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A retrospective study of nursing diagnoses, outcomes, and interventions for patients with mental disorders

Paula Escalada-Hernández, PhD, MSc a,⁎, Paula Muñoz-Hermoso, BSc b, Eduardo González–Fraile, Msc, BSc c, Borja Santos, Msc, BSc d, José Alonso González-Vargas, PMH CNS, BSc e, Isabel Feria-Raposo, PMH CNS, BSc f, José Luis Girón-García, PMH CNS, BSc g, Manuel García-Manso, BSc h THE CUISAM GROUP 1

a Public University of Navarre, Pamplona, Spain b Clínica Psiquiátrica Padre Menni, Pamplona, Spain c Instituto de Investigaciones Psiquiátricas, Bilbao, Spain d Universidad del País Vasco, Bilbao, Spain e Complejo Asistencial Hermanas Hospitalarias, Málaga, Spain f Benito Menni CASM, Sant Boi, Spain g Centro Neuropsiquiátrico Nuestra Sra. Del Carmen, Garrapinillos, Spain h Complejo Hospitalario San Luis, Palencia, Spain

a b s t r a c ta r t i c l e i n f o

Article history: Received 15 August 2013 Revised 24 March 2014 Accepted 28 May 2014

Keywords: NANDA-I nursing diagnoses NIC interventions NOC outcomes Psychiatric diagnoses Mental disorders

Aim: The aim of this study is to describe the most frequent NANDA-I nursing diagnoses, NOC outcomes, and NIC interventions used in nursing care plans in relation to psychiatric diagnosis. Background: Although numerous studies have described the most prevalent NANDA-I, NIC and NOC labels in association with medical diagnosis in different specialties, only few connect these with psychiatric diagnoses. Methods: This multicentric cross-sectional study was developed in Spain. Data were collected retrospectively from the electronic records of 690 psychiatric or psychogeriatric patients in long and medium-term units and, psychogeriatric day-care centres. Results: The most common nursing diagnoses, interventions and outcomes were identified for patients with schizophrenia, organic mental disorders, mental retardation, affective disorders, disorders of adult personality and behavior, mental and behavioural disorders due to psychoactive substance use and neurotic, stress-related and somatoform disorders. Conclusion: Results suggest that NANDA-I, NIC and NOC labels combined with psychiatric diagnosis offer a complete description of the patients' actual condition.

© 2014 Elsevier Inc. All rights reserved.

1. Background

Over the last decades, in the context ofmental health care, important reforms have taken place to promote the deinstitutionalization of patients in many occidental countries (WHO & Wonca, 2008). In this line, in Spain numerous changes have been undertaken to adopt a community-based model of mental health care (Ministry of Health, Equality Social Services, 2012). The Mental Health Strategy of the Spanish National Health System 2009–2013 is the current guidance document that, basedon theevaluationof thepresent situation, outlines themain lines of strategy and objectives for the improvement of mental health care (Ministry of Health, Equality Social Services, 2012). This document acknowledges the relevance of nurses' function and promotes the incorporation of nurses who are certified as psychiatric– mental health clinical nurse specialist as part of interdisciplinary teams among all mental health care services. The mental health care services include a variety of different types of health care settings for adult patients: community mental health care centres, day care/psychosocial rehabilitation centres, community residential/supported living services,

Applied Nursing Research 28 (2015) 92–98

⁎ Corresponding author at: Health Science Department, Public University of Navarre., Avenida de Barañain s/n. 31008, Pamplona, Navarre, Spain. Tel.: +34 948 14 06 11.

E-mail addresses: [email protected] (P. Escalada-Hernández), [email protected] (P. Muñoz-Hermoso), [email protected] (E. González–Fraile), [email protected] (B. Santos), [email protected] (J.A. González-Vargas), [email protected] (I. Feria-Raposo), [email protected] (J.L. Girón-García), [email protected] (M. García-Manso).

1 The researchers who were part of the CUISAM Group were: Uxua Lazkanotegui Matxiarena, Itxaso Marro Larrañaga, Janire Martínez Berrueta, Miren Arbelóa Álvarez, Miriam García Sanabria, David Rodríguez Merchán, Cristina Flores Del Redal López and Marta Alameda Blanco from Clínica Psiquiátrica Padre Menni (Pamplona, Spain); Mertxe Olondriz Urrutia and Maite Dendarrieta Bardot from Centro Hospitalario Benito Menni (Elizondo, Spain); Almudena Bueno García, Elena Muñoz Jiménez, Mª Esperanza Pozo Cambeiro, Inmaculada Romero López, Juan Tomás Jiménez Pereña, Laura Cebreros Cuberos, Laura Marín Rubio, Marina Rubio Guerrrero, Rocío Jiménez Sánchez, Sergio Víctor Mata Reyes, Antonia Mª Ariza Nevado and Verónica Aguilar Pérez from Complejo Asistencial Hermanas Hospitalarias (Málaga, Spain); Mª Carmen Vilchez Estévez, Mónica Pastor Ramos and Alberto Carnero Treviño from Benito Menni CASM (Sant Boi, Spain); Nuria García Sola, Natividad Izaguerri Mochales, Elena Martínez Araus, Eva Sanz Báguena, Silvia Gabasa Galbez from Centro Neuropsiquiátrico Nuestra Sra. Del Carmen (Zaragoza, Spain); Emilio Negro González from Complejo Hospitalario San Luis (Palencia, Spain).

http://dx.doi.org/10.1016/j.apnr.2014.05.006 0897-1897/© 2014 Elsevier Inc. All rights reserved.

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acute psychiatric units, medium and long-term psychiatric units and psychogeriatric residential units (SIAP, 2009).

The nurses' role within the interdisciplinary teams can be supported and enhanced with research on nursing care and practice in the differentmental health care services of the Spanish context. The use of standardized languages to describe the elements of the nursing process provides a systematic approach toward patient care and allows describing nursing practice in a precise way (Johnson, Moorhead, Bulechek, Maas, & Swanson, 2011; Nanda International, 2012; Thoroddsen, Ehnfors, & Ehrenberg, 2010). The nursing diagnoses classification of the NANDA-International (NANDA-I; Nanda International, 2012), the Nursing Outcomes Classification (NOC; Moorhead, Johnson, Maas, & Swanson, 2013) and the Nursing Interventions Classification (NIC; Bulechek, Butcher, Dochterman, & Wagner, 2013) are three coded and standardized nomenclatures that refer to the nursing process elements of diagnoses, interventions, and outcomes. Each element in NANDA-I, NIC and NOC taxonomies consists of a label name, a definition and a unique numeric code. NANDA-I, NIC and NOC terminologies have widely been researched and applied (Anderson, Keenan, & Jones, 2009; Johnson et al., 2011).

The three classifications together have the potential to represent the domain of nursing in all settings (Johnson et al., 2011). Thoroddsen et al. (2010) compared nursing diagnoses and nursing interventions in four selected nursing specialties, including surgical, medical, geriatric, and psychiatric areas. They concluded that NANDA-I and NIC taxonomies illustrated the specific knowledge of each specialty and were very useful in describing basic human needs and nursing care in clinical practice. Nonetheless, they argued that further research should be developed to identify specific nursing diagnoses, nursing interventions and outcomes in different special- ties. Two studies identified nursing phenomena (Frauenfelder, Müller-Staub, Needham, & Van Achterberg, 2011) and nursing interventions (Frauenfelder, Müller-Staub, Needham, & Achterberg, 2013) mentioned in journal articles on adult psychiatric inpatient nursing care and compared them with the NANDA-I and NIC terminologies respectively. Both studies concluded that these taxon- omies described the majority, but not all, of concepts mentioned in the literature. The authors suggested that additional development of the taxonomies is needed to include all the relevant phenomena and interventions for the nursing work in adult inpatient settings (Frauen- felder et al., 2011, 2013).

Numerous studies in different specialties have analyzed NANDA-I, NIC and NOC elements in association with medical diagnoses or diagnosis-related groups. It has been demonstrated that their concurrent application offers complementary information about a patient's actual condition that can be employed to predict patient outcomes or use of resources (Güler, Eser, Khorshid, & Yücel, 2012; van Beek, Goossen, & van der Kloot, 2005; Welton & Halloran, 2005). In psychiatry and mental health care, only two studies examining the prevalence of nursing diagnoses according to different psychiatric diagnoses have been located. Ugalde Apalategui and Lluch Canut (2011) described the most prevalent NANDA-I labels for nine diagnosis-related groups and Vílchez Esteve, Atienza Rodríguez, Delgado Almeda, González Jiménez, and Lorenzo Tojeiro (2007) for five psychiatric diagnoses. Moreover, two additional papers examined nursing diagnoses in patients with a specific psychiatric diagnosis, such as schizophrenia (Chung, Chiang, Chou, Chu, & Chang, 2010; Lluch Canut et al., 2009).

Beyond prevalence analyses, several research projects have examined the relationship between the number of nursing diagnoses, as a measure of nursing complexity, and patient outcomes. For example, Moon (2011) found that the number of nursing diagnoses was significantly related to the changes in selected NOC scores in ICU patients and Sherb et al. (2013) obtained similar results in patients with pneumonia or heart failure. In acute cardiac care, Meyer, Wang, Li, Thomson, and O'Brien-Pallas (2009) demonstrated that the

number of nursing diagnoses increased the likelihood of suffering medical consequences (e.g., medical errors with consequences, urinary tract or wound infections) and reduce the extent to which physical and mental health improved at discharge (measured by difference scores between admission and discharge in the SF-12 Health Status Survey). To the author's knowledge, this aspect has not been explored in psychiatric patients.

Examining nursing practice by analyzing NANDA-I, NIC and NOC labels mentioned in nursing records in mental health nursing practice may contribute to develop knowledge within the specialty. The aim of this study is to describe the most frequent nursing diagnoses, outcomes, and interventions used in nursing care plans for psychiatric and psychogeriatric patients in medium and long-term care facilities in relation to psychiatric diagnosis. The research questions were: (a) Which nursing diagnoses, outcomes and interventions are used in nursing care plans according to psychiatric diagnosis? (b) Is there any relationship between the variables number of nursing diagnoses, psychiatric diagnosis, age or gender and the degree of severity of problems associated with mental illness?

2. Research methods

2.1. Data collection procedures and sample

This multicentric cross-sectional study was performed in 5 psychiatric clinics in different regions of Spain. These centres belong to the Congregation of Sisters Hospitallers of the Sacred Heart of Jesus. The electronic medical record software used in these centres integrates NANDA-I, NIC and NOC taxonomies and nurses have used them routinely to develop healthcare plans for some years now.

Data were collected retrospectively from the nursing care plans included in the electronic patient records. No sampling strategy was used as the whole study population was included in the study. The study population consisted of all those records of patients fulfilling the inclusion/exclusion criteria who were hospitalized between June 2010 and July 2011. Subjects eligible for inclusion were adult (aged over 18) psychiatric and psychogeriatric patients, who had a nursing care plan with NANDA-I, NIC and NOC labels and stayed at any of the healthcare facilities under study. These were long-term psychiatric units, medium-term psychiatric units, long-term psychogeriatric units and psychogeriatric day-care centres. Long-term units are residential services and patients may stay there indefinitely. Patients usually stay in medium-term units between 1 and 6 months. As exclusion criteria, due to ethical considerations, all patients in a terminal condition were not considered eligible. Records of patients who were readmitted after discharge during the data collection period were excluded.

This research project was approved by the Ethical and Scientific Research Committee of Navarra. To ensure anonymity each electronic patient recordwas assigned an ID-number. Access tomedical electronic records was granted by participating centres. In addition, although not necessary, written informed consent from all participants or their legal guardians was obtained to add ethical value to the study. In order to facilitate a systematic data collection, all members of the research team used a data collection form and received a training session.

2.2. Variables

The content of the data collection form consisted of 4 data sets relating to socio-demographic details, medical information, NANDA-I, NIC and NOC codes and the Health of the Nation Outcome Scale (HoNOS), respectively. The socio-demographic details collected were age, gender, marital status, socio-economic status, education and employment situation. The medical information included primary psychiatric diagnosis according to ICD-10 classification (secondary diagnoses, if present, were not considered), clinical area (psychiatry or psychogeriatry) and type of healthcare setting (i.e. day-care centre,

93P. Escalada-Hernández et al. / Applied Nursing Research 28 (2015) 92–98

medium or long-term unit). In relation to NANDA-I, NIC and NOC taxonomies, the codes of nursing diagnoses, outcomes and interven- tions documented in nursing care plans were recorded. In addition, clinical problems and social functioning of patients were assessed by HoNOS in its Spanish version (Uriarte et al., 1999). HoNOS is an instrument with 12 items designed to measure the whole range of physical, personal and social problems associated with mental illness. The score in each item ranges from 0 (i.e. without problems) to 4 (serious or very serious problems). Thus, the total HoNOS score may range from 0 to 48.

This scale has a broad clinical and a social coverage; it is used as a clinical outcome measure and is suitable for routine application by nurses (Pirkis et al., 2005; Wing et al., 1998). Different studies of the psychometric properties of the scale showed an adequate internal consistence with Cronbach's alpha ranging from 0.59 to 0.76, indicating that HoNOS provides a clear overview of severity of symptoms (Pirkis et al., 2005). Studies that analyzed the test–retest reliability of the scale have reported fair to moderate scores and those that examined its inter-rater reliability concluded that overall agreement between raters was moderate to good for the HoNOS total score (Pirkis et al., 2005).

2.3. Data analyses

Data were analyzed with MS Excel and STATA V.12.1 software (StataCorp LP). To determine the most frequent NANDA-I, NIC and NOC labels in relation to psychiatric diagnosis, the sample was divided into groups according psychiatric diagnosis categories. Descriptive analyses were performed using absolute frequency distribution and percentage. For the second research question, additional statistical analyses were executed on the data from the total sample. The Pearson correlation coefficient was calculated to explore the relation- ship between the number of nursing diagnoses and the total score in

HoNOS. A multiple regression model was performed where total HoNOS score was the independent variable and the dependent variables were psychiatric diagnosis, number of nursing diagnoses, age and gender.

3. Results

Socio-demographic information of the study sample is presented in Table 1. The final sample included the records of 690 patients. From them, 434 (62.90%) were female and 256 (37.10%) were male. The average age was 67.9 ± 16.8 years (range 19–101). More than 50% of subjects were married, around 70% had a socio-economic status between low and medium, the majority (88%) were in pension and approximately 50% had primary school level education. The number of participants admitted in long-term psychiatric units was 219 (31.74%), 54 (7.83%) in medium-term psychiatric units, 351 (50.87%) in long-term psychogeriatric units and, 66 (9.56%) in psychogeriatric day-care centres.

Psychiatric diagnoses were classified according to the main categories of ICD-10, obtaining the following groups: group 1: schizophrenia, schizotypal and delusional disorders (n = 362; 52.46%); group 2: organic mental disorders (n = 182; 26.38%); group 3: mental retardation (n = 37; 5.36%); group 4: bipolar affective disorders (n = 33; 4.78%); group 5: depressive and other affective disorders (n = 22; 3.19%); group 6: disorders of adult personality and behaviour (n = 21; 3.04%); group 7: mental and behavioural disorders due to psychoactive substance use (n = 17; 2.46%); group 8: neurotic, stress-related and somatoform disorders (n = 14; 2.03%); other disorders (n = 2; 0.30%).

Below, the main results will be presented in order of the research questions.

3.1. (a) Which nursing diagnoses, outcomes and interventions are used in nursing care plans according to psychiatric diagnosis?

In all, 3681 nursing diagnoses, 4685 nursing outcomes and 13396 nursing interventions were recorded. The average number of nursing diagnoses per patient was 5.3. Similarly, the average numbers of nursing outcomes and nursing interventions per patient were 6.8 and 19.4 respectively.

Nursing diagnoses, outcomes and interventions were analyzed within each psychiatric diagnosis group. The most frequent NANDA-I, NOC and NIC labels for each group are illustrated in Tables 2A and 2B. The most prevalent labels are mainly related to psychosocial and self-care deficit aspects. Certain patterns or profiles were observed within each psychiatric diagnosis group. In group 1 (schizophrenia, schizotypal and delusional disorders), NANDA-I, NIC and NOC terms illustrated the usual needs faced by patients with schizophrenia such as disturbance of thought processes and social, communication, anxiety and treatment compliance problems. Nursing diagnoses, outcomes and interventions in relation to self-care deficit were more predominant in groups 2 (organic mental disorders) and 3 (mental retardation). Within group 4 (bipolar affective disorders), NANDA-I, NIC and NOC labels are mainly related to self-care deficits and, symptom and side-effects management (i.e. disturbance of thought processes and constipation) and treatment compliance. NANDA-I, NIC and NOC labels in groups 5 (depressive and other affective disorders) and 8 (neurotic, stress-related and somatoform disorders) showed a special focus on anxiety problems. Groups 6 (disorders of adult personality and behaviour) and 7 (mental and behavioural disorders due to psychoactive substance use) had a majority of nursing diagnoses, outcomes and interventions related to social interaction and self-care needs. Moreover, some labels in group 7 (mental and behavioural disorders due to psychoactive substance use) referred to side-effects such as constipation.

Table 1 Socio-demographic characteristics of the sample.

Data n %

Age groups 19–30 year 15 2.17 31–50 years 101 14.62 51–65 years 153 22.14 66–85 years 326 47.18 ≥85 years 96 13.89

Gender Women 432 62.70 Men 257 37.30

Marital status Single 381 55.14 Married 99 14.33 Divorced/Separated 60 8.68 Widower 130 18.81 Unkown 21 3.04

Socio-economic status Low 179 25.90 Low-medium 173 25.04 Medium 156 22.57 High-medium 63 9.12 High 16 2.32 Unkown 104 15.05

Education Illiterate 74 10.71 Primary school level 332 48.05 Secondary school level 100 14.47 University level 51 7.38 Unknown 134 19.39

Employment situation Employed 6 0.88 Unemployed 75 10.98 In pension 602 88.14

94 P. Escalada-Hernández et al. / Applied Nursing Research 28 (2015) 92–98

3.2. (b) Is there any relationship between the variables number of nursing diagnoses, psychiatric diagnosis, age or gender and the degree of severity of problems associated with mental illness?

Data from the total sample were used to examine potential relationships between number of nursing diagnoses, psychiatric diagnosis, age or gender and the degree of severity of problems associatedwithmental illness (as reflected by HoNOS total score). The mean of the HoNOS score in the total sample was 13.24 ± 5.97. The result of the Pearson correlation test (r = 0.22) was statistically significant (p b 0.05) and indicated a moderate positive linear relationship between HoNOS total score and the number of nursing diagnoses. Several stepwise regression models were devised to determine the explanatory factors for the HoNOS total score. Initially, number of nursing diagnoses, psychiatric diagnoses, age and gender were included as independent variables the HoNOS total score as dependent variable. The final multiple regression model (Table 3) revealed that only gender and number of nursing diagnoses had a significant influence on the HoNOS total score. The gender coefficient (−1.35 ± 0.45) represents that adjusting for the nursing diagnoses, women would have had a HoNOS total score one point less than men. According to the coefficient of the number of nursing diagnoses (0.44 ± 0.07), an increment of five diagnoses adjusting for gender represents a 2-point increment in the HoNOS total score.

4. Discussion

The findings of this study describe themost frequent NANDA-I, NIC and NOC labels for groups of patients with different psychiatric diagnoses in medium and long-term units. Overall, some common aspects among all groups were found. NANDA-I, NIC and NOC labels in all groups reflected nursing care related to patients' psychosocial needs, self-care deficits and management of the therapeutic regimen. The domain of psychiatric nursing specialty, although not exclusively, focuses on these aspects (Frauenfelder et al., 2011; Sales Orts, 2005; Ugalde Apalategui & Lluch Canut, 2011). Nursing care related to patients' psychosocial needs were described by nursing diagnoses such as disturbed thought processes, impaired social interaction, impaired verbal communication, deficient diversional activity or anxiety; outcomes such as distorted thought self-control, social interaction skills, cognitive orientation, leisure participation or anxiety self-control; and interventions such as active listening, anxiety reduction, socialization enhancement, reality orientation, exercise promotion or coping enhance- ment. In relation to self-care needs, for instance, several nursing diagnoses of self-care deficit (i.e. bathing, dressing, and feeding) and its related outcomes and interventions can be observed. Furthermore, NANDA-I, NIC and NOC labels such as ineffective self health management, medication management or medication administration illustrated how attention to the management of the therapeutic

Table 2A Most frequent NNN labels by psychiatric diagnosis group.

Group 1: schizophrenia, schizotypal and delusional disorders (n = 362)

Group 2: organic mental disorders (n = 182)

Group 3: mental retardation (n = 37)

Group 4: bipolar affective disorders (n = 33)

NANDA n % NANDA n % NANDA n % NANDA n % 108 self-care deficit: bathing 207 57,18 109 self-care deficit: dressing 122 67,03 108 self-care deficit: bathing 17 45,95 108 self-care deficit: bathing 16 48,48 130 disturbed thought processes

174 48,07 108 self-care deficit: bathing 116 63,74 109 self-care deficit: dressing 15 40,54 11 constipation 13 39,39

52 impaired social interaction 139 38,40 102 self-care deficit: feeding 89 48,90 102 self-care deficit: feeding 8 21,62 130 disturbed thought processes

12 36,36

51 impaired verbal communication

108 29,83 131 impaired memory 71 39,01 11 constipation 7 18,92 78 ineffective self health management

12 36,36

78 ineffective self health management

108 29,83 51 impaired verbal communication

59 32,42 97 deficient diversional activity

6 16,22 97 deficient diversional activity

11 33,33

NOC n % NOC n % NOC n % NOC n % 305 self-care: hygiene 168 46,41 300 self-care: activities of daily

living (ADL) 150 82,42 300 self-care: activities of

daily living (ADL) 19 51,35 1612 weight control 9 27,27

1403 distorted thought self-control

153 42,27 305 self-care: hygiene 105 57,69 305 self-care: hygiene 15 40,54 300 self-care: activities of daily living (ADL)

8 24,24

300 self-care: activities of daily living (ADL)

133 36,74 1101 tissue integrity: skin and mucous membranes

80 43,96 302 self-care: dressing 10 27,03 305 self-care: hygiene 8 24,24

901 cognitive orientation 126 34,81 302 self-care: dressing 77 42,31 1604 leisure participation 8 21,62 1403 distorted thought self-control

8 24,24

1502 social interaction skills 126 34,81 902 cognitive orientation 57 31,32 501 bowel elimination 7 18,92 1608 symptom control 8 24,24

NIC n % NIC n % NIC n % NIC n % 1801 self-care assistance: bathing/hygiene

226 62,43 6480 environmental management

156 85,71 5606 teaching: individual 24 64,86 200 exercise promotion 23 69,70

5606 teaching: Individual 212 58,56 1801 self-care assistance: bathing/hygiene

137 75,27 1801 self-care assistance: bathing/hygiene

19 51,35 5820 anxiety reduction 20 60,61

5820 anxiety reduction 194 53,59 5606 teaching: Individual 128 70,33 5820 anxiety reduction 16 43,24 4820 reality orientation 17 51,52 4820 reality orientation 175 48,34 6490 fall prevention 120 65,93 200 exercise promotion 15 40,54 2300 medication

administration 16 48,48

5100 socialization enhancement

153 42,27 1802 self-care assistance: dressing/grooming

119 65,38 1800 self-care assistance 13 35,14 5606 teaching: individual 15 45,45

2380 medication management

152 41,99 6486 environmental management: safety

115 63,19 6480 environmental management

12 32,43 1801 self-care assistance: bathing/hygiene

14 42,42

4920 active listening 147 40,61 1800 self-care assistance 107 58,79 1802 self-care assistance: dressing/grooming

12 32,43 4920 active listening 14 42,42

4480 self-responsibility facilitation

146 40,33 6460 dementia management 102 56,04 1670 hair care 12 32,43 2380 medication management

13 39,39

5230 coping enhancement 145 40,06 4820 reality orientation 97 53,30 1680 nail care 11 29,73 4480 self-responsibility facilitation

13 39,39

4362 behavior modification: social skills

133 36,74 1803 self-care assistance: feeding

92 50,55 1660 foot care 11 29,73 5100 socialization enhancement

13 39,39

95P. Escalada-Hernández et al. / Applied Nursing Research 28 (2015) 92–98

regimen also appeared in the nursing care plans. This supports the conclusions of Thoroddsen et al. (2010), who demonstrated that standardized nursing languages have the potential of representing specific knowledge within nursing specialties, including mental health nursing.

Within each psychiatric diagnosis group specific patterns and features can be observed, demonstrating that psychiatric diagnosis and NANDA-I, NIC and NOC labels were related. Findings in group 1 (i.e. patients with schizophrenia) are consistent with the literature. Three of the most prevalent nursing diagnoses in this group: disturbed thought processes, ineffective self health management and self-care deficit: bathing were also found very frequent in other studies on

patients with schizophrenia and schizotypal and delusional disorders (Chung et al., 2010; Lluch Canut et al., 2009; Ugalde Apalategui & Lluch Canut, 2011; Vílchez Esteve et al., 2007) For the rest of the psychiatric diagnosis groups, comparisons between this study and the other two existing studies are difficult as they classified psychiatric diagnoses in a different way, using diagnosis-related groups (Ugalde Apalategui & Lluch Canut, 2011) or other diagnostic categories such as mania, depression, dual disorders or adaptative disorders (Vílchez Esteve et al., 2007). Clinical manifestations and diagnostic criteria differ among classifications, and therefore, patients' characteristics and needs in each group will be different in some degree.

The statistical analyses performed showed that HoNOS total score was related with the variable number of nursing diagnoses and not with the variable psychiatric diagnosis. Based on these results, it could be argued that the degree of severity of patients' problems has an impact on nursing care requirements. This relationship between patients' level of physical and mental health and number of nursing diagnoses has been demonstrated in previous research (Meyer et al., 2009). This result supports the use of …