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Operationalizing Engagement With an Interpretation Bias Smartphone App Intervention: Case Series.
Ramadurai, Ramya; Beckham, Erin; McHugh, R Kathryn; Björgvinsson, Thröstur; Beard, Courtney.
Afiliação
  • Ramadurai R; Department of Psychology, American University, Washington, DC, United States.
  • Beckham E; Cognition and Affect Research and Education Lab, McLean Hospital, Belmont, MA, United States.
  • McHugh RK; Division of Alcohol, Drugs, and Addiction, McLean Hospital, Harvard Medical School, Belmont, MA, United States.
  • Björgvinsson T; Behavioral Health Partial Hospital Program, McLean Hospital, Harvard Medical School, Belmont, MA, United States.
  • Beard C; Cognition and Affect Research and Education Lab, McLean Hospital, Belmont, MA, United States.
JMIR Ment Health ; 9(8): e33545, 2022 Aug 17.
Article em En | MEDLINE | ID: mdl-35976196
ABSTRACT

BACKGROUND:

Engagement with mental health smartphone apps is an understudied but critical construct to understand in the pursuit of improved efficacy.

OBJECTIVE:

This study aimed to examine engagement as a multidimensional construct for a novel app called HabitWorks. HabitWorks delivers a personalized interpretation bias intervention and includes various strategies to enhance engagement such as human support, personalization, and self-monitoring.

METHODS:

We examined app use in a pilot study (n=31) and identified 5 patterns of behavioral engagement consistently low, drop-off, adherent, high diary, and superuser.

RESULTS:

We present a series of cases (5/31, 16%) from this trial to illustrate the patterns of behavioral engagement and cognitive and affective engagement for each case. With rich participant-level data, we emphasize the diverse engagement patterns and the necessity of studying engagement as a heterogeneous and multifaceted construct.

CONCLUSIONS:

Our thorough idiographic exploration of engagement with HabitWorks provides an example of how to operationalize engagement for other mental health apps.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: JMIR Ment Health Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: JMIR Ment Health Ano de publicação: 2022 Tipo de documento: Article