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10.2196/27132 http://scihub22266oqcxt.onion/10.2196/27132 34033582!8183599!34033582     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Med+Internet+Res 2021 ; 23 (6): e27132 Nephropedia Template TP {{tp|p=34033582|t=2021. Proof-of-Concept Support for the Development and Implementation of a Digital Assessment for Perinatal Mental Health: Mixed Methods Study |pdf=|usr=}}{{34033582}} gab.com Text Proof-of-Concept Support for the Development and Implementation of a Digital Assessment for Perinatal Mental Health: Mixed Methods Study JO: J Med Internet Res http://www.kidney.de/pget.php?&tw=1&pmid=34033582 #FOAvip BACKGROUND: Perinatal mental health symptoms commonly remain underdiagnosed and undertreated in maternity care settings in the United Kingdom, with outbreaks of disease, like the COVID-19 pandemic, further disrupting access to adequate mental health support. Digital technologies may offer an innovative way to support the mental health needs of women and their families throughout the perinatal period, as well as assist midwives in the recognition of perinatal mental health concerns. However, little is known about the acceptability and perceived benefits and barriers to using such technologies. OBJECTIVE: The aim of this study was to conduct a mixed methods evaluation of the current state of perinatal mental health care provision in the United Kingdom, as well as users' (women and partners) and midwives' interest in using a digital mental health assessment throughout the perinatal period. METHODS: Women, partners, and midwives were recruited to participate in the study, which entailed completing an online survey. Quantitative data were explored using descriptive statistics. Open-ended response data were first investigated using thematic analysis. Resultant themes were then mapped onto the components of the Capability, Opportunity, and Motivation Behavior model and summarized using descriptive statistics. RESULTS: A total of 829 women, 103 partners, and 90 midwives participated in the study. The provision of adequate perinatal mental health care support was limited, with experiences varying significantly across respondents. There was a strong interest in using a digital mental health assessment to screen, diagnose, and triage perinatal mental health concerns, particularly among women and midwives. The majority of respondents (n=781, 76.42%) expressed that they would feel comfortable or very comfortable using or recommending a digital mental health assessment. The majority of women and partners showed a preference for in-person consultations (n=417, 44.74%), followed by a blended care approach (ie, both in-person and online consultations) (n=362, 38.84%), with fewer participants preferring online-only consultations (n=120, 12.88%). Identified benefits and barriers mainly related to physical opportunity (eg, accessibility), psychological capability (eg, cognitive skills), and automatic motivation (eg, emotions). CONCLUSIONS: This study provides proof-of-concept support for the development and implementation of a digital mental health assessment to inform clinical decision making in the assessment of perinatal mental health concerns in the United Kingdom. Twit Text FOAVip Proof-of-Concept Support for the Development and Implementation of a Digital Assessment for Perinatal Mental Health: Mixed Methods Study ????J Med Internet Res http://www.kidney.de/pget.php?&tw=1&pmid=34033582 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34033582 #FOAvip English Wikipedia <ref>{{Cite pmid|34033582}}</ref> Proof-of-Concept Support for the Development and Implementation of a Digital Assessment for Perinatal Mental Health: Mixed Methods Study #MMPMID34033582 Martin-Key NA; Spadaro B; Schei TS; Bahn S J Med Internet Res 2021[Jun]; 23 (6): e27132 PMID34033582show ga BACKGROUND: Perinatal mental health symptoms commonly remain underdiagnosed and undertreated in maternity care settings in the United Kingdom, with outbreaks of disease, like the COVID-19 pandemic, further disrupting access to adequate mental health support. Digital technologies may offer an innovative way to support the mental health needs of women and their families throughout the perinatal period, as well as assist midwives in the recognition of perinatal mental health concerns. However, little is known about the acceptability and perceived benefits and barriers to using such technologies. OBJECTIVE: The aim of this study was to conduct a mixed methods evaluation of the current state of perinatal mental health care provision in the United Kingdom, as well as users' (women and partners) and midwives' interest in using a digital mental health assessment throughout the perinatal period. METHODS: Women, partners, and midwives were recruited to participate in the study, which entailed completing an online survey. Quantitative data were explored using descriptive statistics. Open-ended response data were first investigated using thematic analysis. Resultant themes were then mapped onto the components of the Capability, Opportunity, and Motivation Behavior model and summarized using descriptive statistics. RESULTS: A total of 829 women, 103 partners, and 90 midwives participated in the study. The provision of adequate perinatal mental health care support was limited, with experiences varying significantly across respondents. There was a strong interest in using a digital mental health assessment to screen, diagnose, and triage perinatal mental health concerns, particularly among women and midwives. The majority of respondents (n=781, 76.42%) expressed that they would feel comfortable or very comfortable using or recommending a digital mental health assessment. The majority of women and partners showed a preference for in-person consultations (n=417, 44.74%), followed by a blended care approach (ie, both in-person and online consultations) (n=362, 38.84%), with fewer participants preferring online-only consultations (n=120, 12.88%). Identified benefits and barriers mainly related to physical opportunity (eg, accessibility), psychological capability (eg, cognitive skills), and automatic motivation (eg, emotions). CONCLUSIONS: This study provides proof-of-concept support for the development and implementation of a digital mental health assessment to inform clinical decision making in the assessment of perinatal mental health concerns in the United Kingdom. |*Maternal Health Services[MESH] |*Proof of Concept Study[MESH] |Adult[MESH] |Clinical Decision-Making[MESH] |Female[MESH] |Humans[MESH] |Mental Disorders/*diagnosis[MESH] |Mental Health[MESH] |Midwifery[MESH] |Parturition[MESH] |Perinatal Care/*methods[MESH] |Pregnancy[MESH] |Pregnancy Complications/*diagnosis[MESH] |Surveys and Questionnaires[MESH]Proof-of-Concept Support for the Development and Implementation of a D(epmc).pdf DeepDyve Pubget Overpricing