Prevention of Suicidal Behavior with Telemedicine in Patients with a Recent Suicide Attempt: Is a 6‐month Intervention Long Enough?

Gabilondo, Andrea; Aristegi, Edurne; González-Pinto, Ana; Zurimendi, José Martin; Pino, Maider Mateos del; Roca, Raquel; Zorrilla, Iñaki; Iruín, Álvaro

doi:10.1111/sltb.12576

Cited by 10 publications

(20 citation statements)

References 19 publications

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“…Sankar et al (2021) found that the intervention had high retention rates (77%), high scores on the client satisfaction questionnaire, and increased participant global scores on the working alliance inventory, which indicates a strong therapeutic alliance (Sankar et al, 2021). Similarly, Gabilondo et al (2020) found that the intervention was well-accepted and showed improved adherence to outpatient follow-up. However, it is important to note that some studies found worse results in preventing suicidality when programmes do not last 12 months or more.…”

Section: Discussionmentioning

confidence: 84%

The effectiveness of telehealth interventions in suicide prevention: A systematic review and meta-analysis

Shoib,

Shaheen,

Anwar

et al. 2023

Int J Soc Psychiatry

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Background: Suicidal attempt is a significant risk factor for future attempts, with the highest risk during the first-year post-suicide. Telepsychiatry has shown promise by providing easy access to evidence-based interventions during mental health crises. Aims: investigation the effectiveness of telehealth interventions in suicide prevention Methods: Four electronic databases (PubMed, Scopus, Web of Science, and Ovid) were systematically searched for studies on patients undergoing telepsychiatry intervention (TPI) up to June 2022. Following PRISMA guidelines, a systematic review and meta-analysis were conducted to investigate the effectiveness of telehealth interventions in suicide prevention. Continuous data were pooled as standardised mean difference (SMD), and dichotomous data were pooled as risk ratio using the random effects model with the corresponding 95% confidence intervals (CI). Results: Sixteen studies were included in the review. Most studies were case-control and randomised controlled trials conducted in Europe and North America. The findings of the studies generally showed that TPIs are effective in reducing suicide rates (odds ratio = 0.68; 95% CI [−0.47, 0.98], p = .04) and suicidal reattempts. The interventions were also found to be well-accepted, with high retention rates. Conclusion: Our results suggest that TPIs are well-accepted and effective in reducing suicide rates and reattempts. It is recommended to maintain telephone follow-ups for at least 12 months. Further research is needed to understand the potential of telepsychiatry in suicide prevention fully.

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Section: Discussionmentioning

confidence: 84%

The effectiveness of telehealth interventions in suicide prevention: A systematic review and meta-analysis

Shoib,

Shaheen,

Anwar

et al. 2023

Int J Soc Psychiatry

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“…Future studies should focus on the implementation and validation of these tools in real-world clinical settings. It is worth noting that a study on telephone follow-up programs for suicide prevention concluded that longer programs lasting ≥12 months were more effective in preventing suicidality compared with shorter programs [ 76 ], highlighting the importance of longitudinal assessment and intervention for suicide prevention.…”

Section: Discussionmentioning

confidence: 99%

Acoustic Analysis of Speech for Screening for Suicide Risk: Machine Learning Classifiers for Between- and Within-Person Evaluation of Suicidality

Min¹,

Shin²,

Rhee³

et al. 2023

J Med Internet Res

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Background Assessing a patient’s suicide risk is challenging for health professionals because it depends on voluntary disclosure by the patient and often has limited resources. The application of novel machine learning approaches to determine suicide risk has clinical utility. Objective This study aimed to investigate cross-sectional and longitudinal approaches to assess suicidality based on acoustic voice features of psychiatric patients using artificial intelligence. Methods We collected 348 voice recordings during clinical interviews of 104 patients diagnosed with mood disorders at baseline and 2, 4, 8, and 12 months after recruitment. Suicidality was assessed using the Beck Scale for Suicidal Ideation and suicidal behavior using the Columbia Suicide Severity Rating Scale. The acoustic features of the voice, including temporal, formal, and spectral features, were extracted from the recordings. A between-person classification model that examines the vocal characteristics of individuals cross sectionally to detect individuals at high risk for suicide and a within-person classification model that detects considerable worsening of suicidality based on changes in acoustic features within an individual were developed and compared. Internal validation was performed using 10-fold cross validation of audio data from baseline to 2-month and external validation was performed using data from 2 to 4 months. Results A combined set of 12 acoustic features and 3 demographic variables (age, sex, and past suicide attempts) were included in the single-layer artificial neural network for the between-person classification model. Furthermore, 13 acoustic features were included in the extreme gradient boosting machine learning algorithm for the within-person model. The between-person classifier was able to detect high suicidality with 69% accuracy (sensitivity 74%, specificity 62%, area under the receiver operating characteristic curve 0.62), whereas the within-person model was able to predict worsening suicidality over 2 months with 79% accuracy (sensitivity 68%, specificity 84%, area under receiver operating characteristic curve 0.67). The second model showed 62% accuracy in predicting increased suicidality in external sets. Conclusions Within-person analysis using changes in acoustic features within an individual is a promising approach to detect increased suicidality. Automated analysis of voice can be used to support the real-time assessment of suicide risk in primary care or telemedicine.

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Section: Methodological Quality Analysismentioning

confidence: 99%

“…The analysis based on the criteria already presented showed that not all the interventions had a control group to compare their effects. A proportion of 4/23 in the Spanish sample [21][22][23][24] and 5/23 in the Japanese sample [25][26][27][28][29] included a control group exempt from treatment, although some had a group that received a different treatment, with a proportion of 5/23 in the Spanish sample [30][31][32][33][34] and 3/23 in the Japanese sample [35][36][37]. While, in the Japanese sample, two articles [38,39] included the relatives of the patient, in the Spanish sample we found two articles [24,40].…”

Section: Methodological Quality Analysismentioning

confidence: 99%

Suicide Interventions in Spain and Japan: A Comparative Systematic Review

Martínez-Rives,

Martín Chaparro,

Dhungel

et al. 2024

Healthcare

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(1) Background: This systematic review presents an overview of psychological interventions in suicide published between 2013 and 2023 in Spain and Japan, sparked by Spain’s alarming recent increase in suicide rates and the potential exemplar of Japan’s reduction efforts. (2) Methods: Following the PRISMA checklist, the databases Web of Science, Scopus, PubMed, and PsycInfo were searched using the terms [(“suicide” OR “suicidal behavior” OR “suicidal attempt” OR “suicidal thought” OR “suicidal intention”) AND (“prevention” OR “intervention” OR “psychosocial treatment” OR “Dialectical Behavior Therapy” OR “Cognitive Therapy” OR “psychotherap*”)] AND [(“Spain” OR “Spanish”) OR (“Japan” OR “Japanese”)]. We included articles published in peer-reviewed academic journals, written in English, Spanish, and Japanese between 2013 and 2023 that presented, designed, implemented, or assessed psychological interventions focused on suicidal behavior. (3) Results: 46 studies were included, concerning prevention, treatment, and training interventions. The risk of bias was low in both Spanish and Japanese studies, despite the lack of randomization of the samples. We identified common characteristics, such as psychoeducation and coping skills. Assertive case management was only highlighted in Japan, making an emphasis on active patient involvement in his/her care plan. (4) Conclusions: The findings will help professionals to incorporate into their interventions broader, more comprehensive approaches to consider more interpersonal components.

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Prevention of Suicidal Behavior with Telemedicine in Patients with a Recent Suicide Attempt: Is a 6‐month Intervention Long Enough?

Cited by 10 publications

References 19 publications

The effectiveness of telehealth interventions in suicide prevention: A systematic review and meta-analysis

The effectiveness of telehealth interventions in suicide prevention: A systematic review and meta-analysis

Acoustic Analysis of Speech for Screening for Suicide Risk: Machine Learning Classifiers for Between- and Within-Person Evaluation of Suicidality

Suicide Interventions in Spain and Japan: A Comparative Systematic Review

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