Introduction
The concept of mental health need has been suggested as a vital paradigm in planning mental health service interventions (Lasalvia et al., Reference Lasalvia, Ruggeri, Mazzi and Dall'Agnola2000) because it has direct treatment implications. Different definitions of mental health need have been suggested (Ruggeri et al., Reference Ruggeri, Leese, Slade, Bonizzato, Fontecedro and Tansella2004), such as the public mental health need, assessed to provide services, programmes and staff to address this need, or the need for treatment of patients in specific mental health settings (e.g. a patient discharged from a psychiatric hospitalisation or receiving community psychiatric treatment). Furthermore, different assessment tools have been developed (Lasalvia et al., Reference Lasalvia, Bonetto, Salvi, Bissoli, Tansella and Ruggeri2007; Campion et al., Reference Campion, Coombes and Bhaduri2017; Mazzaia, Reference Mazzaia2018; Norman et al., Reference Norman, McDonald, Schneider, Malinovsky, Goldmann, Blauschild and Driver2018; Reisinger et al., Reference Reisinger, Moore, Tapscott, Alperin, Cumming and Druss2021). In this study, we focus on the ‘need for care’, which indicates a perceived problem in a health or social domain of life (Ruggeri et al., Reference Ruggeri, Leese, Slade, Bonizzato, Fontecedro and Tansella2004), as assessed by staff and patients with schizophrenia spectrum disorder (SSD) using the Camberwell Assessment of Need (CAN) to investigate a comprehensive range of health and social needs (Wennström and Wiesel, Reference Wennström and Wiesel2006).
A growing body of evidence has shown that mental health professionals and users may have different perceptions of needs for care (Slade et al., Reference Slade, Phelan and Thornicroft1998; Brunt and Hansson, Reference Brunt and Hansson2002; Ochoa et al., Reference Ochoa, Haro, Autonell, Pendàs, Teba and Màrquez2003). Patients and staff may disagree on both the presence of a need for care and on whether a need has or has not been met (Lasalvia et al., Reference Lasalvia, Ruggeri, Mazzi and Dall'Agnola2000; Cleary et al., Reference Cleary, Hunt, Walter and Freeman2006; Grinshpoon et al., Reference Grinshpoon, Friger, Orev, Shvarts, Kaplan, Abramowitz and Ponizovsky2008; Wiersma et al., Reference Wiersma, van den Brink, Wolters, McCabe, Bullenkamp, Hansson, Lauber, Martinez-Leal, Rössler, Salize, Björkman, Torres-Gonzales, Wright and Priebe2009; Eklund and Ostman, Reference Eklund and Ostman2010; de Girolamo et al., Reference de Girolamo, Rocchetti, Benzi, Agosta, Casiraghi, Ferrari, De Franceschi, Macis, Pogliaghi and Starace2020). The disagreement between patients and professionals is a critical issue for service delivery, and any effort should be made to improve strategies aimed at increasing consensus between staff and patients, as a better staff–patient agreement may help improve treatment outcomes (Lasalvia et al., Reference Lasalvia, Bonetto, Tansella, Stefani and Ruggeri2008).
Several studies have found an association between higher needs for care and specific sociodemographic variables, such as having a disability with severe symptomatology and low social functioning (Ruggeri et al., Reference Ruggeri, Leese, Slade, Bonizzato, Fontecedro and Tansella2004). Moreover, needs for care are a better predictor of quality of life than clinical or sociodemographic variables, and are associated with patient-reported satisfaction with care (Ådnanes et al., Reference Ådnanes, Kalseth, Ose, Ruud, Rugkåsa and Puntis2019).
The Experience Sampling Method (ESM) tracks experiences in the real world and real-time (Granholm et al., Reference Granholm, Loh and Swendsen2008; Wee et al., Reference Wee, Yong, Chew, Guan, Lee and Sim2019; Myin-Germeys and Kuppens, Reference Myin-Germeys and Kuppens2022) using self-reports to capture momentary experiences and their context. To date, several studies have used ESM in patients with SSD to evaluate daily mood or symptomatology (Myin-Germeys et al., Reference Myin-Germeys, van Os, Schwartz, Stone and Delespaul2001; Cho et al., Reference Cho, Gonzalez, Lavaysse, Pence, Fulford and Gard2017; Granholm et al., Reference Granholm, Holden, Mikhael, Link, Swendsen, Depp, Moore and Harvey2020); however, very few have used this methodology for assessing daily life activities of people with SSD (van Os et al., Reference van Os, Lataster, Delespaul, Wichers and Myin-Germeys2014; Kluge et al., Reference Kluge, Kirschner, Hager, Bischofm, Habermeyer, Seifritz, Walther and Kaiser2018; Granholm et al., Reference Granholm, Holden, Mikhael, Link, Swendsen, Depp, Moore and Harvey2020; Culbreth et al., Reference Culbreth, Barch and Moran2021). To the best of our knowledge, only van Os et al. (Reference van Os, Lataster, Delespaul, Wichers and Myin-Germeys2014) have explicitly examined the association between needs for care evaluated via CAN and ecological indices monitored using the ESM in individuals with psychosis (Janney et al., Reference Janney, Ganguli, Richardson, Holleman, Tang, Cauley and Kriska2013; van Os et al., Reference van Os, Lataster, Delespaul, Wichers and Myin-Germeys2014). They found an association between psychotic experiences and unmet needs moderated by negative affect (higher levels increased the number of unmet needs), positive affect (higher levels decreased the number of unmet needs) and environmental stress associated with events and activities (higher levels increased the number of unmet needs).
Community care in Italy is organised through 127 Departments of Mental Health that provide direct outpatient, hospital and residential care. In addition, many residential facilities (RFs) are managed by private (both non-profit and for-profit) organisations. All patients treated in private RFs are fully covered by the National Health Service for their stay and care. Previous studies have thoroughly assessed the residential care system (de Girolamo et al., Reference de Girolamo, Picardi, Micciolo, Falloon, Fioritti and Morosini2002, Reference de Girolamo, Picardi, Santone, Falloon, Morosini, Fioritti and Micciolo2005; Santone et al., Reference Santone, de Girolamo, Falloon, Fioritti, Micciolo, Picardi and Zanalda2005; Picardi et al., Reference Picardi, Lega, Candini, Dagani, Iozzino and de Girolamo2014).
RFs in Italy admit patients with SSD who have increased needs for care, severe psychopathology and low functioning (de Girolamo et al., Reference de Girolamo, Picardi, Micciolo, Falloon, Fioritti and Morosini2002; Ministero Italiano della Salute, 2013; Martinelli et al., Reference Martinelli, Iozzino, Pozzan, Cristofalo, Bonetto and Ruggeri2022a, Reference Martinelli, Killaspy, Zarbo, Agosta, Casiraghi, Zamparini, Starace, Rocchetti, de Girolamo, Ruggeri, Barlati, Boero, Cerveri, Clerici, D'Anna, De Novellis, Di Michele, Di Prisco, Durbano, Facchini, Ghio, Giosuè, Greco, Latorre, Leuci, Maone, Marina, Maurizi, Monzani, Placenti, Rancati, Rippa, Rovera, Silva, Tura and Zanolini2022b), and who would have been hospitalised for a long time in a psychiatric hospital before de-institutionalisation (de Girolamo et al., Reference de Girolamo, Picardi, Micciolo, Falloon, Fioritti and Morosini2002; Thornicroft and Tansella, Reference Thornicroft and Tansella2004; McPhearson et al., Reference McPhearson, Krotofil and Killaspy2018). RFs represent a fundamental component of long-term care and aim to support users in learning or relearning daily living skills and gaining confidence to achieve social inclusion, independent living and personal recovery (UN General Assembly, 2006; Priebe et al., Reference Priebe, Saidi, Want, Mangalore and Knapp2009; Martinelli and Ruggeri, Reference Martinelli and Ruggeri2020a; Raugh et al., Reference Raugh, James, Gonzalez, Chapman, Cohen, Kirkpatrick and Strauss2021), and to cover all adult roles (Ruggeri et al., Reference Ruggeri, Leese, Slade, Bonizzato, Fontecedro and Tansella2004; Kimhy et al., Reference Kimhy, Vakhrusheva, Liu and Wang2014; McPhearson et al., Reference McPhearson, Krotofil and Killaspy2018).
Despite the importance of RFs in Italian community mental health care after the early reform of psychiatric hospitals (Basaglia, Reference Basaglia1968; Becker and Fangerau, Reference Becker and Fangerau2018), they have not been surveyed for approximately 20 years (Culbreth et al., Reference Culbreth, Barch and Moran2021). Furthermore, indeed the mission of Italian RFs to implement strategies aimed at developing rehabilitation activities oriented to the personal recovery ethos in order to increase personal daily life skills and well-being, and based on the real needs for care of residents (Junghan et al., Reference Junghan, Leese, Priebe and Slade2007; Grinshpoon et al., Reference Grinshpoon, Friger, Orev, Shvarts, Kaplan, Abramowitz and Ponizovsky2008; Killaspy, Reference Killaspy2016), no studies have investigated the association between needs for care and daily life activities in a sample of residents with SSD, in detail, using the ESM.
In the current study, we aimed to assess the needs for care as perceived by residents with SSDs and their key professionals, evaluate the agreement between users and staff perceptions of unmet needs, and identify sociodemographic and clinical predictors of unmet needs. Moreover, we aimed to address the gap in the literature by identifying unmet need predictors of daily activities and momentary mood as assessed using the ESM and investigating the interaction between symptomatology, momentary mood and unmet needs for care.
Materials and methods
This study is part of the national project ‘DAily time use, Physical Activity, quality of care and interpersonal relationships in patients with Schizophrenia spectrum disorders (DIAPASON)’ (de Girolamo et al., Reference de Girolamo, Rocchetti, Benzi, Agosta, Casiraghi, Ferrari, De Franceschi, Macis, Pogliaghi and Starace2020).
The DIAPASON project included 20 Departments of Mental Health and 17 private RFs in different Italian regions.
The inclusion criteria were: age between 20 and 55 years old, a DSM-5 diagnosis of SSD (American Psychiatric Association, 2013) and speaking and writing in the Italian language to participate adequately in a research interview. The exclusion criteria were: severe cognitive deficits (i.e. a Mini-Mental State Examination corrected score of <24), inability to provide informed consent, a recent (last 6 months) DSM-5 diagnosis of substance use disorder (American Psychiatric Association, 2013), a cerebrovascular/neurological disease and a history of clinically significant head injury.
In the participating RFs, the facility chiefs prepared an alphabetical list of patients with SSD on an index day, and based on this list, residents were consecutively invited to participate in the study until the recruitment target was achieved. From October 2020 to October 2021, 340 residents with SSD were recruited from 98 (public and private) RFs across Italy (12.8 ± 5.7 residents). Six patients (1.8%) were excluded due to severe cognitive deficits, and 21 (6.2%) dropped out after providing informed consent. A total of 313 patients were included in this study. Each RF recruited a mean of 3.5 (± 2.6) residents. Therefore, based on the total number of occupied beds, we recruited approximately 27% of the patients from each participating RF. The sample size calculation is described in detail in the study protocol (de Girolamo et al., Reference de Girolamo, Rocchetti, Benzi, Agosta, Casiraghi, Ferrari, De Franceschi, Macis, Pogliaghi and Starace2020).
Due to logistic and financial limitations, the ecological ESM study was possible only in a sub-sample of RFs (N = 30); in these RFs, 56 (17.9%) residents were assessed using the ESM.
Assessment of needs for care
Needs for care were assessed using the Italian version of the CAN (Phelan et al., Reference Phelan, Slade, Thornicroft, Dunn, Holloway, Wykes, Strathdee, Loftus, McCrone and Hayward1995; Ruggeri et al., Reference Ruggeri, Lasalvia, Nicolaou and Tansella1999), an interview developed for patients (CAN-P) and staff (CAN-S), comprising 22 items divided into five domains: health (physical health, psychotic symptoms, drugs, alcohol, safety to self, safety to others and psychological distress), basic (accommodation, food and daytime activities), social (sexual expression, social networks and intimate relationships), service (information, telephone, transport and benefits) and functioning (basic education, money, childcare, self-care and looking after the room). Each item was assessed on a three-point scale with 0 = no problem, 1 = no/moderate problem because of interventions (met need), and 2 = current serious problem (unmet need).
Users and their corresponding key professionals completed the two CAN versions in separate interviews.
Assessment of the severity of symptomatology
The 24-item Brief Psychiatric Rating Scale (BPRS) (Overall and Gorham, Reference Overall and Gorham1962; Morosini and Casacchia, Reference Morosini and Casacchia1995) was used to assess symptom severity. The BPRS items were rated on a seven-point Likert scale ranging from 1 (no symptoms) to 7 (extremely severe symptoms) and divided into five categories (depression/anxiety, excitement, positive symptoms, negative symptoms and cognitive symptoms). The Brief Negative Symptom Scale (BNSS) (Strauss et al., Reference Strauss, Keller, Buchanan, Gold, Fischer, McMahon, Catalano, Culbreth, Carpenter and Kirkpatrick2012; Mucci et al., Reference Mucci, Galderisi, Merlotti, Rossi, Rocca, Bucci, Piegari, Chieffi, Vignapiano and Maj2015) was used to assess the severity of negative symptoms. The BNSS items were rated on a six-point Likert scale ranging from 0 (no symptoms) to 6 (severe symptoms), and they evaluated blunted affect, alogia, asociality, anhedonia and avolition. For both the BPRS and BNSS, higher total mean scores indicated more severe symptomatology.
Assessment of daily time use and emotions
Daily time use (i.e. daily activities) and emotions were assessed using a questionnaire on a smartphone-based application for ESM, developed ad hoc for the project (see the mobile application for ESM in online Supplementary materials). The mobile application comprised three sections: current activities, social contacts and mood. The first section asked, ‘What are you doing right now’? The participants could choose one or more of the following activity categories: sleeping; staying sick in bed; eating/self-care working; studying, doing housework; taking care of someone or something; voluntary working; doing leisure activities, thinking, resting, or doing nothing, performing sports or physical activity; getting around watching television or listening to the radio; and participating in religious activities (see list of daily activities in the online Supplementary Table 1).
The second section asked, ‘Who are you with right now’? and the participants could choose ‘alone’ or ‘with other people’. The third section showed seven mood conditions (happy, sad, tired, relaxed, nervous, quiet and full of energy) and asked the participants how they felt at that moment. The participants had to push on the screen and select the measure of that mood on a bar from 0 (not at all) to 100 (a lot).
Notifications appeared eight times a day, from 8:00 a.m. to 12:00 p.m., for 7 consecutive days. The notifications were semi-randomised (i.e. randomly sent within the scheduled time slots) in the following time slots: 8–10 a.m., 10 a.m.–12 p.m., 12 p.m.–2 p.m., 2–4 p.m., 4–6 p.m., 6–8 p.m., 8–10 p.m., 10 p.m.–12 a.m. A reminder notification appeared after 15 min. The participants had a maximum of 30 min to reply.
Statistical analysis
Data were analysed using SAS, SPSS and R (R Core Team, 2013; SAS Institute Inc, 2013; IBM Corp. Released, 2020). Descriptive statistics comprised frequency tables for categorical variables and mean (standard deviation [SD]) for continuous variables. We tested the hypothesis of normality of continuous variables using the Kolmogorov–Smirnov test. To assess differences between matched user-rated and staff-rated needs for care, we used Wilcoxon's signed-rank test (because the variables were not normally distributed).
In addition to the number of needs (total, met and unmet), the met/unmet ratio was computed. Focusing only on unmet needs, we investigated the agreement between CAN-P and CAN-S on the total, domains and items using Cohen's k coefficient. According to Landis and Koch, the agreement is poor with k < 0.00, slight with k = 0.00–0.20, fair with k = 0.21–0.40, moderate with k = 0.41–0.60, substantial with k = 0.61–0.80 and almost perfect with k = 0.81–1.00 (McHugh, Reference McHugh2012).
To understand if the number of unmet needs (total and domains) could be associated with daily activities, we used generalised linear models (GLM) adjusted for age, sex and the BPRS total score.
With an additional statistical model, we tested the interaction between mood ratings collected through the ESM (momentary negative and positive mood considered as independent variables), the level of symptomatology severity (assessed through the BPRS, considered as a moderator) and unmet needs (both user-rated and staff-rated, considered as dependent variables).
To understand which clinical and/or sociodemographic factors could be associated with the difference between the unmet needs rated by the staff and users, we used GLM. Finally, as an external validation of our sample, we compared (through confidence intervals) the recorded percentages of unmet needs with those reported in similar previous studies (see online Supplementary Tables 2 and 3).
Results
Sociodemographic characteristics of the residents
As shown in Table 1, the users had a mean age of 41.0 years (s.d. = 9.7), and most users were males (70.3%), single (86.9%) and unemployed (83.3%). The mean length of mental disorder was 18.3 years (s.d. = 9.6), and they mostly had spent more than 5 years in the RF (43.9%).
a ‘Working’ includes ‘full-time or part-time job in a protected environment’ and ‘protected environment job’. ‘Studying’ includes ‘job training course’, ‘student’. ‘Not working’ includes ‘housemaker’, ‘unemployed or looking for their first job’ and ‘retired who does not carry out any remuneration activity’ (including those who benefit from the invalidity pension).
Most patients' family/friends were available but not actively supportive (42.9%). Most users actively sought treatment (42%) or wanted to be helped but lacked motivation (33.3%). A few users (9.6%) performed no activities in the RFs, while the main activities performed were housekeeping (63.5%) and cleaning up (12.3%). The severity of symptomatology was mild (BPRS, mean total score 2.1 [range: 1–7; s.d. = 0.7] and BNSS, mean total score 2.0 [range: 0–6; s.d. = 1.3]) (Table 1).
Differences in total, met and unmet needs between users and staff
The staff reported a significantly higher number of needs for care (p < 0.001) and met needs (p < 0.001) than users in all domains, except socially met needs (p = 0.138). Both the users and staff found the highest number of needs for care in health (users: 1.7; s.d. = 1.2 v. staff: 2.6; s.d. = 1.3) and the lowest in service (users: 0.9; s.d. = 0.9 v. staff: 1.0; s.d. = 1.0) (Table 2).
Scoring of CAN items: 0 = no problem, 1 = no/moderate problem because of continuing interventions (met need) and 2 = current serious problem whether or not help is offered or given (unmet needs ratio ⩾ 1 indicates a proportion between met and unmet needs in favour of met needs). Bold values denote statistical significance at the p < 0.05 level.
The overall ratio was similar between the two groups (total: users 2.2 v. staff 2.3). The highest differences in the ratio among the users and staff were found in basic (ratio: users 5.0 v. staff 2.5) and functioning (ratio: users 5.0 v. staff 3.2) needs (Table 2).
Percentage of agreement on unmet needs between users and staff
Of the 313 user–staff pairs included in the analyses, 175 (55.9%) of the user–staff pairs reported unmet needs (Table 3). The highest number of unmet needs was reported by the staff and users in social (98; 31.3) needs, while the lowest was in functioning needs for users (55; 17.6) and service needs for the staff (68; 21.7) (Table 3).
We did not find any substantial or almost perfect agreement on unmet needs between staff and users. The highest agreement was moderate for accommodation (k = 0.484), food (k = 0.406), childcare (k = 0.530), physical health (k = 0.470), telephone (k = 0.458) and transportation (k = 0.425). A slight agreement was found in self-care (k = 0.106), where mental health professionals rated lower than patients, and information (k = 0.100), where mental health professionals rated higher than patients. A fair agreement was found for the other CAN items (Table 3).
Predictors of differences of unmet needs between users and staff
As shown in online Supplementary Table 3, negative associations were found between the following variables: social unmet needs and age (older age decreased the number of unmet needs) (β = −0.15; p < 0.01), length of mental health disorder (longer diagnosis of SSD decreased the number of unmet needs) (β = −0.16; p < 0.01), functioning unmet needs and collaboration skills (higher collaboration decreased the number of unmet needs) (β = −0.16; p < 0.01), BPRS (lower symptomatology decreased the number of unmet needs) (β = −0.17; p < 0.01), total unmet needs and collaboration skills (higher collaboration decreased the number of unmet needs) (β = −0.12; p < 0.05) and BPRS (shorter symptomatology decreased the number of unmet needs) (β = −0.16; p < 0.01).
Positive associations were found between unmet health needs and sex (being a female increased the number of unmet needs) (β = 0.27; p < 0.05), social unmet needs and length of stay in the RF (shorter length of stay in the RF increased the number of unmet needs), particularly when the length of stay was <1 year (β = 0.54; p < 0.001) and between 1 and 5 years (β = 0.36; p < 0.1) (online Supplementary Table 4).
User-rated and staff-rated unmet need predictors of activities and momentary mood as measured using the ESM
As shown in Table 4, among the predictors, negative associations were similarly found in users and staff between leisure activities and health (users: β = −0.22; p < 0.05 v. staff: β = −0.33; p < 0.05) and total unmet needs (users: β = −0.29; p < 0.05 v. staff: β = −0.11; p < 0.05) (higher number of unmet needs decreased leisure activities); positive mood and unmet health needs (users: β = −0.41; p < 0.001 v. staff: β = −0.32; p < 0.05). Only for users, there was a negative association between leisure activities and social (β = −0.29; p < 0.05) and service unmet needs (β = −0.28; p < 0.05) (higher number of unmet needs decreased leisure activities), and positive mood and total unmet needs (β = −0.62; p < 0.001) (higher number of unmet needs was associated with lower positive mood). Only for the staff, there was a negative association between leisure activities and basic needs (β = −0.41; p < 0.05) (a higher number of unmet needs decreased leisure activities).
A linear regression, adjusted for age, sex and BPRS (standardised coefficients), was undergone. Bold values denote statistical significance at *p < 0.05 **p < 0.01 ***p < 0.001 level.
A positive association in both user and staff ratings was found between non-productive activities and functioning (users: β = 0.27; p < 0.01 v. staff: β = 0.39; p < 0.05) (higher number of unmet needs were associated to higher non-productive activities), negative mood and health (users: β = 0.38; p < 0.001 v. staff β = 0.39; p < 0.01) and total unmet needs (users: β = 0.29; p < 0.05 v. staff: β = 0.12; p < 0.05) (higher number of unmet needs was associated with more negative mood). Only in staff ratings was there a positive association between religious activities and basic needs (β = 0.45; p < 0.05) (a higher number of unmet needs increased religious activities) (Table 4).
Association between momentary mood (as assessed using the ESM) and user-rated and staff-rated unmet needs at different levels of the BPRS
As shown in Fig. 1, a higher number of user-rated and staff-rated unmet needs negatively influenced users' positive moods and positively influenced users' negative moods. However, the associations between user-rated and staff-rated unmet needs and momentary mood (negative and positive), as assessed using the ESM, were not moderated by the level of severity of symptomatology, as assessed using the BPRS (negative mood and number of unmet needs in CAN-P [interaction coefficient = 0.06 (−0.30; 0.41), p = 0.745], and CAN-S [interaction coefficient = −0.03 (−0.32; 0.26), p = 0.828]; positive mood and the number of unmet needs in both CAN-P [interaction coefficient = −0.08 (−0.42; 0.26), p = 0.641] and CAN-S [interaction coefficient = −0.08 (−0.21; 0.37), p = 0.567]).
Discussion
This was the first study to investigate the association between needs for care and ecological indices, as assessed using the ESM, in residents with SSD. We confirmed the sociodemographic and clinical characteristics of similar samples from previous surveys (de Girolamo et al., Reference de Girolamo, Picardi, Micciolo, Falloon, Fioritti and Morosini2002; Martinelli et al., Reference Martinelli, Killaspy, Zarbo, Agosta, Casiraghi, Zamparini, Starace, Rocchetti, de Girolamo, Ruggeri, Barlati, Boero, Cerveri, Clerici, D'Anna, De Novellis, Di Michele, Di Prisco, Durbano, Facchini, Ghio, Giosuè, Greco, Latorre, Leuci, Maone, Marina, Maurizi, Monzani, Placenti, Rancati, Rippa, Rovera, Silva, Tura and Zanolini2022b). Our findings reveal that users who were younger, females, with the most severe symptomatology, the shortest length of stay in an RF or without collaborative behaviour were the most likely to report unmet needs in social, functioning and health areas. This feature might be related not only to the natural course of SSD with reduced symptoms and increased psychosocial functioning when patients are more collaborative, but also to the process of ‘institutionalisation’ (Wennström and Wiesel, Reference Wennström and Wiesel2006; SAS Institute Inc, 2013; Martinelli et al., Reference Martinelli, Iozzino, Ruggeri, Marston and Killaspy2019) which implies limitations in their social reintegration in society. The longer their stay in an RF, the higher the risk of being socially isolated (Federici et al., Reference Federici, Meloni, Mancini, Lauriola and Olivetti Belardinelli2009; Gold, Reference Gold2014; Martinelli et al., Reference Martinelli, Iozzino, Pozzan, Cristofalo, Bonetto and Ruggeri2022a).
Our findings reveal that the agreement between users and professionals concerning needs for care (Phelan et al., Reference Phelan, Slade, Thornicroft, Dunn, Holloway, Wykes, Strathdee, Loftus, McCrone and Hayward1995) is currently a challenge for Italian RFs. Moderate agreement was reported in areas where it was easier to allocate resources, such as housing and daytime activities (Werner, Reference Werner2012), which represent the most frequent activities carried out by the residents of our sample. The slight agreement on self-care, which usually represents one of the main objectives in RFs, might be due to an overestimation of self-care by users with SSD, who frequently have negative symptoms which may impair their body perception and lead to neglecting personal hygiene (Goldstone, Reference Goldstone2020). Furthermore, although the staff reported that patients were adequately informed about their disorder and ongoing treatments, users evaluated this information as not comprehensive. This might be due to staff overestimation of their communication skills or to the effect of self-stigma in patients' reticence about asking for more information (Lanfredi et al., Reference Lanfredi, Zoppei, Ferrari, Bonetto, van Bortel, Thornicroft, Knifton, Quinn, Rossi and Lasalvia2015; Winkler et al., Reference Winkler, Krupchanka, Roberts, Kondratova, Machů, Höschl, Sartorius, Van Voren, Aizberg, Bitter, Cerga-Pashoja, Deljkovic, Fanaj, Germanavicius, Hinkov, Hovsepyan, Ismayilov, Ivezic, Jarema, Jordanova, Kukić, Makhashvili, Šarotar, Plevachuk, Smirnova, Voinescu, Vrublevska and Thornicroft2017; Atwoli and Muhia, Reference Atwoli, Muhia and Okpaku2021). The finding of a relatively close agreement on unmet needs concerning social life (sex life in particular) was somewhat surprising, considering that this area may otherwise be challenging to investigate (Ruggeri et al., Reference Ruggeri, Leese, Slade, Bonizzato, Fontecedro and Tansella2004). However, the highest unmet needs in social areas domain confirmed (Eklund and Ostman, Reference Eklund and Ostman2010; Gold, Reference Gold2014) that few services are able to fulfil personal and subjective needs. A moderate disagreement was reported between staff and users on functioning, probably because most residents collaborated in the rehabilitative programme, which positively balanced the number of unmet needs in this area.
Most users performed some kinds of activity in the RF. However, the increase in unmet needs influenced the level of performed activity. In particular, the lack of productive activities strongly correlated with high unmet needs in functioning, while leisure activities seemed to be the first activities not performed when there was an overall increase in unmet needs, particularly in physical and psychological health, social life, media and transport.
Higher levels of met needs in physical and psychological health were associated with an increase in positive mood. Furthermore, a higher number of unmet needs were negatively associated with the fulfilment of everyday productive activities. These features may hinder the achievement of users' recovery because the lesser the user is active, motivated to pursue a productive activity, and proactive, the lesser they will have to cover all adult roles, live independently and be socially integrated (Argentzell et al., Reference Argentzell, Bäckström, Lund and Eklund2020).
Interestingly, our findings reveal that the association between mood and unmet needs is not moderated by the severity of symptomatology, leading us to conclude that needs for care, and particularly unmet needs, represent an important feature to be considered when planning residential interventions, independent of the severity of symptoms (Grinshpoon and Ponizovsky, Reference Grinshpoon and Ponizovsky2008; Oorschot et al., Reference Oorschot, Lataster, Thewissen, Lardinois, van Os, Delespaul and Myin-Germeys2012; Salisbury et al., Reference Salisbury, Killaspy and King2016).
Strengths and limitations
A major strength of this study is the use of the ESM, which allows the collection of longitudinal, prospective data in real-time, reducing reporting biases and acquiring information that cannot be easily observed or monitored in daily life.
The possible assessment bias due to staff socio-demographics was reduced thanks to a comprehensive staff training on the use of the CAN and other assessment tools.
Although residents with SSD represent most of those living in RFs (Starace et al., Reference Starace, Baccari and Mungai2017), these findings cannot be generalised to residents with other diagnostic profiles or those with SSD also showing marked cognitive impairment.
A limitation of the study was that because of logistic and financial limitations, the use of ESM was possible only in 17.9% of enrolled residents living in a subgroup of RFs, therefore reducing the generalisation of our findings.
Another limitation was the lack of a detailed statistical analysis plan for this specific CAN investigation in the study protocol (de Girolamo et al., Reference de Girolamo, Rocchetti, Benzi, Agosta, Casiraghi, Ferrari, De Franceschi, Macis, Pogliaghi and Starace2020).
We were also not able to perform a detailed statistical analysis, such as to cluster the sample, particularly the ESM subsample, based on the RFs where they live because of the limitation in the overall sample size.
Finally, data were collected during the coronavirus disease 2020 pandemic, which influenced daily clinical practice and routine activities.
Conclusions
This is the first study to investigate the needs for care of residents with SSD and its association with daily activities and mood, as monitored using the ESM.
Our findings reveal that although needs for care are important for planning rehabilitative activities (Lasalvia et al., Reference Lasalvia, Bonetto, Tansella, Stefani and Ruggeri2008; National Institute for Health and Care Excellence, 2020; Martinelli and Ruggeri, Reference Martinelli and Ruggeri2020a), Italian RFs deliver interventions which do not fully meet them. Furthermore, despite national and international guidelines (Grinshpoon and Ponizovsky, Reference Grinshpoon and Ponizovsky2008; IBM Corp. Released, 2020; Martinelli and Ruggeri, Reference Martinelli and Ruggeri2020b) recommending the implementation of shared decision-making to promote users' recovery, we found a substantial disagreement concerning unmet care needs between users and staff. Hence, Italian RFs need to deliver rehabilitative interventions that match real users' needs for care to facilitate their productive activities and progress towards recovery.
Further studies are needed to evaluate whether the use of the ESM might facilitate the design of tailored rehabilitative interventions based on the consensus of users and staff regarding needs for care.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S2045796023000124.
Data
Dataset referring to this manuscript is published with restricted access on Zenodo platform and accessible at this link: https://doi.org/10.5281/zenodo.686604.
Acknowledgements
We thank all members of the DiAPAson Consortium who actively worked to make this project possible: Niccolò Rossetto (Du Parc project, Torino), Rodolfo Pessina and Anna Auxilia (DSMD, ASST di Monza, Monza), Samantha Panigada and Stefania Ravera (Fondazione Giuseppe Costantino CRCRC Onlus, Pavia), Livia Elena Fussi and Valter Masseroni (DSMD, ASST di Melegnano e Martesana, Melegnano), Maria Concetta Miranda and Rosa Verrona (DSM, ASL Napoli 2 Nord, Napoli), Daniela di Cosimo (Fatebenefratelli, Centro Sacro Cuore di Gesù, San Colombano al Lambro), Alessandro Norbedo and Paolo Peressutti (DSM, ASUITS, Trieste), Gaetano Nappi and Domenico Semisa (DSM, ASL Bari, Bari), Fabio de Dominicis and Elisa Castagno (SRP 1 San Benedetto Menni, S. Maurizio Canavese), Lucio Ghio and Michele Tosato (DSMD, ASL 3 Genovese, Genova), Sarah Tosato and Michela Nosè (DSM, AULSS 9 Scaligera, Verona), Lorenzo Tatini and Giulio D'Anna (DSM, USL Toscana centro, Prato), Annalisa Maurizi and Filippo Maria Jacoponi (Comunità Passaggi, Aquila), Vittorio di Michele (DSM, ASL di Pescara, Penne), Vera Abbiati and Roberto Colombo (DSMD, ASST di Pavia, Pavia), Luca Rancati (CPA La Perla CREST, Grumello del Monte), Valentina Regina and Cassandra Ariu (DSMD, ASST di Brescia, Brescia), Carmela Schiavo and Carlotta lanzi (Centro Ippocrate, Cagliari), Emanuela Leuci e Lorenzo Pelizza (DSM-DP, AUSL di Parma, Parma). Graham Thornicroft is supported by the National Institute for Health Research (NIHR) Applied Research Collaboration South London at King's College London NHS Foundation Trust, and by the NIHR Asset Global Health Unit award. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. GT is also supported by the Guy's and St Thomas' Charity for the On Trac project (EFT151101), and by the UK Medical Research Council (UKRI) in relation to the Emilia (MR/S001255/1) and Indigo Partnership (MR/R023697/1) awards.
Financial support
The DiAPAson project is funded by the Italian Ministry of Health (Bando per la ricerca Finalizzata 2018: RF-2018-12365514). The Ministry of Health has no role in the analyses and interpretation of study findings.
Conflict of interest
None.
Ethical standards
The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2013. 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) and by the ECs of all participating sites. All participants provided informed consent to the participation.