After two fascinating talks by Dr. Patrick Mallon and Dr. Geoff Symonds around great medical strides being developed, another facet of care and project development shone in the plenary session.

 

Andrew Jolivette’s elegant talk brought focus back to how we as practitioners and researchers can widen our perspective by weaving past social constructs, acknowledgement of generational impact and group solidarity into how we view and address health concerns in today’s world - especially in light of how our world's cultures are blending and evolving.

 

This session tied in quite nicely with James Blanchard’s talk and ‘Mega Model’, exploring windows of opportunity and individual timeline trajectories. Jolivette goes further, asking us to examine windows of opportunity and change for past generations – to include the impact our own previous generations have made on Indigenous cultural practice and social perception of self and others.

 

Again, the one-size-fits-all approach is noted as not working. Jolivette encourages us to work inclusively and collaboratively alongside groups to build community solidarity and ‘weave’ projects to improve outcomes in health and well-being.  He argues the incorporation of research justice and Indigenous methodologies can help build better programs while challenging identity and behavioural categorisations that continue to pigeonhole gender, sexuality and multiracial individuals/ populations.

 

In an interesting train of thought, he also asks we approach research as an act of ceremony to build cohesiveness while remembering the context some indigenous populations view research and how they benefit from projects.

 

Jolivette also notes the importance of peace of mind and the acceptance of disease as a process of healing –and that healing is an ongoing process of wellness.

 

I think there are strong parallels to be drawn between Native American experiences and the situations Australian Aboriginal peoples face. There is great potential for us to better tailor programs and I will be paying particular attention to what is happening in the gaps and blank spaces in program frameworks and research.

 

Andrew Jolivette’s talk today challenges all of us to examine the dynamics in public health programs and process implementation – and most importantly, finally acknowledge individual difference as a societal contribution rather than a hurdle.

 

Australia is on the way to reaching the UNAIDS 90-90-90 goal but is hoping to fill in the blanks around why clients are lost to follow up care.

Several sessions this afternoon attempted to assess individual linkage to care and identify factors around why +HIV patients disengage with care.

Individual reasons for disengagement were not surprising with 'Feeling well' and 'Too Busy' listed as the most commonly identified issues. Additionally, the lack of up to date contact details and phone numbers were also listed as an issue.

Predictors associated with a true loss from care were clients in younger age groups, individuals not on treatment, detectable viral loads and previous issues with treatment adherence. Additionally, there were signs drug use, specifically Crystal, was a factor in loss to follow up. There is a need for further examination into the influence of drug use on individual loss of care.

Increased and improved recall systems within clinic practices, additional care team support (presumably nursing and allied health members), better identification of clients at risk of care disengagement and improved inter-practice communication could reduce those individuals lost to follow up.

 

What a start to the conference!

 

The theme of harnessing HIV and STI prevention opportunities rang throughout the hall during the plenary sessions - and continued to echo throughout the presentations.

 

Of particular note (for me) was the Causal Interactions Session - specifically the ‘Mega Model’ session presented initially by Marissa Becker and later by James Blanchard. At the base of these talks were the Mega Model diagram and a central concept of fluidity in program design approach. He asks us to specifically consider population transmission dynamics and individual risk, namely looking at biology, behaviour and networks when planning research and developing projects. Blanchard illustrated his ideas through asking the group: why do populations that look similar often have very different HIV epidemics?

 

The mega model helps address this. In part, this diagram takes a look at how we can modify our approach to problems and adjust our actions along what is occurring in a group or individual’s time line. Without getting too complicated, his argument is that for every phase in a timeline, we should be examining what is actually happening for people during each phase or ‘window’ of the continuum. This is done by considering each phase by analysing 1. Behaviours of groups/individuals 2. Networks that affect group/individual decision making and 3. Biological influences that impact on health changes/disease processes during each window.

 

An example might be a woman is sexually active at age 14, has casual partners for 2 years, commences sex work in a brothel for 4 years and then ceases sex work. In addition to larger influences, say limited access to education or gender violence, these timeline windows or phases can be examined for influences. Behaviour might include early sexual debut, Networks she interacts within might be intergenerational relationships and Biologically, an immature cervix and high levels of inflammation play significant roles on the trajectory of her timeline.  Different influences at each window will be affecting her individually but they can also change how a program or intervention might be aimed.

 

By examining the nuances of individual and group timelines, you can negotiate and recognise the smaller differences that can greatly influence group outcomes.

 

Essentially, we should be approaching problems in a flexible manner that considers all angles of influence for a group or individual PRIOR to instituting a program. This would help stop a ‘one size fits all’ approach while recognizing and accounting for variables that have previously gone unrecognized or acknowledged in program or study development. This will allow us to closely examine the influence of individual or group variables more fully.

It is much simpler than it sounds! Of course, everyone has their favourite method but I saw this as a thoughtful approach to research and project development.