2013 issue 1


Volume 22, issue 1

Original article

Relationship of socio-demographic and clinical predictors with social networks in people suffering from schizophrenic psychoses

Andrzej Cechnicki1, Anna Wojciechowska2, Aneta Kalisz3, Piotr Błądziński1, Michał Skalski4
1. Zakład Psychiatrii Środowiskowej Katedry Psychiatrii UJ CM, Kraków
2. Stowarzyszenie na Rzecz Rozwoju Psychiatrii i Opieki Środowiskowej, Kraków
3. Oddział Dzienny Leczenia Psychoz, Klinika Psychiatrii Dorosłych, Dzieci i Młodzieży, Szpital Uniwersyteckiego, Kraków
4. Dzienny Oddział Rehabilitacji Psychiatrycznej, Klinika Psychiatrii Dorosłych, Dzieci i Młodzieży, Szpital Uniwersytecki, Kraków
Postępy Psychiatrii i Neurologii 2013; 22 (1): 33–40
Keywords: schizophrenia, social network, predictors


Objectives. This report is a part of the Cracow prospective study on the course of schizophrenia. Links between socio-demographic and clinical factors on the one hand and the patient social network indicators on the other, as well as stability of the relationships found were examined at seven and twelve years of living with illness.
Methods. The study sample comprised 47 patients with the DSM-IV diagnosis of schizophrenia, assessed at two time points: at seven and twelve years from their index hospitalization. Social network indicators including the network scope, size of extrafamilial networks, and overall level of instrumental and emotional support outside the family were measured using the Bizoń Social Support Questionnaire. Major socio-demographic predictors of the future course of illness were assessed with a Prognostic Scale (modified from the Strauss-Carpenter Scale). The Expressed Emotion indicator was evaluated during the index hospitalization using the Camberwell Family Interview, and the Brief of Psychiatric Rating Scale was employed to rate symptom severity. Impact assessment was carried out using linear stepwise regression analysis.
Results. The constellation of socio-demographic and clinical factors under study explained 46% of the scope of the patient’s social network after 7 years of illness, and 32% after 12 years (both significant at p < 0.001). The figures for the scope of the extrafamilial social network were 25% (p = 0.003) and 24% (p = 0.005) at the 7- and 12-year follow-ups, respectively. High levels of social support were explained as follows: overall social support 36% and 33%, instrumental support 31% and 38%, emotional support 31% and 28%, respectively; all the values significant at p = 0.001. Finally, the predictors explained 17% (p = 0.012) and 19% (p = 0.016) of high levels of social support outside the family.
Conclusions. 1) Socio-demographic and clinical predictors explain between 17% and 46% of variability in social network indicators in short-term and long-term treatment outcomes. 2) Socio-demographic and clinical predictors offer the highest degree of explanation for the scope of the network, and the lowest degree of explanation for the scope of support outside the family. 3) It is most usually a higher education level, profound and satisfying social contacts outside the family prior to the onset of illness, and later age of onset in various configurations that contribute most to the explanation of positive social network indicators. 4) The amount of variability explained between the 7th and 12th years of illness is relatively stable.

Address for correspondence:
Andrzej Cechnicki
Pracownia Psychiatrii Środowiskowej, Katedra Psychiatrii Collegium Medicum UJ
Pl. Sikorskiego 2/8, 31-115 Kraków
tel. 12 421 51 17, e-mail: mzcechni@cyf-kr.edu.pl