Ansell H, Meyer A, Thompson S. Why don't nurses consistently take patient respiratory rates?. Br J Nurs. 2014; 23:(8)414-418

Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society, Series B. 1995; 57:(1)289-300

Benson M, Koenig KL, Schultz CH. Disaster triage: START, then SAVE--a new method of dynamic triage for victims of a catastrophic earthquake. Prehosp Disaster Med. 1996; 11:(2)117-124

BTS guidelines for the management of community acquired pneumonia in adults. Thorax. 2001; 56:iv1-iv64

Cooper S, Cant R, Sparkes L. Respiratory rate records: the repeated rate?. J Clin Nurs. 2014; 23:(9-10)1236-1238

Cretikos MA, Bellomo R, Hillman K, Chen J, Finfer S, Flabouris A. Respiratory rate: the neglected vital sign. Med J Aust. 2008; 188:(11)657-659

Dalkey N, Helmer O. An experimental application of the DELPHI method to the use of experts. Management Science. 1963; 9:(3)458-467

Elliott M. Why is respiratory rate the neglected vital sign? A narrative review. International Archives of Nursing and Health Care. 2016; 2:(3)1-4

Elliott M, Baird J. Pulse oximetry and the enduring neglect of respiratory rate assessment: a commentary on patient surveillance. Br J Nurs. 2019; 28:(19)1256-1259

Fieselmann JF, Hendryx MS, Helms CM, Wakefield DS. Respiratory rate predicts cardiopulmonary arrest for internal medicine inpatients. J Gen Intern Med. 1993; 8:(7)354-360

Flenady T, Dwyer T, Applegarth J. Accurate respiratory rates count: so should you!. Australas Emerg Nurs J. 2017; 20:(1)45-47

Goldhill DR, McNarry AF, Mandersloot G, McGinley A. A physiologically-based early warning score for ward patients: the association between score and outcome. Anaesthesia. 2005; 60:(6)547-553

Gravel J, Opatrny L, Gouin S. High rate of missing vital signs data at triage in a paediatric emergency department. Paediatr Child Health. 2006; 11:(4)211-215

Gravelyn TR, Weg JG. Respiratory rate as an indicator of acute respiratory dysfunction. JAMA. 1980; 244:(10)1123-1125

Harry ML, Heger AMC, Woehrle TA, Kitch LA. Understanding respiratory rate assessment by emergency nurses: a health care improvement project. J Emerg Nurs. 2020; 46:(4)488-496

Hernandez-Silveira M, Ahmed K, Ang SS, Zandari F Assessment of the feasibility of an ultra-low power, wireless digital patch for the continuous ambulatory monitoring of vital signs. BMJ Open. 2015; 5:(5)e006606-e006606

Hogan J. Why don't nurses monitor the respiratory rates of patients?. Br J Nurs. 2006; 15:(9)489-492

Knaus WA, Draper EA, Wagner DP, Zimmerman JE. APACHE II: a severity of disease classification system. Crit Care Med. 1985; 13:(10)818-829

Lee PJ. Clinical evaluation of a novel respiratory rate monitor. J Clin Monit Comput. 2016; 30:(2)175-183

Elderly patients with community-acquired pneumonia are not treated according to current guidelines. 2013.

Lovett PB, Buchwald JM, Stürmann K, Bijur P. The vexatious vital: neither clinical measurements by nurses nor an electronic monitor provides accurate measurements of respiratory rate in triage. Ann Emerg Med. 2005; 45:(1)68-76

McBride J, Knight D, Piper J, Smith GB. Long-term effect of introducing an early warning score on respiratory rate charting on general wards. Resuscitation. 2005; 65:(1)41-44

McFadden JP, Price RC, Eastwood HD, Briggs RS. Raised respiratory rate in elderly patients: a valuable physical sign. BMJ. 1982; 284:(6316)626-627

Mehmood A, He S, Zafar W, Baig N, Sumalani F, Razzak J. How vital are the vital signs? A multi-center observational study from emergency departments of Pakistan. BMC Emerg Med. 2015; 15

Ministry of Health Labour and Welfare. Survey of medical institution in 2018. e-Stat (official Japanese Government Statistics portal). 2020. (accessed 20 April 2022)

Morgan RJM, Williams F, Wright M. An early warning scoring system for detecting developing critical illness. p100 in: Abstracts – Intensive Care Society Spring meeting, May 1997. Clinical Intensive Care. 1997; 8:(2)93-110

Mower WR, Sachs C, Nicklin EL, Safa P, Baraff LJ. A comparison of pulse oximetry and respiratory rate in patient screening. Respir Med. 1996; 90:(10)593-599

National Institute for Health and Care Excellence. Acutely ill patients in hospital: recognition of and response to acute illness in adults in hospital. NICE Clinical Guideline [CG50]. 2007. (accessed 20 April 2022)

Nicolò A, Massaroni C, Schena E, Sacchetti M. The importance of respiratory rate monitoring: from healthcare to sport and exercise. Sensors (Basel). 2020; 20:(21)

Odell M, Rechner IJ, Kapila A The effect of a critical care outreach service and an early warning scoring system on respiratory rate recording on the general wards. Resuscitation. 2007; 74:(3)470-475

Philip K, Richardson R, Cohen M. Staff perceptions of respiratory rate measurement in a general hospital. Br J Nurs. 2013; 22:(10)570-574

Philip KEJ, Pack E, Cambiano V, Rollmann H, Weil S, O'Beirne J. The accuracy of respiratory rate assessment by doctors in a London teaching hospital: a cross-sectional study. J Clin Monit Comput. 2015; 29:(4)455-460

Rimbi M, Dunsmuir D, Ansermino JM, Nakitende I, Namujwiga T, Kellett J. Respiratory rates observed over 15 and 30 s compared with rates measured over 60 s: practice-based evidence from an observational study of acutely ill adult medical patients during hospital admission. QJM. 2019; 112:(7)513-517

Semler MW, Stover DG, Copland AP Flash mob research: a single-day, multicenter, resident-directed study of respiratory rate. Chest. 2013; 143:(6)1740-1744

Smith GB, Redfern OC, Pimentel MAF The National Early Warning Score 2 (NEWS2). Clin Med (Northfield Ill). 2019; 19:(3)

World Health Organization. Programme for Control of Acute Respiratory Infections: fourth programme report 1988-1989. 1990. (accessed 20 April 2022)

Factors associated with the frequency of respiratory rate measurement by hospital nurses: a multicentre cross-sectional study

12 May 2022
16 min read
Volume 31 · Issue 9



Although the respiratory rate (RR) is a sensitive predictor of patient deterioration, it is often neglected. Moreover, only a few studies have investigated the factors that cause health professionals to disregard RR.


This cross-sectional study aimed to elucidate the factors affecting the frequency of RR measurement by the nurses.


An original questionnaire, comprising 18 factors extracted from previous studies, was administered to nurses from nine hospitals.


Of the 644 eligible nurses, 592 (92%) completed the questionnaire. The adjusted odds ratios and 95% confidence intervals of the factors of importance, educational experiences, shortened-count method use, negative experiences, and inconvenience were 2.24 (1.13–4.45), 2.26 (1.20–4.26), 0.61 (0.42–0.91), 0.45 (0.29–0.70), and 0.41 (0.26–0.65), respectively.


Education, feedback systems, and automation are the primary issues that need attention. Prioritising these factors could provide a practical guide for optimising the frequency of RR measurement.

Respiratory rate (RR), one of the four traditional vital signs measurable in almost any medical setting, could be a crucial early indicator of patient deterioration (National Institute for Health and Care Excellence, 2007). An abnormal RR can be indicative of the early stages of patient deterioration (Gravelyn and Weg, 1980; McFadden et al, 1982; Fieselmann et al, 1993). Hence, the RR has been incorporated in many clinical prediction models, such as the Simple Triage And Rapid Treatment for medical emergencies and disasters (START) (Benson et al, 1996), early warning score (EWS) for establishing rapid response systems (Morgan et al, 1997; Smith et al, 2019), CURB-65 for severity scale for pneumonia (British Thoracic Society Standards of Care Committee 2001), and Acute Physiology and Chronic Health Evaluation II (APACHE II) for severity assessment of patients in the intensive care unit (Knaus et al, 1985). All of which indicates that health professionals should assess the RR thoroughly.

Despite its clinical significance in predicting patient deterioration, RR has been widely neglected for many decades (Gravel et al, 2006; Cretikos et al, 2008; Lindhardt et al, 2013; Mehmood et al, 2015). Several studies have reported that over half of RR measurements taken were not recorded (Semler et al, 2013; Cooper et al, 2014). Given the high relevancy of RR to patient wellbeing, this gap in medical literature needs to be explored.

However, only a limited number of studies have investigated the reasons for neglecting RR measurement (Hogan, 2006; Philip et al, 2013; Ansell et al, 2014; Elliott, 2016). Previous qualitative investigations have contributed to the extraction of a number of factors that potentially inhibit or promote the measurement of RR. Some factors hindering the monitoring of this vital sign include nursing workload, insufficient emphasis on RR in nursing education, lack of understanding of the importance of RR measurement, lack of required skill set, lack of electronic equipment, patient conditions, time pressure, clinical decision-making process, and organisation of nursing care activities (Hogan, 2006; Ansell et al, 2014). Notably, no existing quantitative evaluation studies investigate why health professionals tend to neglect RR measurement. Thus, it remains unclear which factors should be prioritised by staff in order to reduce this neglect.

The main aim of this study was to evaluate and prioritise the factors extracted from previous studies that are associated with the frequency of RR measurement by nurses. This exploratory study aimed to draw a conclusion that may help to reduce the neglect of RR measurement in the future.


Study design

This cross-sectional study was conducted to assess the factors associated with the frequency of RR measurement by nurses using an original questionnaire in Yamaguchi prefecture in Japan between March and August 2018.

Setting and participants

With the aim of having a sample that was representative of the general population of hospital nurses in Japan, nine hospitals were selected based on the hospital scale from the survey of medical institutions conducted in 2018 (Ministry of Health Labour and Welfare, 2020). This study included two large hospitals with more than 200 beds (Facilities A and B), three mid-sized hospitals with 100–199 beds (Facilities C, D, and E), and four small hospitals with fewer than 99 beds (Facilities F, G, H, and I). All nurses who worked in each of these hospitals were invited to participate in this study. Because the aim was to investigate the perceptions of hospital nurses regarding RR measurement, those who did not have an opportunity to evaluate vital signs in a clinical setting were excluded. Based on the pre-interview with the representative of each facility, nurses who were in managerial positions or performing clerical work usually did not assess vital signs, but this was dependent on each facility. Nurses who had insufficient information on the main outcome regarding the frequency of RR measurement (item 19) and did not provide consent to participate were also excluded. Overall, questionnaires were distributed to 644 nurses across nine hospitals. Participants were given 4 weeks to answer the questionnaires with two reminders.


An original questionnaire was developed for this study using the principle of the Delphi technique (Dalkey and Helmer, 1963). Through the three rounds of the questionnaire-creation procedure, the factors that could influence the frequency of RR measurement by the nurses were determined. In the first round, 10 expert nurses, including two certified respiratory care nurses, were individually asked to share their broad views before and after introducing the findings of the previous studies. After discussion with the experts, the authors categorised all opinions into 31 factors and created the first prototype questionnaire. In the second round, the prototype questionnaire was sent to 60 nurses from different facilities, as well as experts. In addition to answering the questionnaire, the nurses and experts were asked to score the relevance of each question. All participants in the second round responded to the prototype. The final version of the questionnaire was completed after repeating the same process.

The factors in the questionnaire developed for this study encompassed all the perspectives derived from previous studies (Hogan, 2006; Philip et al, 2013; Ansell et al, 2014; Elliott, 2016). However, the factor of lack of automatic devices to measure RR was excluded from the questionnaire, because practical and reliable devices are not currently available outside of critical care settings, meaning there was little point in investigating this as a modifiable factor at this time. The questions were organised and duplicates were deleted, but invert scale questions were not eliminated. Ultimately, the questionnaire comprised 18 different factors and one outcome question (see Table 1). Statements eliciting responses on the four-point Likert scale (strongly agree, agree, disagree, and strongly disagree) were adopted for items 1–18 (1, personal autonomy; 2, importance; 3, usefulness; 4, requests from co-workers; 5, positive experiences; 6, severity of patient's condition; 7, reliability; 8, workplace habits; 9, dispensability; 10, cost-effectiveness; 11, busyness; 12, negative experiences; 13, non-severity of patient's condition; 14, inconvenience; 15, confidence in intuitive understanding; 16, procedural difficulty; 17, premonition of failure; 18, educational experiences). Item 19 asked how often a patient's RR is measured during the vital signs check in a regular shift, and the response was based on a four-point scale (always, frequently, occasionally, and never). Sex, age, years of experience, department (outpatient, internal ward, surgical ward, mixed ward, or emergency room), and RR measurement method (full 1-minute count, 30-second count doubled, 15-second count multiplied by 4, or 10-second count multiplied by 6) were also assessed in the same questionnaire. Table 1 and Table 2 show the two parts of the questionnaire in English, although the study was performed using the Japanese version.

Table 1. Factors associated with the frequency of respiratory rate measurement, questionnaire part 1
Use the following scale to describe how you feel about each of the statements given below Strongly agree Agree Disagree Strongly disagree
1 You yourself decide whether to check a patient's respiratory rate
2 Respiratory rate is important
3 Respiratory rate is helpful
4 Your co-workers ask you to check the respiratory rate
5 Your experience says that the respiratory rate is important
6 You may change the frequency of checking the respiratory rate depending on the severity of the patient's condition
7 Respiratory rate is reliable
8 Your workplace habits determine whether you check the patient's respiratory rate
9 Checking the respiratory rate is NOT necessary during every vital check
10 The work burden for checking the respiratory rate outweighs the profits
11 You might omit to check the respiratory rate due to busyness
12 Your experience says that measuring the respiratory rate is not important
13 You might omit checking the respiratory rate when the patient's condition is good
14 You might feel that checking the patient's respiratory rates is troublesome/inconvenient
15 You can instinctively recognise abnormal respiratory rate without actually measuring it
16 Measuring the respiratory rate is a challenging procedure.
17 Measuring the respiratory rate could fail in some conditions
18 Have you had formal education regarding respiratory rate? Yes ☐ No ☐
19 How often do you check the patient's respiratory rate during the vital signs check in a regular shift? Always ☐ Frequently ☐ Sometimes ☐ Never ☐

Table 2. Factors associated with the frequency of respiratory rate measurement, questionnaire part 2
Which of the following methods do you usually use to check the patient's respiratory rate?
1 minute counting (Take 1 minute for counting respiratory rate)
30-second doubled (Take 30 seconds for counting respiratory rate and double it)
15-second x4 (Take 15 seconds for counting respiratory rate and multiply by 4)
10-second x6 (Take 10 seconds for counting respiratory rate and multiple by 6)
Sex Man Woman
Age [ ] year old
How many years have you ever worked in medical settings? [ ] years
Which of the following settings is closest to your working place?
Outpatient Internal ward Surgical ward Mixed ward Emergency room

Statistical analysis

As an outcome variable, item 19 includes the question, ‘How often you check patients' RR during a usual shift?’. The researchers divided the participants into two categories based on their answers to item 19: frequent measurers who answered ‘always’ or ‘frequently’ and infrequent measurers who answered ‘sometimes’ or ‘never’. The participants' characteristics based on the aforementioned categories are presented as percentages for categorical variables and means and standard deviations (SDs) for continuous variables. The authors estimated the odds ratios (ORs) and 95% confidence intervals (CIs) of the frequent measurers by the two categories using a multilevel mixed-effect logistic regression model. Considering the intra-cluster correlation, facilities and departments were considered as a two-level hierarchical structure in this order.

As independent variables, responses to items 1–18 in the questionnaire were divided into two categories: agree and disagree. Individuals who answered ‘strongly agree’ or ‘agree’ were allocated to the ‘pros’, and those who answered ‘disagree’ or ‘strongly disagree’ were allocated to the ‘cons’. The factor of years of experience was used as a continuous variable. Age data were excluded from the model to avoid the excess risk of multicollinearity with the factor of years of experience.

The RR measurement method (item 20) was divided into two categories: ‘full 1 minute’ or ‘30-second doubled’ and ‘15-second multiplied by 4’ or ‘10-second multiplied by 6’, with the former category considered as standard. All P-values were two-tailed; P-values less than 0.05 were considered statistically significant in the univariate analysis. The main aim of this study was to prioritise the potential factors. Thus, the Benjamini–Hochberg procedure was used to adjust the P-values in multiple testing in order to control the false discovery rate (FDR) (Benjamini and Hochberg, 1995); FDR <0.1 was considered the threshold. As there were few missing data, the authors performed a complete case analysis. Data were analysed using STATA, version 16.1 (Stata Corp, College Station, TX, USA).

Ethics approval

The Institutional Review Board of Jichi Medical University approved this study (Clinical research 17-165). All the participants included in this study provided written informed consent.


Participant characteristics

Of the 644 nurses eligible for this study, 592 (92%) responded to the questionnaire. After excluding participants who did not respond (n=52), did not engage in vital signs assessment at all (n=8), did not provide consent (n=2), and had missing outcome data (n=9), 573 (89%) participants were included in the study. The completion rates of each facility were as follows: Facility A, 82.2%; Facility B, 96.9%; Facility C, 82.7%; Facility D, 92.1%; Facility E, 90.3%; Facility F, 93.2%; Facility G, 82.5%; Facility H, 98.4%; and Facility I, 55.6%. The participants' baseline data are presented in Table 3. The overall proportion of men was 9.5%. The overall mean (SD) age and years of experience were 41.3 ± 12.3 years and 15.3 ± 11.1 years, respectively. The distribution of the participants according to the departments was as follows: emergency room, 3.3%; internal ward, 9.4%; mixed ward, 53.2%; outpatient, 23.2%; and surgical ward, 10.6%. The distribution of the participants as per the shortening method used was as follows:1 minute, 41.0% 30-second doubled, 32.1%; 15-second multiplied by 4, 18.5%; and 10-second multiplied by 6, 8.2%.

Table 3. Characteristics of participants
Infrequent measurers* (n=426) Frequent measurers (n=147) Total (n=573)
Age, mean (SD) (years)   41 (12) 41 (12) 41 (12)
Sex, male   39 (9.2%) 16 (10.9%) 55 (9.6%)
Years of experience, mean (SD) (years)   15 (11) 16 (12) 15 (11)
Facility, N (%) Facility A (>200 beds) 81 (19.0%) 18 (12.2%) 99 (17.3%)
Facility B (>200 beds) 85 (20.0%) 41 (27.9%) 126 (22.0%)
Facility C (100–199 beds) 60 (14.1%) 10 (6.8%) 70 (12.2%)
Facility D (100–199 beds) 54 (12.7%) 29 (19.7%) 83 (14.5%)
Facility E (100–199 beds) 31 (7.3%) 24 (16.3%) 55 (9.6%)
Facility F (<99 beds) 35 (8.2%) 8 (5.4%) 43 (7.5%)
Facility G (<99 beds) 22 (5.2%) 0 (0.0%) 22 (3.8%)
Facility H (<99 beds) 48 (11.3%) 15 (10.2%) 63 (11.0%)
Facility I (<99 beds) 10 (2.3%) 2 (1.4%) 12 (2.1%)
Department, N (%) Emergency room 12 (2.8%) 7 (4.8%) 19 (3.3%)
Internal ward 41 (9.6%) 13 (8.8%) 54 (9.4%)
Mixed ward 228 (53.5%) 77 (52.4%) 305 (53.2%)
Outpatient 97 (22.8%) 36 (24.5%) 133 (23.2%)
Surgical ward 48 (11.3%) 13 (8.8%) 61 (10.6%)
No response 0 (0.0%) 1 (0.7%) 1 (0.2%)
Length of time for respiratory rate measurement, N (%) 1 minute 179 (42.0%) 56 (38.1%) 235 (41.0%)
30-second doubled 138 (32.4%) 46 (31.3%) 184 (32.1%)
15-second multiplied by 4 76 (17.8%) 30 (20.4%) 106 (18.5%)
10-second multiplied by 6 32 (7.5%) 15 (10.2%) 47 (8.2%)
No response 1 (0.2%) 0 (0.0%) 1 (0.2%)

SD=standard deviation

* Participants who answered ‘sometimes’ or ‘never’ for item 19

Participants who answered ‘always’ or ‘frequently’ for item 19

Association between hospital nurses' factors and the frequency of RR measurement

The proportion of frequent measurers was 25.7% (n=147). Table 4 shows the ORs and 95% CIs regarding the association between the hospital nurses' factors and the frequency of RR measurements. The model fits the data well, as reflected in the goodness-of-fit statistics. Five factors, shortened-count method use, importance (item 2), negative experiences (item 12), inconvenience (item 14), and educational experiences (item 18), showed independent associations with the frequency of RR measurement after controlling for FDR. The adjusted ORs (95% CIs) for the factors of importance (item 2) and educational experiences (item 18) were 2.24 (1.13–4.45) and 2.26 (1.20–4.26), respectively. The adjusted ORs (95% CIs) for the factors of shortening method use, negative experiences (item 12), and inconvenience (item 14) were 0.61 (0.42–0.91), 0.45 (0.29–0.70), and 0.41 (0.26–0.65), respectively. The estimates of the between facility level and department level variances (95% CI) were 0.58 (0.17–2.05) and 0.05 (0.01–1.81), respectively.

Table 4. Factors associated with frequent measurement of respiratory rate (n=753)
Crude OR 95% CI P-values Adjusted OR 95% CI P-values P<(i/m)Q
Sex (male) 1.10 [0.63–1.94] 0.340 1.10 [0.61 - 1.99] 0.760  
Years of experience 0.96 [0.68–1.35] 0.791 1.11 [0.77 - 1.61] 0.564  
Shortened-count method use 0.79 [0.54–1.14] 0.177 0.61 [0.42 - 0.91] 0.014 *
Item 1: Personal autonomy 2.24 [1.47–3.42] < 0.001 1.52 [0.95 - 2.44] 0.079  
Item 2: Importance 5.29 [3.12–9.00] < 0.001 2.24 [1.13 - 4.45] 0.021 *
Item 3: Usefulness 4.47 [2.66–7.49] < 0.001 1.33 [0.66 - 2.69] 0.429  
Item 4: Requests from co-workers 2.2 [1.56–3.12] < 0.001 1.51 [1.03 - 2.22] 0.035  
Item 5: Positive experiences 3.73 [2.41–5.76] < 0.001 1.34 [0.78 - 2.28] 0.290  
Item 6: Severity of patient's condition 2.65 [1.60–4.37] < 0.001 0.90 [0.51 - 1.60] 0.723  
Item 7: Reliability 1.63 [1.04–2.56] 0.033 0.89 [0.53 - 1.49] 0.644  
Item 8: Workplace habits 1.71 [1.21–2.42] 0.002 1.22 [0.83 - 1.78] 0.320  
Item 9: Dispensability 0.46 [0.32–0.65] < 0.001 0.71 [0.48 - 1.05] 0.083  
Item 10: Cost-effectiveness 0.50 [0.32–0.77] 0.002 1.24 [0.76 - 2.02] 0.396  
Item 11: Busyness 0.44 [0.31–0.62] < 0.001 0.85 [0.56 - 1.28] 0.434  
Item 12: Negative experiences 0.28 [0.19–0.41] < 0.001 0.45 [0.29 - 0.70] < 0.001 *
Item 13: Non-severity of patient's condition 0.75 [0.52–1.07] 0.116 1.16 [0.77 - 1.74] 0.479  
Item 14: Inconvenience 0.27 [0.18–0.40] < 0.001 0.41 [0.26 - 0.65] < 0.001 *
Item 15: Confidence of intuitive understanding 0.94 [0.64–1.37] 0.743 1.30 [0.86 - 1.97] 0.213  
Item 16: Procedural difficulty 0.92 [0.54–1.56] 0.763 1.07 [0.60 - 1.91] 0.828  
Item 17: Premonition of failure 0.81 [0.58–1.13] 0.210 0.96 [0.67 - 1.38] 0.841  
Item 18: Educational experiences 2.06 [1.14–3.71] 0.016 2.26 [1.20 - 4.26] 0.011 *

OR=odds ratio; CI=confidence interval

* P-values smaller than (i/m)Q were considered significant (i: ascending order of P-values; m: number of comparisons; Q: false discovery rate)


This study detected five independent factors associated with the frequency of RR measurement by the nurses. The perception of importance (item 2) and educational experiences (item 18) were positively associated with the frequency of RR measurement. However, shortening method use, negative experiences (item 12), and inconvenience (item 14) showed a negative association. The authors concluded that the three potential concepts of promoting education, feedback systems, and automation should be prioritised to optimise the frequency of RR measurement, arriving at this conclusion by reviewing relevant previous research.


The result that educational experiences (item 18) had the highest OR out of all variables for the frequency of RR measurement supports the previous findings. As only 33% of patients with oxygen saturation below 90% show tachypnea, the RR cannot be substituted by pulse oximetry (Mower et al, 1996). However, a previous study noted that poor understanding of and overconfidence in pulse oximetry could contribute to poor assessment of the RR (Elliott and Baird, 2019). Therefore, the importance of educational opportunities to correct misunderstandings and overconfidence cannot be overemphasised. The other independent factor of importance (item 2) showing positive association could be an outcome of education. The present study confirmed that nurses considering RR measurement important and having educational experiences tend to perform the RR measurement frequently.

Feedback systems

Considering the independent association of negative experiences (item 12), a substantial number of nurses might have reduced the frequency of RR measurement based on their workplace experiences. A reasonable explanation for this phenomenon could be the lack of feedback in the workplace. Even though requests from co-workers (item 4) did not show a statistically significant association in this study, this perception had a relatively high positive association with the frequency of RR measurement by the nurses. This result also potentially explains the importance of feedback. Hogan (2006), one of the early researchers in this field, mentioned the necessity of feedback systems in the workplace to reduce the neglect of RR measurement. The results shown here support this suggestion.

The EWS, one of the clinical scoring systems used to determine the severity of a patient's condition quickly, has been used as a criterion in the rapid response system (RRS). The RRS is a feedback system used to respond to the early signs of deterioration in patients (Morgan and Williams, 1997; Goldhill et al, 2005). Indeed, two previous studies reported a positive effect stemming from the introduction of the EWS with regard to the frequency of RR measurement. One observation made was that the frequency of RR measurement improved dramatically following the introduction of the EWS (Odell et al, 2007). The study further revealed that EWS introduction and critical care outreach service significantly improved the rate of RR measurement from 6.0% to 77.9%. The second study reported that EWS introduction increased the RR measurement rate from 29.5% to 91.2% over 12 months (McBride et al, 2005). These studies clearly demonstrate the importance of feedback systems in the workplace. Nurses who infrequently assess the patient's RR seem to start checking vital signs once they have obtained the specific criteria for how to use RR data in their daily tasks.

Shortened-count method use

Estimation methods (calculating breaths per minute from a count over a much shorter time) are designed to reduce the time taken for RR measurement. This type of adaptive behaviour might be justified when it improves the accessibility of RR measurement. Although such methods have been criticised in several previous studies (Philip et al, 2015; Flenady et al, 2017; Rimbi et al, 2019; Harry et al, 2020), the 30-second count doubled method is probably one of the most common used to measure RR (Gravelyn and Weg, 1980). The results of the present study showed that less than half of the participants used the 1-minute method, which is the most conservative method, and that the frequent measurers tended to use shorter-count methods, especially the 15-second multiplied by 4 and 10-second multiplied by 6 methods. However, shortened-count method use based on the set categorisation (‘shortened’ 15-second or 10-second count factored up vs ‘standard’ 1 full minute or 30-second count doubled) showed a negative association with the frequency of RR measurement. Considering the positive association of educational experiences (item 18) and importance (item 2) factors and the negative association of inconvenience (item 14), promoting the use of such estimation methods is less likely to improve the frequency of RR measurement by nurses.

Potential need for automation

Of the four traditional vital signs, RR is the only one measured through direct and physical observation as the gold standard, whereas the measurement of the other vital signs has become automated by digital machines in most clinical settings. RR examiners have to focus on the patient's respiratory movements with utmost care and attention. At the same time, they also have to check the time during the measurement (World Health Organization, 1990). In most busy clinical situations, this type of double task could present an excessive work burden both physically and mentally. Hence, it was expected that inconvenience (item 14) would show an independent negative association with the frequency of RR measurement.

A previous study revealed that a patient check taking place during the evening shift was one of the strongest risk factors for not measuring RR in a three-shift setting (Gravel et al, 2006). The authors reasoned that the imbalance in the nurse–patient ratio during this shift could induce an excessive workload; thus, RR measurement was missed 4.26 times more often during the evening shift than that during the night shift. Therefore, automation of RR measurement is necessary to reduce the workload by mitigating inconvenience (Hogan, 2006; Philip et al, 2013; Ansell et al, 2014; Nicolò et al, 2020).

As many health professionals are facing clinical burdens and a shortage of time, wearable electronic devices could be an ideal solution. Various electronic devices that automatically measure the RR have been developed as an opportunity to reduce the workload (Lovett et al, 2005). Recently, many researchers have begun verifying the accuracy of these new electronic devices in clinical settings (Hernandez-Silveira et al, 2015; Lee, 2016).

Thus, promotion of education, feedback systems, and automation should be the primary issues addressed in future studies on the neglect of RR measurement. Further studies are warranted to identify ways to implement appropriate interventions for these improvements.


This study has several limitations. First, it was conducted in only one prefecture in Japan. Hence, the results may not be directly applicable to other settings. Second, as the design of this study was cross-sectional and observational, no causal relationship could be deduced from the data. However, the main aim of this study was to identify the nurse-related factors associated with the frequency of RR measurement. These results provide new information to prioritise the crucial factors from the several potential factors. These data could be used to plan future interventional studies. Third, the frequency of RR measurement as an outcome was based on self-reported data. Therefore, the reported frequency may differ from the actual frequency. Fourth, although the original questionnaire was developed based on the Delphi method to select relevant perceptions comprehensively with consensus, each question was not subjected to the statistical validation process. Thus, some questions that showed no association even before adjustment may fail to capture the nurses' perceptions. Finally, this study did not obtain detailed information on the participants' baseline characteristics, such as the level of education and years of experience in the current department. Further studies are needed to overcome these limitations.


The nurses' perceptions of importance and their educational experiences showed a positive association with the frequency of RR measurement, whereas shortening method use, negative experiences, and perception of inconvenience showed a negative association. Prioritising the crucial factors from the several potential factors could prove beneficial for optimising the frequency of RR measurement in clinical settings.


  • Respiratory rate is often neglected, despite the fact that it is a sensitive predictor of patient deterioration.
  • The reason for this neglect in clinical settings remains unclear, and only a few studies have investigated why health professionals disregard respiratory rate measurement
  • This study investigated the influence of 18 factors extracted from previous studies on the frequency of respiratory rate measurement by nurses.
  • The nurses' perceptions of importance and their educational experiences showed a positive association with the frequency of respiratory rate measurement, whereas use of shortening methods, negative experiences, and perception of inconvenience showed a negative association.
  • Prioritising these independent factors from among the several potential factors might prove beneficial in optimising the frequency of respiratory rate measurement in clinical settings.

CPD reflective questions

  • Do you ever feel that your perception of a nursing task affects your behaviour towards it?
  • Can you think of a vital sign that is frequently neglected, regardless of its clinical importance?
  • Considering some of the factors discussed here, what changes would help to optimise nursing care in this respect?