Skip to main content
Download PDF

DAily time use, Physical Activity, quality of care and interpersonal relationships in patients with Schizophrenia spectrum disorders (DiAPASon): an Italian multicentre study

BMC Psychiatry volume 20, Article number: 287 (2020) Cite this article

Abstract

Background

Schizophrenia spectrum disorders (SSD) are ranked among the leading causes of disabilities worldwide. Many people with SSD spend most of their daily time being inactive, and this is related to the severity of negative symptoms. Here, we present the 3-year DiAPAson project aimed at (1) evaluating the daily time use among patients with SSD living in Residential Facilities (RFs) compared to outpatients with SSD and to the general population (Study 1); (2) evaluating the quality of staff-patient relationships, its association with specific patient outcomes and the quality of care provided in RFs (Study 2); and (3) assessing daily activity patterns in residential patients, outpatients with SSD and healthy controls using real-time methodologies (Study 3).

Methods

Study 1 will include 300 patients with SSD living in RFs and 300 outpatients; data obtained in these clinical populations will be compared with normative data obtained by the National Institute of Statistics (ISTAT) in the national survey on daily time use. Time use assessments will consist of daily diaries asking participants to retrospectively report time spent in different activities.

In Study 2, a series of questionnaires will be administered to 300 residential patients (recruited for Study 1) to evaluate the quality of care and staff-patient relationships, level of well-being and burnout of RFs’ staff, and quality of RFs using a European standardized questionnaire (QuIRC-SA).

In Study 3, the daily time use will be evaluated in a subgroup of 50 residential patients, 50 outpatients and 50 healthy controls using the Experience Sampling Method approach (participants will complete a brief questionnaire -about time use, mood and perceived energy- on a smartphone 8 times a day for 1 week) to compare retrospective and real-time reports. Moreover, their level of physical activity, sleep patterns, and energy expenditure will be monitored through a multi-sensor device.

Discussion

This project is highly innovative because it combines different types of assessments (i.e., retrospective and real-time reports; multi-sensor monitoring) to trace an accurate picture of daily time use and levels of physical activity that will help identify the best therapeutic options promoting daily activities and physical exercise in patients with SSD.

Trial registration

ISRCTN registry ID ISRCTN21141466.

Peer Review reports

Background

Schizophrenia is one of the most disabling and severe mental disorders: while its incidence and prevalence are relatively low (McGrath and colleagues found a median prevalence of schizophrenia of 15.2 per 100,000 persons and a median lifetime morbid risk for schizophrenia of 7.2 per 1000 persons), its burden is substantial both for individuals and society [1, 2].

Here, we present the DiAPAson study, a 3-year-long project aimed at fostering our knowledge about the daily time use among people with Schizophrenia Spectrum Disorders (SSD) using different methodologies. The study will address the relationship between the daily time use and negative symptoms and will evaluate the level of Physical Activity (PA), which is known to be reduced in this clinical population. We will also investigate the quality of the staff-patient relationships and the quality of care in Residential Facilities (RFs), which provide long-term care in a country where all former mental hospitals have been shut down.

Time and psychopathology: historical roots

The study of time and its perception among people with different types of mental disorders has long been an object of investigation for scientists and clinicians active in this field. The idea that temporality had a connection with the state of mind was initially formulated by Augustine of Hippo in his “Confessions” [3]. Later, over the nineteenth century, time became an essential variable for the emerging experimental or natural sciences until the philosopher Henri Bergson recognized the special status of the “subjective” time, in contrast to “objective” or chronological time: he called the former “lived time”, characterized by the expansion of vital momentum [4]. The prominent German philosopher Heidegger identified the very meaning of being in the future (as opposed to the past and the present) and thoroughly reflected on the temporality of human existence [5]. However, it was the French (born in Poland) psychiatrist Eugene Minkowski, relying on his Bergsonian readings, to work on the notion of time in psychiatry: in 1914, he published a monograph entitled “The Essential Elements of Time-Quality”, and in 1933, he produced his fundamental book entitled “Lived Time: Phenomenological and Psychopathological studies”, where he draws a vision of mental disorders based on temporality [6, 7]. Melancholy, in particular, was seen as a disorder where the past was frozen and no longer “passing”: in depression, time does not allow the present and the future to happen; on the contrary, in mania, time runs away, and the patient is unable to stop it. Overall, temporality in psychopathology can be considered the primary modality constituting the experience, that is, it gives shape to the experience, as well as to the symptoms of mental disorders.

Daily time use in the general population and in people with severe mental disorders

“Daily time use” has been investigated since the late 1920s in the US, initially with a focus on economic productivity and inequalities in labour force and later expanded to assess the use of time among different socioeconomic groups [8]. Within a few years, this research area became of high relevance to describe social conditions and understand people’s behaviour, so that governments in different countries started to map how people used their time with “time use surveys” (TUS [9]). More recently, in 2000, Eurostat released a series of methodological guidelines for facilitating the data collection process and comparison over time of daily time use within and between countries (i.e., Harmonised European Time Use Surveys; HETUS).

Importantly, TUS validation has also allowed a comparison between normative and clinical samples. Several studies have shown that mental disorders are negatively linked to engagement in structured activities throughout the day [10, 11]. While it has long been known that many people with SSD are mainly inactive and apathetic, only recently the study of daily time use has started to be conducted with valid methodologies. These studies have shown that patients with SSD spend significantly less time engaging in structured, functional and social activities and more time resting and “doing nothing” than non-clinical populations [11, 12]. The disorder has a severe impact on social and leisure activities [13], producing a self-maintenance cycle for negative symptoms and influencing functional outcomes [14, 15]. All these findings highlight the importance of assessing daily time use, especially in at-risk populations such as individuals with SSD.

How to assess daily time use in patients with schizophrenia?

Time-use surveys are usually conducted through semi-structured interviews where participants are asked to retrospectively report the time spent in a variety of daily activities. According to the latest HETUS guidelines, TUS provide comprehensive coverage of all activities in which the subject was involved during the day and facilitate epidemiological research into cross-national comparisons and trend analyses [8].

However, the use of clinical interviews and questionnaires for assessing time use in SSD patients might be biased due to their memory deficits [16, 17], with increased reporting of time engaged in activities while they are indeed “doing nothing” [12]. Thus, recent studies on time use in this clinical population have been based on prospective and real-time assessments, such as the Experience Sampling Method (ESM) approach [18]. The ESM approach provides an ecologically valid time sampling of self-reports that allows studying person-environment interactions in daily time use (e.g., places, people, activities, emotions). Furthermore, it gives instant estimates of current behaviour that are less vulnerable to recall biases [19,20,21,22]. This approach might be particularly efficient in evaluating SSD patients given their cognitive deficits and inclination to biases [23]. To assess instantaneous estimates of behaviour, current practice adds real-time measurements taken from accelerometers to ESM data [21, 24]. A recent study demonstrated the feasibility, sensitivity, reliability and validity of ESM methods to assess functioning in patients with SSD [18].

Physical activity in people with SSD

SSD patients show higher morbidity and mortality compared with the general population [25]. Overall, these patients are at risk for physical comorbidities [26], mainly cardiovascular diseases, metabolic syndromes and diabetes, which cause a 7–20 year reduction in life expectancy [27,28,29,30,31]. Sedentary behaviour and low PA are risk factors for the development of these medical conditions and thus premature mortality [32, 33].

The effect of PA on chronic disease prevention is well documented [34]. In SSD patients, PA interventions have been shown to improve global cognition, working memory and attention [35] and increase white matter connectivity, brain volume, and serum brain-derived neurotrophic factor levels [36, 37]. Moreover, PA shows positive effects on psychological well-being and anxiety [38] and can improve mental and physical quality of life, reducing metabolic risk and overweight [39, 40]. Given that sedentary behaviour is an independent predictor (from PA) of cardiovascular diseases [41], emerging evidence suggests the importance of monitoring both PA and sedentary behaviour in SSD patients [42].

Collecting precise data on the actual levels of PA and sedentary behaviour is, therefore, of paramount importance in SSD patients. In this project, we will use objective measurement methods, such as (i) overall PA dose, assessed as the amount (minutes per day) and intensity (metabolic equivalents) and (ii) amount of sedentary time and sleep quantity and quality.

Previous Italian studies investigating the time spent doing nothing among SSD patients

In Italy, some studies conducted among a large sample of patients staying in RFs have shown that most patients (in particular patients with SSD) spend little time in meaningful activities and have low levels of PA. In the nationwide PROGRES survey, de Girolamo et al. [43] found that 45% of the sample of 2932 residential patients was inactive, not even assisting with domestic activities in the facility.

Low levels of activity among RFs’ patients have been confirmed by a more recent longitudinal study (PERDOVE study, [44]) conducted among 403 patients hosted by 22 RFs in Northern Italy. This study evaluated in detail the daily time use, showing that (i) 30.8% of the sample spent most of their time alone and uninvolved in any activity; (ii) approximately 1/3 of the patients did “nothing” for more than 6 h/day; and (iii) negative symptoms in patients with SSD were highly prevalent. Similar findings have been obtained in other studies with patients living in RFs [45]. Surprisingly, there are very scant data about the amount of time spent in structured activities among outpatients with SSD, and this makes it impossible to understand whether the amount of daily time spent in meaningful activities is higher, comparable or lower among outpatients with SSD, living independently or with their families, compared to SSD patients living in RFs. Indeed, someone may argue that patients living in the community (often alone) may be more likely to be inactive than patients living in an assisted environment, where staff can stimulate patients and engage them in structured activities.

Given the importance of daily time use and its correlation with psychopathology, it is justified to state that time management represents one of the more informative prognostic indicators for patients with SSD.

Quality of care and interpersonal relationships in residential facilities

For patients living in RFs, the quality of therapeutic relationships with staff plays a critical role and is a powerful predictor of patient outcomes [46,47,48]. Bordin [49] provided a useful framework to investigate the quality of the therapeutic relationship by introducing the concept of “working alliance”. The three main components of the therapeutic alliance are agreement on goals, assignment of tasks and development of bonds.

Another fundamental aspect to consider when exploring the quality of relationships in mental health settings is the level of burnout among staff members. An extensive literature has shown how working in mental health settings and experiencing and dealing with patients’ suffering on a daily basis places the clinical staff at risk for burnout [50, 51].

For all these reasons, it is essential to assess the overall quality of care and staff-patient relationships in long-term settings (such as RFs) and correlate these data to the overall functioning of patients living in these facilities.

Hypotheses and objectives

The assumption underlying the DiAPAson project is that patients with SSD, living in RFs or living independently in the community, spend more time during the day “doing nothing” compared to the general population. We also assume that psychiatric severity, in particular, the severity of negative symptoms, will be positively correlated with the amount of time spent doing nothing.

Additionally, we hypothesize that significant discrepancies will be found comparing the assessment of daily time using a standard paper-and-pencil approach and the ESM methodology. Moreover, we assume that patients with SSD evaluated with real-time assessment through ESM and with appropriate body sensors (actigraphy) will show significant differences when compared to healthy controls: we suggest that specific patterns of associations related to the type of activity performed during the day, the perceived level of energy, PA level and mood will be found.

Finally, we assume that staff well-being and burnout levels will be associated with the quality of staff-patient relationships and specific patient outcomes and that ratings of RF’s quality using the QuIRC-SA will be positively associated with patients’ satisfaction.

Objectives

The three main aims of the DiAPAson study, a 36-month-long project, are as follows:

Objective 1

To evaluate the daily time use (e.g., use of time spent in different activities) of patients with SSD living in RFs compared to outpatients with SSD and to a large, normative sample of the general population; to assess the relationship between the severity of psychiatric symptoms (in particular negative symptoms) and the amount of time spent doing nothing and being sedentary.

Objective 2

To assess the quality of staff-patient relationships for patients living in RFs and its relationship with the staff’s well-being and burnout, and to evaluate the quality of RFs rated by service managers using the Quality Indicator for Rehabilitative Care – Supported Accomodation (QuIRC-SA).

Objective 3

To compare real-time ESM data about daily activities with retrospective, paper-and-pencil assessments to evaluate the consistency between these two data collection methodologies, and to assess levels of PA with a multi-sensor monitor (actigraphy) in three groups (RF patients and outpatients with SSD compared to healthy subjects).

Methods/Design

Study design and management

Data collection will take place in many Departments of Mental Health (DMHs) and RFs across the country, and will start in June 2020; data collection will end on May 2021. The project will be coordinated by the IRCCS Fatebenefratelli of Brescia (coordinating centre), the DMH of Modena and the DMH of Pavia. To date, approximately over 35 DMHs and RFs have expressed written interest for inclusion in the project (see Acknowledgements for a list of participating facilities). Formal agreements are currently being finalized.

Participants will be selected according to the inclusion and exclusion criteria shown in Table 1. They will approve and sign an informed consent form before inclusion in the study. The flow diagram shown in Fig. 1 provides a clear picture of enrolment and assessment procedures of all study subjects.

Table 1 Patients’ recruitment: inclusion and exclusion criteria
Full size table
Fig. 1
figure 1

Flow-diagram showing procedures for enrolment and assessment of clinical subjects and healthy controls

Full size image

Study 1 design

Participants

The sample will include 300 residential patients diagnosed with SSD (G1), matched by age and gender to 300 outpatients (G2). General population data will be extracted from the National Institute of Statistics (ISTAT) survey “Uso del tempo quotidiano”, a national survey that assesses how people spend their time, which was conducted in 2013 in Italy (ISTAT, https://www4.istat.it/it/prodotti/microdati#file_ricerca) in a representative sample of the Italian population including approximately 27,000 families (with a total of approximately 60,000 surveyed individuals) living in 508 municipalities (out of over 8000 Italian municipalities) of different sizes.

Measures and variables

A general assessment, together with demographics, will include measures of psychiatric symptoms (in particular negative symptoms), psychosocial functioning and time perception. Variables related to daily time use will include the number of daily hours spent in different activities: paid work, study, travel, doing nothing/resting, social/leisure activities, activities related to child/household care, voluntary activities, sport, and hobbies. Table 2 shows a comprehensive overview of the measures and areas of investigation; all reported instruments have been tested for validity and reliability in Italian: Table 2 shows the reference of the original paper for each instrument, and the reference of the Italian validation study. Time use assessments will consist of a pre-filled daily diary (to be completed twice a week, on a working day and on a weekend day) adapted from the ISTAT’s national survey on time use, asking participants to retrospectively report the daily time spent in different activities. The time spent in each activity will be calculated as number of hours per week.

Table 2 Assessment measures, domains and subjects receiving the assessment
Full size table

Procedure

Clinicians and mental health workers at the participating sites will receive a training session on questionnaires’ administration. Participants will be asked to complete the instruments and will receive a 20-min training session on daily diary instructions. A web portal that will allow clinicians to directly fill in the study questionnaires will be developed, and this procedure will be guided with clear and simple user interfaces. The software will perform data validation to highlight possible errors. If there is no local access to an internet connection, it will be possible to use an off-line desktop application with the same functionalities but with the ability to locally save the collected data on a computer. Data will then be uploaded to the online database when the internet connection is available.

Study 2 design

Participants

The sample will include 300 patients living in RFs (G1) and RF staff (approximately 1 staff member every 5 patients).

Measures and variables

Patients will be evaluated using a set of standardized instruments, as summarized in Table 2. The variables being studied will encompass quality of care and quality of relationships between patients and staff, level of well-being and level of burnout of RF staff, and quality of the facility assessed with the QuIRC-SA (i.e., living environment, treatments and interventions, therapeutic environment, self-management and autonomy, social interface, human rights, recovery-based practice).

Procedure

RF staff and RF managers will receive a specific training session about questionnaire administration. The facility manager will fill in the QuIRC-SA.

Study 3 design

Participants

The sample will include a sub-group of at least 50 RF patients (drawn from G1), 50 outpatients (drawn from G2) and 50 healthy controls from the general population matched by age and gender. This latter group will also complete the TUS. Healthy controls will be recruited through ads, both using the project’s website and spreading the news of the study through social networks.

Measures and variables

We will perform a time use evaluation with the ESM data, and these reports will be compared with retrospective paper-and-pencil assessments to evaluate the degree of consistency between the two information sources. Patients and healthy controls performing the ESM assessment will also be asked to wear a multi-sensor device (actigraphy) to assess levels of PA over the course of 1 week. For the ESM assessment, participants will be equipped with smartphones where a DiAPAson app will be installed. The answer to the smartphone’s prompt will allow easy evaluation of the following:

  • the specific activity being carried out by the patient (e.g., paid work, leisure, resting/doing nothing);

  • mood (i.e., rating of different adjectives on a scale from 0 to 100; e.g., “sad”, “happy”, etc.);

  • perceived level of energy (i.e., rating of different adjectives on a scale from 0 to 100; e.g., “active”, “tired”, etc.).

Procedure

Each participant will receive a 30-min training session on the ESM procedure. Participants will install the DiAPAson app on their smartphones (or will be lent a smartphone if they do not have one) and will be asked to carry the device with them over a 7-day period. The smartphone will generate a prompting auditory “recall” signal, sending a notification 9 times a day at random intervals between 7 AM and 11 PM. Participants will have to complete the ESM questionnaire on the smartphone screen (it takes approximately 1 min and has to be completed no later than 30 min after being prompted). ESM reports will allow the assessment of some of the variables examined in the TUS, as well as perceived energy and mood.

After a short training on PA assessment, participants will be asked to wear a multi-sensor device, ActiGraph GT9X Link (manufactured by ActiGraph, Pensacola, FL 3250, USA), continuously over 7 consecutive 24-h periods. The device will be worn on the non-dominant arm and set to record 60-s epochs, computing a total activity count for each active minute of the day. This method relies on a wearable device (combining accelerometer with measurements of heat production and skin conductivity) that measures physiological variables and bodily movements over prolonged periods of time. An algorithm converts raw data into estimates of Energy Expenditure (EE), which are expressed both in kcal/min and Metabolic EquivalenTs (METs) [81]. The multi-sensor device has been shown to provide accurate results for estimating EE and time spent in various activities and to provide valid estimates of EE in the general population [82]. The following PA parameters will be measured: (i) average physical activity: the average of all active minutes during days and nights; (ii) total idle time as well as sleeping (including sleep latency, sleep efficiency and total sleep time): average number of inactive minutes between morning alarm and time when going to bed; (iii) energy expenditure; (iv) MET rates; and (v) body position. These data will be collected as integrated activities every 60 s using arbitrary units.

Measurements via smartphone and actigraphy will be simultaneous (i.e., during the same week). Outpatients and healthy controls participating in the ESM and PA monitoring will receive a € 25 reimbursement in supermarket vouchers as compensation for travel expenses to receive the training. All these data will be saved in a secure database for future analysis. At the end of the assessment week, the project web portal will be used to upload the armband data.

Recruitment and data collection

Eligible participants will be recruited from a large number of RFs across the entire country, allowing meaningful comparisons of facilities and services located in different areas. Consent forms will be collected according to the local ethical committee requirements. Participants will be matched by age, gender and diagnosis. Both residential patients and outpatients will be recruited by treating clinicians; outpatients meeting inclusion criteria will be consecutively invited to join the study. Similar number of participants will be recruited at each participating centre, also accounting for the specific characteristics of each participating facility. Overall, patients to be recruited in each center will range from 15 (smaller ones) to 40 subjects (bigger ones).

As spelled out in the original protocol approved by the funding agency, data collection will last 8 months. Questionnaires will be administered as participants are enrolled. Patients and controls participating in Study 3 (and Objective 3) will be invited to start the ESM and the monitoring of PA immediately after questionnaire administration. The administration of tools to be filled by clinicians for all patients (BPRS, BNSS and SLOF) will last approximately 1 hour; the administration of tools to be filled by clinicians only for residential patients (e.g., WAI-TP, CAN and WAS) will last approximately one additional hour. Self-administered tools (e.g., WHOQOL-Bref, WHODAS 2.0, ZTPI, P Scale, CAN, VSSS, WAI-PT, WAS) for patients will take approximately 15 min each, and can also be filled at different times. Training for both TUS, ESM and actigraphy administration will last approximately 40 min and will be organized in small groups of 2–3 participants.

Data analyses

Study 1

Data on daily time use in the different groups will be compared using parametric and non-parametric methods depending on the distribution of the investigated variables. Correlation estimates (Pearson or Spearman) will be used to assess the associations between the severity of psychiatric symptoms and the amount of sedentary time.

Sample size was calculated based on Cella and colleagues’ study [12], which compared patients with SSD (N = 170) and a general population sample (N = 1124). Their results showed that the average time spent “doing nothing” (target) in the patient group was 5.17 h per day, while for the general population, it was 0.76 h with a standard deviation of 5 for both groups. With such data, the effect size for a linear model is 0.44. As a precaution, assuming a lower effect size equal to approximately 0.15, using ANCOVA (including age and gender in the model) with three groups, and choosing a power of 0.8, the estimated total sample size is equal to N = 435. Moreover, considering a total of approximately 25 different recruitment centres, the correction for the design effect (DE = 1 + (435/25–1)*0.02 = 1.3, with an intraclass correlation coefficient equal to 0.02) leads to a sample size of about N = 570, which was increased to N = 600 (300 for each group) to account for possible dropouts of about 10%. Finally, 300 matched subjects randomly sampled from the ISTAT general population sample will be added as third group, for a total of N = 900 subjects evaluated for daily time use.

Study 2

To evaluate how the level of burnout of the staff affects the quality of the therapeutic relationships with the staff, correlation estimates (Pearson or Spearman) will be used. The influence of the burnout level (categorized as high/low) of staff (each staff member associated with a patient) on the quality of the therapeutic relationship with patients (WAI-pt) will be investigated by comparing groups (patients and staff in RFs) with generalized linear or linear models. To evaluate the associations between the quality of RFs rated by service managers and patient experiences of care, in accordance with Killaspy and colleagues [83], we will perform multilevel modelling analyses of associations between service user ratings (level 1 data) as dependent variables with unit QuIRC-SA domain ratings (level 2 data) as independent variables. The models will also include potential mediators (i.e., age, gender, and level of severity of psychiatric symptoms as assessed in Study 1).

Study 3

Appropriate tests will be used to compare the daily time use with routine methods and with ESM according to the distribution of the data. In particular, frequencies and corresponding chi-square tests, as well as Cohen’s kappa concordance index, will be used to compare ESM reports and retrospective assessments and to assess the degrees of consistency between the two sources of information.

The sub-sample chosen for Study 3 (N = 150, including 50 randomly chosen from Group 1, 50 randomly chosen from Group 2 and 50 healthy subjects) is in line with the sample size of Merikangas and colleagues [84]. Multilevel models (MLM [85]) will be used to simultaneously evaluate within- and between-subject associations, taking into account repeated measurements. In addition, cross-lagged analyses will be carried out to examine the directionality of the measured effects. Comparisons of PA quantity variables between groups will be evaluated using linear and generalized linear models.

Discussion

The overarching focus of the DiAPAson project is to collect valid and reliable research data to suggest recommendations for improving mental health services in Italy. In particular, previous studies, everyday clinical experience, and more importantly, the perspectives of people with SSD highlight the urgency of formulating innovative intervention strategies.

Currently, research on people with SSD in the field of long-term care is lagging behind more “fashionable” areas of research in psychiatry and neuroscience. This project, in line with previous health services research conducted in Italy [43, 44], aims to shed light on some crucial clinical dimensions of SSD that have substantial translational implications. The study includes several highly innovative components and combines various types of evaluation to draw an accurate picture of daily time use and PA levels in a heterogeneous clinical population. In Italy, only a single study, with a small sample (N = 27), has been conducted with ESM on patients with severe mental disorders [86]. For this reason, the present study represents a critical innovation for mental health research. Second, no studies have ever been conducted in Italy using multi-sensors for PA in patients with SSD (or any other mental disorders), and our study methodology represents a novelty. Finally, the large sample size (N = 600) may overcome the main limitations of previous studies on daily time use.

Strengths

An in-depth overview of the daily time use in patients with SSD in RFs and outpatients

The DiAPAson project will offer a unique opportunity for an in-depth examination of the daily time use in different subgroups of people with SSD compared with healthy controls. The project will also clarify whether there is a relationship between the level of functioning of these patients and their daily time use. Moreover, it will critically and objectively assess the effect of the everyday life “setting” for patients with SSD (RFs vs community). Overall, data gathered from the DiAPAson project might be very relevant if we consider that time management is one of the more informative outcomes for patients with SSD.

Real-time exploration of daily time use, PA and mood

To the best of our knowledge, DiAPAson is the first study investigating daily time use in patients with SSD using both a retrospective assessment (diaries and TUS) and real-time momentary assessment (ESM and actigraphy). Importantly, in SSD patients, studies conducted to date have shown that even when negative symptoms are relevant, patients may be more active than it is generally thought [87, 88]. For these reasons, a real-time survey will allow us to explore multiple levels of complexity at once. Moreover, ESM guarantees the possibility of capturing individual variability (within-subject) for several types of data and not only a global overview (between-subject).

Passive monitoring of PA is another essential aspect of the project. To our knowledge, this is the first study investigating these critical aspects using ESM together with actigraphy in this specific clinical population. The only study using a similar approach was previously conducted with patients suffering from bipolar disorder [84].

A multiple-perspective approach to mental health and care services

One of the crucial aspects that the DiAPAson project focuses on is the complexity of the interactions that shape daily life in RFs. Moreover, to assess the quality of staff-patient relationships in patients living in RFs, it is essential to acknowledge not only multiple aspects of the residents but also to shed light on the staff’s general well-being. It has long been known that a staff member who is burned out and unsatisfied with work is likely to face many difficulties in dealing with patients suffering from severe, long-term mental disorders.

Limitations

The evaluation process includes many tools and will take some time to be completed, especially for the participants who will be enrolled in all three studies. Although this may lead to high refusal rates, previous experience with health services research carried out in Italy has shown that, due to the high degree of collaboration between staff and patients, refusal rates can be kept very low [43, 44, 89, 90].

The facilities participating in the study will not be randomly chosen for obvious organizational reasons and therefore might not be representative of all Italian mental health services. During data analysis, appropriate corrections will be introduced to limit possible biases.

Study status

The current protocol is updated to February 2020. Recruitment will take place from June 2020 to July 2021.

Availability of data and materials

The datasets generated and/or analysed during the current study will be available in the UniData – Bicocca Data Archive repository (https://www.unidata.unimib.it/?lang=en).

Abbreviations

DMH:

Department of Mental Health

DMHD:

Department of Mental Health and Dependence

DSM-5:

Diagnostic and Statistical Manual of Mental Disorders 5th Edition

EE:

Energy expenditure

ESM:

Experience sampling method

G1:

Group 1

G2:

Group 2

HETUS:

Harmonised European Time Use Surveys

ISTAT:

Italian National Institute of Statistics

PA:

Physical activity

RF:

Residential facility

SMD:

Severe mental disorders

SSD:

Severe Mental Disorder

TUS:

Time Use Survey

References

  1. McGrath J, Saha S, Chant D, Welham J. Schizophrenia: a concise overview of incidence, prevalence, and mortality. Epidemiol Rev. 2008;30(1):67–76.

    Article  PubMed  Google Scholar 

  2. Charlson FJ, Ferrari AJ, Santomauro DF, Diminic S, Stockings E, Scott JG, McGrath JJ, Whiteford HA. Global epidemiology and burden of schizophrenia: findings from the global burden of disease study 2016. Schizophr Bull. 2018;44(6):1195–203.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Augustine A. The confessions of St. Augustine (Bishop of Hippo), trans by Pilkington JG. Edinburgh: T. & T. Clark; 1876.

  4. Guerlac S. Thinking in time: an introduction to Henri Bergson. Ithaca: Cornell University Press; 2006.

  5. Heidegger M. Being and time, trans by Macquarrie J, Robinson E. Oxford: Blackwell Publisher Ltd; 1962.

  6. Minkowski E. Betrachtungen im Anschluss an das Prinzip des psychophysischen Parallelismus. Leipzig: Veit; 1914.

  7. Minkowski E. Le temps vécu: études phénoménologiques et psychopathologiques. Paris: J.L.L. d’Artrey; 1933.

  8. Bauman A, Bittman M, Gershuny J. A short history of time use research; implications for public health. BMC Public Health. 2019;19(2):607.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Stinson LL. Measuring how people spend their time: a time-use survey design. Monthly Lab Rev. 1999;122:12.

    Google Scholar 

  10. Fletcher AC, Nickerson P, Wright KL. Structured leisure activities in middle childhood: links to well-being. J Commun Psychol. 2003;31(6):641–59.

    Article  Google Scholar 

  11. Hodgekins J, French P, Birchwood M, Mugford M, Christopher R, Marshall M, et al. Comparing time use in individuals at different stages of psychosis and a non-clinical comparison group. Schizophr Res. 2015;161(2–3):188–93.

    Article  PubMed  Google Scholar 

  12. Cella M, Edwards C, Wykes T. A question of time: a study of time use in people with schizophrenia. Schizophr Res. 2016;176(2–3):480–4.

    Article  PubMed  Google Scholar 

  13. Cichocki L, Cechnicki A, Franczyk-Glita J, Bladzinski P, Kalisz A, Wronski K. Quality of life in a 20-year follow-up study of people suffering from schizophrenia. Compr Psychiatry. 2015;56:133–40.

    Article  PubMed  Google Scholar 

  14. Foussias G, Mann S, Zakzanis KK, van Reekum R, Agid O, Remington G. Prediction of longitudinal functional outcomes in schizophrenia: the impact of baseline motivational deficits. Schizophr Res. 2011;132(1):24–7.

    Article  CAS  PubMed  Google Scholar 

  15. Loas G, Azi A, Noisette C, Legrand A, Yon V. Fourteen-year prospective follow-up study of positive and negative symptoms in chronic schizophrenic patients dying from suicide compared to other causes of death. Psychopathology. 2009;42(3):185–9.

    Article  PubMed  Google Scholar 

  16. Aleman A, Hijman R, de Haan EH, Kahn RS. Memory impairment in schizophrenia: a meta-analysis. Am J Psychiatry. 1999;156(9):1358–66.

    CAS  PubMed  Google Scholar 

  17. Danion JM, Huron C, Vidailhet P, Berna F. Functional mechanisms of episodic memory impairment in schizophrenia. Can J Psychiatry. 2007;52(11):693–701.

    Article  PubMed  Google Scholar 

  18. Granholm E, Holden JL, Mikhael T, Link PC, Swendsen J, Depp C, et al. What do people with schizophrenia do all day? Ecological momentary assessment of real-world functioning in schizophrenia. Schizophr Bull. 2019;46:242–51.

  19. Shiffman S, Stone AA, Hufford MR. Ecological momentary assessment. Annu Rev Clin Psychol. 2008;4:1–32.

    Article  PubMed  Google Scholar 

  20. Biddle SJH, Gorely T, Marshall SJ, Cameron N. The prevalence of sedentary behavior & physical activity in leisure time: a study of Scottish adolescents using ecological momentary assessment. Prev Med. 2009;48(2):151–5.

    Article  PubMed  Google Scholar 

  21. Kanning M, Schlicht W. Be active and become happy: an ecological momentary assessment of physical activity and mood. J Sport Exerc Psychol. 2010;32(2):253–61.

    Article  PubMed  Google Scholar 

  22. Cho H, Gonzalez R, Lavaysse LM, Pence S, Fulford D, Gard DE. Do people with schizophrenia experience more negative emotion and less positive emotion in their daily lives? A meta-analysis of experience sampling studies. Schizophr Res. 2017;183:49–55.

    Article  PubMed  Google Scholar 

  23. Ben-Zeev D, Brenner CJ, Begale M, Duffecy J, Mohr DC, Mueser KT. Feasibility, acceptability, and preliminary efficacy of a smartphone intervention for schizophrenia. Schizophr Bull. 2014;40(6):1244–53.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Romanzini CLP, Romanzini M, Batista MB, Barbosa CCL, Shigaki GB, Dunton G, et al. Methodology used in ecological momentary assessment studies about sedentary behaviour in children, adolescents, and adults: systematic review using the checklist for reporting ecological momentary assessment studies. J Med Internet Res. 2019;21(5):e11967.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Westman J, Eriksson SV, Gissler M, Hällgren J, Prieto ML, Bobo WV, et al. Increased cardiovascular mortality in people with schizophrenia: a 24-year national register study. Epidemiol Psychiatr Sci. 2018;27(5):519–27.

    Article  CAS  PubMed  Google Scholar 

  26. Killaspy H, Priebe S, Bremner S, McCrone P, Dowling S, Harrison I, et al. Quality of life, autonomy, satisfaction, and costs associated with mental health supported accommodation services in England: a national survey. Lancet Psychiatry. 2016;3(12):1129–37.

    Article  PubMed  Google Scholar 

  27. Vancampfort SR, Probst M, Stubbs B. Aerobic exercise in people with schizophrenia. In: The Exercise Effect on Mental Health, Neurobiological Mechanisms. New York: Routledge; 2018.

    Google Scholar 

  28. Vancampfort D, Stubbs B, Mitchell AJ, De Hert M, Wampers M, Ward PB, et al. Risk of metabolic syndrome and its components in people with schizophrenia and related psychotic disorders, bipolar disorder and major depressive disorder: a systematic review and meta-analysis. World Psychiatry. 2015;14(3):339–47.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Firth J, Siddiqi N, Koyanagi A, Siskind D, Rosenbaum S, Galletly C, et al. The lancet psychiatry commission: a blueprint for protecting physical health in people with mental illness. Lancet Psychiatry. 2019;6(8):675–712.

    Article  PubMed  Google Scholar 

  30. Li M, Fan YL, Tang ZY, Cheng XS. Schizophrenia and risk of stroke: a meta-analysis of cohort studies. Int J Cardiol. 2014;173(3):588–90.

    Article  PubMed  Google Scholar 

  31. Laursen AH, Kristiansen OP, Marott JL, Schnohr P, Prescott E. Intensity versus duration of physical activity: implications for the metabolic syndrome. A prospective cohort study. BMJ Open. 2012;2(5):e001711.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Vancampfort D, Firth J, Schuch FB, Rosenbaum S, Mugisha J, Hallgren M, et al. Sedentary behavior and physical activity levels in people with schizophrenia, bipolar disorder and major depressive disorder: a global systematic review and meta-analysis. World Psychiatry. 2017;16(3):308–15.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Stubbs B, Firth J, Berry A, Schuch FB, Rosenbaum S, Gaughran F, et al. How much physical activity do people with schizophrenia engage in? A systematic review, comparative meta-analysis and meta-regression. Schizophr Res. 2016;176(2–3):431–40.

    Article  PubMed  Google Scholar 

  34. Warburton DE, Nicol CW, Bredin SS. Health benefits of physical activity: the evidence. CMAJ. 2006;174(6):801–9.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Firth J, Stubbs B, Rosenbaum S, Vancampfort D, Malchow B, Schuch F, et al. Aerobic exercise improves cognitive functioning in people with schizophrenia: a systematic review and meta-analysis. Schizophrenia Bull. 2017;43(3):546–56.

  36. Svatkova A, Mandl RC, Scheewe TW, Cahn W, Kahn RS, Hulshoff Pol HE. Physical exercise keeps the brain connected: biking increases white matter integrity in patients with schizophrenia and healthy controls. Schizophr Bull. 2015;41(4):869–78.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Scheewe TW, van Haren NE, Sarkisyan G, Schnack HG, Brouwer RM, de Glint M, et al. Exercise therapy, cardiorespiratory fitness and their effect on brain volumes: a randomised controlled trial in patients with schizophrenia and healthy controls. Eur Neuropsychopharmacol. 2013;23(7):675–85.

    Article  CAS  PubMed  Google Scholar 

  38. Holley J, Crone D, Tyson P, Lovell G. The effects of physical activity on psychological well-being for those with schizophrenia: a systematic review. Br J Clin Psychol. 2011;50(1):84–105.

    Article  PubMed  Google Scholar 

  39. Vera-Garcia E, Mayoral-Cleries F, Vancampfort D, Stubbs B, Cuesta-Vargas AI. A systematic review of the benefits of physical therapy within a multidisciplinary care approach for people with schizophrenia: an update. Psychiatry Res. 2015;229(3):828–39.

    Article  PubMed  Google Scholar 

  40. Dauwan M, Begemann MJ, Heringa SM, Sommer IE. Exercise improves clinical symptoms, quality of life, global functioning, and depression in schizophrenia: a systematic review and meta-analysis. Schizophrenia Bull. 2015;42(3):588–99.

  41. Biswas A, Oh PI, Faulkner GE, Bajaj RR, Silver MA, Mitchell MS, Alter DA. Sedentary time and its association with risk for disease incidence, mortality, and hospitalization in adults: a systematic review and meta-analysis. Ann Intern Med. 2015;162(2):123–32.

    Article  PubMed  Google Scholar 

  42. Rashid NAA, Nurjono M, Lee J. Clinical determinants of physical activity and sedentary behavior in individuals with schizophrenia. Asian J Psychiatr. 2019;46:62–7.

    Article  PubMed  Google Scholar 

  43. De Girolamo G, Picardi A, Santone G, Falloon I, Morosini P, Fioritti A, Micciolo R. The severely mentally ill in residential facilities: a national survey in Italy. Psychol Med. 2005;35(3):421–31.

    Article  PubMed  Google Scholar 

  44. De Girolamo G, Candini V, Buizza C, Ferrari C, Boero ME, Giobbio GM, et al. Is psychiatric residential facility discharge possible and predictable? A multivariate analytical approach applied to a prospective study in Italy. Soc Psychiatry Psychiatr Epidemiol. 2014;49(1):157–67.

    Article  PubMed  Google Scholar 

  45. De Girolamo G, Bassi M. Residential facilities as the new scenario of long-term psychiatric care. Curr Opin Psychiatry. 2004;17(4):275–81.

    Article  Google Scholar 

  46. Taylor TL, Killaspy H, Wright C, Turton P, White S, Kallert TW, et al. A systematic review of the international published literature relating to quality of institutional care for people with longer term mental health problems. BMC Psychiatry. 2009;9(1):55.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Catty J. ‘The vehicle of success’: theoretical and empirical perspectives on the therapeutic alliance in psychotherapy and psychiatry. Psychol Psychother Theory Res Pract. 2004;77(2):255–2.

    Article  Google Scholar 

  48. McCabe R, Priebe S. The therapeutic relationship in the treatment of severe mental illness: a review of methods and findings. Int J Soc Psychiatry. 2004;50(2):115–28.

    Article  PubMed  Google Scholar 

  49. Bordin ES. The generalizability of the psychoanalytic concept of the working alliance. Psychotherapy. 1979;16(3):252.

    Article  Google Scholar 

  50. Lim SO, Kim HH. The moderating effects of professional identity on the relationship between job stress and burnout of care workers from care facilities. J Korean Soc Welfare Admin. 2011;13(3):151–76.

    Google Scholar 

  51. O’Connor K, Neff DM, Pitman S. Burnout in mental health professionals: a systematic review and meta-analysis of prevalence and determinants. European Psychiatry. 2018;53:74–99.

    Article  PubMed  Google Scholar 

  52. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 5th ed. Washington, DC: Author; 2013.

    Book  Google Scholar 

  53. Cockrell JR, Folstein MF. Mini-mental state examination. In: Copeland JRM, Abou-Saleh MT, Blazer DG, editors. Principle and Practice of Geriatric Psychiatry. Chichester: Wiley; 2002. p. 140–1.

  54. Measso G, Cavarzeran F, Zappala G, Lebowitz BD, Crook TH, Pirozzolo FJ, et al. The mini-mental state examination: normative study of an Italian random sample. Dev Neuropsychol. 1993;9(2):77–85.

    Article  Google Scholar 

  55. Overall JE, Gorham DR. The brief psychiatric rating scale. Psychol Rep. 1962;10(3):799–812.

    Article  Google Scholar 

  56. Morosini PL, Casacchia M. Traduzione italiana della Brief Psychiatric Rating Scale, versione 4.0 ampliata (BPRS 4.0). Rivista di Riabilitazione Psichiatrica e Psicosociale. 1995;3:199–228.

    Google Scholar 

  57. Strauss GP, Keller WR, Buchanan RW, Gold JM, Fischer BA, McMahon RP, et al. Next-generation negative symptom assessment for clinical trials: validation of the brief negative symptom scale. Schizophr Res. 2012;142(1–3):88–92.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Mucci A, Galderisi S, Merlotti E, Rossi A, Rocca P, Bucci P, et al. The brief negative symptom scale (BNSS): independent validation in a large sample of Italian patients with schizophrenia. European Psychiatry. 2015;30(5):641–7.

    Article  CAS  PubMed  Google Scholar 

  59. Schneider LC, Struening EL. SLOF: a behavioural rating scale for assessing the mentally ill. Soc Work Res Abstr. 1983;19(3):9–21 Oxford University press.

    Article  CAS  PubMed  Google Scholar 

  60. Mucci A, Rucci P, Rocca P, Bucci P, Gibertoni D, Merlotti E, et al. The specific level of functioning scale: construct validity, internal consistency and factor structure in a large Italian sample of people with schizophrenia living in the community. Schizophr Res. 2014;159(1):144–50.

    Article  PubMed  Google Scholar 

  61. Whoqol Group. Development of the World Health Organization WHOQOL-BREF quality of life assessment. Psychol Med. 1998;28(3):551–8.

    Article  Google Scholar 

  62. De Girolamo G, Rucci P, Scocco P, Becchi A, Coppa F, D’Addario A, et al. Quality of life assessment: validation of the Italian version of the WHOQOL-brief. Epidemiol Psychiatr Sci. 2000;9(1):45–55.

    Article  Google Scholar 

  63. Gold LH. DSM-5 and the assessment of functioning: the World Health Organization disability assessment schedule 2.0 (WHODAS 2.0). J Am Acad Psychiatry Law. 2014;42(2):173–81.

    PubMed  Google Scholar 

  64. Federici S, Meloni F, Mancini A, Lauriola M, Olivetti Belardinelli M. World Health Organisation disability assessment schedule II: contribution to the Italian validation. Disabil Rehabil. 2009;31(7):553–64.

    Article  PubMed  Google Scholar 

  65. Zimbardo PG, Boyd JN. Putting time in perspective: a valid, reliable individual-differences metric. In: In time perspective theory; review, research and application. Cham: Springer; 2015. p. 17–55.

    Google Scholar 

  66. Laghi F, Baiocco R, D’Alessio M, Gurrieri G. Suicidal ideation and time perspective in high school students. European Psychiatry. 2009;24(1):41–6.

    Article  PubMed  Google Scholar 

  67. Caprara GV, Alessandri G, Eisenberg N, Kupfer A, Steca P, Caprara MG, et al. The positivity scale. Psychol Assess. 2012;24(3):701–12.

    Article  PubMed  Google Scholar 

  68. Harms T, Gershuny J, Doherty A, et al. A validation study of the Eurostat harmonised European time use study (HETUS) diary using wearable technology. BMC Public Health. 2019;19:455.

    Article  PubMed  PubMed Central  Google Scholar 

  69. Ruggeri M, Dall’Agnola R. The development and use of the Verona expectations for care scale (VECS) and the Verona service satisfaction scale (VSSS) for measuring expectations and satisfaction with community-based psychiatric services in patients, relatives and professionals. Psychol Med. 1993;23(2):511–23.

    Article  CAS  PubMed  Google Scholar 

  70. Hatcher RL, Gillaspy JA. Development and validation of a revised short version of the working Alliance inventory. Psychother Res. 2006;16(1):12–25.

    Article  Google Scholar 

  71. Lo Coco G, Gullo S, Prestano C, Gelso CJ. Relation of the real relationship and the working alliance to the outcome of brief psychotherapy. Psychotherapy. 2011;48(4):359.

    Article  Google Scholar 

  72. Phelan M, Slade M, Thornicroft G, Dunn G, Holloway F, Wykes T, et al. The Camberwell assessment of need: the validity and reliability of an instrument to assess the needs of people with severe mental illness. Br J Psychiatry. 1995;167(5):589–95.

    Article  CAS  PubMed  Google Scholar 

  73. Ruggeri M, Lasalvia A, Nicolaou S, Tansella M. The Italian version of the Camberwell assessment of need (CAN), an interview for the identification of needs of care. Epidemiol Psychiatr Sci. 1999;8(2):135–9.

    Article  CAS  Google Scholar 

  74. Moos RH, Houts PS. Assessment of the social atmospheres of psychiatric wards. J Abnorm Psychol. 1968;73(6):595.

    Article  CAS  PubMed  Google Scholar 

  75. Burti L, Glick ID, Tansella M. Measuring the treatment environment of a psychiatric ward and a community mental health center after the Italian reform. Community Ment Health J. 1990;26(2):193–204.

    Article  CAS  PubMed  Google Scholar 

  76. Goldberg DP, Blackwell B. Psychiatric illness in general practice: a detailed study using a new method of case identification. Br Med J. 1970;1:439–43.

    Article  CAS  PubMed  Google Scholar 

  77. Fontanesi F, Gobetti C, Zimmermann-Tansella C, Tansella M. Validation of the Italian version of the GHQ in a general practice setting. Psychol Med. 1985;15(2):411–5.

    Article  CAS  PubMed  Google Scholar 

  78. Maslach C, Jackson SE. The Maslach burnout inventory: manual. Palo Alto: Consulting psychologists Press; 1981.

  79. Sirigatti S, Stefanile C, Menoni E. Per un adattamento italiano del Maslach burnout inventory (MBI). Bollettino di Psicologia Applicata. 1988;187(188):33–9.

    Google Scholar 

  80. Killaspy H, White S, Dowling S, Krotofil J, McPherson P, Sandhu S, et al. Adaptation of the quality Indicator for rehabilitative care (QuIRC) for use in mental health supported accommodation services (QuIRC-SA). BMC Psychiatry. 2016;16(1):101.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  81. Jakicic JM, Marcus M, Gallagher KI, Randall COLBY, Thomas E, Goss FL, Robertson RJ. Evaluation of the SenseWear pro armband™ to assess energy expenditure during exercise. Med Sci Sports Exerc. 2004;36(5):897–904.

    Article  PubMed  Google Scholar 

  82. Fruin ML, Rankin JW. Validity of a multi-sensor armband in estimating rest and exercise energy expenditure. Med Sci Sports Exerc. 2004;36(6):1063–9.

    Article  PubMed  Google Scholar 

  83. Killaspy H, White S, Wright C, Taylor TL, Turton P, Kallert T, et al. Quality of longer term mental health facilities in Europe: validation of the quality indicator for rehabilitative care against service users’ views. PLoS One. 2012;7(6):e38070.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Merikangas KR, Swendsen J, Hickie IB, Cui L, Shou H, Merikangas AK, et al. Real-time mobile monitoring of the dynamic associations among motor activity, energy, mood, and sleep in adults with bipolar disorder. JAMA Psychiatry. 2019;76(2):190–8.

    Article  PubMed  Google Scholar 

  85. Finch WH, Bolin JE, Kelley K. Multilevel modeling using R. New York: CRC Press; 2019.

  86. Bassi M, Ferrario N, Ba G, Delle Fave A, Viganò C. Quality of experience during psychosocial rehabilitation: a real-time investigation with experience sampling method. Psychiatr Rehabil J. 2012;35(6):447.

    Article  PubMed  Google Scholar 

  87. Myin-Germeys I, Delespaul PA, DeVries MW. Schizophrenia patients are more emotionally active than is assumed based on their behavior. Schizophr Bull. 2000;26(4):847–54.

    Article  CAS  PubMed  Google Scholar 

  88. Myin-Germeys I, Birchwood M, Kwapil T. From environment to therapy in psychosis: a real-world momentary assessment approach. Schizophr Bull. 2011;37(2):244–7.

    Article  PubMed  PubMed Central  Google Scholar 

  89. De Girolamo G, Carrà G, Fangerau H, Ferrari C, Gosek P, Heitzman J, et al. European violence risk and mental disorders (EU-VIORMED): a multi-Centre prospective cohort study protocol. BMC Psychiatry. 2019;19(1):1–13.

    Article  Google Scholar 

  90. Bottesi G, Candini V, Ghisi M, Bava M, Bianconi G, Bulgari V, et al. Personality, schizophrenia, and violence: a longitudinal study: the second wave of the VIORMED Project. J Pers Disord. 2019;14:1–19.

Download references

Acknowledgements

The authors wish to thank the Vodafone Foundation Italy for providing 10 smartphones free of charge for the ESM part of the project. This paper is dedicated to Dr. Metello Corulli, for many years Director of the RF “Il Porto Onlus” in Turin: Metello had the initial idea of a collaborative study involving RFs in Italy, and his suggestions led to the development and submission of this project to the Ministry of Health. He passed away only a few weeks before the approval of the project. Thanks are due to Dr. Gilberto Di Petta for his suggestion and to Dr. Tania Cappadozzi, ISTAT, Rome, for her invaluable support with the ISTAT survey of daily time use, to Drs. Camilla Giugni, Giacomo Goglia, Giulio Sbravati and Laura Zagarese for their help in project planning and coordination.

Thanks are due to the large number of colleagues in all Italy who have expressed interest in the project and have agreed to participate, listed below by alphabetical order of the location:

DMH ASL Ancona (Massimo Mari, Stefania Impicci); RF Passaggi Srl-Oricola, Aquila Annalisa Maurizi (Alessandro Bellotta, Filippo Jacoponi, Annalisa Maurizi); DMH ULSS 8 Berica, Arzignano, Vicenza (Stefano Zanolini), DMH ASL Bari (Domenico Semisa, Valeria Latorre, Gaetano Nappi); DMHD ASST Bergamo Ovest (Emiliano Monzani); DMHA ASST Spedali Civili Brescia (Antonio Vita, Stefano Barlati); Fatebenefratelli Sant’Ambrogio, Cernusco sul Naviglio, Milano (Gian Marco Giobbio); DMHD ASST Cremona (Franco Spinogatti); DMHD ASST Rhodense Garbagnate, Milano (Marco Toscano); DMHD ASL 3 Genova (Marco Vaggi, Lucio Ghio); RF CREST ‘La Perla’, Grumello del Monte, Bergamo (Salvatore Zizolfi); DMHD ASST Lodi (Giancarlo Cerveri); RF Centro Ippocrate CRA Macchiareddu, Cagliari (Benedetto Piccicacchi, Carmela Schiavo); DMHD ASST Melegnano and Martesana, Milano (Federico Durbano); RF Fondazione Castellini ONLUS, Melegnano, Milano (Rosangela Scioli); RF Associazione Il Porto ONLUS, Moncalieri, Torino (Patrizia Giannini); DMHD ASST Monza (Massimo Clerici); DMH Napoli 2 Nord (Angelo Cuciniello); RF Fondazione Giuseppe Costantino, Pavia (Marina Marina); DMH ASL Pescara (Vittorio Di Michele); DMHD AUSL Parma (Giuseppina Paulillo); DMH USL Toscana Centro, Prato (Giuseppe Cardamone, Tommaso Vannucchi); DMH ASL Roma1 (Giuseppe Ducci, Antonio Maone); Fatebenefratelli Beata Vergine Consolata, San Maurizio Canavese, Torino (Fabio De Dominicis, Maria Elena Boero); DMH ASL Teramo (Patricia Giosuè); DMH ASL Torino 5 (Giorgio D’Allio); DMH ASL Città di Torino (Giorgio Gallino); RF Progetto Du Parc, Torino (Jessica Orticola, Nicolò Rossetto); DMH APSS Trento Centro di Rovereto (Marco Goglio, Fabio Lucchi); DMH ULSS 2 Marca Trevigiana and Consorzio Restituire scs, Treviso (Angelo Brega); RF Le Vele ONLUS ‘Villa Gatta’, Trezzo sull’Adda, Milano (Alessandra Pozzi, Marinella Roncalli); DMH ASUITS Trieste (Elisabetta Pascolo Federici, Arturo Rippa); RF Le Vele ONLUS La Nostra Locanda, Vaprio d’Adda, Milano (Laura Colasuonno); DMH AOUI Verona (Alessandra Martinelli, Mirella Ruggeri); RF CTRP Associazione Don Giuseppe Girelli, Verona (Tiziana Signoretti); RF CREST, Vinago, Varese (Carlo M. Dentali, Martina Minotto).

An updated list of participating sites can be found at https://www.diapason-study.eu/.

Funding

The DiAPAson project is entirely funded by the Italian Ministry of Health (Bando per la ricerca Finalizzata 2018: RF-2018-12365514). The Ministry of Health organized the peer review of the study protocol to grant approval. The Ministry of Health has no role in the analyses and interpretation of study findings.

Author information

Authors and Affiliations

  1. Unit of Epidemiological and Evaluation Psychiatry, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy

    Giovanni de Girolamo & Ilaria Maria Antonietta Benzi

  2. Department of Mental Health and Dependence, ASST of Pavia, Pavia, Italy

    Matteo Rocchetti & Letizia Casiraghi

  3. Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy

    Matteo Rocchetti & Letizia Casiraghi

  4. Department of Mental Health and Dependence, AUSL of Modena, Modena, Italy

    Sara Agosta & Fabrizio Starace

  5. Service of Statistics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy

    Clarissa Ferrari & Ambra Macis

  6. Department of Information Engineering, University of Brescia, Brescia, Italy

    Nicola De Franceschi

  7. Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy

    Silvia Pogliaghi

Authors
  1. Giovanni de Girolamo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Matteo Rocchetti
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ilaria Maria Antonietta Benzi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sara Agosta
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Letizia Casiraghi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Clarissa Ferrari
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Nicola De Franceschi
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ambra Macis
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Silvia Pogliaghi
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Fabrizio Starace
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

GDG is the PI of the project; he conceived the project and is responsible for its realization. GDG, together with FS and MR, designed the study protocol. IMAB, LC and SA contributed to the drafting, revising and finalizing of the manuscript. NDF developed the project database and DiAPAson app. CF calculated the sample size and wrote the statistical sections. All authors contributed to scientific discussion providing critical feedback. All authors contributed to the refinement of the study protocol and approved the final manuscript.

Corresponding author

Correspondence to Giovanni de Girolamo.

Ethics declarations

Ethics approval and consent to participate

The study has been approved by the ethical committees (Ecs) of the three main participating centres: EC of IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (31/07/2019; no. 211/2019), EC of Area Vasta Emilia Nord (25/09/2019; no. 0025975/19), and EC of Pavia (02/09/2019, no. 20190075685). The research team will obtain oral and written informed consent to participate in the study from all participants before enrolment. All changes to this protocol will be sent for approval to the Ethical Committee of the IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (Brescia, Italy) and to the Ecs of the other participating centres.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

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

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

de Girolamo, G., Rocchetti, M., Benzi, I.M.A. et al. DAily time use, Physical Activity, quality of care and interpersonal relationships in patients with Schizophrenia spectrum disorders (DiAPASon): an Italian multicentre study. BMC Psychiatry 20, 287 (2020). https://doi.org/10.1186/s12888-020-02588-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12888-020-02588-y

Keywords

BMC Psychiatry

ISSN: 1471-244X

Contact us