Blog

  • Association of lung field area with mortality in Mycobacterium avium complex lung disease: a longitudinal cohort study | BMC Infectious Diseases

    Association of lung field area with mortality in Mycobacterium avium complex lung disease: a longitudinal cohort study | BMC Infectious Diseases

    Study design and participants

    This study was conducted as a longitudinal cohort study through a retrospective review of medical records at NHO Fukuoka National Hospital. We reviewed 288 patients aged ≥ 20 years who met the American Thoracic Society/Infectious Diseases Society of America (ATS/IDSA) diagnostic criteria for MAC lung disease between April 1, 1996, and December 31, 2021 [6]. Of these, we excluded 42 patients with no available data of chest computed tomography (CT) scans between June 1, 2017, and December 31, 2021, 4 patients whose CT image data were unable to be processed for the present analysis by the software, 2 patients without any follow-up medical records after the date of CT scanning, 1 patient with no information concerning smoking history, and 7 patients without body mass index (BMI) data. Hence, the remaining 232 subjects with MAC lung disease were enrolled in the present study (Fig. 1). When multiple CT scans were available during the 2017–2021 period, the earliest scan was used for analysis. The follow-up period was defined as the time from the CT scan to either July 2023 or a maximum of 5 years.

    Fig. 1

    Quantitative CT image analysis

    CT examinations were performed with a 160-slice multidetector CT scanner (Aquilion Lightning, Canon Medical Systems, Otawara, Japan) with a slice thickness of 5 mm. Quantitative CT image analyses were performed using dedicated software (AZE Virtual Place, Canon Medical Systems, Otawara, Japan) by a radiologic technologist without prior knowledge of the clinical data. For each patient, the lung field areas (LFAs) were evaluated separately in six domains using three axial CT slices in accordance with the Goddard score assessment protocols—the levels of the upper margin of the aortic arch (right and left upper lung field), the carina (right and left middle lung field), and 1–3 cm above the top of the diaphragm (right and left lower lung field) [13]. To identify the extent of cavitary destruction of the lung, the low-attenuation areas (LAAs) were defined as lung areas below − 950 Hounsfield units (HU), as in previous literature [14], and were also semiautomatically estimated using the same images (see Fig. S1 in Additional file 1) [15]. Mean values of LFA and LAA were calculated and used for the present analyses. The LFA/LAA ratio was computed for each of the six lung fields, and the average of these six values was used in the analysis. When dividing the study subjects into three groups based on the tertile distribution of the mean LFA, the cutoff values were as follows: lowest, ≤ 69.54 cm2 (N = 78); middle, 69.55–85.59 cm2 (N = 77); and highest, ≥ 85.60 cm2 (N = 77). For validation analysis between the mean values of LFA and lung volume (LV), a total of 9 subjects were randomly selected in order to assess LV. LV was calculated with the following 3 steps: at first, the lung plus bronchus volume (LBV) was identified by extracting the area less than − 500 HU. Next, the bronchus volume (BV) was measured by extracting the area less than − 920 HU and by ensuring the continuity of connection to other bronchi. Lastly, the LV was calculated by subtracting the BV from the LBV.

    Clinical evaluations

    For each case, respiratory physicians reviewed the patient’s medical records and assessed the demographic and clinical characteristics: age, gender, height, weight, smoking history, medical history, and results of mycobacterial cultures. BMI (kg/m2) was calculated as weight divided by squared height. Smoking habit was dichotomized as never smokers and smokers, considering that smoking could have affected emphysematous changes of the lung, appearing as low-attenuation areas (< −950 HU). Antibiotic treatment for MAC disease was defined as the prescription of clarithromycin and/or rifampicin and/or ethambutol. MAC species were categorized into three groups: M. avium group, Mycobacterium intracellulare (M. intracellulare) group, and co-infection group (subjects with both M. avium and M. intracellulare detected).

    Statistical analysis

    R software version 4.1.2 (R Foundation for Statistical Computing, Vienna, Austria) was used to perform all statistical analyses. A two-sided P < 0.05 was considered to indicate statistical significance. For baseline characteristics, the heterogeneity in each variable among the levels of mean LFA was evaluated using the analysis of variance (ANOVA), chi-square test, or Kruskal–Wallis test. Pearson’s correlation coefficient was calculated to assess the correlation between the mean values of LFA and those of LV. Kaplan–Meier curves were constructed to show the survival rate over the follow-up period. The unadjusted and multivariable-adjusted hazard ratios (HRs) with their 95% confidence intervals (95% CIs) according to the levels of mean LFA for all-cause mortality were estimated using a Cox proportional hazards model. Adjustments were made for age, gender, BMI, smoking history, MAC treatment, MAC species, co-infection with NTM other than MAC, and mean LAA, which has been reported as a potential prognostic factor in patients with NTM lung disease [16, 17]. Relevant models were used to evaluate the linear trends in the risk of all-cause death across the tertile classification of mean LFA. We evaluated the ability of mean LFA and mean LAA to predict mortality using receiver operating characteristic curves and estimated the area under the curve (AUC) for each. The AUCs were compared using the DeLong method. The robustness of the main results was tested through sensitivity analyses limiting the subjects to M. avium-positive or M. intracellulare-positive cases individually. Since smoking exposure can accelerate emphysematous change and increase the value of LAA in the lung, stratified analysis was performed by smoking status.

    Ethical considerations

    The study was approved by the NHO Fukuoka National Hospital Institutional Review Board for Clinical Research (#F5-34). For this study, informed consent has been waived by the NHO Fukuoka National Hospital Institutional Review Board due to the anonymity and retrospective nature of the study. This study was conducted according to the principles of the Declaration of Helsinki.

    Continue Reading

  • Baby’s birthweight increases risk of cardiovascular disease in preeclamptic and hypertensive women

    Baby’s birthweight increases risk of cardiovascular disease in preeclamptic and hypertensive women

    A new study shows that preeclamptic and hypertensive pregnant women’s risk of getting cardiovascular disease is linked to their baby’s birthweight.

    Preeclampsia and other hypertensive disorders of pregnancy (HDPs) are serious…

    Continue Reading

  • Baby’s birthweight increases risk of cardiovascular disease in preeclamptic and hypertensive women

    Baby’s birthweight increases risk of cardiovascular disease in preeclamptic and hypertensive women

    A new study shows that preeclamptic and hypertensive pregnant women’s risk of getting cardiovascular disease is linked to their baby’s birthweight.

    Preeclampsia and other hypertensive disorders of pregnancy (HDPs) are serious…

    Continue Reading

  • Professional quality of life is related to emotional intelligence, self-care, and work conditions in healthcare workers: findings from a moderated mediation analysis | BMC Health Services Research

    Professional quality of life is related to emotional intelligence, self-care, and work conditions in healthcare workers: findings from a moderated mediation analysis | BMC Health Services Research

  • Stamm HB. Professional quality of life: compassion satisfaction and fatigue. Pocadello. 2010. https://proqol.org/.

  • Sacco TL, Copel LC. Compassion satisfaction: a concept analysis in nursing. Nurs Forum. 2018;53(1):76–83. https://doi.org/10.1111/nuf.12213.

    Article 
    PubMed 

    Google Scholar 

  • Youn H, Lee M, Jang SJ. Person-centred care among intensive care unit nurses: a cross-sectional study. Intensive And Crit Care Nurs. 2022;73:103293. https://doi.org/10.1016/j.iccn.2022.103293.

    Article 

    Google Scholar 

  • Zhang Y-Y, Han W-L, Qin W, Yin H-X, Zhang C-F, Kong C, Wang Y-L. Extent of compassion satisfaction, compassion fatigue and burnout in nursing: a meta-analysis. J Nurs Manag. 2018;26(7):810–19. https://doi.org/10.1111/jonm.12589.

    Article 
    PubMed 

    Google Scholar 

  • Figley CR. Compassion fatigue: Toward a new understanding of the costs of caring. In secondary traumatic stress: self-care issues for clinicians, researchers, & educators. Vol. 2nd. Sidran Press; 1995. p. 3–28.

    Google Scholar 

  • Joinson C. Coping with compassion fatigue. Nursing. 1992;22(4):116, 118–119, 120.

    PubMed 

    Google Scholar 

  • Peters E. Compassion fatigue in nursing: a concept analysis. Nurs Forum. 2018;53(4):466–80. https://doi.org/10.1111/nuf.12274.

    Article 
    PubMed 

    Google Scholar 

  • Sinclair S, Raffin-Bouchal S, Venturato L, Mijovic-Kondejewski J, Smith-MacDonald L. Compassion fatigue: a meta-narrative review of the healthcare literature. Int J Nurs Stud. 2017;69:9–24. https://doi.org/10.1016/j.ijnurstu.2017.01.003.

    Article 
    PubMed 

    Google Scholar 

  • Sorenson C, Bolick B, Wright K, Hamilton R. An evolutionary concept analysis of compassion fatigue. J Nurs Scholarsh. 2017;49(5):557–63. https://doi.org/10.1111/jnu.12312.

    Article 
    PubMed 

    Google Scholar 

  • Garnett A, Hui L, Oleynikov C, Boamah S. Compassion fatigue in healthcare providers: a scoping review. BMC Health Serv Res. 2023;23(1):1336. https://doi.org/10.1186/s12913-023-10356-3.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Sorenson C, Bolick B, Wright K, Hamilton R. Understanding compassion fatigue in healthcare providers: a review of current literature. J Nurs Scholarsh. 2016;48(5):456–65. https://doi.org/10.1111/jnu.12229.

    Article 
    PubMed 

    Google Scholar 

  • Maslach C, Jackson SE. The measurement of experienced burnout. J Organizational Behav. 1981;2(2):99–113.

    Article 

    Google Scholar 

  • Maslach C, Schaufeli WB, Leiter MP. Job Burnout. 2001;52:397–422. https://doi.org/10.1146/annurev.psych.52.1.397.

    Article 

    Google Scholar 

  • Bianchi R, Truchot D, Laurent E, Brisson R, Schonfeld I. Is burnout solely job-related? A critical comment. Scand J Psychol. 2014;55:357–61. https://doi.org/10.1111/sjop.12119.

    Article 
    PubMed 

    Google Scholar 

  • Demerouti E, Bakker AB, Peeters MCW, Breevaart K. New directions in burnout research. Eur J Work Organ Psy. 2021;30(5):686–91. https://doi.org/10.1080/1359432X.2021.1979962.

    Article 

    Google Scholar 

  • Edu-Valsania S, Laguia A, Moriano J. Burnout: a review of theory and measurement. Int J Environ Res Pub Health And Public Health. 2022, (1780;19. https://doi.org/10.3390/ijerph19031780.

  • Maslach C, Leiter MP. Understanding the burnout experience: Recent research and its implications for psychiatry. World Pscychiatry. 2016;15:103–11. https://doi.org.ezproxy.brunel.ac.uk/10.1002/wps.20311

  • Cavanagh N, Cockett G, Heinrich C, Doig L, Fiest K, Guichon JR, Page S, Mitchell I, Doig CJ. Compassion fatigue in healthcare providers: a systematic review and meta-analysis. Nurs Ethics. 2020;27(3):639–65. https://doi.org/10.1177/0969733019889400.

    Article 
    PubMed 

    Google Scholar 

  • Maillet S, Read E. Work environment characteristics and emotional intelligence as correlates of nurses’ compassion satisfaction and compassion fatigue: a cross-sectional survey study. Nurs Rep. 2021;11(4):847–58. https://doi.org/10.3390/nursrep11040079.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Xie W, Chen L, Feng F, Okoli CTC, Tang P, Zeng L, Jin M, Zhang Y, Wang J. The prevalence of compassion satisfaction and compassion fatigue among nurses: a systematic review and meta-analysis. Int J Nurs Stud. 2021;120:103973. https://doi.org/10.1016/j.ijnurstu.2021.103973.

    Article 
    PubMed 

    Google Scholar 

  • Leo CG, Sabina S, Tumolo MR, Bodini A, Ponzini G, Sabato E, Mincarone P. Burnout among healthcare workers in the COVID 19 era: a review of the existing literature. Front Public Health. 2021;9. https://www.frontiersin.org/articles/10.3389/fpubh.2021.750529.

  • Zhang X, Song Y, Jiang T, Ding N, Shi T. Interventions to reduce burnout of physicians and nurses: an overview of systematic reviews and meta-analyses. Med (baltim). 2020;99(26). https://journals.lww.com/md-journal/fulltext/2020/06260/interventions_to_reduce_burnout_of_physicians_and.89.aspx.

  • De Simone S, Vargas M, Sevillo G. Organizational strategies to reduce physician burnout: a systematic review and meta-analysis. Aging Clin Exp Res. 2021;33(4):883–94. https://doi.org.ezproxy.brunel.ac.uk/10.1007/s40520-019-01368-3 .

  • DeChant PF, Acs A, Rhee KB, Boulanger TS, Snowdon JL, Tutty MA, Sinsky CA, Craig KJT. Effect of organization-directed workplace interventions on Physician burnout: a systematic review. Mayo Clinic Proc: Innovations, Qual & Outcomes. 2019;3(4):384–408. https://doi.org/10.1016/j.mayocpiqo.2019.07.006.

    Article 

    Google Scholar 

  • Fox S, Lydon S, Byrne D, Madden C, Connolly F, O’Connor P. A systematic review of interventions to foster physician resilience. Postgrad Med J. 2018;94(1109):162–70. https://doi.org/10.1136/postgradmedj-2017-135212.

  • Panagioti M, Panagopoulou E, Bower P, Lewith G, Kontopantelis E, Chew-Graham C, Dawson S, van Marwijk H, Geraghty K, Esmail A. Controlled interventions to reduce burnout in physicians: a systematic review and meta-analysis. JAMA Intern Med. 2017;177(2):195–205. https://doi.org/10.1001/jamainternmed.2016.7674.

    Article 
    PubMed 

    Google Scholar 

  • Petrie K, Crawford J, Baker STE, Dean K, Robinson J, Veness BG, Randall J, McGorry P, Christensen H, Harvey SB. Interventions to reduce symptoms of common mental disorders and suicidal ideation in physicians: a systematic review and meta-analysis. Lancet Psychiatry. 2019;6(3):225–34. https://doi.org/10.1016/S2215-0366(18)30509-1.

    Article 
    PubMed 

    Google Scholar 

  • Coles E, Anderson J, Maxwell M, Harris FM, Gray NM, Milner G, MacGillivray S. The influence of contextual factors on healthcare quality improvement initiatives: a realist review. Systematic Rev. 2020;9(1):94. https://doi.org/10.1186/s13643-020-01344-3.

    Article 

    Google Scholar 

  • Chen C-C, Lan Y-L, Chiou S, Y-C. The effect of emotional labor on the physical and mental health of health professionals: emotional exhaustion has a mediating effect. Healthcare. 2023;11(1):104. https://doi.org/10.3390/healthcare11010104.

  • Maben J, Bridges J. Covid-19: Supporting nurses’ psychological and mental health. J Clin nursing. 2020;29(15–16):2742–50. https://doi.org/10.1111/jocn.15307.

    Article 

    Google Scholar 

  • Agler R, De Boeck P. On the interpretation and use of mediation: multiple perspectives on mediation analysis. Front psychol. 2017;8. https://doi.org/10.3389/fpsyg.2017.01984.

  • Rohlf VI, Scotney R, Monaghan H, Bennett P. Predictors of professional quality of life in veterinary professionals. J Vet Med Educ. 2022;49(3):372–81. https://doi.org/10.3138/jvme-2020-0144.

    Article 
    PubMed 

    Google Scholar 

  • Rohrer JM, Hünermund P, Arslan RC, Elson M. That’s a lot to process! Pitfalls of popular path models. Adv Met pract psychol Sci. 2022;5(2). https://doi.org/10.1177/25152459221095827.

  • Bronfenbrenner U. The ecology of human development. Harvard University Press; 1979.

    Book 

    Google Scholar 

  • Mayer JD, Salovey P. The intelligence of emotional intelligence. Intelligence. 1993;17:433–42.

    Article 

    Google Scholar 

  • Sarrionandia A, Mikolajzak. A meta-analysis of the possible behavioural and biological variables linking trait emotional intelligence to health. Health Psychol Rev. 2020;14(2):220–44. https://doi.org/10.1080/17437199.2019.1641423.

    Article 
    PubMed 

    Google Scholar 

  • Lea R, Davis SK, Mahoney B, Qualter P. Do emotionally intelligent adolescents flourish or flounder under pressure? Linking emotional intelligence to stress regulation mechanisms. Pers Indiv Differ. 2023;201:111943. https://doi.org/10.1016/j.paid.2022.111943.

    Article 

    Google Scholar 

  • Ma J, Zeng Z, Fang K. Emotionally savvy employees fail to enact emotional intelligence when ostracized. Pers Indiv Differ. 2022;185:111250. https://doi.org/10.1016/j.paid.2021.111250.

    Article 

    Google Scholar 

  • Pena-Sarrionandia A, Mikolajczak M, Gross JJ. Integrating emotion regulation and emotional intelligence traditions: a meta-analysis. Front psychol. 2015;6:article 160.

    Article 
    PubMed 

    Google Scholar 

  • Matarese M, Lommi M, Marinis MGD, Riegel B. A systematic review and integration of concept analyses of self-care and related concepts. J Nurs scholarsh. 2018;50(3):296–305. https://doi.org/10.1111/jnu.12385.

  • Riegel B, Dunbar SB, Fitzsimons D, Freedland KE, Lee CS, Middleton S, Stromber A, Vellone E, Webber DE, Jaarsma T. Self-care research: Where are we now? Where are we going? Int J Nurs Stud. 2021;116. https://doi-org.ezproxy.brunel.ac.uk/10.1016/j.ijnurstu.2019.103402.

  • Keesler JM, Troxel J. They care for others, but what about themselves? Understanding self-care among DSPs’ and its relationship to professional quality of life. Intellect Dev Disab. 2020;58(3):221–40. https://doi.org/10.1352/1934-9556-58.3.221.

    Article 

    Google Scholar 

  • Nogueiro J, Cañas-Lerma AJ, Cuartero-Castañer ME, Bolaños I. The professional quality of life and its relation to self-care in mediation professionals. Soc Work Soc Sci Rev. 2022;23:55–73. https://doi.org/10.1921/swssr.v23i1.1972.

    Article 

    Google Scholar 

  • Bermejo-Martins E, Luis EO, Fernandez-Berrocal P, Martinez M, Sarrionandia A. The role of emotional intelligence and self-care in the stress perception during COVID-19 outbreak: an intercultural moderated mediation analysis. Pers Indiv Differ. 2021;177:110679. https://doi.org/10.1016/j.paid.2021.110679.

    Article 

    Google Scholar 

  • Antonovsky A. Health, stress, and coping. Jossey-Bass; 1979.

    Google Scholar 

  • Antonovsky A. Unraveling the mystery of health: how people manage stress and stay well. Jossey-Bass; 1987.

    Google Scholar 

  • Zapf D, Kern M, Tschan F, Holman D, Semmer NK. Emotion work: A work psychology perspective. Annu Rev Organ Psychol Organ Behav. 2021;8(1):139–72.

    Article 

    Google Scholar 

  • Peacock A. Compassion satisfaction, compassion fatigue, and vicarious trauma. Nurs ManAge. 2023;54(1). https://journals.lww.com/nursingmanagement/fulltext/2023/01000/compassion_satisfaction,_compassion_fatigue,_and.4.aspx

  • Rivera-Kloeppel B, Mendenhall T. Examining the relationship between self-care and compassion fatigue in mental health professionals: a critical review. Traumatology. 2023;29(2):163.

    Article 

    Google Scholar 

  • Sansó N, Galiana L, Oliver A, Tomás-Salvá M, Vidal-Blanco G. Predicting professional quality of life and life satisfaction in Spanish nurses: a cross-sectional study. Int J Environ Res Pub Health and Public Health. 2020;17(12). https://doi.org/10.3390/ijerph17124366.

  • Kong F, Gong X, Sajjad S, Yang K, Zhao J. How is emotional intelligence linked to life satisfaction? The mediating role of social support, positive affect and negative affect. J Retailing Happoness Stud. 2019;20:2733–45. https://doi.org/10.1007/s10902-018-00069-4.

    Article 

    Google Scholar 

  • Harris JI, Winskowski AM, Engdahl BE. Types of workplace social support in the prediction of job satisfaction. The Career Devel Q. 2007;56(2):150–56. https://doi.org/10.1002/j.2161-0045.2007.tb00027.x.

    Article 

    Google Scholar 

  • Browning BR, McDermott RC, Scaffa ME. Transcendent characteristics as predictors of Counselor professional quality of life. J Ment Health counselling. 2019;41(1):51–64. https://doi.org/10.17744/mehc.41.1.05.

    Article 

    Google Scholar 

  • Duarte J. Professional quality of life in nurses: contribution for the validation of the Portuguese version of the professional quality of life scale-5 (ProQOL-5). Analise PsicoLogica. 2017;35. https://doi.org/10.14417/ap.1260.

  • Tran ANP, To QG, Huynh V-AN, Le KM, To KG. Professional quality of life and its associated factors among Vietnamese doctors and nurses. BMC Health Serv Res. 2023;23(1):924. https://doi.org/10.1186/s12913-023-09908-4.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Yılmaz G, Üstün B. Sociodemographic and professional factors influencing the professional quality of life and post-traumatic growth of oncology nurses*. J Psychiatr Nurs. 2019;10(4):241–50. https://doi.org/10.14744/phd.2019.43255.

    Article 

    Google Scholar 

  • Ball HL. Conducting online surveys. J Hum LAct. 2019;35(3):413–17. https://doi.org/10.1177/0890334419848734.

    Article 
    PubMed 

    Google Scholar 

  • Thompson CB, Panacek EA. Research study designs: Non-experimental. Air Med J. 2007;26(1):18–22. https://doi.org/10.1016/j.amj.2006.10.003.

    Article 
    PubMed 

    Google Scholar 

  • Vogt WP. The dictatorship of the problem: Choosing research methods. Methodol Innov Online. 2008;3(1):1–17. https://doi.org/10.4256/mio.2008.0006.

    Article 

    Google Scholar 

  • NSW Government. NSW health workforce Data. 2023. https://www.psc.nsw.gov.au/assets/psc/PSC-2023-Workforce-Profile-Report.pdf. NSW Public Commission.

  • Galiana L, Oliver A, Arena F, Simone GD, Tomas JM, Vidal-Blanco G, Munoz-Martinez I, Sanso N. Development and validation of the short professional quality of life scale based on versions IV and V of the professional quality of life scale. Health And Qual Of Life Outcomes. 2020;18:364. https://doi.org/10.1186/s12955-020-01618-3.

    Article 

    Google Scholar 

  • Wong C-S, Law KS. The effects of leader and follower emotional intelligence on performance and attitude: an exploratory study. Leadersh Q. 2002;13(3):243–74. https://doi.org.ezproxy.brunel.ac.uk/10.1016/S1048-9843(02)00099-1

  • Lee J, Miller SE, Bride BE. Development and initial validation of the self-care practices scale. Soc Work. 2020;65(1):21–28. https://doi.org.ezproxy.brunel.ac.uk/10.1093/sw/swz045.

  • Cook-Cottone CP, Guyker WM. The development and validation of the mindful self-care scale (MSCS): An assessment of practices that support positive embodiment. Mindfulness. 2018;9:161–75.

    Article 

    Google Scholar 

  • Li Q, Xu L, Wang Y, Zhu Y, Huang Y. Exploring the self-care practices of social workers in China under the COVID-19 pandemic. Soc Work And Policy. 2022;16(3):265–74. https://doi.org.ezproxy.brunel.ac.uk/10.1111/aswp.12266

  • Bloomquist K, Wood L, Friedmeyer-Trainor K, Kim H-W. Self-care and professional quality of life: Predictive factors among MSW practitioners. Adv Soc Work. 2015;16(2):292–311. https://doi.org/10.18060/18760.

  • Bur H, Bethelsen H, Moncada S, Nubling M, Dupre E, Demiral Y, Oudyk J, Kristensen TS, Llorens C, Navarro A, Lincke H-J, Bocerean C, Sahan S, Prhrt P, A., Copsoq Network I. The third version of the Copenhagen psychosocial questionnaire. Saf Health Work. 2019;10(4):482–503. https://doi.org/10.1016/j.shaw.2019.10.002.

    Article 

    Google Scholar 

  • Hayes AF. Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. 3rd. The Guilford Press; 2022. https://ebookcentral.proquest.com/lib/jcu/detail.action?docID=6809031.

    Google Scholar 

  • Hayes AF, Coutts JJ. Use omega rather than Cronbach’s alpha for estimating reliability. But …. Commun Methods and measures. 2020;14(1):1–24. https://doi.org/10.1080/19312458.2020.1718629.

    Article 

    Google Scholar 

  • Kalkbrenner MT. Alpha, omega, and H internal consistency reliability estimates: Reviewing these options and when to use them. Couns Outcome Res And evaluation. 2023;14(1):77–88. https://doi.org/10.1080/21501378.2021.1940118.

    Article 

    Google Scholar 

  • Hayes AF. Partial, conditional, and moderated moderated mediation: Quantification, inference, and interpretation. Commun Monogr. 2018;85(1):4–40. https://doi.org/10.1080/03637751.2017.1352100.

    Article 

    Google Scholar 

  • Ma J, Zeng Z, Fang K. Emotionally savvy employees fail to enact emotional intelligence when ostracized. Pers Indiv Differ. 2021;185:111250. https://doi.org/10.1016/j.paid.2021.111250.

    Article 

    Google Scholar 

  • Singh J, Karanika-Murray M, Baguley T, Hudson J. A systematic review of job demands and resources associated with compassion fatigue in mental health professionals. Int J Environ Res Pub Health And Public Health. 2020;17(19). https://doi.org/10.3390/ijerph17196987.

  • Kim HJ, Hur W-M, Moon T-W, Jun J-K. Is all support equal? The moderating effects of Supervisor, coworker, and organizational support on the link between emotional labor and job performance. BRQ Bus Res Q. 2017;20(2):124–36. https://doi.org/10.1016/j.brq.2016.11.002.

    Article 

    Google Scholar 

  • Ormiston HE, Nygaard MA, Apgar S. A systematic review of secondary traumatic stress and compassion fatigue in teachers. Sch Ment Health. 2022;14(4):802–17. https://doi.org/10.1007/s12310-022-09525-2.

    Article 

    Google Scholar 

  • Hunsaker S, Chen H-C, Maughan D, Heaston S. Factors that influence the development of compassion fatigue, burnout, and compassion satisfaction in emergency department nurses. J Nurs scholarsh. 2015;47(2):186–94. https://doi.org/10.1111/jnu.12122.

    Article 
    PubMed 

    Google Scholar 

  • Sanchez-Gomez M, Sadovyy M, Breso E. Health-care professionals amid the COVID-19 Pandemic: how emotional intelligence may enhance work performance traversing the mediating role of work engagement. J Clin Med. 2021;10(18). https://doi.org/10.3390/jcm10184077.

  • Alonazi WB. The impact of emotional intelligence on job performance during COVID-19 crisis: a cross-sectional analysis. Phychol Res Behav Manag. 2020;13(null):749–57. https://doi.org/10.2147/PRBM.S263656.

    Article 

    Google Scholar 

  • Mackay SJ, Baker R, Collier D, Lewis S. A comparative analysis of emotional intelligence in the UK and Australian radiographer workforce. Radiography. 2013;19(2):151–55. https://doi.org/10.1016/j.radi.2012.11.005.

    Article 

    Google Scholar 

  • Shah DK. WLEIS as a measure of emotional intelligence of healthcare professionals: a confirmatory factor analysis. J Health Manag. 2022;24(2):268–74. https://doi.org/10.1177/09720634221088057.

    Article 

    Google Scholar 

  • Sun H, Wang S, Wang W, Han G, Liu Z, Wu Q, Pang X. Correlation between emotional intelligence and negative emotions of front-line nurses during the COVID-19 epidemic: a cross-sectional study. J Clin nursing. 2021;30(3–4):385–96. https://doi.org/10.1111/jocn.15548.

    Article 

    Google Scholar 

  • Weng H-C, Hung C-M, Liu Y-T, Cheng Y-J, Yen C-Y, Chang C-C, Huang C-K. Associations between emotional intelligence and doctor burnout, job satisfaction and patient satisfaction. Med Educ. 2011;45(8):835–42. https://doi.org/10.1111/j.1365-2923.2011.03985.x.

    Article 
    PubMed 

    Google Scholar 

  • Bhullar N, Schutte NS, Malouff JM. Associations of individualistic-collectivistic orientations with emotional intelligence, mental health, and satisfaction with life: a tale of two countries. Individual Differences Res. 2012;10(3).

  • Gunkel M, Schlagel C, Engle RL. Culture’s influence on emotional intelligence: An empirical study of nine countries. J Int Manag. 2014;20:256–74. https://doi.org/10.1016/j.intman.2013.10.002.

    Article 

    Google Scholar 

  • Foster K, Fethney J, McKenzie H, Fisher M, Harkness E, Kozlowski D. Emotional intelligence increases over time: A longitudinal study of Australian pre-registration nursing students. Nurse Educ Today. 2017;55:65–70. https://doi.org/10.1016/j.nedt.2017.05.008.

    Article 
    PubMed 

    Google Scholar 

  • Cary H. A review of factors influencing employee retention within the HealthCare workforce. 2024.

  • Sybert QM. Healthcare workers with attitude: COVID-19 Pandemic affects their Work-related attitudes. 2024.

  • Weidman AJ. Establishing a sustainable healthcare delivery workforce in the wake of COVID-19. J Health Care Manag. 2022;67(4):234–43. https://doi.org/10.1097/JHM-D-22-00100.

    Article 
    PubMed 

    Google Scholar 

  • Bandura A. Social foundations of thought and action: a social cognitive theory. Prentice-Hall, Inc; 1986. p. xiii, 617.

    Google Scholar 

  • Goncher ID, Sherman MF, Barnett JE, Haskins D. Programmatic perceptions of self-care emphasis and quality of life among graduate trainees in clinical psychology: The mediational role of self-care utilization. Train And Educ In Profesional Phychol. 2013;7(1):53–60. https://doi.org/10.1037/a0031501.

    Article 

    Google Scholar 

  • Eaves T, Mauldin L, Megan CB, Robinson JL. The professional is the personal: A qualitative exploration of self-care practices in clinical infant mental health practitioners. J Soc Service Res. 2020;47(3):369–87. https://doi.org/10.1080/01488376.2020.1817228.

    Article 

    Google Scholar 

  • Zeidner M, Mathews G, Olenik Shemesh D. Cognitive-social sources of wellbeing: Differentiating the roles of coping style, social support and emotional intelligence. J Happiness Stud. 2016;17:2481–501. https://doi.org/10.1007/s10902-015-9703-z.

    Article 

    Google Scholar 

  • Cho H, Lee D. Effects of affective and cognitive empathy on compassion fatigue: Mediated moderation effects of emotion regulation capability. Pers Indiv Differ. 2023;211:112264. https://doi.org/10.1016/j.paid.2023.112264.

    Article 

    Google Scholar 

  • Huang X, Chan SCH, Lam W, Nan X. The joint effect of leader-member exchange and emotional intelligence on burnout and work performance in call centers in China. Int J Hum Resour MAn. 2010;21(7):1124–44. https://doi.org/10.1080/09585191003783553.

    Article 

    Google Scholar 

  • Psilopanagioti A, Anagnostopoulos F, Mourtou E, Niakas D. Emotional intelligence, emotional labor, and job satisfaction among physicians in Greece. BMC Health Serv Res. 2012;12(1):463. https://doi.org/10.1186/1472-6963-12-463.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Barnett MD, Hays KN, Cantu C. Compassion fatigue, emotional labor, and emotional display among hospice nurses. Death Stud. 2022;46(2):290–96. https://doi.org/10.1080/07481187.2019.1699201.

    Article 
    PubMed 

    Google Scholar 

  • Pekaar KA. Self- and other-focused emotional intelligence. 2019. http://hdl.handle.net/1765/116478.

  • Pekaar KA, Bakker AB, van der Linden D, Born MP. Self- and other-focused emotional intelligence: development and validation of the Rotterdam emotional intelligence scale (REIS). Pers Indiv Differ. 2018;120:222–33. https://doi.org/10.1016/j.paid.2017.08.045.

    Article 

    Google Scholar 

  • Asensio-Martínez Á, Leiter MP, Gascón S, Gumuchian S, Masluk B, Herrera-Mercadal P, Albesa A, García-Campayo J. Value congruence, control, sense of community and demands as determinants of burnout syndrome among hospitality workers. Int J Occup Saf Ergon. 2019;25(2):287–95. https://doi.org/10.1080/10803548.2017.1367558.

    Article 
    PubMed 

    Google Scholar 

  • Nahum-Shani I, Henderson MM, Lim S, Vinokur AD. Supervisor support: Does supervisor support buffer or exacerbate the adverse effects of supervisor undermining? J Appl psychol. 2014;99(3):484–503. https://doi.org/10.1037/a0035313.

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Kim N, Kang YJ, Choi J, Sohn YW. The crossover effects of Supervisors’ workaholism on subordinates’ turnover intention: the mediating role of two types of job demands and emotional exhaustion. Int J Environ Res Pub Health And Public Health. 2020;17(21):7742. https://doi.org/10.3390/ijerph17217742.

    Article 

    Google Scholar 

  • Tucker MK, Jimmieson NL, Bordia P. Supervisor support as a double-edged sword: Supervisor emotion management accounts for the buffering and reverse-buffering effects of supervisor support. Int J Stress Manag. 2018;25(1):14–34. https://doi.org/10.1037/str0000046.

    Article 

    Google Scholar 

  • Charoensukmongkol P, Moqbel M, Gutierrez-Wirsching S. The role of coworker and supervisor support on job burnout and job satisfaction. J Educ Chang Adv Manag Res. 2016;13(1). https://doi.org/10.1108/JAMR-06-2014-0037.

  • Gillet N, Morin AJ, Fouquereau E. A person-centered perspective on work behaviors. Curr Phychol. 2023;42(32):28527–48.

    Article 

    Google Scholar 

  • Choi JH, Miyamoto Y. Cultural differences in self-rated health: the role of influence and adjustment. Jpn Psychol Res. 2022;64(2):156–69. https://doi.org/10.1111/jpr.12405.

    Article 

    Google Scholar 

  • Eriksson M, Ghazinour M, Hammarström A. Different uses of Bronfenbrenner’s ecological theory in public mental health research: What is their value for guiding public mental health policy and practice? Soc Theor Health. 2018;16(4):414–33. https://doi.org/10.1057/s41285-018-0065-6.

    Article 

    Google Scholar 

  • NSW Government. (People matter, NSW Public Sector employee survey 2024, central coast local health district. 2024. https://files.dcu.nsw.gov.au/dpc/pmse2024/Health/Central%20Coast%20Local%20Health%20District.pdf.

Continue Reading

  • Explainer: Britain’s Prince Andrew and the sex scandal he cannot shrug off

    Explainer: Britain’s Prince Andrew and the sex scandal he cannot shrug off

    LONDON, Oct 21 (Reuters) – Britain’s Prince Andrew faced renewed scrutiny on Tuesday after the release of a posthumous memoir by Virginia Giuffre, one of the most prominent accusers of the late U.S. sex offender Jeffrey Epstein, which detailed…

    Continue Reading

  • The foldable iPhone is reportedly delayed: Here’s what we know so far

    The foldable iPhone is reportedly delayed: Here’s what we know so far

    Apple’s foldable iPhone, long rumored and eagerly awaited, could now arrive in 2027 pushing back expectations by a year. While whispers of delays have been around for some time, the latest reports point to hinge and design challenges as the…

    Continue Reading

  • Variations in initiation of first antenatal care among women of reproductive age in sub-Saharan Africa: an event history analysis approach | Reproductive Health

    Variations in initiation of first antenatal care among women of reproductive age in sub-Saharan Africa: an event history analysis approach | Reproductive Health

    Data

    The data for this study were sourced from the most recent Demographic and Health Survey (DHS) conducted in thirty-six (36) sub-Saharan African countries. The DHS is a nationally representative sample survey that collects data on demographic and health indicators, including measures of reproductive health such as ANC attendance among women of reproductive age (15–49 years). The data for the current study were drawn from DHS surveys conducted between 2007 and 2019 in the thirty-six countries involved in the study. The data were downloaded from the MEASURE DHS website at http://dhsprogram.com/data/available-datasets.cfm on February 1st, 2021. The list of countries by sub-region and the respective survey years and corresponding sample sizes are presented in Appendix 1 as part of the supplementary results.

    Study sample and management of missing cases

    The sample for this study was based on the last pregnancies completed by women aged 15–49 years within the 2 years preceding the DHS survey and who made at least one ANC visit during this index pregnancy. After pooling the data for the most recent surveys in the thirty-six countries, 377,112 pregnancies were identified within the preceding five years of the survey. Among them, 119,657 pregnancies that were not the most recent were excluded. Approximately 105,321 such pregnancies were completed more than two years before the survey and were excluded from the analysis as shown in Fig. 1.

    Fig. 1

    Flow diagram showing the inclusion and exclusion criteria for selecting the study sample

    A total of 152,134 pregnancies were completed within the last two years, among which 16,373 pregnancies that did not receive any ANC were excluded. The percentage of missing data on related variables for the current study is low (less than 6% on single variable and less than 10% for the whole data set). The analyses were thus limited to cases with complete data employing listwise or case wise deletions. Excluding missing cases from the final sample does not pose a challenge for the analysis because it is generally accepted that if the presence of missing data on related variables are unrelated to any other variable, then the data are missing completely at random, and data missing completely at random with a small amount of missing data (less than 10% as in the case of the current study) still provide reliable and valid results as analysis of all cases with complete data [18, 19]. Thus, the final analysis was based on 123,134 completed pregnancies with valid data on all the variables included in the analysis. A table showing the percentage of missing cases per variable has been presented in the supplementary materials (see Appendix 2 in the supplementary materials).

    Variables

    Dependent variable

    The outcome variable for this study was a time variable measured for each pregnancy (pregnant woman) subject to the risk of ANC initiation. The dependent variable equals the duration before the event of the first ANC attendance. The duration of the dependent variable was measured in months and ranged from 1 to 9 months.

    Independent variables

    The predictor variables for this study included factors associated with ANC according to the literature and available in the data sets. Previous studies have identified the factors associated with the utilization of ANC services in LMICs to include household wealth quintiles [12, 13, 17, 20,21,22,23,24,25], place of residence [9, 12, 24,25,26], female education [9, 12, 13, 22,23,24,25], desire for pregnancy [8, 12, 13, 23, 25], female occupation [9, 23], age [12, 24,25,26,27], pregnancy rank/parity [9, 23, 25, 26], mass media exposure [12, 23, 25], number of children under five [8, 9], sociocultural norms and practices [20, 25], women’s autonomy [9, 25], marital status [25], and husbands’ education [9]. Additionally, some studies provide evidence that the odds of ANC coverage are lower among women from households belonging to the poor wealth quintile, women who have no formal education or who are less educated [17, 20, 21, 25] and women living in rural areas [12, 20, 25, 26]. There is also empirical evidence showing the link between family/community involvement and utilization of ANC services [5], while others have noted the role of sociocultural factors [21, 25]. For example, in Ghana, women in predominantly Muslim areas appear to be more limited in their ability to participate in reproductive health decision-making [21]. Additionally, other factors, such as exposure to mass media, especially locally driven mass media, have been shown to strongly impact health service utilization [28]. Furthermore, there has been extensive research on barriers to ANC utilization in SSA. A systematic review of outcome measures and determinants of unmet reproductive health needs revealed that economic constraints, long-distance travel to access services and low education are among the key predictors of ANC utilization among women in some West African countries [22]. Again, the results of a systematic review and meta-analysis in Ethiopia showed that improving female education and women’s empowerment could reduce the magnitude of delayed ANC uptake [9]. The results of other studies also indicate that women with wanted pregnancies are more likely to receive antenatal care [8, 13, 23]. The results regarding place of residence show that while some studies [9, 20, 26] have found a strong relationship between ANC uptake and place of residence, others [13] have reported weak or no significant associations. Additionally, while some studies have shown a negative relationship between female age and ANC uptake [26], another study [13] has shown no such association.

    The present study investigates variations in the first initiation of ANC over time during pregnancy and examines the influence of associated risk factors at the global SSA, controlling for covariates identified from previous research. Drawing on an adaptation of the Andersen behavioral model (1995), the various factors controlled for in this study were grouped into four categories consisting of environmental factors, predisposing characteristics, enabling factors and need factors, as shown in Fig. 2. The environmental/external factors included place of residence (urban or rural), country (all 36 countries included in the study) and sub-region (eastern, middle, southern or western Africa). Predisposing characteristics include respondent’s age at the birth of the child (in five-year age groups), highest level of education, type of occupation, marital status, mass media exposure (ranking variable from “very low” to “very high”)Footnote 1, and partner’s level of education. The enabling factors considered were household wealth quintile and women’s participation in the household’s decision-making processFootnote 2 (coded as involved in 0 – no decision; 1–1 decision; 2–2 decisions; 3–3 decisions; 4–4 decisions). Need factors included desire for pregnancy (wanted then, wanted later, wanted no more), number of births and ever had a pregnancy terminated. The list of independent variables and their categorization are shown in Table 1.

    Table 1 Percentage distribution of study population by selected characteristics
    Fig. 2
    figure 2

    Conceptual Model Showing Factors Associated with initiation of antenatal care visits among women of reproductive age in sub-Saharan Africa

    To ensure the reliability and accuracy of the regression models, a comprehensive multicollinearity test was conducted to assess correlation between all independent variables. Variables found to be highly correlated were systematically excluded. These variables were language, sub-region, and year of interview which were highly correlated with country of residence. However, due to the importance of these variables in the understanding of the context and to assess the variations in the chances of ANC initiation across the various sub-Saharan African regions, an alternative model excluding country was implemented. The alternate model accommodated the categorization of countries by sub-region and controlled for survey year. The results of the alternate model are included as supplementary results (see Appendix 4). These adjustments were made to enhance the clarity and interpretability of the models while addressing multicollinearity concerns.

    Analytical strategy

    The characteristics of the study sample were described using percentage distributions. All the independent variables, including survey year, were coded as categorical variables. The association between the timing of the first ANC visit and each independent variable was assessed using cross-tabulation with the Pearson chi-square test. Kaplan-Meier survivor curves were generated to examine the extent to which ANC initiation occurred over time according to the selected covariates. The Kaplan-Meier curves were generated to explore temporal trends in ANC initiation and to construct survival curves for participants stratified according to the selected covariates. The log-rank test was used to determine the significance of differences in survival distributions. At the multivariate level, a number of modeling techniques were explored, and model diagnostics and fitness tests were used to determine the best fit model for the data. The first modeling approach that was explored was multilevel modeling considering the nesting of respondents in countries, clusters and households. The intraclass coefficient (ICC) from the null model showed that only 0.6% (ICC = 0.0063) of the variation in ANC initiation was explained by between-cluster differences, indicating that a conventional one-level regression model fits the data better than a multilevel model [29]. After ruling out multilevel modeling, event history analysis was explored given the nature of the dependent variable. Discrete–time logit models were specified to examine the unadjusted and adjusted effects of each covariate on the dependent variable. The discrete-time survival analysis employed does not require an assumption of proportional hazards as piecewise exponentials [30]. In conducting the statistical analysis, the data were weighted to make the findings generalizable to women of reproductive age (15–49 years) within each country, and differences were tested for significance at the 5% level. All the statistical analyses were performed in R [31]. The analyses employed many R packages including survival [32], dplyr [33], knitr [34], haven [35], survey [36], gtools [37], numDervi [38], car [39], vim [40], summarytools [41], discsurv [42], survminer [43], flextable [44], officer [45], jtools [46], and finalfit [47].

    Continue Reading

  • Brevundimonas vesicularis sepsis in a 2-month-old infant in rural Gambia: a case report | Journal of Medical Case Reports

    Brevundimonas vesicularis sepsis in a 2-month-old infant in rural Gambia: a case report | Journal of Medical Case Reports

    Brevundimonas vesicularis is a non-lactose fermenter, Gram-negative bacillus, and is usually isolated from clinical and environmental samples. It is an opportunistic pathogen that affects children and adults. Most cases may be due to underlying…

    Continue Reading

  • New moon likely to be sighted on October 21 :SUPARCO

    New moon likely to be sighted on October 21 :SUPARCO

    – Advertisement –

    ISLAMABAD, Oct 21 (APP):The Space and Upper Atmosphere Research Commission (SUPARCO) has announced that the new moon of Jamadi ul awwal, 1447 AH, is expected to be born on October 21 at 17:25 PST.

    At the time of sunset on…

    Continue Reading

  • MultiModalGraphics: an R package for graphical integration of multi-omics datasets | BMC Bioinformatics

    MultiModalGraphics: an R package for graphical integration of multi-omics datasets | BMC Bioinformatics

    MultiModalGraphics is an R/Bioconductor package that leverages object-oriented S4 classes to visualize multimodal biological data with embedded statistical annotations. Originally developed for collaborative multi-omics studies [23,24,25], the…

    Continue Reading