PROBE: A Computer Instrument for Field Surveys of Psychiatric Disorder

Benfari, Robert C.

doi:10.1001/archpsyc.1970.01750040064010

Cited by 7 publications

(4 citation statements)

References 5 publications

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“…At the follow-up, ten years after the first survey, as computer programme based on discriminant function analysis, the probability of being a â€˜¿ psychiatric case' was estimated in the same way as in the Stirling County study (Benfari & Leighton, 1970). In addition to a global score on â€˜¿ caseness', the symptoms were grouped into the syndromes of anxiety, depression and somatisation by the use of factor analysis.…”

Section: Methodsmentioning

confidence: 99%

Social Support, Negative Life Events and Mental Health

Dalgard¹,

Bjørk²,

1995

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Section: Methodsmentioning

confidence: 99%

Social Support, Negative Life Events and Mental Health

Dalgard¹,

Bjørk²,

1995

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“…Thanks to June Murphy, who, together with Alexander H. Leighton, has helped with the study in many ways, it has been possible to adapt a statistical computer program based on discriminant function analysis (Benefuri di Leighton (1970)) so as to estimate, on the basis of symptom scores, the probability of being "a psychiatric case" in the same way as in the Sterling County study, and other studies of the Leighton group. Hence the respondents are split into 4 groups, according to their symptom loading, A, B, C and D, where A means "almost certain psychiatric case", and D "almost certain mentally healthy person", with B and C in an intermediate position.…”

Section: Methodsmentioning

confidence: 99%

Mental health, neighborhood and related social variables in Oslo

Dalgard¹

1980

Acta Psychiatr Scand

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The present study aims at screening the psychiatric morbidity in different areas of Oslo, relating the findings to qualitative aspects of neighborhood. The general hypothesis is that the risk of mental disorders increases by decreasing quality of neighborhood, possibly through negative impact on psycho‐social variables like social network. The sample which consists of 1,003 randomly picked adults from five main types of neighborhood is interviewed by means of a structured questionnaire, and a statistical procedure is applied to estimate, on the basis of symptom scores, the risk of being “a psychiatric case”. In short, the hypothesis is by and large confirmed by the study, indicating that the lower the quality of neighborhood, in terms of possibilities for recreation and social interaction, as well as private and public services, the higher the prevalence of mental disorder, treated as well as untreated. Unsatisfactory social network is related to low quality of neighborhood and seems to interact with negative neighborhood characteristics, increasing sharply the risk of mental disorder in low quality areas. Variables like sex, age, marital status, education or place of birth can not explain the differences in psychiatric morbidity between the qualitatively different neighborhoods, nor can variables indicating mental health problems before moving into the present neighborhood.

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“…While we were familiar with how the Stirling model worked through the narrative account provided by the psychiatrists, our understanding of it was increased by a certain amount of trial and error in the early attempts at computer replication. At first we tried simpler models involving only one step and then two steps (Benfari & Leighton, 1970). Although these steps replicated some of the ratings, their lack of success in reproducing the original PSYATT assessments convinced us that a fully algorithmic 4-step model was necessary for DPAX.…”

Section: Diagnostic Algorithmsmentioning

confidence: 99%

Computer diagnosis of depression and anxiety: the Stirling County Study

et al. 1985

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SynopsisA computer programme (DPAX) was constructed for a longitudinal study of psychiatric epidemiology in Stirling County (Canada). It identifies disorders involving the syndromes of depression and anxiety based on responses given in structured questionnaire interviews. The programme follows a diagnostic algorithm that uses criteria for: (1) essential features; (2) number, frequency, and pattern of associated symptoms; (3) impairment; and (4) duration. The programme reproduces case evaluations provided by psychiatrists, as conveyed by a sensitivity of 92% and a specificity of 98%.

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PROBE: A Computer Instrument for Field Surveys of Psychiatric Disorder

Cited by 7 publications

References 5 publications

Social Support, Negative Life Events and Mental Health

Social Support, Negative Life Events and Mental Health

Mental health, neighborhood and related social variables in Oslo

Computer diagnosis of depression and anxiety: the Stirling County Study

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