Asymmetrical Gene Flow in a Hybrid Zone of Hawaiian Schiedea (Caryophyllaceae) Species with Contrasting Mating Systems

Asymmetrical gene flow, which has frequently been documented in naturally occurring hybrid zones, can result from various genetic and demographic factors. Understanding these factors is important for determining the ecological conditions that permitted hybridization and the evolutionary potential inherent in hybrids. Here, we characterized morphological, nuclear, and chloroplast variation in a putative hybrid zone between Schiedea menziesii and S. salicaria, endemic Hawaiian species with contrasting breeding systems. Schiedea menziesii is hermaphroditic with moderate selfing; S. salicaria is gynodioecious and wind-pollinated, with partially selfing hermaphrodites and largely outcrossed females. We tested three hypotheses: 1) putative hybrids were derived from natural crosses between S. menziesii and S. salicaria, 2) gene flow via pollen is unidirectional from S. salicaria to S. menziesii and 3) in the hybrid zone, traits associated with wind pollination would be favored as a result of pollen-swamping by S. salicaria. Schiedea menziesii and S. salicaria have distinct morphologies and chloroplast genomes but are less differentiated at the nuclear loci. Hybrids are most similar to S. menziesii at chloroplast loci, exhibit nuclear allele frequencies in common with both parental species, and resemble S. salicaria in pollen production and pollen size, traits important to wind pollination. Additionally, unlike S. menziesii, the hybrid zone contains many females, suggesting that the nuclear gene responsible for male sterility in S. salicaria has been transferred to hybrid plants. Continued selection of nuclear genes in the hybrid zone may result in a population that resembles S. salicaria, but retains chloroplast lineage(s) of S. menziesii

A qualitative exploration of SMART Recovery Meetings in Australia and the role of a Digital Platform to Support Routine Outcome Monitoring:A qualitative exploration of SMART Recovery

Previous research has reported on the benefits of mutual support groups. However, such groups do not routinely collect data on participant outcomes. Moreover, the effect of collecting outcomes measures on these groups is unknown. The objective of this mixed methods study was to elicit participant views on using a novel, purpose built digital platform for routine outcome monitoring (ROM) as a standard component of a mutual support group. SMART Recovery, or the Self-Management and Recovery Training program, is group-based and uses professional clinicians to facilitate discussion and foster mutual support for a range of addictive behaviours, alongside Cognitive Behavioural Therapy and Motivational Interviewing techniques. This paper reports on the qualitative component of this study and how participants perceive ROMs, and the potential shift to technological resources. Twenty semi-structured telephone interviews were conducted with participants from SMART Recovery groups across New South Wales, Australia. Participants discussed their use of mutual support within group meetings to manage their recovery, including: naming their goals in front of peers; learning from clinicians and group discussion; and developing reciprocal and caring relationships. They also described any previous experience with routine outcomes measures and how digital technologies might enhance or hinder group function. Participants valued mutual support groups and reported that digital technologies could be complementary to physical, weekly group meetings. They were also concerned that the introduction of technological resources might pose a threat to physical meetings, thereby risking their access to mutual support. Findings have implications for the implementation of ROM when delivered via digital mechanisms, and indicate threats and opportunities that warrant consideration for future initiatives

Developing a mHealth routine outcome monitoring and feedback app ("SMART Track") to support self-management of addictive behaviours.

Routine outcome monitoring (ROM) has been implemented across a range of addiction treatment services, settings and organisations. Mutual support groups are a notable exception. Innovative solutions are needed. SMART Track is a purpose built smartphone app designed to capture ROM data and provide tailored feedback to adults attending Australian SMART Recovery groups for addictive behaviour(s). Details regarding the formative stage of app development is essential, but often neglected. Improved consideration of the end-user is vital for curtailing app attrition and enhancing engagement. This paper provides a pragmatic example of how principles embedded in published frameworks can be operationalised to address these priorities during the design and development of the SMART Track app. Three published frameworks for creating digital health technologies ("Person-Based Approach," "BIT" Model and IDEAS framework) were integrated and applied across two stages of research to inform the development, design and content of SMART Track. These frameworks were chosen to ensure that SMART Track was informed by the needs and preferences of the end-user ("Person-Based"); best practise recommendations for mHealth development ("BIT" Model) and a collaborative, iterative development process between the multi-disciplinary research team, app developers and end-users (IDEAS framework). Stage one of the research process generated in-depth knowledge to inform app development, including a comprehensive set of aims (clinical, research/organisation, and usage); clear articulation of the target behaviour (self-monitoring of recovery related behaviours and experiences); relevant theory (self-determination and social control); appropriate behavioural strategies (e.g., behaviour change taxonomy and process motivators) and key factors that may influence engagement (e.g., transparency, relevance and trust). These findings were synthesised into guiding principles that were applied during stage two in an iterative approach to app design, content and development. This paper contributes new knowledge on important person-centred and theoretical considerations that underpin a novel ROM and feedback app for people with addictive behaviour(s). Although person-centred design and best-practise recommendations were employed, further research is needed to determine whether this leads to improved usage outcomes. Pilot Trial: http://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377336

Three-dimensional computed tomography cephalometry of plagiocephaly: Asymmetry and shape analysis

Copyright © 2006 The American Cleft Palate-Craniofacial AssociationObjectiveTo investigate facial asymmetry associated with both deformational and synostotic plagiocephaly and to identify variables based on skeletal landmarks that distinguish the conditions and quantify severity.DesignRetrospective, cross sectional.SettingAustralian Craniofacial Unit, Adelaide.Main outcome measuresProportional differences between bilateral distances and principal component (PC) analysis of the skeletal landmarks.PatientsThe three-dimensional positions of 78 osseous landmarks were determined from computed tomography (CT) scans of 21 patients with deformational plagiocephaly (DP), 20 patients with unilateral coronal synostosis (UCS), and 2 patients with unilateral lambdoid synostosis (ULS).ResultsFor both DP and UCS, significant asymmetry was found for the orbital depths, mandibular lengths, maxillary depths, zygomatic arch lengths, lateral base of the parietal bone, and the angle between the anterior and the posterior cranial base projected onto the axial plane. The small sample size for ULS precluded definitive statistical statements but allowed some useful comparisons with the other conditions. The first three PC scores were able to distinguish among the three conditions and which side was affected.ConclusionsThe asymmetry of the cranial base and facial structures, arising from localized abnormality or deformational forces in either the frontal or the occipital regions, can be quantified by a plethora of bilateral features or summarized by PC analysis.D.J. Netherway, A.H. Abbott, N. Gulamhuseinwala, K.L. McGlaughlin, P.J. Anderson, G.C. Townsend, D.J. Davi

Developing a mHealth Routine Outcome Monitoring and Feedback App (“SMART Track”) to Support Self-Management of Addictive Behaviours

Background: Routine outcome monitoring (ROM) has been implemented across a range of addiction treatment services, settings and organisations. Mutual support groups are a notable exception. Innovative solutions are needed. SMART Track is a purpose built smartphone app designed to capture ROM data and provide tailored feedback to adults attending Australian SMART Recovery groups for addictive behaviour(s). Objective: Details regarding the formative stage of app development is essential, but often neglected. Improved consideration of the end-user is vital for curtailing app attrition and enhancing engagement. This paper provides a pragmatic example of how principles embedded in published frameworks can be operationalised to address these priorities during the design and development of the SMART Track app. Methods: Three published frameworks for creating digital health technologies (“Person-Based Approach,” “BIT” Model and IDEAS framework) were integrated and applied across two stages of research to inform the development, design and content of SMART Track. These frameworks were chosen to ensure that SMART Track was informed by the needs and preferences of the end-user (“Person-Based”); best practise recommendations for mHealth development (“BIT” Model) and a collaborative, iterative development process between the multi-disciplinary research team, app developers and end-users (IDEAS framework). Results: Stage one of the research process generated in-depth knowledge to inform app development, including a comprehensive set of aims (clinical, research/organisation, and usage); clear articulation of the target behaviour (self-monitoring of recovery related behaviours and experiences); relevant theory (self-determination and social control); appropriate behavioural strategies (e.g., behaviour change taxonomy and process motivators) and key factors that may influence engagement (e.g., transparency, relevance and trust). These findings were synthesised into guiding principles that were applied during stage two in an iterative approach to app design, content and development. Conclusions: This paper contributes new knowledge on important person-centred and theoretical considerations that underpin a novel ROM and feedback app for people with addictive behaviour(s). Although person-centred design and best-practise recommendations were employed, further research is needed to determine whether this leads to improved usage outcomes. Clinical Trial Registration: Pilot Trial: http://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377336

Incorporating routine outcome monitoring and tailored feedback into SMART Recovery Australia mutual support groups using a novel mHealth application (‘Smart Track’): Protocol for a pilot study examining feasibility and acceptability

Background: Despite the importance and popularity of mutual support groups, there have been no systematic attempts to implement and evaluate routine outcome monitoring (ROM) in these settings. Unlike other mutual support groups for addiction, trained facilitators lead all SMART Recovery groups, thereby providing an opportunity to implement ROM as a routine component of SMART Recovery groups. Objective: This study protocol describes a stage one pilot study designed to explore the feasibility and acceptability of a novel, purpose-built mHealth ROM and Feedback app (“Smart Track”) in SMART Recovery Australia mutual support groups. Secondary objectives are to describe Smart Track usage patterns, explore psychometric properties of the ROM items (internal reliability, convergent and divergent validity) and provide preliminary evidence for participant reported outcomes (alcohol and/ other drug use, self-reported recovery and mental health). Methods: The Smart Track app was developed during the first phase of this study using participatory design methods and an iterative development process. During phase two, 100 participants from SMART Recovery groups across New South Wales, Australia, will be recruited to a non-randomised, prospective, single-arm trial of the Smart Track app. There are four modes of data collection: (i) ROM data collected from group participants via Smart Track app, (ii) backend app data summarising user interactions with Smart Track; (iii) quantitative interview/survey data of group participants (baseline, 2week- and 2month- follow-up); and (iv) qualitative interviews with group participants (n=20) and facilitators (n=10). Feasibility and acceptability (primary objectives) will be analysed via descriptive statistics, a cost analysis and qualitative evaluation. Secondary objectives are to a) explore the relationship between participant characteristics and app use (via linear regression, graphic representation and latent trajectory analysis, as appropriate); b) provide preliminary evidence for the psychometric properties of Smart Track items (via sensitivity to change, internal consistency, test-retest reliability, convergent validity and exploratory factor analysis) and c) describe participant reported outcomes (via descriptive statistics summarising self-reported addictive behaviour(s), recovery and mental health). Results: At the time of submission 13 sites (n=25 groups) had agreed to participate. Enrolment is due to commence in July 2019. Data collection is due to be finalised October 2019. Conclusions: To the best of our knowledge, this project will be the first time that ROM and tailored feedback have been used within a mutual support group setting for addictive behaviours. Our study design will provide an opportunity to identify the acceptability of a novel mHealth ROM and feedback app within this setting, and provide detailed information on what factors promote or hinder ROM use within this context. Should Smart Track prove feasible and acceptable, this project offers a new tool that service providers, policy makers and researchers could one day use to understand the impact of SMART Recovery. Clinical Trial: Registration: Australian New Zealand Clinical Trials Registry (ANZCTR) Registration Number: ACTRN12619000686101 Date of Registration: 07/05/201