Abstract

Introduction: Depression is a major public health issue. One of the concerns in depression research and practice pertains to non-compliance to prescribed medications. The purpose of the study was to predict compliance with medication use for patients with depression using social cognitive theory (SCT). Based on this study it was envisaged that recommendations for interventions to enhance compliance for medication use could be developed for patients with depression. Methods: The study was conducted using cross sectional design (n=148) in southern United States with a convenience sample of clinic-based depression patients with a 37-item valid and reliable questionnaire. Sample size was calculated to be 148 using G*Power (five predictors with a 0.80 power at the 0.05 alpha level and an estimated effect size of 0.10 with an inflation by 10% for missing data). Social cognitive theory constructs of expectations, self-efficacy and self-efficacy in overcoming barriers, self-control, and environment were reified. Data were analyzed using multiple linear regression and multiple logistic regression analyses. Results: Self-control for taking medication for depression (P=0.04), expectations for taking medication for depression (P=0.025), age (P<0.0001) and race (P=0.04) were significantly related to intent for taking medication for depression (Adjusted R2 = 0.183). In race, Blacks had lower intent to take medication for depression. Conclusion: Social cognitive theory is weakly predictive with low explained variance for taking medication for depression. It needs to be bolstered by newer theories like integrative model or multi-theory model of health behavior change for designing educational interventions aimed at enhancing compliance to medication for depression.

Highlights

  • Depression is a major public health issue

  • The target population for this study consisted of all mental health patients suffering from depression at some point in their lives living in a metropolitan area in Southern United States in the metropolitan area of Jackson, Mississippi

  • For multiple linear regression the a priori criteria of probability of F to enter the predictor in the model was chosen as less than and equal to 0.05 and for removing the predictor as greater than and equal to 0.10

Read more

Summary

Introduction

Depression is a major public health issue. One of the concerns in depression research and practice pertains to non-compliance to prescribed medications. The purpose of the study was to predict compliance with medication use for patients with depression using social cognitive theory (SCT). Based on this study it was envisaged that recommendations for interventions to enhance compliance for medication use could be developed for patients with depression. Conclusion: Social cognitive theory is weakly predictive with low explained variance for taking medication for depression. It needs to be bolstered by newer theories like integrative model or multi-theory model of health behavior change for designing educational interventions aimed at enhancing compliance to medication for depression. Hospital admissions due to depression are accountable for 21.8 billion dollars of hospital cost in the United States.. Suicide is contemplated by more than 8 million people each year, suicide is attempted by more than 1 million people, and about 38,000 of those people are successful in their attempt to commit suicide. Depression claims nearly half of all suicide attempts and actual suicides in the United States.

Objectives
Methods
Results
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.