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Stopping Antidepressants and Anxiolytics as Major Concerns Reported in Online Health Communities: A Text Mining Approach.

ABSTRACT: Internet is a particularly dynamic way to quickly capture the perceptions of a population in real time. Complementary to traditional face-to-face communication, online social networks help patients to improve self-esteem and self-help.The aim of this study was to use text mining on material from an online forum exploring patients' concerns about treatment (antidepressants and anxiolytics).Concerns about treatment were collected from discussion titles in patients' online community related to antidepressants and anxiolytics. To examine the content of these titles automatically, we used text mining methods, such as word frequency in a document-term matrix and co-occurrence of words using a network analysis. It was thus possible to identify topics discussed on the forum.The forum included 2415 discussions on antidepressants and anxiolytics over a period of 3 years. After a preprocessing step, the text mining algorithm identified the 99 most frequently occurring words in titles, among which were escitalopram, withdrawal, antidepressant, venlafaxine, paroxetine, and effect. Patients' concerns were related to antidepressant withdrawal, the need to share experience about symptoms, effects, and questions on weight gain with some drugs.Patients' expression on the Internet is a potential additional resource in addressing patients' concerns about treatment. Patient profiles are close to that of patients treated in psychiatry.

SUBMITTER: Abbe A

PROVIDER: S-EPMC5673886 | biostudies-other | 2017 Oct

REPOSITORIES: biostudies-other

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Stopping Antidepressants and Anxiolytics as Major Concerns Reported in Online Health Communities: A Text Mining Approach.

Abbe Adeline A Falissard Bruno B

JMIR mental health 20171023 4

<h4>Background</h4>Internet is a particularly dynamic way to quickly capture the perceptions of a population in real time. Complementary to traditional face-to-face communication, online social networks help patients to improve self-esteem and self-help.<h4>Objective</h4>The aim of this study was to use text mining on material from an online forum exploring patients' concerns about treatment (antidepressants and anxiolytics).<h4>Methods</h4>Concerns about treatment were collected from discussion ...[more]

PMID: 29061554

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Project description:AimsTo describe the characteristics of medication administration (MA) incidents reported to have occurred in patients' own homes (reporters' profession, incident types, contributing factors, patient consequence, and most common medications involved) and to identify the connection terms related to the most common contributing factors based on free text descriptions.DesignA retrospective study using descriptive statistical analysis and text mining.MethodsMedication administration incidents (N = 19,725) reported to have occurred in patients' homes between 2013-2018 in one district in Finland were analysed, describing the data by the reporters' occupation, incident type, contributing factors, and patient consequence. SAS® Text Miner was used to analyse free text descriptions of the MA incidents to understand contributing factors, using concept linking.ResultsMost MA incidents were reported by practical (lower level) nurses (77.8%, N = 15,349). The most common category of harm was 'mild harm' (40.1%, N = 7,915) and the most common error type was omissions of drug doses (47.4%, N = 9,343). The medications most commonly described were Marevan [warfarin] (N = 2,668), insulin (N = 811), Furesis [furosemide] (N = 590), antibiotic (N = 446), and Panadol [paracetamol] (N = 416). The contributing factors most commonly reported were 'communication and flow of information' (25.5%, N = 5,038), 'patient and relatives' (22.6%, N = 4,451), 'practices' (9.9%, N = 1,959), 'education and training' (4.8%, N = 949), and 'work environment and resources' (3.0%, N = 598).ConclusionThere is need for effective communication and clear responsibilities between home care patients and their relatives and health providers, about MA and its challenges in home environments. Knowledge and skills relating to safe MA are also essential.ImpactThese findings about MA incidents that have occurred in patients' homes and have been reported by home care professionals demonstrate the need for medication safety improvement in home care.

Dataset Information

Stopping Antidepressants and Anxiolytics as Major Concerns Reported in Online Health Communities: A Text Mining Approach.

Publications

Stopping Antidepressants and Anxiolytics as Major Concerns Reported in Online Health Communities: A Text Mining Approach.

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