Abstract
ObjectivesPoor symptom appraisal (detection, interpretation and response to symptoms) plays a major role in prolonged prediagnosis interval in various health conditions. Theories and models have been proposed to study the symptom appraisal process but how they could be employed to improve symptom appraisal remains unclear. We therefore aimed to review approaches to improving symptom appraisal in the literature and to develop a theoretical framework that could guide the development of approaches to improving symptom appraisal among individuals in the general population.DesignSystematic review.Data sourcesMedline, Web of Science, PsycINFO, Embase, CINAHL and Scopus were searched from inception to 30 March 2021.Eligibility criteriaWe included original articles in English in which approaches to improve the detection, interpretation or response to symptoms for symptomatic individuals were described. We excluded articles in which approaches were developed to improve symptom appraisal among healthcare professionals.Data extraction and synthesisA predefined data extraction form was used to extract the development, characteristics and evaluation of approaches to improving symptom appraisal. This formed the basis for the narrative synthesis.ResultsOf 19 046 publications identified from the literature search, 112 were selected for full-text review and 29 approaches comprising provision of knowledge of symptoms/signs and additional components (eg, symptom self-examination and comparison) for symptom appraisal were included in the synthesis. Less than half (41.4%) of these approaches were developed based on theories/models. Interestingly, despite the variety of theories/models adopted in developing these approaches, the components of these approaches were similar.ConclusionSymptom appraisal is an essential process in a patient’s journey that can be targeted to facilitate early diagnosis but is largely unstudied. Building on the literature, we proposed a theoretical framework and approaches to improving symptom appraisal. This could facilitate early identification of a variety of health conditions in the general population.Trial registration numberCRD42021279500.
Funder
SingHealth Duke-NUS Academic Medicine Research Grant
Goh Cheng Liang Rheumatology ARISE (Advancing Research and Innovation with Synergistic Expertise) Programme Fund
Cited by
2 articles.
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