Determinants of adoption of cognitive behavioral interventions in a hospital setting: Example of a minimal-contact smoking cessation intervention for cardiology wards

https://doi.org/10.1016/j.pec.2005.04.004Get rights and content

Abstract

Objective

The aim of our study was to identify the psychological and organizational determinants of adopting a smoking cessation intervention in cardiology wards, using the Integrated Change Model (I-Change Model) as the theoretical basis.

Methods

A cross-sectional survey by means of questionnaires was conducted among the heads of all 121 cardiology wards in Dutch hospitals, of whom 77 (64%) responded.

Results

Adopters had a significantly lower level of formalization and more nurses working on the ward. Adopters also had a significantly more positive attitude towards working with the intervention, perceived more positive social influences from their direct environment and had higher self-efficacy. Psychological determinants explained adoption to a greater extent than organizational determinants did.

Conclusion

It is very important to take psychological factors into account when studying the adoption of preventive innovations and developing diffusion strategies.

Practice implications

Programs for dissemination of preventive innovations in a hospital setting should primarily focus on psychological characteristics like social influence and self-efficacy.

Introduction

Cigarette smoking is a major cause of cardiovascular disease [1], [2], and smoking cessation reduces the mortality risk of patients with coronary heart disease [3]. During hospitalization, patients are more receptive to information on smoking cessation, since they are more aware of their personal vulnerability [4], [5]. For these reasons, the opportunity to help people stop smoking during hospital admission should be seized upon.

Much research has been done into effective smoking cessation interventions for hospitalized patients [6], [7]. Despite their effectiveness, the adoption of these interventions in hospital practice often fails [7], [8]. Adoption has been studied by researchers from several disciplines, ranging from business marketing to psychology. These studies identified a wide variety of factors that might influence adoption, such as the size of the organization [9], [10], group membership [10], and innovation characteristics [11]. The problem with such studies has been that the results are difficult to extrapolate to other settings [12], [13]. Hence, research is needed to identify reasons for adoption in specific settings and specific populations.

Our study aimed to identify psychological and organizational determinants of the adoption of an intervention for smoking cessation guidance at cardiology wards. As far as we know, no other studies have been published on the adoption of preventive innovations at cardiology wards. Although we found some studies on the adoption of preventive interventions in a hospital setting [14], [15], these did not address psychological determinants.

The present study focused on a Minimal Intervention Strategy for smoking cessation for cardiac inpatients (C-MIS), which has been disseminated to Dutch cardiology wards nationwide since 1999. The C-MIS is a stepwise strategy in which cardiologists and nurses cooperate in assisting smokers to quit smoking, and was recently tested for its effectiveness [16], [17]. STIVORO, the Dutch Expert Centre on Tobacco Control, took care of the dissemination. Over a period of 4 years, STIVORO distributed information on the C-MIS through various channels, such as direct mailing, professional journals, and conferences. Training courses on how to introduce the C-MIS at the ward and how to use it were offered to cardiology nurses, and supporting materials like manuals and information brochures for patients were widely distributed.

To define the determinants of adoption of the C-MIS, we used the Integrated Change Model (I-Change Model) [18], [19]. This model integrates concepts of various cognitive models, such as the Social Cognitive Theory [20], the Theory of Planned Behavior [21], [22], the Transtheoretical Model [23], and the Precaution Adoption Model [24]. It also includes predisposing factors, like organizational factors and individual characteristics.

The I-Change Model states that behavior can be predicted by an individual's intention, which is determined by three types of motivational factors [19]. The first is an individual's attitude towards a new behavior, which is assumed to be the result of weighing the perceived pros (advantages) and cons (disadvantages) of its use. The second is the social influence encountered, i.e., norms, modeling, and pressure. The third type is that of self-efficacy expectations. The Attitude, Social Influence, and Self-Efficacy concepts have already been used to explain the adoption of various types of health behavior, like the adoption of classroom-based AIDS education [25], the adoption of hormone replacement therapy for menopausal complaints [26], and the adoption of physical activity behavior by mothers in the Women, Infants, and Children (WIC) program [27]. The I-Change Model assumes that these motivational factors are determined by various distal factors such as awareness factors (i.e., knowledge, personal relevance, and risk perceptions), information factors (the quality of messages, channels, and sources used), and predisposing factors (e.g. behavioral factors, biological factors, and social and cultural factors) [18]. Information factors were not included in our study since the possible sources from which wards could gather information on the C-MIS, with their accompanying messages and channels, were the same for all wards.

The predisposing factors were defined on the basis of the theory about decision-making processes from the organizational psychology perspective developed by Koopman and Pool [28], [29]. The applicability of this model in implementation research has been described by Willemsen et al. [30]. Koopman and Pool defined three major groups of characteristics influencing the decision-making process: the content and context of decision-making, and the decision-making style of the organization. Since in our research, the decision-making content was the same for all wards, namely introducing the C-MIS, it was not included in our study. The context consisted of characteristics of the environment (e.g., being a ward of a university hospital), the organization (e.g., ward size), and the decision-maker (e.g., age, being a smoker). Characteristics of the decision-maker belong to the behavioral and biological factors in the I-Change Model, while the organizational and environmental context and the decision-making style belong to the social and cultural factors in this model. Decision-making style may vary in terms of the level of centralization, the level of formalization, the handling of confrontation, and the way information is gathered. High levels of centralization and formalization are assumed to inhibit adoption [11].

The results of the present study can be used to develop research-based implementation strategies to further increase and facilitate adoption of interventions in hospital settings. The Integrated Change Model that we used to study adoption is presented in Fig. 1.

Section snippets

Study design and procedure

A cross-sectional study was conducted among all heads of cardiology wards in Dutch hospitals (N = 121), 4 years after the start of the nationwide dissemination of the C-MIS. Cardiology wards usually have a high level of autonomy in terms of decision-making, and both nurses and cardiologists play a major role in deciding on changes at the ward. A key person in the ward network is the head of the ward. In Dutch cardiology wards, this person most of the time works as a nurse on the ward. Nursing

Respondent characteristics

Of the 121 ward heads who received a questionnaire, 77 (64%) responded. One questionnaire was excluded from further analysis because 90% of the data was missing, reducing the total sample to 76 respondents. The sample consisted of 37% men (N = 28) and 63% women (N = 48). The mean age was 38 (S.D. = 9). The ward heads had been working on the wards for an average of 7 years (S.D. = 6) and had been working in their current profession (mostly as a nurse) for an average of 15 years (S.D. = 9). A remarkable

Discussion

The present study aimed to identify psychological and organizational determinants of the adoption of an intervention for smoking cessation guidance on cardiology wards.

The study found that psychological factors are important determinants of adoption. They were found to explain the adoption of the C-MIS to a larger extent than organizational factors.

Very few organizational factors were found to be related to adoption. A low level of formalization was found to increase the chance of adoption

References (36)

  • C.T. Orleans et al.

    A hospital quit-smoking consult service: clinical report and intervention guidelines

    Prev Med

    (1990)
  • N.A. Rigotti et al.

    Interventions for smoking cessation in hospitalised patients

    Cochrane Database Syst Rev

    (2003)
  • A. Haines et al.

    Getting research findings into practice: making better use of research findings

    Brit Med J

    (1998)
  • M.K. Moch et al.

    Size centralization and organizational adoption of innovations

    Am Sociol Rev

    (1977)
  • N.G. Castle

    Innovation in nursing homes: which facilities are the early adopters?

    Gerontologist

    (2001)
  • E.M. Rogers

    Diffusion of innovations

    (1995)
  • R. Foy et al.

    Why does primary care need more implementation research?

    Fam Pract

    (2001)
  • R.E. Glasgow et al.

    Why don’t we see more translation of health promotion research to practice? Rethinking the efficacy-to-effectiveness transition

    Am J Public Health

    (2003)
  • Cited by (25)

    • Exploring individual and contextual factors contributing to tobacco cessation intervention implementation

      2019, Addictive Behaviors
      Citation Excerpt :

      However, previous studies have identified deficiencies in implementing smoking cessation interventions in hospital settings as part of routine practice (Freund et al., 2008; Martinez et al., 2009; Ravara, Calheiros, Aguiar, & Taborda-Barata, 2012). Previous findings in health care services and implementation research have provided some insight into the most frequent barriers to the provision of smoking cessation interventions, including: [i] individual and psychological factors such as smoking by the health care provider, low motivation and confidence in providing the intervention, and lack of knowledge and training to provide such intervention (Applegate, Sheffer, Crews, Payne, & Smith, 2008; Leitlein, Smit, de Vries, & Hoving, 2012; Martinez, 2009; Sarna et al., 2009; Sarna, Wewers, Brown, Lillington, & Brecht, 2001; Smit, de Vries, & Hoving, 2013); [ii] cognitive factors such as preconceived ideas about the intervention or viewing smoking cessation interventions as time-consuming, ineffective, or intrusive to patient privacy (Godin, Belanger-Gravel, Eccles, & Grimshaw, 2008; Hall & Marteau, 2007; Vogt, Hall, & Marteau, 2005); [iii] organizational barriers such as an absence of protocols, records, educational materials for patients, or pharmacological aids (Eby, Laschober, & Muilenburg, 2014; Freund et al., 2009; Leitlein et al., 2012; Smith, Sellick, & Spadoni, 2012) and; [iv] organizational support such as social support from supervisors and/or coworkers (Choi & Kim, 2016; Laschober, Muilenburg, & Eby, 2015; Segaar, Bolman, Willemsen, & Vries, 2006). These factors have never been studied together to determine how they interact in the implementation of the 5 A's model or how they contribute to the performance of each component in the model (Fiore & Baker, 2011).

    • Factors Affecting Korean Registered Nurses' Intention to Implement Smoking Cessation Intervention

      2016, Osong Public Health and Research Perspectives
      Citation Excerpt :

      Higher total scores suggested more positive attitudes toward smoking cessation intervention. Social influence was assessed by using the Social Influence tool with three constructs (i.e., support, norms, and modeling) developed by Segaar et al [14]. Social influence was defined as the support experienced from important others in the work environment (e.g., from supervisory staff) and the behavior perceived in the work environment (e.g., of colleagues).

    • Understanding the stakeholders' intention to use economic decision-support tools: A cross-sectional study with the tobacco return on investment tool

      2016, Health Policy
      Citation Excerpt :

      We applied the I-Change Model (see Fig. 1) [14,26–28] to explain behaviour related to the uptake of any innovation like a health economic decision model, by integrating concepts of various health behaviours, – communication, and promotion models [29–33]. The I-Change model has been used widely in identifying the determinants of health behaviour and behaviour related to the uptake of health promoting interventions [34–38]. The model explains uptake of health behaviour and health behaviour promoting policies in (at least) three phases (i.e., awareness, motivation, and action phase), with each phase having phase specific determinants.

    View all citing articles on Scopus
    View full text