Adherence predictors in an Internet-based Intervention program for depression

Castro, Adoración; López‐Del‐Hoyo, Yolanda; Peake, Christian; Mayoral, Fermín; Botella, Cristina; Garcı́a-Campayo, Javier; Baños, Rosa; Nogueira-Arjona, Raquel; Roca, Miquel; Gili, Margalida

doi:10.1080/16506073.2017.1366546

Cited by 22 publications

(24 citation statements)

References 47 publications

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“…Many of these programmes utilise cognitive-behavioural therapy strategies and are delivered in a structured format, grouping topics into approximately five or six modules designed to be accessed sequentially or to be explored freely as a user needs. 9 Frequency of logins, time spent online, number of modules or activities completed, 23 data entered, minimum number of modules required 20 as well as pages accessed and printed are common ways to measure adherence. 19,24,25 While these data may be collected, they are often not reported.…”

Section: The Concept Of Adherence and The Impact On Outcomesmentioning

confidence: 99%

“…25 Importantly, this would help determine whether early treatment improvements do influence further programme usage. 20 Currently, research on the effects of alliance on adherence in e-mental health programmes is scarce. 70,71 However, one study demonstrated a positive relationship between perceived emotional connection with the programme (myCompass) and number of logins, psychoeducation modules completed and frequency of self-monitoring.…”

Section: Further Evaluationsmentioning

confidence: 99%

“…The terms 'adherence', 'usage', 'engagement', 'attrition', 'compliance' and 'drop-out' are used interchangeably to describe users' interaction with online programmes. [19][20][21][22] In many e-health interventions, log data are recorded automatically and can provide objective information about how users interact with a programme. Many of these programmes utilise cognitive-behavioural therapy strategies and are delivered in a structured format, grouping topics into approximately five or six modules designed to be accessed sequentially or to be explored freely as a user needs.…”

Section: The Concept Of Adherence and The Impact On Outcomesmentioning

confidence: 99%

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Adherence to e-mental health among youth: Considerations for intervention development and research design

Achilles

Anderson

et al. 2020

DIGITAL HEALTH

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E-mental health programmes have great potential to provide young people with access to mental health support. However, it is commonly reported that adherence to these programmes is low. Low adherence can be problematic, particularly if young people do not receive the full benefits of a programme. In a research trial setting, non-adherence to treatment recommendations can prevent researchers from drawing strong conclusions about effectiveness. Although adherence has been recognised as an issue in need of attention, many of the reviews available are focused on adults and lack clear direction towards what strategies to employ. This paper presents a broad review of the adherence literature, focusing on factors associated with improving adherence to e-mental health among youth. Our view on the key elements to improve adherence identified from the existing literature are presented, and key recommendations for e-mental health intervention design are provided. These include: developing and communicating adherence guidelines based on individuals’ needs and symptom severity, including customisable features to provide a tailored experience and promote a sense of agency, including engagement checks and adopting a user-centred approach by utilising strategies such as co-design. This paper provides guidance to intervention designers and researchers by outlining recommendations and considerations for intervention development and research design.

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Section: The Concept Of Adherence and The Impact On Outcomesmentioning

confidence: 99%

Section: Further Evaluationsmentioning

confidence: 99%

Section: The Concept Of Adherence and The Impact On Outcomesmentioning

confidence: 99%

See 1 more Smart Citation

Adherence to e-mental health among youth: Considerations for intervention development and research design

Achilles

Anderson

et al. 2020

DIGITAL HEALTH

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“…A large body of research has focused on the study of adherence predictors in the past years [21,[24][25][26][27][28][29][30][31]. Nevertheless, the results are contradictory.…”

Section: Introductionmentioning

confidence: 99%

Predictors of Adherence in Three Low-Intensity Intervention Programs Applied by ICTs for Depression in Primary Care

Castro

García‐Palacios

López‐Del‐Hoyo

et al. 2021

IJERPH

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Depression is one of the most common disorders in psychiatric and primary care settings, and is associated with disability, loss in quality of life, and economic costs. Internet-based psychological interventions have been shown to be effective in depression treatment but present problems with a low degree of adherence. The main aim of this study is to analyze the adherence predictors in three low-intensity interventions programs applied by Information and Communication Technologies (ICTs) for depression. A multi-center, randomized, controlled clinical trial was conducted with 164 participants with depression, who were allocated to: Healthy Lifestyle Program, Positive Affect Promotion Program or Mindfulness Program. Sociodemographic characteristics, Patient Health Questionnaire-9, Visual Analog Scale, Short Form Health Survey, Positive and Negative Affect Schedule, Five Facets Mindfulness Questionnaire, Pemberton Happiness Index and Treatment Expectancy Questionnaire were used to study adherence. Results showed that positive affect resulted in a predictor variable for Healthy Lifestyle Program and Positive Affect Promotion Program. Perceived health was also a negative adherence predictor for the Positive Affect Promotion Program. Our findings demonstrate that there are differences in clinical variables between treatment completers and non-completers and we provide adherence predictors in two intervention groups. Although new additional predictors have been examined, further research is essential in order to improve tailored interventions and increase adherence treatment.

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“…[ 31 ] There is evidence that psychotherapy delivered by telephone or online may be useful for patients with depression, but less information is available regarding the use of Internet-based programs that focus on lifestyle in health emergency situations in which people are required to restrict their mobility and maintain physical distance. [ 32 , 33 ] As far as we are aware, no previous studies have examined the effect of this approach for patients with TRD.…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of a healthy lifestyle promotion program as adjunctive teletherapy for treatment-resistant major depression during COVID 19 pandemic

Navarro

Yáñez²,

Garcia

et al. 2020

Medicine

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Introduction: Treatment-resistant depression (TRD) has a high prevalence and can be exacerbated by poor physical health and economic hardships, which have become common stressors during the current COVID-19 pandemic. The therapeutic approaches used to treat these patients are not always available, may be not be accepted by some patients, and often require face-to-face interactions. Objective: The main aim of this study will be to evaluate the effectiveness of an Internet-based adjuvant lifestyle-based intervention for patients with TRD. Methods: This will be a parallel, randomized, and controlled clinical trial. A total of 180 patients with TRD will be randomly allocated (1:1:1) to 1 of 3 groups: treatment prescribed by the mental health team and written suggestions for lifestyle changes (placebo control group); treatment prescribed by the mental health team, written suggestions for lifestyle changes, and an 8-week mindfulness-based cognitive therapy program (active control group); or treatment prescribed by the mental health team, written suggestions for lifestyle changes, and an 8-week lifestyle change promotion program (intervention group). We will perform this study during the COVID-19 pandemic, and will administer interventions by teletherapy, and contact participants by telephone calls, text messages, and/or teleconferences. We will collect patient data using questionnaires administered at baseline, immediately after the intervention, and after 6 and 12 months. The primary outcome will be score on the Beck Depression Inventory-II. The secondary outcomes will be score on the Clinical Global Impressions Scale (used to quantify and track patient progress and treatment response over time) and health-related quality of life measured using the European Quality of Life-5 Dimensions Questionnaire. Discussion: Patients with TRD are especially vulnerable when face-to-face psychotherapy is unavailable. The main strength of the proposed study is the novelty of the intervention to be used as an adjuvant therapy. Our results may provide guidance for treatment of patients with TRD in future situations that require lockdown measures. ClinicalTrials registration number: NCT04428099

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Adherence predictors in an Internet-based Intervention program for depression

Cited by 22 publications

References 47 publications

Adherence to e-mental health among youth: Considerations for intervention development and research design

Adherence to e-mental health among youth: Considerations for intervention development and research design

Predictors of Adherence in Three Low-Intensity Intervention Programs Applied by ICTs for Depression in Primary Care

Effectiveness of a healthy lifestyle promotion program as adjunctive teletherapy for treatment-resistant major depression during COVID 19 pandemic

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