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Identifying teachable moments for health behavior counseling in primary care.

ABSTRACT: Situations with potential to motivate positive change in unhealthy behavior have been called 'teachable moments'. Little is known about how they occur in the primary care setting.Cross-sectional observational design. Audio-recordings collected during 811 physician-patient interactions for 28 physicians and their adult patients were analyzed using conversation analysis.Teachable moments were observed in 9.8% of the cases, and share three features: (1) the presence of a concern that is salient to the patient that is either obviously relevant to an unhealthy behavior, or through conversation comes to be seen as relevant; (2) a link that is made between the patient's salient concern and a health behavior that attempts to motivate the patient toward change; and (3) a patient response indicating a willingness to discuss and commit to behavior change. Additionally, we describe phenomena related to, but not teachable moments, including teachable moment attempts, missed opportunities, and health behavior advice.Success of the teachable moment rests on the physician's ability to identify and explore the salience of patient concerns and recognize opportunities to link them with unhealthy behaviors.The skills necessary for accomplishing teachable moments are well within the grasp of primary care physicians.

SUBMITTER: Cohen DJ

PROVIDER: S-EPMC4389220 | biostudies-literature | 2011 Nov

REPOSITORIES: biostudies-literature

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Identifying teachable moments for health behavior counseling in primary care.

Cohen Deborah J DJ Clark Elizabeth C EC Lawson Peter J PJ Casucci Brad A BA Flocke Susan A SA

Patient education and counseling 20101222 2

<h4>Objective</h4>Situations with potential to motivate positive change in unhealthy behavior have been called 'teachable moments'. Little is known about how they occur in the primary care setting.<h4>Methods</h4>Cross-sectional observational design. Audio-recordings collected during 811 physician-patient interactions for 28 physicians and their adult patients were analyzed using conversation analysis.<h4>Results</h4>Teachable moments were observed in 9.8% of the cases, and share three features: ...[more]

PMID: 21183305

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Project description:OBJECTIVE:Analysis of routinely collected electronic health record (EHR) data from primary care is reliant on the creation of codelists to define clinical features of interest. To improve scientific rigour, transparency and replicability, we describe and demonstrate a standardised reproducible methodology for clinical codelist development. DESIGN:We describe a three-stage process for developing clinical codelists. First, the clear definition a priori of the clinical feature of interest using reliable clinical resources. Second, development of a list of potential codes using statistical software to comprehensively search all available codes. Third, a modified Delphi process to reach consensus between primary care practitioners on the most relevant codes, including the generation of an 'uncertainty' variable to allow sensitivity analysis. SETTING:These methods are illustrated by developing a codelist for shortness of breath in a primary care EHR sample, including modifiable syntax for commonly used statistical software. PARTICIPANTS:The codelist was used to estimate the frequency of shortness of breath in a cohort of 28?216 patients aged over 18 years who received an incident diagnosis of lung cancer between 1 January 2000 and 30 November 2016 in the Clinical Practice Research Datalink (CPRD). RESULTS:Of 78 candidate codes, 29 were excluded as inappropriate. Complete agreement was reached for 44 (90%) of the remaining codes, with partial disagreement over 5 (10%). 13?091 episodes of shortness of breath were identified in the cohort of 28?216 patients. Sensitivity analysis demonstrates that codes with the greatest uncertainty tend to be rarely used in clinical practice. CONCLUSIONS:Although initially time consuming, using a rigorous and reproducible method for codelist generation 'future-proofs' findings and an auditable, modifiable syntax for codelist generation enables sharing and replication of EHR studies. Published codelists should be badged by quality and report the methods of codelist generation including: definitions and justifications associated with each codelist; the syntax or search method; the number of candidate codes identified; and the categorisation of codes after Delphi review.

Project description:Counseling has been suggested as a promising approach for facilitating changes in health behavior. The aim of this systematic review of counseling interventions for people with COPD was to describe: 1) counseling definitions, 2) targeted health behaviors, 3) counseling techniques and 4) whether commonalities in counseling techniques were associated with improved health behaviors. Ten databases were searched for original randomized controlled trials which included adults with COPD, used the term "counseling" as a sole or component of a multifaceted intervention and were published in the previous 10 years. Data extraction, study appraisal and coding for behavior change techniques (BCTs) were completed by two independent reviewers. Data were synthesized descriptively, with meta-analysis conducted where possible. Of the 182 studies reviewed as full-text, 22 were included. A single study provided a definition for counseling. Two key behaviors were the main foci of counseling: physical activity (n=9) and smoking cessation (n=8). Six studies (27%) reported underlying models and/or theoretical frameworks. Counseling was the sole intervention in 10 studies and part of a multicomponent intervention in 12. Interventions targeting physical activity included a mean of 6.3 (±3.1) BCTs, smoking cessation 4.9 (±2.9) BCTs and other behaviors 6.5 (±3.9) BCTs. The most frequent BCTs were social support unspecified (n=22; 100%), goal setting behavior (n=11), problem-solving (n=11) and instructions on how to perform the behavior (n=10). No studies shared identical BCT profiles. Counseling had a significant positive effect for smoking cessation and positive but not significant effect for physical activity. Counseling for health behavior change was rarely defined and effectiveness varied by target behavior. Provision of specific details when reporting studies of counseling interventions (definition, BCTs, dosage) would allow clarification of the effectiveness of counseling as an approach to health behavior change in people with COPD.

Project description:BackgroundCommunity-based primary care focuses on health promotion, awareness raising, and illnesses treatment and prevention in individuals, groups, and communities. Community Health Workers (CHWs) are the leading actors in such programs, helping to bridge the gap between the population and the health system. Many mobile health (mHealth) initiatives have been undertaken to empower CHWs and improve the data collection process in the primary care, replacing archaic paper-based approaches. A special category of mHealth apps, known as mHealth Data Collection Systems (MDCSs), is often used for such tasks. These systems process highly sensitive personal health data of entire communities so that a careful consideration about privacy is paramount for any successful deployment. However, the mHealth literature still lacks methodologically rigorous analyses for privacy and data protection.ObjectiveIn this paper, a Privacy Impact Assessment (PIA) for MDCSs is presented, providing a systematic identification and evaluation of potential privacy risks, particularly emphasizing controls and mitigation strategies to handle negative privacy impacts.MethodsThe privacy analysis follows a systematic methodology for PIAs. As a case study, we adopt the GeoHealth system, a large-scale MDCS used by CHWs in the Family Health Strategy, the Brazilian program for delivering community-based primary care. All the PIA steps were taken on the basis of discussions among the researchers (privacy and security experts). The identification of threats and controls was decided particularly on the basis of literature reviews and working group meetings among the group. Moreover, we also received feedback from specialists in primary care and software developers of other similar MDCSs in Brazil.ResultsThe GeoHealth PIA is based on 8 Privacy Principles and 26 Privacy Targets derived from the European General Data Protection Regulation. Associated with that, 22 threat groups with a total of 97 subthreats and 41 recommended controls were identified. Among the main findings, we observed that privacy principles can be enhanced on existing MDCSs with controls for managing consent, transparency, intervenability, and data minimization.ConclusionsAlthough there has been significant research that deals with data security issues, attention to privacy in its multiple dimensions is still lacking for MDCSs in general. New systems have the opportunity to incorporate privacy and data protection by design. Existing systems will have to address their privacy issues to comply with new and upcoming data protection regulations. However, further research is still needed to identify feasible and cost-effective solutions.

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Identifying teachable moments for health behavior counseling in primary care.

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Identifying teachable moments for health behavior counseling in primary care.

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