Evidence map›Paper›PMID 40372941›Full record

ArticleJMIR human factors2025

Mobile Therapeutic Attention for Treatment-Resistant Schizophrenia (m-RESIST) Solution for Improving Clinical and Functional Outcomes in Treatment-Resistant Schizophrenia: Prospective, Multicenter Efficacy Study.

Jussi Seppälä, Eva Grasa, Anna Alonso-Solis, Alexandra Roldan-Bejarano, Marianne Haapea, Matti Isohanni, Jouko Miettunen, Johanna Caro Mendivelso, Cari Almazán, Katya Rubinstein and 10 more

Abstract readMulticenter Study
In one paragraph

Article in JMIR human factors, 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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0citing papers 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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

Corrections and comments

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

20 authors.

Jussi SeppäläSocial Insurance Institution of Finland, Suokatu 40, Kuopio, 50700, Finland, 358 0413172293.ORCID 0000-0002-8752-2041
Eva GrasaMental Health, Institut de Recerca Sant Pau IR SANT PAU, SantQuintí 77-79, Barcelona, Spain.ORCID 0000-0003-1100-7489
Anna Alonso-SolisCentro de Investigación Biomédica en Red de Salud Mental CIBERSAM, Madrid, Spain.ORCID 0000-0002-5393-9391
Alexandra Roldan-BejaranoMental Health, Institut de Recerca Sant Pau IR SANT PAU, SantQuintí 77-79, Barcelona, Spain.ORCID 0000-0001-9905-3943
Marianne HaapeaResearch Unit of Population Health, University of Oulu, Oulu, Finland.ORCID 0000-0002-3989-9354
Matti IsohanniResearch Unit of Population Health, University of Oulu, Oulu, Finland.ORCID 0000-0002-3692-8228
Jouko MiettunenResearch Unit of Population Health, University of Oulu, Oulu, Finland.ORCID 0000-0003-0575-2669
Johanna Caro MendivelsoAgency for Health Quality and Assessment of Catalonia AQuAS, Barcelona, Spain.ORCID 0000-0001-6405-6239
Cari AlmazánAgency for Health Quality and Assessment of Catalonia AQuAS, Barcelona, Spain.ORCID 0000-0001-8556-0792
Katya RubinsteinThe Gertner Institute of Epidemiology and Health Policy Research, Sheba Medical Center, Tel Aviv University, Tel Aviv, Israel.ORCID 0000-0003-2875-4456
Asaf CaspiThe Gertner Institute of Epidemiology and Health Policy Research, Sheba Medical Center, Tel Aviv University, Tel Aviv, Israel.ORCID 0000-0003-1205-6557
Zolt UnokaDepartment of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary.ORCID 0000-0003-0103-5064
Kinga FarkasDepartment of Psychiatry and Psychotherapy, Semmelweis University, Budapest, Hungary.ORCID 0000-0002-1125-3957
Elisenda ReixachTicSalut Health Department, Generalitat de Catalunya, Barcelona, Spain.ORCID 0000-0001-8557-0771
Jesus BerdunDigital Health Unit, Hospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau IIB SANT PAU, Barcelona, Spain.ORCID 0000-0002-5955-9920
Judith UsallCentro de Investigación Biomédica en Red de Salud Mental CIBERSAM, Madrid, Spain.ORCID 0000-0002-1746-7737
Susana OchoaCentro de Investigación Biomédica en Red de Salud Mental CIBERSAM, Madrid, Spain.ORCID 0000-0001-6792-1080
Iluminada Corripio *Centro de Investigación Biomédica en Red de Salud Mental CIBERSAM, Madrid, Spain.ORCID 0000-0003-2562-711X
Erika Jääskeläinen *Unit of Population Health, University of Oulu, Oulu, Finland.ORCID 0000-0001-5760-7389
m-Resist Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Treatment-resistant schizophrenia (TRS) is a severe form of schizophrenia associated with low adherence to treatment and poor outcomes. Mobile health (mHealth) interventions may be effective in preventing relapses, increasing treatment adherence, and managing some of the symptoms of schizophrenia. Mobile therapeutic attention for treatment-resistant schizophrenia (m-RESIST) is an innovative mHealth developed specifically for TRS. Objective: We aim to evaluate the effects of m-RESIST on the clinical and functional outcomes and on the perceived quality of life in people with TRS. Methods: A feasibility study without a control group was performed to test the m-RESIST solution on patients with TRS. Participants were recruited from Spain, Israel, and Hungary. This study's population (N=31) followed 3 months of intervention. The m-RESIST was configured by an app, a wearable, and a web-based platform. The severity of symptoms was evaluated by using the Positive and Negative Syndrome Scale (PANSS) and the Clinical Global Impression-Schizophrenia (CGI-SCH) scale. Functionality was assessed by the Global Assessment of Functioning and perceived quality of life was evaluated by the EuroQol visual analogue scale (EQ-VAS). Results: Significant reductions were found in symptoms from pretrial to posttrial on the PANSS total (mean difference -7.2, 95% CI -11.1 to -3.4; P=.001), the PANSS positive (mean difference -1.36, 95% CI -2.6 to -0.1; P=.04), the PANSS negative (mean difference -2.1, 95% CI -3.1 to -1.1; P<.001), and the PANSS general symptoms (mean difference -3.8, 95% CI -6.8 to -0.8; P=.02). In almost one-fifth of the participants (6/31), the overall score for the PANSS decreased by more than 20%, which may be considered a clinically significant change. On the CGI-SCH scale, the sum of total severity of illness decreased significantly (P=.03). A decrease in the sum of positive and negative symptoms of the CGI-SCH score was also found (P=.04 and P=.03, respectively). The sum of depressive or cognitive symptoms did not change. The functionality of participants increased significantly on the Global Assessment of Functioning (P≤.001). The perceived quality of life on the EQ-VAS also improved (mean difference 6.7, 95% CI 0.5 to 12.9; P=.04). Conclusions: To our best knowledge, this was the first study to address the efficacy of the mHealth app m-RESIST on the symptoms and functional capacity and on the quality of life for people with TRS. Our preliminary findings showed that implementing the m-RESIST solution decreased the symptoms and severity of disease, and improved the functionality and perceived quality of life among those with TRS. The change of symptoms on the PANSS total may be clinically significant. Modern technologies such as mHealth interventions may be useful in treating symptoms and functionality even in TRS, which is a major clinical challenge, with usually poor outcomes. These results should be corroborated by performing a controlled trial.

Indexed as

Mobile ApplicationsSchizophrenia, Treatment-ResistantAdultFeasibility StudiesFemaleHumansHungaryIsraelMaleMiddle AgedProspective StudiesQuality of LifeSchizophreniaSpainTelemedicineTreatment Outcomeapplicationdigital healthfeasibility studymHealthmobile healthmobile phonemobile therapeutic attention for treatment-resistant schizophreniam-RESISTpsychosistreatment-resistant schizophrenia

Identifiers

PMID40372941
PMCPMC12140382

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.