Laurence Tan1, Hui Jin Toh2, Lai Kiow Sim3, James Alvin Low4. 1. 1 Laurence Tan, MBBS, MMed (FM), Department of GeriCare@North, Khoo Teck Puat Hospital, Singapore; Department of Geriatric Medicine and Palliative Care, Khoo Teck Puat Hospital, Singapore; Department of Education Research, Geriatric and Education Research Institute, Singapore. 2. 2 Hui Jin Toh, B Eng (Hons), Department of GeriCare@North, Khoo Teck Puat Hospital, Singapore; Department of Education Research, Geriatric and Education Research Institute, Singapore. 3. 3 Lai Kiow Sim, BSc (Nursing), Department of Geriatric Medicine and Palliative Care, Khoo Teck Puat Hospital, Singapore. 4. 4 James Alvin Low, MBBS, FRCP (Edin), FAMS, Department of GeriCare@North, Khoo Teck Puat Hospital, Singapore; Department of Geriatric Medicine and Palliative Care, Khoo Teck Puat Hospital, Singapore; Department of Education Research, Geriatric and Education Research Institute, Singapore.
Abstract
BACKGROUND: The current screening tools for depression can be tedious to administer, especially in the elderly population with hearing impairment and/or limited proficiency in English language. OBJECTIVES: To look at the feasibility of using emoticon as a screening and assessment tool for depression in the elderly. DESIGN: Cross-sectional study. METHOD: A total of 77 elderly patients completed the study from June 2014 to August 2015 in a general geriatric outpatient clinic of an acute care hospital in Singapore. Patients rated their mood using an emoticon scale, which ranges from 1 ( most happy face) to 7 ( most sad face). Depression was assessed using the Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV) criteria as the gold standard. Sensitivity and specificity for depression were calculated for the cutoff scores from 1 to 7 on the emoticon scale. RESULTS: The sensitivity percentages were low across all cutoff scores. The specificity was more than 90% for the cutoff score of 5 and above on the emoticon scale. However, all the patients who had depression diagnosed using the DSM-IV criteria did not have emoticon scores of 5 and above. CONCLUSIONS: The emoticon scale was easy to use, but its effectiveness in the screening of depression in the elderly needs to be explored further. The inability to use the emoticon scale as a tool may be the lack of measurements in the other domains of the DSM-IV criteria (sleep, energy, appetite, etc.), rather than failure of the emoticon scale to assess mood.
BACKGROUND: The current screening tools for depression can be tedious to administer, especially in the elderly population with hearing impairment and/or limited proficiency in English language. OBJECTIVES: To look at the feasibility of using emoticon as a screening and assessment tool for depression in the elderly. DESIGN: Cross-sectional study. METHOD: A total of 77 elderly patients completed the study from June 2014 to August 2015 in a general geriatric outpatient clinic of an acute care hospital in Singapore. Patients rated their mood using an emoticon scale, which ranges from 1 ( most happy face) to 7 ( most sad face). Depression was assessed using the Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV) criteria as the gold standard. Sensitivity and specificity for depression were calculated for the cutoff scores from 1 to 7 on the emoticon scale. RESULTS: The sensitivity percentages were low across all cutoff scores. The specificity was more than 90% for the cutoff score of 5 and above on the emoticon scale. However, all the patients who had depression diagnosed using the DSM-IV criteria did not have emoticon scores of 5 and above. CONCLUSIONS: The emoticon scale was easy to use, but its effectiveness in the screening of depression in the elderly needs to be explored further. The inability to use the emoticon scale as a tool may be the lack of measurements in the other domains of the DSM-IV criteria (sleep, energy, appetite, etc.), rather than failure of the emoticon scale to assess mood.
Entities:
Keywords:
cross-cultural issues; depression; health services; rating scale; scales
Authors: Marta Fadda; Martin Sykora; Suzanne Elayan; Milo A Puhan; John A Naslund; Stephen J Mooney; Emiliano Albanese; Rosalba Morese; Oliver Gruebner Journal: Digit Health Date: 2022-04-12