General Help-Seeking Questionnaire (GHSQ), an adaptable self-report measure that assesses intention to seek help if experiencing an emotional problem or suicidal thoughts. Multiple possible sources of help are presented, and response options for each range from 1=extremely unlikely to 7=extremely likely. Because original items were developed in Australia, we slightly modified them for an American context and added Facebook as another potential source of help. Participants were asked about help-seeking on Facebook generally, without specifying particular areas or functions within Facebook . We sorted sources into 4 categories: (1) Facebook help-seeking; (2) informal help-seeking, which is drawn from members of one’s social network such as friends and family; (3) phone helpline help-seeking, which cited the Veteran’s Crisis Line as an example; and (4) formal help-seeking, which included a mental health professional or primary care provider. For categories with multiple items, we averaged participant responses to each source. The GHSQ has strong reliability and validity , particuWe used a series of survey items adapted from questions used by the Pew Research Center ,36 to asWe assessed additional sociodemographic and clinical characteristics including age, gender, minority status, education level, rurality of residence, stability of housing, financial hardship, history of suicide attempt, alcohol misuse, posttraumatic stress disorder symptoms, depression symptoms, and offline social contact. See t tests and Pearson Chi-square tests. To compare help-seeking intentions from different GHSQ source categories, we used multilevel mixed-effects linear regressions. We performed subgroup analyses to determine whether the pattern of help-seeking intentions differed when the sample was restricted to various groups of participants, including frequent Facebook users (defined as visiting at least daily), active Facebook users , and users of social media platforms other than Facebook. Analyses were performed using Stata versions 14.2 and 15.0 (StataCorp LLC), and 2-sided statistical significance was defined as P<.05.We first examined missingness of data; all survey items had less than 2% missing data. We used mean imputation for missing responses to GHSQ items that were part of informal or formal help-seeking. We summarized key variables using descriptive statistics. We analyzed sociodemographic and clinical characteristics of participants who were Facebook users and nonusers using 2-sample In terms of help-seeking intentions, 58.1% (157/270) endorsed having at least 1 source they intended to use (GHSQ score of 5 or more) if experiencing an emotional problem. If having suicidal thoughts, 55.6% (150/270) endorsed having at least 1 help-seeking source.Of our 270 participants, 162 (60.0%) were Facebook users, 106 (39.3%) used Facebook at least daily, and 65 (24.1%) used Facebook actively (as opposed to passively) at least daily. Use of any social media platform other than Facebook was uncommon , with use of individual platforms  even more rare. Compared to nonusers, Facebook users were younger and used other social media and more likely to be women, live in urban areas, and be at risk for misusing alcohol; they were less likely to have a history of a suicide attempt . HoweverA total of 58.6% 95/162) of Facebook users endorsed having at least 1 help-seeking source for emotional problems; for suicidal thoughts, 50.6% (82/162) intended to use at least 1 source of help. The mean help-seeking intention for emotional problems via Facebook was 1.67 (95% CI 1.46 to 1.87) on a scale ranging from 1=extremely unlikely to 7=extremely likely. Help-seeking intention for suicidal thoughts via Facebook was similarly low .  of FacebP<.001) and suicidal thoughts  compared to Facebook. In addition, the mean level of help-seeking intentions was highest for formal sources for both emotional problems  and suicidal thoughts . Detailed data on comparisons of different help-seeking sources is contained in As shown in P=.01) in intention to seek help from Facebook for emotional problems and a 0.33-point increase  in intention to seek help from Facebook for suicidal thoughts, compared to nonactive Facebook users. Among Facebook users who also used other forms of social media (42/162), help-seeking intentions via Facebook were not significantly different from those who exclusively used Facebook, either for emotional problems  or suicidal thoughts .Results were mostly similar when we restricted analyses to participants who were frequent Facebook users (106/162) and active Facebook users (65/162) , help-seeking intentions via Facebook were not significantly different from men for emotional problems. Finally, among participants younger than age 40 years (37/162), help-seeking intentions via Facebook were not significantly different from participants age 40 years and over, either for emotional problems or suicidal thoughts.P=.003) higher than other Facebook users.We identified a small subgroup (9/162) of participants who indicated intention to seek help for emotional problems or suicidal thoughts from Facebook (GHSQ score of 5 or more). These individuals had somewhat higher levels of help-seeking intentions more generally. Their mean help-seeking intentions using formal, informal, and phone sources for either emotional problems or suicidal thoughts was 4.83, which was 1.29 points  . FindingThe lack of interest in Facebook for help-seeking is all the more striking when compared to higher levels of interest in offline sources of help. The majority of our military veterans endorsed at least one venue they were likely to use for help-seeking. Mean help-seeking intentions for formal help and phone helplines in our sample were higher than in a prior study of Iraq/Afghanistan-era military veterans  and simiThis study does not reveal why individuals do not intend to seek help from Facebook. However, we suspect several possible reasons for the large discrepancy in the likelihood of informal help-seeking via Facebook versus offline sources. First, many “Facebook friends” are not “real friends,” or at least not close ones. Prior empirical work has shown that only a small segment of Facebook friends are actually close, personal social connections . It is tIn addition, help-seeking intentions via Facebook may be more favorable in individuals younger than our sample population, such as millennials who have grown up with Web 2.0 and social media . Prior rThe primary limitation of this study is the lack of measurement of actual help-seeking or treatment utilization, given that research has found stated intentions of help-seeking may not translate into actual help-seeking behaviors . LikewisOur results should not be interpreted as negating the relevance of tools, such as one recently rolled out by Facebook , to assi


Autism spectrum disorder (ASD) is a heterogeneous disorder characterized not only by deficits in communication and social interactions but also a high rate of co-occurring disorders, including metabolic abnormalities, gastrointestinal and sleep disorders, and seizures. Seizures, when present, interfere with cognitive development and are associated with a higher mortality rate in the ASD population.To determine the relative prevalence of non-febrile seizures in children with idiopathic ASD from multiplex and simplex families compared with the unaffected siblings in a cohort of 610 children with idiopathic ASD and their 160 unaffected siblings, participating in the Autism Genetic Resource Exchange project, the secondary analysis was performed comparing the life-time prevalence of non-febrile seizures. Statistical models to account for non-independence of observations, inherent with the data from multiplex families, were used in assessing potential confounding effects of age, gender, and history of febrile seizures on odds of having non-febrile seizures.The life-time prevalence of non-febrile seizures was 8.2% among children with ASD and 2.5% among their unaffected siblings. In a logistic regression analysis that adjusted for familial clustering, children with ASD had 5.27 (95%CI: 1.51–18.35) times higher odds of having non-febrile seizures compared to their unaffected siblings. In this comparison, age, presence of gastrointestinal dysfunction, and history of febrile seizures were significantly associated with the prevalence of non-febrile seizures.Children with idiopathic ASD are significantly more likely to have non-febrile seizures than their unaffected siblings, suggesting that non-febrile seizures may be ASD-specific. Further studies are needed to determine modifiable risk factors for non-febrile seizures in ASD. Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized not only by the deficits in communication and social interaction but also by the high prevalence of co-occurring medical conditions such as seizures and epilepsy, metabolic abnormalities, gastrointestinal dysfunctions, and sleep disorders –6. EpileThe estimates of seizures and epilepsy rates in children with ASD range from 7% (Interactive Autism Network registry) to 15%  , 13. RatTo bridge the gap in current knowledge, this study assesses the relative prevalence of non-febrile seizures in a large cohort of children age 2 to 18 years with well-documented idiopathic ASD compared with their unaffected siblings from the Autism Genetic Resource Exchange (AGRE). We hypothesize that children with idiopathic ASD will be more likely to have reported at least one non-febrile seizure episode compared to their unaffected siblings.Despite the growing body of scientific literature on prevalence of non-febrile seizures in children with ASD, to date few studies assessed febrile and non-febrile seizures separately. Yet such distinction is critical since the pathophysiology and risk factors associated with febrile seizures differ from other types of seizures, and febrile seizures are known to increase the risk of developing non-febrile seizures later in life –20. AlsoWe conducted a secondary analysis of data from a registry-based retrospective cohort study of 731 children with ASD and their 192 children unaffected siblings from the AGRE project for whom phenotypic data were collected . PermissThe study sample was drawn from the subset of AGRE participants registered with AGRE from 1999 to 2009 (year AGRE suspended further recruitment), and for whom phenotypic data were collected. This population includes children diagnosed with an ASD from families with one or more affected children and their linked unaffected siblings, for whom medical histories, environmental exposure histories, and physical/neurological exam data were available. Data that flagged possible non-idiopathic autism were also collected by AGRE using the following indicators: known neurogenic disorders, abnormal neurological exams, abnormal molecular or medical tests, focal abnormality on structural imaging, significant dysmorphology, known chromosomal abnormality, fragile X (full mutation), pre- or peri-natal injuries, prematurity less than 35 weeks, or small nuclear ribonucleoprotein polypeptide N (SNRPN) duplications.Children were included in the study sample if they were age 2 to 18 years and had a confirmed ASD diagnosis. A minimum age of 2 was chosen to ensure that diagnostic criteria involving language function could be evaluated accurately. Also included were their unaffected siblings, age 2 to 18 years, registered within the same period. Not every child with ASD had an unaffected sibling.Children with diagnoses of tuberous sclerosis, Landau-Kleffner Syndrome, Rett syndrome, cerebral palsy, Lennox-Gastaut syndrome, West syndrome, and continuous spike-and-wave syndrome (CSWS) were excluded as having conditions indicative of secondary ASD, as well as independent risk factors for epilepsy. Individuals with history of status epilepticus , neonataThe ASD diagnosis received by participants from a physician was verified by AGRE using the Autism Diagnostic Observation Schedule (ADOS) and the Autism Diagnostic Interview-revised (ADI-R), both based on DSM-IV diagnostic criteria –26. AGREThe ADOS is a semi-structured assessment of communication, social interaction, repetitive behavior, and play characteristics for individuals suspected of having autism or other pervasive developmental disorders. The ADOS is based on the examiner’s observation of the individual, and consists of four modules, each of which is appropriate for children and adults of differing developmental and language levels, ranging from nonverbal to verbally-fluent .The ADI-R is a clinical diagnostic instrument for assessing autism in children and adults. The ADI-R is based on historical data from parent interviews, and provides a diagnostic algorithm for autism as described in both the ICD-10 and DSM-IV. The instrument focuses on behavior in three main areas: qualities of reciprocal social interaction; communication and language; and restricted and repetitive, stereotyped interests and behaviors. The ADI-R is appropriate for children and adults with mental ages from about 18 months and above . Both, ALastly, AGRE pediatric neurologists conducted an in-home structured medical history interview to collect retrospective health information on each study participant. More detailed medical information was collected for the affected children than unaffected. The interview questions relevant to this study are included in Table In our study, the outcome variable was coded as “yes” if the AGRE records indicated presence of at least one non-febrile seizure that was not classified as infantile spasms. That is, children were not excluded from the study sample if they had a history of febrile seizures, but to be included in the seizure positive group for testing the study hypothesis, they had to have had at least one seizure episode not due to fever. To produce a conservative estimate of prevalence, those who did not report having seizures or who provided no response on the seizure type variable were coded as negative on our outcome variable. This rationale was based on two assumptions: (a) those who had seizures would have reported them; and (b) those who had no seizures would not have necessarily responded to the question. Presence of febrile seizures was defined as at least one seizure episode provoked by fever reported in AGRE records. Gastrointestinal (GI) dysfunctions were defined as presence of at least one GI disorder symptom in AGRE records.All analyses were performed using SAS version 9.4. Frequency distributions and prevalence rates were calculated for each of the characteristics of interest. The AGRE data includes families with more than one child with ASD so not all observations were independent. The non-independence of observations was accounted for in all analyses by adjusting variance estimations using SAS PROC SURVEY procedures (PROC SURVEYFREQ and PROC SURVEYLOGISTIC). The SAS PROC SURVEY methods were developed for complex survey data in which the assumptions of random population sampling and independence of observations are not met. To measure the association between non-febrile seizures and ASD affected status logistic regression analysis was used, treating each family as a cluster. This approach accounted for random effects of the within-family covariates and, subsequently, adjusted the variance, significance levels, and confidence intervals for family clusters. It also allowed full statistical control for the main effects of measured and unmeasured familial confounders.2 test for association. Group means were assessed using cluster-adjusted Wald F tests for linear regression models. All statistical tests were 2-tailed with statistical significance attained when the 2-tailed p-value was less than .05, unless otherwise stated.Confounding effects of febrile seizures and GI dysfunctions were statistically controlled for in our analyses. Bivariate analyses were performed to measure the association of non-febrile seizures with affected or unaffected ASD status. A prevalence odds ratio was calculated to test for a significant difference. Categorical variables were assessed using Rao-Scott adjusted χAfter selection criteria were applied, the total sample comprised 770 children age 2 to 18 years with a mean age of 8.48 years (SE = 0.16) . This ratio is consistent with the known 3:1 to 4:1 male-female ratio for the full spectrum of ASD . Of the The total prevalence of seizures, including febrile, was 9.4% (72/770). The overall prevalence of non-febrile seizures was 7.0% (54/770). The prevalence of non-febrile seizures in the ASD group was 8.2% (50/610) and 2.5% in the unaffected siblings (4/160). The overall prevalence of febrile seizures was 3.1% (24/770). The prevalence of febrile seizures in the ASD group was 3.1% (19/610) and 3.1% among the unaffected siblings (5/160). Among the ASD group, 1% (6/610) reported having both febrile seizures and non-febrile seizures. The mean age-at-onset for febrile seizures in the ASD group was 1.99 (SE = 0.35) years. The mean age-at-onset for non-febrile seizures in the ASD group was 4.24 (SE = 0.55). Age-at-onset was unavailable for the unaffected siblings. Among 50 children with ASD and non-febrile seizures, 48% (24/50) reported having seizures requiring pharmacological treatment, and, among these, 16.7% (4/24) reported having seizures that were refractory to treatment.n = 9; 1.5% of all ASD children), generalized / grand mal , absence / petit mal , other , unknown type , and multiple types . Among children with ASD, 1.5% (9/610) reported having only one seizure episode, 4.6% (28/610) reported having two or more seizure episodes, and for 2.1% (13/610) episode information was unavailable. The types of non-febrile seizures among the unaffected siblings were complex partial , absence / petit mal , and other    than for their unaffected siblings 2.5%; 4/160)  (Table /160 (adj(age): 1.13; 95% CI: 1.04 – 1.23), presence of GI dysfunction (OR(GI): 1.91; 95% CI: 1.05–3.48), and those with a history of febrile seizures had five times the odds of reporting non-febrile seizures OR(febrile): 5.46; 95% CI: 1.96 – 15.23) (Table (gender): 1.58; 95% CI: 0.84 – 2.98). The inclusion of history of febrile seizures, age, and gender each changed the adjusted odds ratio by more than 10% and, therefore, these variables were retained in the final model [p < 0.01). Accordingly, children affected with ASD had five-times the odds of having non-febrile seizures compared to their unaffected siblings  we conducted secondary analyses excluding children from simplex families in order to test whether results for multiplex families differ from the combined results. These results were consistent with those in primary analyses.Our study is one of the largest studies to date estimating the prevalence of non-febrile seizures in a well-defined population of children with idiopathic ASD while controlling for familial aggregation, age, history of febrile seizures and GI dysfunctions. Our study is also one of the largest studies comparing the lifetime prevalence of non-febrile seizures between ASD affected and unaffected siblings in simplex and multiplex families throughout the United States. In both the crude and adjusted statistical models where familial clustering was statistically controlled, odds of having non-febrile seizures were significantly higher among children with idiopathic ASD than their unaffected siblings . In our sample, having a history of febrile seizures increased the odds of reporting non-febrile seizures five-fold. Also, odds of non-febrile seizures increased with age, and presence of GI dysfunctions while gender was not significantly associated with the prevalence of non-febrile seizures.Multiple studies have reported high prevalence rates of seizures in children with ASD , 32–35. Though AGRE participants were recruited nationwide, the sample is not representative of the US population as most of the families were recruited in regions where Autism Speaks has significant activity. The data also came from largely multiplex families, limiting reported findings to families with more than one child affected with ASD. Our secondary analyses performed with data from multiplex families alone were consistent with our primary results and, though point estimates were slightly higher, the exclusion of simplex families did not change the results appreciably. In addition, some of the data collection was based on parental report rather than direct assessment and not all medical histories were verified. The use of secondary data poses certain limitations. Classification of seizure type was limited by the way the questions were asked which varied between the children with ASD and their unaffected siblings. In our case, some of the variables needed were unavailable or had high levels of missing data. For example, prior studies identified  moderate-to-severe intellectual disability, motor deficits, and severe receptive language disorder among the risk factors for seizures in the ASD population . High peOur study used a population whose ASD diagnoses were uniformly verified with gold-standard diagnostic instruments. All children were tested by AGRE physicians trained by a research-certified ADOS/ADI-R trainer to confirm the diagnosis they received from their physician prior to inclusion into the registry. The tests were electronically scored and rerated for validity and reliability. The AGRE reliability protocol requires re-rating ten percent of the ADI-R and ADOS assessments conducted by AGRE for each audit. The assessments were scored and validated through the Internet System for Assessing Autistic Children (ISAAC), thereby eliminating manual scoring errors. In addition, the use of AGRE, one of the largest data repositories containing genetic and phenotypic data on ASD, allowed a very large sample for our analyses.By using unaffected siblings as a reference group, we were able to produce more accurate and conservative estimates of prevalence odds ratios. This method allowed us to account for differences while controlling for shared environment and genes, since siblings share both. It also enabled us to separate phenotypical characteristics specific to ASD from the general phenotypes due to familial aggregation. Furthermore, since febrile seizures represent an independent risk factor for developing non-febrile seizures later in life , 19, we The SAS PROC SURVEY methods allow for variance estimation when working with complex survey sampling that does not meet the assumption of a simple random sample of an infinite population . The useOur study found a five-fold higher lifetime prevalence of non-febrile seizures in children with idiopathic ASD from largely multiplex families compared to their unaffected siblings. These findings suggest that the reported non-febrile seizures may be ASD-specific and cannot be explained by genetic predisposition alone. We also found a higher prevalence of non-febrile seizures among unaffected siblings than reported for the general population, which suggests some degree of familial aggregation of genetic and phenotypic characteristics. However, the ASD-specific effect on prevalence was much stronger than the effect of familial aggregation. This study provides clear evidence for health care professionals as well as parents of children with ASD that suggest higher vulnerability of children with idiopathic ASD to non-febrile seizures. Such evidence can inform further research aimed at elucidating risk factors for non-febrile seizures in children with idiopathic ASD and possible approaches for reducing these risk factors. Future research is needed to identify risk early in life, to possibly ameliorate risk, and to prevent the onset of seizures in the ASD population.