Literature DB >> 20708273

Knowledge of and attitudes towards depression and adherence to treatment: the Antidepressant Adherence Scale (AAS).

Adel Gabriel1, Claudio Violato.   

Abstract

BACKGROUND: Non-adherence to treatment can result from forgetting, carelessness, stopping the drug when feeling worse, or stopping the drug when feeling better.
OBJECTIVE: To develop and psychometrically assess a brief instrument that can be easily used in clinical practice to measure adherence to antidepressants.
METHOD: We developed the Antidepressants Adherence Scale (AAS); a self report rating scale including four items to assess the degree to which forgetting, carelessness, and stopping due to feeling worse or feeling better interfere with adherence in the last 4 weeks. Our proposed four-item adherence instrument was developed based on previous research and theory. PARTICIPANTS: Experts in mood disorders (n=12) participated in the formal validity assessment of the instrument, and the developed instrument was administered to patients who were prescribed antidepressants (n=63). All patients also completed a multiple choice question instrument to measure knowledge of depression, and a Likert self report questionnaire to assess attitudes towards depression and its treatment.
RESULTS: There was 90% agreement among experts that the items were highly relevant providing strong evidence for content validity. Also, there was empirical evidence for validity. There were significant correlations (p<0.05) between knowledge and attitude subscales and adherence items. The internal consistency reliability (Cronbach's alpha) was 0.66 for the instrument. CONCLUSION AND SIGNIFICANCE: Knowledge of and attitudes to depression and its treatment may have significant impact on the adherence to antidepressants. The AAS can be used in clinical settings (2-3 min to administer) to evaluate patients' adherence to antidepressants.
Copyright © 2010 Elsevier B.V. All rights reserved.

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Year:  2010        PMID: 20708273     DOI: 10.1016/j.jad.2010.07.013

Source DB:  PubMed          Journal:  J Affect Disord        ISSN: 0165-0327            Impact factor:   4.839


  8 in total

1.  Machine Learning for Predicting Risk of Early Dropout in a Recovery Program for Opioid Use Disorder.

Authors:  Assaf Gottlieb; Andrea Yatsco; Christine Bakos-Block; James R Langabeer; Tiffany Champagne-Langabeer
Journal:  Healthcare (Basel)       Date:  2022-01-25

2.  Attitudes and beliefs of patients with chronic depression toward antidepressants and depression.

Authors:  Sabrina Anne Jacob; Ab Fatah Ab Rahman; Mohamed Azmi Ahmad Hassali
Journal:  Neuropsychiatr Dis Treat       Date:  2015-05-27       Impact factor: 2.570

Review 3.  Understanding patients' adherence-related beliefs about medicines prescribed for long-term conditions: a meta-analytic review of the Necessity-Concerns Framework.

Authors:  Rob Horne; Sarah C E Chapman; Rhian Parham; Nick Freemantle; Alastair Forbes; Vanessa Cooper
Journal:  PLoS One       Date:  2013-12-02       Impact factor: 3.240

4.  Development of an Item Bank to Measure Medication Adherence: Systematic Review.

Authors:  Yu Heng Kwan; Livia Jia Yi Oo; Dionne Hui Fang Loh; Truls Østbye; Lian Leng Low; Hayden Barry Bosworth; Julian Thumboo; Jie Kie Phang; Si Dun Weng; Dan V Blalock; Eng Hui Chew; Kai Zhen Yap; Corrinne Yong Koon Tan; Sungwon Yoon; Warren Fong
Journal:  J Med Internet Res       Date:  2020-10-08       Impact factor: 5.428

5.  Measurement Properties of Existing Patient-Reported Outcome Measures on Medication Adherence: Systematic Review.

Authors:  Yu Heng Kwan; Si Dun Weng; Dionne Hui Fang Loh; Truls Østbye; Lian Leng Low; Hayden Barry Bosworth; Julian Thumboo; Jie Kie Phang; Livia Jia Yi Oo; Dan V Blalock; Eng Hui Chew; Kai Zhen Yap; Corrinne Yong Koon Tan; Sungwon Yoon; Warren Fong
Journal:  J Med Internet Res       Date:  2020-10-09       Impact factor: 5.428

6.  Patient-reported outcome measures to detect intentional, mixed, or unintentional non-adherence to medication: a systematic review.

Authors:  Mathumalar Loganathan Fahrni; Kamaliah Md Saman; Ali Saleh Alkhoshaiban; Faiza Naimat; Farzan Ramzan; Khairil Anuar Md Isa
Journal:  BMJ Open       Date:  2022-09-19       Impact factor: 3.006

7.  The effect of knowledge and expectations on adherence to and persistence with antidepressants.

Authors:  Sophie Claire Woodward; Bonnie Jayne Bereznicki; Juanita Louise Westbury; Luke Ryan Elliot Bereznicki
Journal:  Patient Prefer Adherence       Date:  2016-05-06       Impact factor: 2.711

8.  Identifying the Underlying Factors Associated With Patients' Attitudes Toward Antidepressants: Qualitative and Quantitative Analysis of Patient Drug Reviews.

Authors:  Maryam Zolnoori; Kin Wah Fung; Paul Fontelo; Hadi Kharrazi; Anthony Faiola; Yi Shuan Shirley Wu; Virginia Stoffel; Timothy Patrick
Journal:  JMIR Ment Health       Date:  2018-09-30
  8 in total

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