Solenopsis invicta Buren (Hymenoptera: Formicidae) show modest changes of shape with increases in body size. These shape changes  have been described only for workers taken from mature colonies of the monogyne social form. For the study reported here, workers were collected from small and large monogyne and large polygyne colonies for tests of the effects of colony size and social form on allometry. The differential growth of body parts in relation to total body growth was determined by measurement of all major body parts and regression of the logs of these measurements, or their ratios, on the log of the body size. The slopes of these regressions defined the allometric relationships, and the slopes for these three types of colonies were compared for determination of the influence of colony size and social form on allometric rules. Most allometric constants did not differ with colony size or social form, but head shape, relative antennal size, and alinotum shape did. For a given worker size, heads of workers from small monogyne colonies or from polygyne colonies were narrower above the eyes. Antennae of workers from large monogyne colonies were relatively shorter than those from small monogyne or polygyne colonies (which did not differ). Alinotum heights of small workers from small monogyne colonies were greater than those from large monogyne or polygyne colonies (which were isometric and did not differ). These observed differences in allometric constants suggest that the relative growth rules are not completely determined by worker body size but are affected by colony size and social form. These differences are discussed in light of the growth of imaginai discs under conditions of fixed resources.Workers of the polymorphic fire ant  Solenopsis invicta Buren (Hymenoptera: Formicidae) is a widespread polymorphic species adapted for inhabiting disturbed areas . Because application of RMA did not change any conclusions about differences among colony types, OLS is the basis of this report. A comparison of the parameters for OLS and RMA is presented in Appendix 4 (appendices available online).The 25 measurements of each ant were compiled, log-transformed, and subjected to ordinary least squares (OLS) linear regressions with STATISTICA 6.0. At the urging of a reviewer, reduced major axis regression (RMA) was performed on the log-transformed data with a program by A. J. Bohonak and K. van der Linde . Slopes greater than 1.0 indicated positive allometry, and slopes less than 1.0 negative allometry. For easier comparison, we regressed the ratio of body parts on total body length. When the shape  changes with body size, such regressions of ratios have slopes significantly different from zero. The slopes of significant regressions of different colony types were compared by means of the standard error of the slope estimate and Allometric constants for large monogyne colonies were first tested against those of Tschinkel et al.  to deterNext, nonisometric relationships were tested for differences of slopes between the colony types, that is, whether, even if a body part grew at a rate different from that of the whole body in all three colony types, types did so at significantly different rates.The differences between our allometric constants for large monogyne colonies and those of Tschinkel et al.  were fewand in which at least two of the three colony types differed significantly in growth rates (slopes). The parameters for all regressions within colony types are shown in Appendices 1–3. The polymorphism in polygyne colonies is shown in The following sections describe only major body parts that were allometric Workers of the same body length did not have the same shapes in the three colony types, differing primarily in the shape of the head, the antennal length, and the shape of the alinotum. The ratio of head width above the eyes (HW2) to body length (BL) was used to estimate changes in head shape [head length (HL) was not considered further here because it is isometric to body length and therefore mathematically redundant with it  is an index of the “robustness” of the alinotum shape. Higher values of the AH-to-BL ratio indicate an alinotum that is deeper relative to its own length or the body length (which are isometric to one another). AH was isometric to BL in both large monogyne and polygyne colonies . Interest-test: -7.03; p < 0.00001).Plotting the ANT-to-BL ratio against the HW2-to-BL ratio  showed tComparing the intercepts indicated that the ANT-to-BL ratio was about 10–12% greater for workers from small monogyne colonies than for workers of any HW2-to-BL ratio from large monogyne colonies, and the ratios of workers from polygyne colonies were about 10% greater than those from small monogyne colonies. The ratios for all three colony types were in a constant ratio to each other across the entire range of HW2-to-BL ratio, suggesting processes that affect both antennal length and head width in a tightly linked fashion and a fixed difference due to colony type. Most probably, these processes are related to the competitive growth of the respective imaginai discs in the head. The ratios of these head measurements to body length were independent of the ratios of alinotum height to body length, possibly because of the greater distance between them.In relation to worker size, the proportions of worker heads, antennae, and alinota changed at different rates in large monogyne, small monogyne, and polygyne colonies. The differences were not large, and the question remains whether they are functionally important, but they do suggest that changes in worker shape during growth do not derive only from factors intrinsic to the workers themselves but are influenced by colony level factors. Workers from large monogyne colonies started with lower HW2-to-BL ratios than those from the other colony types but increased more rapidly through a greater range of HW2-to-BL ratios than the others. In other words, their heads started out more barrel-shaped and became heart-shaped more rapidly than those of the other two colony types. Similarly, the antennae of workers from large monogyne colonies become relatively shorter more rapidly than the other colony types as worker size increases. The fact that relative antennal length follows the opposite pattern to HW2 suggests that the imaginai discs for these two dimensions compete for resources, and that investment in the growth of one of them reduces growth in the other.Gp-9,S. invicta.The allometric differences are probably best described as environmental static allometries, as defined by Shingleton et al.  because The greater similarity of worker allometry between polygyne and small monogyne colonies than with that of large monogyne ones is probably significant. The factor that links the first two and differentiates them from the last is probably colony nutrition, with its echo in individual worker nutrition. Within the life cycle of monogyne colonies, the rate of brood production per worker decreases as colonies grow, so the ratio of workers to brood increases and each larva potentially receives more food and care . This grOur data accord with the predictions of the imaginai disk—interaction growth model proposed by Nijhout and Wheeler , in whicIn light of the imaginal-disk-competition hypothesis, the proximity of imaginai discs may explain why the allometries within the head (antennae and head width 2) remain in constant relationship to each other within each colony type  while thAlinotum shape is isometric to worker size in polygyne and large monogyne colonies but not in small monogyne colonies. In these last, the greater robustness of the alinotum in small workers and its lesser robustness in large workers is odd, as it is opposite to the usual trend. Perhaps this is, after all, an interaction with the imaginai discs in the head. Whether it has functional importance is unknown.


How thoroughly can 1 book address 2 complex aspects of the host-agent-environment triad, especially for a topic as broad as respiratory tract infections? Every author of an infectious disease topic assumes this task, at least implicitly. For example, the clinical aspects of adenovirus infection are hard to discuss without also highlighting the host factors that lead to greater susceptibility. The value of a book dedicated to the host-pathogen interaction depends on the book's ability to focus explicitly and narrowly on this relationship as the main topic.Mycoplasma pneumoniae and the subsequent development of asthma.Common to all 13 chapters of this first edition is the subject matter expertise of the authors. In addition to their thorough treatment of each subject, extensive referencing shows clearly the authors' command of current and past literature . Beyond these common features, different chapters address particular facets of the host-agent relationship. Several chapters treat the host itself as the key subject, for example, the chapter on genetic background. Others place greater emphasis on the features of the microbes themselves, such as their pathogenicity and mechanisms for evading the host immune system. Still other chapters dissect and analyze every aspect of the complex relationship between host and agent, successfully making this interaction the central topic. The chapter on the pathogenesis of bacterial respiratory tract infections is a particularly strong example. Finally, some chapters look at the host-microbe interface over a period longer than the time of acute infection. For example, the chapter on atypical bacteria summarizes the evidence for a causal relationship between infection with If the authors' expertise is the primary strength of the book, the lack of organization and focus is its principal weakness. Most infectious disease textbooks adopt a pyramidal structure, beginning with foundational concepts, such as clinical syndromes, followed by specifics, such as the clinical presentation and treatment of individual pathogens. No such analogous structure is apparent in this book. Although the book begins with a discussion of genetics and the hygiene hypothesis, it quickly digresses into issues less relevant to the main point of the book, such as new diagnostic tests. A clear structure would also help ensure that all major topics are included. For example, many respiratory tract infections have a bimodal age distribution with the greatest incidence in the very young and the very old. However, this book largely omits any discussion of host-microbe interactions among the elderly. Similarly absent is a description of how pandemic influenza viruses emerge and evade the host immune system. Simply put, structure would unify what could otherwise be considered a series of well-done monographs.Most readers who want to understand the host-agent interplay in respiratory infections might find that a general infectious disease text meets their needs. However, others who need more depth in selected topics should search the table of contents before adding this book to their library.


Multi attribute utility (MAU) instruments are used to include the health related quality of life (HRQoL) in economic evaluations of health programs. Comparative studies suggest different MAU instruments measure related but different constructs. The objective of this paper is to describe the methods employed to achieve content validity in the descriptive system of the Assessment of Quality of Life (AQoL)-6D, MAU instrument.The AQoL program introduced the use of psychometric methods in the construction of health related MAU instruments. To develop the AQoL-6D we selected 112 items from previous research, focus groups and expert judgment and administered them to 316 members of the public and 302 hospital patients. The search for content validity across a broad spectrum of health states required both formative and reflective modelling. We employed Exploratory Factor Analysis and Structural Equation Modelling (SEM) to meet these dual requirements.The resulting instrument employs 20 items in a multi-tier descriptive system. Latent dimension variables achieve sensitive descriptions of 6 dimensions which, in turn, combine to form a single latent QoL variable. Diagnostic statistics from the SEM analysis are exceptionally good and confirm the hypothesised structure of the model.The AQoL-6D descriptive system has good psychometric properties. They imply that the instrument has achieved construct validity and provides a sensitive description of HRQoL. This means that it may be used with confidence for measuring health related quality of life and that it is a suitable basis for modelling utilities for inclusion in the economic evaluation of health programs. Health related Multi-Attribute Utility (MAU) instruments seek to measure the quality of life (QoL) of individuals in a way which allows its inclusion in economic evaluation studies and, in particular, Cost Utility Analyses (CUA). While their defining characteristic is the creation of an index of utility (or strength of preference) they may also be used, like non-utility generic instruments such as the SF-36, to measure health related quality of life (HRQoL) or to provide health profiles. Construction of an MAU instrument involves two tasks: creating a descriptive system - a set of questions whose answers describe a person's health state - and devising a scoring formula, which combines and reduces the answers to a single number which seeks to measure utility. The present paper is concerned with the first of these tasks. The methods used for deriving the scoring formula for the AQoL-6D are described in another paper .To date a small number of MAU instruments have dominated the field. These include the EQ-5D, SF-6D, Health Utilities Index HUI 1, 2, 3), the 15D, the QWB and the AQoL-4D. Descriptions and comparison of these are given elsewhere , 3, the . Despiteprima facie, to lack sensitivity. A review of the literature suggested that these included health states which are sensitive to the social context ('handicap' i.e. activity/participation) . ThThe AQoL-4D item bank included items obtained from a review of published health related instruments, from focus groups and from expert analyses . The AQoThe construction survey provided a set of completed items for statistical analysis to determine the final content and structure of the AQoL-6D. Four main criteria determined item selection: (i) that items should be structurally similar (item stem and response levels) to AQoL-4D items to allow for comparison of results; (ii) that content should be similar to the AQoL-4D as the purpose was an improved instrument covering broadly, the same dimensions of health related QoL; (iii) that items should improve sensitivity; and (iv) that there should be multiple items describing in different ways each of the hypothesised elements shown to be important by the empirical results to this point. Each item included a rating scale to indicate item importance for a person's QoL.We administered the survey to selected members of the adult population aged 18 and above and to hospital patients in Victoria, Australia. Patient groups were included to increase the likelihood that responses would include the more severe health states described by the items.The population sample was selected in two stages. In the first, telephone addresses were selected from a computerised directory stratified by postcode, population of postcode and the social economic status of the postcode. A random start sampling interval (RSSI) procedure was used in the case of postcodes with populations that were too small to otherwise warrant inclusion in the sample. In the second stage an introductory letter was followed by a telephone call, a mailed questionnaire and up to two reminder letters or phone calls.Inpatients were selected from four wards of a major Melbourne teaching hospital. Inpatients and outpatients were initially approached by clinical staff with an explanatory statement and consent form. Interviews were conducted by members of the research team.The questionnaire was separated into 8 sequences to offset question order effects. Data from the completed questionnaires were double entered and inconsistencies checked and re-entered.Items were discarded if they had insufficient variance to detect change, if they were expected to discriminate between hospital and population respondents but failed to do so, or if the response level selected constantly conflicted with the importance rating on the accompanying rating scale. Other items were excluded during the subsequent analysis.Because data from the items was ordinal, the search for instrument structure employed polychoric correlations. Structural equation modelling (SEM) was conducted in two broad stages using the LISREL statistical package. Initially, analysis was conducted dimension by dimension. For example, all items associated with 'social relations' were examined, then items relating to 'independent living' and so forth. Items were excluded which significantly cross-loaded between dimensions. Secondly, the internal structure of each dimension was examined. The objective was to select a small number of items (3-4) which retained a strong substantive coverage of all of the relevant items from the construction survey.More specifically, the modelling of dimensions was carried out in four steps. The first step was the construction of a model which included all of the items initially included in the construction survey to measure a construct (dimension). Secondly modification indices provided by LISREL were examined to determine additional items. These were added to the model when they improved the fit. Paths were identified by the existence of a correlation between items after taking account of the underlying latent characteristic.Thirdly, the correlated errors in the resulting model were used to further search for structure among the items, and particularly for "subsets" of variables that could be shown to be measuring the same specific aspects of the dimension . Variables were excluded at this stage  to determine Raykov's composite scale reliability, within each dimension. This assisted in further identifying redundant items and, together with the distributional characteristics of responses and the level of missing data, guided the selection of the final set of items. Raykov's composite scale reliability overcomes shortcomings in Cronbach's Alpha which underestimates the coefficient when items are not Tau equivalent, that is to say, when they are differentially related to the underlying construct .The process was iterative and eventually identified items that formed a robust but parsimonious scale within each dimension. These were then combined into an overall model and tested to ensure that each dimension loaded onto a single latent variable, i.e. health related quality of life.Missing data were dealt with using the Expectation Maximisation (EM) process of the SPSS missing values procedure. This is a form of SEM, which utilises a process similar to estimation by regression, but using latent variables constructed from those items for which responses are available. Variables must be specified for the analysis on a priori grounds such as the substantive context of the items. In effect, the technique allows for errors on the predictor, as well as on the predicted variables. Day et al.  provide We conducted four focus groups and combined results with those obtained during the construction of the AQoL-4D. Two groups included health professionals and two employed members of the public. In total, 22 individuals participated in the new groups. All groups identified intrinsic and mediating factors as important for HRQoL, i.e. factors describing the self, and factors facilitating the achievement of HRQoL. We added the former group to the item bank.The two focus groups which included health professionals sought to identify elements which would be of increasing importance for future HRQoL. Some anticipated the increased importance of less material elements in health, for example spi rituality and sexual fulfillment, while others believed that there would be a movement away from individual level objectives towards the achievement of collective goals. These results led to the addition of new items in the item bank.Item analysis and triage resulted in the inclusion of 112 items in the questionnaire, a ratio of approximately 5:1 with the targeted instrument size of 15-25 items.Three hundred and sixteen 316) members of the general public completed and returned the construction questionnaire, a response rate of 31 percent of the sample initially targeted, 44 percent of the in-scope respondents and 78 percent of those sent a questionnaire. None of the 206 outpatients and 96 inpatients approached by interviewers refused to participate. Table 16 memberTable Figure The six dimensions all load on the one HRQoL factor, while the results of the SEM indicate that they are measuring different aspects of HRQoL. This suggests that the items form a uni-dimensional, parsimonious scale. Where data deviate substantially from normality Yu  recommenThis paper described the methods used to achieve content validity in the AQoL-6D and, particularly, to increase instrument sensitivity as compared with its predecessor the AQoL-4D. To achieve this we employed psychometric methods. We constructed an item bank using the results of earlier studies supplemented by the results from additional focus groups. After initial triage, patients and members of the public were asked to complete the items - the 'construction survey'. Analysis of the 618 sets of completed items employed polychoric correlations and structural equation modeling to optimise the number of items in each of the postulated dimensions while simultaneously determining the configuration of dimensions which best represented the postulated concept of HRQoL.causes high achievement.) With formative models causation is reversed [inter alia, define SES.This latter task encounters a particular challenge which arises from the distinction between formative and reflective modelling. In the latter, causation runs from the latent (unobserved) variable to the items.  are generally high, the loading on question 18 is only 0.58. This suggests that vision is less closely related to HRQoL than most other items in the model. This is readily interpretable: people can suffer poor vision without it being related to other deficiencies in HRQoL. However, to exclude vision from a generic instrument would violate the usual understandings of HRQoL, and, consequently, it is included in the model. Despite the low loading it does not compromise the overall fit of the model.13 health states. This does not guarantee content validity, but the methods employed increase the likelihood that this has been achieved. The prima facie evidence for this is presented in Table Successful application of these methods resulted in a relatively large instrument. Its 20 items define 5.4 × 10The differences are the result of two decisions made during construction of each instrument. The first is the conceptual basis of the instrument. As described earlier, AQoL instruments sought to model 'handicap' (activity/participation). In contrast, the 15D and HUI 3 focused upon body function and structures (a 'within the skin' framework). Their items, including those noted above  are important but in a handicapped based instrument these items are, in principle, reflected in the consequences of body impairment for handicap.The second decision is the extent of the trade-off between sensitivity and parsimony. All instruments necessarily limit the number of items and some elements of a health state are necessarily under-represented. In principle, the choice of items should be made on the basis of the psychometric evidence relating to the goodness of fit of the alternative combinations of items. This has been the subject matter of the present article. The success of the modelling, as compared with the alternative models must be determined by comparative studies.The existence of multiple instruments, including multiple AQoL instruments, raises three questions. The first is why more than one 'generic' instrument is necessary. From the evidence of comparative studies cited in the introduction MAU instruments (and not just AQoL instruments) produce different scores. One of two conclusions must therefore be drawn: either different instruments have a differing capacity for detecting utility in different contexts or, all of the instruments with one exception, create scores which do not correspond with utility. To date this latter possibility remains unproven and the evidence supports the former conclusion. From its construction and the evidence in Table The strength of the AQoL instruments relative to other MAU instruments to date is that they have been derived using psychometric procedures, which increases the evidence for reliability and validity in the dimensions of health covered by the instruments. This does not, however, guarantee the universal superiority of the instruments. Context specific strengths and weaknesses of instruments require independent empirical research and a recent review of this literature indicates that this comparative research has not been carried out satisfactorily for the other major instruments . The eviThe second question is how scores from different instruments might be compared. One approach to the question is to side-step the problem by only using a single instrument. However the result would be analogous to the use of a single diagnostic test, for example, blood pressure, to compare the severity of all diseases. Comparisons would not be valid without the demonstration of a universal 'best' generic instrument. Part of the final answer is likely to include the creation of statistical transformations between instrument scores as has been done between the AQoL instruments . HoweverThis raises the third question of which MAU instrument should be used. As suggested above there is, at present, no general answer implying that researchers must judge which instrument is most likely to detect program specific changes in the quality of life. Economic evaluation of health programs, in particular, requires the inclusion of all utility-relevant information in the description of health states and the omission of this will compromise the validity of the measurement. The AQoL-6D was a response to evidence that the sensitivity of existing instruments is imperfect. The extent to which the resulting instrument meets this need is a matter for further research.We created the AQoL-6D as the descriptive system for an MAU instrument. While the utility algorithm is available on the AQoL website  the instprima facie, detect the changes in health states which the researcher expects to observe. The breadth of the AQoL-6D implies that it should rate highly on this criterion. The evidence presented in this paper should also increase confidence in the validity and reliability of the instrument.The comparative strengths of existing MAU instruments have not been satisfactorily documented. This implies that individual researchers must choose between them. The primary criterion is that an instrument can, Despite this conclusion, the AQoL-6D is a relatively new instrument and further research is needed to establish its validity in specific contexts. In particular, it would be desirable to use the instrument in tandem with a disease specific instrument and, preferably, with another generic QoL instrument. This maximises confidence in particular results and assists with the process of validating the AQoL-6D in that context.The authors declare that they have no competing interests.JR, Original conceptual design; primary responsibility writing the paper. SP, Assistance with interpretation of data. GH, Conceptual input; interpretation of data. AI, Project management; data collection. GE, Interpretation of data; assistance with analysis. ND, Conceptual input; statistical analysis. All authors read and approved the final manuscript.Appendix 1 AQoL-6D Questionnaire.Click here for file


The only way we can interact with the world is through movement, and our hands are our primary mode of interaction with objects and other individuals. Understanding the neural computations underlying hand motor control in real-life situations are critical, both for the development of dexterous neuroprosthetic hands, as well as studying a defining element of human nature. Here, we take the view that motor behaviour can be understood by identifying a simplicity, which may reflect upon the underlying mechanism. Yet, the analysis of movements, and specifically hand movements is complicated by the highly variable nature of behaviour . HoweverWe therefore asked 7 subjects between 20-30 years of age, to interact in 17 daily-life situations with defined objects , each actions was repeated ten times. We collected object manipulation data using a calibrated CyberGlove I data glove ) that recorded the angles of the joints of each digit and the abduction angles between digits, 15 angles in total sampled at 80 Hz . PPCA rems of hand configurations  was sufficient to characterize the entire hand task. This supports the view that motor cortex organises behaviour in a low-dimensional manner to avoid the curse of dimensionality in terms of computational complexity. This predictability could be exploited to build smart, context-sensitive neuroprosthetics controllers that infer the task “at hand” based on the movements of remaining fingers or the activity of finger muscles in the arm stump.Importantly, the low-dimensional subspaces appeared numerically distinct from each other for individual actions. This suggest the hypothesis, that specific tasks may engage specific sets of motor controllers, which orchestrated actions result in the overall behavior and produce movement variability in characteristic sub-spaces. If this is the case, then we should be able to infer the task the hand is engaged in by observing some initial portion of the finger movement data. To this end we exploit that PPCA yields us for a given set of hand configurations the likelihood that it was generated by each task. We simply predict task based on the task with the highest PPCA likelihood. Note, that PPCA ignores the temporal structure of movements  – thus correct classification relies on the sub-space of finger movement variability alone. For each of the seventeen activities parameters that characterize its distribution were determined. Half of the data were used to find the PPCA parameters, while the other half was used for testing. Using only the first 4 PPCA components in the process of classification the success of classification was 83.53% . Crucially, the classification performance was about 7 times higher then chance performance for only the first 0.06% of hand configuration samples for each task. Thus, observing the first approx. 200


In Germany, a multidisciplinary rehabilitation named “behavioural medical rehabilitation” (BMR) is available for treatment of chronic low back pain (clbp). A central component of BMR is standard exercise therapy (SET), which is directed mainly to improve physical fitness. There is a need to address psychosocial factors within SET and therefore to improve behavior change with a focus on the development of self-management skills in dealing with clbp. Furthermore, short-term effectiveness of BMR with a SET has been proven, but the impact of a behavioural exercise therapy (BET) for improvement of the long-term effectiveness of BMR is unclear.To compare the effectiveness of two exercise programs with different approaches within BMR on the effects of BMR a prospective randomized controlled trial (RCT) in two rehabilitation centres will be performed. 214 patients aged 18–65 with clbp will be, based on an "urn randomisation"-algorithm, randomly assigned to a BMR with SET  and BMR with BET . Both exercise programs have a mean duration of 26 hours in three weeks and are delivered by a limited number of not-blinded study therapists in closed groups with six to twelve patients who will be masked regarding study group. The main differences of BET lie in its detailed manualised program with a theory-based, goal-orientated combination of exercise, education and behavioural elements, active participation of patients and consideration of their individual preferences and previous experiences with exercise. The primary outcome is functional ability assessed with the Hannover Functional Ability Questionnaire directly before and after the rehabilitation program, as well as a six and twelve-month follow-up.This RCT is designed to explore the effects of BET on the effectiveness of a BMR compared to a BMR with SET in the management of patients with clbp. Methodological challenges arise from conducting a RCT within routine health care as well as from ensuring high treatment integrity. Findings of this study might contribute to a better understanding of the mechanism of action of BMR and the special effects of BET and may be used to improve the quality of these interventions in routine care, therefore reducing the burden to patients with disabling clbp.NCT01666639Current controlled trials  Non-specific low back pain is one of the leading health problems regarding its medical and economic impact worldwide -4. This While the lifetime prevalence of low back pain is reported to be up to 84%, little scientific evidence is available for the prevalence of disabling chronic low back pain . In a muIntensive multidisciplinary rehabilitation is recommended as first-line treatment for the management of disabling clbp ,7,9. It A corner-stone is SET, which represents approximately 70% of all interventions within multidisciplinary rehabilitation, received by orthopedic patients in Germany . SET is There is also evidence available confirming that psychosocial factors play a pivotal role in the development of clbp -21. AddrAn enhancement of long-term adherence to physical activity in chronically ill adults via patient-oriented methods directed at motivation and volition (e.g. planning) has been effective ,31,32. CThere has not been in-depth research about the biopsychosocial effects of theory-based exercise therapy with a behavioural approach, named behavioural exercise therapy (BET), as part of the BMR in the management of disabling clbp. So the impact of a BET for improvement of the effectiveness of BMR is unclear.Therefore the aims of this study are a) the development and implementation of a BET into an existing BMR and b) the evaluation of the effectiveness of BMR with BET compared to BMR with SET in routine health care  in the management of patients with disabling clbp.To evaluate the effects of BET on the effectiveness of a BMR, a multicentre-study with a prospective randomised controlled design is conducted. This study takes place in two inpatient rehabilitation centres in Germany. Participants with clbp will be randomised into either a) the usual BMR with the SET as the control group (CG) or b) the BMR with the extended BET as the intervention group (IG) , patient enrollment takes place in the participating rehabilitation centres based on the assessment of the inclusion and exclusion criteria by the attending physician. Next, patients are randomly assigned to the different treatment groups.The recruitment procedure is adjusted to each of the centre’s internal structures and processes regarding the invitation of patients.In the rehabilitation centre “Paracelsus-Klinik an der Gande” potential study participants will be identified by a screening of the patient record by the head physician prior to the invitation to the BMR. Afterwards, eligible patients will obtain written patient information and a consent form about the study and will be asked to participate. After returning the signed consent form within seven days, the patients will be randomised online. The invitation of the randomised patients will take place weekly and in groups according to the group assignment in the respective week of arrival. At the beginning of the rehabilitation program, an information meeting will be held by the head physician for all eligible patients fully explaining the study.In the rehabilitation centre “Klinik Weser” potential study participants will be identified at the beginning of the BMR in medical admission interviews and will obtain a written consent form. In an information meeting all eligible patients are fully informed about the study primarily by the head physician. On the second day, after returning the signed consent form, the online-based randomisation will take place. Due to spatial and personnel-wise requirements, one control and one intervention group will start simultaneously every fourteen days. Therefore, the recruitment of eligible patients will take place in a biweekly rhythm.In both rehabilitation centres, the group size is limited to twelve participants. If the number of eligible study patients is too small for starting a control or intervention group, the participation of non-eligible patients who do not take part in the study is accepted to reach the necessary group size. At least 40 potentially eligible patients will be treated every month in both rehabilitation centres. Considering a recruitment rate of 60%, 358 eligible patients will have to be asked to participate in the study in order to achieve the required sample size. Based on the assumption that average closed groups consist of six to seven participants, the recruitment period is predefined as a period of twelve months. Both rehabilitation centres confirmed that a sufficient number of eligible patients would exist to achieve the necessary sample size in the study period.The collection of consent forms, distribution and collection of questionnaires and the delivery of the latter to the study team are adjusted to the process of patient admission and discharge in standardised form. The process will be tested and automated in each of the rehabilitation centres during the phase of implementation.The follow-up questionnaires will be sent to the former participants six and twelve months after the rehabilitation treatment by the university. Postal reminders will be send after three weeks if the questionnaire has not been sent back by patients.Dropouts are defined as patients who do refuse to participate in the study at the end of the rehabilitation program. These patients will not be contacted after six and twelve months for further evaluation.Also, dropouts are patients who withdraw the entire study participation and prohibit the use of existing personnel data. In this case, the questionnaire filled out at the beginning of the rehabilitation program must be given to the patient.If patients don’t fill out the questionnaire at the end of the rehabilitation (despite former reminder), they will still receive a questionnaire after six and twelve months, if they don’t explicitly refuse or withdrew from the study participation.The registration of all eligible patients and the reporting of the number and the sex of eligible patients who do not participate  during the time of the study will take place for the identification of selection effects during the recruitment process.The randomisation procedure of the participants takes place with an online-based randomisation feature. Therefore, we implement a central data base for electronic data recording which will be used in each of the two rehabilitation centres. An independent administration employee, who is not involved in the study, will use the online-based randomization feature within each rehabilitation centre to register eligible participants via a web application. After registration, the online-based randomisation feature automatically accomplishes the allocation to one of the treatment groups.This system has been developed in a prior study  and incoThe randomisation process of patients will be planned together with the staff of the participating rehabilitation centres, especially the medical directors, administration staff, system administrator and those responsible for therapy planning in the rehabilitation centres during the phase of preparation and implementation. For the planning of the randomisation process, the implementation of the data base and the training of administration staff to handle the data base, the rehabilitation centres will be visit two to three times.Thinking of the short-term effectiveness of both interventions, only small differences between groups and small effect sizes at the end of rehabilitation (t2) =0,15) are expected to be found ,41,42. BBoth of the participating rehabilitation centres have a conceptually similar BMR for patients with orthopedic functional impairment and concurrent substantial psychological or social component of this impairment. The behavioural medical concept takes into account the biopsychosocial mechanisms relevant for the chronification of musculoskeletal disorders ,45. EmpoParticipants in the intervention arm will also receive a BMR, but with a specific behaviour-oriented exercise therapy (BET), which replaces SET. BET has been developed on the basis of previous work . In geneThe major part of BET consists of fifteen sessions with duration of 60 minutes each. Every single session comprises an introduction (approx. 5min), structured active play (approx. 5min), short education periods on selected topics (approx. 10min), exercises and relaxation (approx. 30min) as well as conclusion and sporadically a metaphoric story (approx. 10min). The entire thematic topic overview of the fifteen sessions can be seen in the in the Additional files  and two 30 min. introductions in aqua training . Further three modules of planning out of every 60 minutes duration are distributed over three weeks. The purpose of these related modules is for patients to become familiar with different types of exercises in the first week supervised by a BET-therapist followed by a more self-directed planning and performing of exercises during the rehabilitation stay. Therefore during the four weeks of treatment the supervision by the therapist decreases, while the performing of self-directed exercises increases. At the end of the second week, the BET-therapist will reflect together with the group reviewing, how well the individual realisation of planned exercises itself is managed. If barriers occur, they will be discussed and alternative possibilities will be developed. To be available for consult in case of any questions especially related to weight-lifting training, additional three appointments will be scheduled (one each in the 2nd to 4th week of therapy) under supervision of a BET therapist. Table In summary, the following key features characterized BET:– Patient-centred approach through active participation of patients in the entire treatment process and considering their individual preferences and previous experiences with exercise– Goal-oriented combination of exercise, education, and behavioural elements within the BET– Psychosocial factors that contribute to the chronification of clbp  are systematically modified by the use of structured contents and methods which refer to exercise, education and behavioural elements– Theory-based use of behavioural techniques to influence motivational and volitional determinants of health behavior change to promote long-term maintenance of self-directed physical activity– Specific patient-oriented, plain media and materials with a very demanding character are used– Trainer manual with a detailed description of the BET program for a standardized execution of the exercise, educational and behavioural elements, as well as a standardized use of media and materials to achieve multidimensional objectives of the BET is available– Objectives, contents and methods of BET are matched in terms of a consistent approach and cooperation of all professions involved in the BMR– Key messages and competencies trained by medical and psychological professions in the BMR will be reflected and reinforced within the BET.More information can be found in the Additional files  at intervals of eight weeks will take place together with all BET-therapists from both rehabilitation centres. The workshops are provided on the basis of a manualised intervention concept and are delivered by the same trainers. Moreover, pilot groups with the BET program will be performed within the implementation phase. The BET-therapists are skilled in the use of the program and try out the approach with the specific goal-orientated components as well as the media and materials.The intensive training of BET-therapists and the implementation of the BET-groups will be supervised and evaluated. For data collection, quantitative methods are used (self-constructed questionnaires). The acceptance of the therapists  and difficulties during the implementation as well as acceptance of the patients (program satisfaction) will be recorded.Both exercise programs (SET and BET) within the BMR have the same duration. The duration of both exercise programs as well as additional interventions within the BMR are documented for each study patient during the intervention phase.A potential source of bias in the execution of RCT in the inpatient rehabilitation is the potential mixture between the study group and the control group through a communication about intervention contents between patients as well as therapists within each rehabilitation centre. The adaptations in the BET aimed at the integration of behavioural techniques and a modified use of teaching approaches. A reflected effective exchange of the adapted intervention contents requires extensive knowledge of the underlying theoretical models of the chronification of lbp. This is generally not expected from patients of a BMR. In addition, the patients of both study groups will be informed that both exercise programs within in the BMR are of high quality and will be delivered based on actual scientific evidence.Trained BET-therapists will sign a written contract concerning discretion about objectives, contents, structure, methods, media and materials used within the BET. Regularly, announced visitations during the intervention phase will occur in order to assure adherence to the treatment protocol. Individual deviations from the treatment protocol will be recorded. In the case of vacation or sick leave, a trained BET-therapist for replacement is available.Standardised questionnaires will be used to measure the primary and secondary outcomes. Our choice of outcome measures is based on two previous trials of our working group to evaluate effectiveness of different interventions in the management of clbp ,46. TheyWe will use the level of functional limitations associated to clbp twelve months after the end of BMR measured by the Hannover Functional Ability Questionnaire (FFbH-R) as our primary outcome . The FFbSecondary outcome measures refer to demographics and related characteristics, pain, physical activity, health-related quality of life, depression, anxiety, stress, pain-related cognitions, emotions and behavior, motivational and volitional determinants of physical activity, attitudes towards performing physical activity, satisfaction with exercise therapy and satisfaction with the rehabilitation process . InformIn the management of disabling clbp intensive multidisciplinary rehabilitation is recommended. But, the reported effects especially in the long-term are low ,10. A trTherefore, there is a need for the development, implementation and evaluation of a theory-based exercise therapy with a behavioural approach (BET) in the context of a BMR. To our knowledge, this is the first RCT to examine the effects of BET for the overall treatment success of BMR in the routine healthcare management of patients with disabling clbp.Methodological challenges arise from conducting a RCT, which claims a lot of resources, within routine health care in two rehabilitation centres as well as from ensuring high treatment integrity. The latter refers particularly to a potential mixture between the study group and the control group through a communication about intervention contents between patients and therapists within each rehabilitation centre, as well as individual deviations from the treatment protocol. To overcome those potential sources of bias BET is delivered by the same BET-therapist, who will be intensively trained in the use of the program and will receive a detailed trainer manual. BET-therapists will sign a written contract concerning discretion about BET. Regularly, announced visitations during the intervention phase will occur in order to assure adherence to the treatment protocol. Individual deviations from the treatment protocol will be recorded.Altogether, findings of this study might contribute to a better understanding of the mechanism of action of BMR and the special effects of BET and might be used to improve the quality of these interventions in routine care and therefore reduce the burden to patients with clbp.BMR: Behavioural medical rehabilitation; BET: Behavioural exercise therapy; clbp: Chronic non-specific low back pain; min: Minutes; RCT: Randomised controlled trial; SET: Standard exercise therapy.The authors declare to have no competing interests.JH drafted the manuscript and contributed substantially to the development of the research questions, the study design and the study protocol in general. Prior to all of that, JH was also responsible for conducting an in-depth literature search to prepare the BET and the study as a whole. JH is further responsible for the study organisation and oversees patient enrollment and data management. JH is also the coach at the train-the-trainer seminar, who teaches the main part. SP contributed to the development of the assessment tools for the research questions and was a major contributor to the creation of the BET and also teaches several parts at the above mentioned train-the-trainer seminar. SP wrote the respective chapters of this manuscript and contributed substantially to the other chapters. CH contributed substantially to the determination of primary and secondary outcomes and the according assessment tools. CH further oversaw the creation of the study design and is the main contributor regarding randomization, data management and data analysis. WG contributed substantially to the development of the research questions, the study design and the development of contents, methods and materials of BET. KP conceived the study and was responsible for identifying the research question beforehand. KP drafted the study design and was accountable for determining primary and secondary outcomes. KP contrived the basis for development of the experimental treatment. Every author read and approved the final version of this paper.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2474/14/89/prepubDescription of two main interventions within BMR - psychological group therapy and standard exercise therapy (SET) in both participating rehabilitation centres (control group).Click here for fileIntervention group.Click here for fileBET_Therapy plan.Click here for file


Job strain  is a frequently used indicator of harmful work stress, but studies have often used partial versions of the complete multi-item job demands and control scales. Understanding whether the different instruments assess the same underlying concepts has crucial implications for the interpretation of findings across studies, harmonisation of multi-cohort data for pooled analyses, and design of future studies. As part of the 'IPD-Work'  consortium, we compared different versions of the demands and control scales available in 17 European cohort studies.Six of the 17 studies had information on the complete scales and 11 on partial scales. Here, we analyse individual level data from 70 751 participants of the studies which had complete scales .We found high Pearson correlation coefficients between complete scales of job demands and control relative to scales with at least three items (r > 0.90) and for partial scales with two items only (r = 0.76-0.88). In comparison with scores from the complete scales, the agreement between job strain definitions was very good when only one item was missing in either the demands or the control scale (kappa > 0.80); good for job strain assessed with three demand items and all six control items (kappa > 0.68) and moderate to good when items were missing from both scales (kappa = 0.54-0.76). The sensitivity was > 0.80 when only one item was missing from either scale, decreasing when several items were missing in one or both job strain subscales.Partial job demand and job control scales with at least half of the items of the complete scales, and job strain indices based on one complete and one partial scale, seemed to assess the same underlying concepts as the complete survey instruments. Work-related psychosocial factors or "stressors at work" have been linked to increased risk of ill health and mortality in some -8 but noA frequently used measure of work stress is the two-dimensional job strain model, originally described by Karasek  and furtThe two standardised, widely used questionnaires developed to measure the demand and control dimensions, and hence job strain, are: the Job Content Questionnaire (JCQ)  and the Investigators examining the relationship between job strain and health outcomes have often used partial versions of the questionnaires. Study-specific questionnaires have also been developed which can differ from the JCQ or DCQ in terms of the number of items, content and wording of the questions, and response alternatives. It is important to understand whether the different survey instruments assess the same underlying concepts, as this has implications for the interpretation of findings across studies, harmonisation of multi-cohort data for pooled analyses, and design of future studies .Accordingly, the aim of the present analyses was to evaluate the comparability of alternative job demands, job control and job strain measures by assessing agreement against the complete scale. To do so, we use data from six studies together with information from additional 11 European cohort studies that comprise the "Individual-participant-data meta-analysis in working populations" (IPD-Work) Consortium.This study is part of the "Individual-participant-data meta-analysis in working populations" (IPD-Work) consortium of European cohort studies. This collaboration was established at a workshop, the annual Four Centers Meeting in London, in November, 2008. New cohort studies have subsequently been added. The overall aim of the IPD-Work consortium is to aggregate raw data from a series of studies in order to obtain reliable estimates of the influence of psychosocial risk factors at work on chronic diseases, mental health, disability, and mortality.In IPD-Work, a pre-defined two-stage data acquisition protocol is being used. The first stage involves the acquisition of baseline data on work stress as well as socio-demographic and lifestyle factors and the definition and harmonisation of these baseline characteristics across the studies. The second stage involves the acquisition of data on disease outcomes ascertained subsequent to the baseline survey. The present analyses were based on stage one only and were thus conducted before any linkage to disease data, planned for the second stage.We examined the agreement between complete and partial psychological demands and control scales separately in the six cohort studies of the IPD-Work consortium that had the complete job demands and job control scales. These were: the Job Stress Study I  ; the GazThe studies from which data was used in the present analysis were approved by the ethics committees of the University Hospital of Ghent and the Faculty of Medicine of the Université Libre de Bruxelles (Belstress); the National Commission Overseeing Ethical Data Collection in France  (GAZEL); the Turku University Central Hospital Ethics Committee (HeSSup); the Regional Research Ethics Board in Stockholm (SLOSH); and the ethics committee at Karolinska Institutet, Stockholm (WOLF N and WOLF S). All studies adhered to the Helsinki Declaration on ethical principles for medical research involving human subjects. Details of ethical approval of all the IPD-Work studies are described in Additional file Complete scale measures of job demands and job control were based on five items from the psychological demands scales and six items from the control scales from the JCQ and DCQ  to sufficiently resemble the original questions such that they could be used as proxy items. For example, the question on conflicting demands in Still Working study was expressed as "Do your superiors or workmates give you contradictory orders or instructions?" as compared with the corresponding item in the DCQ "Does your work often involve conflicting demands?"; and in POLS the item "Do you have to work under great time pressure?" was judged to capture the same content as "Do you have enough time to do everything?" in the DCQ. The scales with proxy items are labelled as "other" in table Using our analytical sample from the six studies with the complete scales, mean response scores for job demands items and for job control items were calculated for each study participant, for both the complete and the different partial scales. For each scale, the mean response score was calculated for participants who had answered half or more of the demand or control questions in that specific scale. However, where only two items were used in a partial scale, both items had to have non-missing values for the mean score to be calculated.The presence of job strain was defined as having high demands  and a low control score . This definition of job strain based on the quadrant approach has been widely used and will be the main method to define job strain in the IPD-Work consortium, including the present analyses. However, other approaches to derive measures of job strain from the demands and control scores have also been proposed, including the quotient method (job demands/job control); the logarithmic approach (log[job demands/job control]); and the subtraction approach (job demands minus job control) . As a suThe relationship between the complete and partial scales for the demands and control scales was ascertained using Pearson correlation coefficients with accompanying 95% confidence intervals. These were computed using Fisher's transformation. Sensitivity, specificity and Kappa (κ) statistics were calculated to evaluate the agreement between the job strain definitions based on the complete versus partial scales. The following interpretations of the Kappa statistic were utilised : 0.00-0.Pearson's correlation coefficients between the complete demand scale and partial scales are shown in table Table Table The aim of the present analyses was to evaluate the comparability of alternative job demands, job control and job strain measures by assessing agreement against the complete scales. To do so, we analysed data from a total of 70 751 participants in six European cohort studies with complete data on five job demand and six control items. We found very high correlation coefficients between the complete and partial job demands and control scales, which included a minimum of three items. The agreement for the dichotomised job strain measure was 'good' to 'very good' when at least one of the underlying subscales was complete. When one or more of the items of the underlying scales were excluded, this agreement ranged from moderate to good, depending on the specific items left out in the partial versions.The main strength of the present study is the utilisation of data from multiple independent cohort studies which collectively comprised a very large analytical sample, so providing a high level of statistical precision. Despite slight variation in the exact wording of the questionnaire items between these studies, our findings were remarkably consistent across the six cohort studies drawn from Belgium, France, Finland and Sweden. This supports the generalisability of the present analysis across different settings in four European countries. However, in the studies included in the IPD-Work Consortium, no standardised procedure had been followed to translate the original job strain questionnaire across all studies. Thus, cross-cultural adaptation of the job strain instrument remains a source of error for an individual-participant data meta-analysis project on job strain. Based on a review of job demand and control questions used in 17 European cohort studies, our tests were limited to a total of 10 different partial scales that were available in these studies. It is therefore unclear how other scale modifications, including those with additional study-specific questions, agree with the complete scales. These differences, as well as those related to translation and cultural meaning of the wording, may affect the assessment of demands and control in international comparative studies .Previously, a comparison of JCQ and DCQ-like questionnaires has been conducted in 682 participants in the JACE study . The invIn epidemiological studies, researchers often have to make a trade-off between the amount of data they would like to collect and the amount of data it is possible to collect without increasing the non-response due to overly burdensome inventories. In these circumstances, it is not uncommon for the original scales to be abbreviated. Research using job strain as the exposure measure has not always been based on validated standardised protocols and modifications in the questionnaire may have contributed to inconsistencies in the observed job strain-disease association across various studies. For example, in a recent meta-analysis of ten prospective cohort studies, the authors reported a pooled relative risk of 1.4  for incident coronary heart disease among participants with job strain compared to those without . HoweverInformation on the agreement between alternative operationalisations of job strain may help with the interpretation of previous findings, and harmonisation of multi-cohort data for pooled analyses. Our study provides information on the agreement between complete and partial job strain scales based on existing data from several European cohort studies. A high agreement for partial scales with at least half of the items of the complete scales, and an accurate classification of job strain when at least one of the scales has no missing items, suggest that these abbreviated scales assess the same underlying concepts as the complete survey instrument. However, all the partial scales in the present study , showed high to reasonable agreement with the complete scales. In order to capture the theoretical background for job strain and to measure the same construct as the complete JCQ/DCQ, it is important that the abbreviated control scales cover both the skill discretion and the decision authority dimensions.The authors declare that they have no competing interests.All authors participated in designing the study, generating hypotheses, interpreting the data and writing or critically reviewing the paper. Eleonor I Fransson, Töres Theorell and Mika Kivimäki analysed the data and wrote the first draft. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/12/62/prepubDescription of the studies included in IPD-Work Consortium.Click here for fileAppendix tables correlations, sensitivity, specificity and Kappa statistics for complete and partial job strain scales defined by the quotient, logarithmic, and subtraction approaches.Click here for file


Multistrategy Learning of Self-Organizing Map (SOM) and Particle Swarm Optimization (PSO) is commonly implemented in clustering domain due to its capabilities in handling complex data characteristics. However, some of these multistrategy learning architectures have weaknesses such as slow convergence time always being trapped in the local minima. This paper proposes multistrategy learning of SOM lattice structure with Particle Swarm Optimisation which is called ESOMPSO for solving various classification problems. The enhancement of SOM lattice structure is implemented by introducing a new hexagon formulation for better mapping quality in data classification and labeling. The weights of the enhanced SOM are optimised using PSO to obtain better output quality. The proposed method has been tested on various standard datasets with substantial comparisons with existing SOM network and various distance measurement. The results show that our proposed method yields a promising result with better average accuracy and quantisation errors compared to the other methods as well as convincing significant test. In classification process; normally, large classes of objects are separated into smaller classes. This approach can be very complicated due to the challenge in identifying the criteria especially for procedures involving complex data structures. In this scenario; practically, the Machine Learning (ML) techniques will be used and introduced by many researchers as alternative solutions to solve the above problems. Among the ML methods and tools, Artificial Neural Network (ANN), Fuzzy Set, Genetic Algorithm (GA), Swarm Intelligence (SI), and rough set are commonly used by researchers. However, the most popular ML method widely used by the practitioners is ANN . VariousANN and evolutionary computation methodologies have each been proven effective in solving certain classes of problems. For example, neural networks are very efficient at mapping input to output vectors and evolutionary algorithms are very useful at optimization. ANN weaknesses could be solved either by enhancing the structures of ANN itself or by hybridizing it with evolutionary optimisation , 6. EvolThe searching implementation with evolutionary method such as ANN learning may overcome the gradient-based handicaps. However, the convergence is in general much slower, since these are general purpose methods. Kennedy and Eberhart  proposedEarly studies have shown that the multistrategy learning of PSO-SOM approach was first introduced by Shi and Eberhart  with modMoreover, Chandramouli  used SOMSharma and Omlin  utilizedSince 1993, Extension of SOM network topologies such as self-organization network has been implemented in many applications. Fritzke  introducHybridization of SOM and evolutionary method was proposed by Créput et al.  to addreThe quality of the Kohonen map is determined by its lattice structure. This is because the weights for each neuron in the neighborhood will be updated by these lattice structures. There are many types of SOM lattice structures: circle lattice structure, rectangular, hexagonal, spherical , and tor Spherical and Torus SOM representing the plane lattice give a better view of the input data as well as provide closer links to edge nodes. They make the 2D visualisation of multivariate data possible using SOM's code vectors as data source . SphericAccording to Middleton et al. , hexagon samples . BasicalAstel et al.  has alsoWu and Takatsuka  used fasDue to limitations of the previous studies focusing on the improvement of SOM lattice structure, this study enhanced SOM lattice structure with improved hexagonal lattice area. In SOM competitive learning process, wider lattice are needed for searching the winning nodes as well as for weights adjustment. This allows SOM to get a good set of weights for improving the quality of data classification and labeling. Particle Swarm Optimisation (PSO) is developed to optimize SOMs' training weights accordingly. The hybridisation of SOM-PSO architecture, so-called Enhanced SOM with Particle Swarm Optimisation (ESOMPSO) is proposed with improvement on the lattice structure for better classification. The performance of the proposed ESOMPSO is validated based on the classification accuracy and quantization errors (QE). The error deviations between the proposed methods are computed to further illustrate the efficiency of these approaches accordingly.N instead of the neighbourhood width, N(j). Since D(t) is a threshold value, it will decrease gradually as training progresses. For this neighbourhood function, the distance is determined by considering the distance of each dimension. The dimension with the maximum value is chosen as distance node from BMU, d(j). N(j) corresponds to a hexagonal lattice around nwin having neighbourhood width as below:In this study, we proposed multistrategy learning with the Enhancement of SOM with PSO (ESOMPSO) and improved formulation of hexagonal lattice structure. Unlike conventional hexagonal lattice (as given in ), a neigR is the standard hexagonal lattice andN(j) = 1, while the others remaining unchanged. As the training progresses, this neighborhood gets smaller, resulting in the neurons that are very close to the winner and will get updated accordingly. The training stops when there is no more neuron in the neighborhood. Usually, the neighborhood function, N, is chosen as an L-dimensional Gaussian function as given below:The weights of all neurons within this hexagon are updated with V, do the following.For each input vector Initialisation—set initial synaptic weights to small random values, say in a interval , and assign a small positive value to the learning rate parameter. j, calculate the value D(V − Wj) of the scoring function. For instance, Euclidean distance measurement is denoted asJ that minimizes D(V − Wj) overall output nodes.Competition—for each output node j within the neighborhood of J defined by the neighborhood size R. For these nodes, do the following for all input records. Reduce the radius with exponential decay function:σ0 is the initial radius, λ is the maximum iteration, t is the current iteration; and formulation of improved hexagonal lattice is given asRnew is the enhanced/improved hexagonal lattice, r is the neighborhood radius.Cooperation—identify all output nodes L is the learning rate, Θ is the influence a node's distance from the BMU,L0 is the initial learning rate,σ is the width of neighborhood.Adaptation—adjust the weights:x, y), left_border , up_right_border , up_left_border , bottom_right_border , bottom_left_border   and stop when the termination criteria are met. The improved hexagonal lattice area consists of six important points: right_border  is one of the Swarm Intelligence (SI) techniques that are inspired by social behavior of bird flocking and fish schooling. The pioneers of the PSO algorithm are Kennedy, Eberhart, and Shi in 1995 . PSO is inuously . The algmi, where i = 1,2,…, K randomly, where K is the length of the feature vector.The rectangular topology and hexagonal lattice structure of the SOM is initialized with feature vectors x is presented to the network and the winner node J, that is closest to the input pattern, x is chosen using the equation:Input feature vector d dimensional problem space.Initialise the population array of particle representing random solutions for For each particle, the distance function is evaluated,pbest is updated by the following condition:The personal best gbest is updated with the following condition:The global best Vid usingC1 > 0  and  C2 > 0 constants are called the cognitive and social parameters, and W > 0 is a constant called the inertia parameter. Update the velocity Xid usingXid is the new position X and Vid is the new velocity V.Update the position Repeat steps 2 to 9 until all input patterns are exhausted in the training.To investigate the effectiveness of PSO in evolving the weights from SOM, the proposed method has been performed in the testing and validation process. In the testing phase, data is presented to the network with target nodes for each input sets. The reference attributes or classifier computed during training process is used to classify input data set. The algorithm identifies the winning node that will be used for determining the output of the network. Then, the output of the network is compared to the expected result to decide the ability of the network for classification phase. This classification stage will classify test data into correct predefined classes obtained during training process. A number of data is presented to the network, and the percentage of correct classified data is calculated. The percentage of the correctness is measured to obtain the accuracy and the learning ability of the network. The result is validated and compared using several performance measurements: quantisation error (QE) and classification accuracy. Later, the error differences between the proposed methods are computed for further validations.xi is exactly similar as xi, the error in precision is 0.0. The equation is given as followsThe performance measurement of the proposed methods is based on quantisation error (QE) and classification accuracy (CA). QE is measured after SOM's training, and CA is the analysis for testing. The efficiency of the proposed methods is validated accordingly; if QE values are smaller and the classification accuracy is higher, then the results are promising. QE is used for measuring the quality of SOM map. QE of an input vector is defined by the difference between the input vector and the closest codebook vectors. QE describes how accurately the neurons respond to the given dataset. For example, if the reference vector of the BMU calculated for a given testing vector wmk is the best unit of weight on times t. Quantization Error:While the classification accuracy indicates how well the classes are separated on the map, the classification accuracy of new samples measures the networks generalisation for better quality of SOM's mapping. n is the number of classified pattern, N is the total number of testing data.Classification accuracy,gbest of BMU as well as wider coverage for updating nodes with the improved lattice structure.The goal of the conducted experiments is to investigate the performance of the proposed methods. The comparisons are done on ESOMPSO, SOM with PSO (SOMPSO), and enhanced SOM (ESOM). The results are validated in terms of classification accuracy and quantisation error (QE) on standard universal machine learning datasets: Iris, XOR, Cancer, Glass, and Pendigits. From the conducted experiments, it shows that the proposed methods, ESOMPSO and SOMPSO, give better accuracy despites higher convergence time. As PSO and improved lattice structure are being implemented, the convergence time is increasing. This scenario is due to the PSO process in searching for the Self-Organizing Maps (SOM) has two layers: input and output layers. The basic SOM architecture consists of a lattice that acts as an output layer with its input nodes fully connected. In this study, the network architecture is designed based on the selected real world classification problems. The input layer is comprised of input pattern with different nodes that is randomly chosen from training data set. Input patterns are presented to all output nodes (neurons) in the network simultaneously. The number of input node determines the number of data required to be fed into the network, while the numbers of nodes in the Kohonen layer represent the maximum number of possible classes. The training starts once the dataset has been initialised and input patterns have been selected. The learning phase of the SOM algorithm repeatedly presents numerous patterns to the network. The learning rule of the classifier allows these training cases to organize in a two-dimensional feature map. Patterns which resemble each other are mapped onto a specific cluster. During the training phase, the class for randomly selected input node is determined. This is done by labeling the output node that is more similar (best-matching unit) to the input node compared to other nodes in the Kohonen mapping structure. The outputs from the training are the resulting map that contains the winning neurons and its associated weight vectors. Subsequently, these weight vectors are optimised by PSO. The quality of the classification accuracy is calculated to investigate the behavior of the network in the training data. mth neuron is the winner, it belongs to the mth clusters. In this case, we were able to test the capacity of the network to correctly classify new independent test set to a reasonable class. An independent test set is a set similar to the input set but not part of the training set. The testing set can be seen as a representative of the general case. There is no weight updating in the recalling phase. A series of datasets obtained that was not used in learning phases, but was previously interpreted, was presented to the network. For each case, the response of the network (the label of the associated neuron) was compared to the expected result, and the percentage of correct responses was computed. This simulation results obtained from standard SOM and Enhanced SOM classifiers were used for further analysis. In the testing phase, for any input patterns, if the It is often reported in the literature that the success of the Self-Organizing Maps (SOM) formation is critically dependent on the initial weights and the selection of main parameters of the algorithm, namely, the learning rate parameter and the neighborhood set , 37. TheThere is no guideline in suggesting good learning rates to any given learning problem. In standard SOM, too large and too small learning rates can lead to poor network performance . NeighboThe accuracy of the map also depends on the number of iterations of the SOM algorithm. A rule of thumb states, for good statistical accuracy, number of iterations should be at least 500 times the number of neurons. According to , the totThe experiments were conducted with various datasets and distance measurements: Euclidean, Manhattan, and Chebyshev distance. The comparisons were conducted between standard SOM and standard SOM with improved hexagonal structure, so-called ESOM. Standard SOM was trained using standard hexagonal lattice, while ESOM with improved hexagonal lattice. The choice of distance measure influences the accuracy, efficiency, and generalisation ability of the results. From Similar experiments were conducted for standard SOM with PSO, so-called SOMPSO and ESOMPSO with Euclidean, Manhattan's, and Chebyshev's distance measurements. SOMPSO was trained using standard hexagonal lattice, while ESOMPSO was trained with improved hexagonal lattice. The results were compared in terms of classification accuracy, quantisation error, and convergence error. As illustrated in gbest globally and locally. ESOMPSO with Euclidean distance gives the highest classification accuracy of 95.22% and the least quantisation error of 0.0038, accordingly.Figures No Free Lunch Theorem [However, this tradeoff, that is, higher accuracy with more convergence time and vice versa, does not give big impact on the success of the proposed methods due to the concept of  Theorem . It meanr = 2. The radius will decrease with exponential decay function. The improved neighborhood hexagonal lattice area is defined as  for classification problems. The proposed method was successfully implemented on machine learning datasets: XOR, Cancer, Glass, Pendigits, and Iris. The analysis was done by comparing the results for each dataset produced by Self-Organising Map (SOM), Enhanced Self-Organising Map (ESOM), Self-Organizing Map with Particle Swarm Optimization (SOMPSO) and ESOMPSO with different distance measurements. The analysis reveals that ESOMPSO with Euclidean distance generate promising results based on the highest accuracy and the least quantization errors (referring to Figures