A Daily Diary Approach to the Examination of Chronic Stress, Daily Hassles and Safety Perceptions in Hospital Nursing



Stress is a significant concern for individuals and organisations. Few studies have explored stress, burnout and patient safety in hospital nursing on a daily basis at the individual level. This study aimed to examine the effects of chronic stress and daily hassles on safety perceptions, the effect of chronic stress on daily hassles experienced and chronic stress as a potential moderator.


Utilising a daily diary design, 83 UK hospital nurses completed three end-of-shift diaries, yielding 324 person days. Hassles, safety perceptions and workplace cognitive failure were measured daily, and a baseline questionnaire included a measure of chronic stress. Hierarchical multivariate linear modelling was used to analyse the data.


Higher chronic stress was associated with more daily hassles, poorer perceptions of safety and being less able to practise safely, but not more workplace cognitive failure. Reporting more daily hassles was associated with poorer perceptions of safety, being less able to practise safely and more workplace cognitive failure. Chronic stress did not moderate daily associations. The hassles reported illustrate the wide-ranging hassles nurses experienced.


The findings demonstrate, in addition to chronic stress, the importance of daily hassles for nurses’ perceptions of safety and the hassles experienced by hospital nurses on a daily basis. Nurses perceive chronic stress and daily hassles to contribute to their perceptions of safety. Measuring the number of daily hassles experienced could proactively highlight when patient safety threats may arise, and as a result, interventions could usefully focus on the management of daily hassles.

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  1. 1.

    39.8% of participants completed five diaries, 18.1% completed four diaries, 34.9% completed three diaries, and 7.2% completed two diaries; 83.6% of the diaries were completed on a weekday.

  2. 2.

    Cronbach’s alphas (α) we report are from our analyses.

  3. 3.

    Hassle categories were not mutually exclusive.

  4. 4.

    Intra-class correlation coefficients (ICC) for outcome variables: perceptions of patient safety .42, safe practitioner measure .23 and workplace cognitive failure .66


  1. 1.

    Milliken TF, Clements PT, Tillman HJ. The impact of stress management on nurse productivity and retention. Nurs Econ. 2007;25(4):203–10.

    PubMed  Google Scholar 

  2. 2.

    Moustaka Å, Constantinidis TC. Sources and effects of work-related stress in nursing. Health Sci J. 2010;4:210–6.

    Google Scholar 

  3. 3.

    Carayon P, Gurses AP. Nursing workload and patient safety—a human factors engineering perspective. In: Hughes R, editor. Patient safety and quality: an evidence–based handbook for nurses [internet]. Rockville: Agency for Healthcare Research and Quality; 2008. [cited 2016 January 10]. Available from http://archive.ahrq.gov/professionals/clinicians-providers/resources/nursing/resources/nurseshdbk/CarayonP_NWPS.pdf.

    Google Scholar 

  4. 4.

    Gifford BD, Zammuto RF, Goodman EA, Hill KS. The relationship between hospital unit culture and nurses' quality of work life/practitioner application. J Healthc Manag. 2002;47(1):13–25.

    PubMed  Google Scholar 

  5. 5.

    Ball JE, Murrells T, Rafferty AM, Morrow E, Griffiths P. ‘Care left undone’during nursing shifts: associations with workload and perceived quality of care. BMJ Qual Saf. 2013;23(2):116–25.

    Article  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Wray J. The impact of the financial crisis on nurses and nursing. J Adv Nurs. 2013;69(3):497–9.

    Article  PubMed  Google Scholar 

  7. 7.

    Royal College of Nursing. Guidance on nurse staffing levels in the UK. London: RCN; 2010.

    Google Scholar 

  8. 8.

    Royal College of Nursing. Mandatory nurse staffing levels. London: RCN; 2012.

    Google Scholar 

  9. 9.

    Spetz J, Given R. The future of the nurse shortage: will wage increases close the gap? Health Affair. 2003;22(6):199–206.

    Article  Google Scholar 

  10. 10.

    Greenglass ER, Burke RJ, Fiksenbaum L. Workload and burnout in nurses. J Community Appl Soc. 2001;11(3):211–5.

    Article  Google Scholar 

  11. 11.

    Purcell SR, Kutash M, Cobb S. The relationship between nurses’ stress and nurse staffing factors in a hospital setting. J Nurs Manag. 2011;19(6):714–20.

    Article  PubMed  Google Scholar 

  12. 12.

    Sharma P, Davey A, Davey S, Shukla A, Shrivastava K, Bansal R. Occupational stress among staff nurses: controlling the risk to health. Indian J Occup Environ Med. 2014;18(2):52.

    Article  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Chang EM, Daly JW, Hancock KM, Bidewell J, Johnson A, Lambert VA, et al. The relationships among workplace stressors, coping methods, demographic characteristics, and health in Australian nurses. J Prof Nurs. 2006;22(1):30–8.

    Article  PubMed  Google Scholar 

  14. 14.

    Letvak S. We cannot ignore nurses’ health anymore: a synthesis of the literature on evidence-based strategies to improve nurse health. Nurs Adm Q. 2013;37(4):295–308.

    Article  PubMed  Google Scholar 

  15. 15.

    Tucker SJ, Weymiller AJ, Cutshall SM, Rhudy LM, Lohse CM. Stress ratings and health promotion practices among RNs: a case for action. J Nurs Adm. 2012;42(5):282–92.

    Article  PubMed  Google Scholar 

  16. 16.

    Ida H, Miura M, Komoda M, Yakura N, Mano T, Hamaguchi T, Yamauchi K. Relationship between stress and performance in a Japanese nursing organization. Int J Health Care Qual Assur. 2009;22(6):642–57.

    Article  PubMed  Google Scholar 

  17. 17.

    Parker PA, Kulik JA. (1995). Burnout, self-and supervisor-rated job performance, and absenteeism among nurses. J Behav Med. 1995;18(6):581–99.

    CAS  Article  PubMed  Google Scholar 

  18. 18.

    Carter MR, Tourangeau AE. Staying in nursing: what factors determine whether nurses intend to remain employed? J Adv Nurs. 2012;68(7):1589–600.

    Article  PubMed  Google Scholar 

  19. 19.

    Heinen MM, van Achterberg T, Schwendimann R, Zander B, Matthews A, Kózka M, et al. Nurses’ intention to leave their profession: a cross sectional observational study in 10 European countries. Int J Nurs Stud. 2013;50(2):174–84.

    Article  PubMed  Google Scholar 

  20. 20.

    Mosadeghrad AM. Occupational stress and turnover intention: implications for nursing management. Int J Health Policy Manag. 2013;1(2):169–76.

    Article  PubMed  PubMed Central  Google Scholar 

  21. 21.

    Wu TY, Fox DP, Stokes C, Adam C. Work-related stress and intention to quit in newly graduated nurses. Nurse Educ Today. 2012;32(6):669–74.

    Article  PubMed  Google Scholar 

  22. 22.

    AbuAlRub RF. Job stress, job performance, and social support among hospital nurses. J Nurs Sch. 2004;36(1):73–8.

    Article  Google Scholar 

  23. 23.

    Bakker AB, Heuven E. Emotional dissonance, burnout, and in-role performance among nurses and police officers. Int J Stress Manag. 2006;13(4):423.

    Article  Google Scholar 

  24. 24.

    Packard JS, Motowidlo SJ. Subjective stress, job satisfaction, and job performance of hospital nurses. Res Nurs Health. 1987;10(4):253–61.

    CAS  Article  PubMed  Google Scholar 

  25. 25.

    Poghosyan L, Clarke SP, Finlayson M, Aiken LH. Nurse burnout and quality of care: cross-national investigation in six countries. Res Nurs Health. 2010;33(4):288–98.

    Article  PubMed  PubMed Central  Google Scholar 

  26. 26.

    Vahey DC, Aiken LH, Sloane DM, Clarke SP, Vargas D. Nurse burnout and patient satisfaction. Med Care. 2004;42(2 Suppl):II57.

    PubMed  PubMed Central  Google Scholar 

  27. 27.

    Dugan J, Lauer E, Bouquot Z, Dutro BK, Smith M, Widmeyer G. Stressful nurses: the effect on patient outcomes. J Nurs Care Qual. 1996;10(3):46–58.

    CAS  Article  PubMed  Google Scholar 

  28. 28.

    Virtanen M, Kurvinen T, Terho K, Oksanen T, Peltonen R, Vahtera J, et al. Work hours, work stress, and collaboration among ward staff in relation to risk of hospital-associated infection among patients. Med Care. 2009;47(3):310–8.

    Article  PubMed  Google Scholar 

  29. 29.

    Halbesleben JR, Wakefield BJ, Wakefield DS, Cooper LB. Nurse burnout and patient safety outcomes nurse safety perception versus reporting behavior. West J Nurs Res. 2008;30(5):560–77.

    Article  PubMed  Google Scholar 

  30. 30.

    Jennings B. Work stress and burnout among nurses: role of the work environment and working conditions. In: Hughes R, editor. Patient safety and quality: an evidence–based handbook for nurses [internet]. Rockville: Agency for Healthcare Research and Quality; 2008. [cited 2016 January 10]. Available from http://www.ncbi.nlm.nih.gov/books/NBK2676/?report=reader.

    Google Scholar 

  31. 31.

    Aiken LH, Clarke SP, Sloane DM, Sochalski J, Silber JH. Hospital nurse staffing and patient mortality, nurse burnout, and job dissatisfaction. JAMA. 2002;288(16):1987–93.

    Article  PubMed  Google Scholar 

  32. 32.

    Cimiotti JP, Aiken LH, Sloane DM, Wu ES. Nurse staffing, burnout, and health care–associated infection. Am J Infect Control. 2012;40(6):486–90.

    Article  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Teng CI, Shyu YIL, Chiou WK, Fan HC, Lam SM. Interactive effects of nurse-experienced time pressure and burnout on patient safety: a cross-sectional survey. Int J Nurs Stud. 2010;47(11):1442–50.

    Article  PubMed  Google Scholar 

  34. 34.

    Elfering A, Semmer NK, Grebner S. Work stress and patient safety: observer-rated work stressors as predictors of characteristics of safety-related events reported by young nurses. Ergonomics. 2006;49(5–6):457–69.

    CAS  Article  PubMed  Google Scholar 

  35. 35.

    Affleck G, Zautra A, Tennen H, Armeli S. Multilevel daily process designs for consulting and clinical psychology: a preface for the perplexed. J Consult Clin Psychol. 1999;67(5):746.

    CAS  Article  PubMed  Google Scholar 

  36. 36.

    Ferguson E. The use of diary methods in clinical and health psychology. In: Miles J, Gilbert P, editors. A handbook of research methods in clinical and health psychology. Oxford: Oxford University Press; 2005.

    Google Scholar 

  37. 37.

    O’Connor DB, Ferguson E. Stress and stressors. In: Benyamini Y, Johnston M, Karademas EC, editors. Assessment in health psychology. Göttingen/Boston: Hogrefe; 2016. p. 104–18.

    Google Scholar 

  38. 38.

    Nezlek JB. Multilevel random coefficient analyses of event-and interval-contingent data in social and personality psychology research. Personal Soc Psychol Bull. 2001;27(7):771–85.

    Article  Google Scholar 

  39. 39.

    Hofmann DA, Mark B. An investigation of the relationship between safety climate and medication errors as well as other nurse and patient outcomes. Pers Psychol. 2006;59(4):847–69.

    Article  Google Scholar 

  40. 40.

    Huang DT, Clermont G, Kong L, Weissfeld LA, Sexton JB, Rowan KM, et al. Intensive care unit safety culture and outcomes: a US multicenter study. Int J Qual Health Care. 2010;22(3):151–61.

    Article  PubMed  PubMed Central  Google Scholar 

  41. 41.

    Mardon RE, Khanna K, Sorra J, Dyer N, Famolaro T. Exploring relationships between hospital patient safety culture and adverse events. J Patient Saf. 2010;6(4):226–32.

    Article  PubMed  Google Scholar 

  42. 42.

    Petrowski K, Paul S, Albani C, Brähler E. Factor structure and psychometric properties of the Trier Inventory for Chronic Stress (TICS) in a representative German sample. BMC Med Res Methodol. 2012;12(1):42.

    Article  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Gartland N, O’Connor DB, Lawton R, Bristow M. Exploring day-to-day dynamics of daily stressor appraisals, physical symptoms and the cortisol awakening response. Psychoneuroendocrinology. 2014;50:130–8.

    CAS  Article  PubMed  Google Scholar 

  44. 44.

    O'Connor DB, Jones F, Conner M, McMillan B, Ferguson E. Effects of daily hassles and eating style on eating behavior. Health Psychol. 2008;27(1S):S20.

    Article  PubMed  Google Scholar 

  45. 45.

    Sliwinski MJ, Almeida DM, Smyth J, Stawski RS. Intraindividual change and variability in daily stress processes: findings from two measurement-burst diary studies. Psychol Aging. 2009;24(4):828.

    Article  PubMed  PubMed Central  Google Scholar 

  46. 46.

    Serido J, Almeida DM, Wethington E. Chronic stressors and daily hassles: unique and interactive relationships with psychological distress. J Health Soc Behav. 2004;45(1):17–33.

    Article  PubMed  Google Scholar 

  47. 47.

    Reason J. Human error: models and management. BMJ. 2000;320(7237):768–70.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  48. 48.

    Lupien SJ, Maheu F, Tu M, Fiocco A, Schramek TE. The effects of stress and stress hormones on human cognition: implications for the field of brain and cognition. Brain Cogn. 2007;65(3):209–37.

    CAS  Article  PubMed  Google Scholar 

  49. 49.

    Renner KH, Beversdorf DQ. Effects of naturalistic stressors on cognitive flexibility and working memory task performance. Neurocase. 2010;16(4):293–300.

    Article  PubMed  Google Scholar 

  50. 50.

    Starcke K, Wolf OT, Markowitsch HJ, Brand M. Anticipatory stress influences decision making under explicit risk conditions. Behav Neurosci. 2008;122(6):1352.

    Article  PubMed  Google Scholar 

  51. 51.

    Broadbent DE, Cooper PF, FitzGerald P, Parkes KR. The cognitive failures questionnaire (CFQ) and its correlates. Br J Clin Psychol. 1982;21(1):1–16.

    Article  PubMed  Google Scholar 

  52. 52.

    Park YM, Kim SY. Impacts of job stress and cognitive failure on patient safety incidents among hospital nurses. Saf Health Work. 2013;4(4):210–5.

    Article  PubMed  PubMed Central  Google Scholar 

  53. 53.

    Louch G, O’Hara J, Gardner P, O’Connor DB. The daily relationships between staffing, safety perceptions and personality in hospital nursing: a longitudinal on-line diary study. Int J Nurs Stud. 2016;59:27–37.

    Article  PubMed  Google Scholar 

  54. 54.

    Schulz P, Schlotz W, Becker P. Trierer Inventar zum chronischen Stress (TICS) [Trierer Inventory of Chronic Stress]. Gottingen: Hogrefe; 2004.

  55. 55.

    Schulz P, Schlotz W. Trierer Inventar zur Erfassung von chronischem Streß (TICS): Skalenkonstruktion, teststatistische Überprüfung und Validierung der Skala Arbeitsüberlastung [The Trier Inventory for Chronic Stress (TICS): scale construction, statistical testing and validation of the scale work overload]. Diagnostica. 1999;45(1):8–19. doi:10.1026//0012-1924.45.1.8.

  56. 56.

    Sorra JS, Nieva VF. Hospital survey on patient safety culture. AHRQ Publication No. 04-0041. Rockville, MD: Agency for Healthcare Research and Quality, September 2004. (Available from: http://www.ahrq.gov/qual/hospculture; accessed January, 2016).

  57. 57.

    Blegen MA, Gearhart S, O'brien R, Sehgal NL, Alldredge BK. AHRQ’s hospital survey on patient safety culture: psychometric analyses. J Patient Saf. 2009;5(3):139–44.

    Article  PubMed  Google Scholar 

  58. 58.

    Sorra JS, Dyer N. Multilevel psychometric properties of the AHRQ hospital survey on patient safety culture. BMC Health Serv Res. 2010;10(1):199.

    Article  PubMed  PubMed Central  Google Scholar 

  59. 59.

    Wallace JC, Chen G. Development and validation of a work-specific measure of cognitive failure: implications for occupational safety. J Occup Organ Psychol. 2005;78(4):615–32.

    Article  Google Scholar 

  60. 60.

    Elfering A, Grebner S, Dudan A. Job characteristics in nursing and cognitive failure at work. Saf Health Work. 2011;2(2):194–200.

    Article  PubMed  PubMed Central  Google Scholar 

  61. 61.

    Raudenbush SW. HLM 6: Hierarchical linear and nonlinear modeling. Scientific Software International; 2004.

  62. 62.

    Bryk AS, Raudenbush SW. Hierarchical linear models. Newbury Park: Sage; 1992.

    Google Scholar 

  63. 63.

    Kreft IG, De Leeuw J, Aiken LS. The effect of different forms of centering in hierarchical linear models. Multivariate Behav Res. 1995;30(1):1–21.

    CAS  Article  PubMed  Google Scholar 

  64. 64.

    Hall LH, Johnson J, Watt I, Tsipa A, O’Connor DB. Healthcare staff wellbeing, burnout, and patient safety: a systematic review. PLoS One. 2016;11(7):e0159015.

    Article  PubMed  PubMed Central  Google Scholar 

  65. 65.

    Griffin MA. Interaction between individuals and situations: using HLM procedures to estimate reciprocal relationships. J Manage. 1997;23(6):759–73.

    Google Scholar 

  66. 66.

    Hofmann DA. An overview of the logic and rationale of hierarchical linear models. J Manage. 1997;23(6):723–44.

    Google Scholar 

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We would like to thank the nurses who completed the questionnaires and made this study possible. The study was funded by the University of Leeds and Bradford Institute for Health Research (PhD Studentship).

Author information



Corresponding author

Correspondence to Gemma Louch.

Ethics declarations

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The study was approved by the University of Leeds School of Psychology Ethics Committee in February 2013. Informed consent was obtained from all individual participants included in the study.

Conflict of Interest

The authors declare that they have no conflict of interest.


Appendix 1 General Form of Models and Equations for Research Questions

Are higher ratings of chronic stress related to nurses’ daily safety perceptions?

The general form of the model is expressed by the following equation:

$$ \begin{array}{l}\begin{array}{l}\mathrm{Outcome}\ \mathrm{variable}\left(\mathrm{e}.\mathrm{g}.\mathrm{safety}\ \mathrm{perception}\right)={\upbeta}_{00}+{\upbeta}_{01}\left(\mathrm{gender}\right)+{\upbeta}_{02}\left(\mathrm{age}\right)+{\upbeta}_{03}\left(\mathrm{length}\ \mathrm{of}\ \mathrm{time}\ \mathrm{qualified}\right)+{\upbeta}_{04}\left(\mathrm{chronic}\ \mathrm{stress}\right)+\upvarepsilon \\ {}{\upbeta}_{00}=\mathrm{Mean}\ \mathrm{level}\ \mathrm{of}\ \mathrm{outcome}\ \mathrm{variable}\left(\mathrm{e}.\mathrm{g}.\mathrm{safety}\ \mathrm{perception}\right)\end{array}\hfill \\ {}{\upbeta}_{01}=\mathrm{Indicates}\ \mathrm{the}\ \mathrm{extent}\ \mathrm{to}\ \mathrm{which}\ \mathrm{this}\ \mathrm{average}\ \mathrm{is}\ \mathrm{influenced}\ \mathrm{by}\ \mathrm{gender}\hfill \\ {}{\upbeta}_{02}=\mathrm{Indicates}\ \mathrm{the}\ \mathrm{extent}\ \mathrm{to}\ \mathrm{which}\ \mathrm{this}\ \mathrm{average}\ \mathrm{is}\ \mathrm{influenced}\ \mathrm{by}\ \mathrm{age}\hfill \\ {}{\upbeta}_{03}=\mathrm{Indicates}\ \mathrm{the}\ \mathrm{extent}\ \mathrm{to}\ \mathrm{which}\ \mathrm{this}\ \mathrm{average}\ \mathrm{is}\ \mathrm{influenced}\ \mathrm{by}\ \mathrm{length}\ \mathrm{of}\ \mathrm{time}\ \mathrm{qualified}\hfill \\ {}{\upbeta}_{04}=\mathrm{Indicates}\ \mathrm{the}\ \mathrm{extent}\ \mathrm{to}\ \mathrm{which}\ \mathrm{this}\ \mathrm{average}\ \mathrm{is}\ \mathrm{influenced}\ \mathrm{by}\ \mathrm{level}\ \mathrm{of}\ \mathrm{chronic}\ \mathrm{stress}\hfill \\ {}\upvarepsilon =\mathrm{Error}\ \mathrm{term}\hfill \end{array} $$

Are more daily hassle experiences related to nurses’ daily safety perceptions?

The general form of the model is expressed by the following equation:

$$ \begin{array}{l}\begin{array}{l}\mathrm{Outcome}\ \mathrm{variable}\left(\mathrm{e}.\mathrm{g}.\mathrm{safety}\ \mathrm{perception}\right)={\upbeta}_{00}+{\upbeta}_{01}\left(\mathrm{gender}\right)+{\upbeta}_{02}\left(\mathrm{age}\right)+{\upbeta}_{03}\left(\mathrm{length}\ \mathrm{of}\ \mathrm{time}\ \mathrm{qualified}\right)+{\upbeta}_{10}\left(\mathrm{total}\ \mathrm{hassle}\ \mathrm{experience}\right)+\upvarepsilon \\ {}{\upbeta}_{00}=\mathrm{Mean}\ \mathrm{level}\ \mathrm{of}\ \mathrm{outcome}\ \mathrm{variable}\left(\mathrm{e}.\mathrm{g}.\mathrm{safety}\ \mathrm{perception}\right)\end{array}\hfill \\ {}{\upbeta}_{01}=\mathrm{Indicates}\ \mathrm{the}\ \mathrm{extent}\ \mathrm{to}\ \mathrm{which}\ \mathrm{this}\ \mathrm{average}\ \mathrm{is}\ \mathrm{influenced}\ \mathrm{by}\ \mathrm{gender}\hfill \\ {}{\upbeta}_{02}=\mathrm{Indicates}\ \mathrm{the}\ \mathrm{extent}\ \mathrm{to}\ \mathrm{which}\ \mathrm{this}\ \mathrm{average}\ \mathrm{is}\ \mathrm{influenced}\ \mathrm{by}\ \mathrm{age}\hfill \\ {}{\upbeta}_{03}=\mathrm{Indicates}\ \mathrm{the}\ \mathrm{extent}\ \mathrm{to}\ \mathrm{which}\ \mathrm{this}\ \mathrm{average}\ \mathrm{is}\ \mathrm{influenced}\ \mathrm{by}\ \mathrm{length}\ \mathrm{of}\ \mathrm{time}\ \mathrm{qualified}\hfill \\ {}{\upbeta}_{10}=\mathrm{Indicates}\ \mathrm{the}\ \mathrm{extent}\ \mathrm{to}\ \mathrm{which}\ \mathrm{this}\ \mathrm{average}\ \mathrm{is}\ \mathrm{influenced}\ \mathrm{by}\ \mathrm{level}\ \mathrm{of}\ \mathrm{to}\mathrm{tal}\ \mathrm{hassle}\ \mathrm{experience}\hfill \\ {}\upvarepsilon =\mathrm{Error}\ \mathrm{term}\hfill \end{array} $$

Do nurses who report higher ratings of chronic stress also report more daily hassle experiences?

The general form of the model is expressed by the following equation:

$$ \begin{array}{l}\begin{array}{l}\mathrm{Outcome}\ \mathrm{variable}\left(\mathrm{e}.\mathrm{g}.\mathrm{safety}\ \mathrm{perception}\right)={\upbeta}_{00}+{\upbeta}_{01}\left(\mathrm{gender}\right)+{\upbeta}_{02}\left(\mathrm{age}\right)+{\upbeta}_{03}\left(\mathrm{length}\ \mathrm{of}\ \mathrm{time}\ \mathrm{qualified}\right)+{\upbeta}_{10}\left(\mathrm{total}\ \mathrm{hassle}\ \mathrm{experience}\right)+\upvarepsilon \\ {}{\upbeta}_{00}=\mathrm{Mean}\ \mathrm{level}\ \mathrm{of}\ \mathrm{outcome}\ \mathrm{variable}\ \left(\mathrm{total}\ \mathrm{hassle}\ \mathrm{experience}\right)\end{array}\hfill \\ {}{\upbeta}_{01}=\mathrm{Indicates}\ \mathrm{the}\ \mathrm{extent}\ \mathrm{to}\ \mathrm{which}\ \mathrm{this}\ \mathrm{average}\ \mathrm{is}\ \mathrm{influenced}\ \mathrm{by}\ \mathrm{gender}\hfill \\ {}{\upbeta}_{02}=\mathrm{Indicates}\ \mathrm{the}\ \mathrm{extent}\ \mathrm{to}\ \mathrm{which}\ \mathrm{this}\ \mathrm{average}\ \mathrm{is}\ \mathrm{influenced}\ \mathrm{by}\ \mathrm{age}\hfill \\ {}{\upbeta}_{03}=\mathrm{Indicates}\ \mathrm{the}\ \mathrm{extent}\ \mathrm{to}\ \mathrm{which}\ \mathrm{this}\ \mathrm{average}\ \mathrm{is}\ \mathrm{influenced}\ \mathrm{by}\ \mathrm{length}\ \mathrm{of}\ \mathrm{time}\ \mathrm{qualified}\hfill \\ {}{\upbeta}_{04}=\mathrm{Indicates}\ \mathrm{the}\ \mathrm{extent}\ \mathrm{to}\ \mathrm{which}\ \mathrm{this}\ \mathrm{average}\ \mathrm{is}\ \mathrm{influenced}\ \mathrm{by}\ \mathrm{level}\ \mathrm{of}\ \mathrm{chronic}\ \mathrm{stress}\hfill \\ {}\upvarepsilon =\mathrm{Error}\ \mathrm{term}\hfill \end{array} $$

Does chronic stress moderate the relationships between nurses’ daily hassle experiences and daily safety perceptions?

The general form of the model is expressed by the following equation:

$$ \begin{array}{l}\mathrm{Outcome}\ \mathrm{variable}\left(\mathrm{e}.\mathrm{g}.\mathrm{safety}\ \mathrm{perception}\right)={\upbeta}_{00}+{\upbeta}_{01}\left(\mathrm{gender}\right)+{\upbeta}_{02}\left(\mathrm{age}\right)+{\upbeta}_{03}\left(\mathrm{length}\ \mathrm{of}\ \mathrm{time}\ \mathrm{qualified}\right)+{\upbeta}_{04}\left(\mathrm{chronic}\ \mathrm{stress}\right)+{\upbeta}_{10}\left(\mathrm{total}\ \mathrm{hassle}\ \mathrm{experience}\right)+{\upbeta}_{11}\left(\mathrm{chronic}\ \mathrm{stress}\ \mathrm{X}\ \mathrm{to}\mathrm{tal}\ \mathrm{hassle}\ \mathrm{experience}\right)+\upvarepsilon \hfill \\ {}{\upbeta}_{00}=\mathrm{Mean}\ \mathrm{level}\ \mathrm{of}\ \mathrm{outcome}\ \mathrm{variable}\left(\mathrm{e}.\mathrm{g}.\mathrm{safety}\ \mathrm{perception}\right)\hfill \\ {}{\upbeta}_{01}=\mathrm{Indicates}\ \mathrm{the}\ \mathrm{extent}\ \mathrm{to}\ \mathrm{which}\ \mathrm{this}\ \mathrm{average}\ \mathrm{is}\ \mathrm{influenced}\ \mathrm{by}\ \mathrm{gender}\hfill \\ {}{\upbeta}_{02}=\mathrm{Indicates}\ \mathrm{the}\ \mathrm{extent}\ \mathrm{to}\ \mathrm{which}\ \mathrm{this}\ \mathrm{average}\ \mathrm{is}\ \mathrm{influenced}\ \mathrm{by}\ \mathrm{age}\hfill \\ {}{\upbeta}_{03}=\mathrm{Indicates}\ \mathrm{the}\ \mathrm{extent}\ \mathrm{to}\ \mathrm{which}\ \mathrm{this}\ \mathrm{average}\ \mathrm{is}\ \mathrm{influenced}\ \mathrm{by}\ \mathrm{length}\ \mathrm{of}\ \mathrm{time}\ \mathrm{qualified}\hfill \\ {}{\upbeta}_{04}=\mathrm{Indicates}\ \mathrm{the}\ \mathrm{extent}\ \mathrm{to}\ \mathrm{which}\ \mathrm{this}\ \mathrm{average}\ \mathrm{is}\ \mathrm{influenced}\ \mathrm{by}\ \mathrm{level}\ \mathrm{of}\ \mathrm{chronic}\ \mathrm{stress}\hfill \\ {}\begin{array}{l}{\upbeta}_{10}=\mathrm{Indicates}\ \mathrm{the}\ \mathrm{extent}\ \mathrm{to}\ \mathrm{which}\ \mathrm{this}\ \mathrm{average}\ \mathrm{is}\ \mathrm{influenced}\ \mathrm{by}\ \mathrm{level}\ \mathrm{of}\ \mathrm{to}\mathrm{tal}\ \mathrm{hassle}\ \mathrm{experience}\\ {}{\upbeta}_{11}=\mathrm{Indicates}\ \mathrm{the}\ \mathrm{extent}\ \mathrm{to}\ \mathrm{which}\ \mathrm{this}\ \mathrm{average}\ \mathrm{is}\ \mathrm{conditional}\ \mathrm{on}\ \mathrm{the}\ \mathrm{level}\ \mathrm{of}\ \mathrm{chronic}\ \mathrm{stress}\\ {}\upvarepsilon =\mathrm{Error}\ \mathrm{term}\end{array}\hfill \end{array} $$

Appendix 2

Table 6 Hassle categories, frequencies and descriptions

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Louch, G., O’Hara, J., Gardner, P. et al. A Daily Diary Approach to the Examination of Chronic Stress, Daily Hassles and Safety Perceptions in Hospital Nursing. Int.J. Behav. Med. 24, 946–956 (2017). https://doi.org/10.1007/s12529-017-9655-2

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  • Nursing
  • Chronic stress
  • Patient safety
  • Daily hassles
  • Diary methods