Can the mandatory isolation predict changes in mental health due to COVID-19 lockdown after accounting for an individual’s pre-existing resilience?
I carried out a hierarchical multiple regression. Please see the attach results that need to be written up and interpreted. I have also attached a piece of work (labelled old work) (old work which is much shorter) please use it for guidance / format and style write up.
I have attached the results that need interpreting.
When I look at the results, it looks like there are a few significants, and that participants did get more depressed. Looking at the negative values.
Can you mention the ceiling effect / floor effect if neccessary
Bit of background:
I used the DASS-21 (depression, anxiety stress scale – they are being viewed as one) to measure mental health. Participants were asked to answer retrospectively pre government-enforced lockdown and during COVID-19. The change score was calculated to carry out the analysis. To see if participants mental health got worse (criterion variable)
Participants were asked to retrospectively answer the brief resilience scale pre-government-enforced lockdown. (predictor-controlled variable)
Participants were asked to answer isolation questions I created retrospectively to during the enforced lockdown. (predictor variables)
Within the word count I have included wording for the hypothesis to be done. I messaged the site and they said that was fine (200 words roughly)
The first hypothesis I was thinking is below.
The model hypothesis is that changes in mental health due to the Covid-19 lockdown can be predicted by specific aspects of self-perceived experiences of social isolation (daily routine, exercise, physical contact and shopping) after taking into consideration participants’ pre-existing levels of resilience.
Can you please help with two more? (roughly please 200 words for the hypothesis) It would be great if the hypotheses can be significant, and that they are reflected in the results (that’s if of course some of the results are).