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Reason: Due to conditions of participant consent, data cannot be made openly available but may be shared with researchers on request. To request access, please email research.data@kcl.ac.uk

Psychotic major depression (PMD) data

dataset
posted on 2024-06-19, 10:08 authored by Margaret HeslinMargaret Heslin, Emilia Loane, Norha Vera San JuanNorha Vera San Juan

Aim

Although there are multiple theories as to why PMD is diagnosed late, this has not been fully investigated. Therefore, this study aimed to explore service users’ perspectives and experiences of their diagnosis of PMD, with a focus on exploring instances where the diagnosis was made later in the illness course.


Materials and methods

We followed COREQ reporting guidelines for qualitative research.


Design

This study used qualitative methods to explore the diagnostic process of PMD from the service users' subjective views, experiences, and opinions. Semi-structured one-off interviews were conducted with people who had a formal diagnosis of PMD according to medical records.


Participants

Purposive sampling was used to recruit a sample of service users between 18-64, who did not need a translator to participate, who had a formal recorded clinical diagnosis of PMD in the last 3 years, and did not have a different psychosis related diagnosis since then.


Recruitment

Participants were recruited using two methods: consent for contact (C4C); and referrals from clinical teams. C4C was conducted through a research register held by the NHR Maudsley biomedical research centre (BRC) partnered with the south London and Maudsley NHS foundation trust (SLaM). Participants are added to the C4C register when in the care of SLaM and having consented to being contacted regarding research. The study's inclusion and exclusion criteria were used to complete a C4C search, creating a list of potential participants. Eligible participants were then contacted.


Relevant clinical teams within SLAM were contacted with details of the study and asked to refer any potentially relevant service users who were interested in receiving more information about the study. Any referrals were contact directly.


All potentially relevant service users were contacted by phone and given brief information about the study. If the person was interested, they were sent a participant information sheet and given at least 24 hours to consider before being recontacted by the researcher. Verbal informed consent was obtained from each service user after a full explanation of the participant information sheet. The audio recording of informed consent was listened to by another researcher who then signed the consent form to confirm consent had been given.


Data Collection

Due to the COVID-19 pandemic, interviews were conducted through Microsoft teams via videoconferencing or freephone options. Following the recruitment and consent procedure, interviews were conducted, audio or video recorded with the video removed post-interview. We requested that service users made sure they were in a quiet space and alone during interviews. Interviews lasted approximately 1 hour. Data collection started in 13/06/2022 and ended on 10/08/2023.


Open-ended, in-depth questions were used to reduce bias and increase rapport. This was facilitated by the use of a topic guide. The questions explored the individual's journey to diagnosis, factors that helped and hindered diagnosis and their interactions with mental health services. A debrief sheet and £20 Amazon voucher was emailed post-interview.

Transcription was completed verbatim within the Microsoft teams' transcription tool, which was then confirmed and anonymised by the researcher. No field notes were made. Transcripts were not returned to service users for comment.


Ethics

Ethical approval was provided by Oxford REC and has received HRA and HCRW approval – 287774. Participants provided verbal informed consent.


Data analysis

Data were analysed using reflexive thematic analysis. Data was coded using NVivo 14. The six thematic analysis steps were followed: (1) familiarisation with the data, through repeated reading & annotation; (2) generation of initial codes, through intense open-coding of data to generate an initial coding frame based on thematic categories rooted in the data; (3) identification of themes, through a detailed review of the coding frame to sort codes in to potential themes; (4) review of themes, through refinement of the developing themes; (5) definition & refinement of themes, through exploration of relationships within & between codes, & revision of thematic definitions, and (6) writing up the study findings. Steps 1-3 were performed independently by two authors (EL & MH) who then performed steps 4-6 collaboratively with NVSJ. Data saturation was not considered.


Reflexivity

EL conducted all interviews. EL is a female, White British Masters’ student with a BSc in Psychology. In preparation for this study, EL completed training in: good clinical practice; gaining informed consent; safeguarding; GDPR; information governance; Nvivo; C4C guidelines; completed a master’s module in qualitative research; and took part in several role play interviews. EL previous conducted research interviews for her BSc. EL was responsible for approaching and recruiting all service users. NVSJ is a female, Latina of mixed ethnic background, Senior Research Fellow. MH is a White British female Senior Lecturer.

During analysis, MH and NVSJ had reflective sessions where we discussed emerging themes, and different interpretations of the data.


Content

Data include the 10 transcripts from participant one-to-one interviews.

Funding

N/A

History

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