Pilot trials in health-related behavioral intervention research: Problems, solutions, and recommendations.

2020 ◽  
Vol 39 (10) ◽  
pp. 851-862
Author(s):  
Kenneth E. Freedland
Keyword(s):  
Behavioral Intervention ◽  
Intervention Research ◽  
Pilot Trials ◽  
Research Problems ◽  
Health Related

Theory-driven behavioral intervention research for the control of diarrheal diseases

1992 ◽  
Vol 35 (11) ◽  
pp. 1405-1420 ◽  
Author(s):  
Bonita Stanton ◽  
Robert Black ◽  
Patrice Engle ◽  
Gretel Pelto
Keyword(s):  
Behavioral Intervention ◽  
Intervention Research ◽  
Diarrheal Diseases

scholarly journals Selection biases in technology-based intervention research: patients’ technology use relates to both demographic and health-related inequities

2019 ◽  
Vol 26 (8-9) ◽  
pp. 835-839 ◽  
Author(s):  
Tammy Toscos ◽  
Michelle Drouin ◽  
Jessica Pater ◽  
Mindy Flanagan ◽  
Rachel Pfafman ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Technology Use ◽  
Intervention Group ◽  
Patient Activation ◽  
Intervention Research ◽  
The Internet ◽  
Health Records ◽  
Cardioverter Defibrillator ◽  
Health Related ◽  
Methodological Reflection

Abstract Objective Researchers conduct studies with selection biases, which may limit generalizability and outcomes of intervention research. In this methodological reflection, we examined demographic and health characteristics of implantable cardioverter defibrillator patients who were excluded from an informatics intervention due to lack of access to a computer and/or the internet. Materials and Methods Using information gathered from surveys and electronic health records, we compared the intervention group to excluded patients on demographic factors, computer skills, patient activation, and medical history. Results Excluded patients were older, less educated, less engaged and activated in their health, and had worse health (ie, more medical comorbidities) than nonexcluded patients. Discussion Although excluded from the intervention based solely on lack of access to a computer and/or internet, excluded patients may have needed the intervention more because they were sicker with more comorbidities. Conclusion Researchers must be mindful of enrollment biases and demographic and health-related inequities that may exist during recruitment for technology-based interventions.

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