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Multicenter Study
. 2019 Jan 15;19(1):20.
doi: 10.1186/s12887-018-1380-8.

The influence of gestational age in the psychometric testing of the Bernese Pain Scale for Neonates

Karin Schenk  1 , Liliane Stoffel  2 , Reto Bürgin  3 , Bonnie Stevens  4 , Dirk Bassler  5 , Sven Schulzke  6 , Mathias Nelle  2 , Eva Cignacco  3
Affiliations
Multicenter Study

The influence of gestational age in the psychometric testing of the Bernese Pain Scale for Neonates

Karin Schenk et al. BMC Pediatr. .

Abstract

Background: Assessing pain in neonates is challenging because full-term and preterm neonates of different gestational ages (GAs) have widely varied reactions to pain. We validated the Bernese Pain Scale for Neonates (BPSN) by testing its use among a large sample of neonates that represented all GAs.

Methods: In this prospective multisite validation study, we assessed 154 neonates between 24 2/7 and 41 4/7 weeks GA, based on the results of 1-5 capillary heel sticks in their first 14 days of life. From each heel stick, we produced three video sequences: baseline; heel stick; and, recovery. Five blinded nurses rated neonates' pain responses according to the BPSN. The underlying factor structure of the BPSN, interrater reliability, concurrent validity with the Premature Infant Pain Profile-Revised (PIPP-R), construct validity, sensitivity and specificity, and the relationship between behavioural and physiological indicators were explored. We considered GA and gender as individual contextual factors.

Results: The factor analyses resulted in a model where the following behaviours best fit the data: crying; facial expression; and, posture. Pain scores for these behavioural items increased on average more than 1 point during the heel stick phases compared to the baseline and recovery phases (p < 0.001). Among physiological items, heart rate was more sensitive to pain than oxygen saturation. Heart rate averaged 0.646 points higher during the heel stick than the recovery phases (p < 0.001). GA increased along with pain scores: for every additional week of gestation, the average increase of behavioural pain score was 0.063 points (SE = 0.01, t = 5.49); average heart rate increased 0.042 points (SE = 0.01, t = 6.15). Sensitivity and specificity analyses indicated that the cut-off should increase with GA. Modified BPSN showed good concurrent validity with the PIPP-R (r = 0.600-0.758, p < 0.001). Correlations between the modified behavioural subscale and the item heart rate were low (r = 0.102-0.379).

Conclusions: The modified BPSN that includes facial expression, crying, posture, and heart rate is a reliable and valid tool for assessing acute pain in full-term and preterm neonates, but our results suggest that adding different cut-off points for different GA-groups will improve the BPSN's clinical usefulness.

Trial registration: The study was retrospectively registered in the database of Clinical Trial gov. Study ID-number: NCT 02749461 . Registration date: 12 April 2016.

Trial registration: ClinicalTrials.gov NCT02749461.

Keywords: Contextual factors; Gestational age; Neonates; Pain assessment; Premature infants; Psychometric testing; Reliability; Validity.

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Conflict of interest statement

Ethics approval and consent to participate

The study was approved by the Ethics Committee Bern (2015–238), the Ethics Committee northwest/central Switzerland EKNZ (2015–385) and the Ethics Committee Zurich (2015–563).

Written informed consent was obtained from parents according to the protocol approved by the ethics committees. We did not expose infants to additional painful situations. No heel sticks were performed solely for research purposes. We upheld the current standard of care in pain prevention by giving oral sucrose to all infants before the heel stick procedure.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
The structure of the factor model used for the subjective subscale of the BPSN
Fig. 2
Fig. 2
The structure of the factor model used for the physiological subscale of the BPSN
Fig. 3
Fig. 3
Specified covariances between factors
Fig. 4
Fig. 4
Flow diagram of the recruitment and data collection process
Fig. 5
Fig. 5
Factor loadings of the baseline factor models for the subjective subscale
Fig. 6
Fig. 6
Factor loadings of the baseline factor models for the physiological subscale
See this image and copyright information in PMC

References

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