Between crisis and opportunity, old age has many faces in Lebanon. While old age was first seen as a time of wisdom, the current trend accentuated by migration and the economic crisis sets a challenge for the Lebanese elder; they may be left behind unless something is done in all communities at a national level. In this short communication, we attempt to broaden the scope of thinking about training programs to target population-shift and create a true change. We reflect on our results as an intermediate outcome of public health interventions. We suggest that it may be worthwhile to evaluate population-shifts further and base the success of an intervention on measures of Health Related Quality of Life through the response-shift created by such national public health programs.
The Lebanese elder population currently represents 8.5 percent of the entire Lebanese population [
In this report, the authors take the time to ponder on needed population shift as new elder/geriatric training programs are built in specific regions of the world, with intent to create the change at a population-level regarding ageism [
Response shift refers to a change in the meaning of one’s evaluation of a construct as a result of a change in one’s internal standards of measurements, a change in one’s values, or a change in one’s definition of the construct [
We will consider two examples specific to Lebanon whose effects lead to population-level response shifts that modified Health Related Quality of Life (HRQL): the 2006 war in Lebanon and the Lebanese smoking ban. These examples serve two purposes. First, they assert that population shifts are possible and have happened before. Thus, an initiative to produce a positive response shift may be effective. Second, they illustrate that positive population level shifts might not be apparent at first glance. Nevertheless, a deeper analysis could reveal immense progress on the wellbeing for when an initiative to produce a positive response shift appears ineffective, one would first need to revise the metric being evaluated before jumping to conclusions.
The 2006 Lebanon war provided an example of a traumatic event affecting a large population. Elders in Lebanon are a vulnerable group during a war, regardless of what part of the country they reside in. During the 2006 war, a majority of Lebanon’s residents reported increased symptoms of Post Traumatic Stress Disorder (PTSD) [
The smoking ban in Lebanon provided another example of population-level response shift. Smoking ban is likely to induce a population-level shift including wellbeing, prosperity, diet and social norms though affecting the prevalence of smoking as a social pressure. A substantial proportion of smokers (81%) started perceiving little social approval for their smoking (this shift in perception referred to as denormalization), would have fewer places to smoke [
Taken the two examples above to assess the impact of a training initiative on response shift could be based on pre- and post-workshop and training session tests [
Furthermore, the dataset provided by the pre- and post-test presented a cross sectional assessment. A long-term analysis would necessarily require a sequence of follow-up evaluations timed accordingly. Those should not only focus on detecting an increase of knowledge and confidence, but would also include long term evaluation questions assessing the impact of the training in implementing policy, clinical, education and/or research activities in the communities.
We expect that response-shifts at the level of the Lebanese population would be better achieved if the cared-for cases were “organic” (i.e. “home-grown”). For example, and drawing on our own experience in the field, it would be beneficial to allow the social workers under training to get to know the elders they care for better, and incentivize them to work specifically in the geriatric field [
Also, while planning the trainings, many factors ought to be taken into consideration. Beyond general logistics (e.g. weather, number of participants, holiday schedule…) trainers would need to account for the political and cultural contexts in some societies [
The legal and other implications of aging are many and complex, and implementing resources to address potential concerns need to be a part of programs targeting geriatric care. Given this, the authors would like to caution that specific interpretations of population-level response shift would add complexity to the program selection. Nevertheless, geriatric HRQL in the Lebanese population would not occur without taking these factors into consideration. These factors are mandatory in the selection and interpretation of preferential functions for HQOL economic applications such as pushing a bill covering elders’ medical services and allowing for continuous medical insurances and elder pensions and benefits.
In this short communication, we have tried to broaden the scope of thinking about training programs abroad to target population-shift creating a true change. Response shift occurs at the level of the population when a large proportion of the population experiences the shift simultaneously and as a core group, and when the cause of the shift becomes socially a significant event or trend. Such catalysts are often qualitative and differ highly from placing numbers and tags on interventions as we often do with our quantitative measures. When we measure the impact of an intervention, we do not know whether a specific training or campaign has resulted in a response shift unless we allow ourselves to ask the right questions and seek out the answers on the field. We would not know instantaneously whether a shift had any bearing on the conduct and interpretation of research. We caution the reader to question at a deeper level the impact of an awareness campaign and to observe for shifts. In posing this debate, we suggest that it might be worthwhile to further evaluate population-shifts and measure not only through ear and mouth a specific training but base the success of an intervention on measures of HRQL in large populations through the response-shift created by such national public health programs.