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Effectiveness of a personalized health profile on specificity of self-management goals among people living with HIV in Canada: findings from a blinded pragmatic randomized controlled trial

PURPOSE: To estimate among people living with chronic HIV, to what extent providing feedback on their health outcomes will affect the number and specificity of patient-formulated self-management goals. METHODS: A personalized feedback profile was produced for individuals enrolled in a Canadian HIV B...

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Detalles Bibliográficos
Autores principales: Mozafarinia, Maryam, Rajabiyazdi, Fateme, Brouillette, Marie-Josée, Fellows, Lesley K., Knäuper, Bärbel, Mayo, Nancy E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9464055/
https://www.ncbi.nlm.nih.gov/pubmed/36088501
http://dx.doi.org/10.1007/s11136-022-03245-5
Descripción
Sumario:PURPOSE: To estimate among people living with chronic HIV, to what extent providing feedback on their health outcomes will affect the number and specificity of patient-formulated self-management goals. METHODS: A personalized feedback profile was produced for individuals enrolled in a Canadian HIV Brain Health Now study. Goal specificity was measured by total number of specific words (matched to a domain-specific developed lexicon) per person-words using text mining techniques. RESULTS: Of 176 participants enrolled and randomly assigned to feedback and control groups, 110 responses were received. The average number of goals was similar for both groups (3.7 vs 3.9). The number of specific words used in the goals formulated by the feedback and control group were 642 and 739, respectively. Specific nouns and actionable verbs were present to some extent and “measurable” and “time-bound” words were mainly missing. Negative binomial regression showed no difference in goal specificity among groups (RR = 0.93, 95% CI 0.78–1.10). Goals set by both groups overlapped in 8 areas and had little difference in rank. CONCLUSION: Personalized feedback profile did not help with formulation of high-quality goals. Text mining has the potential to help with difficulties of goal evaluation outside of the face-to-face setting. With more data and use of learning models automated answers could be generated to provide a more dynamic platform. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11136-022-03245-5.