Teletherapy and hospitalizations in patients with serious mental illness during the COVID-19 pandemic: A retrospective multicenter study

Antonio José Sánchez-Guarnido; Beatriz Machado Urquiza; Maria del Mar Soler Sánchez; Carmen Masferrer; Francisca Perles; Eleni Petkari

doi:10.1371/journal.pone.0267209

. 2022 Apr 18;17(4):e0267209. doi: 10.1371/journal.pone.0267209

Teletherapy and hospitalizations in patients with serious mental illness during the COVID-19 pandemic: A retrospective multicenter study

Antonio José Sánchez-Guarnido ¹, Beatriz Machado Urquiza ¹, Maria del Mar Soler Sánchez ², Carmen Masferrer ³, Francisca Perles ⁴, Eleni Petkari ^5,^*

Editor: Xenia Gonda⁶

PMCID: PMC9015154 PMID: 35436291

Abstract

Background

Interventions with patients with Serious Mental Illness (SMI) had to adapt rapidly to the COVID-19 safety restrictive measures, leading to the widespread use of teletherapy as an alternative.

Objectives

The aims of this study were to compare the use of different intervention modalities with patients with SMI during the first wave of the pandemic and examine their association with emergency hospital visits and hospitalization rates six months later.

Methods

Records of 270 service users of fifteen outpatient mental health services across Spain, were retrospectively assessed. We retrieved clinical data and data on the modality of intervention received (in-person, over the phone, videoconferencing) in three time points (before, during and after the first COVID-19 wave). Also, data were retrieved regarding the frequency of their emergency hospital visits and hospitalization rates, two, four and six months later.

Results

During the first wave of the pandemic, teletherapy (over the phone and videoconferencing) was the modality most widely used, whilst in-person therapy sessions were significantly reduced, though they seemed to return to pre-COVID levels after the first wave had passed. Importantly, patients receiving teletherapy during the first wave seemed to have significantly fewer emergency visits and hospitalization rates four and six months later (χ² = 13.064; p < .001). Multilevel analyses revealed that patients receiving videoconferencing interventions had fewer hospitalizations six months after the first wave (OR = 0.25; p = .012).

Conclusions

Under challenging circumstances as those created by the COVID pandemic, teletherapy is a useful tool for protection against hospitalizations and can be used as an alternative to in-person therapy, to ensure continuity of care for patients with SMI.

Introduction

The impact of the COVID-19 pandemic [1] on physical and mental health [2] has been widely reported in the literature. Social distancing, uncertainty about the crisis caused by the pandemic, and the consequent economic collapse, may negatively affect mental health, particularly in individuals with pre-existing mental disorders [3, 4]. Under such circumstances, individuals with Serious Mental Illness (SMI) have been shown to experience greater anxiety than people without previously reported psychopathology [5].

Social distancing practices may pose a great negative impact on individuals with psychotic disorders, as they are known to have small and low quality social networks [6], and are under increased risk of suicide due to isolation [7]. Furthermore, their ability to cover their basic needs may also be compromised, as many of them rely on community services (i.e. employment, occupational, and mutual support groups) that are less accessible under the circumstances created by the pandemic [8].

At the same time, the health crisis caused by the COVID-19 pandemic has posed a major challenge to mental health services. At the peaks of the pandemic, in-person interventions were limited, as they were considered a risk regarding coronavirus transmission. However, since continuity of care plays a key role in preventing the exacerbation of symptoms, and in reducing emergency consultations, hospital admissions, and suicide attempts [9], it was considered vital to find alternative ways of maintaining that continuity without exposing people with SMI to a greater risk of infection.

Alternatives to in-person care were in fact implemented with the aid of teletherapy, un umbrella term for what are known as telematic psychological interventions (telepsychotherapy and e-therapy) [10, 11]. Teletherapy is based on information and communications technology (computer-based Internet tools, mobile and land telephone calls, emails, fax, text messages, and videoconferencing consisting of patient-clinician communication through video consultations) [12]. It is a feasible and effective therapy modality that does not inhibit the therapeutic relationship [13–15] and seems to be widely accepted by both patients and professionals [16]. Despite some reported barriers associated with fears regarding loss of confidentiality, privacy, and legal regulations [14, 15], teletherapy seems to be a valid alternative for treating common mental health disorders, such as anxiety, depression, post-traumatic stress, and eating disorders [17, 18]. Videoconferencing, for example, has been found to be efficient with patients suffering from a variety of mental disorders [19] and is considered a useful tool for maintaining key aspects of the therapeutic process, such as therapeutic alliance [20]. Similarly, help lines are useful when patients do not have an adequate social network [21], while over the phone interventions are effective in reducing depressive symptoms [22, 23]. Teletherapy has been successfully used to implement several treatment models, including cognitive behavioral therapy [24], dialectical behavioral therapy [25], interpersonal therapy [22], and psychoanalysis [26], among others.

But despite the reported benefits of its use with individuals suffering from different mental disorders [19, 27], it has been barely explored in individuals with SMI, and even those studies that have been carried out rarely included patients with increased symptom severity [28]. However, the provision of therapy through telephone calls, Internet, and videoconferencing does, however, seem feasible in patients with schizophrenia and related conditions [29]. The results of a recent systematic review [30] comparing the effectiveness of in-person and videoconferencing interventions in patients with psychosis showed similar levels of effectiveness in terms of health, psychiatric symptoms, and functionality. Also, in two of the studies included in this review treatment adherence was greater when videoconferencing was used. Overall, patients displayed high levels of satisfaction with teletherapy, this modality always being preferred to the waiting list, or having to travel a long distance to the hospital.

One of the reasons behind the limited use of teletherapy with patients with SMI and the lack of research in this regard may be that teletherapy is frequently studied as a complement to treatment as usual [31], and thus, its efficacy as the primary therapeutic modality is not clearly recognized [28]. Also, most studies are characterized by methodological shortcomings, such as small sample sizes, absence of control groups, lack of randomized clinical trials, or short follow-up periods [27, 30]. Importantly, there may also be some sample selection bias, with the inclusion of patients and therapists who have more favorable attitudes towards this intervention modality [28]. Moreover, the use of digital technology among individuals with SMI is lower compared to the general population [32].

However, the COVID-19 pandemic has forced a transition from in-person therapy to teletherapy in patients with more severe conditions, even among patients and health professionals whose attitudes that were not so positive towards this intervention modality [17]. To date, no studies have been carried out into teletherapy outcomes with patients with SMI under adverse psychosocial and health circumstances, such as those created by the COVID-19 pandemic. During the SARS epidemic in 2003, smartphones and internet services were not widely available, and online mental health services were scarce [33], so the study of teletherapy applications was not considered relevant.

It is therefore necessary for research into the impact of COVID-19 to focus on the provision of mental health care for the most vulnerable groups, such as the individuals with SMI. Many of these patients experienced interruptions to the continuity of their care, due to the measures taken to reduce infection rates over the first few months of the pandemic, while others managed to maintain contact with their services through teletherapy. To the best of our knowledge, to date no studies have examined how services were provided to such patients, and how the differences may be associated with a risk of hospitalization.

Therefore, the present study aimed to: a) explore the types of care offered to people with SMI during the first COVID-19 wave, the alternatives used when in person interventions were not possible, and the changes in the modality of interventions used over time (before the first wave, during lockdown, and after the first wave); b) examine whether receiving teletherapy, compared to not receiving teletherapy during the lockdown was associated with the frequency of visits to the emergency department and of hospital admissions, two, four, and six months after the lockdown; and c) examine if different teletherapy modalities are associated with hospitalization rates six months after the lockdown.

Materials and methods

The Strobe checklist was used to prepare the manuscript (See S1 Checklist).

Study design

Retrospective multicenter cohort study.

Setting and participants

The Spanish mental healthcare system

Mental healthcare provision in Spain is quite complex. Among other facilities it includes a) the community mental health units, which constitute the first level of care units for people with SMI and provide both outpatient and homecare service; b) the mental health day hospitals, which constitute an intermediate resource between community mental health and hospitalization units, and provide specialized care in an outpatient/midday-stay mode; c) the inpatient units in general hospitals, providing full and partial hospitalization. Emergencies are handled by the general hospital emergency departments (psychiatry section), as well as the outpatient mental health units. For further information see: National Health System [34]. Fifteen community mental health hospitals in Spain were selected using stratified sampling, to achieve generalization in the Spanish population of people with SMI. Serious Mental Illness (SMI) was defined based on the ICD diagnosis, and on the intensity of the required care required [35]. This criterion was implemented by selecting all the patients who, due to the severity of their condition required follow-ups in an outpatient mental health hospital during the time period of the study. As this is a retrospective study based on clinical records, only patients who fulfilled the above criteria were included.

Patients with incomplete data were excluded from the study.

The total sample consisted of 270 people with SMI over 18 years old of age, nearly reaching the minimum required sample size of (N = 272) as calculated using the GPower analysis [36]. To calculate the sample size, we considered a 20% relapse rate for the group that received teletherapy and 30% relapse rate for the group that did not, with a potential sample loss of 15%, a Confidence Interval of 95% and 80% statistical power (see S1 File).

Variables and data sources/measurement

Three two-month observation periods were established for the first wave of COVID-19 (2020): the period before the pandemic (January 16 to March 15), the lockdown period (March 16 to May 15), and the period following the first wave (May 16 to July 15).

The following variables were collected based on the patients’ clinical records:

Sociodemographic variables: sex, age (in years), living status, occupational status, maximum level of education attained.

Clinical variables: Diagnosis based on the ICD-10 classification [37].

Treatment Adherence (yes/partially/no).

Treatment adherence was determined using the Medication Possession Ratio, defined as the proportion of time when medication supply is available [38].

Use of psychological interventions (yes/no): in-person (individual/group), over the phone, videoconferencing (individual/group)

Modality of intervention received (in-person/teletherapy).

Type of teletherapy received (videoconferencing individual/group, over the phone)

Intervention characteristics

In-person: once per week, individual (45–60 minutes)/group (90 minutes)

Over the phone: once per week, individual (30–45 minutes). Sessions were held using the health service’s landlines, following the same procedures as routine calls.

Videoconferencing: once per week, individual (30–45 minutes, one to one basis)/group (90 minutes, six to eight participants). The sessions were held through the health system enterprise video-calls software and were similar across sites.

Outcome variables: assessed two, four, and six months after the end of the first wave.

Percentage of hospitalizations (defined as admissions to a Mental Health Hospitalization Unit) calculated against the study sample

Mean number of visits to a Mental Health Emergency Department.

Procedure

After receiving the approval of the corresponding ethics committees of the participating centers, data were collected retrospectively (October to November 2020) based on the patients’ clinical records. The overall approval was obtained by the Medical Research Ethics Committee of the Andalusian Government stating the following: "This study fulfills the ethical principles required for conducting studies of this type" (REF: 202077133825). Patients were informed verbally and in writing about the project aims, and signed an informed consent. A password-protected database with sound error prevention mechanisms was designed, which granted access only to the study researchers; clinical data were handled without patient identification details. The study was performed in line with the principles of the Declaration of Helsinki. Data privacy requirements were met in accordance with the European Union legislation.

Statistical methods

Statistical analyses were performed using the SPSS software v.21.0 [39], with a statistical significance of p-values < .05. We first examined the sociodemographic and clinical characteristics of our sample with descriptive statistics.

To study the first aim, we used a series of Cochrane’s tests to determine whether there were statistically significant differences in the proportion of patients making use of the different intervention types over the three time points (before, during, and after the lockdown). We also performed pairwise comparisons through a series of McNemar’s tests, to check whether the proportion of patients using the interventions was sustained or varied from one time point to another (before, during and after the lockdown). For these analyses, we applied a Bonferroni correction to the significance levels as follows: p = .005/3 = .016. For the second aim, we used Chi-square tests to compare the hospitalization rates at two, four, and six months after the first wave, and Student’s t-tests were used to compare the mean number of visits to the Mental Health Emergency Department, between the patients who received teletherapy during the lockdown and those that did not. For the third aim, we first used Chi-square tests to compare the hospitalization rates six months after the lockdown between the patients that received each type of teletherapy (over the phone, videoconferencing individual and group) and those that did not. We then performed a mixed effects multilevel logistic regression including random effects for each patient nested in the three time points (before, during and after the first wave), and adjusting for individual characteristics, interdependence effects and confounding variables. We established Level 1 for interventions received and level 2 for the individual characteristics of the patients nested in them. The dependent variable was the frequency of hospitalizations 6 months after the first wave. In the first step the null model resulted in an ICC = 0.36, explained by level 2 variables, confirming the consideration of multilevel models. The first model included level 1 variables: videoconferencing (individual and group were considered together, due to lack of sufficient cases), over the phone, and in-person. For the second model we added the level 2 sociodemographic variables (sex and age) and for the third model we added the level 2 clinical variables (diagnosis and treatment adherence).

Results

Participants and descriptive data

Our sample consisted of 120 men and 150 women (55.6%), aged between 18 and 67 years (M = 39.90 years). Most of the participants had primary (35.8%) or secondary (41.5%) education, and 14.8% had university studies. The majority of the patients lived with their family of origin (28.9%), their own family (28.9%), or alone (17%); 29.3% were retired, 26.3% were unemployed, 20% had short-term disability, and 16.7% were working (Table 1). The most frequent diagnosis was Schizophrenia or other psychosis (30.4%), followed by personality (27.8%), bipolar (10.4%), or major depressive disorders (9.8%). The majority showed treatment adherence (85.9%). No statistically significant differences were found between the patients that received some type of teletherapy and those who did not, in terms of sex (χ² = 0.208; p = .649), age (t = -0.059; p = .953), occupational status (χ² = 6.286; p = .279), level of education (χ² = 2.993; p = .559) diagnosis (χ² = 3.853; p = .426), or treatment adherence (χ² = 0.422; p = .810).

Table 1. Sociodemographic and clinical characteristics of the sample.

	Total N (%)	Patients who received teletherapy N (%)	Patients who did not receive teletherapy N (%)	t/χ² p-value
Total Sample N	270 (100%)	175 (64.8%)	95 (35.2%)
Age Mean (SD)	39.90 (11.81)	39.93 (11.12)	39.84 (13.06)	t = -0.059
Age Mean (SD)	39.90 (11.81)	39.93 (11.12)	39.84 (13.06)	p = .953
Gender				χ² = 0.208
Female	150 (55.6%)	99 (56.6%)	51 (53.7%)	p = .649
Male	120 (44.4%)	76 (43.4%)	44 (46.3%)	p = .649
Living status				χ² = 5.664
Family of origin (parents w/wo siblings)	78 (28.9%)	52 (29.7%)	26 (27.4%)	p = .462
Own family (partner and/or children)	78 (28.9%)	54 (30.9%)	24 (25.3%)
With friends or siblings	16 (5.9%)	8 (4.6%)	8 (8.4%)
One parent w/wo siblings	37 (13.7%)	23 (13.1%)	14 (14.7%)
Other	7 (2.6%)	6 (3.4%)	1 (1.1%)
Single household	46 (17%)	26 (14.9%)	20 (21.1%)
Supported housing	8 (3%)	6 (3.4%)	2 (2.1%)
Occupational status				χ² = 6.286
Student	20 (7.4%)	13 (7.4%)	7 (7.4%)	p = .279
STD	54 (20%)	39 (22.3%)	15 (15.8%)
Retired, pensioner	79 (29.3%)	48 (27.4%)	31 (32.6%)
Unemployed	71 (26.3%)	50 (28.6%)	21 (22.1%)
Working	45 (16.7%)	24 (13.7%)	21 (22.1%)
Volunteer/Mutual support agent	1 (0.4%)	1 (0.6%)	0 (0.0%)
Level of Education				χ² = 2.993
No schooling	8 (3%)	3 (1.7%)	5 (5.3%)	p = .559
Primary (BGE-CSE)	96 (35.6%)	61 (34.9%)	35 (36.8%)
Secondary education	112(41.5%)	76 (43.4%)	36 (37.9%)
University studies (BSc)	40 (14.8%)	26 (14.9%)	14 (14.7%)
Postgraduate studies (MSc-PhD)	14 (5.2%)	9 (5.1%)	5 (5.3%)
Diagnosis (ICD)				χ² = 5.743
Schizophrenia/Other psychosis	82 (30.4%)	50 (28.6%)	32 (33.7%)	p = .570
Bipolar disorder	28 (10.4%)	18 (10.3%)	10 (10.5%)
Personality disorders	75 (27.8%)	53 (30.3%)	22 (23.2%)
Depressive disorder	26 (9.6%)	17 (9.7%)	9 (9.5%)
Anxiety/Other disorders	59 (21.9%)	37 (21.1%)	22 (23.1%)
Treatment Adherence				χ² = 0.422
Yes	232(85.9%)	152(86.9%)	80 (84.2%)	p = .810
Partially	27 (10%)	16 (9.1%)	11 (11.6%)
No	11 (4.1%)	7 (4%)	4 (4.2%)

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Outcome data and main results

Comparison between the different types of intervention before the pandemic, during lockdown, and after the first wave

Table 2 displays the percentages of patients who received the different types of interventions over the three time periods. Overall, there were statistically significant differences across the usage of all types of interventions, as indicated by the Cochrane’s Q results (Table 2). In-person individual interventions decreased from 80.4% before the pandemic to 23% during the lockdown (p < .001), and then increased to 73.7% after the first wave (p < .001); there were no significant differences in the use of in-person individual interventions after the first wave, in comparison with before the pandemic (p = .043).

Table 2. Comparison of interventions received before the pandemic, during the lockdown, and after the first wave.

Type of intervention	Before the lockdown (Jan 16 –March 15) %	During the lockdown (March 16 –May 15) %	After the lockdown (May 16 –July 15) %	Cochrane´s Q	χ² /p values
Type of intervention	Before the lockdown (Jan 16 –March 15) %	During the lockdown (March 16 –May 15) %	After the lockdown (May 16 –July 15) %		Before vs during the lockdown	Before vs after the lockdown	During vs after the lockdown
In-person individual	80.4	23	73.7	Q = 224.573 p < .001	χ² = 142.012 p < .001	χ² = 4.129 p = .042	χ² = 125.823 p < .001
In-person group	29.3	1.1	23.3	Q = 99.299 p < .01	χ² = 70.313 p< .001	χ² = 4.500 p = .034	χ² = 54.391 p< .001
Over the phone	4.4	60	21.9	Q = 214.048 p> .001	χ² = 144.162 p < .001	χ² = 38.473 p < .001	χ² = 85.983 p < .001
Videoconferencing individual	0	3.7	1.5	Q = 11.692 p = .003	p = .002	p = .125	p = .146
Videoconferencing group	0	9.3	11.1	Q = 44.286 p < .001	p < .001	χ² = 28.033 p< .001	p = .302

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In-person group interventions decreased from 29,3% before the pandemic to 1,1% during the lockdown (p< .001) and then increased to 23,3% after the first wave (p< .001). There were no significant differences in the use of in-person group interventions after the first wave, in comparison with before the lockdown (p = .034).

The percentage of patients who received over the phone interventions increased from 4.4% before lockdown, to 60% during the lockdown (p < .001), and then significantly decreased to 21.9% after the first wave (p < .001). However, this percentage was still significantly higher than before the lockdown (p < .001).

The percentage of patients receiving an intervention through individual videoconferencing before the pandemic increased from 0% to 3.7% during the lockdown (p < .001) and decreased, although not significantly, to 1.5% after the first wave (p = .146). The differences between the period before and after the first wave (p < .125) were also not statistically significant.

Lastly, patients receiving videoconferencing group interventions increased from 0% before the pandemic to 9,3% during the lockdown (p < .001) and to 11,1% after the first wave (p< .302), with a significant increase in the use of such interventions between the period before the pandemic and the period after the first wave (p< .001).

Differences in hospitalization rates and visits to the mental health emergency department in patients who received teletherapy during the lockdown and those who did not

Hospitalization rates two months after the lockdown did not differ between patients who received teletherapy, and those who did not (p = .068). However, hospitalization rates were significantly lower for the first group of patients at four (p = .004) and six months after the lockdown (p < .001).

Patients who received teletherapy made fewer visits to Mental Health Emergency Department, at two months (p = .030), four months (p = .11NS), and six months (p = .034) after lockdown, than those who did not. The results are shown at Table 3.

Table 3. Hospitalizations and emergency visits two, four and six months after the lock down.

	Total (%)	Patients who received teletherapy (%)	Patients who did not receive teletherapy (%)	RR	95%CI	χ² /p-value
Hospitalizations
Two months after the lockdown	6.7	4.6	10.5	0.43	0.18 to 1.06	χ² = 3.334 p = .068
Four months after the lockdown	13.7	9.1	22.1	0.41	0.23 to 0.75	χ² = 8.350 p = .004
Six months after the lockdown	20.4	13.7	32.6	0.42	0.26 to 0.67	χ² = 13.064 p< .001
Number of visits to the Mental Health Emergency Department		*Mean (SD)*	*Mean (SD)*	MD		*t /p-value*
Two months after the lockdown		0.22 (0.80)	0.55 (1.64)	0.33	0.03–0.62	t = 2.185 p = .030
Four months after the lockdown		0.42(1.28)	1.18 (3.52)	0.76	0.18–1.35	t = 2.571 p = .110
Six months after the lockdown		0.70 (2.19)	1.65 (5.14)	0.95	0.72–1.84	t = 2.129 p = .034

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Differences in hospitalization rates six months after lockdown based on the type of teletherapy

Patients who received therapy over the phone had less hospitalizations six months later than those who did not (14.2% vs 29.6%; RR = 0.47; χ² = 9.340; p = .002). Similarly, those who received videoconferencing interventions during the lockdown had less hospitalizations than those who did not (3.4% vs 22.4%; RR = 0.15; χ² = 7.840; p = .005).

Table 4 shows the three models built from the multilevel logistic regression analyses. As can be seen, the factor associated with the lowest risk of having a hospitalization six months after the lockdown was receiving an intervention through videoconferencing (OR = 0.25; p = .012), followed by receiving an intervention over the phone (OR = 0.50; p = .003). These findings were maintained when including potential confounders, with lower risk for hospitalizations associated with receiving in-person interventions (OR = 0.56; p = .003), being a woman (OR = 1,50; p = .04) and being older (OR = 1.01; p = .049), whereas diagnosis and treatment adherence were not significantly associated with more hospitalizations (model 3).

Table 4. Multilevel logistic regression models predicting hospitalizations 6 months after the lockdown.

Factor	Model 1: Interventions				Model 2: Interventions +Sociodemographic Factors				Model 3: Interventions +Sociodemographic +Clinical Factors
	B (SE)	β	p	95% CI	B (SE)	β	p	95%CI	B (SE)	β	p	95%CI	Wald
Videoconferencing ^a	-1.58 (0.55)	0.25	.012	0.09 to 0.74	-1.45 (0.55)	0.23	.008	-2.5 to -0.37	-1.32 (0.55)	0.27	.002	0.09 to 0.79	-2.40
Over the phone ^b	-0.69 (0.23)	0.50	.003	0.31 to 0.78	-0.71 (0.23)	0.50	.002	-1.16 to -0.25	-0.75 (0.24)	0.47	.002	0.30 to 0.75	-3.13
In-person ^c	-0.57 (0.19)	0.56	.003	0.39 to 0.83	-0.59 (0.19)	0.56	.003	-0.97 to-0.20	-0.62 (0.2)	0.54	.001	0.36 to 0.79	-3.10
Being a woman ^d					0.45 (0,18)	1.56	.016	0.08 to 0.80	0.41 (0.20)	1.50	.040	1.02 to 2.21	2.05
Age (in years)					0.01 (0.01)	1.01	.83	-0.002 to 0.003	0.02 (0.01)	1.02	.049	1.00 to 1.03	2.00
Bipolar Disorder ^e									0.04 (0.25)	1.04	.868	0.64 to 1.69
Personality Disorder ^e									0.51 (0.30)	1.66	.092	0.92 to 3.00
Depressive Disorder ^e									-0.41 (0.38)	0.27	.661	0.32 to 1.06
Anxiety/Other Disorders ^e									-0.48 (0.28)	0.62	.081	0.36 to 1.06
Treatment Adherence ^f									-0.36 (0.24)	0.69	.129	0.43 to 1.11

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Reference groups:

^a,b,c Not having received this intervention;

^d: Being a man;

^e: Psychosis;

^f: No/Partial Adherence

Discussion

Key results and interpretation

We performed a retrospective analysis to study the impact of the COVID-19 pandemic on the psychotherapeutic care received by patients with SMI, examining the use of teletherapy alternatives applied when in-person interventions were not feasible. We also examined the potential associations between different types of teletherapy and SMI patients’ hospitalization rates and visits to emergency departments in the medium term.

Our findings suggested that individual in-person interventions were significantly reduced during the lockdown, while group therapy nearly disappeared. On the other hand, teletherapy over the phone was the type most frequently used during the lockdown, perhaps because this was the only type of teletherapy intervention used before the pandemic. Teletherapy via videoconferencing, especially in group format, was introduced during the lockdown, but the percentage of patients who received it was lower in comparison with the over the phone modality. The preference for over the phone interventions may be explained by the scarcity of online platforms available within the Spanish public healthcare system [40], and perhaps also by certain limitations associated with videoconferencing, such as the difficulty of its use [41], poor training [42], or the perception that videoconferencing may increase the clinical workload [43]. Also, previous findings indicate that patients with SMI prefer using the telephone rather than videoconferencing, as they believe it reduces the intensity of the sessions [44]. Notably, to date, Spain has no established deontological framework providing guidelines for the teletherapy practice, and such practices are therefore applied in line with the traditional therapy framework principles. This has created major loopholes [45], especially concerning the information confidentiality and privacy [14, 15].

In our study, the use of the in-person modality returned to previous levels after the lockdown, despite a greater risk of viral transmission. This coincided with a significant decrease in the use of over the phone interventions. These findings indicate that when the restrictions were loosened and the situation was perceived as less critical, there was a clear tendency towards resuming routine intervention modes. Although there was no generalized rejection for teletherapy, professionals still seemed to prefer traditional approaches [46], particularly with high-risk patients [28]. Nonetheless, and albeit to a lesser extent, clinicians continued the implementation of group interventions by means of videoconferencing, as this modality may have offered a good alternative for avoiding the physical gathering of various individuals within the same room, and thus preventing the spread of the virus. It therefore seems that the mental health services opted to offer their patients a range of options with which to guarantee the continuity of services, in line with the recommendations of Kopelovich et al. [47] for good practices in mental health services in times of COVID.

Importantly, for patients who received teletherapy during the lockdown, emergency visits and hospitalization rates were lower four and six months after the first wave of COVID-19. Receiving teletherapy during stressful periods, when in-person sessions are not possible, appears to be a protective factor against hospitalization, particularly in the medium-term. This concurs with previous findings suggesting that over the phone [48] and videoconferencing [41, 49] interventions have levels of clinical effectiveness, similar to those of in-person therapy. The interruption of psychotherapy in times of uncertainty and fear, may certainly have triggered a feeling of loss, helplessness, or sense of vulnerability. Patient-family cohabitation in confined spaces for a long period of time and the emotional discomfort associated with the pandemic, may also have led to tensions within the family affecting expressed emotion levels [50], a well-known risk factor for relapse [51]. In this regard, continuity of care through teletherapy may have offset the negative effects of expressed emotions and have prevented crisis [52]. Importantly, patients that received therapy via videoconferencing seemed to have less hospitalizations six months after the first wave of the pandemic. This supports recommendations that videoconferencing should be used as a means of assuring continuity of care during the pandemic [8]. It also concurs with the conclusions of a systematic review of 65 videoconferencing-based psychotherapy studies that suggested videoconferencing as a feasible alternative to in-person interventions, as it is associated with positive outcomes such as treatment adherence, social functioning, and quality of life levels [53].

Limitations and strengths

This study is the first to explore psychotherapeutic intervention alternatives for individuals with SMI, during the COVID-19 pandemic, a topic that has been largely neglected in the literature. The study’s observational nature, together with the participation of multiple healthcare sites allowed us to draw comprehensive conclusions regarding the clinical care provided in Spain, under the specific conditions created by the COVID-19 pandemic. The extraction of the patients’ data from routine clinical practice records also ensured greater reliability of the findings, while the retrospective design with multiple follow-ups provided us with a unique opportunity to observe the associations of a variety of teletherapy types with the patients’ hospitalization rates after the first wave of the pandemic.

However, the following limitations need to be considered. Firstly, as this is an observational study, it is not possible to establish direct causal relationships, as other confounding variables may play a role in the association between the intervention modalities and the hospitalization rates. Secondly, the study design did not allow for the comparison of teletherapy with in-person interventions, since, due to the special conditions created by the COVID-19 crisis in-person therapy was barely used during the studied period. This explains why the in-person modality was considered as a confounding factor, and not as an independent variable in the multilevel analysis. Thirdly, the retrospective nature of the study may have biased the results, despite the inclusion of objective routine data based on clinical records specifically aimed at reducing such bias. Fourthly, patients were grouped under the Serious Mental Illness condition, and we did not perform a separate analysis for each diagnostic category. Diagnoses in mental health are in fact collections of symptoms and could be explained using completely different lenses to the medical lens [54]. Therefore, including all patients with SMI in our study allowed for an overall and realistic perspective of the routine clinical practice during the first wave of the pandemic. It should be noted that, the multilevel findings suggested that the probability of having a hospitalization six months after the first wave did not seem to vary between patients with different diagnoses. Similarly, previous studies have reported associations between sociodemographic and clinical factors such as sex, age, medication adherence, and hospitalizations [55, 56]. We also included those factors as confounding variables in our multilevel analyses, to control for their potential contribution. Although it lay beyond the scope of this study to focus on such associations, future research should conduct a more in-depth examination of each diagnostic category and of the role played by sociodemographic factors in the context of teletherapy. Lastly, information on theoretical approaches of the specific interventions, was not taken into account for our analyses. This was beyond the scope of the present study, which focused exclusively on the use of teletherapy as a valid alternative in the unique restrictive context of the pandemic.

Future research perspectives

Future research into the topic should compare the implementation of teletherapy in different diagnostic categories of SMI, and also examine its impact on psychosocial outcomes, such as functioning and recovery. Extending the follow-up period would also make it possible to observe any potential changes in the use of teletherapy in the long run, while a detailed description of the specific interventions performed within each therapeutic mode would provide useful information regarding the feasibility of their telematic alternatives. Finally, the application of experimental designs such as randomized control trials would throw light on the effectiveness of teletherapy, beyond the context of the pandemic, as current results are inconsistent [57]. It is worth noting that, to date, no official guidelines exist in Spain for the use of telematic means in healthcare, making this a challenging task in this context [58].

Conclusions

In conclusion, the COVID-19 pandemic seems to have brought changes in the practice of psychological interventions, as in-person interventions decreased, and the use of teletherapy increased, providing an opportunity to explore its applicability with individuals with SMI. This study discusses the implications of the pandemic on the provision of care for individuals with SMI, and opens the door to further research on the effectiveness of teletherapy beyond the pandemic context. Our findings suggest that teletherapy can indeed serve as a valid alternative for protecting patients with SMI against hospitalizations, especially under circumstances where in-person interventions are not feasible.

Supporting information

S1 File. G-power_analysis.

(PDF)

Click here for additional data file.^{(29.9KB, pdf)}

S1 Checklist. STROBE-checklist.

(PDF)

Click here for additional data file.^{(125.7KB, pdf)}

Acknowledgments

The authors wish to acknowledge the collaboration of the day hospitals section of the Spanish Neuropsychiatry Association.

Data Availability

Our data cannot be shared publicly because they contain sensitive patient information, such as sex, age, living and occupational status, and most importantly, diagnosis and records of mental healthcare visits. Such information is based on the clinical records of specific community healthcare centers, where most of the authors of this paper work as clinicians. Therefore, we consider that there is a risk of potential identification of the patients. To avoid such risk, access to the database can be formally requested through contacting the Biomedical Research Ethics Committee of the Government of Andalusia, Spain in the following address portaldeetica.csalud@juntadeandalucia.es.

Funding Statement

AS received funding by the FPS 2020 – Primary Care Regional Hospitals and CHARES R&D Projects, (within the Project AP-0028-2020-C1-F2) and AS, MS, CM and FP received funding by the Outpatient Mental Health Day Hospitals of the Spanish Association of Neuropsychiatry. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0267209.r001

Decision Letter 0

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11 Feb 2022

PONE-D-21-24939Teletherapy and hospitalizations in patients with serious mental illness during the COVID-19 pandemic: A retrospective multicenter studyPLOS ONE

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Reviewer #1: Thanks for giving me the opportunity to review this paper. The paper covers an important and current topic of remotely delivered mental health services during COVID-19 pandemic. I have few comments which may need to be addressed by the authors.

1) I think it would be a good idea if the authors provide more details for how the ‘treatment adherence’ was measured in the methodology section.

2) I wonder if the authors can explore further how the % of hospitalization was calculated? Was it calculated against the individual’s history of admission or to all patients in the current sample.

3) I am not sure if McNamar test was the appropriate test to examine the changes over the three periods of time. This test examines each couple of periods individually, so the error may be amplified over the three comparisons. I think Friedman test would be more fitting here.

4) Similarly, table three demonstrates individual lines of analyses (chi square or t test for each line), which I find difficult to interpret. It could be more comprehensible to apply one chi square analysis for one table (3x2) and the same for t test, instead ANOVA test would be used.

5) It is not clear why authors included these specific factors in the hierarchal regression model (specific sociodemographic or clinical). I may suggest adding some details in the introduction section to justify the work.

6) From table 4, I would appreciate if the authors could provide the Wald value for the significant predictors to identify the strongest predictor, given that all interventions were significant, including the In-person intervention. Particularly when the CI of the Videoconference intervention is quite high.

Reviewer #2: The article reflects a topic of very current interest. They carry out an adequate bibliographic review of the topic. The methodology is correct and they meet the ethical requirements for this issue. In the discussion the critical aspects of the work are reviewed in a very appropriate way. It is important that the deficit aspects are well specified in the limitations section.

Reviewer #3: Peer review PONE

Thank you for the opportunity to review this manuscript entitled “Teletherapy and hospitalizations in patients with serious mental illness during the COVID-19 pandemic: A retrospective multicenter study”

Please find my comments below.

Major Comments

1) Please include a clear definition of each of the modalities you are talking about in the introduction and use consistent terms throughout (i.e. what is involved in “videoconferencing”? Does it have to involve more than 2 parties? Did this vary at all for the people involved in the study/across hospitals?)

2) In line 146 you state: “Serious Mental Illness was defined based on the ICD diagnosis, as well as on the intensity of the required care provision”. But you do not specify which diagnoses specifically were considered SMI. “SMI” is not a diagnosis itself. Your sample includes people with anxiety disorders – this is usually not categorised as a SMI. In addition to this clarification regarding the definition of SMI, some justification and discussion of the heterogeneity of diagnoses included in the study is needed. Why not focus on one diagnosis? How do you think the heterogeneity of diagnoses might be impacting the results? Please add this to the discussion, explaining the reasoning and the possible impact of this inclusion of different diagnoses.

3) More information is needed on the G*Power analysis: what effect size were you using? How was that justified/what was it based on? The full calculation should be found in the appendix.

4) IS there a reason that the results not reported according to a standardised checklist? Please see a list of checklists and arrange the results in line with a standardised approach, including the checklist in the appendix: https://www.strobe-statement.org/checklists/

5) It would be useful to a have a few lines on the mental health system in Spain where the study took place. It seems from the method section that there are specific Accident and Emergency units for mental health. Is this the case? A small introduction to the context would help the reader – this could be added to the method or to the introduction.

6) More explanation and justification is needed in the statistical analysis section. For example, why was McNemar’s test used?

7) Lines 249-250: “Statistically significant differences were also found in the use of phone interventions before and after the first wave (p < .001).” Please give more details: what was this statistically significant difference? What was bigger/smaller?

8) Line 288-289: please revise, it is not clear what the sense of the sentence is.

9) The language in the discussion section “Principal Results and Comparison with Prior Work” of the finding that having more videoconferencing was associated with lower hospitalisation rates suggests causality. However, the study is observational (which is reflected in the limitations section). This finding, though striking and important, should be described with great care.

Minor Comments

10) The methods of the abstract is hard to follow – please break into 2 sentences.

11) The aims of the study are expressed in a way that is difficult to understand. A suggested alternative follows (to replace lines 131-139). “The present study aimed to: a) explore the types of care offered to people with SMI during the first COVID-19 wave, the alternatives used when in person interventions were not possible, and the changes in the modality of interventions used over time (before the first wave, during lockdown, and after the first wave); b) examine whether receiving teletherapy, compared to not receiving teletherapy during the lockdown was associated with the frequency of visits to the emergency department and of hospital admissions, two, four, and six months after the lockdown; and c) examine if different teletherapy types (modalities?) are associated with hospitalization rates six months after the lockdown.”

12) Line 329: “telematic intervention”: what does this mean? Using consistent words/terms throughout and not introducing new terms in the discussion section will make it easier for the reader to follow.

13) Line 329: “the percentage of patients that received it was lower” lower than what? Please clarify.

14) Please have this carefully read by a native English speaker. Terms like “originated” (line 66), “smoothened” (line 367) are not incorrect but very unusual. Throughout “videoconference” should be changed in most cases to “videoconferencing”, or another new term that makes it clearer what you mean (“video call”?).

15) Lines 59-60: please rephrase, people being “characterised” by social networks is not quite correct. Perhaps change to say: “Social distancing practices may pose a great negative impact on individuals with pychotic disorders, as they are known to have small and low quality social networks”

16) line 352: please replace the number 45 with words.

17) Line 382: “recompilation” what does this mean?

**********

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Reviewer #1: Yes: Reham Shalaby

Reviewer #2: Yes: Cristina Romero-Lopez-Alberca

Reviewer #3: No

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PLoS One. 2022 Apr 18;17(4):e0267209. doi: 10.1371/journal.pone.0267209.r002

Author response to Decision Letter 0

10 Mar 2022

Manuscript ID PONE-D-21-24939

Response to the Reviewers’ comments

1) I think it would be a good idea if the authors provide more details for how the ‘treatment adherence’ was measured in the methodology section.

___This is now specified at the manuscript, Section “Variables and Data sources/measurement, page…, as follows:

“Treatment adherence was determined through the Medication Possession Ratio, defined as the proportion of time when medication supply is available [38]”

Andrade, S. E., Kahler, K. H., Frech, F., & Chan, K. A. (2006). Methods for evaluation of medication adherence and persistence using automated databases. Pharmacoepidemiology and drug safety, 15(8), 565-574.

2) I wonder if the authors can explore further how the % of hospitalization was calculated? Was it calculated against the individual’s history of admission or to all patients in the current sample

___The percentage of hospitalizations is calculated against the study sample.

We have now added this to the Methods section (Outcome Variables, page 10)

—-We thank the Reviewer for the suggestion. Given that our data are expressed in proportions, to perform comparisons between the different time points we have calculated a series of Cochran´s Q tests. Results can be seen at Table 2.

___We have kept the McNemar results displaying the between time points differences, for the interest of the Reader

—--We have clarified this to the Statistical methods section, page 11, as follows:

“we used a series of Cochrane’s tests to determine whether there were statistically significant differences in the proportion of patients making use of the different intervention types over the three time points (before, during, and after the lockdown). We also performed pairwise comparisons through a series of McNemar's tests, to check whether the proportion of patients using the interventions was sustained or varied from one time point to another (before, during and after the lockdown)”

___We thank the Reviewer for the suggestion. However, the individual lines of analyses in Table 3 represent independent comparisons between people that have received teletherapy and those that have not (two groups). Therefore, we performed three chi-square tests to compare the two groups in terms of Hospitalization rates (for each of the three different time points). Similarly, we performed three t-test analyses to compare the two groups in terms of Emergency visits.

__The sociodemographic and clinical variables added to the model were chosen based on previous evidence suggesting such variables as potential risk factors for relapse. It was beyond the scope of the current study to further explore their potential associations with relapse, however, we considered it was important to add them in the model to control for their potential confounding effect.

___We have now added further clarifications in the Limitations section as follows (manuscript page 23):

“Similarly, previous studies have reported associations between sociodemographic and clinical factors such as sex, age, medication adherence, and hospitalizations [54, 55]. We also included those factors as confounding variables in our multilevel analyses, to control for their potential contribution. Although it lay beyond the scope of this study to focus on such associations, future research should conduct a more in-depth examination of each diagnostic category and of the role played by sociodemographic factors in the context of teletherapy.”

___We have now added the Wald value, check Table 4.

___Thank you for your comments and the positive feedback to our manuscript

Reviewer #3: Peer review PONE

Please find my comments below.

Major Comments

___We have now provided more complete definitions for each of the teletherapy modalities (Introduction page 5).

___In the methods section, we have provided more details regarding the specific modalities used in our study (Introduction pages 9-10)

___We have adopted the National Institute of Mental Health definition for Severe Mental Illness, as such perspective allows for the classification of patients not only based on their Diagnosis, but also on the severity of their condition in terms of functional impairment that substantially interferes with the person's everyday life, and thus calls for intensive care. Besides Psychosis and Affective disorders, anxiety disorders, eating disorders, and personality disorders are also considered Severe Mental Illnesses when a) the degree of functional impairment is severe (Evans et al., 2016; Wing et al., 2004) and b) there is a need for an interdisciplinary treatment approach (Moreno et al., 2020).

In the Spanish Healthcare system, such an approach is offered by the Community Mental Health Hospitals network, that is destined to patients with major complexity in terms of functional impairment and treatment needs. Therefore, our sample consisted of all the patients that attended any of the Community Mental health Hospitals that took part in the study, as those patients were fulfilling the above-mentioned conditions, and therefore had the need of attending such services.

Evans TS, Berkman N, Brown C, Gaynes B, Weber RP. Disparities within serious mental illness. Agency for Healthcare Briefs and Quality, Rockville, USA. 2016; 25.

Moreno, M. J., Jaén, M. J., Lillo, R., Guija, J. A., & Medina, A. Severe Mental Illness: Psychiatry and Law. Spanish Federation of Psychiatry and Mental Health, Madrid, Spain. 2020 (book in Spanish)

Wing JK. Severe Mental Illness. In: Stevens a (ed). Health Care Needs Assessment: The Epidemiologically Based Needs. Assessment Reviews, vol 2. Oxford-San Francisco. Radcliff Publishing. 2004; 159-237.

___We agree with this Reviewer that the inclusion of all patients with SMI without distinguishing among different diagnoses may influence our results, therefore we included Diagnosis as a confounding variable to our multilevel analyses. The findings suggested that Diagnosis did not seem to be associated with hospitalizations six months after the first wave (check Methods and Results sections).

____However, we still acknowledge that Diagnostic heterogeneity may play a role, and added this to the Limitations of our study:

“Fourthly, patients were grouped under the Serious Mental Illness condition, and we did not perform a separate analysis for each diagnostic category. Including all patients with SMI in our study allowed for an overall and realistic perspective of the routine clinical practice during the first wave of the pandemic. It should be noted that, the multilevel findings suggested that the probability of having a hospitalization six months after the first wave did not seem to vary between patients with different diagnoses…Although it lay beyond the scope of this study to focus on such associations, future research should conduct a more in-depth examination of each diagnostic category and of the role played by sociodemographic factors in the context of teletherapy”

3) More information is needed on the G*Power analysis: what effect size were you using? How was that justified/what was it based on? The full calculation should be found in the appendix.

___More details were added to the Setting and Participants section, page 9 as follows:

“To calculate the sample size, we considered a 20% relapse rate for the group that received teletherapy and 30% relapse rate for the group that did not, with a potential sample loss of 15%, a Confidence Interval of 95% and 80% statistical power (see S1 for details).”

___We have added the G-power calculation at the appendix (S1), using the corresponding formula provided at: https://www.fisterra.com/mbe/investiga/9muestras/9muestras2.asp

___As per the recommendations of this Reviewer, we have adapted the manuscript following the STROBE checklist approach.

___We include the checklist as a supplementary file (S2).

___We have now added a paragraph briefly explaining the Spanish mental healthcare system. See Methods, Settings and Participant Recruitment section, page 8

6) More explanation and justification is needed in the statistical analysis section. For example, why was McNemar’s test used?

___Please see answer to Comment 3 Reviewer 1

___We have modified the sentence to provide clarity as follows (page 14)

“However, this percentage was still significantly higher than before the lockdown (p < .001).”

8) Line 288-289: please revise, it is not clear what the sense of the sentence is.

___We have now revised the sentence to provide clarity.

___We have now modified the sentence to provide clarity and avoid causality conclusions, as follows (page 21):

“Importantly, patients that received therapy through videoconferencing seemed to have less hospitalizations six months after the first wave of the pandemic…”

Minor Comments

10) The methods of the abstract is hard to follow – please break into 2 sentences.

__We have now restructured the methods section of the abstract, to provide clarity

___We thank the Reviewer for this suggestion, which we used to replace the original aims section.

___Please check page 5, where telematic psychological interventions are defined as follows, based on the literature:

“Alternatives to in-person care were in fact implemented with the aid of teletherapy, un umbrella term for what are known as telematic psychological interventions (telepsychotherapy and e-therapy), Teletherapy is based on information and communications technology (computer-based Internet tools, mobile and land telephone calls, emails, fax, text messages, and videoconferencing consisting of patient-clinician communication through video consultations) [12].”

___We have also modified the term across the text replacing it with the term teletherapy when feasible, and consistent with the meaning.

13) Line 329: “the percentage of patients that received it was lower” lower than what? Please clarify.

___We have now specified that the percentage of patients that received teletherapy through videoconference was lower as compared to those receiving the over the phone modality

___We have now replaced videoconference with videoconferencing, following the suggestion of this Reviewer.

___ We have also replaced originated with caused by. smoothened with offset.

—-We also had a native English speaker proofreading our text and taken care of potentially unclear sentences.

___We have replaced the sentence as per the instructions of this Reviewer

16) line 352: please replace the number 45 with words.

___We have now added the first author´s name for this citation

17) Line 382: “recompilation” what does this mean?

___We have now replaced recompilation with “extraction” to provide clarity.

We would like to thank the Reviewers for their valuable and helpful suggestions that helped us improve our manuscript.

Attachment

Submitted filename: Response to the Reviewers_26Feb22.docx

Click here for additional data file.^{(28.4KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0267209.r003

Decision Letter 1

Xenia Gonda

29 Mar 2022

PONE-D-21-24939R1Teletherapy and hospitalizations in patients with serious mental illness during the COVID-19 pandemic: A retrospective multicenter studyPLOS ONE

Dear Dr. Petkari,

Please submit your revised manuscript by May 13 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
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An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Xenia Gonda

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

As you will see, the reviewers found that you have addressed all your comments which improved this already excellent paper. Before your paper is ready to be accepted, please address the minor comments raised by Reviewer 1.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #3: I Don't Know

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: (No Response)

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: (No Response)

Reviewer #3: Yes

**********

6. Review Comments to the Author

Reviewer #1: I would like to thank the authors for the prompt reply to the raised points.

Only few concerns are still there:

1) Thanks for using Cochrane’s test, I think, therefore the authors would need to report McNemar’s test with manually Bonferroni correction, rather than McNemar’s test only.

2) Table 3 seems quite confusing to me. The title refers to six months after the first wave, while in the table there are two months after the lock down. Similarly, in narration, the two terms were used interchangeably “Hospitalization rates two months after the first wave did not differ between patients who received …”, please consider revision

3) I may disagree with “… with slight risks associated with receiving in-person interventions (OR=0.56; p=.03)”, this seems to me not a risk, however in-person interventions seems going in the same direction as videoconferencing and interventions over the phone, with a lower risk for hospitalization.

4) A typo in “(p = .11NS)” and in Table 4 “-0,69 (0.23)”

Reviewer #3: Peer review PONE

Dear Authors,

Thank you for the thorough responses to my queries. I think a final point on the diagnosis question, although you have addressed this very thoroughly with the changes to the method and discussion, is maybe to hint at the fact that diagnoses in mental health are all collections of symptoms, or syndromes, and could be explained using completely different lenses to the medical lens. This, I think, would aid in making the argument for why it was justified, and better, that you did not stick very strictly to one country’s narrow diagnostic category, from a single point in time, but rather took a more inclusive view, that reflects the uncertainties around the nature and aetiology of mental illness and our ever-evolving understandings.

Some references to include in making this point (a sentence in the discussion or methods would suffice I believe):

Bhui, K., & Priebe, S. (2006). Assessing explanatory models for common mental disorders. The Journal of clinical psychiatry, 67(6), 1441.

Conneely, M., Higgs, P., & Moncrieff, J. (2021). Medicalising the moral: the case of depression as revealed in internet blogs. Social Theory & Health, 19(4), 380-398.

There are a few minor changes that need correcting that should be picked up in a thorough proof-read, a few are picked up below:

1. Repetition of the word “challenging” in the concluding paragraph of the abstract.

2. “Less” should be “fewer” in the last line of the Results section of the abstract.

3. First paragraph of the discussion, last sentence, there is an unnecessary “of”

4. Discussion: “crise” � “crisis”

Congratulations on this impressive piece of work!

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Reham Shalaby

Reviewer #3: No

PLoS One. 2022 Apr 18;17(4):e0267209. doi: 10.1371/journal.pone.0267209.r004

Author response to Decision Letter 1

1 Apr 2022

Manuscript ID PONE-D-21-24939-R1

Response to the Reviewers’ comments

Reviewer #1: I would like to thank the authors for the prompt reply to the raised points.

Only few concerns are still there:

1) Thanks for using Cochrane’s test, I think, therefore the authors would need to report McNemar’s test with manually Bonferroni correction, rather than McNemar’s test only.

_We added a sentence in the Statistical Methods section specifying the Bonferroni correction applied (page 11)

_ To reflect the applied correction to the results, we modified the corresponding Results section (page 14)

___We have now revised the Table title and the text to provide consistency

___We have now modified this sentence to provide clarity, as follows: “These findings were maintained when including potential confounders, with lower risk for hospitalizations associated with receiving in-person interventions(…)”

4) A typo in “(p = .11NS)” and in Table 4 “-0,69 (0.23)”

__Thank you for the suggestion, these typos are corrected

Reviewer #3: Peer review PONE

Dear Authors,

Some references to include in making this point (a sentence in the discussion or methods would suffice I believe):

Bhui, K., & Priebe, S. (2006). Assessing explanatory models for common mental disorders. The Journal of clinical psychiatry, 67(6), 1441.

Conneely, M., Higgs, P., & Moncrieff, J. (2021). Medicalising the moral: the case of depression as revealed in internet blogs. Social Theory & Health, 19(4), 380-398.

__We thank the Reviewer for the suggestion, we have now added a sentence at the Discussion section: See Limitations, p.22

There are a few minor changes that need correcting that should be picked up in a thorough proof-read, a few are picked up below:

1. Repetition of the word “challenging” in the concluding paragraph of the abstract.

__The word is now erased

2. “Less” should be “fewer” in the last line of the Results section of the abstract.

_”Less” is replaced with “fewer”

3. First paragraph of the discussion, last sentence, there is an unnecessary “of”

__”Of” is erased

4. Discussion: “crise” � “crisis”

__This is now replaced

Once again, we thank the Reviewers for their valuable comments that brought considerable improvements to our manuscript

Attachment

Submitted filename: Response to the Reviewers_1Apr22.docx

Click here for additional data file.^{(19.9KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0267209.r005

Decision Letter 2

Xenia Gonda

5 Apr 2022

Teletherapy and hospitalizations in patients with serious mental illness during the COVID-19 pandemic: A retrospective multicenter study

PONE-D-21-24939R2

Dear Dr. Petkari,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

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Kind regards,

Xenia Gonda

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0267209.r006

Acceptance letter

Xenia Gonda

8 Apr 2022

PONE-D-21-24939R2

Teletherapy and hospitalizations in patients with serious mental illness during the COVID-19 pandemic: A retrospective multicenter study

Dear Dr. Petkari:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Xenia Gonda

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 File. G-power_analysis.

(PDF)

Click here for additional data file.^{(29.9KB, pdf)}

S1 Checklist. STROBE-checklist.

(PDF)

Click here for additional data file.^{(125.7KB, pdf)}

Attachment

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Attachment

Submitted filename: Response to the Reviewers_26Feb22.docx

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Attachment

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Data Availability Statement

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PERMALINK

Teletherapy and hospitalizations in patients with serious mental illness during the COVID-19 pandemic: A retrospective multicenter study

Antonio José Sánchez-Guarnido

Beatriz Machado Urquiza

Maria del Mar Soler Sánchez

Carmen Masferrer

Francisca Perles

Eleni Petkari

Roles

Abstract

Background

Objectives

Methods

Results

Conclusions

Introduction

Materials and methods

Study design

Setting and participants

Variables and data sources/measurement

Intervention characteristics

Procedure

Statistical methods

Results

Participants and descriptive data

Table 1. Sociodemographic and clinical characteristics of the sample.

Outcome data and main results

Comparison between the different types of intervention before the pandemic, during lockdown, and after the first wave

Table 2. Comparison of interventions received before the pandemic, during the lockdown, and after the first wave.

Differences in hospitalization rates and visits to the mental health emergency department in patients who received teletherapy during the lockdown and those who did not

Table 3. Hospitalizations and emergency visits two, four and six months after the lock down.

Differences in hospitalization rates six months after lockdown based on the type of teletherapy

Table 4. Multilevel logistic regression models predicting hospitalizations 6 months after the lockdown.

Discussion

Key results and interpretation

Limitations and strengths

Future research perspectives

Conclusions

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Xenia Gonda

Roles

Author response to Decision Letter 0

Decision Letter 1

Xenia Gonda

Roles

Author response to Decision Letter 1

Decision Letter 2

Xenia Gonda

Roles

Acceptance letter

Xenia Gonda

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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