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Nurses' interaction styles when supporting patients in self-management: A profile approach.

Identifieur interne : 000122 ( Main/Corpus ); précédent : 000121; suivant : 000123

Nurses' interaction styles when supporting patients in self-management: A profile approach.

Auteurs : Veerle Duprez ; Jolene Van Der Kaap-Deeder ; Dimitri Beeckman ; Sofie Verhaeghe ; Maarten Vansteenkiste ; Ann Van Hecke

Source :

RBID : pubmed:32702566

Abstract

BACKGROUND

The rising attention to participation and self-regulation in chronic care requires nurses to move towards an approach in which patients' perspectives and choices are central, and in which patients' competency is fostered. According to Self-Determination Theory, nurses can differ in the way they interact with patients living with a chronic illness. That is, they can interact in an autonomy-supportive, controlling, structuring or chaotic way. However, in practice, nurses often use these styles side by side depending on personal and situational demands.

OBJECTIVE

Rooted in Self-Determination Theory, this study sought to identify distinct profiles among nurses involving the co-occurrence of autonomy support, structure, control and chaos (aim 1), and to examine whether such profiles are meaningfully driven by nurse-related indicators (aim 2).

DESIGN

A cross-sectional design with latent profile analysis.

METHODS

Data were collected using validated self-report questionnaires among nurses counselling chronically ill patients (N = 389). Latent profile analysis was performed to shed light on how nurses use different styles side by side; and subsequent MANCOVA testing was used to examine differences between the profiles in terms of nurse-related indicators.

RESULTS

Four profiles could be identified, each characterised by a unique combination of differing degrees of autonomy support, structure, control and chaos. The profiles included a motivating profile (20.31%) characterised by the dominant presence of autonomy support and structure; a demotivating chaotic profile (17.74%) characterised by the dominant presence of chaos; an active profile (24.17%) where all styles were highly present; and an undifferentiated profile (37.79%) characterised by an average presence of all styles. These four profiles were meaningfully related to a set of nurse-related indicators. Multivariate analysis (Pillai's Trace test = .38, F(15, 756) = 7.28; p < .001; η

CONCLUSION

Profiling has supported our understanding of the natural co-occurrence of more motivating and demotivating styles among nurses when counselling patients in self-managing their life with chronic illness. The pattern of retained profiles indicates that, for some nurses, it will be important to move away from controlling or chaotic interactions. Future intervention development should augment nurses' competence levels and high-quality motivation, with attention to reduce the pressure in nurses to act in a result-based manner. Profiling can also be valuable to better assign nurses to an employment in chronic care, and to support their personal professional growth.


DOI: 10.1016/j.ijnurstu.2020.103604
PubMed: 32702566

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pubmed:32702566

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<p>
<b>BACKGROUND</b>
</p>
<p>The rising attention to participation and self-regulation in chronic care requires nurses to move towards an approach in which patients' perspectives and choices are central, and in which patients' competency is fostered. According to Self-Determination Theory, nurses can differ in the way they interact with patients living with a chronic illness. That is, they can interact in an autonomy-supportive, controlling, structuring or chaotic way. However, in practice, nurses often use these styles side by side depending on personal and situational demands.</p>
</div>
<div type="abstract" xml:lang="en">
<p>
<b>OBJECTIVE</b>
</p>
<p>Rooted in Self-Determination Theory, this study sought to identify distinct profiles among nurses involving the co-occurrence of autonomy support, structure, control and chaos (aim 1), and to examine whether such profiles are meaningfully driven by nurse-related indicators (aim 2).</p>
</div>
<div type="abstract" xml:lang="en">
<p>
<b>DESIGN</b>
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<p>A cross-sectional design with latent profile analysis.</p>
</div>
<div type="abstract" xml:lang="en">
<p>
<b>METHODS</b>
</p>
<p>Data were collected using validated self-report questionnaires among nurses counselling chronically ill patients (N = 389). Latent profile analysis was performed to shed light on how nurses use different styles side by side; and subsequent MANCOVA testing was used to examine differences between the profiles in terms of nurse-related indicators.</p>
</div>
<div type="abstract" xml:lang="en">
<p>
<b>RESULTS</b>
</p>
<p>Four profiles could be identified, each characterised by a unique combination of differing degrees of autonomy support, structure, control and chaos. The profiles included a motivating profile (20.31%) characterised by the dominant presence of autonomy support and structure; a demotivating chaotic profile (17.74%) characterised by the dominant presence of chaos; an active profile (24.17%) where all styles were highly present; and an undifferentiated profile (37.79%) characterised by an average presence of all styles. These four profiles were meaningfully related to a set of nurse-related indicators. Multivariate analysis (Pillai's Trace test = .38, F(15, 756) = 7.28; p < .001; η</p>
</div>
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<p>
<b>CONCLUSION</b>
</p>
<p>Profiling has supported our understanding of the natural co-occurrence of more motivating and demotivating styles among nurses when counselling patients in self-managing their life with chronic illness. The pattern of retained profiles indicates that, for some nurses, it will be important to move away from controlling or chaotic interactions. Future intervention development should augment nurses' competence levels and high-quality motivation, with attention to reduce the pressure in nurses to act in a result-based manner. Profiling can also be valuable to better assign nurses to an employment in chronic care, and to support their personal professional growth.</p>
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