Insights into the characteristics of treatment seekers for lifestyle changes and treatment preferences are necessary for intervention planning.To compile a profile of treatment-seeking obese patients with non-communicable diseases (NCDs) or NCD risk factors and to compare patients who choose group-based (facility-based therapeutic group [FBTG]) versus usual care  treatment.A primary healthcare facility in Cape Town, South Africa.One hundred and ninety-three patients were recruited in this cross-sectional study. Ninety six chose FBTG while 97 chose usual care. A questionnaire, the hospital database and patients’ folders were used to collect data. Weight, height and waist circumference were measured. STATA 11.0 was used for descriptive statistics and to compare the two groups.2 and waist circumference 117 (12.6) cm). These figures were undesirable although pharmacological treatment for diabetes and hypertension was in place. Only 14% were physically active, while TV viewing was > 2h/day. Mean daily intake of fruit and vegetables (2.2 portions/day) was low while added sugar (5 teaspoons) and sugar-sweetened beverages (1.3 glasses) were high. Usual care patients had a higher smoking prevalence, HbA1c, number of NCD risk factors and refined carbohydrate intake, and a lower fruit and vegetable intake.The subjects’ mean age was 50.4 years, 78% were women and of low education levels and income, and 41.5% had type 2 diabetes, 83.4% hypertension and 69.5% high cholesterol. Mean (s.d.) HbA1c was 9.1 (2.0)%, systolic BP 145.6 (21.0) mmHg, diastolic BP 84.5 (12.0) mmHg, cholesterol 5.4 (1.2) mmol/L), body mass indicator (BMI) 39.3 (7.3) kg/mTreatment seekers were typically middle-aged, low income women with various modifiable and intermediate risk factors for NCDs. Patients choosing usual care could have more NCD risks. Research indicates that socio-economic, cultural, political and environmental determinants, including population aging, globalisation, urbanisation and the accompanied nutrition transition contribute to the increase in NCDs in developing countries.14 Levitt et al.4 suggested that the considerable attention and robust interventions implemented to manage the HIV and AIDS epidemic in South Africa should be applied similarly to NCDs. The restructuring of primary health care (PHC) and district health services in areas of the country such as Cape Town in Western Cape Province to improve standards of care, accommodate the growing population and manage escalating disease burdens15 is a step in the right direction. The substantial improvements in NCD surveillance,9 medication distribution16 and policy development17 in the country are also encouraging. However, according to Parker et al.,18 health promotion, behavioural counseling services and continuity of care in PHC facilities for patients with obesity and NCDs are probably insufficient to address the mentioned lifestyle risk factors. In an attempt to improve this situation, the Western Cape Provincial Department of Health (DoH) developed a NCD management policy that included a six-week, group-based intervention for roll-out at governmental PHC facilities to address modifiable risk factors through behaviour change and treatment adherence.19 At the point of roll-out, no research had been done on the socio-demographic, lifestyle and health profiles of patients seeking treatment at these facilities or the potential efficacy. Interestingly, there seems to be a paucity of research on the effectiveness/efficacy of group-based lifestyle interventions in the international literature.20 The same is true for research on the characteristics of those who would choose to enroll in such interventions.20 Work by Steinsbek et al.21 and Galagher et al.22 showed that there was little difference between baseline characteristics of participants in group versus standard treatment modalities. However, current literature suggests that patients’ preference for a treatment type for obesity or NCDs in general may be influenced by factors such as age, gender, cultural perceptions, health status, access to quality healthcare and practical difficulties.25 Insights into the characteristics of treatment seekers regarding lifestyle changes and treatment preference are necessary for intervention planning.Both international and national policymakers have called for urgent prioritisation of the prevention and management of NCDs.The aims of the present research were to compile a socio-demographic, health, lifestyle and stage of change profile of treatment-seeking obese patients with NCDs or risk factors for NCDs attending a district PHC hospital in Cape Town, and to compare these characteristics between patients who chose the group-based programme and patients who chose the usual care option.The present paper provides secondary analysis of cross-sectional baseline data of a 6-month lifestyle intervention study where patients could choose to participate in either a 6-week facility-based therapeutic group (FBTG) programme or the usual care option available at a government district PHC hospital in Cape Town, South Africa.The FBTG intervention comprised six weekly sessions (60 to 90 minutes per week) facilitated by a multi-disciplinary team consisting of a dietitian, medical doctor, pharmacist, physiotherapist and nurse. Education on goal setting, healthy eating, physical activity, behaviour change, adherence to medication and treatment recommendations as well as advice on weight and behaviour maintenance were provided during the six sessions. Six to twelve patients were recruited per FBTG. The usual care group received standard treatment provided to a patient with NCDs and/or risk factors for NCDs at the district PHC hospital. This involves initial one-on-one consultations with the medical doctor and dietitian. Patient-initiated follow-up appointments with the dietitian were possible, pending the availability of the dietitian.The study population were obese patients attending False Bay Hospital who required management of NCDs or risk factors for NCDs. False Bay Hospital provides medical care for patients without medical health insurance. However, a small minority of patients who have private medical aid are also treated at False Bay Hospital. Patients attending this hospital feed in from suburbs containing formal and informal housing.2, with one or more intermediate risk factor(s) such as raised blood pressure (BP) (> 130/80 mmHg), raised HbA1c (> 7%), raised total cholesterol (> 4.5 mmol/L), or one or more existing NCDs such as type 2 DM or CVD. The doctors made their decision to refer eligible patients to the hospital dietitian based on the most recent biochemical and clinical measures. A basic understanding of the English language was also necessary as both interventions were conducted in English. Patients were excluded if they were pregnant or lactating, or had any form of organ failure, severe psychiatric disorder or physical restrictions. A description of the FBTG intervention was provided during the recruitment consultation with the dietitian, after which eligible patients were given the option to choose the FBTG or the usual care intervention.Eligible patients were identified by the medical doctors employed by the hospital during routine appointments and were subsequently referred to the hospital dietitian for an individual consultation and possible recruitment. Eligible patients had to be older than 18 years and have a body mass index (BMI) ≥ 30 kg/m27 As attrition rates in weight loss interventions have been reported to be high (between 10 and 80%),28 we recruited a sample including 96 intervention patients and 97 usual care patients, resulting in a total sample of 193 for the development of a profile of patients seeking treatment at the hospital.The sample size for the cross-sectional arm of the study was based on the sample estimation for the intervention arm. These calculations indicated that 44 to 60 participants would be required in each treatment choice group to achieve 80% power at a 5% significance level. Relevant published results of group-based lifestyle (weight loss) interventions were used for the calculations.Relevant information was obtained using an interviewer-administered questionnaire developed for the purpose of the study, the CLINICOM hospital database and patient folders. During the initial recruitment consultation, the hospital dietitian interviewed the patient to complete the questionnaire and conducted the necessary anthropometric measurements. All biochemical and clinical measures were obtained on the day of recruitment.Socio-demographic characteristics transferred directly from CLINICOM to the data spreadsheet included information on race , gender , date of birth, family income and residential address of patients. Family income per month was classified using the Western Cape provincial categories, namely H0 for R0.00 and/or government pension, H1 for > R0.00 to R4166.66, H2 for R4166.67 to R8333.33, H3 for > R8333.34, and P for private medical aid. Information collected using the interviewer-administered questionnaire included employment status, number of years of formal education  and reason for declining the 6-week FBTG intervention . All patients were also asked to indicate their 6-month weight loss goal.For the physical activity assessment, patients were asked whether or not they participated in formal and/or informal exercise and to specify the exercise type. The frequency of exercise sessions was recorded as the number of times each exercise type was performed per day, per week or per month. The typical duration for each session was recorded in minutes. To calculate the minutes of physical activity performed per week, the number of times the patient exercised was multiplied by seven if daily, divided by one if weekly, and by four if monthly. The subsequent value was multiplied by the indicated duration. If a patient participated in more than one type of exercise, the weekly minutes per week of each exercise were summed. The number of minutes per day spent watching television was recorded and used as a reflection of leisure time sedentary activity.29 for the assessment of the healthfulness of food choices in educators from low socio-economic areas in the Western Cape was adapted for the purposes of the present research by an expert panel of dietitians. The rigorous process followed by Seme29 in the development of the food list and the further consideration thereof by the expert panel for application in this study contributed to construct, content and face validity.The focus of the dietary assessment was on determining the number of standard portions consumed per day from indicator food groups. For these purposes, a semi-quantified food frequency questionnaire (FFQ) consisting of 54 food items was developed, from which 10 indicator food groups were derived . The ind30 The plate model was used to illustrate standard portion sizes to patients. The number of standard portions consumed per day for each food item was calculated by dividing the number of times the patient consumed the standard portion by one if consumed daily, by seven if consumed weekly, and by 28 if consumed monthly. These values were summed for food items contributing to a particular indicator food group to calculate the daily number of standard portions consumed from each of the 10 indicator food groups. Patients were also asked how many formal meals and snacks they consumed daily.The frequency of intake of a standard portion of each food item was recorded as the number of times the food was consumed per day, per week or per month. For quantification purposes, a standard portion size was allocated to each food item and alcoholic or non-alcoholic drinks  using th14 Weight and height was measured in light clothing and without shoes, using a calibrated scale and stadiometer respectively. BMI was calculated as weight in kilograms (kg) divided by height in metres (m) squared and categorised according to the WHO classification,31 namely 30 kg/m2 – 34.9 kg/m2 as obese class I, 35 kg/m2 – 39.9 kg/m2 as obese class II, and > 40 kg/m2 as obese class III or morbidly obese. Waist circumference was measured midway between the last palpable rib and the top of the hip-bone after normal expiration using a non-stretchable tape measure.14 Waist circumference was classified as reflecting increased risk for the development of metabolic syndrome and NCDs if > 102 cm in men and > 88 cm in women.32Anthropometric measurements were conducted according to the World Health Organization (WHO) guidelines.Fasting blood samples and BP measurements were collected by nursing staff. The blood samples were analysed by the National Health Laboratory Service (NHLS) for glycated haemoglobin (HbA1c) and total cholesterol. HbA1c was only analysed in patients with type 2 DM. An automated sphygmomanometer was used to measure the BP of each patient when in a seated position with the cuff above the elbow. The diagnosis of hypercholesterolaemia and high BP was confirmed by the medical doctors using the International Classification of Disease codes (ICD-10). Missing values were issued for patients who did not attend their scheduled appointment for biochemical and clinical assessments.33The diagnosis of DM and CVD  was recorded by the medical doctor in the patient’s folder using the ICD-10 codes. Medication usage was recorded from the medication prescription chart in the patient’s folder. Current smoking status (yes or no and number of cigarettes per day) was determined to calculate the number of ’pack years’ i.e. the number of years an individual had smoked one packet of cigarettes per day.6 were adapted to describe the risk factor profile  in our sample. For these purposes, a score of one was allocated to each of the following: high BP, high cholesterol, current smoking, physical activity < 150 minutes per week,34 leisure time sedentary activity > 120 minutes per day,35 and fruit and vegetable intake < 5 portions per day.36 A minimum of zero indicated no risk factors present while a maximum of six could be obtained if all risk factors were present.The risk factor profile calculations described by Van Zyl et al.37 was used to determine patient readiness to increase their intake of healthy foods. The original RCQ was developed to determine the stage of change in individuals with excessive alcohol intake.37 This was adapted by Senekal et al. (unpublished) for research on the readiness of members of a South African medical scheme to consume healthy foods. The adapted RCQ aimed to categorise patients in a pre-contemplation (PC), contemplation (C) or action stage (A). The adapted questionnaire consists of the following nine statements, with three relating to each stage of change category:An adapted version of the 12-item Readiness for Change questionnaire (RCQ)‘I do not worry about what I eat.’ (PC)‘I am trying to eat more healthy foods than I used to.’ (A)‘I enjoy eating unhealthy foods, but eat too much of them at times.’ (C)‘Eating more healthy foods would be pointless for me.’ (PC)‘I recently started to eat more healthy foods.’ (A)‘My intake of unhealthy foods is a problem sometimes.’ (C)‘There is no need to think about changing what I eat.’ (PC)‘Sometimes I think that I should eat more healthy foods.’ (C)‘Anyone can talk about wanting to eat more healthy foods, but I am actually doing something about it.’ (A).37 with a score of -2 allocated to ’Strongly disagree’, -1 to ’Disagree’, 0 to ’Unsure’, +1 to ’Agree’, and +2 to ’Strongly agree’. These scores were summed, with the total score for each stage potentially ranging from -6 to +6. The highest of the three scores reflects the patient’s stage of change. In the event of the scores for two of the three categories being equal, the patient would be classified as being in the higher stage of the two stages.38The response categories and scoring were based on the scoring system used by Rollnick et al.,Data were entered into a Microsoft Excel (2007) spreadsheet and cleaned prior to analysis in STATA 11.0 . Numerical variables were checked for normality by exploratory analysis using box and whisker plots and the Shapiro-Wilk test.t-tests  and rank-sum tests  were used to compare numerical variables between those who chose the FBTG intervention versus those who chose usual care (referred to as treatment choice groups in the results and discussion). Pearson chi-squared or Fisher’s exact tests (if expected frequencies were < 5) were used to compare categorical variables between the two treatment choice groups. All results with a p-value < 0.05 were described as statistically significant.Descriptive analyses included calculation of frequencies for categorical data, as well as means (standard deviation) for numerical data. Independent Permission to conduct the research was obtained from the South African DoH and the medical superintendent of the healthcare facility . Ethical approval was granted by the University of Cape Town’ (UCT) Faculty of Health Science’s Human Research Ethics Committee (Ref: 118/2010). Written informed consent was obtained from each patient.The majority of patients who entered the study were women and of the coloured race . The patn = 37; 38.1%), preference for individual consultations , transport problems , family commitments , medical problems , demotivation , out of area  and time limitations . Twenty-seven (27.8%) patients gave no reason for declining the FBTG intervention.The reasons indicated by usual care choice patients for declining entrance into the FBTG intervention included work commitments  were in the contemplative stage of change at the time of the study, with 1.6% (n = 3) being in the pre-contemplative stage and 29.6% (n = 56) in the action stage. There were no significant differences between the two treatment choice groups .The majority of patients  on average have not completed secondary level education (12 years of schooling), with no difference between treatment choice groups. The low education level of the total sample may thus affect treatment outcomes and level of engagement in both treatment choice groups. Shankar et al.52 Although it has been suggested by the hospital administration that some patients under-report their income in order to qualify for lower hospital rates, the low income was expected as the catchment area for the hospital includes mainly low socio-economic households, education levels were low, and only half of the total sample were employed. It is plausible that low income may reduce treatment-seeking behaviour in general and, if treatment is sought, to opt for a less costly option. The perceived and actual higher cost of healthy eating53 may also be a barrier to enrolment in a lifestyle intervention for either treatment group. It is interesting to note that, despite the fact that there was no difference between treatment choice groups for employment status, usual care patients cited work commitments as the main reason for declining the FBTG intervention. It is plausible that unemployed or part-time employed individuals would be more likely to attend a regular FBTG programme or individual dietetic consultations  than employed individuals. However, financial constraints associated with unemployment may preclude them from doing so.The total sample had an average household income of up to R4167.00 per month, with an annual income of up to R50 004.00, which is considerably less than the average annual income of R78 157.00 to R14 3460.00 in Western Cape Province, as reported in the 2011 Census.9 Patients in the usual care choice group were significantly more likely to be current smokers, and may therefore be at higher risk for NCDs.DM was more prevalent in our sample than CVD, with the elevated HbA1c in those with DM, especially patients in the usual care choice group, reflecting poor long-term blood glucose control. High BP and high cholesterol were present in the majority of the sample. Better control of blood glucose and hypertension was expected as pharmacological treatment for the management of these indicators seemed to be in place. However, only half of those with high cholesterol were on statins, possibly because doctors in this PHC hospital applied risk stratification in patient management that involves an initial focus on lifestyle change for patients who have high cholesterol levels, but are not at high risk for CVD. Factors such as poor compliance with treatment, age, weight status, unhealthy diet and physical inactivity might have contributed to the poor control of blood glucose, BP and cholesterol. Furthermore, NCD risk may be increased in the 16% current and 25% past smokers (= 41% ever smokers) in the total group. The Western Cape population is known to have the highest smoking prevalence in South Africa, with 38.5% being ever smokers, which is in line with our results but much lower than the national prevalence of 20.8%.2). Weight loss should clearly be a major priority in the treatment and management of these patients. The estimated mean 6-month weight loss goal of 12.7 kg for the total group (not significantly different between the two treatment choice groups) equates to approximately 0.5 kg per week and is in line with the general recommendation for weight loss of 0.5 kg to 1 kg per week.54 If this rate of weight loss is attained, a weight loss of 12.4% can be expected if the initial mean weight of 102.4 kg for the total group is considered. Modest but sustained weight loss of 10% of initial weight may result in substantial improvements in glycaemic control, BP and lipid profiles, if maintained.56 Weight loss may also contribute to a reduction in waist circumference, which was in the undesirable range for almost all patients in the study sample, that will contribute to further NCD risk reduction and improved management for those with DM and/or CVD as central adiposity is known to exacerbate insulin resistance, dyslipidaemia and hyperglycaemia.32 As there were no differences in anthropometric measures between the treatment choice groups, it is possible that weight status did not influence treatment choice in our study sample.Although a BMI in the obese range was expected, it is very concerning that over a third (37.3%) of patients recruited into the study were morbidly obese  is considered an unhealthy behaviour as it is known to displace formal moderate physical activity and promote the consumption of unhealthy snacks and beverages, increasing the incidence and mortality from DM and CVD.35 The proportion of the sample who were physically inactive was 86%, which is much higher than the national prevalence of inactivity for men (44.7%) and women (47.6%).58 It is also higher than the prevalence of 66.5% found in a study of urban dwellers in Free State Province in South Africa.6 Furthermore, the reported 21 minutes per week of physical activity in the total sample is much lower than the 150  to 300 minutes per week recommended by the WHO for adults aged 18 to 64 years old, to reduce the risk of NCDs.34 The causes of low physical activity were not assessed in this sample, although other research has indicated that socio-environmental factors such as poor neighbourhood safety, lack of recreational space, and lack of exposure to physical activity education over an individual’s lifetime are the primary causes.59One of the most concerning findings among the total group of patients in the present study is the combination of the low level of self-reported physical activity and the time spent watching TV (2 hours per day on average), which was equally poor in both treatment choice groups. Time spent watching TV is often used to gauge the level of sedentary activity.60 On average, 8.4 standard portions of fats, high fat foods and energy-dense snacks (combined), 1.3 glasses of sugar-sweetened beverages and approximately five teaspoons of added sugar were typically consumed by our sample per day. Furthermore, refined carbohydrates (10.6 standard portions per day) were consumed more regularly than high-fibre foods (3.1 standard portions per day) and the usual care choice group had a higher intake of refined carbohydrates. The patients in the present study reside in urban communities where there is access to a variety of fast-food restaurants and informal vendors who typically sell foods that are energy-dense and high in fat, salt, sugar and refined carbohydrates. Alcohol intake amounted to approximately half a unit per day, which is in line with recommendations of one unit per day for women and two for men.61 Although moderate alcohol intake has been associated with decreased CVD risk and DM incidence, excessive alcohol intake may increase the risk for high BP.62 It is possible that some patients might have underreported their alcohol intake, which has been found to be a limitation in other South African studies investigating alcohol intake.63The present study demonstrated that the dietary intake reflects the ‘Western’ eating patterns that have been associated with an increased risk of developing NCDs.36 and also the recommendations of the dietary approaches to stop hypertension (DASH) programme that promotes 8 to 10 portions of fruit and vegetables per 8400 kcal.64 Low intakes of fruit and vegetables may increase the burden of disease and reduce survival rates.36 Low intakes in South African populations are not uncommon, with primary school educators in lower socio-economic areas in the Western Cape29 and South Africans in general36 reportedly consuming less than the FBDG recommendation. Intake of low-fat food choices, reflecting healthy lower fat choices over energy-dense, high fat or fried foods, was low at 2.4 standard portions per day. It is known that healthy food choices are affected by their cost, preference and access as well as cultural acceptance, knowledge and perceived control over healthy food choices.65 It could therefore be argued that health education may not be sufficient to change purchasing and eating behaviours if the cost of healthy foods continues to be unfavourable, while cheap, unhealthy foods are readily accessible in urban communities. In line with findings from educators in low socio-economic areas in Cape Town,29 our results show that the patients’ meal patterns were regular, with infrequent snacking. The latter was more frequent in patients who chose the FBTG intervention, but still below two times per day.Fruit and vegetable intake was low at 2.2 standard portions per day and falls short of the recommendations made by the 2012 South African food-based dietary guidelines that promote a minimum of five portions per day66 are summed, the total attributable burden of death from these four risk factors is 22.5%. Our findings are similar to those found in a cross-sectional study of urban dwellers in Free State Province in South Africa that ranked physical inactivity, high BMI, hypertension, smoking and high cholesterol in descending order as the primary risk factors for NCDs in their study sample.7 The mean number of risk factors was close to four in both groups, which was expected as the sample included patients seeking treatment for NCD-related conditions. The significantly higher number of risk factors in the usual care choice group is an interesting observation, especially as it seemed to be as a result of a higher prevalence of smoking and lower proportion of patients achieving five fruit and vegetable portions daily in the usual care group. Jimenez-Garcia et al.67 reported that patients who presented with several risk factors such as smoking, high alcohol intake, physical inactivity and poor diet were more likely to be non-adherent to lifestyle guidelines and have fewer contacts with health professionals. It could be argued that usual care patients were less likely to have changed their lifestyle in the past six months and therefore chose the less intensive usual care option. However, this possibility is not supported by the results of our stages of change assessment, as there were no significant differences between the two treatment choice groups for stages of change. It is important to note that the majority of patients in the total sample were in the contemplative stage, indicating that they were not actively changing unhealthy food choices yet may show intention to change behaviour.69Finally, over and above the presence of a high BMI (obesity), the top three risk factors for NCD development in the total group and in each treatment choice group were inadequate physical activity, low fruit and vegetable intake, and high blood pressure. It is important to note that, if the burden attributable (in percentage) to each of these three risk factors plus being obese in terms of death as reported by Norman et al.The findings of the present research need to be considered while bearing in mind the limitations of using self-reported data. The comprehensive process followed in the development of the questionnaire, as well as the fact that all interviews were conducted by the same well-trained dietitian addresses some of these concerns. Although content, construct and face validity of the food list included in the FFQ were ensured, validation of the daily frequency of intake of items in the indicator food groups is recommended. A further limitation is the fact that data for biochemical measures, including HbA1c and cholesterol levels, were not complete, reducing the sample size and therefore power to detect differences between treatment choice groups for these variables.The primary aim of the present research was to describe the characteristics of patients seeking treatment for NCDs and/or risk factors for NCDs. The socio-demographic and health profile of this urbanised sample of obese patients with NCDs (DM or CVD) or risk factors for NCDs shows that treatment-seeking patients attending a district PHC hospital in Cape Town were representative of a middle-aged, low income group comprising mostly coloured women. The most prevalent NCD among this sample was DM, followed by CVD, while the majority of patients suffered from hypertension and over two-thirds had high cholesterol despite the availability of pharmacological treatment. The sample was also characterised by low levels of physical activity and poor food choices that may explain the seemingly poor management of the diseases, as well as the intermediate risk indicators, including obesity. Patients choosing the less intensive usual care may have more NCD risks as they had a higher smoking prevalence, HbA1c, number of NCD risk factors and refined carbohydrate intake, and a lower proportion consumed adequate fruit and vegetables.The baseline patient profile may aid intervention planners, including the DoH, to ensure the planning of appropriate lifestyle interventions. The results clearly point to the importance of including a strong focus on healthy eating and physical activity options in interventions targeted at patients with NCDs or risk factors for NCDs. The inclusion of specific lifestyle advice for the management of hypertension, hypercholesterolaemia and hyperglycaemia is deemed necessary. It is also important that a behaviour change theory or model should be used in planning and implementing such lifestyle interventions. We recommend that future qualitative research should also investigate the reasons for choosing or declining specific weight loss interventions.


The packaging of chromatin into the nucleus of a eukaryotic cell requires an extraordinary degree of compaction and physical organization. In recent years, it has been shown that this organization is dynamically orchestrated to regulate responses to exogenous stimuli as well as to guide complex cell-type-specific developmental programs. Gene expression is regulated by the compartmentalization of functional domains within the nucleus, by distinct nucleosome compositions accomplished via differential modifications on the histone tails and through the replacement of core histones by histone variants. In this review, we focus on these aspects of chromatin organization and discuss novel approaches such as live cell imaging and photobleaching as important tools likely to give significant insights into our understanding of the very dynamic nature of chromatin and chromatin regulatory processes. We highlight the contribution plant studies have made in this area showing the potential advantages of plants as models in understanding this fundamental aspect of biology. In eukaryotic cells the nuclear DNA does not appear naked but is associated with many proteins to form the complex called chromatin. The most prominent proteins in chromatin are the histone proteins—basic proteins responsible for the vast degree of packaging of the DNA within the confines of the eukaryotic nucleus. Approximately 146 base pairs of DNA are wrapped around an octamer of histones containing two copies of each of the four core histones  forming the most fundamental unit of chromatin—the nucleosome [.Core histones have been structurally conserved through evolution and have evolved to accomplish two conflicting and yet vital tasks: on one hand the long DNA molecules have to be packaged within the limits of the eukaryotic nucleus, preventing knots and tangles and protecting the genome from physical damage; on the other hand the information that is encoded in the DNA needs to be accessed at appropriate times. These functions are, at least in part, regulated by local changes in nucleosome and chromatin structure by complex mechanisms that have only recently begun to be understoodThe nucleosomes are positioned every ~200 bp on a typical DNA strand, and can be linked together by the linker histone H1. Electron microscopy of isolated polynucleosomes clearly reveals the open “beads-on-a-string” structure of the so-called 10 nm DNA fibre ,4. It wa. In nuclei of mammals and some other eukaryotes these domains are organized in the nucleus with heterochromatin mainly localized towards the nuclear periphery and euchromatin in the interior of the nucleus [Chromatin has traditionally been divided in two distinct classes: euchromatin and heterochromatin . Origina nucleus ,19,20. The ability of a gene to be transcribed is thought to depend on its accessibility to the transcription machinery. In fact nucleosomes represent a barrier to many protein complexes that need to contact the DNA and regulate gene expression . The mecIn this review we consider two main aspects of chromatin regulation at the nucleosome level (histone modifications and histone variants) as well as the spatial distribution of genes within the three-dimensional space of the nucleus as a means to regulate transcriptional activity.DNA methylation at 5-methylcytosine (5-mC) is one of the best studied epigenetic marks implicated in regulation of gene expression. The function of DNA methylation includes roles in development and in genome defense against transposons. DNA methylation is confined to relatively specific regions of the genome. Highly methylated regions comprise: transposons, rDNA arrays and centromeric repeats. Heterochromatin knobs  and periIn mammals, methylation is found almost exclusively in CG dinucleotides , with exRecent advances in high-throughput sequencing technologies combined with bisulfite treatment of Arabidopsis genomic DNA allow analyses and the generation of high resolution genome-wide methylation maps and are now revealing in unprecedented detail the patterns and dynamic changes of DNA methylation in plants. We will not discuss it further for the purpose of this article but there is currently a great body of literature on this subject ,42,43,44Histone proteins contain flexible N-terminal tails that extend outward from the nucleosome core and that are subject to diverse post-translational modifications (PTMs). Although histone tails are the main targets for post-translational modifications, the histone core domains can also be modified (reviewed in ). For th. This suggests that the regulation is highly complex, rather than being a simple and predictable code in which each modification has a unique effect.In recent years the number of modifications that have been identified on histones has increased quite dramatically. Over eight different classes have been characterized to date and many sites have been described within each class. An additional degree of complexity is that multiple modifications can be added simultaneously in the same nucleosome or even on the same histone tail  creatingHistone modifications are caused by the direct action of histone-modifying enzymes. During the last few years, enzymes have been identified for almost all types of modification (reviewed in ). A numbRapid progress in recent years has brought plenty of data about the diverse roles and mechanisms of histone modifications in regulating gene expression. For instance the arrival of genome sequencing brought the possibility to map genome modifications at high resolution and led ultimately to the concept of the “epigenome”. There are now several examples of epigenomic profiling in Arabidopsis ,55,56,57Not much is known, however, about the interplay between the mechanisms responsible for the addition and removal of these marks and how they are involved in orchestrating development. Further studies to reveal the molecular role of these factors will be necessary to understand the mechanisms underlying cell differentiation and development. The best characterized post-translational modification regulating chromatin structure is the acetylation of one or more of the lysine residues in the histone N-terminal tails. Its regulatory role was proposed about 50 years ago . Histonein vitro [Of all modifications acetylation has the highest potential to induce chromatin unfolding. The neutralization of the positive charge of lysine at the histone tails has a strong effect in destabilizing inter-nucleosome contacts and therefore the chromatin structure itself. Experiments in which tail residues were chemically modified on recombinant histone core preparations showed that acetylation of histone H4 on lysine 16 (H4-K16Ac) has a negative effect on the formation a higher order chromatin structures in vitro . The enzymes that acetylate histones, the histone acetyltransferases, are classified into three main families, GNAT, MYST and CBP/p300 . In geneTriticum aestivum) inhibition of HDAC activity by trichostatin-A (TSA) was shown to affect gene positioning and the overall structure of interphase chromosomes [In wheat  [In plants the LIKE HETEROCHROMATIN PROTEIN 1 (LHP1), also known as TERMINAL FLOWER 2 and considered to accomplish the role of Polycombs (PcG) in plants, has the ability to bind to H3K27me3 ,76). LHP C (FLC) .Histones can also be mono- or dimethylated on arginines ; howeverHistone modifications and their implications for chromatin structure and regulatory processes that act on DNA, such as replication, repair and regulation of gene expression, have long been recognized. Similarly to histone modifications, the incorporation of histone variants into chromatin contributes to its regulatory repertoire. The expression of most of histones is tightly coupled to S phase of the cell cycle, when the newly synthesized DNA requires additional histone molecules . These hWith the exception of histone H4, all of the core histones have a number of variants, which probably arose through gene duplication . Here, wThe cenH3 is an H3 variant that is specialized for packaging chromatin at eukaryotic centromeres and is essential for the assembly of kinetochores ,84,85,86CenH3 variants have unusual features. Relative to the canonical H3, which is one of the most conserved proteins, cenH3 sequences are surprisingly divergent. Sequence analysis has revealed 50%–60% similarity with the canonical form at the C-terminal histone-fold domain (HFD) and little or no conservation at the N-terminal region . In spitThe dynamic behaviour of cenH3 was studied in Arabidopsis by developing transgenic lines in which this variant was tagged with GFP . Using fDrosophila melanogaster cenH3) nucleosomes have only half of the height of canonical nucleosomes. Together these observations support a model in which cenH3-containing nucleosomes consist of stable heterotypic tetramers —the “hemisome” model [CenH3-containing nucleosomes have been traditionally considered as octamers; however recent studies suggest that they might be organized as tetramers. Evidence for that comes from MNase assays in Drosophila . Unlike e” model . Howevere” model .Another potentially important feature of cenH3 variants is that in common with archeal histones, they induce positive supercoils in DNA . This poBesides cenH3, other H3 variants have been reported. H3.3 differs from the canonical H3 only at four amino acid residues and is incorporated into chromatin in a replication independent fashion . Three oin vivo into a transgene array as the array undergoes activation [Additionally, while the canonical H3 is incorporated in chromatin by the chromatin-assembly factor 1 (CAF1) during DNA replication and repair, H3.3 is assembled into chromatin by another complex—histone regulator A (HIRA)—independently of DNA synthesis . In spittivation .D. melanogaster revealed that H3.3 is turned over more rapidly than H3 [Studies in  than H3 , which m than H3 . A possi than H3 . On thatH2A.Z is a highly conserved variant of the canonical histone H2A. Phylogenetic analysis indicates that H2A.Z diverged from the canonical form early on during the evolution of eukaryotes but since then it has been fairly well conserved. In fact, the H2A.Z variants of different organisms show a higher degree of sequence similarity (approximately 90%) than the H2A.Z and H2A within the same organism ,102. Saccharomyces cerevisiae it is not essential for viability but has a function that cannot be substituted by the canonical H2A [Arabidopsis thaliana there are three different H2A.Z genes , which are redundant to some extent and differ in cell-cycle regulation [The H2A.Z variant has been widely studied and has been shown to be essential in both mammals and in Drosophila ,104. In ical H2A . Unlike ical H2A . In Arabgulation .The H2A.Z variant is incorporated into nucleosomes by the action of a specific multi-subunit complex termed SWR1 in yeast and SRCAP in humans. SWR1 is an ATP-dependent remodelling complex that exchanges H2A-H2B dimers for H2A.Z-H2B in the nucleosomes ,110,111.Tetrahymena thermophila H2A.Z was found to be associated with the transcriptionally active macronucleus but absent in the transcriptionally inert micronucleus [. The crystal structure of H2A.Z-containing nucleosomes suggested that its incorporation destabilises the interface between H2A.Z-H2B and the H3-H4 dimers [In onucleus . These o4 dimers . Accordi4 dimers . A separ4 dimers ,122.Saccharomyces cerevisiae H2A.Z has been implicated in diverse biological processes including the control of gene expression [Studies of the properties of H2A.Z-containing nucleosomes have led to conflicting conclusions over the past few years. It appears that in spite of great sequence conservation, the function might have diverged considerably, with different functions described for different organisms ,124. In pression ,128,129,pression , chromospression , DNA reppression  and prevpression . In highpression , embryonpression  and antapression . Its funH2A.Z can show contradictory functions even within the same organism. In differentiated mouse fibroblasts H2A.Z is distributed across the entire interphase nucleus but is excluded from transcriptionally silent and HP1 enriched pericentromeric regions . HoweverRecent studies have suggested one reason why H2A.Z function shows such contrasting effects. Genome-wide ChIP sequencing or ChIP-microarray experiments showed that H2A.Z preferentially localizes in the 5' regions of genes within euchromatic regions ,141,142.Finally, research in Arabidopsis presented a new concept where H2A.Z-containing nucleosomes provide thermosensory information for coordinating temperature responses in plants . H2A.Z nAs well as modification either covalently by histone post-translational modifications or by incorporation of histone variants, nucleosomes can also be mobilized to different positions along the DNA, or evicted by ATP-dependent remodelling enzymes. ATP-dependent remodelling factors play an essential role in gene expression by regulating the access of the transcription machinery to DNA sequences . GeneralCurrent data from studies in animals suggest that the biochemical mechanism by which each type of remodeller acts is distinct and may account for their unique biological functions. For example SWI/SNF complexes are able to induce ATP-dependent disruption of nucleosome structure, facilitating the binding of transcription factors to their target sites on nucleosomal templates . In contAn obvious question is how these ATP remodellers are targeted to the appropriate genomic regions. Different mechanisms have been proposed; the best studied is based on targeting via DNA-sequence-specific factors . For insBromodomain factor 1) as a member of the SWR1 complex [Another way by which ATP remodelers regulate chromatin structure and gene regulation is via incorporation of histone variants. One example, mentioned previously, is the ATP-dependent remodelling enzyme responsible exchanging the canonical histone H2A with the variant H2A.Z. The SWR1 complex is named after its ATPase sub-unit Swr1 (for Swi2/Snf2 related). This complex seems to be targeted to specific sites by a mechanism that involves the recognition of histone acetylation. This conclusion came from the identification of Bdf1 , sorghum (Sorghum bicolor) and Arabidopsis this arrangement is not observed, and chromosomes seem to lose their polarized anaphase configuration after entering interphase. In Arabidopsis, the telomeres have a strong tendency to be associated with the nucleolar periphery, and this association has been suggested to be an initial stage in meiotic homologue pairing [While not much is known about what controls the organization of CT in interphase it is believed that several factors might be involved, including content and distribution of heterochomatin and repetitive regions, association with the nuclear envelope among others . In many pairing .Oryza sativa) the Rabl congfiguration is only observed in certain tissues [In rice  the activation of the avenacin gene cluster is accompanied by chromatin decondensation [Sad1 and Sad2 genes and used mRNA and DNA in situ hybridization techniques to show that the two genes moved apart from approximately 0.45 to 0.90 µm upon activation in a cell type-specific manner. They also showed that individual genes elongated on activation to the order of about 20-fold compaction compared to naked B-DNA. This is more compact than the 10 nm fibre, but less than the proposed 30 nm fibre  and immunofluorescence-FISH, and in molecular approaches such as chromosome conformation capture (3C) and related methods [Another possibility is the occurrence of discrete sites for transcription in the nucleus, which have been termed transcription factories . Accordi methods ,183 that methods ). The development of new molecular, genomic and computational approaches based on chromosome conformation capture technology  are currently helping us to study the spatial organization of genomes at an extraordinary level resolution. In 3C-based methods cells are initially cross-linked with formaldehyde to preserve chromatin structure and subsequently digested with restriction enzymes or sonication. Cross-linked fragments are then ligated resulting in segments that contain sequences that were in close spatial proximity. The DNA is then finally purified and analysed.The different 3C-based methods differ essentially in the way the DNA segments are detected and quantified. In conventional 3C techniques, single ligation products are detected by PCR one at a time using primers from specific sequences. 4C, chromosome conformation capture-on-chip, combines 3C technology with microarrays to analyse the contacts of a specific genomic site with all of the genomic fragments present on the array generating therefore a genome-wide interaction profiles for single loci ,186. In in vivo. Recently, a combination of molecular biology and live cell microscopy techniques has allowed observation of the dynamic behaviour of chromatin in vivo within the natural environment of the nucleus. For many years the majority of studies that examined the mechanisms by which chromatin regulates transcriptional activity focused on measuring steady-state levels. A typical biochemical approach is chromatin immunoprecipitation, in which chromatin fragments still associated with histones or other chromatin proteins  are precipitated using a specific antibody, and the DNA or proteins associated with the target are then analysed. The trouble with these types of approach is that often they do not take into account the dynamic properties of chromatin, leading to rigid assumptions about stable interactions between chromatin and chromatin proteins in vivo.The first experimental evidence to indicate that the protein composition of chromatin was not static came from radioactive isotope labelling studies in the early 1980s ,193,194.fluorescence recovery after photobleaching (FRAP) confirmed that most of the functionally important characteristics of chromatin show a dynamic behaviour. With the development of confocal microscopes and their laser illumination systems, FRAP became a very accessible technique for analysing the kinetics of molecules in living cells . FRThe first results of FRAP experiments on histone H1-GFP fusions appeared in 2000 ,198. Bott1/2≅ 130 min) independent of ongoing DNA replication and transcription, and another (>50%) that remains bound stably (t1/2 > 8.5 h) [Apart from histone H1 the mobility of many other histones has also been assessed by FRAP (reviewed in ). Compar> 8.5 h) . in vitro studies showed that the transfer of H2A–H2B from nucleosomes to histone chaperone Nap1 (nucleosomes assembly protein 1) is facilitated by p300-mediated acetylation [The mechanism that accounts for the differences in kinetics between different histones and between the different pools within the same type of histone is related to differences in biochemical modifications. For instance it is known that acetylation of histone tails alters the stability of nucleosomes and also has been shown to alter the dynamics of H2B in living cells . Acetylatylation . Althougin vivo [Recently the development of photoswitchable or photoactivatable tags has made them an optimal tool for studying the spatial and temporal dynamics of proteins in vivo . As the Drosophila melanogaster S2 cells with the methionine (Met) surrogate azidohomoalanine (Aha). The surrogate amino acid is incorporated into histones, and Aha coupled with biotin. Streptavidin beads are then used to affinity purify nucleosomes containing newly synthesized histones. The nucleosomal DNA is finally hybridized to a high-density tiling microarray to create a map of nucleosomes that have turned over during the pulse. The great advantage of this strategy is the possibility of assaying native histones, overcoming limitations related to requirements for transgenics and tags. The method should be applicable across species; however; there are only a few reports available so far.An alternative method for measuring histone turnover showing great promise has recently been developed . The metWhile it is clear that spatial organization of chromatin in the nucleus is highly correlated with gene expression, the majority of the techniques used to study chromatin structure are unable to reveal a real dynamic view, providing instead a static analysis under a particular condition. The observation of chromatin motion requires the labelling of specific chromatin loci with techniques that are compatible with live cell imaging.lac operator/repressor (lacO/LacI) [tetO/TetR) [Recently, taking advantage of the exploitation of bacterial repressor/operator interactions in conjugation with GFP technology, significant breakthroughs in this field have been possible. Two systems are currently in use: one is based on the cO/LacI) ,207,208,tO/TetR) ,210. BottO/TetR) ,212. TheDrosophila nuclei [The initial surprise from this approach was the dynamic behaviour that chromatin exhibits in both yeast and a nuclei ,214. Thea nuclei . In anota nuclei . Studiesa nuclei . These oExperiments in yeast showed that early and late origins of replication were more mobile in G1 than in S phase, and that the movement in G1 was highly sensitive to ATP depletion and changes in metabolic status . This colac operator system has been used to analyse the repositioning of alleles of a Polycomb target gene, FLOWERING LOCUS C (FLC), during an environmentally-triggered silencing process involved in the control of flowering time—vernalization [FLC locus physically associate and reposition in the nucleus during in the silencing process (see In plants a few studies have used this approach. The first use  showed tlization . This stcess see , and theOne drawback of this type of approach is the high sensitivity to photodamage and bleaching. It was shown for both yeast and mammalian cells that the movement of the tagged sequence is affected by long time-course imaging ,225. ThuIn summary, as the field of chromatin dynamics has developed, it has become increasingly clear that a large number of underlying physical and molecular phenomena is involved, and that to fully understand them, information at many different levels is required. The study of chromatin dynamics and its effect on gene expression has opened new and exciting perspectives and one important goal of current research is to be able to relate these different levels of regulation. Advances and new strategies that allow “super” resolution in light microscopy will soon be in common use and may open the way to this type of correlative work.


Measurement of MRP8/14 serum levels has shown potential in predicting clinical response to different biological agents in rheumatoid arthritis (RA). We aimed to develop a treatment algorithm based on a prediction score using MRP8/14 measurements and clinical parameters predictive for response to different biological agents.Baseline serum levels of MRP8/14 were measured in 170 patients starting treatment with infliximab, adalimumab or rituximab. We used logistic regression analysis to develop a predictive score for clinical response at 16 weeks. MRP8/14 levels along with clinical variables at baseline were investigated. We also investigated how the predictive effect of MRP8/14 was modified by drug type. A treatment algorithm was developed based on categorizing the expected response per drug type as high, intermediate or low for each patient and optimal treatment was defined. Finally, we present the utility of using this treatment algorithm in clinical practice.The probability of response increased with higher baseline MRP8/14 complex levels (OR = 1.39), differentially between the TNF-blockers and rituximab (OR of interaction term = 0.78), and also increased with higher DAS28 at baseline (OR = 1.28). Rheumatoid factor positivity, functional disability (a higher HAQ), and previous use of a TNF-inhibitor decreased the probability of response. Based on the treatment algorithm 80 patients would have been recommended for anti-TNF treatment, 8 for rituximab, 13 for another biological treatment (other than TNFi or rituximab) and for 69 no recommendation was made. The predicted response rates matched the observed response in the cohort well. On group level the predicted response based on the algorithm resulted in a modest 10% higher response rate in our cohort with much higher differences in response probability in individual patients treated contrary to treatment recommendation.Prediction of response using MRP8/14 levels along with clinical predictors has potential in personalizing treatment for RA patients starting biological anti-rheumatic treatment, and might increase cost-effectiveness. Biological therapies have become commonly available for the treatment of rheumatoid arthritis (RA) over the past decades. BiologicTools which can be used in daily practice to predict response to biological drugs and guide the choice of treatment are relatively scarce. Although many studies have explored predictive factors for response to biological therapies, only few have been confirmed. ConceivaWe used a previously published dataset to determine the association between serum levels of MRP8/14 at baseline and the clinical response to treatment with infliximab, adalimumab and, rituximab. 170 patiAlthough it has previously been found that MRP8/14 complexes are associated with clinical response to adalimumab, infliximab and rituximab separately, it has aTo test whether there are differences in prediction of response by MRP8/14 levels between different biologicals, we calculated the discriminative ability of MRP8/14 complexes for EULAR moderate or good response (defined as EULAR moderate or good response) to treatment at 4–5 months. This was done separately for adalimumab, infliximab, and rituximab using the area under the receiver operating curve (ROC), as described before . DiffereBased on the results of the above analysis we either grouped the drugs (per class: TNF-inhibitors or anti-B cell treatment) or used them separately in the logistic regression analysis to develop the predictive score for EULAR response. We built the predictive model using logistic regression in a stepwise manner with in the first step the variables age, gender, IgM RF, ACPA, DAS28, HAQ, MRP4/18 complex level, previous use of TNF inhibitors and the type of drug in the model. Next, we removed variables one by one, based on p value and regression coefficient to arrive at a final model. We also investigated modification of the predictive effect of MRP8/14 serum levels by the other predictors in the final model. A liberal p value of <0.3 was considered for statistical significance for this predictive analysis. To correct the regression coefficients for over fitting and internally validate the model, we used bootstrapping and the bootstrapped version of the model was used to compare predicted and observed response rates graphically to assess model fit.---+-)--). When predicted probabilities for rituximab are calculated drug type = 0 and when predicted probabilities for TNF blockers are calculated drug type = 1. Using these predicted scores, each patient was classified as having a high, intermediate or low predicted probability of EULAR response for each biological. We considered a predicted probability for response below 0.5 to be a low chance and a predicted probability above 0.9 as a high chance, with probabilities in between considered as an intermediate chance of response. This classification was based on the average response in the total population being 74.1% and clear deviations (of about 25%) from this average response. Based on the expected (i.e. predicted) response categories for each treatment modality as mentioned above, we defined the optimal treatment/treatments, providing the treatment advice in each patient.The validated predictive model (logistic regression function) was used to calculate predicted probabilities (i.e. chances) for EULAR response for each patient for treatment with each biological (class), by filling in the specific drug type in the predictive model and using the following formula: 1/ 1+eThe added value of using the algorithm was calculated by comparing the average (mean) predicted response in the cohort based with recommended treatment with the observed average response in the cohort and with the predicted response with treatment contrary to the treatment advice.All statistical analyses were performed in SPSS version 20 and SAS version 9.2The discriminative ability of MRP8/14 baseline serum levels for EULAR response was comparable for adalimumab and infliximab  with AUCTable 2)The logistic regression analysis resulted in a final model after internal validation using bootstrapping as shown in The theoretical optimal treatment choice was defined based on the expected probability (‘chance’) of response to (both) TNF-inhibitors and the expected probability of response to rituximab for an individual patient. If no distinction between drug types was present using the algorithm , treatment decisions should be made solely by the treating physician together with the patient (‘no recommendation’). Table 3). The probability of response was clearly lower if the patients were treated with the other drug instead of the one indicated.We compared observed responses in the cohort to predicted responses  in patients where a clear treatment advice could be given , to assess the benefit of using this treatment algorithm in decision making. The predicted response when treated according to the algorithm was higher than observed in the cohort ) based on recommendations for logistic regression analysis.Taken together, we have shown that MRP8/14 holds promise as a predictor for treatment response on TNF-inhibiting biologicals and rituximab and this biomarker might be a useful tool in an algorithm facilitating the decision making on which type of biological treatment has the best chance of success in individual RA patients.MRP8/14 holds promise as a predictor for treatment response.A treatment algorithm was developed based on the predictive value of MRP8/14 serum levels when combined with clinical parameters.This biomarker might be a useful tool in an algorithm facilitating the decision making on which type of biological treatment has the best chance of success in individual RA patients.


Postdischarge death in children is increasingly being recognized as a major contributor to overall child mortality. The PAediatric Risk Assessment (PARA) app is an mHealth tool developed to aid health care workers in resource-limited settings such as Sub-Saharan Africa to identify pediatric patients at high risk of both in-hospital and postdischarge mortality. The intended users of the PARA app are health care workers  with varying levels of education and technological exposure, making testing of this clinical tool critical to successful implementation.Our aim was to summarize the usability evaluation of the PARA app among target users, which consists of assessing the ease of use, functionality, and navigation of the interfaces and then iteratively improving the design of this clinical tool.Health care workers (N=30) were recruited to participate at Mbarara Regional Referral Hospital and Holy Innocents Children’s Hospital in Mbarara, Southwestern Uganda. This usability study was conducted in two phases to allow for iterative improvement and testing of the interfaces. The PARA app was evaluated using quantitative and qualitative measures, which were compared between Phases 1 and 2 of the study. Participants were given two patient scenarios that listed hypothetical information  to be entered into the app and to determine the patient’s risk of in-hospital and postdischarge mortality. Time-to-completion and user errors were recorded for each participant while using the app. A modified computer system usability questionnaire was utilized at the end of each session to elicit user satisfaction with the PARA app and obtain suggestions for future improvements.The average time to complete the PARA app decreased by 30% from Phase 1 to Phase 2, following user feedback and modifications. Participants spent the longest amount of time on the oxygen saturation interface, but modifications following Phase 1 cut this time by half. The average time-to-completion (during Phase 2) for doctors/medical students was 3 minutes 56 seconds. All participants agreed they would use the PARA app if available at their health facility. Given a high PARA risk score, participants suggested several interventions that would be appropriate for the sociocultural context in southwestern Uganda, which involved strengthening discharge and referral procedures within the current health care system.Through feedback and modifications made during this usability study, the PARA app was developed into a user-friendly app, encompassing user expectations and culturally intuitive interfaces for users with a range of technological exposure. Doctors and medical students had shorter task completion times, though all participants reported the usefulness of this tool to improve postdischarge outcomes. Infectious disease in Sub-Saharan Africa is the leading cause of child mortality, accounting for 6.3 million deaths among children under 5 years old . A systeOne promising approach is a clinical tool to allow for early identification of at-risk patients. The PAediatric Risk Assessment (PARA) mobile app is a simple, easy-to-use mHealth tool developed to aid health care workers in resource-limited settings to identify pediatric patients at high risk of mortality. The PARA app uses prediction models to accurately predict and categorize newly admitted patients as having high or low risk of death, both in-hospital and after discharge ,4. This Improved access to technology in Sub-Saharan Africa, particularly mobile technology, creates an enabling environment for mobile apps such as the PARA app. The mobile network coverage in Sub-Saharan Africa is high, with availability of third generation (3G) connections rapidly growing ,6. As ofMobile phones are currently utilized for a wide array of mHealth interventions . These rThe primary PARA models ,4 were d2) when connected to a pulse oximeter . On. On16]. The usability tasks  were adapted from the Pre-eclampsia Integrated Estimate of RiSk on the Move usability study and developed to encapsulate the specific functionalities of the PARA app see  17]. Th. Th17]. The PARA app was evaluated using quantitative and qualitative measures, which were compared between Phases 1 and 2 of the study. Quantitative measures were limited to descriptive statistics. Time-to-completion was recorded for each participant and compared between patient scenarios and occupational groups.2). Severity was based on the impact of errors on the achievability and specificity of the PARA risk score. Errors were categorized into navigation errors (low severity), control usage errors (medium severity), and outcome errors (high severity)  see . High seIn total, 30 health care workers  participated in the PARA app usability study, with 15 male and 15 female. Participant populations between Phases 1 and 2 of testing had an equivalent number of doctors/medical students and nurses/clinical officers for each phase. More participants came from HICH  than MRRH . The majority of participants  were between 20-30 years old. All participants owned a cell phone, with the majority of doctors/medical students owning a smartphone . Few had used a tablet  or health app  previously.2 dropped from 2 minutes 23 seconds for the first patient scenario to 1 minute 28 seconds for the second patient scenario. Doctors took the least amount of time to complete the app, averaging 4 minutes 38 seconds during the second patient scenario.For the first patient scenario, the average time-to-completion was 9 minutes 58 seconds. By the second patient scenario, the average time-to-completion dropped to 6 minutes 23 seconds. In particular, the average amount of time spent obtaining the SpO2 not being recorded. Two participants did not reach the final interface and failed to calculate the patient’s risk score.In addition to time, the average number of errors dropped between the first and second patient scenario from 4.3 to 3.2 errors see . The majBased on Phase 1 results and participant feedback, modifications were made to the PARA app to decrease user errors and time-to-completion of tasks. Error-producing interfaces were simplified by adjusting the instructional dialogue, interface design, or error messages.2 screen and interpreting how to use the tablet-based system. Since the previous SpO2 recording was retained, some participants thought the SpO2 was already recorded when it was not. One participant said “So what will happen? Will [the SpO2 recording] stop? Will it stop or am I the one to stop it? [Sees SpO2 from previous recording] But I think the oxygen saturation is 93, it is just at 93. So I am moving to the next.”Errors caused by the oxygen saturation and summary interfaces were the most common issues. The oxygen saturation interface produced the most difficulties, as participants had trouble accessing the SpOParticipants also had difficulty interpreting the summary of risk factors screen. When asked to identify the most important risk factors listed on the summary interface, one participant said:I am imagining that red means danger so if it is more red, then it is contributing a lot. But you can’t tell to what degree, to what percentage. Here they are almost all the same for example, so you almost think that perhaps they all almost have perhaps the same contribution. I’m thinking like that but it’s not so clear here to tell which one or to what degree.2, the tablet-based SpO2 was changed to be the default display, with an option to enter SpO2 from another device at the bottom of the screen. Additional instructional messages were incorporated, indicating when to push start and when the SpO2 recording was complete. These were moved to the top of the screen and the current SpO2 and heart rate values were not displayed until the recording was started, to avoid users’ thinking they were already done. To avoid confusion, each new assessment started with a blank SpO2 screen instead of the previous values. For the summary interface, the risk factor scales were removed; instead risk factors were categorized into red, yellow, and green boxes and labeled as having high, medium, or low contribution to risk. A large “Calculate Risk Mortality” button was added at the bottom of the screen. This was in addition to the top right navigation button but was felt to be necessary to prevent users from stopping the app early with unattained risk scores.Based on this user feedback, the PARA app was modified and subsequently tested during Phase 2 for improved usability see . Instead2 dropped from 1 minute 32 seconds for the first patient scenario to 1 minute 4 seconds for the second patient scenario. Doctors again took the least amount of time to complete the app, averaging 3 minutes 56 seconds during the second patient scenario.For the first patient scenario, the average time-to-completion was 7 minutes 10 seconds. By the second patient scenario, the average time-to-completion dropped to 4 minutes 44 seconds. In particular, the average amount of time spent obtaining the SpOThe average number of errors dropped between the first and second patient scenario from 3.4 to 2.5 errors . The majThe average time to complete the PARA app was lower for Phase 2, following user feedback and modifications, than for Phase 1 of testing, decreasing by 30% . ParticiP<.05) when combining Phases 1 and 2. The adjustments made to the PARA app between Phases 1 and 2 decreased the number of errors and overall time-to-completion, particularly for those with less medical education.The average time-to-completion (during patient Scenario 2) for doctors/medical students was 4 minutes 38 seconds for Phase 1 and 3 minutes 56 seconds for Phase 2, as compared to nurses/clinical officers whose average was 7 minutes 54 seconds for Phase 1 and 5 minutes 26 seconds for Phase 2. The differences in completion times between doctors/medical students and nurses/clinical officers was statistically significant (P<.05). During Scenario 1, doctors/medical students averaged 2.3 errors while nurses/clinical officers averaged 5.2 errors. User errors bilaterally decreased with Scenario 2, with doctors/medical students averaging 1.6 errors and nurses/clinical officers averaging 3.9 errors. Nurses/clinical officers were more likely to make outcome errors (high severity) than doctors/medical students. They accounted for all of the errors leading to no risk score (n=4), and the majority of the errors leading to incomplete data entry (n=13).Overall, doctors/medical students had fewer user errors on patient scenarios than nurses/clinical officers (CSUQ results were very low (indicating positive opinions) with no substantial differences according to phase. On a scale from 1-7 (from “strongly agreed” to “strongly disagreed”), most responses were 1, with an average score of 2.07 on all questions. Overall, people found the app easy to use and understand. All participants (n=30) strongly agreed to the statements “I liked using this app,” “The organization of information on the app screen is clear,” and “I would use this interface if it were available at my health facility.”When asked about the positive aspects of the PARA app, participants generally commented on simplicity and utility. One participant summarized, “The app is advanced, but the interface is easy to understand.” Most reported that the app was easy to learn how to use, though some, particularly those with less medical education, requested more training. Participants felt the error messages helped guide them through the app, and many felt the PARA app was quick, as it automatically calculated the risk score preventing added burden on the health care worker. One provider said, “But the most important thing is it’s really very fast and saves time—so you are not wasting the patient’s time or your own time. That’s the most important thing, it’s really very fast.”Participants suggested several means by which the PARA app could improve patient care both in-hospital and after discharge. For children at high risk of in-hospital mortality, health care workers thought these patients would need more attention on the ward, through more frequent assessment or prioritized medication during shortages. One participant explains, “So if they are on the ward, still I can know this is a high-risk child and take extra caution in caring for this child.”For children at high risk following discharge, participating health care workers suggested clinical and educational interventions to curb mortality . Many reThough rated highly on the CSUQ, the purpose and practical application of the PARA app was sometimes unclear. The purpose of this clinical tool is to provide early indication of heightened risk of pediatric mortality. Some participants mistook the PARA app as electronic medical records, while others assumed the PARA app could be used to continually assess a patient’s progress through treatment or to make discharge decisions. These misinterpretations were summarized by one participant’s comment:The app helps a lot because it tries to make for you a decision. It decides for you whether to discharge or not to discharge...If the patient is at high risk while at the hospital, it gives you the opportunity to discharge the patient early before the risk comes in. So I feel it can help you make a rightful decision.Development of a mobile app to be utilized in a low-resource, cross-cultural setting requires iterative testing and adaptation to produce an intuitive design. Through feedback and modifications made during this usability study, the PARA app was developed into a user-friendly design, encompassing user expectations and culturally intuitive interfaces for users with a range of technological exposure. Time-to-completion and number of user errors decreased between Phases 1 and 2 of testing, following modifications made to PARA app interfaces. Overall, participants consistently reported the ability to learn and utilize the PARA app quickly and easily. The majority of errors, particularly the navigation errors, were due to unfamiliarity with apps and touch screen devices for those with limited experience.Based on time-to-completion measurements, doctors and medical students were identified as the ideal end-users, or at least the most likely early adopters. With fairly little guidance, doctors and medical students had an intuitive grasp of the app’s purpose and functionalities. On average, nurses and clinical officers had less previous exposure to touch screen technology and therefore experienced more difficulty with the PARA app. However, all participants found the PARA app to be a useful clinical tool, agreeing they would use it if available at their health facility. The impact on workflow in a clinical environment could not be assessed in our standardized testing environment. Future research will be conducted in clinical environments utilizing actual end-users.However, education gaps were identified during the study, which would impact future implementation and training. Some participants overestimated the scope and purpose of the PARA app, leading them to mistake the app for an electronic records system or continual assessment tool. As the PARA app is scaled in clinical settings, consideration should be given to the best way to train and educate clinicians on appropriate functionalities. The addition of a training video upon installation of the PARA app may curb misunderstanding during scale-up. Other studies have found that stakeholder collaboration, governmental support, and local adaptation are important factors to successful implementation of mHealth programs .Given a high PARA risk score, participants suggested several interventions that would be appropriate for the sociocultural context in southwestern Uganda. Most suggestions centered on strengthening discharge and referral procedures within the current health care system. Participants felt that educational interventions on discharge or convenient and consistent follow-up after discharge could improve mortality outcomes for children with high PARA scores . Though these interventions have been studied in other contexts, little evidence exists on their effectiveness at diminishing postdischarge mortality, and more research regarding effective strategies to decrease postdischarge mortality are urgently required ,19.As this was an initial evaluation of a novel app, this usability study was not conducted in a clinical context, but instead with purposively sampled potential end-users in an artificial environment. Therefore, findings may not be generalizable to a clinical context. However, efforts were made to encompass a variety of target users, in order to understand the utility of the app from a variety of professional perspectives and technological skill levels. Further, our clinical scenarios were carefully developed to ensure a balanced and representative evaluation from both a clinical and usability/design perspective.In addition, given varied exposure to technology, there was some degree of novelty and expectancy effects. To address these concerns, clear instructions were given to each participant on how to use a touch screen, as well as reinforcement that the only expected outcome from the study was improvement of the app. The patient scenario instructions were adjusted between Phases 1 and 2 to account for modifications made to the app. However, patient scenarios and sequence of tasks remained standardized between phases, so comparable testing conditions were preserved.Postdischarge mortality is a neglected but significant cause of child mortality in resource-constrained settings. The PARA app can begin to address this burden through its ability to quickly identify children at highest risk of death during the postdischarge period. Our research team in Uganda is currently conducting a feasibility study of a comprehensive postdischarge intervention (discharge kits) to distribute to vulnerable children at discharge. Over the next 24-36 months, our research team in Uganda will begin to integrate the PARA app with discharge kits to evaluate their effect on health seeking, hospital re-admissions, and mortality during the postdischarge period.