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Yehoshua I, Adler L, Hermoni SA, Mizrahi Reuveni M, Bilitzky A, Oren K, Zacay G. Smoking quit rates among patients receiving pharmacotherapy who received general practitioner counselling versus intensive counselling: a retrospective cohort study. BMC PRIMARY CARE 2022; 23:340. [PMID: 36575392 PMCID: PMC9793508 DOI: 10.1186/s12875-022-01953-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Accepted: 12/21/2022] [Indexed: 05/30/2023]
Abstract
BACKGROUND Behavioral treatments can augment the success of pharmacotherapy in smoking cessation. The aim of this study was to compare smoking quit rates between patients receiving individual counseling with their general practitioner during office visits or intensive counselling with behavioral support, both augmented by varenicline. METHODS A nationwide retrospective cohort study conducted in a large Healthcare Maintenance Organization in Israel. We selected randomly patients who filled a prescription for varenicline and received either individual consulting by their general practitioner or intensive counselling with behavioural support, and asked them to answer a questionnaire. The outcome variables were smoking cessation 26-52 weeks following the beginning of treatment and satisfaction with the process. RESULTS 870 patients were contacted and 604 agreed to participate (a response rate of 69%); 301 patients in the general practitioner group, 300 in the intensive counselling group and 3 were excluded due to missing date. The quit rate was 36.5% in the general practitioner group and 42.3% in the intensive counselling group (P = 0.147). In a logistic regression analysis, controlling for age, gender, socioeconomic status, ischemic heart disease, chronic obstructive pulmonary disease, pack years and duration of varenicline consumption, the adjusted OR for quitting in the general practitioner group was 0.79 (95% CI 0.56,1.13). The adjusted OR was higher in the group with the highest socioeconomic status at 2.06 (1.39,3.07) and a longer period of varenicline consumption at 1.30 (1.15,1.47). Age, gender and cigarette pack-years were not associated with quit rate. In the general practitioner group 68% were satisfied with the process, while 19% were not. In the intensive counselling group 64% were satisfied and 14% were not (P = 0.007). CONCLUSION We did not detect a statistically significant difference in smoking quit rates, though there was a trend towards higher quit rates with intensive counselling.
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Affiliation(s)
- Ilan Yehoshua
- Health Division, Maccabi Healthcare Services, Tel Aviv, Israel
- Department of Family Medicine, Ben-Gurion University of the Negev, Beer Sheva, Israel
| | - Limor Adler
- Health Division, Maccabi Healthcare Services, Tel Aviv, Israel.
- Department of Family Medicine, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
| | | | | | - Avital Bilitzky
- Health Division, Maccabi Healthcare Services, Tel Aviv, Israel
- Department of Family Medicine, Ben-Gurion University of the Negev, Beer Sheva, Israel
| | | | - Galia Zacay
- Department of Family Medicine, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
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Danan ER, Joseph AM, Sherman SE, Burgess DJ, Noorbaloochi S, Clothier B, Japuntich SJ, Taylor BC, Fu SS. Does Motivation Matter? Analysis of a Randomized Trial of Proactive Outreach to VA Smokers. J Gen Intern Med 2016; 31:878-87. [PMID: 27071399 PMCID: PMC4945562 DOI: 10.1007/s11606-016-3687-1] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2015] [Revised: 02/10/2016] [Accepted: 03/17/2016] [Indexed: 10/27/2022]
Abstract
BACKGROUND Current guidelines advise providers to assess smokers' readiness to quit, then offer cessation therapies to smokers planning to quit and motivational interventions to smokers not planning to quit. OBJECTIVES We examined the relationship between baseline stage of change (SOC), treatment utilization, and smoking cessation to determine whether the effect of a proactive smoking cessation intervention was dependent on smokers' level of motivation to quit. DESIGN Secondary analysis of a multicenter randomized controlled trial. PARTICIPANTS A total of 3006 current smokers, aged 18-80 years, at four Veterans Affairs (VA) medical centers. INTERVENTIONS Proactive care included proactive outreach (mailed invitation followed by telephone outreach), offer of smoking cessation services (telephone or face-to-face), and access to pharmacotherapy. Usual care participants had access to VA smoking cessation services and state telephone quitlines. MAIN MEASURES Baseline SOC measured with Readiness to Quit Ladder, and 6-month prolonged abstinence self-reported at 1 year. KEY RESULTS At baseline, 35.8 % of smokers were in preparation, 38.2 % in contemplation, and 26.0 % in precontemplation. The overall interaction between SOC and treatment arm was not statistically significant (p = 0.30). Among smokers in preparation, 21.1 % of proactive care participants achieved 6-month prolonged abstinence, compared to 13.1 % of usual care participants (OR, 1.8 [95 % CI, 1.2-2.6]). Similarly, proactive care increased abstinence among smokers in contemplation (11.0 % vs. 6.5 %; OR, 1.8 [95 % CI, 1.1-2.8]). Smokers in precontemplation quit smoking at similar rates (5.3 % vs. 5.6 %; OR, 0.9 [95 % CI, 0.5-1.9]). Within each stage, uptake of smoking cessation treatments increased with higher SOC and with proactive care as compared with usual care. LIMITATIONS Mostly male participants limits generalizability. Randomization was not stratified by SOC. CONCLUSIONS Proactive care increased treatment uptake compared to usual care across all SOC. Proactive care increased smoking cessation among smokers in preparation and contemplation but not in precontemplation. Proactively offering cessation therapies to smokers at all SOC will increase treatment utilization and population-level smoking cessation.
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Affiliation(s)
- Elisheva R Danan
- VA HSR&D Center for Chronic Disease Outcomes Research, Minneapolis VA Health Care System, Minneapolis, MN, USA
- Department of Medicine, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Anne M Joseph
- Department of Medicine, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Scott E Sherman
- VA New York Harbor Healthcare System, New York City, NY, USA
- Department of Population Health, New York University School of Medicine, New York City, NY, USA
| | - Diana J Burgess
- VA HSR&D Center for Chronic Disease Outcomes Research, Minneapolis VA Health Care System, Minneapolis, MN, USA
- Department of Medicine, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Siamak Noorbaloochi
- VA HSR&D Center for Chronic Disease Outcomes Research, Minneapolis VA Health Care System, Minneapolis, MN, USA
- Department of Medicine, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Barbara Clothier
- VA HSR&D Center for Chronic Disease Outcomes Research, Minneapolis VA Health Care System, Minneapolis, MN, USA
| | - Sandra J Japuntich
- National Center for PTSD, VA Boston Healthcare System, Boston, MA, USA
- Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA
| | - Brent C Taylor
- VA HSR&D Center for Chronic Disease Outcomes Research, Minneapolis VA Health Care System, Minneapolis, MN, USA
- Department of Medicine, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Steven S Fu
- VA HSR&D Center for Chronic Disease Outcomes Research, Minneapolis VA Health Care System, Minneapolis, MN, USA.
- Department of Medicine, University of Minnesota Medical School, Minneapolis, MN, USA.
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Baker TB, Collins LM, Mermelstein R, Piper ME, Schlam TR, Cook JW, Bolt DM, Smith SS, Jorenby DE, Fraser D, Loh WY, Theobald WE, Fiore MC. Enhancing the effectiveness of smoking treatment research: conceptual bases and progress. Addiction 2016; 111:107-16. [PMID: 26581974 PMCID: PMC4681592 DOI: 10.1111/add.13154] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2015] [Revised: 04/21/2015] [Accepted: 09/08/2015] [Indexed: 12/01/2022]
Abstract
BACKGROUND AND AIMS A chronic care strategy could potentially enhance the reach and effectiveness of smoking treatment by providing effective interventions for all smokers, including those who are initially unwilling to quit. This paper describes the conceptual bases of a National Cancer Institute-funded research program designed to develop an optimized, comprehensive, chronic care smoking treatment. METHODS This research is grounded in three methodological approaches: (1) the Phase-Based Model, which guides the selection of intervention components to be experimentally evaluated for the different phases of smoking treatment (motivation, preparation, cessation, and maintenance); (2) the Multiphase Optimization Strategy (MOST), which guides the screening of intervention components via efficient experimental designs and, ultimately, the assembly of promising components into an optimized treatment package; and (3) pragmatic research methods, such as electronic health record recruitment, that facilitate the efficient translation of research findings into clinical practice. Using this foundation and working in primary care clinics, we conducted three factorial experiments (reported in three accompanying papers) to screen 15 motivation, preparation, cessation and maintenance phase intervention components for possible inclusion in a chronic care smoking treatment program. RESULTS This research identified intervention components with relatively strong evidence of effectiveness at particular phases of smoking treatment and it demonstrated the efficiency of the MOST approach in terms both of the number of intervention components tested and of the richness of the information yielded. CONCLUSIONS A new, synthesized research approach efficiently evaluates multiple intervention components to identify promising components for every phase of smoking treatment. Many intervention components interact with one another, supporting the use of factorial experiments in smoking treatment development.
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Affiliation(s)
- Timothy B. Baker
- University of Wisconsin School of Medicine and Public Health, Center for Tobacco Research and Intervention, 1930 Monroe St., Suite 200, Madison, WI 53711,University of Wisconsin School of Medicine and Public Health, Department of Medicine, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI 53705
| | - Linda M. Collins
- The Pennsylvania State University, The Methodology Center and Department of Human Development & Family Studies, 404 Health and Human Development Building, University Park, PA 16802
| | - Robin Mermelstein
- University of Illinois at Chicago Institute for Health Research and Policy 544, Westside Research Office Bldg., 1747 West Roosevelt Rd., Chicago, IL 60608
| | - Megan E. Piper
- University of Wisconsin School of Medicine and Public Health, Center for Tobacco Research and Intervention, 1930 Monroe St., Suite 200, Madison, WI 53711,University of Wisconsin School of Medicine and Public Health, Department of Medicine, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI 53705
| | - Tanya R. Schlam
- University of Wisconsin School of Medicine and Public Health, Center for Tobacco Research and Intervention, 1930 Monroe St., Suite 200, Madison, WI 53711,University of Wisconsin School of Medicine and Public Health, Department of Medicine, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI 53705
| | - Jessica W. Cook
- University of Wisconsin School of Medicine and Public Health, Center for Tobacco Research and Intervention, 1930 Monroe St., Suite 200, Madison, WI 53711,University of Wisconsin School of Medicine and Public Health, Department of Medicine, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI 53705,William S. Middleton Memorial Veterans Hospital, 2500 Overlook Terrace, Madison, WI 53705
| | - Daniel M. Bolt
- University of Wisconsin, Department of Educational Psychology, 1025 W. Johnson St., Madison, WI 53706
| | - Stevens S. Smith
- University of Wisconsin School of Medicine and Public Health, Center for Tobacco Research and Intervention, 1930 Monroe St., Suite 200, Madison, WI 53711,University of Wisconsin School of Medicine and Public Health, Department of Medicine, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI 53705
| | - Douglas E. Jorenby
- University of Wisconsin School of Medicine and Public Health, Center for Tobacco Research and Intervention, 1930 Monroe St., Suite 200, Madison, WI 53711,University of Wisconsin School of Medicine and Public Health, Department of Medicine, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI 53705
| | - David Fraser
- University of Wisconsin School of Medicine and Public Health, Center for Tobacco Research and Intervention, 1930 Monroe St., Suite 200, Madison, WI 53711,University of Wisconsin School of Medicine and Public Health, Department of Medicine, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI 53705
| | - Wei-Yin Loh
- University of Wisconsin, Department of Statistics, 1220 Medical Sciences Center 1300 University Ave., Madison, WI 53706
| | - Wendy E. Theobald
- University of Wisconsin School of Medicine and Public Health, Center for Tobacco Research and Intervention, 1930 Monroe St., Suite 200, Madison, WI 53711,University of Wisconsin School of Medicine and Public Health, Department of Medicine, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI 53705
| | - Michael C. Fiore
- University of Wisconsin School of Medicine and Public Health, Center for Tobacco Research and Intervention, 1930 Monroe St., Suite 200, Madison, WI 53711,University of Wisconsin School of Medicine and Public Health, Department of Medicine, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI 53705
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Prenger R, Pieterse ME, Braakman-Jansen LMA, van der Palen J, Christenhusz LCA, Seydel ER. Moving beyond a limited follow-up in cost-effectiveness analyses of behavioral interventions. THE EUROPEAN JOURNAL OF HEALTH ECONOMICS : HEPAC : HEALTH ECONOMICS IN PREVENTION AND CARE 2013; 14:297-306. [PMID: 22223124 PMCID: PMC3579467 DOI: 10.1007/s10198-011-0371-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2011] [Accepted: 12/02/2011] [Indexed: 05/31/2023]
Abstract
BACKGROUND Cost-effectiveness analyses of behavioral interventions typically use a dichotomous outcome criterion. However, achieving behavioral change is a complex process involving several steps towards a change in behavior. Delayed effects may occur after an intervention period ends, which can lead to underestimation of these interventions. To account for such delayed effects, intermediate outcomes of behavioral change may be used in cost-effectiveness analyses. The aim of this study is to model cognitive parameters of behavioral change into a cost-effectiveness model of a behavioral intervention. METHODS The cost-effectiveness analysis (CEA) of an existing dataset from an RCT in which an high-intensity smoking cessation intervention was compared with a medium-intensity intervention, was re-analyzed by modeling the stages of change of the Transtheoretical Model of behavioral change. Probabilities were obtained from the dataset and literature and a sensitivity analysis was performed. RESULTS In the original CEA over the first 12 months, the high-intensity intervention dominated in approximately 58% of the cases. After modeling the cognitive parameters to a future 2nd year of follow-up, this was the case in approximately 79%. CONCLUSION This study showed that modeling of future behavioral change in CEA of a behavioral intervention further strengthened the results of the standard CEA. Ultimately, modeling future behavioral change could have important consequences for health policy development in general and the adoption of behavioral interventions in particular.
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Affiliation(s)
- Rilana Prenger
- Department of Psychology, Health and Technology, University of Twente, Enschede, The Netherlands.
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Noordman J, de Vet E, van der Weijden T, van Dulmen S. Motivational interviewing within the different stages of change: an analysis of practice nurse-patient consultations aimed at promoting a healthier lifestyle. Soc Sci Med 2013; 87:60-7. [PMID: 23631779 DOI: 10.1016/j.socscimed.2013.03.019] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2012] [Revised: 11/07/2012] [Accepted: 03/15/2013] [Indexed: 11/16/2022]
Abstract
Combining the Stages of Change (SOC) model with Motivational Interviewing (MI) is seen as a helpful strategy for health care providers to guide patients in changing unhealthy lifestyle behaviour. SOC suggests that people are at different stages of motivational readiness for engaging in health behaviours and that intervention methods are most useful when tailored to a person's stage of change. However, it is unknown whether practice nurses (PNs) actually adapt their MI and more generic communication skills to a particular stage during real-life face-to-face consultations with their patients. The aim of this study was to explore whether and how PNs apply MI and general communication skills to the different SOC of patients, targeting behaviour change about smoking, alcohol use, dietary habits and/or physical activity. Real-life consultations between nineteen Dutch PNs and 103 patients were recorded on video between June 2010 and March 2011. All consultations focused on a discussion of patients' lifestyle behaviour. The Behaviour Change Counselling Index (BECCI) was used to code PNs' MI skills. Generic communication skills were rated with the MAAS-global. Patients' SOC was assessed for each consultation by observing the communication between patient and PN regarding the patient's current lifestyle behaviour. Multilevel analyses revealed that PNs adapt their MI skills to a patient's SOC to some extent. On average PNs apply MI skills more to patients in the preparation stage (P < 0.05) than during the other stages of change. PNs adjusted three MI skills and one generic communication skill to patients' SOC. This explorative study suggests that, at least to some extent, PNs intuitively assess the stage of patients' readiness to change and tailor their communication accordingly. However, differences between the stages were small. By teaching PNs to explicitly identify patients' SOC they could further enhance and adapt their MI and general communication skills to the individual.
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Affiliation(s)
- Janneke Noordman
- NIVEL (Netherlands Institute for Health Services Research), PO Box 1568, 3500 BN Utrecht, The Netherlands.
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Prenger R, Braakman-Jansen LM, Pieterse ME, van der Palen J, Seydel ER. The role of cognition in cost-effectiveness analyses of behavioral interventions. COST EFFECTIVENESS AND RESOURCE ALLOCATION 2012; 10:3. [PMID: 22380627 PMCID: PMC3311086 DOI: 10.1186/1478-7547-10-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2010] [Accepted: 03/01/2012] [Indexed: 11/13/2022] Open
Abstract
Background Behavioral interventions typically focus on objective behavioral endpoints like weight loss and smoking cessation. In reality, though, achieving full behavior change is a complex process in which several steps towards success are taken. Any progress in this process may also be considered as a beneficial outcome of the intervention, assuming that this increases the likelihood to achieve successful behavior change eventually. Until recently, there has been little consideration about whether partial behavior change at follow-up should be incorporated in cost-effectiveness analyses (CEAs). The aim of this explorative review is to identify CEAs of behavioral interventions in which cognitive outcome measures of behavior change are analyzed. Methods Data sources were searched for publications before May 2011. Results Twelve studies were found eligible for inclusion. Two different approaches were found: three studies calculated separate incremental cost-effectiveness ratios for cognitive outcome measures, and one study modeled partial behavior change into the final outcome. Both approaches rely on the assumption, be it implicitly or explicitly, that changes in cognitive outcome measures are predictive of future behavior change and may affect CEA outcomes. Conclusion Potential value of cognitive states in CEA, as a way to account for partial behavior change, is to some extent recognized but not (yet) integrated in the field. In conclusion, CEAs should consider, and where appropriate incorporate measures of partial behavior change when reporting effectiveness and hence cost-effectiveness.
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Affiliation(s)
- Rilana Prenger
- University of Twente, Department of Psychology, Health and Technology, PO Box 217, 7500 AE Enschede, The Netherlands.
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Abstract
BACKGROUND The transtheoretical model is the most widely known of several stage-based theories of behaviour. It proposes that smokers move through a discrete series of motivational stages before they quit successfully. These are precontemplation (no thoughts of quitting), contemplation (thinking about quitting), preparation (planning to quit in the next 30 days), action (quitting successfully for up to six months), and maintenance (no smoking for more than six months). According to this influential model, interventions which help people to stop smoking should be tailored to their stage of readiness to quit, and are designed to move them forward through subsequent stages to eventual success. People in the preparation and action stages of quitting would require different types of support from those in precontemplation or contemplation. OBJECTIVES Our primary objective was to test the effectiveness of stage-based interventions in helping smokers to quit. SEARCH STRATEGY We searched the Cochrane Tobacco Addiction Group's specialised register for trials, using the terms ('stage* of change', 'transtheoretical model*', 'trans-theoretical model*, 'precaution adoption model*', 'health action model', 'processes of change questionnaire*', 'readiness to change', 'tailor*') and 'smoking' in the title or abstract, or as keywords. The latest search was in August 2010. SELECTION CRITERIA We included randomized controlled trials, which compared stage-based interventions with non-stage-based controls, with 'usual care' or with assessment only. We excluded trials which did not report a minimum follow-up period of six months from start of treatment, and those which measured stage of change but did not modify their intervention in the light of it. DATA COLLECTION AND ANALYSIS We extracted data in duplicate on the participants, the dose and duration of intervention, the outcome measures, the randomization procedure, concealment of allocation, and completeness of follow up.The main outcome was abstinence from smoking for at least six months. We used the most rigorous definition of abstinence, and preferred biochemically validated rates where reported. Where appropriate we performed meta-analysis to estimate a pooled risk ratio, using the Mantel-Haenszel fixed-effect model. MAIN RESULTS We found 41 trials (>33,000 participants) which met our inclusion criteria. Four trials, which directly compared the same intervention in stage-based and standard versions, found no clear advantage for the staging component. Stage-based versus standard self-help materials (two trials) gave a relative risk (RR) of 0.93 (95% CI 0.62 to 1.39). Stage-based versus standard counselling (two trials) gave a relative risk of 1.00 (95% CI 0.82 to 1.22). Six trials of stage-based self-help systems versus any standard self-help support demonstrated a benefit for the staged groups, with an RR of 1.27 (95% CI 1.01 to 1.59). Twelve trials comparing stage-based self help with 'usual care' or assessment-only gave an RR of 1.32 (95% CI 1.17 to 1.48). Thirteen trials of stage-based individual counselling versus any control condition gave an RR of 1.24 (95% CI 1.08 to 1.42). These findings are consistent with the proven effectiveness of these interventions in their non-stage-based versions. The evidence was unclear for telephone counselling, interactive computer programmes or training of doctors or lay supporters. This uncertainty may be due in part to smaller numbers of trials. AUTHORS' CONCLUSIONS Based on four trials using direct comparisons, stage-based self-help interventions (expert systems and/or tailored materials) and individual counselling were neither more nor less effective than their non-stage-based equivalents. Thirty-one trials of stage-based self help or counselling interventions versus any control condition demonstrated levels of effectiveness which were comparable with their non-stage-based counterparts. Providing these forms of practical support to those trying to quit appears to be more productive than not intervening. However, the additional value of adapting the intervention to the smoker's stage of change is uncertain. The evidence is not clear for other types of staged intervention, including telephone counselling, interactive computer programmes and training of physicians or lay supporters. The evidence does not support the restriction of quitting advice and encouragement only to those smokers perceived to be in the preparation and action stages.
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Affiliation(s)
- Kate Cahill
- Department of Primary Health Care, University of Oxford, Rosemary Rue Building, Old Road Campus, Oxford, UK, OX3 7LF
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Theory development in health promotion: are we there yet? J Behav Med 2010; 33:259-63. [PMID: 20379800 DOI: 10.1007/s10865-010-9260-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2010] [Accepted: 03/31/2010] [Indexed: 10/19/2022]
Abstract
Theory development has not proceeded at a pace commensurate with the evolution of health promotion practice. At least three examples of this disparity are apparent: (1) theory is developed in an evidence-based paradigm rather than a practice-based paradigm, (2) a substantial majority of health behavior theories exist at the individual level, thereby neglecting contextual realities that shape behavior, and (3) "accessibility" levels of theory to practitioners may be quite low in comparison to the growing demands to prevent disease through expanding health promotion practices. The challenges of health promotion demand a great deal more attention to developing theories that reflect the reality of broad influences on health behavior. One critical question that must be answered involves setting limits regarding the realistic role of behavioral interventions in public health practice. The evolution of theory should be practice-based, largely ecological in nature, and the resulting theories should be easily accessible to practitioners.
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Getting beyond outcomes: a realist approach to help understand the impact of a nutritional intervention during smoking cessation. Eur J Clin Nutr 2009; 63:1136-42. [PMID: 19536164 DOI: 10.1038/ejcn.2009.38] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
OBJECTIVES This paper discusses the benefits that a 'realist' approach can bring to an outcome study using the example of a nutritional intervention offered as an adjunct to the existing smoking cessation programmes to limit post-cessation weight gain. SUBJECTS AND SETTING Participants of a smoking cessation programme in areas of deprivation in the north, south and west of Glasgow. RESULTS A realist approach enabled the development of a framework able to investigate both implementation and outcomes of the intervention. Drawing on theoretical and experiential knowledge, context-mechanism-outcome hypotheses were developed for further testing at later stages of evaluation. This will focus the further stages of evaluation on testing these specific hypotheses using outcome data collected at the end of the intervention. CONCLUSION Adopting such an evaluation approach enables integration of process and outcome data that will refine our understanding of contexts and mechanisms, which are associated with these behavioural changes. It can aid further policy decisions by identifying the type of participant and circumstances that are associated with positive outcomes and those subgroups of participants that can be targeted more effectively using other approaches.
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