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  • 1.
    Af Sandeberg, Margareta
    et al.
    Department of Women's and Children's Health, Karolinska Institutet, Children's and Women's Health, Karolinska University Hospital.
    Wenemark, Marika
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Business support and Development, Department of Health and Care Development.
    Bartholdson, Cecilia
    Department of Women's and Children's Health, Karolinska Institutet, Children's and Women's Health, Karolinska University Hospital.
    Lützén, Kim
    Department of Women's and Children's Health, Karolinska Institutet.
    Pergert, Pernilla
    Department of Women's and Children's Health, Karolinska Institutet, Children's and Women's Health, Karolinska University Hospital.
    To change or not to change - translating and culturally adapting the paediatric version of the Moral Distress Scale-Revised (MDS-R)2017In: BMC Medical Ethics, ISSN 1472-6939, E-ISSN 1472-6939, Vol. 18, no 14, p. 1-9Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Paediatric cancer care poses ethically difficult situations that can lead to value conflicts about what is best for the child, possibly resulting in moral distress. Research on moral distress is lacking in paediatric cancer care in Sweden and most questionnaires are developed in English. The Moral Distress Scale-Revised (MDS-R) is a questionnaire that measures moral distress in specific situations; respondents are asked to indicate both the frequency and the level of disturbance when the situation arises. The aims of this study were to translate and culturally adapt the questionnaire to the context of Swedish paediatric cancer care. In doing so we endeavoured to keep the content in the Swedish version as equivalent to the original as possible but to introduce modifications that improve the functional level and increase respondent satisfaction.

    METHODS: The procedure included linguistic translation and cultural adaptation of MDS-R's paediatric versions for Physicians, Nurses and Other Healthcare Providers to the context of Swedish paediatric cancer care. The process of adjustment included: preparation, translation procedure and respondent validation. The latter included focus group and cognitive interviews with healthcare professionals in paediatric cancer care.

    RESULTS: To achieve a Swedish version with a good functional level and high trustworthiness, some adjustments were made concerning design, language, cultural matters and content. Cognitive interviews revealed problems with stating the level of disturbance hypothetically and items with negations caused even more problems, after having stated that the situation never happens.

    CONCLUSIONS: Translation and cultural adaptation require the involvement of various types of specialist. It is difficult to combine the intention to keep the content as equivalent to the original as possible with the need for modifications that improve the functional level and increase respondent satisfaction. The translated and culturally adapted Swedish MDS-R seems to have equivalent content as well as improved functional level and respondent satisfaction. The adjustments were made to fit paediatric cancer care but it could be argued that the changes are relevant for most areas of paediatric care of seriously ill patients.

  • 2.
    Delisle Nyström, Christine
    et al.
    Karolinska Institute, Sweden.
    Sandin, Sven
    Karolinska Institute, Sweden; Icahn School Medical Mt Sinai, NY 10029 USA; Icahn School Medical Mt Sinai, NY 10029 USA.
    Henriksson, Pontus
    University of Granada, Spain.
    Henriksson, Hanna
    University of Granada, Spain.
    Trolle-Lagerros, Ylva
    Karolinska Institute, Sweden; Karolinska University Hospital, Sweden.
    Larsson, Christel
    University of Gothenburg, Sweden.
    Maddison, Ralph
    Deakin University, Australia.
    Ortega, Francisco B.
    University of Granada, Spain.
    Pomeroy, Jeremy
    Marshfield Clin Research Fdn, WI USA.
    Ruiz, Jonatan R.
    University of Granada, Spain.
    Silfvernagel, Kristin
    Linköping University, Department of Behavioural Sciences and Learning, Psychology. Linköping University, Faculty of Arts and Sciences.
    Timpka, Toomas
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Business support and Development, Department of Health and Care Development.
    Löf, Marie
    Karolinska Institute, Sweden.
    Mobile-based intervention intended to stop obesity in preschool-aged children: the MINISTOP randomized controlled trial2017In: American Journal of Clinical Nutrition, ISSN 0002-9165, E-ISSN 1938-3207, Vol. 105, no 6, p. 1327-1335Article in journal (Refereed)
    Abstract [en]

    Background: Traditional obesity prevention programs are time-and cost-intensive. Mobile phone technology has been successful in changing behaviors and managing weight; however, to our knowledge, its potential in young children has yet to be examined. Objective: We assessed the effectiveness of a mobile health (mHealth) obesity prevention program on body fat, dietary habits, and physical activity in healthy Swedish children aged 4.5 y. Design: From 2014 to 2015, 315 children were randomly assigned to an intervention or control group. Parents in the intervention group received a 6-mo mHealth program. The primary outcome was fat mass index (FMI), whereas the secondary outcomes were intakes of fruits, vegetables, candy, and sweetened beverages and time spent sedentary and in moderate-to-vigorous physical activity. Composite scores for the primary and secondary outcomes were computed. Results: No statistically significant intervention effect was observed for FMI between the intervention and control group (mean +/- SD: -0.23 +/- 0.56 compared with -0.20 +/- 0.49 kg/m(2)). However, the intervention group increased their mean composite score from baseline to follow-up, whereas the control group did not (+ 0.36 +/- 1.47 compared with -0.06 +/- 1.33 units; P = 0.021). This improvement was more pronounced among the children with an FMI above the median (4.11 kg/m(2)) (P = 0.019). The odds of increasing the composite score for the 6 dietary and physical activity behaviors were 99% higher for the intervention group than the control group (P = 0.008). Conclusions: This mHealth obesity prevention study in preschool-aged children found no difference between the intervention and control group for FMI. However, the intervention group showed a considerably higher postintervention composite score (a secondary outcome) than the control group, especially in children with a higher FMI. Further studies targeting specific obesity classes within preschool-aged children are warranted.

  • 3.
    Fagher, Kristina
    et al.
    Rehabilitation Medicine Research Group, Department of Health Sciences, Lund University, Lund, Sweden.
    Jacobsson, Jenny
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Dahlström, Örjan
    Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Medicine and Health Sciences.
    Timpka, Toomas
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Business support and Development, Department of Health and Care Development.
    Lexell, Jan
    Rehabilitation Medicine Research Group, Department of Health Sciences, Lund University, Lund, Sweden; Department of Neurology and Rehabilitation Medicine, Skåne University Hospital, Lund, Sweden; Department of Health Science, Luleå University of Technology, Luleå, Sweden.
    An eHealth Application of Self-Reported Sports-Related Injuries and Illnesses in Paralympic Sport: Pilot Feasibility and Usability Study2017In: JMIR Human Factors, E-ISSN 2292-9495, Vol. 4, no 4, article id e30Article in journal (Refereed)
    Abstract [en]

    Sport participation is associated with a risk of sports-related injuries and illnesses, and Paralympic athletes additional medical issues can be a challenge to health care providers and medical staff. However, few prospective studies have assessed sports-related injuries and illnesses in Paralympic sport (SRIIPS) over time. Advances in mobile phone technology and networking systems offer novel opportunities to develop innovative eHealth applications for collection of athletes self-reports. Using eHealth applications for collection of self-reported SRIIPS is an unexplored area, and before initiation of full-scale research of SRIIPS, the feasibility and usability of such an approach needs to be ascertained.

  • 4.
    Festin, Karin
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Thomas, Kristin
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Ekberg, Joakim
    Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Business support and Development, Department of Health and Care Development.
    Kristenson, Margareta
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Choice of measure matters: A study of the relationship between socioeconomic status and psychosocial resources in a middle-aged normal population2017In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 12, no 8, article id e0178929Article in journal (Refereed)
    Abstract [en]

    Psychosocial resources may serve as an important link to explain socioeconomic differences in health. Earlier studies have demonstrated that education, income and occupational status cannot be used interchangeably as indicators of a hypothetical latent social dimension. In the same manner, it is important to disentangle the effect of measuring different constructs of psychosocial resources. The aim of this study was therefore to analyse if associations between socioeconomic status (SES) and psychosocial resources differ depending on the measures used. A cross-sectional population-based study of a random sample (n = 1007) of middle-aged individuals (45-69 years old, 50% women) in Sweden was performed using questionnaire and register data. SES was measured as education, occupation, household income and self-rated economy. Psychosocial resources were measured as social integration, social support, mastery, self-esteem, sense of coherence (SOC) and trust. Logistic regression models were applied to analyse the relationships controlling for the effects of possible confounders. The measures of SES were low or moderately correlated to each other as were the measures of psychosocial resources. After controlling for age, sex, country of birth and employment status, household income and self-rated economy were associated with all six psychosocial resources; occupation was associated with three (social integration, self-esteem and trust) and education with two (social integration and self-esteem). Social integration and self-esteem showed a significant and graded relationship with all SES measures; trust was associated with all SES measures except education, whereas SOC and mastery were only associated with household income and self-rated economy. After controlling for other SES measures, no associations with psychosocial resources remained for education or occupation. In conclusion, associations between SES and psychosocial resources did differ depending on the measures used. The findings illustrate the importance of the choice of measure when investigating SES as well as psychosocial resources.

  • 5.
    Hulme, Adam
    et al.
    Federat University of Australia, Australia.
    Oestergaard Nielsen, Rasmus
    Aarhus University, Denmark.
    Timpka, Toomas
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Business support and Development, Department of Health and Care Development.
    Verhagen, Evert
    Federat University of Australia, Australia; Vrije University of Amsterdam, Netherlands.
    Finch, Caroline
    Federat University of Australia, Australia.
    Risk and Protective Factors for Middle- and Long-Distance Running-Related Injury2017In: Sports Medicine, ISSN 0112-1642, E-ISSN 1179-2035, Vol. 47, no 5, p. 869-886Article, review/survey (Refereed)
    Abstract [en]

    Background Despite a rapidly growing body of research, a systematic evidence compilation of the risk and protective factors for middle- and long-distance running-related injury (RRI) was lacking. Objectives Our objective was to compile the evidence about modifiable and non-modifiable training-related and behavioral risk and protective factors for middle- and long-distance RRI. Methods We searched five databases (PubMed, CINAHL, MEDLINE, SPORTDiscus, and PsycINFO) for the dates 1 January 1970 to 31 December 2015, inclusive, for original peer-reviewed articles. The eligible designs were cross-sectional, case-control, longitudinal observational studies, and randomized controlled trials involving runners competing at distances from amp;gt;= 800 m to amp;lt;= 42.2 km. Outcomes were any specific and/or general RRI, and exposures included training-related and behavioral factors. We extracted authors and date, study design, injury type(s), descriptors and comparators for each exposure, and results and measures of association from the selected studies. Methodological quality was independently appraised using two separate checklists: a modified checklist for observational study designs and the Physiotherapy Evidence Database (PEDro) scale for randomized controlled trials. Results Among 73 articles eligible for inclusion, 19 (26.0%) and 30 (41.0%) were of high or satisfactory methodological quality, respectively. As a non-modifiable exposure, a history of previous injury was found to be associated with an increased risk of both general and specific RRI. In terms of modifiable exposures, irregular and/or absent menstruation was found to be associated with an increased risk of stress fracture development, whereas the use of oral contraceptives was found to be associated with a decreased risk. High clinical, methodological, and statistical heterogeneity meant it was not feasible to estimate a pooled effect size across similar studies. Conclusions A history of previous injury was associated with an increased risk of both general and specific RRI. The use of oral contraceptives was found to be associated with a decreased risk of skeletal stress fracture. Conversely, irregular and/or absent menstruation was associated with an increased risk. The varied effect directions and/or a number of statistically insignificant results associated with the majority of factors hindered our ability to draw any definitive conclusions about their relationship to RRI risk.

  • 6.
    Nadri, Hamed
    et al.
    Urmia University of Medical Science, Iran.
    Rahimi, Bahlol
    Urmia University of Medical Science, Iran.
    Timpka, Toomas
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Department of Computer and Information Science. Linköping University, Faculty of Science & Engineering. Region Östergötland, Center for Business support and Development, Department of Health and Care Development.
    Sedghi, Shahram
    Iran University of Medical Science, Iran.
    The Top 100 Articles in the Medical Informatics: a Bibliometric Analysis2017In: Journal of medical systems, ISSN 0148-5598, E-ISSN 1573-689X, Vol. 41, no 10, article id 150Article in journal (Refereed)
    Abstract [en]

    The number of citations that a research paper receives can be used as a measure of its scientific impact. The objective of this study was to identify and to examine the characteristics of top 100 cited articles in the field of Medical Informatics based on data acquired from the Thomson Reuters Web of Science (WOS) in October, 2016. The data was collected using two procedures: first we included articles published in the 24 journals listed in the "Medical Informatics" category; second, we retrieved articles using the key words: "informatics", "medical informatics", "biomedical informatics", "clinical informatics" and "health informatics". After removing duplicate records, articles were ranked by the number of citations they received. When the 100 top cited articles had been identified, we collected the following information for each record: all WOS database citations, year of publication, journal, author names, authors affiliation, country of origin and topics indexed for each record. Citations for the top 100 articles ranged from 346 to 7875, and citations per year ranged from 11.12 to 525. The majority of articles were published in the 2000s (n=43) and 1990s (n=38). Articles were published across 10 journals, most commonly Statistics in medicine (n=71) and Medical decision making (n=28). The articles had an average of 2.47 authors. Statistics and biostatistics modeling was the most common topic (n=71), followed by artificial intelligence (n=12), and medical errors (n=3), other topics included data mining, diagnosis, bioinformatics, information retrieval, and medical imaging. Our bibliometric analysis illustrated a historical perspective on the progress of scientific research on Medical Informatics. Moreover, the findings of the current study provide an insight on the frequency of citations for top cited articles published in Medical Informatics as well as quality of the works, journals, and the trends steering Medical Informatics.

  • 7.
    Periard, Julien D.
    et al.
    Aspetar Orthopaed and Sports Medical Hospital, Qatar.
    Racinais, Sebastien
    Aspetar Orthopaed and Sports Medical Hospital, Qatar.
    Timpka, Toomas
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Business support and Development, Department of Health and Care Development.
    Dahlström, Örjan
    Linköping University, Department of Behavioural Sciences and Learning, Disability Research. Linköping University, Faculty of Arts and Sciences. Linköping University, The Swedish Institute for Disability Research.
    Spreco, Armin
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Jacobsson, Jenny
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Swedish Athlet Assoc, Sweden.
    Bargoria, Victor
    Linköping University. Moi University, Kenya.
    Halje, Karin
    Region Östergötland, Local Health Care Services in Central Östergötland.
    Alonso, Juan-Manuel
    Aspetar Orthopaed and Sports Medical Hospital, Qatar.
    Strategies and factors associated with preparing for competing in the heat: a cohort study at the 2015 IAAF World Athletics Championships2017In: British Journal of Sports Medicine, ISSN 0306-3674, E-ISSN 1473-0480, Vol. 51, no 4, p. 264-271Article in journal (Refereed)
    Abstract [en]

    Purpose Assess exertional heat illness (EHI) history and preparedness in athletes competing in a World Athletics Championships under hot/humid conditions and identify the factors associated with preparedness strategies. Methods Of the 207 registered national teams invited to participate in the study, 50 (24%) accepted. The 957 athletes (49% of all 1965 registered) in these teams were invited to complete a precompetition questionnaire evaluating EHI history, heat stress prevention (heat acclimatisation, precooling and hydration) and recovery. Responses from 307 (32%) athletes were separated in field events, sprints, middle-distance and long-distance running, and decathlon/heptathlon for analysis. Results 48% of athletes had previously experienced EHI symptoms and 8.5% had been diagnosed with EHI. 15% heat acclimatised (similar to 20 days) before the championships. 52% had a precooling strategy, ice slurry ingestion (24%) being the most prevalent and women using it more frequently than men (p=0.005). 96% of athletes had a fluid consumption strategy, which differed between event categories (pamp;lt;0.001). The most common volumes planned on being consumed were 0.5-1 L (27.2%) and amp;gt;= 2 L (21.8%), water being the most frequent. 89% of athletes planned on using at least one recovery strategy. Female sex (p=0.024) and a previous EHI diagnosis increased the likelihood of using all 3 prevention strategies (pamp;lt;0.001). Conclusions At a World Championships with expected hot/humid conditions, less than one-fifth of athletes heat acclimatised, half had a precooling strategy and almost all a hydration plan. Women, and especially athletes with an EHI history, were more predisposed to use a complete heat stress prevention strategy. More information regarding heat acclimatisation should be provided to protect athlete health and optimise performance at major athletics competitions in the heat.

  • 8.
    Spreco, Armin
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Health Care Analysis. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Business support and Development, Department of Health and Care Development.
    Eriksson, Olle
    Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Faculty of Arts and Sciences.
    Dahlström, Örjan
    Linköping University, Department of Behavioural Sciences and Learning, Disability Research. Linköping University, Faculty of Arts and Sciences.
    Cowling, Benjamin John
    Univ Hong Kong, Peoples R China.
    Timpka, Toomas
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Business support and Development, Department of Health and Care Development.
    Evaluation of Nowcasting for Detecting and Predicting Local Influenza Epidemics, Sweden, 2009-20142018In: Emerging Infectious Diseases, ISSN 1080-6040, E-ISSN 1080-6059, Vol. 24, no 10, p. 1868-1873Article in journal (Refereed)
    Abstract [en]

    The growing availability of big data in healthcare and public health opens possibilities for infectious disease control in local settings. We prospectively evaluated a method for integrated local detection and prediction (nowcasting) of influenza epidemics over 5 years, using the total population in Ostergotland County, Sweden. We used routine health information system data on influenza-diagnosis cases and syndromic telenursing data for July 2009-June 2014 to evaluate epidemic detection, peak-timing prediction, and peak-intensity prediction. Detection performance was satisfactory throughout the period, except for the 2011-12 influenza A(H3N2) season, which followed a season with influenza B and pandemic influenza A(H1N1) pdm09 virus activity. Peak-timing prediction performance was satisfactory for the 4 influenza seasons but not the pandemic. Peak-intensity levels were correctly categorized for the pandemic and 2 of 4 influenza seasons. We recommend using versions of this method modified with regard to local use context for further evaluations using standard methods.

  • 9.
    Spreco, Armin
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Eriksson, Olle
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Dahlström, Örjan
    Linköping University, Department of Behavioural Sciences and Learning, Disability Research. Linköping University, Faculty of Arts and Sciences. Linköping University, The Swedish Institute for Disability Research.
    Cowling, Benjamin John
    University of Hong Kong, Peoples R China.
    Timpka, Toomas
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Business support and Development, Department of Health and Care Development.
    Integrated Detection and Prediction of Influenza Activity for Real-Time Surveillance: Algorithm Design2017In: Journal of Medical Internet Research, ISSN 1438-8871, E-ISSN 1438-8871, Vol. 19, no 6, article id e211Article in journal (Refereed)
    Abstract [en]

    Background: Influenza is a viral respiratory disease capable of causing epidemics that represent a threat to communities worldwide. The rapidly growing availability of electronic "big data" from diagnostic and prediagnostic sources in health care and public health settings permits advance of a new generation of methods for local detection and prediction of winter influenza seasons and influenza pandemics. Objective: The aim of this study was to present a method for integrated detection and prediction of influenza virus activity in local settings using electronically available surveillance data and to evaluate its performance by retrospective application on authentic data from a Swedish county. Methods: An integrated detection and prediction method was formally defined based on a design rationale for influenza detection and prediction methods adapted for local surveillance. The novel method was retrospectively applied on data from the winter influenza season 2008-09 in a Swedish county (population 445,000). Outcome data represented individuals who met a clinical case definition for influenza (based on International Classification of Diseases version 10 [ICD-10] codes) from an electronic health data repository. Information from calls to a telenursing service in the county was used as syndromic data source. Results: The novel integrated detection and prediction method is based on nonmechanistic statistical models and is designed for integration in local health information systems. The method is divided into separate modules for detection and prediction of local influenza virus activity. The function of the detection module is to alert for an upcoming period of increased load of influenza cases on local health care (using influenza-diagnosis data), whereas the function of the prediction module is to predict the timing of the activity peak (using syndromic data) and its intensity (using influenza-diagnosis data). For detection modeling, exponential regression was used based on the assumption that the beginning of a winter influenza season has an exponential growth of infected individuals. For prediction modeling, linear regression was applied on 7-day periods at the time in order to find the peak timing, whereas a derivate of a normal distribution density function was used to find the peak intensity. We found that the integrated detection and prediction method detected the 2008-09 winter influenza season on its starting day (optimal timeliness 0 days), whereas the predicted peak was estimated to occur 7 days ahead of the factual peak and the predicted peak intensity was estimated to be 26% lower than the factual intensity (6.3 compared with 8.5 influenza-diagnosis cases/100,000). Conclusions: Our detection and prediction method is one of the first integrated methods specifically designed for local application on influenza data electronically available for surveillance. The performance of the method in a retrospective study indicates that further prospective evaluations of the methods are justified.

  • 10.
    Spreco, Armin
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Eriksson, Olle
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Dahlström, Örjan
    Linköping University, Department of Behavioural Sciences and Learning, Disability Research. Linköping University, Faculty of Arts and Sciences. Linköping University, The Swedish Institute for Disability Research.
    Timpka, Toomas
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Business support and Development, Department of Health and Care Development.
    Influenza detection and prediction algorithms: comparative accuracy trial in Ostergotland county, Sweden, 2008-20122017In: Epidemiology and Infection, ISSN 0950-2688, E-ISSN 1469-4409, Vol. 145, no 10, p. 2166-2175Article in journal (Refereed)
    Abstract [en]

    Methods for the detection of influenza epidemics and prediction of their progress have seldom been comparatively evaluated using prospective designs. This study aimed to perform a prospective comparative trial of algorithms for the detection and prediction of increased local influenza activity. Data on clinical influenza diagnoses recorded by physicians and syndromic data from a telenursing service were used. Five detection and three prediction algorithms previously evaluated in public health settings were calibrated and then evaluated over 3 years. When applied on diagnostic data, only detection using the Serfling regression method and prediction using the non-adaptive log-linear regression method showed acceptable performances during winter influenza seasons. For the syndromic data, none of the detection algorithms displayed a satisfactory performance, while non-adaptive log-linear regression was the best performing prediction method. We conclude that evidence was found for that available algorithms for influenza detection and prediction display satisfactory performance when applied on local diagnostic data during winter influenza seasons. When applied on local syndromic data, the evaluated algorithms did not display consistent performance. Further evaluations and research on combination of methods of these types in public health information infrastructures for nowcasting (integrated detection and prediction) of influenza activity are warranted.

  • 11.
    Strömgren, M.
    et al.
    Umeå University, Sweden.
    Holm, E.
    Umeå University, Sweden.
    Dahlström, Örjan
    Linköping University, Department of Behavioural Sciences and Learning, Disability Research. Linköping University, Faculty of Arts and Sciences. Linköping University, The Swedish Institute for Disability Research.
    Ekberg, Joakim
    Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Business support and Development, Department of Health and Care Development.
    Eriksson, Henrik
    Linköping University, Department of Computer and Information Science, Human-Centered systems. Linköping University, Faculty of Science & Engineering.
    Spreco, Armin
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Timpka, Toomas
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Department of Computer and Information Science. Linköping University, Faculty of Science & Engineering. Region Östergötland, Center for Business support and Development, Department of Health and Care Development.
    Place-based social contact and mixing: a typology of generic meeting places of relevance for infectious disease transmission2017In: Epidemiology and Infection, ISSN 0950-2688, E-ISSN 1469-4409, Vol. 145, no 12, p. 2582-2593Article in journal (Refereed)
    Abstract [en]

    This study aims to develop a typology of generic meeting places based on social contact and mixing of relevance for infectious disease transmission. Data were collected by means of a contact diary survey conducted on a representative sample of the Swedish population. The typology is derived from a cluster analysis accounting for four dimensions associated with transmission risk: visit propensity and its characteristics in terms of duration, number of other persons present and likelihood of physical contact. In the analysis, we also study demographic, socio-economic and geographical differences in the propensity of visiting meeting places. The typology identifies the family venue, the fixed activity site, the family vehicle, the trading plaza and the social network hub as generic meeting places. The meeting place typology represents a spatially explicit account of social contact and mixing relevant to infectious disease modelling, where the social context of the outbreak can be highlighted in light of the actual infectious disease.

  • 12.
    Timpka, Toomas
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Business support and Development, Department of Health and Care Development.
    Jacobsson, Jenny
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences. Swedish Athlet Assoc, Sweden.
    Bargoria, Victor
    Linköping University. Moi University, Kenya.
    Periard, Julien D.
    Aspetar Orthopaed and Sports Medical Hospital, Qatar.
    Racinais, Sebastien
    Aspetar Orthopaed and Sports Medical Hospital, Qatar.
    Ronsen, Ola
    Medical and Antidoping Commiss, Monaco; Aker Solut, Norway.
    Halje, Karin
    Region Östergötland, Local Health Care Services in Central Östergötland.
    Andersson, Christer A.
    Linköping University, Department of Clinical and Experimental Medicine, Orthopaedics and Sports Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Orthopaedics in Linköping.
    Dahlström, Örjan
    Linköping University, Department of Behavioural Sciences and Learning, Disability Research. Linköping University, Faculty of Arts and Sciences. Linköping University, The Swedish Institute for Disability Research.
    Spreco, Armin
    Linköping University, Department of Medical and Health Sciences, Division of Community Medicine. Linköping University, Faculty of Medicine and Health Sciences.
    Edouard, Pascal
    University Hospital St Etienne, France; University of Lyon, France; Medical Commiss, France.
    Alonso, Juan-Manuel
    Medical and Antidoping Commiss, Monaco; Aspetar Orthopaed and Sports Medical Hospital, Qatar.
    Preparticipation predictors for championship injury and illness: cohort study at the Beijing 2015 International Association of Athletics Federations World Championships2017In: British Journal of Sports Medicine, ISSN 0306-3674, E-ISSN 1473-0480, Vol. 51, no 4, p. 272-+Article in journal (Refereed)
    Abstract [en]

    Objectives To determine preparticipation predictors of injury and illness at a major Athletics championship. Methods A cohort study design was used. Before the 2015 International Association of Athletics Federations World Championships in Athletics, all 207 registered national teams were approached about partaking in a study of preparticipation health; 50 teams accepted. The athletes (n=957) in the participating teams were invited to complete a preparticipation health questionnaire (PHQ). New injuries and illnesses that occurred at the championships were prospectively recorded. Logistic regression analyses were performed with simple and multiple models using any in-championship injury and in-championship illness as outcomes. Results The PHQ was completed by 307 (32.1%) of the invited athletes; 116 athletes (38.3%) reported an injury symptom during the month before the championships, while 40 athletes (13%) reported an illness symptom. 20 (6.5%) of the participating athletes sustained a health problem during the championships. Endurance athletes were almost 10-fold more likely to sustain an in-championship illness than speed/power athletes (OR, 9.88; 95% CI 1.20 to 81.31; p=0.033). Participants reporting a preparticipation gradual-onset injury symptom were three times more likely (OR, 3.09; 95% CI 1.08 to 8.79; p=0.035) and those reporting an illness symptom causing anxiety were fivefold more likely (OR, 5.56; 95% CI 1.34 to 23.15; p=0.018) to sustain an in-championship injury. Summary and conclusions Analyses of preparticipation predictors of injury and illness at a major Athletics championship suggest that endurance athletes require particular clinical attention. Preparticipation symptoms causing anxiety are interesting predictors for in-championship health problems.

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