search
Back to results

Emoji-based Attention Bias Modification Training for Depressive Young Adults

Primary Purpose

Depressive Symptoms, Mood Disorders

Status
Not yet recruiting
Phase
Not Applicable
Locations
Study Type
Interventional
Intervention
Attention Bias Modification
Deep-breathing training
Sham Training
Sponsored by
Universiti Tunku Abdul Rahman
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional treatment trial for Depressive Symptoms focused on measuring Attention, Attention Bias Modification

Eligibility Criteria

18 Years - 30 Years (Adult)All SexesAccepts Healthy Volunteers

Inclusion Criteria:

  • Aged between 18 and 30 years old
  • Give informed consent

Exclusion Criteria:

  • Past or present diagnosis of other major psychiatric disorders (e.g., suicidality, substance dependence, psychosis)
  • Recently started psychotropic or medical prescriptions within the previous two weeks
  • Visual impairments that cannot be corrected with contact lenses or glasses

Sites / Locations

    Arms of the Study

    Arm 1

    Arm 2

    Arm 3

    Arm 4

    Arm Type

    Experimental

    Sham Comparator

    Active Comparator

    No Intervention

    Arm Label

    Attention Bias Modification Training

    Sham Training

    Deep-breathing training

    No-intervention control

    Arm Description

    Participants randomized to the ABMT group will undergo active attention bias modification training. The emoji-based ABMT protocol will be adapted from the attention bias modification task from Browning et al., 2012. The stimuli used during the task are pictures of emoji displaying emotional expressions that have valences that are either positive, neutral, or negative. The positive, negative and neutral emojis will be chosen from the outcome of a preliminary rating questionnaire.

    Participants in the sham control group will receive a sham version of the ABMT task. This condition is identical to the active ABM condition except for the location of the probe, which replaces the positive, negative, and neutral stimuli with equal probability. This control procedure is not expected to modify any underlying biases present.

    The protocol for the deep breathing practice will be adapted from the procedure outlined in (Cheng et al., 2019). Participants randomized to the deep breathing group will undergo mindful deep breathing practice. Participants will be required to follow an instructional video and perform mindful deep breathing. The video guide will be sent to each participant in the deep breathing group, and they will be instructed to perform the exercise once a day at any time of their choice for the 14-day period.

    Participants in the no-intervention control group will not be required to undergo any intervention.

    Outcomes

    Primary Outcome Measures

    Attention Bias Index
    The participant response times from the ABM task will be collected and used to obtain an attention bias index which is calculated using the formula: Attention bias index = ½ [RpLe - RpRe) + (LpRe - LpLe)] where R is right position, L is left position, p is the position of the probe, and e is the position of the emotional (positive/negative) stimulus. A positive score indicates a bias toward emotional stimuli, while a negative score indicates a bias away from emotional stimuli. A score of 0 indicates no bias in either direction. The higher the score value, the stronger the bias.
    Post-Intervention Event-related Potentials
    Participants' EEG signal will be obtained using a 32-channel EEG system. EEG power in all bands and the event-related potential waveform will be extracted from the signal. ERP measures are widely adopted as an objective measure of the time course of attention during the dot-probe task.
    Change from Baseline Patient Health Questionnaire-9 (PHQ-9) Score at 14 days
    The PHQ-9 is a self-administered instrument for screening and monitoring the severity of depression. The PHQ-9 uses the following scale: a score of 0 to 4 indicates a severity of "None", 5 to 9 indicates "Mild", 10 to 14 indicates "Moderate', 15 to 19 indicates "Moderately Severe", and 20 to 27 indicates "Severe".
    Change from Baseline Depression, Anxiety and Stress Scale-21 (DASS-21) Score at 14 days
    The DASS-21 is a questionnaire designed to assess the dimensions of depression, anxiety and stress. It consists of 21 self-report items. Depression severity is measured on the DASS-21 as follows: a score of 0 to 4 is labelled "Normal", 5 to 6 is "Mild", 7 to 10 is "Moderate", 11 to 13 is "Severe", and 14 and above is "Extremely Severe".

    Secondary Outcome Measures

    Heart Rate Variability
    A photoplethysmogram (PPG) will be obtained from participants to obtain heart rate and cardiac cycle data. From the cardiac cycle, the variation in the intervals between each heart beat can be retrieved, which gives the heart rate variability (HRV). HRV measures are used as an index for the activity of the parasympathetic and sympathetic nervous systems, which are associated with various psychological states.
    Hair Cortisol
    Hair samples will be collected from participants for a hair cortisol test. Approximately 20 strands of hair will be collected from the head for the test to determine the cortisol levels of the participant. Cortisol is a naturally-occurring steroid hormone that is associated with the body's stress response. Chronically high levels of cortisol increases the risk of mood disorders such as anxiety and depression.
    Pre-Intervention Event-Related Potentials
    Participants' EEG signal will be obtained using a 32-channel EEG system. EEG power in all bands and the event-related potential waveform will be extracted from the signal. ERP measures are widely adopted as an objective measure of the time course of attention during the dot-probe task.

    Full Information

    First Posted
    May 24, 2022
    Last Updated
    June 8, 2022
    Sponsor
    Universiti Tunku Abdul Rahman
    search

    1. Study Identification

    Unique Protocol Identification Number
    NCT05415306
    Brief Title
    Emoji-based Attention Bias Modification Training for Depressive Young Adults
    Official Title
    An Emoji-based Attention Bias Modification Intervention for Depressive Symptom Severity in Young Adults
    Study Type
    Interventional

    2. Study Status

    Record Verification Date
    June 2022
    Overall Recruitment Status
    Not yet recruiting
    Study Start Date
    July 2022 (Anticipated)
    Primary Completion Date
    July 2023 (Anticipated)
    Study Completion Date
    September 2024 (Anticipated)

    3. Sponsor/Collaborators

    Responsible Party, by Official Title
    Principal Investigator
    Name of the Sponsor
    Universiti Tunku Abdul Rahman

    4. Oversight

    Studies a U.S. FDA-regulated Drug Product
    No
    Studies a U.S. FDA-regulated Device Product
    No
    Data Monitoring Committee
    No

    5. Study Description

    Brief Summary
    Globally, the rates of young adults and college students reporting symptoms of depression have been rising over the past decade. There are major obstacles being faced in mental healthcare that prevents many individuals from receiving sufficient and quality mental healthcare services. Current treatments for depression are not able to target the underlying factors causing the disorder. In addition, individuals with depressive symptoms face issues with accessibility and social stigma. Hence, there has been increasing interest in behavioural and cognitive mental health interventions with the potential for remote applications. This study aims to evaluate the feasibility and acceptability of using an emoji-based attention bias modification training paradigm on depressive symptom severity compared with a deep breathing practice protocol, a sham training protocol and a control group. It is expected that participants who undergo the attention bias modification training and deep breathing training paradigms will have reduced depressive symptom scores, changes in attention bias indices, and changes in event-related potential component measures compared to participants who did not undergo the interventions.
    Detailed Description
    Depression is a common mental health disorder and is a major cause of disability worldwide. Despite the wide range of treatments currently available, many individuals with depression do not acquire treatment for the disorder. Some patients are concerned about possible negative effects of antidepressants, although there is also a high rate of discontinuation among patients on antidepressant regimens. Relapse is a common occurrence, where at least 50% of the patients who recover from the first episode of depression will experience at least one more depressive episode. The consistent preference for psychological treatments over medication gives particular relevance to research aimed at developing suitable behavioral and psychological treatments for depression. Digital mental health interventions could potentially improve access to mental health services and help overcome the stigma associated with seeking traditional mental health services. Vulnerable young people, especially individuals in rural or low-resource areas and marginalized communities face unequal access to mental health services. In contrast, there is an unprecedented surge in access to digital technology platforms and mobile devices among young adults worldwide. The mental healthcare access gap can be addressed by the opportunities provided by digital technology to provide better care for youth and young adults. The young adult demographic is a critical target group because it is the group with the highest incidence and prevalence of mood disorders. Many people often find it challenging to communicate about mental health issues, but if left unresolved, these issues can lead to deterioration of mental well-being. A growing majority of young adults have access to mobile devices and the Internet. Meta-analyses of computerized and Internet-based treatments for depression found that they significantly reduced depressive symptoms compared to control groups. However, some methodological limitations were reported by the analyses, such as lack of follow-up testing, skewed post-intervention data, and lack of participant feedback. A review by Lamb et al. (2019) on the efficacy and practicality of remote psychotherapy for depression and anxiety disorders, reported that interventions that were administered over the telephone, through video-conferencing, or online were generally effective. Remote psychotherapy was reported to improve accessibility and convenience, especially for individuals living in rural and remote areas or individuals with limited mobility. The dot-probe paradigm is a behavioral task widely employed to measure attention and perception biases. The task can be adapted in different ways to accommodate the investigation of various conditions such as generalized anxiety disorders, eating disorders, and substance use disorders. In the dot-probe task, two stimuli appear on a screen simultaneously in two separate spatial locations. One of the stimuli has an emotional valence, while the other is neutral. The stimuli then are removed, and a dot-probe appears in one of the locations where the stimuli were previously displayed. The subject's response times are recorded and a faster response to the probe when it appears in the previous location of a threatening stimulus is interpreted as vigilance for threat, indicating attentional bias. Individuals suffering from emotional disorders exhibit negative attentional biases. Notably, this negative attention bias can also be present in non-depressed individuals with high risk of developing depression, as well as individuals who have recovered from episodes of depression. In general, studies on healthy adults show that the prefrontal cortex plays a role in response inhibition, specifically the right inferior frontal cortex region. When presented with competing stimuli, certain responses need to be inhibited in order to make a decision. In the case of attention biases, the lateral prefrontal cortex contributes by modulating responses to emotional information. Deficits in response inhibition result in a bias towards certain emotional information. A common application of the dot-probe task is in attention bias modification (ABM), an experimental procedure for treatment of depression, with the intention of supplementing cognitive behavioural therapy (CBT) or as a treatment on its own. Besides treating emotional disorders, attention bias modification interventions are also being used to treat eating disorders, alcohol dependency, and social phobias. ABM procedures modify attention biases in emotional disorders, resulting in subjects learning to deploy their attention toward the more positive stimuli. A computerized attention bias modification intervention for depression involves repeatedly redirecting the attention of the subject away from emotionally relevant threat cues, and towards neutral (non-threatening) stimuli. The effects of the attention bias training are assessed by examining the motivational outcomes on the subjects (i.e. depressive assessment scores). Studies examining the effects of ABM on depressive symptoms generally found reduced symptoms where the attentional biases were successfully modified. Deep breathing is another promising approach to cognitive-behavioral interventions for mood disorders. Deep breathing exercises are known to decrease heart rate and stimulate parasympathetic relaxation. There are observable physical changes associated with breathing relaxation, such as reduced metabolism, muscle tension, brain activity and skin resistance. These effects are associated with lowered anxiety and depression, better quality of sleep, and enhanced concentration. This has led to a growing body of work regarding the use of deep breathing techniques to combat mental health symptoms associated with various physical and mental disorders. Deep breathing exercises have been employed in research on chronic cardiovascular disease, post-traumatic stress disorder (PTSD), pain management, depression, and anxiety. In most deep breathing studies, the duration and frequency of the breathing patterns are notably different across different studies. In a study on the effect of deep breathing duration on depressive symptoms by Cheng et al. (2019), it was found that deep breathing for 5, 7 and 9 minutes produced higher activation of the parasympathetic nervous system compared to the control group. However, only deep breathing durations of 7 or 9 minutes produced significantly lower self-report depressive scores, with the 9-minute group achieving a larger effect size than the 7-minute group. As for breathing frequency, a rate of 6 breaths per minute has been extensively practiced in numerous studies as it has been found to result in significant differences in heart rate variability measures compared to other rates and natural breathing rates. Attention bias modification paradigms and deep breathing exercises have potential as both standalone treatments for mood disorders and complementary regimens to pharmacotherapy. A meta-analysis has found that while psychotherapy and medication are both efficacious in improving depressive symptom severity, a combination of both provides significantly better outcomes for patients. The development of interventions such as attention bias modification and deep breathing training would contribute towards creating highly accessible tools for management and alleviation of depression symptoms. When administered in combination with other psychotherapy and antidepressant treatments, these remote interventions could improve the quality of the mental healthcare experience for patients and healthcare professionals.

    6. Conditions and Keywords

    Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
    Depressive Symptoms, Mood Disorders
    Keywords
    Attention, Attention Bias Modification

    7. Study Design

    Primary Purpose
    Treatment
    Study Phase
    Not Applicable
    Interventional Study Model
    Parallel Assignment
    Masking
    Participant
    Allocation
    Randomized
    Enrollment
    120 (Anticipated)

    8. Arms, Groups, and Interventions

    Arm Title
    Attention Bias Modification Training
    Arm Type
    Experimental
    Arm Description
    Participants randomized to the ABMT group will undergo active attention bias modification training. The emoji-based ABMT protocol will be adapted from the attention bias modification task from Browning et al., 2012. The stimuli used during the task are pictures of emoji displaying emotional expressions that have valences that are either positive, neutral, or negative. The positive, negative and neutral emojis will be chosen from the outcome of a preliminary rating questionnaire.
    Arm Title
    Sham Training
    Arm Type
    Sham Comparator
    Arm Description
    Participants in the sham control group will receive a sham version of the ABMT task. This condition is identical to the active ABM condition except for the location of the probe, which replaces the positive, negative, and neutral stimuli with equal probability. This control procedure is not expected to modify any underlying biases present.
    Arm Title
    Deep-breathing training
    Arm Type
    Active Comparator
    Arm Description
    The protocol for the deep breathing practice will be adapted from the procedure outlined in (Cheng et al., 2019). Participants randomized to the deep breathing group will undergo mindful deep breathing practice. Participants will be required to follow an instructional video and perform mindful deep breathing. The video guide will be sent to each participant in the deep breathing group, and they will be instructed to perform the exercise once a day at any time of their choice for the 14-day period.
    Arm Title
    No-intervention control
    Arm Type
    No Intervention
    Arm Description
    Participants in the no-intervention control group will not be required to undergo any intervention.
    Intervention Type
    Behavioral
    Intervention Name(s)
    Attention Bias Modification
    Intervention Description
    Attention bias modification (ABM) is a procedure for treatment of depression, with the intention of supplementing cognitive behavioural therapy (CBT) or as a treatment on its own. ABM procedures modify attention biases in emotional disorders, resulting in subjects learning to deploy their attention toward the more positive stimuli (Jonassen et al., 2018). A computerized attention bias modification intervention for depression involves repeatedly redirecting the attention of the subject away from emotionally relevant threat cues, and towards neutral (non-threatening) stimuli (Amir et al., 2009). The location of the probe will replace the relatively positive stimulus in the pair with 100% probability.
    Intervention Type
    Behavioral
    Intervention Name(s)
    Deep-breathing training
    Intervention Description
    In most deep breathing studies, participants are required to alter their breathing pattern to a specific frequency for a specific duration of time. In the present study, participants will be required to perform deep-breathing at a rate of 6 breaths per minute for 9 minutes.
    Intervention Type
    Behavioral
    Intervention Name(s)
    Sham Training
    Intervention Description
    This condition is identical to the Attention Bias Modification condition with the except of the location of the probe, which replaces the positive, negative, and neutral stimuli with equal probability. This control procedure is not expected to modify any underlying biases present.
    Primary Outcome Measure Information:
    Title
    Attention Bias Index
    Description
    The participant response times from the ABM task will be collected and used to obtain an attention bias index which is calculated using the formula: Attention bias index = ½ [RpLe - RpRe) + (LpRe - LpLe)] where R is right position, L is left position, p is the position of the probe, and e is the position of the emotional (positive/negative) stimulus. A positive score indicates a bias toward emotional stimuli, while a negative score indicates a bias away from emotional stimuli. A score of 0 indicates no bias in either direction. The higher the score value, the stronger the bias.
    Time Frame
    Up to 14 days
    Title
    Post-Intervention Event-related Potentials
    Description
    Participants' EEG signal will be obtained using a 32-channel EEG system. EEG power in all bands and the event-related potential waveform will be extracted from the signal. ERP measures are widely adopted as an objective measure of the time course of attention during the dot-probe task.
    Time Frame
    Day 14
    Title
    Change from Baseline Patient Health Questionnaire-9 (PHQ-9) Score at 14 days
    Description
    The PHQ-9 is a self-administered instrument for screening and monitoring the severity of depression. The PHQ-9 uses the following scale: a score of 0 to 4 indicates a severity of "None", 5 to 9 indicates "Mild", 10 to 14 indicates "Moderate', 15 to 19 indicates "Moderately Severe", and 20 to 27 indicates "Severe".
    Time Frame
    Baseline and Day 14
    Title
    Change from Baseline Depression, Anxiety and Stress Scale-21 (DASS-21) Score at 14 days
    Description
    The DASS-21 is a questionnaire designed to assess the dimensions of depression, anxiety and stress. It consists of 21 self-report items. Depression severity is measured on the DASS-21 as follows: a score of 0 to 4 is labelled "Normal", 5 to 6 is "Mild", 7 to 10 is "Moderate", 11 to 13 is "Severe", and 14 and above is "Extremely Severe".
    Time Frame
    Baseline and Day 14
    Secondary Outcome Measure Information:
    Title
    Heart Rate Variability
    Description
    A photoplethysmogram (PPG) will be obtained from participants to obtain heart rate and cardiac cycle data. From the cardiac cycle, the variation in the intervals between each heart beat can be retrieved, which gives the heart rate variability (HRV). HRV measures are used as an index for the activity of the parasympathetic and sympathetic nervous systems, which are associated with various psychological states.
    Time Frame
    Day 1, Day 14
    Title
    Hair Cortisol
    Description
    Hair samples will be collected from participants for a hair cortisol test. Approximately 20 strands of hair will be collected from the head for the test to determine the cortisol levels of the participant. Cortisol is a naturally-occurring steroid hormone that is associated with the body's stress response. Chronically high levels of cortisol increases the risk of mood disorders such as anxiety and depression.
    Time Frame
    Day 1
    Title
    Pre-Intervention Event-Related Potentials
    Description
    Participants' EEG signal will be obtained using a 32-channel EEG system. EEG power in all bands and the event-related potential waveform will be extracted from the signal. ERP measures are widely adopted as an objective measure of the time course of attention during the dot-probe task.
    Time Frame
    Baseline

    10. Eligibility

    Sex
    All
    Minimum Age & Unit of Time
    18 Years
    Maximum Age & Unit of Time
    30 Years
    Accepts Healthy Volunteers
    Accepts Healthy Volunteers
    Eligibility Criteria
    Inclusion Criteria: Aged between 18 and 30 years old Give informed consent Exclusion Criteria: Past or present diagnosis of other major psychiatric disorders (e.g., suicidality, substance dependence, psychosis) Recently started psychotropic or medical prescriptions within the previous two weeks Visual impairments that cannot be corrected with contact lenses or glasses

    12. IPD Sharing Statement

    Plan to Share IPD
    No
    Citations:
    Citation
    Caldwell C, Victoria HK. Breathwork in body psychotherapy: Towards a more unified theory and practice. Body, Movement and Dance in Psychotherapy. 2011; (2): 89-101.
    Results Reference
    background
    PubMed Identifier
    31508498
    Citation
    Huckvale K, Venkatesh S, Christensen H. Toward clinical digital phenotyping: a timely opportunity to consider purpose, quality, and safety. NPJ Digit Med. 2019 Sep 6;2:88. doi: 10.1038/s41746-019-0166-1. eCollection 2019.
    Results Reference
    background
    PubMed Identifier
    32739018
    Citation
    Irwin CE Jr. Using Technology to Improve the Health and Well-Being of Adolescents and Young Adults. J Adolesc Health. 2020 Aug;67(2):147-148. doi: 10.1016/j.jadohealth.2020.05.019. No abstract available.
    Results Reference
    background
    PubMed Identifier
    25869930
    Citation
    Jerath R, Crawford MW, Barnes VA, Harden K. Self-regulation of breathing as a primary treatment for anxiety. Appl Psychophysiol Biofeedback. 2015 Jun;40(2):107-15. doi: 10.1007/s10484-015-9279-8.
    Results Reference
    background
    PubMed Identifier
    23513938
    Citation
    Middleton J. Let's talk about mental health. Nurs Times. 2013 Feb 19-25;109(7):27. No abstract available.
    Results Reference
    background
    PubMed Identifier
    32457823
    Citation
    Naslund JA, Gonsalves PP, Gruebner O, Pendse SR, Smith SL, Sharma A, Raviola G. Digital Innovations for Global Mental Health: Opportunities for Data Science, Task Sharing, and Early Intervention. Curr Treat Options Psychiatry. 2019 Dec;6(4):337-351. doi: 10.1007/s40501-019-00186-8. Epub 2019 Sep 7.
    Results Reference
    background
    PubMed Identifier
    31921754
    Citation
    Rojas G, Martinez V, Martinez P, Franco P, Jimenez-Molina A. Improving Mental Health Care in Developing Countries Through Digital Technologies: A Mini Narrative Review of the Chilean Case. Front Public Health. 2019 Dec 20;7:391. doi: 10.3389/fpubh.2019.00391. eCollection 2019.
    Results Reference
    background
    PubMed Identifier
    27931196
    Citation
    Vazquez C, Blanco I, Sanchez A, McNally RJ. Attentional bias modification in depression through gaze contingencies and regulatory control using a new eye-tracking intervention paradigm: study protocol for a placebo-controlled trial. BMC Psychiatry. 2016 Dec 8;16(1):439. doi: 10.1186/s12888-016-1150-9.
    Results Reference
    background
    PubMed Identifier
    20435804
    Citation
    Wadlinger HA, Isaacowitz DM. Fixing our focus: training attention to regulate emotion. Pers Soc Psychol Rev. 2011 Feb;15(1):75-102. doi: 10.1177/1088868310365565. Epub 2010 Apr 30.
    Results Reference
    background
    PubMed Identifier
    29869819
    Citation
    Wilson D, Heaslip V, Jackson D. Improving equity and cultural responsiveness with marginalised communities: Understanding competing worldviews. J Clin Nurs. 2018 Oct;27(19-20):3810-3819. doi: 10.1111/jocn.14546. Epub 2018 Aug 1.
    Results Reference
    background
    Citation
    Zhao Q, Lu Y, Zhou C, Wang X. Effects of chronic exercise on attentional bias among individuals with methamphetamine use disorder. Psychology of Sport and Exercise. 2021; 52(8).
    Results Reference
    background
    PubMed Identifier
    12467953
    Citation
    Agelink MW, Boz C, Ullrich H, Andrich J. Relationship between major depression and heart rate variability. Clinical consequences and implications for antidepressive treatment. Psychiatry Res. 2002 Dec 15;113(1-2):139-49. doi: 10.1016/s0165-1781(02)00225-1.
    Results Reference
    result
    Citation
    Akinsola, E. F., Nwajei, A. D. Test anxiety, depression and academic performance: Assessment and management using relaxation and cognitive restructuring techniques. Psychology. 2013; 04(06), 18-24.
    Results Reference
    result
    PubMed Identifier
    19803575
    Citation
    Amir N, Beard C, Taylor CT, Klumpp H, Elias J, Burns M, Chen X. Attention training in individuals with generalized social phobia: A randomized controlled trial. J Consult Clin Psychol. 2009 Oct;77(5):961-973. doi: 10.1037/a0016685.
    Results Reference
    result
    PubMed Identifier
    28127931
    Citation
    Angermeyer MC, van der Auwera S, Carta MG, Schomerus G. Public attitudes towards psychiatry and psychiatric treatment at the beginning of the 21st century: a systematic review and meta-analysis of population surveys. World Psychiatry. 2017 Feb;16(1):50-61. doi: 10.1002/wps.20383.
    Results Reference
    result
    PubMed Identifier
    15950000
    Citation
    Aron AR, Poldrack RA. The cognitive neuroscience of response inhibition: relevance for genetic research in attention-deficit/hyperactivity disorder. Biol Psychiatry. 2005 Jun 1;57(11):1285-92. doi: 10.1016/j.biopsych.2004.10.026. Epub 2004 Dec 23.
    Results Reference
    result
    PubMed Identifier
    23046776
    Citation
    Beard C, Sawyer AT, Hofmann SG. Efficacy of attention bias modification using threat and appetitive stimuli: a meta-analytic review. Behav Ther. 2012 Dec;43(4):724-40. doi: 10.1016/j.beth.2012.01.002. Epub 2012 Jan 18.
    Results Reference
    result
    PubMed Identifier
    25894440
    Citation
    Beevers CG, Clasen PC, Enock PM, Schnyer DM. Attention bias modification for major depressive disorder: Effects on attention bias, resting state connectivity, and symptom change. J Abnorm Psychol. 2015 Aug;124(3):463-75. doi: 10.1037/abn0000049.
    Results Reference
    result
    PubMed Identifier
    11485292
    Citation
    Bernardi L, Porta C, Gabutti A, Spicuzza L, Sleight P. Modulatory effects of respiration. Auton Neurosci. 2001 Jul 20;90(1-2):47-56. doi: 10.1016/S1566-0702(01)00267-3.
    Results Reference
    result
    PubMed Identifier
    23200784
    Citation
    Britton JC, Bar-Haim Y, Clementi MA, Sankin LS, Chen G, Shechner T, Norcross MA, Spiro CN, Lindstrom KM, Pine DS. Training-associated changes and stability of attention bias in youth: Implications for Attention Bias Modification Treatment for pediatric anxiety. Dev Cogn Neurosci. 2013 Apr;4:52-64. doi: 10.1016/j.dcn.2012.11.001. Epub 2012 Nov 10.
    Results Reference
    result
    PubMed Identifier
    22579509
    Citation
    Browning M, Holmes EA, Charles M, Cowen PJ, Harmer CJ. Using attentional bias modification as a cognitive vaccine against depression. Biol Psychiatry. 2012 Oct 1;72(7):572-9. doi: 10.1016/j.biopsych.2012.04.014. Epub 2012 May 12.
    Results Reference
    result
    PubMed Identifier
    21939499
    Citation
    Busch V, Magerl W, Kern U, Haas J, Hajak G, Eichhammer P. The effect of deep and slow breathing on pain perception, autonomic activity, and mood processing--an experimental study. Pain Med. 2012 Feb;13(2):215-28. doi: 10.1111/j.1526-4637.2011.01243.x. Epub 2011 Sep 21.
    Results Reference
    result
    Citation
    Cheng KS, Croarkin PE, Lee, PF. Heart rate variability of various video-aided mindful deep breathing durations and its impact on depression, anxiety, and stress symptom severity. Mindfulness. 2019; 10(10), 2082-2094.
    Results Reference
    result
    PubMed Identifier
    26404039
    Citation
    Chien HC, Chung YC, Yeh ML, Lee JF. Breathing exercise combined with cognitive behavioural intervention improves sleep quality and heart rate variability in major depression. J Clin Nurs. 2015 Nov;24(21-22):3206-14. doi: 10.1111/jocn.12972. Epub 2015 Sep 25.
    Results Reference
    result
    PubMed Identifier
    20462580
    Citation
    Chung LJ, Tsai PS, Liu BY, Chou KR, Lin WH, Shyu YK, Wang MY. Home-based deep breathing for depression in patients with coronary heart disease: a randomised controlled trial. Int J Nurs Stud. 2010 Nov;47(11):1346-53. doi: 10.1016/j.ijnurstu.2010.03.007. Epub 2010 May 11.
    Results Reference
    result
    PubMed Identifier
    20183695
    Citation
    Andersson G, Cuijpers P. Internet-based and other computerized psychological treatments for adult depression: a meta-analysis. Cogn Behav Ther. 2009;38(4):196-205. doi: 10.1080/16506070903318960.
    Results Reference
    result
    PubMed Identifier
    24836465
    Citation
    Davies EB, Morriss R, Glazebrook C. Computer-delivered and web-based interventions to improve depression, anxiety, and psychological well-being of university students: a systematic review and meta-analysis. J Med Internet Res. 2014 May 16;16(5):e130. doi: 10.2196/jmir.3142.
    Results Reference
    result
    Citation
    D'silva FHV, Muninarayanappa NV. Effectiveness of deep breathing exercise (DBE) on the heart rate variability, Bp, anxiety & depression of patients with coronary artery disease. Journal of Health and Allied Sciences NU. 2014; 04(01), 035-041.
    Results Reference
    result
    PubMed Identifier
    33111377
    Citation
    Gholamrezaei A, Van Diest I, Aziz Q, Vlaeyen JWS, Van Oudenhove L. Psychophysiological responses to various slow, deep breathing techniques. Psychophysiology. 2021 Feb;58(2):e13712. doi: 10.1111/psyp.13712. Epub 2020 Oct 27.
    Results Reference
    result
    PubMed Identifier
    20887977
    Citation
    Hakamata Y, Lissek S, Bar-Haim Y, Britton JC, Fox NA, Leibenluft E, Ernst M, Pine DS. Attention bias modification treatment: a meta-analysis toward the establishment of novel treatment for anxiety. Biol Psychiatry. 2010 Dec 1;68(11):982-90. doi: 10.1016/j.biopsych.2010.07.021. Erratum In: Biol Psychiatry. 2012 Sep 1;72(5):429.
    Results Reference
    result
    PubMed Identifier
    27943285
    Citation
    Hollis C, Falconer CJ, Martin JL, Whittington C, Stockton S, Glazebrook C, Davies EB. Annual Research Review: Digital health interventions for children and young people with mental health problems - a systematic and meta-review. J Child Psychol Psychiatry. 2017 Apr;58(4):474-503. doi: 10.1111/jcpp.12663. Epub 2016 Dec 10.
    Results Reference
    result
    PubMed Identifier
    31068158
    Citation
    Jonassen R, Harmer CJ, Hilland E, Maglanoc LA, Kraft B, Browning M, Stiles TC, Haaland VO, Berge T, Landro NI. Effects of Attentional Bias Modification on residual symptoms in depression: a randomized controlled trial. BMC Psychiatry. 2019 May 8;19(1):141. doi: 10.1186/s12888-019-2105-8.
    Results Reference
    result
    PubMed Identifier
    17324018
    Citation
    Joormann J, Gotlib IH. Selective attention to emotional faces following recovery from depression. J Abnorm Psychol. 2007 Feb;116(1):80-5. doi: 10.1037/0021-843X.116.1.80.
    Results Reference
    result
    PubMed Identifier
    27780478
    Citation
    Kamenov K, Twomey C, Cabello M, Prina AM, Ayuso-Mateos JL. The efficacy of psychotherapy, pharmacotherapy and their combination on functioning and quality of life in depression: a meta-analysis. Psychol Med. 2017 Feb;47(3):414-425. doi: 10.1017/S0033291716002774. Epub 2016 Oct 26.
    Results Reference
    result
    PubMed Identifier
    20708905
    Citation
    Kasper S, Caraci F, Forti B, Drago F, Aguglia E. Efficacy and tolerability of Hypericum extract for the treatment of mild to moderate depression. Eur Neuropsychopharmacol. 2010 Nov;20(11):747-65. doi: 10.1016/j.euroneuro.2010.07.005. Epub 2010 Aug 14.
    Results Reference
    result
    PubMed Identifier
    27666392
    Citation
    Khng KH. A better state-of-mind: deep breathing reduces state anxiety and enhances test performance through regulating test cognitions in children. Cogn Emot. 2017 Nov;31(7):1502-1510. doi: 10.1080/02699931.2016.1233095. Epub 2016 Sep 26.
    Results Reference
    result
    PubMed Identifier
    23720785
    Citation
    Kim SH, Schneider SM, Bevans M, Kravitz L, Mermier C, Qualls C, Burge MR. PTSD symptom reduction with mindfulness-based stretching and deep breathing exercise: randomized controlled clinical trial of efficacy. J Clin Endocrinol Metab. 2013 Jul;98(7):2984-92. doi: 10.1210/jc.2012-3742. Epub 2013 May 29.
    Results Reference
    result
    PubMed Identifier
    30300082
    Citation
    Lamb T, Pachana NA, Dissanayaka N. Update of Recent Literature on Remotely Delivered Psychotherapy Interventions for Anxiety and Depression. Telemed J E Health. 2019 Aug;25(8):671-677. doi: 10.1089/tmj.2018.0079. Epub 2018 Oct 6.
    Results Reference
    result
    PubMed Identifier
    32202692
    Citation
    Leslie M, Leppanen J, Paloyelis Y, Treasure J. A pilot study investigating the influence of oxytocin on attentional bias to food images in women with bulimia nervosa or binge eating disorder. J Neuroendocrinol. 2020 May;32(5):e12843. doi: 10.1111/jne.12843. Epub 2020 Mar 23.
    Results Reference
    result
    PubMed Identifier
    18213440
    Citation
    Lewis PM, Rosenfeld JV, Diehl RR, Mehdorn HM, Lang EW. Phase shift and correlation coefficient measurement of cerebral autoregulation during deep breathing in traumatic brain injury (TBI). Acta Neurochir (Wien). 2008 Feb;150(2):139-46; discussion 146-7. doi: 10.1007/s00701-007-1447-z. Epub 2008 Jan 23.
    Results Reference
    result
    PubMed Identifier
    28493904
    Citation
    Magaard JL, Seeralan T, Schulz H, Brutt AL. Factors associated with help-seeking behaviour among individuals with major depression: A systematic review. PLoS One. 2017 May 11;12(5):e0176730. doi: 10.1371/journal.pone.0176730. eCollection 2017.
    Results Reference
    result
    PubMed Identifier
    11779286
    Citation
    Mojtabai R, Olfson M, Mechanic D. Perceived need and help-seeking in adults with mood, anxiety, or substance use disorders. Arch Gen Psychiatry. 2002 Jan;59(1):77-84. doi: 10.1001/archpsyc.59.1.77.
    Results Reference
    result
    PubMed Identifier
    28370881
    Citation
    Moore RC, Swendsen J, Depp CA. Applications for self-administered mobile cognitive assessments in clinical research: A systematic review. Int J Methods Psychiatr Res. 2017 Dec;26(4):e1562. doi: 10.1002/mpr.1562. Epub 2017 Mar 31.
    Results Reference
    result
    PubMed Identifier
    30661553
    Citation
    Ollendick TH, White SW, Richey J, Kim-Spoon J, Ryan SM, Wieckowski AT, Coffman MC, Elias R, Strege MV, Capriola-Hall NN, Smith M. Attention Bias Modification Treatment for Adolescents With Social Anxiety Disorder. Behav Ther. 2019 Jan;50(1):126-139. doi: 10.1016/j.beth.2018.04.002. Epub 2018 Apr 17.
    Results Reference
    result
    PubMed Identifier
    17004338
    Citation
    Prakash ES, Ravindra PN, Madanmohan, Anilkumar R, Balachander J. Effect of deep breathing at six breaths per minute on the frequency of premature ventricular complexes. Int J Cardiol. 2006 Aug 28;111(3):450-2. doi: 10.1016/j.ijcard.2005.05.075.
    Results Reference
    result
    PubMed Identifier
    19531229
    Citation
    Sawada N, Uchida H, Suzuki T, Watanabe K, Kikuchi T, Handa T, Kashima H. Persistence and compliance to antidepressant treatment in patients with depression: a chart review. BMC Psychiatry. 2009 Jun 16;9:38. doi: 10.1186/1471-244X-9-38.
    Results Reference
    result
    PubMed Identifier
    33658964
    Citation
    Steffen PR, Bartlett D, Channell RM, Jackman K, Cressman M, Bills J, Pescatello M. Integrating Breathing Techniques Into Psychotherapy to Improve HRV: Which Approach Is Best? Front Psychol. 2021 Feb 15;12:624254. doi: 10.3389/fpsyg.2021.624254. eCollection 2021.
    Results Reference
    result
    Citation
    Sunadi A, Ifadah E, Syarif MNO. The effect of deep breathing relaxation to reduce post operative pain in lower limb fracture. Enfermería Clínica. 2020; 30, 143-145.
    Results Reference
    result
    PubMed Identifier
    31336661
    Citation
    Telles S, Gupta RK, Gandharva K, Vishwakarma B, Kala N, Balkrishna A. Immediate Effect of a Yoga Breathing Practice on Attention and Anxiety in Pre-Teen Children. Children (Basel). 2019 Jul 22;6(7):84. doi: 10.3390/children6070084.
    Results Reference
    result
    PubMed Identifier
    25156003
    Citation
    Van Diest I, Verstappen K, Aubert AE, Widjaja D, Vansteenwegen D, Vlemincx E. Inhalation/Exhalation ratio modulates the effect of slow breathing on heart rate variability and relaxation. Appl Psychophysiol Biofeedback. 2014 Dec;39(3-4):171-80. doi: 10.1007/s10484-014-9253-x.
    Results Reference
    result
    PubMed Identifier
    28303742
    Citation
    Wirth BE, Wentura D. Attentional bias to threat in the general population is contingent on target competition, not on attentional control settings. Q J Exp Psychol (Hove). 2018 Apr;71(4):975-988. doi: 10.1080/17470218.2017.1307864. Epub 2018 Jan 1.
    Results Reference
    result
    PubMed Identifier
    25245928
    Citation
    Yang W, Ding Z, Dai T, Peng F, Zhang JX. Attention Bias Modification training in individuals with depressive symptoms: A randomized controlled trial. J Behav Ther Exp Psychiatry. 2015 Dec;49(Pt A):101-11. doi: 10.1016/j.jbtep.2014.08.005. Epub 2014 Sep 8.
    Results Reference
    result
    Links:
    URL
    https://projects.iq.harvard.edu/files/crcs/files/ai4sg_2020_paper_30.pdf
    Description
    Progressing Social Good by Reducing Mental Health Care Inequality with Persuasive Technology
    URL
    https://www.who.int/news-room/fact-sheets/detail/mental-disorders
    Description
    WHO Mental Disorders Fact Sheet

    Learn more about this trial

    Emoji-based Attention Bias Modification Training for Depressive Young Adults

    We'll reach out to this number within 24 hrs