@misc{HasenbringLevenigHallneretal.2018,
  author    = {Hasenbring, Monika Ilona and Levenig, Claudia and Hallner, D. and Puschmann, Anne-Katrin and Weiffen, A. and Kleinert, Jens and Belz, J. and Schiltenwolf, Marcus and Pfeifer, A. -C. and Heidari, Jahan and Kellmann, M. and Wippert, Pia-Maria},
  title     = {Psychosocial risk factors for chronic back pain in the general population and in competitive sports},
  series = {Der Schmerz : Organ der Deutschen Gesellschaft zum Studium des Schmerzes, der {\"O}sterreichischen Schmerzgesellschaft und der Deutschen Interdisziplin{\"a}ren Vereinigung f{\"u}r Schmerztherapie},
  volume    = {32},
  journal   = {Der Schmerz : Organ der Deutschen Gesellschaft zum Studium des Schmerzes, der {\"O}sterreichischen Schmerzgesellschaft und der Deutschen Interdisziplin{\"a}ren Vereinigung f{\"u}r Schmerztherapie},
  number    = {4},
  publisher = {Springer},
  address   = {Heidelberg},
  issn      = {0932-433X},
  doi       = {10.1007/s00482-018-0307-5},
  pages     = {259 -- 273},
  year      = {2018},
  abstract  = {Lumbar back pain and the high risk of chronic complaints is not only an important health concern in the general population but also in high performance athletes. In contrast to non-athletes, there is a lack of research into psychosocial risk factors in athletes. Moreover, the development of psychosocial screening questionnaires that would be qualified to detect athletes with a high risk of chronicity is in the early stages. The purpose of this review is to give an overview of research into psychosocial risk factors in both populations and to evaluate the performance of screening instruments in non-athletes. The databases MEDLINE, PubMed, and PsycINFO were searched from March to June 2016 using the keywords "psychosocial screening", "low back pain", "sciatica" and "prognosis", "athletes". We included prospective studies conducted in patients with low back pain with and without radiation to the legs, aged ae<yen>18 years and a follow-up of at least 3 months. We identified 16 eligible studies, all of them conducted in samples of non-athletes. Among the most frequently published screening questionnaires, the A-rebro Musculoskeletal Pain Screening Questionnaire (A-MPSQ) demonstrated a sufficient early prediction of return to work and the STarT Back Screening Tool (SBT) revealed acceptable performance predicting pain-related impairment. The prediction of future pain was sufficient with the Risk Analysis of Back Pain Chronification (RISC-BP) and the Heidelberg Short Questionnaire (HKF). Psychosocial risk factors of chronic back pain, such as chronic stress, depressive mood, and maladaptive pain processing are becoming increasingly more recognized in competitive sports. Screening instruments that have been shown to be predictive in the general population are currently being tested for suitability in the German MiSpEx research consortium.},
  language  = {en}
}
@misc{FliesserDeWittHubertsWippert2018,
  author    = {Fliesser, Michael and De Witt Huberts, Jessie and Wippert, Pia-Maria},
  title     = {The choice that matters: the relative influence of socioeconomic status indicators on chronic back pain},
  series = {Postprints der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Humanwissenschaftliche Reihe},
  number    = {377},
  issn      = {1866-8364},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-407422},
  year      = {2018},
  abstract  = {Background In health research, indicators of socioeconomic status (SES) are often used interchangeably and often lack theoretical foundation. This makes it difficult to compare results from different studies and to explore the relationship between SES and health outcomes. To aid researchers in choosing appropriate indicators of SES, this article proposes and tests a theory-based selection of SES indicators using chronic back pain as a health outcome. Methods Strength of relationship predictions were made using Brunner \& Marmot's model of 'social determinants of health'. Subsequently, a longitudinal study was conducted with 66 patients receiving in-patient treatment for chronic back pain. Sociodemographic variables, four SES indicators (education, job position, income, multidimensional index) and back pain intensity and disability were obtained at baseline. Both pain dimensions were assessed again 6 months later. Using linear regression, the predictive strength of each SES indicator on pain intensity and disability was estimated and compared to the theory based prediction. Results Chronic back pain intensity was best predicted by the multidimensional index (beta = 0.31, p < 0.05), followed by job position (beta = 0.29, p < 0.05) and education (beta = -0.29, p < 0.05); whereas, income exerted no significant influence. Back pain disability was predicted strongest by education (beta = -0.30, p < 0.05) and job position (beta = 0.29, p < 0.05). Here, multidimensional index and income had no significant influence. Conclusions The choice of SES indicators influences predictive power on both back pain dimensions, suggesting SES predictors cannot be used interchangeably. Therefore, researchers should carefully consider prior to each study which SES indicator to use. The introduced framework can be valuable in supporting this decision because it allows for a stable prediction of SES indicator influence and their hierarchy on a specific health outcomes.},
  language  = {en}
}
@article{FliesserDeWittHubertsWippert2017,
  author    = {Fliesser, Michael and De Witt Huberts, Jessie and Wippert, Pia-Maria},
  title     = {The choice that matters: the relative influence of socioeconomic status indicators on chronic back pain},
  series = {BMC health services research},
  volume    = {17},
  journal   = {BMC health services research},
  publisher = {BioMed Central},
  address   = {London},
  issn      = {1472-6963},
  doi       = {10.1186/s12913-017-2735-9},
  year      = {2017},
  abstract  = {Background In health research, indicators of socioeconomic status (SES) are often used interchangeably and often lack theoretical foundation. This makes it difficult to compare results from different studies and to explore the relationship between SES and health outcomes. To aid researchers in choosing appropriate indicators of SES, this article proposes and tests a theory-based selection of SES indicators using chronic back pain as a health outcome. Methods Strength of relationship predictions were made using Brunner \& Marmot's model of 'social determinants of health'. Subsequently, a longitudinal study was conducted with 66 patients receiving in-patient treatment for chronic back pain. Sociodemographic variables, four SES indicators (education, job position, income, multidimensional index) and back pain intensity and disability were obtained at baseline. Both pain dimensions were assessed again 6 months later. Using linear regression, the predictive strength of each SES indicator on pain intensity and disability was estimated and compared to the theory based prediction. Results Chronic back pain intensity was best predicted by the multidimensional index (beta = 0.31, p < 0.05), followed by job position (beta = 0.29, p < 0.05) and education (beta = -0.29, p < 0.05); whereas, income exerted no significant influence. Back pain disability was predicted strongest by education (beta = -0.30, p < 0.05) and job position (beta = 0.29, p < 0.05). Here, multidimensional index and income had no significant influence. Conclusions The choice of SES indicators influences predictive power on both back pain dimensions, suggesting SES predictors cannot be used interchangeably. Therefore, researchers should carefully consider prior to each study which SES indicator to use. The introduced framework can be valuable in supporting this decision because it allows for a stable prediction of SES indicator influence and their hierarchy on a specific health outcomes.},
  language  = {en}
}