Help-seeker expectations and outcomes of a crisis support service : comparison of suicide-related and non-suicide-related contacts to lifeline Australia
The impact of a novel mimicry task for increasing emotion recognition in adults with autism spectrum disorder and alexithymia : protocol for a randomized controlled trial
Description:
Time judgement and time experience are distinct elements of time perception. It is known that time experience tends to be slow, or dilated, when depressed, but there is less certainty or clarity concerning how depression affects time judgement. Here, we use a Bayesian Prediction Error Minimisation (PEM) framework called 'distrusting the present' as an explanatory and predictive model of both aspects of time perception. An interval production task was designed to probe and modulate the relationship between time perception and depression. Results showed that hopelessness, a symptom of severe depression, was associated with the ordering of interval lengths, reduced overall error, and dilated time experience. We propose that 'distrusting the future' is accompanied by 'trusting the present', leading to the experiences of time dilation when depressed or hopeless. Evidence was also found to support a relative difference model of how hopelessness dilates, and arousal accelerates, the rate of experienced time.
Description:
Time judgement and time experience are distinct elements of time perception. It is known that time experience tends to be slow, or dilated, when depressed, but there is less certainty or clarity concerning how depression affects time judgement. Here, we use a Bayesian Prediction Error Minimisation (PEM) framework called 'distrusting the present' as an explanatory and predictive model of both aspects of time perception. An interval production task was designed to probe and modulate the relationship between time perception and depression. Results showed that hopelessness, a symptom of severe depression, was associated with the ordering of interval lengths, reduced overall error, and dilated time experience. We propose that 'distrusting the future' is accompanied by 'trusting the present', leading to the experiences of time dilation when depressed or hopeless. Evidence was also found to support a relative difference model of how hopelessness dilates, and arousal accelerates, the rate of experienced time.
Description:
Objectives: This study examined the feasibility of delivering an online cognitive behavioural therapy for insomnia intervention (Sleep-e) within an Australian public hospital outpatient insomnia clinic. Method: This study was conducted as an open trial pilot study. Fifty-two patients waiting for clinic treatment were invited to participate, with ten commencing and six completing the 7-week internet intervention. Participants completed a battery of questionnaires regarding their demographic information, sleep and insomnia symptoms, and provided feedback about the program. Exclusion criteria were minimal, and the study allowed for participants to have other health, psychiatric, and sleep disorder co-morbidities. Results: Post-program satisfaction results suggested that Sleep-e was easy to use; participants were satisfied with it; and found it beneficial in improving sleep. Paired samples t tests for the intention-to-treat sample indicated reductions in participants' insomnia severity (p = 0.02) and sleep onset latency (p = 0.04) from pre- to post-program. However, a larger sample is needed to generalise the results to the wider population. Conclusion: The findings support Sleep-e as a helpful treatment for insomnia in a public hospital outpatient population for at least a subgroup of patients. However, significant lessons were learned regarding the importance of educating health care providers and patients about novel models of internet service delivery. Potential models of adaptive or blended stepped-care are discussed to facilitate program implementation. Future research should identify how to implement internet interventions more effectively in public health settings to take advantage of their potential to improve clinical efficiency.
Description:
This study uses a combined categorical-dimensional approach to depict a hierarchical framework for consciousness similar to, and contiguous with, factorial models of cognition (cf., intelligence). On the basis of the longstanding definition of time consciousness, the analysis employs a dimension of temporal extension, in the same manner that psychology has temporally organised memory (i.e., short-term, long-term, and long-lasting memories). By defining temporal extension in terms of the structure of time perception at short timescales (<100 s), memory and time consciousness are proposed to fit along the same logarithmic dimension. This suggests that different forms of time consciousness (e.g., experience, wakefulness, and self-consciousness) are embedded within, or supported by, the ascending timescales of different modes of memory (i.e., short-term, long-term, etc.). A secondary dimension is also proposed to integrate higher-order forms of consciousness/emotion and memory/cognition. The resulting two-dimensional structure accords with existing theories of cognitive and emotional intelligence.
Description:
This study uses a combined categorical-dimensional approach to depict a hierarchical framework for consciousness similar to, and contiguous with, factorial models of cognition (cf., intelligence). On the basis of the longstanding definition of time consciousness, the analysis employs a dimension of temporal extension, in the same manner that psychology has temporally organised memory (i.e., short-term, long-term, and long-lasting memories). By defining temporal extension in terms of the structure of time perception at short timescales (<100 s), memory and time consciousness are proposed to fit along the same logarithmic dimension. This suggests that different forms of time consciousness (e.g., experience, wakefulness, and self-consciousness) are embedded within, or supported by, the ascending timescales of different modes of memory (i.e., short-term, long-term, etc.). A secondary dimension is also proposed to integrate higher-order forms of consciousness/emotion and memory/cognition. The resulting two-dimensional structure accords with existing theories of cognitive and emotional intelligence.
Description:
Background: A recent meta-analysis left open a significant question regarding altered time perception in depression: Why do depressed people overproduce short durations and under-produce longer durations if their present experience is that time flows slowly? Experience and judgement of time do not seem to accord with one another. Analysis: By excluding two of the six studies on methodological grounds from a previous meta-analysis of medium-length interval productions, and re-analysing the remaining four studies, the present paper finds that subjective time accelerates from initial dilation within present experience (approximately 1 s duration) to subsequent acceleration within working memory (approximately 30 s duration) when depressed. Proposals: It is proposed that depressive time dilation and acceleration refer to the default mode and central executive networks, respectively. The acceleration effect is suggested to occur due to mood congruency between long intervals, boredom, and depression. This mood congruency leads to the automatic recall of intrusive, negative, and non-specific autobiographical long-term memories used to judge intervals from previous experience. Acceleration in working memory then occurs according to the contextual change model of duration estimation. Limitations: The meta-analysis is limited to four studies only, but provides a potential link between time experience and judgement within the same explanatory model. Conclusions: Similarities between psychological time dilation/acceleration and physical time dilation/acceleration are discussed.
Description:
Digital-Health intervention (DHI) are used by health care providers to promote engagement within community. Effective assignment of participants into DHI programs helps increasing benefits from the most suitable intervention. A major challenge with the roll-out and implementation of DHI, is in assigning participants into different interventions. The use of biopsychosocial model [18] for this purpose is not wide spread, due to limited personalized interventions formed on evidence-based data-driven models. Machine learning has changed the way data extraction and interpretation works by involving automatic sets of generic methods that have replaced the traditional statistical techniques. In this paper, we propose to investigate relevance of machine learning for this purpose and is carried out by studying different non-linear classifiers and compare their prediction accuracy to evaluate their suitability. Further, as a novel contribution, real-life biopsychosocial features are used as input in this study. The results help in developing an appropriate predictive classication model to assign participants into the most suitable DHI. We analyze biopsychosocial data generated from a DHI program and study their feature characteristics using scatter plots. While scatter plots are unable to reveal the linear relationships in the data-set, the use of classifiers can successfully identify which features are suitable predictors of mental ill health.
Description:
Digital-Health intervention (DHI) are used by health care providers to promote engagement within community. Effective assignment of participants into DHI programs helps increasing benefits from the most suitable intervention. A major challenge with the roll-out and implementation of DHI, is in assigning participants into different interventions. The use of biopsychosocial model [18] for this purpose is not wide spread, due to limited personalized interventions formed on evidence-based data-driven models. Machine learning has changed the way data extraction and interpretation works by involving automatic sets of generic methods that have replaced the traditional statistical techniques. In this paper, we propose to investigate relevance of machine learning for this purpose and is carried out by studying different non-linear classifiers and compare their prediction accuracy to evaluate their suitability. Further, as a novel contribution, real-life biopsychosocial features are used as input in this study. The results help in developing an appropriate predictive classication model to assign participants into the most suitable DHI. We analyze biopsychosocial data generated from a DHI program and study their feature characteristics using scatter plots. While scatter plots are unable to reveal the linear relationships in the data-set, the use of classifiers can successfully identify which features are suitable predictors of mental ill health.
Description:
Study Objectives: To investigate whether cognitive behavior therapy was effective for older adults with comorbid insomnia and depression in a community mental health setting, and explore whether an advanced form of cognitive behavior therapy for insomnia produced better outcomes compared to a standard form of cognitive behavior therapy for insomnia. Methods: An 8-week randomized controlled clinical trial was conducted within community mental health services, Victoria, Australia. Seventy-two older adults (56% female, M age 75 ± 7 years) with diagnosed comorbid insomnia and depression participated. Three conditions were tested using a group therapy format: cognitive behavior therapy for insomnia (CBT-I, standard), cognitive behavior therapy for insomnia plus positive mood strategies (CBT-I+, advanced), psychoeducation control group (PCG, control). The primary outcomes were insomnia severity (Insomnia Severity Index) and depression severity (Geriatric Depression Scale). Primary and secondary measures were collected at pre (week 0), post (week 8), and follow-up (week 20). Results: CBT-I and CBT-I+ both generated significantly greater reductions in insomnia and depression severity compared to PCG from pre to post (p < .001), which were maintained at follow-up. Although the differences between outcomes of the two treatment conditions were not statistically significant, the study was not sufficiently powered to detect either superiority of one treatment or equivalence of the two treatment conditions. Conclusion: CBT-I and CBT-I+ were both effective at reducing insomnia and depression severity for older adults. Mental health services that deliver treatment for comorbid insomnia with cognitive behavior therapy may improve recovery outcomes for older adults with depression. Trial Registration: Australian and New Zealand Clinical Trials Registry (ANZCTR); URL: https://www.anzctr.org.au; Trial ID: ACTRN12615000067572; Date Registered: December 12, 2014.
Description:
As a broader effort to build a holistic biopsychosocial health metric, reaction time data obtained from participants undertaking neurocognitive tests have been examined using Exploratory Data Analysis (EDA) for assessing its distribution. Many of the known existing methods assume, that the reaction time data follows a Gaussian distribution and thus commonly use statistical measures such as Analysis of Variance (ANOVA) for analysis. However, it is not mandatory for the reaction time data, to necessarily follow Gaussian distribution and in many instances, it can be better modeled by other representations such as Gamma distribution. Unlike Gaussian distribution which is defined using mean and variance, the Gamma distribution is defined using shape and scale parameters which also considers higher order moments of data such as skewness and kurtosis. Generalized Linear Models (GLM), based on the family exponential distributions such as Gamma distribution, which have been used to model reaction time in other domains, have not been fully explored for modeling reaction time data in psychology domain. While limited use of Gamma distribution have been reported [5, 17, 21], for analyzing response times, their application has been somewhat ad-hoc rather than systematic. For this proposed research, we use a real life biopsychosocial dataset, generated from the 'digital health' intervention programs conducted by the Faculty of Health, Federation University, Australia. The two digital intervention programs were the 'Mindfulness' program and 'Physical Activity' program. The neurocognitive tests were carried out as part of the 'Mindfulness' program. In this paper, we investigate the participants' reaction time distributions in neurocognitive tests such as the Psychology Experiment Building Language (PEBL) Go/No-Go test [19], which is a subset of the larger biopsychosocial data set. PEBL is an open source software system for designing and running psychological experiments. Analysis of participants' reaction time in the PEBL Go/No-Go test, shows that the reaction time data are more compatible with a Gamma distribution and clearly demonstrate that these can be better modeled by Gamma distribution.
Description:
The biopsychosocial (BPS) model proposes that health is best understood as a combination of bio-physiological, psychological and social determinants, and thus advocates for a far more comprehensive investigation of the relationships between ‘mind-body’ health. For this holistic analysis, we need a suitable measure to indicate participants’ ‘biological’ stress. With the advent of wearable sensor devices, health monitoring is becoming easier. In this study, we focus on bio-physiological indicators of stress, from wearable devices using the heart-rate data. The analysis of such heart-rate data presents a set of practical challenges. We review various measures currently in use for stress measurement and their relevance and significance with the wearables’ heart-rate data. In this paper, we propose to use the novel ‘peak heart-rate count’ metric to quantify level of ‘biological’ stress. Real life biometric data obtained from digital health intervention program was considered for the study. Our study indicates the significance of using frequency of ‘peak heart-rate count’ as a ‘biological’ stress measure.
Description:
Background: This regional pilot site ‘end-user attitudes’ study explored nurses’ experiences and impressions of using the Nurses’ Behavioural Assistant (NBA) (a knowledge-based, interactive ehealth system) to assist them to better respond to behavioural and psychological symptoms of dementia (BPSD) and will be reported here. Methods: Focus groups were conducted, followed by a four-week pilot site ‘end-user attitudes’ trial of the NBA at a regional aged care residential facility (ACRF). Brief interviews were conducted with consenting nursing staff. Results: Focus group feedback (N = 10) required only minor cosmetic changes to the NBA prototype. Post pilot site end-user interview data (N = 10) indicated that the regional ACRF nurses were positive and enthusiastic about the NBA, however several issues were also identified. Conclusions: Overall the results supported the utility of the NBA to promote a person centred care approach to managing BPSD. Slight modifications may be required to maximise its uptake across all ACRF nursing staff.
Description:
BACKGROUND: Prostate cancer treatment often results in significant psycho-sexual challenges for men following treatment; however, many men report difficulty in accessing appropriate care. METHODS: A randomized controlled trial was undertaken to assess the efficacy of a 10-week self-guided online psychological intervention called My Road Ahead (MRA) for men with localized prostate cancer in improving sexual satisfaction. Participants were randomized to 1 of 3 conditions MRA alone or MRA plus online forum, or forum access alone. Pre, post, and follow-up assessments of overall sexual satisfaction were conducted. Mixed models and structural equation modeling were used to analyze the data. RESULTS: One hundred forty-two men (mean age 61 y; SD = 7) participated. The majority of participants had undergone radical prostatectomy (88%) and all men had received treatment for localized prostate cancer. Significant differences were obtained for the 3 groups (P = .026) and a significant improvement in total sexual satisfaction was observed only for participants who were allocated to MRA + forum with a large effect size (P = .004, partial eta2 = 0.256). Structural equation modeling indicated that increases in sexual function, masculine self-esteem, and sexual confidence contributed significantly to overall sexual satisfaction for the MRA + forum plus forum condition. CONCLUSIONS: This study is the first, to our knowledge, that has evaluated a self-guided online psychological intervention tailored to the specific needs of men with prostate cancer. The findings indicate the potential for MRA to deliver support that men may not otherwise receive and also highlight the importance of psychological intervention to facilitate improved sexual outcomes.
Description:
Panic disorder with or without agoraphobia (PD/A) is a disabling disorder that involves physical anxiety symptoms, maladaptive cognitions and avoidance behaviour. Internet-based cognitive behavioural therapy (ICBT) can provide accessible mental health care to those who suffer from PD/A, which may increase the uptake of psychological treatment. The literature on ICBT for PD/A shows largely positive results, especially for therapist-guided ICBT among the general population. Unguided ICBT for PD/A is less studied. It has also demonstrated positive results, but is commonly associated with higher attrition than guided ICBT. There is also some evidence that guided ICBT for PD/A is effective for inpatients. Cost-effectiveness of ICBT for PD/A has only been minimally studied, but some evidence indicates it can be cost saving compared with face-to-face CBT. This chapter further describes the existing ICBT programmes for PD/A, a case study and implementation examples from Sweden and Australia. Finally, this chapter discusses the feasibility of minimally guided ICBT and current innovations in ICBT for PD/A, such as the use of mobile technology and virtual reality, and provides future directions for research and development.
Description:
OBJECTIVE: The MindSpot Clinic provides online mental health services to Australian adults with anxiety and depression. This paper describes users of MindSpot between January 2013 and June 2015. Outcomes are considered against three key objectives: improving access to mental health services, improving public awareness of how to access services and providing evidence-based treatments. METHOD: Website traffic data were examined to determine patterns of use. Demographic characteristics, past service utilisation and reasons for contacting MindSpot were analysed. Outcomes for patients enrolled in a MindSpot treatment course were also analysed. Primary outcomes were scores on the 9-Item Patient Health Questionnaire, Generalised Anxiety Disorder 7-Item, Yale-Brown Obsessive Compulsive Scale and Post-Traumatic Stress Disorder Checklist-Civilian Version, administered at assessment, post-treatment and 3-month follow-up. RESULTS: The website was visited by almost 500,000 Australians, of which 33,990 adults started assessments, and 25,469 people completed assessment and were eligible for analysis. Mean age was 36.4 years (standard deviation = 13.3 years; range = 18-94 years), and 72% were female. The proportion living in rural or remote regions and who identified as Aboriginal and Torres Strait Islander closely matched national statistics. The majority (82%) reported that they were not currently in contact with mental health services. Most patients sought an assessment, information about treatment options, or referral to another service, and only 24% of those completing an assessment commenced a MindSpot treatment course. Of these, large clinical effects (d: 0.7-2.4; average symptom reductions: 25.5% to 61.6%) were found from assessment to follow-up on all outcome measures. Deterioration ranged from 1.0% to 4.3%. CONCLUSION: Based on the number of website visits, completed assessments and treatment outcomes, MindSpot achieved its three programme objectives. This model of service provision has considerable value as a complement to existing services, and is proving particularly important for improving access for people not using existing services.