‘Online therapy’ to reduce caregiver’s distress and to stimulate post-severe acquired brain injury motor and cognitive recovery: A Sicilian hospital experience in the COVID era

Abstract

Introduction

Severe acquired brain injury(SABI) often results in the deterioration of physical, cognitive and emotional functions in the patient and a significant caregiver's distress syndrome, which is now amplified by the social isolation, depression and financial difficulties related to the COVID-19 pandemic. The use of web-based online-therapy has been shown to be useful to overcome caregiver's distress syndrome and further stimulate cognitive-motor recovery of SABI-patients. Our study aimed to investigate whether a systematic online Skype-therapy(OLST) may be of support in favoring global cognitive and sensory-motor recovery in SABI-patients and reducing caregiver distress.

Methods

Twenty-five SABI-subjects in inpatient regimen were provided with intensive OLST with the caregiver for 12 weeks in addition to standard neurorehabilitation. Each subject and caregiver was evaluated before and after the treatment by administering an ad hoc battery. Furthermore, 18 of 27 patients were provided with EEG recording in resting state.

Results

We found a significant reduction in caregiver's anxiety (p<0.0001) and burden(p<0.0001). Patients showed significant improvement in trunk control (p<0.0001), functional independence (p = 0.005), functional (p = 0.01) and global communication (p = 0.004), cognitive functioning (p = 0.001), and behavioral responsiveness (p = 0.0004). The training yielded a significant connectivity change within the fronto-centro-parietal areas in the delta frequency band (p<0.0001) and the centro-parieto-occipital areas in the alpha range (p = 0.004).

Discussion

OLST may be a useful and complementary treatment to optimize global cognitive and functional recovery in SABI-subjects and reduce caregivers' concerns in the Covid-era. OLST can foster cognitive-motor recovery potentially by favoring the plasticity-dependent functional recovery. Therefore, OLST could be proposed as a tool allowing social conversations also in the hospital setting.

Keywords

Online web-based therapy severe acquired brain injury (SABI)caregiver’s distress cognitive and functional recovery psychological well-being,COVID-19.

Introduction

Severe acquired brain injury (SABI) refers to brain damage due to cranioencephalic trauma or other causes (including cerebral anoxia and haemorrhage), such as to determine a more or less protracted condition of coma (lasting more than 24 hours) and motor, sensory, cognitive and/or behavioural sequelae causing a generally very severe disability.¹,²

Particularly, SABI survivors often have to learn to live with a diminished potential for physical, emotional, cognitive and social functioning.³,⁴ Consistently, an adequate, intensive rehabilitation is mandatory to manage functional impairments, restore lost functions and regain independence.⁵

SABI occurrence also has relevant consequences for the caregivers. A caregiver is anyone who provides help to another person in need. Being a caregiver may or may not be experienced as a core value and something the caregiver may or may not wish to provide. In both cases, some features account for the risk of caregiver distress syndrome, i.e., the emotional and physical stress of caregiving (feeling of anger, frustration, exhaustion, loneliness or sadness), including living with the person you are caring for, social isolation, depression, financial difficulties, time spent on caregiving, difficulty in coping strategies and problem-solving skills, and lack of choice in being a caregiver.⁶,⁷ Studies highlighted that caregivers develop a high level of stress, anxiety and depression within 3 to 5 days of intensive or sub-intensive care unit stay.⁸ Besides, changes in the role functions, family system and family integrity are threatened. Caregiving responsibilities are constant and time-consuming. Studies showed that caregiver stress is associated with high rates of depression and poor personal health.⁹,¹⁰ The fact that the caregiver develops a caregiver distress syndrome determines their limited capacity to focus on the loved one and their health and well-being. A caregiver's functional impairment can have relevant consequences for the outcome of SABI patients. It is universally accepted that family members and caregivers play an essential role in the rehabilitation process, particularly the baseline assessment and outcome definition and the precise definition of an individual's difficulties, notably when the patient lacks insight.⁵ Furthermore, the continuous supervision required by the caregiver often results in a stimulating and entraining rehabilitation paradigm, i.e., the patient is more motivated and more likely to participate in rehab sessions.¹¹ Therefore, the caregiver's psychophysical health must be targeted in the rehabilitation processes, especially in the present COVID era, which predisposes many to caregiver distress syndrome because of the impact of factors such as social isolation, depression and financial difficulties).

Patient–caregiver interaction in the COVID era

The outbreak of COVID-19 has thrown the world into disarray. On the one hand, the management of patients with COVID-19 has required and still requires massive health efforts to face and contain COVID-19 sequelae, particularly neurocognitive disorders, including delirium, acute and chronic attention or memory impairment, and learning deficits.¹² On the other hand, the COVID-19 pandemic has been linked to a rise in people reporting mental health problems, such as depression and anxiety, which both represent a consequence either of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (directly) or of social distancing and isolation during and following lock-down periods.¹³ This has a glaringly obvious effect on brain injury survivors’ and their caregivers’ mental and emotional state. The lack of contact between the patient and the caregiver has negative consequences for both a patient’s functional outcome achievement and the caregiver’s psychophysical health.¹⁴ To manage these relevant problems and with the constraints of lock-down in many countries, most therapists have been forced to undertake online therapy for some or all of their clients and to guarantee at least minimal contact between patients, with particular SABI survivors and their caregivers.¹⁵

Online therapies in the Covid era

Cognitive rehabilitation (CR) benefitted from the growing use of computer-based cognitive tools, virtual systems and ad hoc online cognitive training^16–18 using dedicated apps/systems or video call with Skype or WhatsApp, especially in neurological disorders such as stroke, aphasia and SABI.^19–21 Telecommunication applications (including Skype) specializing in providing video chat and voice calls between computers, tablets and mobile devices allowed connecting people remotely in a straightforward and immediate way. The touch-screen platform, speech-to-text and adaptive switches connectivity options allow for ease of use and navigation for stroke survivors. The visual-motor and somatosensory biofeedback provided by touch-screen tablets allow for more effective motor training and sensory stimulation, optimizing post-stroke neuroplasticity and cortical reorganization. In this regard, the uses and benefits of mobile devices and software applications for healthcare professionals have been comprehensively outlined.^22–25

Another relevant problem is assessing the patient’s outcomes more objectively due to potentially limited contact between the therapist and the patient. Example modalities for physiological signal measurement include electroencephalography (EEG). In particular, EEG is a method to capture electrical brain activity, which is expected to contain comprehensive information on the emotional process. Furthermore, EEG has advantages over other cerebral physiological channels, such as high temporal resolution, low cost and equipment portability. Thus, many studies have utilized EEG signals for emotion analysis. In this regard, various time- and frequency-domain features have been extracted from EEG data for emotion recognition, with accurate prediction and detection rate. This is of noticeable importance, particularly regarding the brain–computer interface in patients with low communication capabilities.²⁶ Brain connectivity has been actively employed in neuroscientific research. Moreover, the effectiveness of brain connectivity features in recognizing emotional states was validated in recent studies.²⁷,²⁸

The purpose of the present pilot study was to investigate whether a systematic ‘online Skype therapy’ (OLST) in the COVID era could stimulate global cognitive and sensory-motor recovery in SABI patients and to reduce two main features of the caregiver’s distress, i.e., the depression and other emotional distress (e.g., anxiety) in the domain of the well-being of the caregiver, and the emotional health strain in the domain of the perceived challenges. We also assessed patients’ functional connectivity changes in response to OLST provision using EEG to identify some putative neurophysiological mechanisms underlying OLST’s effectiveness. We planned this pilot study to collect evidence that could allow planning a future, confirmatory study on the clinical applicability of OLST in real, large-scale rehab settings. Therefore, the sample size was determined on the inclusion criteria, and no formal statistical hypothesis was made a priori.

Methods

Study population and paradigm

Twenty-five subjects affected by SABI who attended from April 2020 to June 2020 at the Semi-Intensive Care Unit of the IRCCS Centro Neurolesi Bonino Pulejo (Messina, Italy) were enrolled in the study. All experiments involving humans were conducted according to the ethical policies and procedures approved by the local ethics committee. All patients’ legal guardians gave their written informed consent to study participation and data publication.

Patients’ demographic and clinical features are reported in Table 1. Seventeen males and eight females of white Caucasian race in a SABI post-acute phase (i.e., 3–6 months from the acute traumatic (12%) or vascular (76%) event) were enrolled, with a mean age of 57 years, lower educational level, and a lower-middle (US$31,000–42,000) to middle family income (US$42,000–126,000). Patients with SABI were selected according to the following inclusion criteria: (1) diagnosis of acquired brain injury (vascular or traumatic); (2) aged between 18 and 75 years; (3) according to neuroradiological and clinical assessments; (4) availability of internet connection at caregiver’s home; (5) a Levels of Cognitive Functioning (LCF) ≥ 2; and (6) the presence of a skilled caregiver. In this regard, we included the official patient’s caregiver in the study (Table 1). The caregiver cohort included eight males and 17 females of white Caucasian race, with a mean age of 55 years, secondary/university schooling, and a lower-middle to middle family income.

Table 1.

Clinical and demographic characteristics.

Patients					Caregiver
Age (years)	Gender	Schooling		Aetiology			Age (years)	Gender	Schooling
57	M	Elementary		V	Spouse		53	F	Lower middle
19	M	Lower middle		T	Mother		51	F	University
39	F	Lower middle		V	Father		70	M	Secondary
35	M	Lower middle		V	Mother		66	F	Secondary
73	F	Elementary		V	Son		48	M	University
45	F	Secondary		V	Mother		74	F	Secondary
58	M	Secondary		V	Spouse		59	F	Lower middle
62	M	Lower middle		V	Spouse		60	F	Secondary
70	M	Secondary		V	Spouse		67	F	Secondary
65	F	Lower middle		V	Spouse		67	M	Lower middle
60	M	Secondary		V	Spouse		55	F	Secondary
38	M	Lower middle		V	Mother		65	F	Secondary
73	F	University		V	Nephew		44	N	University
59	M	Lower middle		V	Spouse		55	F	Secondary
75	M	Elementary		V	Son		47	M	University
68	M	Elementary		V	Nephew		41	F	University
69	M	Lower middle		V	Daughter		41	F	University
65	M	Lower middle		V	Spouse		62	F	Secondary
64	F	University		V	Spouse		65	M	Secondary
55	F	Elementary		V	Spouse		58	M	Secondary
54	M	Lower middle		V	Daughter		24	F	University
48	M	University		T	Spouse		49	F	University
59	F	Secondary		T	Spouse		62	M	Secondary
53	M	Lower middle		V	Brother		50	M	University
73	M	Lower middle		V	Daughter		39	F	University
57±14	68%M 32%F	Elementary Lower-middle Secondary University	20% 48% 20% 12%	76% V 12% T	Brother Daughter Father Mother Nephew Son Spouse	4% 12% 4% 16% 8% 8% 48%	55±12	32%M 68%F	Elementary Lower-middle Secondary University	0% 12% 48% 40%

All SABI subjects and their caregivers were provided with an intensive OLST consisting of a daily Skype session (see Table 2), five times a week, for 12 consecutive weeks, in addition to standard neurorehabilitation. Each subject enrolled was evaluated by a medical and rehabilitative team (consisting of a neurologist, psychologist, physiotherapist, speech therapist, and nurse) through the administration of a neuropsychological battery 2 to 3 days before (T0) and after (T1) the treatment. Furthermore, patients were provided with EEG recording in resting state on the same day of the clinical assessment.

Table 2.

Online Skype therapy sessions.

Online therapy	SABIdomains	Caregiver domains	Duration	Scheduling
Up to 1-hour Skype session (video conference modality)	- Sensory-motor - Cognitive - Communicative abilities - Vigilance	- Anxiety - Emotional distress - Depression symptoms	As long as possible depending on patient’s clinical condition and fatigue degree	One session daily in the morning (12–2 pm) or the afternoon (6–8 pm), five times weekly (from Monday to Friday)

V: vascular; T: traumatic; SABI: severe acquired brain injury; MCS: minimally conscious state; M: male; F: female.

Online Skype therapy (OLST)

Skype simplicity of use and high-quality transmission is best experienced via a high-speed internet connection. Most computers or tablets today come equipped with a webcam and microphone. Many webcams come with a built-in microphone. Skype is free and is the most widely available platform. One has to click on the link to join the session. Skype sessions (see Table 2) were organized in specific time activities and conducted in the same way (face-to-face) and for a length of time according to the patient’s clinical condition (on average 32±11 minutes, range 10–50 minutes). Communication by these technologies was encrypted and decrypted automatically, which lowers the chance of communications being intercepted. Despite the intuitive use of the Skype device and the medium–high level of education of the caregivers, they were trained to use Skype in an ad hoc session before beginning the first Skype session. In particular, we recommended that caregivers settled down in a private space that was free from distractions. We also suggested using a headset to increase privacy. Each session was confidential, and each caregiver could freely talk about any issue and variably interact with the patient (for instance, showing photos, reading a book). However, each session was supervised by a therapist to ensure the patient’s participation in the OLST. Each Skype session was recorded on the PC used to carry out the session by the psychiatric therapist in an ad hoc module, to monitor patient’s and caregiver’s physical and mental status (see Figure 1).

Figure 1.

A representative OLST session.

Outcome measures

All individuals with SABI were assessed for common impairments using a multimodal assessment approach²⁹ that included: (1) motor impairments (i.e., weakness, altered tone, balance and incoordination) using the Glasgow Coma Scale (GCS), the functional independence measure (FIM) and the Trunk Control Test (TCT); (2) bulbar problems affecting speech and swallowing using the Functional Communication Scale (FCS) and the global communication (GC) scale; and (3) cognitive dysfunctions such as impairments in attention, orientation and memory, using the Levels of Cognitive Functioning (LCF) assessment scale. Details are as follows:

LCF³⁰ is one of the earlier developed behavioural scales used to assess cognitive functioning in post-coma patients. It systematically describes and categorizes a patient's level of consciousness and cognitive and behavioural functioning through which the patient typically progresses.

The GCS³¹ objectively describes the extent of impaired consciousness in all types of acute medical and trauma patients. This scale investigates patients according to three aspects of responsiveness: eye-opening, motor and verbal responses.

The FIM³² is an 18-item (13 motor (motFIM) and five cognitive (cognFIM)) measurements tool that explores an individual's physical, psychological and social function, used to determine the level of dependence of patients in daily life. This tool is used to assess a patient's level of disability as well as the change in patient status in response to rehabilitation or medical intervention.

The TCT³³ is used to evaluate motor impairment, and it correlates with eventual walking ability, as it tests rolling to each side, maintaining balance in sitting position and sitting up from lying down.

The FCS³⁴ is used to evaluate the language abilities (verbal and non-verbal communication skills), including motivation, collaboration and understanding; the GC scale³⁴ consists of a specialist language questionnaire for verbal and non-verbal abilities.

There are general and ad hoc scales to rate many aspects of caregivers' psychosocial functioning.³⁵ Consistent with the preliminary, explorative nature of our pilot study, we used two specific rather than general scales for the caregivers:

The Zung Self-Rating Anxiety Scale (SAS),³⁶ which is a 20-item self-report assessment device built to measure anxiety levels, is based on scoring in four groups of manifestations: cognitive, autonomic, motor and central nervous system symptoms. Each question is scored on a Likert-type scale of 1–4 (based on these replies: ‘a little of the time,’ ‘some of the time,’ ‘a good part of the time,’ ‘most of the time’). Some questions are negatively worded to avoid the problem of a set response.

the Zarit Burden Interview (ZBI-22),³⁷ which is a popular caregiver self-report measure used by many agencies for ageing, originated as a 22-item questionnaire for assessing caregiver burden; each item in the interview is a statement which the caregiver is asked to endorse using a 5-point scale. Response options range from 0 (Never) to 4 (Nearly Always).

Even though SAS is not a caregiver-specific scale, unlike the ZBI-22,³⁵ these scales reliably (Cronbach's alpha 0.83–0.88) and validly (correlation 0.92–0.97) measure two main features of the caregiver's distress, i.e., the depression and other emotional distress (e.g., anxiety) in the domain of the well-being of the caregiver and, respectively, the emotional health strain in the domain of perceived challenges (i.e., a single summary measure of the caregiver's appraisal of the impact caregiving has had on their lives).

Lastly, we evaluated the globally perceived quality of the OLST by a structured interview and a questionnaire with multiple answers designed by the team, with a focus on specific items: (1) team participation; (2) skills and reliability of the staff; (3) usefulness of the service in the emotional management of family members’ pathology; and (4) whether the caregiver would recommend the use of the OLST or not.

EEG processing and analysis

EEG was recorded for at least 10 minutes in resting state (to have a sufficiently long recording to obtain intervals free from artefacts) while the patient was lying in his/her bed in a quiet and temperature-controlled environment. A standard EEG headset with 19 channels (displaced according to the 10–20 International System) wired to a BrainQuick device (Micromed; Mogliano Veneto, Italy) was used. EEG was sampled at 256 Hz, filtered at 1–60 Hz (by Butterworth filters) and referenced to both the mastoids. The EEG segments without eye blink and other gross artefacts were subjected to ICA to be cleaned further from artefacts. Then, the pruned data were subjected to wavelet decomposition using Synchronization Likelihood (SL) as a non-linear measure of interdependence between EEG signals. This allowed to evidence abnormalities in functional connectivity of brain networks in all EEG sub-bands and full-band EEG.³⁸³⁹ In this regard, we carried out a 4-level wavelet decomposition on each EEG channel,³⁶ obtaining the following sub-bands: gamma (30–60 Hz), beta (15–30 Hz), alpha (8–15 Hz), theta (4–8 Hz) and delta (0–4 Hz). Then, signals were reconstructed in keeping with the Takens theorem.⁴⁰ Lastly, the Fuzzy Synchronization Likelihood (FSL) within and between EEG signals (i.e., EEG signals Xx and Xy obtained from electrodes x and y) from specific regions of interest (ROIs) was computed through averaging the bivariate FSLs (according to FSL-wavelet methodology for the diagnosis of ADHD).⁴¹,⁴² ROIs were defined into six conventional regions: frontal (F) (Fp1/2, Fz, F3/4, and F7/8), right temporal (rT) (T4/6), left temporal (lT) (T3/5), central (C) (C3/4 and Cz), parietal (P) (P3/P4 and Pz) and occipital (O) (O1/2). Then, 100 EEG signals (20 patients × 5 EEG bands) were obtained and used to extrapolate FSL within and between ROIs in each EEG sub-band and the whole-band. A 6 × 6 functional connectivity matrix (between all ROIs) in each of the EEG sub-bands was obtained by averaging the bivariate FSL values. Five functional connectivity matrices (one for each of the four sub-bands and the whole-band) for each of the six ROIs (30 functional connectivity matrices overall) were thus obtained.

Statistical analysis

The Kolmogorov–Smirnov test was used to test normality data distribution (all p>0.1). We carried out an analysis of covariance (ANCOVA) to evaluate the significance of treatment aftereffects using the clinical measures as the independent variable, the T1 values as the dependent variable and the T0 values as the covariates. The demographic features of patients and caregivers (including age, gender, schooling and family income) were included in the analysis. Significant changes in functional connectivity within each of the EEG bands and the whole EEG frequency range were assessed using repeated-measures ANOVA (employing time (two levels: T0 and T1) and ROI (six levels) as factors) on the FSL values. The signiﬁcance level was set to p < 0.05 for all tests. Post hoc analysis with Bonferroni correction was carried out depending on the F value of signiﬁcant main eﬀects. Clinical–electrophysiological correlations were calculated using Spearman's rank correlation coefficient. Statistical analysis was performed using Statview software (BrainPower Inc., Calabasas, CA, USA).

Results

All patients and caregivers completed the intervention. Looking at the individual values, 12 patients (48%) showed a significant improvement in trunk control (TCT, p < 0.0001), 14 (56%) in global independence (FIM, p = 0.005), 13 (52%) in functional (FCS, p = 0.01) and 16 (64%) in global communication (GC, p = 0.004), 17 (68%) in global cognitive function (LCF, p = 0.001) and 17 (68%) in behavioural responsiveness (GCS, p = 0.0004) compared with the corresponding baseline value (Figure 2).

Figure 2.

Outcome measures at baseline (T0) and post-intervention (T1). Data are reported as median with i.q.r. (vertical error bars). Asterisks refer to the statistical significance of pre-post changes (post hoc t-tests with Bonferroni correction; ***p < 0.001, **0.001 < p < 0.01, *0.01 < p < 0.05). LCF: Levels of Cognitive Functioning; GCS: Glasgow Coma Scale; FIM: functional independence measure; TCT: Trunk Control Test; FCS: Functional Communication Scale; GC: global communication; SAS: Zung Self-Rating Anxiety Scale; ZBI-22: Zarit Burden Interview.

All caregivers reported a significant reduction in anxiety (SAS, p < 0.0001) and 23 (92%) in burden (ZBI-22, p < 0.0001) compared to baseline values. Furthermore, 14 (56%) of caregivers highly appreciated the OLST provision (for the satisfactory question item on general utility and appeal of tele-interaction with their own beloved), whereas the remaining caregivers (11, 44%) moderately appreciated the OLST provision (questionnaire score median 3, iqr 2-3). The demographic features of patients and caregivers (including age, gender, schooling and family income) did not significantly influence OLST outcomes.

Concerning EEG findings, we included 18 recordings in the analysis, given that seven recordings were excluded from the analysis owing to excessively poor quality. The training yielded numerous connectivity changes among diverse ROIs and frequency bands (Figure 3). Particularly, we found an FLS increase within the alpha frequency band (time×electrode F = 56, p < 0.001) concerning the centro-parieto-occipital ROIs (p = 0.004) and within the delta frequency band (time×electrode F = 77, p < 0.001) concerning the fronto-centro-parietal ROIs (p < 0.0001). Notably, these EEG changes were significantly correlated with the improvement within FIM (p = 0.003), GCS (p = 0.004), LCF (p = 0.003), FCS (p = 0.004) and GC (p = 0.003). Furthermore, the improvement in these last two scales significantly correlated with anxiety (p < 0.001) and burden decrease (p < 0.001) in the caregiver. The demographic features of patients and caregivers (including age, gender, schooling and family income) did not significantly influence EEG outcomes.

Figure 3.

Topoplots of the average Fuzzy Synchronization Likelihood (FSL) values resulting from 18 patients (seven tracings were of poor transmission quality and thus discarded) within and between the specific regions of interest relative to the baseline for each frequency band. The same scale was used for all frequency bands. Red colour denoted a FLS increase, blue a decrease. An FLS increase within the alpha frequency band concerning the centro-parieto-occipital ROIs, and within the delta frequency band concerning the fronto-centro-parietal ROIs, was appreciable from baseline (T0) to post-intervention (T1). Asterisks denote the significance of post–pre comparison (thresholded at p<0.004).

Discussion

The COVID-19 pandemic represents a challenge for mental health care, i.e., highlighting the great need for support for depressed mood and anxiety arising from social distancing and difficulty in accessing the available social resources.⁴³ Online therapy could be proposed as a tool allowing social conversations also in the hospital setting. To the best of our knowledge, this is the first Sicilian hospital experience in the COVID era aimed at investigating some psychometric and electrophysiological outcomes of online therapy (using OLST) in patients with SABI.

We observed the positive effects of OLST as add-on therapy in stimulating motor and cognitive functioning using emotional and autobiographical stimuli included in the OLST paradigm. The emotional and autobiographical content of OLST is clear, as the patient was allowed to interact with the caregiver freely, thus resulting in a fully entrained virtual interaction. This was ensured by the therapist’s proper supervision, who monitored the patient’s participation in the OLST sessions, and it was confirmed by the high appreciation of OLST sessions by the caregivers. Consistent with this data, we achieved a reduction of the caregiver’s distress.

One may argue that the contribution of OLST in motor and cognitive functioning improvement may occur by chance and not by a real entraining of cognitive functions that favoured the strengthening of the motoric ones. Noteworthy, functional outcome improvement was paralleled by a significant reshaping of functional frontoparietal connectivity in alpha and delta frequency bands. The functional changes could suggest that the provision of significant (i.e., with emotional and autobiographical content) visual stimuli (through the caregiver) can entrain a motor-cognitive neural network communication involved in large-scale sensorimotor processes related to many motor-cognitive functions.^44–47 In this regard, the perceptual aspects of the user experience, such as emotion and preference, are essential for various multimedia applications and services. In particular, emotion, which influences individual and social behaviours,^44–47 is one of the most distinguishing perceptual factors. Although emotion is traditionally investigated through explicit questionnaires or interviews, implicit measurement of emotion via physiological signals has received much attention recently due to its advantages over the explicit approach. We did not directly deal with emotion in our study, but EEG changes in our patients showed a clear correlation with the improvement in patients’ functional communication and caregiver’s anxiety and burden, which is partially related to the emotion domain.⁴⁷

Another main finding in our study was reducing the caregiver’s emotional burden (i.e., caregiver’s anxiety and burden), which is a relevant issue in a period of forbidden social interaction, even within the home environment. Many family members go through periods of sadness and frustration while caring for a loved one. These are normal human responses to the challenges of the situation, and these feelings do not in any way indicate failure or inadequacy in the provision of care. However, a damaging emotional cycle begins when guilt and anxiety develop over these feelings. Caregivers pour their heart and soul into their loved ones’ care, and the stress of this commitment can have unintended emotional consequences. Today, scientific evidence is also limited.⁴⁸,⁴⁹ Even though the caregivers did not receive any specific treatment, they were provided with an albeit indirect emotional support from the professional therapist who supervised each OLST session, besides other friends and family.⁴⁰,⁴¹ Indeed, skilled therapists can help caregivers process feelings, learn to set boundaries, strengthen problem-solving abilities, and improve communication with care recipients and other family members. In this regard, it has been shown that video conferencing interventions reduce anxiety and distress in remote caregivers.^50–53 As a new finding, we showed that using technology helps absent caregivers connect with ill loved ones in meaningful ways, suggesting that using a coaching videoconference intervention significantly reduces anxiety and distress for the family caregiving team. Finally, the significant correlation between the improvement in language communication and cognitive functioning and the reduction in caregiver’s distress should not be neglected. It is likely that the cognitive-motor improvement had a direct positive effect on the psychophysical and mental health of the caregiver simply as a result of the cognitive-motor improvement of the patient, especially in the present situation in which direct contact with patients are forbidden.

Study limitations

One may be concerned that OLST was the primary reason for the improvements to the SABI survivor’s functional status and caregiver’s outcomes due to some limitations of the study, including the type of intervention used, the timing and the study design. Indeed, our study was not a controlled trial due to the lack of a control group, which should have been provided with other online support therapy.

The sample size was determined on the inclusion criteria, and no formal statistical hypothesis was made a priori. However, this was intended as a pilot study aimed at collecting evidence that could allow planning a future, confirmatory study on the clinical applicability of OLST in real, large-scale rehab settings.

OLST was not guided, i.e., the caregivers were left free to interact with their loved ones. Therefore, many variables came into play in entraining motor-cognitive functions as well as brain functional connectivity. Specific OLST protocol might be pre-determined and assessed in future studies to confirm the large-scale rehab setting applicability of OLST.

We limited our observation to the post-intervention only. Therefore, a more extended follow-up period should be planned better to ascertain the validity and durability of OLST intervention effects.

Lastly, some methodological issues concerning the recording technique (as nine EEG recordings were of poor quality utilizing this technology) and the scales used for the clinical assessment, including the GCS, which is best to use in the early acute and acute phase, and the ZBI and SAS, which do not relate at the general level with caregivers’ distress, have to be refined.

Future research

The issue of social isolation among SABI survivors and their caregivers remains to be further assessed. SABI survivors were separated from their caregivers due to the COVID-19 pandemic and likely faced much social isolation and uncertainty that could represent a significant focal point of studies dealing with psychosocial distress. Nevertheless, social isolation needs to be addressed and measured in a specific way.

Conclusions

Despite the abovementioned limitations, our promising data suggest that OLST may help foster functional recovery in SABI people, optimizing psychometric and electrophysiological outcomes. It is our opinion that online therapies, including OLST, may be a useful and complementary treatment to standard rehabilitation in the Covid era and attempt to relieve caregivers’ distress and burden, positively impacting the household. Further larger-sample studies should be fostered in order to confirm these promising findings.

Footnotes

Declaration of conflicting interest

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Rosaria De Luca

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