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DEPRESSIVE PATIENTS' PREFERENCES IN SHARED DECISION-MAKING/PREFERENCIAS POR LAS DECISIONES COMPARTIDAS EN PACIENTES CON DEPRESION/PREFERENCIAS PELAS DECISOES COMPARTILHADAS EM PACIENTES COM DEPRESSAO.

INTRODUCTION

Mood disorders represent one of the most important problems of public health in Western societies. In Spain, from 2006 to 2010, the prevalence rates of patients with mood disorder in primary care services increased by 19.4% for major depression and 4.7% for depressive episodes (Gili, Rock, Basu, McKee & Stuckler, 2013). Depression has been linked to several health problems, functional impairment, and, often, lack of adherence to treatment regimes. These facts could increase the risk of morbidity and mortality (Katon, 2011).

In clinical practice, lack of adherence to antidepressant medication is a major barrier to successful treatment of depression (De las Cuevas & Penate, 2014; Grenard et al., 2011; Perez-Wehbe, Perestelo, Bethencourt, Cuellar & Penate, 2014). The literature has shown that inadequate adherence to prescribed treatment was associated with poorer treatment outcomes, increased risk of relapse and recurrence, and increased health care costs (Cantrell, Eaddy, Shah, Regan & Sokol, 2006; Geddes et al., 2003). These effects have a particular impact in patients with long-term illnesses, requiring a higher medication adherence (Katon, 2011), and could increase the chronicity of the disorder.

It has been suggested that one of the factors that could improve adherence to treatment and its effectiveness is the participation of patients in shared decision-making (SDM). According to the SDM procedure, the health professional exchanges relevant information with the patient about the best treatment available and each option is discussed (Makoul & Clayman, 2006). Patients may engage in various forms of participation, including search and exchange of information, debate on care options, and decision-making about the preferred treatment. SDM has proven to be an effective resource for chronic illnesses and when patients need long-term treatment (Joosten, de Fuentes-Merillas, de Weert, Sensky, Van Der Staak & de Jong, 2008), hence its importance in the treatment of psychiatric disorders. However, not all patients are ready or want to participate to the same degree in the process of making decisions about how to treat their problem. Studies have shown that although some patients want to play an active role in the discussion of treatment options, many of them want their doctors to make decisions on their behalf (Levinson, Kao, Kuby & Thisted, 2005).

The adequacy of a SDM depends on the clinical context, the responsibility of health professionals, patient preferences and certain demographic characteristics (Longtin, Sax, Leape, Sheridan, Donaldson & Pittet, 2010). It has been found that although men and women do not differ in SDM preferences, women usually take a more passive role than men. Similarly, older people and those with a lower educational degree have shown a lesser level of involvement in SDM, showing preference for a paternalistic or more passive role (Schneider, Korner, Mehring, Wensing, Elwyn & Szecsenyi, 2006; Singh et al., 2010).

In depressed patients, both SDM and care provided by mental health services have been associated with higher patient satisfaction (Aljumah, & Hassali, 2015; Swanson, Bastani Rubenstein, Meredith, & Ford, 2007). Furthermore, when the medical staff was trained to take SDM, greater patient's involvement was found (Loh, Simon, Wills, Kriston, Niebling & Harter, 2007).

Also, psychological processes such us psychological reactance, locus of control and self-efficacy have been found to be factors affecting patient involvement in decision-making. Psychological reactance is an aversive affective reaction in response to impositions that impinge on individuals' autonomy (Brehm & Brehm, 2013). Medical prescription recommendations can have a potential reactant effect and can lead reactant patients to ignore the prescribed treatment (De Almeida & Chen, 2008). Psychological reactance has shown to be negatively associated with adherence to treatment in patients with depressive disorder (De las Cuevas, Penate, & Sanz, 2014). Similarly, reactance will have an impact on the degree to which the individual will participate in SDM.

Locus of control related to health refers to individual's beliefs about the causes and results of their behavior (Walls-ton, 1992). Patients with internal locus of control believe that health is a direct result of their own behavior, while external locus patients believe that health is the result of external factors, such us chance or the role of other people (physicians, family members ...). Locus of control has been related to patient's preference, medical decision implications, and medical outcomes (O'Hea, Grothe, Bodenlos, Boudreaux, White, & Brantley, 2005. Severe depressive patients have informed of lower scores on preference for information and greater fatalistic locus of control (Schneider et al., 2006). Moreover, older people have showed lesser involvement in decision-making. For women, higher levels of beliefs regarding health control have been found in comparison with men (Pudrovska, 2015).

Self-efficacy process reflects a belief in the own abilities to plan and carry out activities to deal with problematic situations (Bandura, 1977; Schwarzer & Fuchs, 1996), Self-efficacy produces greater self-confidence, and as a result, increases the probability that people cope with those problematic contexts. Self-efficacy is one of the protective factors for depression and has been associated with a higher quality of life in depressive patients (Botero & Londono, 2013; Serra-Taylor & Irizarry-Robles, 2015). People with greater confidence in their ability to follow a treatment plan and to achieve the desired result are more involved in the necessary behavior (Makoul & Clayman, 2006).

Based on previous research, the aim of this study was to analyze the role of psychological processes, such as locus of control, psychological reactance and self-efficacy on depressed patients' preferences to participate in SDM. It has also an objective to examine the predictive power of these psychological processes against socio-demographic and clinical characteristics. Specifically, the aims of this study were: a)To examine the relationship between socio-demographic and clinical variables and preferences in SDM in patients with depression. b) To analyze the relationship between psychological processes, such as locus of control, psychological reactance and self-efficacy and preference for SDM. c) To study whether depressive women have a different preference on SDM than depressive men. d) To identify whether psychological processes explain to a greater extent preferences in SDM than demographic and/ or clinical characteristics.

METHOD

Participants

In this study 462 patients of the Mental Health Hospital Nuestra Senora de la Candelaria in Tenerife participated. The inclusion criterion was having been diagnosed with a depressive disorder (F32 or F33), according to the International Classification of Diseases-ICD-10 (WHO, 2004). All participants were informed of the overall objective of the study and were asked to use the reported data collected for research consent. The time frame of the study was from October 2012 to April 2014.

In Table 1, the socio-demographic and clinical characteristics of the participants diagnosed with depressive disorder are presented. The age range was between 18 and 85 years, although the highest proportion was between 45 and 60 years. More than three quarters of the participants were women. There were a similar proportion of participants at all academic levels, only 10.6% had not completed their studies. Most participants were receiving medication to control the disorder and had undergone treatment for an average of seven years. About half of them had a depressive episode and the rest had a recurrent depressive disorder. Overall, participants preferred a collaborative passive or fully-passive role in relation to shared decision-making.

Instruments

Socio demographic and clinical characteristics were assessed using a semi-structured interview and through the medical records of the participants. Among those characteristics, age, gender and educational level (no education, primary school, high school and college) were recorded. From the clinical diagnosis, identifying individuals with depressive episode or recurrent depressive disorder, based on ICD-10 was considered. The duration of pharmacological treatment in months and the amount of drugs that they had been prescribed (none, one, two, three, four, five psychotropic drugs) were also recorded.

Control Preferences Scale -CPS- (Degner, Sloan, & Venkatesh, 1997) was designed to assess the degree of control patients take when they make decisions about medical treatments. Individuals were presented with five cards in which the doctor-patient interaction was portrayed along with a phrase that reflected who had a more active role in the decision. Patients had to choose between the cards, observing them one at a time, to establish an order of preference that ranged from a completely active role to a more passive style (from 0 to 5, where the higher the score, the more passive the style). Participants responded to the test twice, before going to consultation and after finishing it. Thereby the variable was continuously analyzed. The preferred decision-making was analyzed from a categorical point of view, which was divided into three styles, giving priority to the card participants chose for the first time. These styles were: a) active, which included people who in both moments of the test chose an active style, and who at first chose active and then chose collaborative; b) collaborative, which included participants who chose this style first no matter whether later they chose an active or passive style; and c) passive, referring to participants who preferred a passive style and then chose a collaborative one, or whom on both occasions chose a passive style. Regarding this issue, the studies by Tariman, Doorenbos, Schepp, Singhal, & Berry (2014) account for preference stability in 50% of participants concerning decision-making.

Multidimensional Health Locus of Control Scale-MHLC-Form C (Wallston, Stein & Smith, 1994). This instrument consists of 18 items that assess the locus of control of the individual in the health context. It uses a six points Likert-scale ranging from disagreement to total agreement so that a high score means a higher locus of control. The scale allows the evaluation of four dimensions: internal locus of control, reflecting the degree to which the individual believes that his health depends on their behavior; locus of control focused on chance, which refers to the belief that health depends on luck, chance or fate; locus of control focused on the health care professional, indicating the belief that this person is who determines the state of health of the patient, and locus of control focused on others, which locates the control condition on family or friends. The Spanish validated version scale was used and it has shown acceptable Cronbach's a: .74 for internal locus, .65 for chance-locus, .54 for doctor- locus and .48 for others-locus (De las Cuevas, Penate, Betancort, & Cabrera, 2015).

General Self-Efficacy Scale-GSS-(Jerusalem & Schwarzer, 1992). The scale consists of 10 Likert type items ranging from 1 (completely false) to 4 (completely true) that assess the belief that the individual's actions affect the successful management of situations. The higher the score on the scale, the greater the self-efficacy. In this study the Spanish validated version of the scale was used, which has a Cronbach's a of .90 (Sanjuan, Perez & Bermudez, 2000).

Hong Psychological Reactance Scale -HPRS- (Hong & Faedda, 1996). It consists of 14 items that measure cognitive and emotional reactance, through a Likert scale ranging from 1 (strongly disagree) to 5 (total agreement). The reactance happens in response to threats to perceived behavioral freedoms and the individual may experience increased desire for the lost freedom (Wallston, 1992). The scale has demonstrated adequate internal consistency of .76 for affective reactance and .62 for cognitive reactance (De las Cuevas, Penate, Betancort & de Rivera, 2014).

Procedure

Professionals of Health Service from Nuestra Senora de la Candelaria Hospital (Canary Islands, Spain) were responsible for informing patients about the research. After signing the informed consent, different sociodemographic and clinical characteristics were recorded and the patients received an assessment protocol that they answered in the waiting room of the Mental Health Unit, lasting approximately 35 minutes.

Statistical analysis

For data analysis SPSS version 21 was used. Frequencies analyses were carried out for studying the distribution of the several sociodemographic and clinical characteristics recorded. Then, to verify whether there were differences in the patients' sociodemographic and clinical variables according to their diagnosis as depressive episode or recurrent depressive disorder, [chi square] test was applied. Subsequently, Spearman (categorical variables) and Pearson correlation (continuous variables) were conducted with all participants, to analyze the association between socio-demographic and clinical variables, psychological processes and shared decision-making. To identify differences in the participants' psychological processes according to their preference in decision-making (active, collaborative or passive), a MANCOVA was performed, where age, educational level and treatment time were controlled, as they had previously shown to be correlated with preference in shared decision making. Given that there were a higher proportion of women than men diagnosed with depressive disorder, a new MANCOVA, controlling age, education and treatment time, was applied to analyze gender differences in psychological processes and shared decision-making. Finally, a hierarchical regression analyses with the step by step method was conducted, where the preference in shared decision making was taken as a criterion variable, considering it as a continuous variable (the higher the score, the greater the preference for the passive style). In the first step, age and educational level were controlled. In the second step, treatment time was included, and in the third step, measures of psychological processes (locus of control, reactance and self-efficacy) were included as predictor variables, taking each gender separately.

RESULTS

In this section, the results of the correlation analysis between sociodemographic, clinical and psychological processes with shared decision-making are presented. Next, the results of the clinical variables and psychological processes that are at the basis of shared decision making, considering gender as a moderator variable, are shown.

Relationship between sociodemographic, clinical characteristics and shared decision-making

Preliminary analysis comparing depressive episode and recurrent depressive disorder individuals showed differences in age ([chi square] (63)= 88.23, p < .05) and gender ([chi square] (1)= 17.98, p < .001). Older patients showed more recurrent depression and men presented greater acute than recurrent depression (no differences between women in the form of depression were found). There were no significant differences in educational level ([chi square] (3)= 6.43, p = .093), nor in the variable of interest, the preference in shared decision-making ([chi square] (5)= 4.83, p = .436). A MANOVA among patients with acute and recurrent depression also failed to show significant differences between groups in any of the psychological processes, Hence for the rest of the statistical analysis, the sample was taken together without making a distinction between acute and recurrent depression.

The correlational analyses showed that the preference in shared decision-making was associated with age (r = .28, p < .001) and educational level (r = -.17, p < .001). Older people preferred a more passive decision-making, while those people with a higher educational level were more active. Also, people with preferences in passive shared decision-making had more duration of psychiatric treatment (r = .09, p < .05). A preference in passive shared decision-making was related to greater doctor locus of control (r = .16, p < .001), chance locus of control (r = .11, p < .05), and lower self-efficacy (r = -.10,p < .05).

Relationship between psychological process and shared decision-making

In Table 2, the results of MANCOVA, controlling age and educational level, are shown. Significant differences were only found in doctor locus of control between the three groups of shared decision-making -active, collaborative and-passive(F(2,455) = 4.64, p < .01, [eta]2 = .02). Bonferroni post-hoc analysis showed that collaborative and passive individuals had greater doctor locus of control than active individuals.

The MANCOVA results, controlling age and educational level and taking gender as an independent variable, showed that men had a higher internal locus of control (F(1,456) = 5.08, p < .05, [eta]2 = .01) and higher cognitive reactance (F(1,456) = 3.64, p = .06, [eta]2 = .008) than women; whereas women showed greater chance locus of control (F(1,456) = 3.09, p = .08, [eta]2 = .007), although differences in cognitive reactance and chance locus of control were only marginally significant. No significant differences were found between men and women in preferred participation in shared decision-making.

Finally, in Table 3, summarized regression analyses are shown. Results indicated that only doctor locus of control predicted passive decision-making for men. In the case of women, age explained 9% of variance when entered the first step. The remaining variables, doctor locus of control, chance locus of control and low self-efficacy explained around 3% of the additional variance of passive shared decision-making preference.

Results indicated that some demographic variables were significant for shared decision-making. Also, psychological processes associated with passive or active character have been of special importance in shared decision-making of depressive individuals.

DISCUSSION

The aim of this study was to analyze the psychological processes underlying the preferences for role and participation in treatment decision making, examining the predictive capacity of these processes against sociodemographic and clinical characteristics in depressed patients.

In this study, most participants assumed a passive-collaborative or completely passive role in relation to treatment decision making, coinciding with previous studies (Arora & McHorney, 2000; Delgado, Lopez, Dios, Saletti, Gil & Puga, 2010). Some authors have reported that 98% of patients with depression and anxiety preferred a semi-passive or semi-active role during the decision-making process of their psychiatric treatment (Patel & Bakken, 2010). On the other hand, in this study there was a similar proportion of patients with acute and chronic recurrent depression and such chronicity in the diagnosis did not affect the preference in shared decision-making. Also, significant differences in age and gender between both types of diagnosis were observed: older patients showed higher rates of recurrent depression than younger ones and there was greater acute depression in men than in women.

Some sociodemographic and clinical characteristics such as age, educational level and duration of psychiatric treatment were related to preference in decision making. Results indicated that older patients and those who had spent more time in psychiatric treatment preferred a more passive role in decision-making, while the patients with higher education preferred an active role. In this sense, previous research have suggested that older people and those who have undergone long psychiatric treatment periods reported lower rates of shared decision-making (Proctor, Hasche, Morrow-Howell, Shumway & Snell, 2008; Schneider et al., 2006; Solberg, Crain, Rubenstein, Unutzer, Whitebird & Beck, 2014).

When differences in the psychological processes between patients who preferred different participation styles in decision-making were analyzed, it was found that people with a passive decision-making role showed greater doctor locus of control. Previously, Hashimoto and Fukuhara (2004) found that informational and decisional preference was associated with individual's health-related control. The remaining psychological processes analyzed in the present study, as reactance and self-efficacy, did not have a direct effect on shared decision making.

Also, the results of the present study showed that there are no gender differences in decision-making preference. Some studies have suggested that women prefer an active role in decision-making (Levinson et al., 2005), while others studies did not find gender differences for ratings of shared decision making (Swanson et al., 2007). The present study found gender differences in some psychological processes: men had more internal locus of control and cognitive reactance than women, while women had greater chance locus of control.

When the processes involved in shared decision-making for men and women separately were analyzed, gender differences were found in the weight of the sociodemographic characteristics against psychological processes for predicting the preferred style in decision-making. Only the doctor locus of control explained the passive role for men. However, age had a greater predictive capacity than the psychological processes -doctor locus of control, chance locus of control and low self-efficacy- for women. Previous studies have shown that self-evaluation and general ability perceived by the individual can be the basis to initiate or maintain a certain decision-making (Thunholm, 2004). Our results underline the need to address the shared decision-making from a differential perspective.

This study has identified the main psychological processes that are at the base of the preference for an active or passive decision-making in depressed patients. In this sense, the locus of control and self-efficacy have proven to be fundamental factors in the degree of involvement that depressive patients want to assume throughout the process of communication with their doctor. These psychological processes have showed to be more or less relevant according to gender. The findings have important clinical implications since both psychological processes can be susceptible to training, so that patients would learn skills to cope with the disease effectively and develop a stronger internal locus of control, while establishing a connection with their doctor to tackle the disease.

However, this study has some limitations. The scale used to assess preference for shared decision-making is based on a classification of patients according to their active, collaborative or passive role, but it might occur that depending on the stage of the disease, patients may wish to have a greater or lesser degree of involvement in decision making to collaborate with their treatment (Flynn, Smith & Vanness, 2006).

In this study, most participants preferred a passive rather than an active role, so it would be necessary to continue exploring which psychological processes would be at the basis of an active decision-making. Another limitation is that a correlational methodology has been employed which does not allow to establish causal relationships between the variables involved in the decision-making process.

Moreover, patients' willingness to participate in decision making could be modulated by available information about their disease as well as by the myths and misconceptions of the general population regarding the same, which might lead the psychiatric patients to feel incapable to make decisions.

A future challenge would be to increase the collaboration between psychiatrists and patients in decision making. A better training provided to medical personnel in shared decision making, as well as the initiative of patients to request information about their illness could result not only in improving the psychiatrist-patient communication but also in achieving better adherence to treatment and greater satisfaction with specialized care (Young, Bell, Epstein, Feldman & Kravitz, 2008).

http://www.dx.doi.org/10.14718/ACP.2016.19.1.11

Recibido, septiembre 11/2015

Concepto evaluacion, noviembre 4/2015

Aceptado, noviembre 20/2015

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Ascension Fumero Hernandez *, Rosario J. Marrero Quevedo, Carlos de las Cuevas Castresana, Wenceslao Penate Castro Facultad de Ciencias de la Salud--Universidad de La Laguna--Espana

* Ascension Fumero, Departamento de Psicologia Clinica, Psicobiologia y Metodologia, Facultad de Ciencias de la Salud- Seccion Psicologia. Campus de Guajara, Universidad de La Laguna 38200 Tenerife (Spain). Tel: 34-922317960. afumero@ull.es Este trabajo se ha desarrollado con el apoyo del Instituto de Salud Carlos III, FEDER Union Europea (PI10/00955)
Table 1.
Sociodemographic and clinical characteristics
of depressive patients (N = 466)

Variables               Category                Frequency   %

Age ([bar.X] =          18-30                   25          5.4
54.29 [+ or -] 13.3)
                        30-45                   76          16.5

                        45-60                   215         46.6

                        60-75                   123         26.7

                        >75                     22          4.8

Gender                  Men                     98          21.3

                        Women                   363         78.7

Educational level       Can read and write      49          10.6

                        Primary                 165         35.7

                        Secondary               150         32.5

                        University              98          21.2

Diagnosis               Depressive episode      237         51.3

                        Recurrent depressive    225         48.7
                        disorder

Psychiatric treatment
time ([bar.X] = 93.60
meses [+ or -] 97.55)

Number of drugs         0                       8           1.7

                        1                       54          11.8

                        2                       142         30.9

                        3                       132         28.8

                        4                       74          16.1

                        [greater than           49          10.7
                        or equal to] 5

Preference shared
decision-making

Active                  Active-active           3           .6

                        Active-collaborative    18          3.9

Collaborative           Collaborative-active    10          2.2

                        Collaborative-passive   294         63.6

Passive                 Passive-collaborative   22          4.8

                        Passive-passive         115         24.9

Table 2.
Differences in psychological processes according to preference
in shared decision-making controlling age, educational level
and psychiatric treatment time

                        Active     Collaborative
                        N = 21        N = 304
                        M D.T.        M D.T.

Locus-internal         4.42 1.79   3.91 1.21
Locus-doctors          4.35 1.56   5.02 1.10
Locus-chance           2.05 .83    2.42 1.17
Locus-other people     3.52 1.31   3.74 1.30
Affective reactance    3.23 1.32   3.45 1.08
Cognitive reactance    2.21 1.09   2.03 .75
Self-efficacy          3.03 .54    2.88 .68

                        Passive
                        N = 137
                        M D.T.        F      [[eta].sup.2]

Locus-internal         3.94 1.21   1.82
Locus-doctors          5.17 1.01   4.64 **
Locus-chance           2.59 1.17   1.99
Locus-other people     3.67 1.17   .52       .02
Affective reactance    3.19 1.16   1.01
Cognitive reactance    1.95 .82    .63
Self-efficacy          2.78 .70    .78

Nota: p < .05 *, p < .01 **, p < .001 ***

Tabla 3.
Summary of regression analysis of sociodemographic, clinical and
psychological process on preference in shared decision-making

                                 Men

Variable         [R.sup.2] adj   [DELTA]R   [beta]   F

Step 1:          .05             .06                 6.52 *
Locus-doctors                               .25 *
Step 1:
Age
Step 2:
Age
Locus-chance
Step 3:
Age
Locus-chance
Locus-doctors
Step 4:
Age
Locus-chance
Locus-doctors
Self-efficacy

                                            Women

Variable         [R.sup.2] adj   [DELTA]R   [beta]    F

Step 1:
Locus-doctors
Step 1:          .09             .09                  35.31 ***
Age                                         .30 ***
Step 2:          .10             .01                  20.80 ***
Age                                         .30 ***
Locus-chance                                .12 *
Step 3:          .11             .01                  15.61 ***
Age                                         .29 ***
Locus-chance                                .12 *
Locus-doctors                               .11 *
Step 4:          .12             .01                  13.05 ***
Age                                         .28 ***
Locus-chance                                .11 *
Locus-doctors                               .11 *
Self-efficacy                               -.11 *

Note: p < .05 *, p < .01 **, p< .001 ***
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Author:Hernandez, Ascension Fumero; Quevedo, Rosario J. Marrero; Castresana, Carlos de las Cuevas; Castro,
Publication:Acta Colombiana de Psicologia
Date:Jan 1, 2016
Words:5785
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