The effect of video visitation on intensive care unit patients and family members outcomes during the COVID-19 pandemic: A randomised controlled trial

Abstract

Objective

To investigate the effect of video visitation on intensive care patients’ and family members’ outcomes during the COVID-19 pandemic.

Design

This is a randomised controlled trial.

Setting

An adult intensive care unit in a tertiary hospital in Beijing, China.

Methods

A total of 121 adults, who were >18 years of age, conscious, able to communicate verbally, and admitted to the intensive care unit for over 24 hours were randomised into the intervention (video visitation) (n = 65) and control (n = 56) Groups. A total of 98 family members participated. Patient primary outcomes included anxiety and depression, measured using the Hospital Anxiety and Depression Scale. Secondary outcomes included patient delirium and family anxiety assessed using the Confusion Assessment Method scale and Self-Rating Anxiety Scale, respectively; and patient and family satisfaction, measured using a questionnaire routinely used in the hospital.

Results

There were no statistically significant differences between the groups in patients’ anxiety (t = 1.328, p = 0.187) and depression scores (t = 1.569, p = 0.119); and no statistically significant differences in delirium incidence between the groups (7.7 % vs 7.1 %, p > 0.05). There were no significant differences in changes in family members’ anxiety scores (t = 0.496, p = 0.621). A statistically significant difference in satisfaction was found between the two group patients (86.1 % vs 57.2 % of patients were satisfied with using video visitation, p < 0.05), and the result of family members’ satisfaction was also statistically significant (88 % vs 62.5 % of family members were satisfied with using video visitation, p < 0.05).

Conclusion

Video visitation did not seem to influence anxiety, but the use of video visitation can improve the patient and their family members’ satisfaction. Future research is needed to determine the feasibility of embedding video visitation into routine practice, and the optimal frequency and length of video visitation in relation to patients’ and family members’ outcomes.

Implications for clinical practice

Video visitation improved patient and family members' satisfaction. Therefore, clinicians should consider using video visitation when face to face visit is restricted. Video visVitation did not reduce patient anxiety significantly in this study maybe because the average length of intensive care stay was too short. Future research is needed on its effect on long term intensive care patients.

Introduction

An intensive care unit (ICU) is a clinical area in a hospital that provides life support for critically ill patients. Admission to the ICU can lead to stress, anxiety, and depression in patients and their family members (Beesley et al., 2018, Ferge et al., 2018). Historically, many ICUs worldwide had restrictive visitation policies due to infection concerns (Giannini et al., 2008, Liu et al., 2013, Noordermeer et al., 2013). However, patient-centred, and family-centred care has now been adopted by ICUs worldwide, and family members are encouraged to visit and participate in patient care (Davidson et al., 2007). Previous studies have demonstrated that family engagement has a positive effect on ICU patients with decreased anxiety, confusion, agitation, and delirium incidence (Marra et al., 2017). Subsequently, ICUs in many countries have adopted a more flexible approach regarding visits. The American Association of Critical Care Nurses and the World Federation of Societies of Intensive and Critical Care Medicine recommend open visitation in ICUs (Johnson et al., 2014, Davidson et al., 2017). The benefits of open visitation include fewer and shorter episodes of ICU delirium in patients, improved patient and family satisfaction, and enhanced family well-being (Nassar Junior et al., 2018, Rosa et al., 2017).

However, the advent of the coronavirus-19 pandemic (COVID-19) has resulted in physical distancing becoming a key strategy to prevent the spread of infection. Consequently, visitation to ICUs was prohibited and family members were not able to be physically present at patients’ bedside. Robert et al. (2020) reported that COVID-19 threatened family-centred care in ICUs. A suitable method was needed to facilitate communication between patients and their families and to reduce their worries and anxiety. Azoulay and Kentish-Barnes (2020) proposed a 5-point strategy to maintain connections between relatives and critically ill patients, including scheduling routine telephone calls and encouraging contact through encouraging families to use options, such as web-based remote family conferences, as well as supplying standardized written information for the relatives. Hart et al. (2020) recommended daily videoconferencing (or telephone contact) with a primary family contact.

There has been a rapid and global acceptance of modern communication technology for clinical purposes, which has developed further during the pandemic. Face-to-face remote communication is well established in ICUs. Video conferencing methods are being used internationally to enable remote communication in intensive care, end-of-life care, and throughout recovery. Sasangohar et al. (2020) showed that the use of a ‘virtual ICU platform’ for remote family visitations promoted happiness, gratitude, and relief, as well as a sense of closure for those who lost loved ones. Mobile phone applications (Apps) with video-conferencing functions, such as FaceTime and WhatsApp, enabled families to see and talk to their loved ones in ICUs, while maintaining the necessary physical distancing (Montauk and Kuhl, 2020). However, there is limited evidence on the effectiveness of video visitation among critically ill patients and their family members. In this study, a family member(s) is defined as the person or people whom the patients identified as a family member(s) and with whom they wanted to be in contact, being individuals who provide support and with whom the patient has a significant relationship.

Aim

This study is aimed to examine the effect of video visitation on patients’ anxiety and depression, the incidence of delirium, family’s anxiety, and patients’ and family members’ satisfaction with visitation during the COVID-19 pandemic.

Methods

Study design

This parallel group single-blind randomised controlled trial was conducted between March and November 2020. The paper was written following the Consolidated Standards of Reporting Trials (CONSORT) criteria (Moher et al., 2012).

Setting

This study was conducted in Peking University First Hospital (PKUFH), an 1,805-bed tertiary teaching hospital and one of the largest hospitals in China, with approximately 10,000 outpatients daily, almost 100,000 patients, and nearly 40,000 operations performed annually. The PKUFH’ surgical ICU is open-plan with 10 beds. It admits post-operative patients who are older, with underlying conditions, and have undergone major surgery. Approximately 1,000 patients are admitted to this surgical ICU every year, and the average ICU length of stay (LOS) is 3.3 days. Patients whose APACHE II score ≥ 8 points accounted for 88 % of patients admitted in the last three years.

Participants

The inclusion criteria for patients were being 18 years old and above, staying in ICU for more than 24 hours, able to communicate verbally, willing to share their WeChat account with nurses, and consenting to participate. The exclusion criteria were as follow: being without caregiver/ family, diagnosed with dementia or mental health diagnosis, having a cognitive disorder, with hearing or speech deficit, and not having a smart phone or WeChat account. Majority of the patients admitted into this ICU were ventilated on admission. If the patient was on a mechanical ventilator on admission, researcher would assess patients for inclusion and exclusion criteria after the endotracheal tube was removed. For family members, the person who was the patient’ closest next of kin (e.g., spouses, children, parents, sisters, or brothers) or the one with whom the patients wanted to be in contact was enrolled. Only one family member per patient is enrolled into the study.

Routine care regarding visitation

Patients allocated to the control group were provided with routine care. No in-person family member visits were allowed during the pandemic in this hospital. After patients were admitted to the ICU, a research nurse was delegated the task to communicate, often via phone call, with the patient’s family members or their proxy. The call was often made when there was an update in care or the patients’ conditions changed.

Intervention

The intervention, video visitation, was commenced after randomisation. The patients and their family members allocated to the intervention group were given the option of using a video call method to communicate with each other once a day, as well as with the patient’s nurse, in addition to the routine visit method used in the control group. The Chinese social media app, WeChat (which has video conferencing capability), was used for the video visitation. WeChat is one of the most widely used social media app and multi- purpose smartphone applications in China (Montag et al., 2018). The core functions of WeChat include messaging services and video chats/conferencing. A research nurse was responsible for initiating a WeChat video call using a mobile device with the patients' family members every afternoon. And the nurse would be at the patient bedside to ensure their safety during the intervention. To reduce bias and ensure the quality of the study, requesting that family members making video calls with patients not talk with other patients’ families about their experience. Furthermore, nurses closed the curtain around patients to ensure privacy whenever a video call was conducted, although there was sufficient distance and space between each patient. There were no side effects reported due to making video calls in the intervention group.

Outcomes and measures

Primary outcomes

The primary patient outcome was symptoms of anxiety and depression among ICU patients, measured using a validated Chinese version of the Hospital Anxiety and Depression Scale (HADS), which is designed to measure anxiety and depression in hospitalized patients. The HADS is a 14-item scale composed of two subscales for anxiety and depression. The scores for each subscale range from 0 (no symptoms) to 21(maximally severe symptoms). A HADS score greater than or equal to 8 on either subscale is indicative of possible or probable anxiety or depression (Zigmond and Snaith, 1983). The internal consistency coefficients measured using Cronbach’s alpha were 0.879 for the total score, 0.806 for the depression subscale, and 0.806 for the anxiety subscale (Zhenxiao et al., 2017).

Secondary outcomes

The secondary outcomes included incidence of delirium in patients during their ICU stay and family member-related outcomes. The incidence of delirium during the ICU stay was measured using the Chinese version of Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) (Ely et al., 2001, Wang et al., 2013). The sensitivity and specificity of the Chinese version of the CAM-ICU were both more than 90 %, and the inter-rater reliability of the two nurse investigators was good, with a κ coefficient of 0.92. Delirium was defined as at least one positive CAM-ICU screening during the entirety of the patients’ ICU stay.

The symptoms of anxiety among family members were measured using a validated Chinese version of the Self-Rating Anxiety Scale (SAS) (Jiong and Yinhua, 2006), a tool that is suitable for adults with anxiety and in the general population. SAS is a self-report scale with 20 items covering a variety of anxiety symptoms. Responses were rated using a 4-point scale, ranging from 1 to 4 (anxiety level ranging from low to high). Items of the SAS scale include both negative and positive experiences, with the latter being reverse-scored. Raw scale scores for the SAS ranged from 20 to 80(Zung, 1971).

The satisfaction of ICU patients and their family was measured using a questionnaire routinely used in the hospital. The questionnaire included five items: visiting method, visiting time, visiting duration, visiting frequency, and whether the patients’ needs were timeously met during their ICU stay.

Sample size calculation

The primary outcome of this study was a change in patient anxiety. The results of a previous study in China showed that the average anxiety score of ICU patients was 6.02 ± 1.65 (Yanmei and Guining, 2019). In this study, the equivalent margin was a reduction of three points on the anxiety scores of the patients in the intervention group compared with the control group. Using two independent sample content calculation formulas with a statistical power of 80 % and an α error of 0.05, the number of participants required as 60 per group for a total of 120 patients in this study. The sample size of family members was calculated based on a ratio of 1:1 between family members and patients. The sample size of this study was not calculated on the depression scores, because based on current evidence, changes to depression scores from interventions often take months of follow up (Werner-Seidler et al., 2017, Kramer et al., 2022). Thus, not anticipate a change in depression scores in this patient/family population due to the short average LOS in ICU.

Randomisation

A researcher (CY), who did not implement interventions or collect data, performed the randomisation using a computer-generated random numbers table and numbered brown envelopes in sequence with the group assignment inside. Patients were then numbered from 1 to 120 based on of the order of meeting eligibility after admission to the ICU. If a patient was conscious and not ventilated in admission into the ICU, their eligibility was assessed 24 h after admission. However, for the ventilated patients on admission, their eligibility was assessed two hours after they were extubated, or after being admitted into ICU for 24 h, whichever occurs later. After patients were admitted into the ICU for more than 24 h and met the inclusion criteria, the researcher opened the envelope with the corresponding serial number. The card in the envelope indicated whether the patient was assigned to the intervention or control group. Only the researcher (CY) knew the patients’ group and was also responsible for obtaining informed consent from the patients and their families and registering patients’ information.

Blinding

Blinding of the nurses and patients was not possible, as the patients in the intervention group knew about the visitation method. However, the assessors were blinded. The ICU nurses who were blinded to the patient group allocation conducted outcome measure. Since the anxiety/depression scales and satisfaction questionnaire involve self-reported information, the patients’ responses may have been influenced by their awareness of being in the intervention group.

Data collection and procedure

The study began on the day when patients met the inclusion criteria. The researcher informed the patients about the study purpose, that participation was voluntary and would not affect their treatment, and obtained their informed consent. Patients’ anxiety and depression were assessed on admission into and discharge from the ICU. Patients’ delirium was measured using the CAM-ICU by blinded trained ICU nurses once every-eight hours from admission. Patients and their family members were asked to complete the satisfaction questionnaire after the patients were discharged from ICU and after they arrived on the general wards. Three research nurses, who had no knowledge of group allocation, were responsible for distributing and collecting the satisfaction questionnaire from the patients and their family members. Patients’ family members’ anxiety scores were assessed using the SAS (self-report) upon admission to and discharge from the ICU. Two researchers (YYX, FW) distributed and collected the completed SAS from patients’ family members.

Statistical analysis

Baseline patient characteristics are presented as mean ± standard deviation (SD) for continuous variables and frequency and percentages for categorical variables. The normality of each variable was verified using the Kolmogorov-Smirnov test. Differences in clinical and demographic variables were analysed using an independent sample t-test for continuous variables that were normally distributed, and a Wilcon’ rank-sum test for data that did not meet a normal distribution. A Pearson’s chi-square test was used for categorical data. The level of significance was set at 0.05. All analyses were performed using SPSS software for Windows (SPSS 17.0, Chicago, IL, USA). Changes in anxiety or depression scores (discharge from ICU - admission to ICU scores) were calculated, and a student’s t-test (unpaired, two-tailed) was used to determine whether anxiety scores differed between the WeChat video visitation and the no visit groups.

Ethical considerations

This study was approved by the Institutional Review Board of the authors’ hospital (2020–235), and the study protocol was registered in the Chinese Clinical Trial Registry (ChiCTR2000034306). While obtaining written consent from patients and their family members, the researcher reassured them that they could decline to participate and opt out at any time and there would be no impact on the treatment they receive in the ICU. A detailed information sheet for the patients and their family members which includes their commitment to the project, their rights to withdraw, privacy, safety, and benefit to them and to the ICU patient population was given to the patients to keep.

Results

Baseline demographics

Screening, eligibility, randomisation, and reasons for participants’ ineligibility after enrolment or withdrawal are shown in Fig. 1 . Of the 696 patients admitted to the ICU between 15 May 2020 and 27 November 2020, a total of 140 patients were eligible, of which 19 were excluded. Following the randomisation procedure, 65 and 56 patients were assigned to the intervention and control group, respectively. The mean age of the 121 participants was 67.0 (14.3) years; 45.5 % were female; and 59.5 % had a high school education or above. The ICU LOS ranged from 1.5 to 14 days and the average length was 3.80 ± 2.39 days. There were no significant differences in baseline characteristics between the intervention and control groups (see Table 1 ). In total, 98 family members participated in this study, including 50 family members in the intervention group and 48 in the control group. Among them, 67.3 % were patients’ children and 24.5 % were spouses. In addition, 15 family members in the intervention group accepted video visitation but did not complete the questionnaire, and 8 family members in the control group did not complete the questionnaire.

Fig. 1.

Flow diagram for the trial.

Table 1.

Baseline characteristics of patients.

Variable		Intervention Group (n = 65)	Control Group (n = 56)	Statistic test χ2/t	P-Value
Age, mean(SD), y		65.51(14.49)	68.82(14.02)	1.273	0.205
Sex, n (%)	Male	35(53.8)	31(55.4)	0.028	0.868
	Female	30(46.2)	25(44.6)
Education level, n (%)	Elementary school	9(13.8)	9 (16.1)	3.490	0.322
	Junior High School	21(32.3)	10(17.9)
	High School	14(21.5)	13(23.2)
	Bachelor degree or above	21(32.3)	24(42.8)
APACHE-II, Mean(SD),		12.78(4.29)	13.24(5.06)	0.526	0.60
HADS anxiety score, Mean (SD)		5.26(3.64)	4.20(3.46)	1.637	0.104
HADS depression score, Mean(SD)		12.89(3.72)	12.60(3.77)	0.428	0.669

Primary outcomes

Changes in patients’ anxiety scores

Table 2 shows the two groups of patients’ anxiety scores at ICU admission and after ICU discharge. The intervention group had a decrease in anxiety scores with a change of 0.48 (SD ± 4.67). The participants in the control group had an increase in anxiety scores of 0.58 (SD ± 4.02). However, t-test showed that there were no statistically significant differences in changes to anxiety scores between admission and discharge (t = 1.328, p = 0.187).

Table 2.

Patients’ anxiety scores measured using HADS.

	Intervention Group (n = 65)	Control Group (n = 56)	Statistic test	P-value
	Mean ± SD	Mean ± SD	t
At admission to ICU	5.26 ± 3.64	4.78 ± 4.24	1.637	0.104
After discharge from ICU	4.20 ± 3.46	4.78 ± 2.77	0.001	0.999
D value	−0.48 ± 4.67	+0.58 ± 4.02	1.328	0.187

Note: D value = After discharge from ICU score- At admission to ICU score.

Changes in patients’ depression scores

Table 3 shows the two groups of patients’ depression scores at admission and after discharge from ICU. After the intervention, the average decrease in depression scores in the intervention group was 7.27(SD ± 4.76), whereas the participants in the control group had an average decrease in depression scores of 5.97(SD ± 4.31). However, these changes in depression scores were not statistically significant.

Table 3.

Patients’ depression scores measured using HADS.

	Intervention Group	Control Group	Statistic test	P-value
	(n = 65)	(n = 56)
	Mean ± SD	Mean ± SD	t
Admission to ICU	12.89 ± 3.72	12.60 ± 3.77	0.428	0.669
Discharge from ICU	5.61 ± 4.59	6.62 ± 4.15	−1.264	0.209
D value	−7.27 ± 4.76	−5.97 ± 4.31	1.569	0.119

Note: D value = After discharge from ICU score- At admission to ICU score.

Secondary outcomes

Patients’ satisfaction with the visiting method

The results of patient satisfaction are summarised in Table 4 . There was a significant difference in patient satisfaction with staff and the visiting method between the two groups (p = 0.033; p = 0.001). Regarding visiting frequency, 70 % of the patients in the intervention group thought that once a day was very suitable or suitable, whereas 13.8 % of the patients wanted more frequent visits. In this study, nurses initiated a WeChat video every afternoon for the intervention group, and approximately 26 % of the patients indicated that the visit time was not suitable. For visit duration, 21.5 % of the patients in the intervention group believed a 5–30 min call to be unsuitable as it was too short.

Table 4.

Patients’ satisfaction with visit.

		Intervention Group (n = 65)	Control Group (n = 56)	Statistic test	P-value
		n(%)	n(%)	χ2
ICU staff solve problem
	Very good	48(73.8)	31(55.4)	4.538	0.033
	Acceptable	17(26.2)	25(44.6)
Visiting method
	Very satisfied	27(41.5)	8(14.3)	17.093	0.001
	satisfied	29(44.6)	24(42.9)
	Medium	5(7.7)	12(21.4)
	Dissatisfied and very dissatisfied	4(6.2)	12(21.4)
Visiting frequency
	Very suitable	25(38.5)	–		–
	Suitable	21(32.3)	–
	Need more	9(13.8)	–
	Need less	10(15.4)	–
Visiting time
	Very suitable	24(36.9)	–		–
	Suitable	24(36.9)	–
	Not suitable	13(20.0)	–
	Very inappropriate	4(6.2)	–
Vising duration
	Very suitable	24(36.9)			–
	Suitable	27(41.5)
	Not suitable	9(13.8)
	Very inappropriate	5(7.7)

The incidence of delirium in patients

Delirium occurred in 5 out of 65 patients (7.7 %) in the intervention group and in 4 out of 56 patients (7.1 %) in the control group. There was no statistically significant difference in the incidence of delirium between the two groups (χ² = 0.013, p = 0.909).

Family members’ anxiety scores

When patients were admitted into the ICU, the baseline anxiety SAS scores of family members showed means of 34.10 (SD ± 8.99) and 31.95 (SD ± 7.75) for the intervention and control group, respectively. No statistically significant differences were found between the two groups at baseline. After the intervention, the anxiety scores of family members in the intervention group showed a mean of 32.40 (SD ± 8.58), whereas the anxiety scores in the control group showed a mean of 31.58 (SD ± 7.67). However, there were no statistically significant differences between the groups (t = 0.496, p = 0.621).

Family members’ satisfaction with visits

The results for family member satisfaction are summarised in Table 5 . There was a significant difference between the intervention and control groups in family members’ satisfaction with the visiting method (p = 0.007). About 62 % (n = 31) of the family members were very satisfied with the WeChat video visitation, and 26 % (n = 13) were satisfied. Regarding visiting frequency, 16 % (n = 8) of the family members wanted more frequent video calls. More than 90 % of the families were satisfied with the video visit time, but 18 % of the family members were not satisfied with the video visit duration.

Table 5.

Family members’ satisfaction with visit.

		Intervention Group (n = 50)	Control Group (n = 48)	Statistic test	P-value
		n(%)	n(%)	χ2
ICU staff solve problem
	Very good	38(76.0)	33(68.8)	0.645	0.422
	Acceptable	12(24.0)	15(31.2)
Visiting method
	Very satisfied	31(62.0)	17(35.4)	10.666	0.007
	satisfied	13(26.0)	13(27.1)
	Medium	4(8.0)	14(29.2)
	Dissatisfied and very dissatisfied	2(4.0)	4(8.4)
Visiting frequency
	Very suitable	26(52.0)	–		–
	Suitable	14(28.0)	–
	Need more	8(16.0)	–
	Need less	2(4.0)	–
Visiting time
	Very suitable	25(50.0)	–		–
	Suitable	21(42.0)	–
	Not suitable	2(4.0)	–
	Very inappropriate	2(4.0)	–
Vising duration
	Very suitable	18(36.0)			–
	Suitable	23(46.0)
	Not suitable	7(14.0)
	Very inappropriate	2(4.0)

Discussion

This randomised controlled trial showed that during the strict hospital visitation restrictions during COVID-19 pandemic, the use of video visitation in the ICU did not significantly reduce patient anxiety, depression, and the incidence of delirium. However, the use of video visitation significantly improved the satisfaction of patients and their families.

To the best of our knowledge, this is the first randomised controlled trial to compare the effectiveness of video visitation in an ICU setting on patient and family outcomes. The results showed that there were no significant changes in patients’ anxiety scores when they were admitted to and discharged from the ICU. Previous studies have shown that 46 % of critically ill patients experience anxiety symptoms (Hatch et al., 2018). One possible explanation for this non-significant change may be because there was only one video call made per day for the patients and family members to communicate. Many other factors can also influence patient anxiety, such as their state of understanding, fear of moving to the ward, and fear of ‘being left’ in a ward, whereas in the ICU they always had a nurse at their bedside. Previous studies have found that patients often report an increased level of anxiety at ICU discharge (Choi et al., 2016). Further research is needed to investigate whether more frequent video visitation or providing video calls after discharge from the ICU could significantly reduce or prevent patient anxiety.

There was no statistical difference in the changes in patient depression scores between the intervention and control groups, possibly because patient ICU length of stay in this study was too short to show an effect (mean 3.80, SD ± 2.39 days).

No statistically significant difference was found in the incidence of delirium between the two groups. Similarly, Pun et al (2021) reported that family visitation (in person or virtual) was associated with a lower risk of delirium. A potential explanation for this finding is that the short implementation duration of the video visitation may have lessened the potential benefits. In addition, the present eligibility criteria excluded patients with an increased risk of delirium.

This study showed statistically significant differences in patient satisfaction scores regarding interaction with staff and the visit method between the two groups. More than 70 % of the patients in the intervention group reported that ICU staff resolved their queries in real-time and met their needs, and about 86.1 % of patients were satisfied with the video visitation. Similarly, Xiaorong Ma and Yawen (2017) compared the effects of video and restricted visits in the ICU and found that the satisfaction of the intervention group was significantly higher than that of the control group. Regarding the frequency of video visitation, 70 % of the patients thought that once a day was very suitable or suitable, whereas 13.8 % of the patients wanted more frequent visits. In this study, nurses initiated a video call every afternoon in the intervention group, and approximately 26 % of the patients indicated that the visit time was not suitable. For visiting duration, 21.5 % of the patients in the intervention group thought 5–30 min was too short. Therefore, if conditions permit, video visiting frequency should be increased, video visitation duration extended, and WeChat video calls further facilitated according to the needs of patients and their families. Common barriers to virtual visiting included insufficient staff time, rapid implementation of more challenging videoconferencing technology, and challenges associated with family member ability to use video technology or in having access to a device (Rose et al., 2021).

Critical care settings may expose family members to various of stressors, such as problems with communication and uncertainty about patient survival and rehabilitation (Schmidt and Azoulay, 2012). The effect of video visitation on family member anxiety in this study showed no differences between the two groups. However, there was a significant difference between the intervention and control groups in family member satisfaction with the visiting method. Approximately 62 % of the family members were very satisfied with the video visitation, and 26 % were satisfied. Similarly, a significantly high percentage of family members have a positive attitude towards virtual visits (Sasangohar et al., 2020). Regarding visiting frequency, 16 % of the family members wanted more frequent visits, and 18 % of the family members were not satisfied with the video visitation duration. Similarly, families consider video communication to be effective, with suggested improvement proposed, including the use of technology as a substitute the family members’ face to face visit at the bedside (Kennedy et al., 2021). The implementation of a video visitation policy in ICU is an important step towards improved patient- and family centred care. The study’s results suggest that ICU staff should be encouraged to initiate video visitation to increase communication between patients and their families, if resources such as smart phone availability permit. Video visitations are easy to implement, do not affect medical care, and will not excessively increase the workload of nurses.

Limitations

This study had some limitations. First, it was a single-centre study; therefore, the results may not be generalisable to other ICUs with different characteristics. Second, patient outcomes were assessed through self-report forms, which may have led to bias due to social desirability factors. For example, patients’ self-report HADS scores may not be accurate, because analgesia and sleep deprivation may have impacted their ability to complete the tool accurately. Third, the questionnaire routinely used in the hospital to survey patient and family satisfaction, has not been tested for validity and reliability. Finally, the reasons for certain family members’ refusal to participate in the study were not explored. Families with high anxiety or depression may not have agreed to participate.

Conclusions

During the COVID-19 pandemic, patient family visits to ICUs have been restricted. This study showed that video visitations did not significantly reduce the anxiety of patients and no significant differences in patient outcomes in relation to depression, delirium, and family members’ anxiety was found. However, it found a significant difference in patients’ and family members’ satisfaction scores between the video visitation (video visit once a day) and routine visit groups (no visits during the pandemic, with only phone calls with the staff). Visiting patients in ICU can be a big burden to some family members due to the distance they have to travel and the time commitments. Video visit should be embedded in clinical practice as a choice for patients and their families. Finally, remains unclear how long and how often video visitation should be. Future research is recommended to determine how to embed video into routine practice, and the optimal frequency and length of video visitation in relation to patient outcomes and preferences.

Ethical considerations

This study was approved by the institutional review board of Peking University First Hospital (2020–235).

Clinical Trial registration

This study was registered in the Chinese Clinical Trial Registry (ChiCTR2000034306).

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.