ArticleBMC nursing2026
Inpatient ward nurses' perceptions of extended visiting hours in a Singapore tertiary acute hospital: a repeated cross-sectional mixed-methods study.
Article in BMC nursing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundExtended family visiting hours may support person- and family-centred care but can increase operational burden for ward nurses. The relevant operational domains include noise and rest, procedure timing and ward routines, family interactions and communication, infection control, ward space and workflow, care quality and coordination, and stress and workload. Evidence on how nurses' perceptions across these domains evolve during implementation remains limited.
methodsWe conducted a repeated cross-sectional, quantitatively dominant mixed-methods study using two anonymous hospital-wide surveys: Wave 1 (16-30 March 2025) and Wave 2 (30 March-15 April 2026). The analytic samples comprised 268 and 338 nursing respondents. Thirteen de novo items derived from operational monitoring objectives were compared using Pearson chi-square tests with Benjamini-Hochberg false-discovery-rate correction; binary logistic regression estimated the odds of reporting 'Worsened'. Brief free-text comments underwent structured descriptive content analysis, with operational themes stratified by the common general-suggestions prompt and the Wave-2-only problem-focused prompt.
resultsBased on human-resources-confirmed inpatient ward nurse denominators (2,625 and 2,792), response rates were 10.2% and 12.1%. Response distributions were more favourable in Wave 2 for 12 of 13 shared items after false-discovery-rate correction (q < 0.05; odds ratios for 'Worsened' 0.33-0.57). Infection control was the sole estimate compatible with no cross-wave difference (OR 0.92, 95% CI 0.67-1.27), while 46.2% still rated it 'Worsened' in Wave 2. Workload (43.2%), ward space (48.8%), noise (39.3%), and workflow (34.0%) also remained substantial burdens. Prompt-stratified free text described relational benefits alongside persistent interruptions, infection-control monitoring, noise/rest concerns, and variable caregiver participation.
conclusionsNursing respondents reported more favourable perceptions in Wave 2 across most domains, particularly relational and communication domains, but the anonymous repeated cross-sectional design cannot distinguish adaptation from differences in respondent composition. The combined pattern is most consistent with partial adaptation rather than full normalisation. Persistent infection-control, workload, noise, and space burdens indicate priorities for structural support and prospective evaluation.
trial registrationNot applicable.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.