Evidence map›Paper›PMID 40577266›Full record

ArticlePloS one2025

Prediction of therapeutic dropout in patients with addictions: Development and validation of the Predictors of Dropout from Addiction Treatment (PDAT) scale.

Carlos Miguel Sirvent-Ruiz, María Miranda, María de la Villa Moral-Jiménez

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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Carlos Miguel Sirvent-RuizResearch and Teaching Department, Fundación Instituto Spiral, Madrid, Spain.ORCID 0000-0002-5495-6716
María MirandaResearch and Teaching Department, Fundación Instituto Spiral, Madrid, Spain.
María de la Villa Moral-JiménezDepartment of Psychology, University of Oviedo, Oviedo, Spain.ORCID 0000-0003-2421-9675

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWithdrawal from addiction treatment is a frequent but difficult-to-predict contingency. We clarify and contextualize the concept of dropouts in addiction treatment, as well as the external and internal elements that most frequently lead to such dropouts. The main instruments used to measure dropout are summarized, after which a new tool, Predictors of Dropout from Addiction Treatment (PDAT) scale, is presented. The PDAT consists of four factors: 1) Motivation: desire to recover and to actively engage in current treatment; 2) Craving: longing for the use of substances and/or the substance addiction environment; 3) Problem awareness: level of insight, or degree of knowledge, and ability to objectify the problem and the disease, with the renunciations and limitations that this entails; and 4) Dysphoria: dyade inner restlessness - moodiness, i.e., emotional disturbance and depressive anticipation that precedes treatment withdrawal.

methodsThe sample consisted of 243 addicted subjects in residential treatment, ranging in age from 18 to 63 years (average = 38.43, standard deviation = 10.95), who completed an initial 26-item PDAT questionnaire. The factor structure of the PDAT was determined by factor analysis. Mixed effects logistic regressions and receiver operating characteristics curve (ROC) analyses were applied to assess the predictive validity of the PDAT. Results: The 13-item PDAT showed adequate reliability and convergent and discriminant validity, with both the general scale and each of its factors having predictive validity 7 and 15 days after administration.

conclusionThe scale is a useful instrument with proven clinical efficacy and brevity of application. In addition, its four factors are useful for targeting interventions based on the unbalanced factors.

Indexed as

Behavior, AddictivePatient DropoutsSubstance-Related DisordersAdolescentAdultFemaleHumansMaleMiddle AgedMotivationSurveys and QuestionnairesYoung Adult

Identifiers

PMID40577266
PMCPMC12204563

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