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Record W3033108140 · doi:10.2196/18259

Guided Self-Help Behavioral Activation Intervention for Geriatric Depression: Protocol for Pilot Randomized Controlled Trial

2020· article· en· W3033108140 on OpenAlexvenueno aff
Xiaoxia Wang, Xiaoyan Zhou, Hui Yang

Bibliographic record

VenueJMIR Research Protocols · 2020
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
FundersArmy Medical University
KeywordsRandomized controlled trialIntervention (counseling)Protocol (science)Depression (economics)MedicineBehavioral activationPhysical therapyPsychologyClinical psychologyGerontologyPsychiatryAlternative medicineCognition

Abstract

fetched live from OpenAlex

BACKGROUND: Aging is a social concern. The increased incidence of depression in older populations in China poses a challenge to the health care system. Older adults who are depressed often suffer from a lack of motivation. Behavioral activation treatment, an evidence-based guided self-help treatment, is effective in reducing anhedonia and amotivation in depression; however, the efficacy of guided self-help behavioral activation in older adults with depression is not yet known. OBJECTIVE: The aim of this study is to pilot a self-help guided intervention for the treatment of depression in older adults. METHODS: This study has been designed as a pilot randomized controlled trial with inpatients (n=60; to be randomly allocated 1:1) between the ages of 60 and 70 and who have major depressive disorder. Patients attending clinical psychological clinics at the Mental Health Center of Chongqing will be randomized to either receive guided self-help behavioral activation (intervention) or to be on a 6-week waiting list (control). Participants in the treatment group will receive 6 sessions of guided self-help behavioral activation delivered over the telephone. The waiting list control group will receive the intervention after a period of 6 weeks. Exclusion criteria will be individuals who are at significant risk of harming themselves or others, who have a primary mental health disorder other than depression, or who have an intellectual disability that would hamper their ability to participate in the intervention. Effects of the treatment will be observed using outcomes in 3 domains: (1) clinical outcomes (symptom severity, recovery rate), (2) process variables (patient satisfaction, attendance, dropout), and (3) economic outcomes (cost and resource use). We will also examine mediators of outcomes in terms of patient variables (behavioral activation or inhibition motivation). We hypothesize that guided self-help behavioral activation will have a beneficial effect. RESULTS: The study was approved by the research ethics committee of the Mental Health Center of Chongqing in November 2019. As of July 2020, recruitment had not yet begun. Data collection is expected to be completed by December 2020. Data analysis is expected to be completed by June 2021. Results will then be disseminated to patients, to the public, to clinicians, and to researchers through publications in journals and presentations at conferences. CONCLUSIONS: This will be the first study in China to investigate guided self-help interventions for patients who are older adults and who are depressed, a group which is currently underrepresented in mental health research. The intervention is modular and adapted from an empirically supported behavioral activation treatment for depression. The generalizability and broad inclusion criteria are strengths. TRIAL REGISTRATION: Chinese Clinical Trial Register ChiCTR1900026066; http://www.chictr.org.cn/showprojen.aspx?proj=43548. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/18259.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.071
Threshold uncertainty score0.237

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.017
Meta-epidemiology (narrow)0.0060.003
Meta-epidemiology (broad)0.0120.005
Bibliometrics0.0020.003
Science and technology studies0.0030.003
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0710.009

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.402
GPT teacher head0.635
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2020
Admission routes1
Has abstractyes

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