Fatigue: Biomedicine, Health & Behavior - Volume 4, Issue 1, 2016

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Titles and abstracts for the journal, Fatigue: Biomedicine, Health & Behavior, Volume 4, Issue 1, 2016.

Volume 4, Issue 1, 2016[edit | edit source]

  • Case definitions integrating empiric and consensus perspectives (Full text)

    Abstract - Background: There has been considerable controversy regarding how to name and define the illnesses known as myalgic encephalomyelitis (ME) and chronic fatigue syndrome (CFS). The Institute of Medicine (IOM) report has proposed new clinical criteria and a new name for this illness, but aspects of these recommendations have been scrutinized by patients and scientists. Purpose: It is possible that both empiric and consensus approaches could be used to help settle some of these diagnostic challenges. Using patient samples collected in the USA, Great Britain, and Norway (N = 556), the current study attempted to categorize patients using more general as well as more restricted case definitions. Results: Overall, the outcomes suggest that there might be four groupings of patients, with the broadest category involving those with chronic fatigue (N = 62), defined by six or more months of fatigue which cannot be explained by medical or psychiatric conditions. A second category involves those patients who have chronic fatigue that can be explained by a medical or psychiatric condition (N = 47). A third category involves more specific criteria that have been posited both by the IOM report, Canadian Clinical Case criteria, ME-ICC criteria and a more empiric approach. These efforts have specified domains of substantial reductions of activity, post-exertional malaise, neurocognitive impairment, and sleep dysfunction (N = 346). Patients with these characteristics were more functionally impaired than those meeting just chronic fatigue criteria, p < .05. Finally, those meeting even more restrictive ME criteria proposed by Ramsay, identified a smaller and even more impaired group, p < .05. Conclusion: It is important that scientists world-wide develop consensus on how to identify and classify patients using clinical and research criteria, and ultimately develop subtypes within such categories.[1]

  • In-depth review of five fatigue measures in shift workers (Full text)

    Abstract - Background: Occupational fatigue is commonly reported in shift-working populations. In the literature, there are several well-known fatigue measures that are regularly used to assess either general or specific aspects of employee fatigue. Purpose: The purpose of this paper was to provide an in-depth review of five fatigue instruments frequently used in occupational science over the past two decades. These instruments are: the Checklist Individual Strength, the Fatigue Assessment Scale, the Need for Recovery, the Occupational Fatigue Exhaustion Recovery, and the Swedish Occupational Fatigue Inventory scales. We describe each instrument in detail, including how it was developed and validated, how it can be obtained, psychometric data, and its use in occupational studies. Conclusion: These instruments provide an understanding of fatigue either as a unidimensional or multidimensional construct. Overall, the five measures are brief (10–20 items), user-friendly, and have minimal respondent and administrative burden. They are reliable and valid based on the psychometric studies in the working population. Each measure has the potential to be utilized as a surveillance tool in monitoring employee fatigue and ensuring workplace safety. Selecting one or combination of these measures depends on the researcher's conceptual and operational definitions of fatigue, and the study objectives.[2]

  • Current therapeutic strategies for myalgic encephalomyelitis/chronic fatigue syndrome: results of an online survey (Full text)

    Abstract - Background: The treatment of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) symptoms poses significant challenges. Purpose: To enumerate current clinical treatment strategies for ME/CFS. Methods: A survey was deployed via the Internet to eleven expert clinicians in ME/CFS. The experts rated medications for 18 symptoms and listed symptom groups that they considered as interrelated and representative of different ME/CFS phenotypes. Respondents rated drug efficacy on an ordinal scale (1 = very effective to 5 = not effective). Free text was also permitted to comment on treatment strategies and ME/CFS phenotypes. Results: Data were available for 11/20 respondents. Citalopram was reported to be more than moderately effective for depression/anxiety and similarly fentanyl for muscle aches and arthralgias. Low-dose stimulants and low-dose bupriopion were viewed as effective for fatigue by five respondents. Regarding ME/CFS phenotypes, respondents suggested that (a) sleep improvement can ameliorate post-exertional malaise, pain and headache, (b) treatment of orthostatic intolerance can improve fatigue, light headedness, mental fog, headache and pain, while (c) epigastric pain, reflux, and early satiety may suggest nutritional hypersensitivity. Conclusion: The views of ME/CFS experts regarding treatment strategies and drug efficacy can aid clinicians in the optimization of their practices, and perhaps can steer ME/CFS research in directions that hold promise.[3]

  • Comparing the DePaul Symptom Questionnaire with physician assessments: a preliminary study (Full text)

    Abstract - Background: Diagnostic assessment of chronic fatigue syndrome (CFS) and myalgic encephalomyelitis (ME) is largely based on a two part process; screening patients who might meet criteria and following up this assessment with physicians’ clinical evaluation of a range of inclusionary symptoms and exclusionary illnesses. Purpose: The aim was to assess how well the DePaul Symptom Questionnaire (DSQ) screened for patients who were ultimately diagnosed by physicians using the Canadian Consensus Criteria (CCC). Methods: Sixty-four patients referred for evaluation of possible CFS or ME were screened initially using the DSQ, and then evaluated and subsequently diagnosed by physicians. To assess the consistency between the self-report DSQ and the physicians’ diagnosis, sensitivity and specificity as well as predictive values were calculated. Results: The DSQ identified 60 and the physicians identified 56 as having a CCC diagnosis. The overall agreement between the two ratings on the diagnostic assessment part was moderate (Kappa = 0.45, p < .001). The sensitivity of DSQ was good (98%) while the specificity was 38%. Positive and negative predictive values were 92% and 75%, respectively. Conclusion: DSQ is useful for detecting and screening symptoms consistent with a CCC diagnosis in clinical practice and research. However, it is important for initial screening of self-report symptoms to be followed up by subsequent medical and psychiatric examination in order to identify possible exclusionary medical and psychiatric disorders.[4]

See also[edit | edit source]

References[edit | edit source]

  1. Jason, L.A.; McManimen, S.; Sunnquist, Madison; Brown, A.; Furst, J.; Newton, J.L.; Strand, E.B. (2016). "Case definitions integrating empiric and consensus perspectives". Fatigue: Biomedicine, Health & Behavior. 4 (1): 1-23. doi:10.1080/21641846.2015.1124520. PMC 4831204. PMID 27088059.
  2. Sagherian, Knar; Geiger Brown, Jeanne (January 2, 2016). "In-depth review of five fatigue measures in shift workers". Fatigue: Biomedicine, Health & Behavior. 4 (1): 24–38. doi:10.1080/21641846.2015.1124521. ISSN 2164-1846.
  3. Deftereos, Spyros N.; Vernon, SuzanneD.; Persidis, Andreas (January 2, 2016). "Current therapeutic strategies for myalgic encephalomyelitis/chronic fatigue syndrome: results of an online survey". Fatigue: Biomedicine, Health & Behavior. 4 (1): 39–51. doi:10.1080/21641846.2015.1126025. ISSN 2164-1846.
  4. Strand, Elin B.; Lillestøl, Kristine; Jason, Leonard A.; Tveito, Kari; Diep, Lien My; Valla, Simen Strand; Sunnquist, Madison; Helland, Ingrid B.; Dammen, Toril (2016). "Comparing the DePaul Symptom Questionnaire with physician assessments: a preliminary study". Fatigue: Biomedicine, Health & Behavior. 4 (1): 52-62. doi:10.1080/21641846.2015.1126026.